function_name stringlengths 1 63 | docstring stringlengths 50 5.89k | masked_code stringlengths 50 882k | implementation stringlengths 169 12.9k | start_line int32 1 14.6k | end_line int32 16 14.6k | file_content stringlengths 274 882k |
|---|---|---|---|---|---|---|
tns_close_short_pos | 事务平空单仓位
1.来源自止损止盈平仓
2.来源自换仓
逻辑: 如果当前账号昨仓满足平仓数量,直接平仓,如果不满足,则创建锁仓网格.
:param 平仓网格
:return: | """"""
import os
import uuid
import bz2
import pickle
import traceback
import zlib
from abc import ABC
from copy import copy,deepcopy
from typing import Any, Callable
from logging import INFO, ERROR
from datetime import datetime
from vnpy.trader.constant import Interval, Direction, Offset, Status, OrderType, Color, Ex... | def tns_close_short_pos(self, grid):
"""
事务平空单仓位
1.来源自止损止盈平仓
2.来源自换仓
逻辑: 如果当前账号昨仓满足平仓数量,直接平仓,如果不满足,则创建锁仓网格.
:param 平仓网格
:return:
"""
self.write_log(u'执行事务平空仓位:{}'.format(grid.to_json()))
# 平仓网格得合约
cover_symbol = grid.snapshot.ge... | 2,027 | 2,125 | """"""
import os
import uuid
import bz2
import pickle
import traceback
import zlib
from abc import ABC
from copy import copy,deepcopy
from typing import Any, Callable
from logging import INFO, ERROR
from datetime import datetime
from vnpy.trader.constant import Interval, Direction, Offset, Status, OrderType, Color, Ex... |
send_message | Sends message in bold mode/Enviar mensagem em negrito.
:param chat_id: ID of Telegram account/ID da conta Telgram.
:param text: Message/Mensagem.
:param parse_mode: Ignore.
:param token: ID Telegram bot/ID do bot Telegram. | #!/usr/bin/python
import pathlib
import requests
import smtplib
import logging
import coloredlogs
import verboselogs
from etc.api.keys import *
path_atual_tl = str(pathlib.Path(__file__).parent.absolute())
path_tl_final = path_atual_tl.replace('/etc/notification','')
def logando_notification(tipo, mensagem):
... | def send_message(chat_id, text=None, parse_mode = 'Markdown', token=None):
"""
Sends message in bold mode/Enviar mensagem em negrito.
:param chat_id: ID of Telegram account/ID da conta Telgram.
:param text: Message/Mensagem.
:param parse_mode: Ignore.
:param token: ID Telegram bot/ID do bot Tel... | 89 | 103 | #!/usr/bin/python
import pathlib
import requests
import smtplib
import logging
import coloredlogs
import verboselogs
from etc.api.keys import *
path_atual_tl = str(pathlib.Path(__file__).parent.absolute())
path_tl_final = path_atual_tl.replace('/etc/notification','')
def logando_notification(tipo, mensagem):
... |
_cnn_net | Create the CNN net topology.
:return keras.Sequential(): CNN topology. | #!/usr/bin/python
# -*- encoding: utf-8 -*-
"""
@ide: PyCharm
@author: Pedro Silva
@contact: pedroh21.silva@gmail.com
@created: out-10 of 2019
"""
import os
import numpy as np
import tensorflow as tf
import tensorflow.keras.backend as kback
from tensorflow import keras
class QRSNet(object):
# MASKED: _cnn_net fun... | @classmethod
def _cnn_net(cls):
"""
Create the CNN net topology.
:return keras.Sequential(): CNN topology.
"""
qrs_detector = keras.Sequential()
# CONV1
qrs_detector.add(keras.layers.Conv1D(96, 49, activation=tf.nn.relu, input_shape=(300, 1), strides=1, n... | 21 | 70 | #!/usr/bin/python
# -*- encoding: utf-8 -*-
"""
@ide: PyCharm
@author: Pedro Silva
@contact: pedroh21.silva@gmail.com
@created: out-10 of 2019
"""
import os
import numpy as np
import tensorflow as tf
import tensorflow.keras.backend as kback
from tensorflow import keras
class QRSNet(object):
@classmethod
d... |
build | Build the CNN topology.
:param str net_type: the network type, CNN or LSTM.
:return keras.Sequential(): CNN topology. | #!/usr/bin/python
# -*- encoding: utf-8 -*-
"""
@ide: PyCharm
@author: Pedro Silva
@contact: pedroh21.silva@gmail.com
@created: out-10 of 2019
"""
import os
import numpy as np
import tensorflow as tf
import tensorflow.keras.backend as kback
from tensorflow import keras
class QRSNet(object):
@classmethod
d... | @classmethod
def build(cls, net_type):
"""
Build the CNN topology.
:param str net_type: the network type, CNN or LSTM.
:return keras.Sequential(): CNN topology.
"""
if net_type == 'cnn':
qrs_detector = cls._cnn_net()
else:
raise Not... | 72 | 84 | #!/usr/bin/python
# -*- encoding: utf-8 -*-
"""
@ide: PyCharm
@author: Pedro Silva
@contact: pedroh21.silva@gmail.com
@created: out-10 of 2019
"""
import os
import numpy as np
import tensorflow as tf
import tensorflow.keras.backend as kback
from tensorflow import keras
class QRSNet(object):
@classmethod
d... |
_prepare_data | Prepare the data for the training, turning it into a numpy array.
:param list data_x: data that will be used to train.
:param tuple input_shape: the input shape that the data must have to be used as training data.
:param list data_y: the labels related to the data used to train.
:param int number_of_classes: number of ... | #!/usr/bin/python
# -*- encoding: utf-8 -*-
"""
@ide: PyCharm
@author: Pedro Silva
@contact: pedroh21.silva@gmail.com
@created: out-10 of 2019
"""
import os
import numpy as np
import tensorflow as tf
import tensorflow.keras.backend as kback
from tensorflow import keras
class QRSNet(object):
@classmethod
d... | @classmethod
def _prepare_data(cls, data_x, input_shape, data_y, number_of_classes, normalize):
"""
Prepare the data for the training, turning it into a numpy array.
:param list data_x: data that will be used to train.
:param tuple input_shape: the input shape that the data must ... | 86 | 107 | #!/usr/bin/python
# -*- encoding: utf-8 -*-
"""
@ide: PyCharm
@author: Pedro Silva
@contact: pedroh21.silva@gmail.com
@created: out-10 of 2019
"""
import os
import numpy as np
import tensorflow as tf
import tensorflow.keras.backend as kback
from tensorflow import keras
class QRSNet(object):
@classmethod
d... |
_convert_dataset_to_image_and_bboxes | @param dataset: [image_path, [[x, y, w, h, class_id], ...]]
@return image, bboxes
image: 0.0 ~ 1.0, Dim(1, height, width, channels) | """
MIT License
Copyright (c) 2019 YangYun
Copyright (c) 2020 Việt Hùng
Copyright (c) 2020-2021 Hyeonki Hong <hhk7734@gmail.com>
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restrictio... | def _convert_dataset_to_image_and_bboxes(self, dataset):
"""
@param dataset: [image_path, [[x, y, w, h, class_id], ...]]
@return image, bboxes
image: 0.0 ~ 1.0, Dim(1, height, width, channels)
"""
# pylint: disable=bare-except
try:
image = cv2... | 121 | 142 | """
MIT License
Copyright (c) 2019 YangYun
Copyright (c) 2020 Việt Hùng
Copyright (c) 2020-2021 Hyeonki Hong <hhk7734@gmail.com>
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restrictio... |
setup_logging | Setup the logging device to log into a uniquely created directory.
Args:
name: Name of the directory for the log-files.
dir: Optional sub-directory within log | # MIT License
# Copyright (c) 2020 Simon Schug, João Sacramento
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, ... | def setup_logging(name, dir=""):
"""
Setup the logging device to log into a uniquely created directory.
Args:
name: Name of the directory for the log-files.
dir: Optional sub-directory within log
"""
# Setup global log name and directory
global log_name
log_name = name
... | 37 | 70 | # MIT License
# Copyright (c) 2020 Simon Schug, João Sacramento
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, ... |
__init__ | Initializes a observation in light dark domain.
Args:
position (tuple): position of the robot. | import pomdp_py
class Observation(pomdp_py.Observation):
"""Defines the Observation for the continuous light-dark domain;
Observation space:
:math:`\Omega\subseteq\mathbb{R}^2` the observation of the robot is
an estimate of the robot position :math:`g(x_t)\in\Omega`.
"""
# the n... | def __init__(self, position, discrete=False):
"""
Initializes a observation in light dark domain.
Args:
position (tuple): position of the robot.
"""
self._discrete = discrete
if len(position) != 2:
raise ValueError("Observation position must b... | 15 | 29 | import pomdp_py
class Observation(pomdp_py.Observation):
"""Defines the Observation for the continuous light-dark domain;
Observation space:
:math:`\Omega\subseteq\mathbb{R}^2` the observation of the robot is
an estimate of the robot position :math:`g(x_t)\in\Omega`.
"""
# the n... |
_find_x12 | If x12path is not given, then either x13as[.exe] or x12a[.exe] must
be found on the PATH. Otherwise, the environmental variable X12PATH or
X13PATH must be defined. If prefer_x13 is True, only X13PATH is searched
for. If it is false, only X12PATH is searched for. | """
Run x12/x13-arima specs in a subprocess from Python and curry results back
into python.
Notes
-----
Many of the functions are called x12. However, they are also intended to work
for x13. If this is not the case, it's a bug.
"""
import os
import subprocess
import tempfile
import re
from warnings import warn
import... | def _find_x12(x12path=None, prefer_x13=True):
"""
If x12path is not given, then either x13as[.exe] or x12a[.exe] must
be found on the PATH. Otherwise, the environmental variable X12PATH or
X13PATH must be defined. If prefer_x13 is True, only X13PATH is searched
for. If it is false, only X12PATH is s... | 46 | 79 | """
Run x12/x13-arima specs in a subprocess from Python and curry results back
into python.
Notes
-----
Many of the functions are called x12. However, they are also intended to work
for x13. If this is not the case, it's a bug.
"""
import os
import subprocess
import tempfile
import re
from warnings import warn
import... |
corpus_reader | Lê as extensões dos arquivos .xml no caminho especificado como path e
retorna uma tupla com duas listas.Uma lista contém os paths para os arquivos
.xml e a outra contém os arquivos Document gerados para aquele arquilo .xml | # -*- coding: utf-8 -*-
"""
Criado por Lucas Fonseca Lage em 04/03/2020
"""
import re, os, spacy
import numpy as np
from my_wsd import my_lesk
from unicodedata import normalize
from document import Document
from gensim.models import Phrases
# Carregamento do modelo Spacy
nlp = spacy.load('pt_core_news_lg')
# Carrega... | def corpus_reader(path):
'''Lê as extensões dos arquivos .xml no caminho especificado como path e
retorna uma tupla com duas listas.Uma lista contém os paths para os arquivos
.xml e a outra contém os arquivos Document gerados para aquele arquilo .xml
'''
prog = re.compile('(\.xml)$')
doc_list = ... | 31 | 49 | # -*- coding: utf-8 -*-
"""
Criado por Lucas Fonseca Lage em 04/03/2020
"""
import re, os, spacy
import numpy as np
from my_wsd import my_lesk
from unicodedata import normalize
from document import Document
from gensim.models import Phrases
# Carregamento do modelo Spacy
nlp = spacy.load('pt_core_news_lg')
# Carrega... |
corpus_yeeter | Similar ao corpus_reader. Recebe um caminho para a pasta contendo o
corpus e cria um generator. Cada iteração retorna uma tupla contendo um
caminho para o arquivo .xml e o objeto Document criado a partir do mesmo | # -*- coding: utf-8 -*-
"""
Criado por Lucas Fonseca Lage em 04/03/2020
"""
import re, os, spacy
import numpy as np
from my_wsd import my_lesk
from unicodedata import normalize
from document import Document
from gensim.models import Phrases
# Carregamento do modelo Spacy
nlp = spacy.load('pt_core_news_lg')
# Carrega... | def corpus_yeeter(path):
'''Similar ao corpus_reader. Recebe um caminho para a pasta contendo o
corpus e cria um generator. Cada iteração retorna uma tupla contendo um
caminho para o arquivo .xml e o objeto Document criado a partir do mesmo
'''
prog = re.compile('(\.xml)$')
for dirpath, dirname... | 51 | 61 | # -*- coding: utf-8 -*-
"""
Criado por Lucas Fonseca Lage em 04/03/2020
"""
import re, os, spacy
import numpy as np
from my_wsd import my_lesk
from unicodedata import normalize
from document import Document
from gensim.models import Phrases
# Carregamento do modelo Spacy
nlp = spacy.load('pt_core_news_lg')
# Carrega... |
subj_n_elements | Recebe a lista de sentenças da redação. Conta a quantidade de elementos
abaixo do sujeito na árvore sintática gerada pelo "dependecy parser" do
Spacy. Retorna o número de sujeitos que possuem uma quantidade de elementos
maior que 7 e também o número total de elementos que fazem parte de um
sujeito em toda a redação. | # -*- coding: utf-8 -*-
"""
Criado por Lucas Fonseca Lage em 04/03/2020
"""
import re, os, spacy
import numpy as np
from my_wsd import my_lesk
from unicodedata import normalize
from document import Document
from gensim.models import Phrases
# Carregamento do modelo Spacy
nlp = spacy.load('pt_core_news_lg')
# Carrega... | def subj_n_elements(sentence_list):
''' Recebe a lista de sentenças da redação. Conta a quantidade de elementos
abaixo do sujeito na árvore sintática gerada pelo "dependecy parser" do
Spacy. Retorna o número de sujeitos que possuem uma quantidade de elementos
maior que 7 e também o número total de eleme... | 157 | 175 | # -*- coding: utf-8 -*-
"""
Criado por Lucas Fonseca Lage em 04/03/2020
"""
import re, os, spacy
import numpy as np
from my_wsd import my_lesk
from unicodedata import normalize
from document import Document
from gensim.models import Phrases
# Carregamento do modelo Spacy
nlp = spacy.load('pt_core_news_lg')
# Carrega... |
__init__ | Initialize the DnsEntry object.
Closely represent the TransIP dnsEntry object
:param content: content (rdata) corresponding to the record type
(e.g. ip), defaults to None
:type content: str, optional
:param expire: Time To Live (TTL) of the record, defaults to None
:type expire: int, optional
:param n... | # MIT License, Copyright (c) 2020 Bob van den Heuvel
# https://github.com/bheuvel/transip/blob/main/LICENSE
"""Interface with the TransIP API, specifically DNS record management."""
import logging
from enum import Enum
from pathlib import Path
from time import sleep
from typing import Dict, Union
import requests
from... | def __init__(
self,
content: str = None,
expire: int = None,
name: str = None,
rtype: str = None,
):
"""Initialize the DnsEntry object.
Closely represent the TransIP dnsEntry object
:param content: content (rdata) corresponding to the record type... | 23 | 49 | # MIT License, Copyright (c) 2020 Bob van den Heuvel
# https://github.com/bheuvel/transip/blob/main/LICENSE
"""Interface with the TransIP API, specifically DNS record management."""
import logging
from enum import Enum
from pathlib import Path
from time import sleep
from typing import Dict, Union
import requests
from... |
extract_valid_cpu_usage_data | This method it to extract the valid cpu usage data according to the poll_interval
1. Find the index for the max one for every poll interval,
2. Discard the data if the index is on the edge(0 o the length of program_to_check_cpu_usage -1)
3. If the index is closed in the neighbour interval, only keep the former one
4. R... | import logging
import pytest
from collections import namedtuple, Counter
from tests.platform_tests.counterpoll.cpu_memory_helper import restore_counter_poll # lgtm [py/unused-import]
from tests.platform_tests.counterpoll.cpu_memory_helper import counterpoll_type # lgtm [py/unused-import]
from tests.platform_test... | def extract_valid_cpu_usage_data(program_to_check_cpu_usage, poll_interval):
"""
This method it to extract the valid cpu usage data according to the poll_interval
1. Find the index for the max one for every poll interval,
2. Discard the data if the index is on the edge(0 o the length of program_to_check... | 156 | 192 | import logging
import pytest
from collections import namedtuple, Counter
from tests.platform_tests.counterpoll.cpu_memory_helper import restore_counter_poll # lgtm [py/unused-import]
from tests.platform_tests.counterpoll.cpu_memory_helper import counterpoll_type # lgtm [py/unused-import]
from tests.platform_test... |
reset_module | reset all local vars
Args:
None
Returns:
None | # blender imports
import bpy
# utility imports
import numpy as np
import csv
import random
import importlib
from src.TSSBase import TSSBase
class TSSMeshHandle(TSSBase):
"""docstring for TSSMeshHandle"""
def __init__(self):
super(TSSMeshHandle, self).__init__()
# class vars ##################... | def reset_module(self):
""" reset all local vars
Args:
None
Returns:
None
"""
# reset all mesh ############################################################################################
for mesh in self._mesh_obj_list:
# reset me... | 22 | 41 | # blender imports
import bpy
# utility imports
import numpy as np
import csv
import random
import importlib
from src.TSSBase import TSSBase
class TSSMeshHandle(TSSBase):
"""docstring for TSSMeshHandle"""
def __init__(self):
super(TSSMeshHandle, self).__init__()
# class vars ##################... |
_create_meshes | create function
Args:
cfg: list of mesh cfgs [list]
general_cfg: general cfg [dict]
stage_dict: dict of stages [dict]
Returns:
success code [boolean] | # blender imports
import bpy
# utility imports
import numpy as np
import csv
import random
import importlib
from src.TSSBase import TSSBase
class TSSMeshHandle(TSSBase):
"""docstring for TSSMeshHandle"""
def __init__(self):
super(TSSMeshHandle, self).__init__()
# class vars ##################... | def _create_meshes(self,cfg,general_cfg,stage_dict):
""" create function
Args:
cfg: list of mesh cfgs [list]
general_cfg: general cfg [dict]
stage_dict: dict of stages [dict]
Returns:
success code [boolean]
"""
... | 71 | 122 | # blender imports
import bpy
# utility imports
import numpy as np
import csv
import random
import importlib
from src.TSSBase import TSSBase
class TSSMeshHandle(TSSBase):
"""docstring for TSSMeshHandle"""
def __init__(self):
super(TSSMeshHandle, self).__init__()
# class vars ##################... |
_set_voldb_empty_at_startup_indicator | Determine if the Cinder volume DB is empty.
A check of the volume DB is done to determine whether it is empty or
not at this point.
:param ctxt: our working context | # Copyright 2010 United States Government as represented by the
# Administrator of the National Aeronautics and Space Administration.
# 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 ... | def _set_voldb_empty_at_startup_indicator(self, ctxt):
"""Determine if the Cinder volume DB is empty.
A check of the volume DB is done to determine whether it is empty or
not at this point.
:param ctxt: our working context
"""
vol_entries = self.db.volume_get_all(ct... | 362 | 377 | # Copyright 2010 United States Government as represented by the
# Administrator of the National Aeronautics and Space Administration.
# 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 ... |
freeze_host | Freeze management plane on this backend.
Basically puts the control/management plane into a
Read Only state. We should handle this in the scheduler,
however this is provided to let the driver know in case it
needs/wants to do something specific on the backend.
:param context: security context | # Copyright 2010 United States Government as represented by the
# Administrator of the National Aeronautics and Space Administration.
# 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 ... | def freeze_host(self, context):
"""Freeze management plane on this backend.
Basically puts the control/management plane into a
Read Only state. We should handle this in the scheduler,
however this is provided to let the driver know in case it
needs/wants to do something spe... | 3,325 | 3,357 | # Copyright 2010 United States Government as represented by the
# Administrator of the National Aeronautics and Space Administration.
# 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 ... |
thaw_host | UnFreeze management plane on this backend.
Basically puts the control/management plane back into
a normal state. We should handle this in the scheduler,
however this is provided to let the driver know in case it
needs/wants to do something specific on the backend.
:param context: security context | # Copyright 2010 United States Government as represented by the
# Administrator of the National Aeronautics and Space Administration.
# 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 ... | def thaw_host(self, context):
"""UnFreeze management plane on this backend.
Basically puts the control/management plane back into
a normal state. We should handle this in the scheduler,
however this is provided to let the driver know in case it
needs/wants to do something s... | 3,359 | 3,390 | # Copyright 2010 United States Government as represented by the
# Administrator of the National Aeronautics and Space Administration.
# 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 ... |
__reduce__ | Provide pickling support. Normally, this just dispatches to Python's
standard handling. However, for models with deferred field loading, we
need to do things manually, as they're dynamically created classes and
only module-level classes can be pickled by the default path. | # -*- coding: utf-8 -*-
from datetime import date
import json
from operator import itemgetter
import os
import warnings
from django.core.urlresolvers import NoReverseMatch
from django.core.exceptions import ValidationError, ObjectDoesNotExist
from django.db import models
from django.db.models import signals, Model
fro... | def __reduce__(self):
"""
Provide pickling support. Normally, this just dispatches to Python's
standard handling. However, for models with deferred field loading, we
need to do things manually, as they're dynamically created classes and
only module-level classes can be pickle... | 94 | 111 | # -*- coding: utf-8 -*-
from datetime import date
import json
from operator import itemgetter
import os
import warnings
from django.core.urlresolvers import NoReverseMatch
from django.core.exceptions import ValidationError, ObjectDoesNotExist
from django.db import models
from django.db.models import signals, Model
fro... |
generate_mesh | Launch Mesh Generator to generate mesh.
@param meshing_dir: the meshing directory
@param params: the meshing parameters
@return: the mesh generation log content
@raise TypeError: if any input parameter is not of required type
@raise ValueError: if any input parameter is None/empty, or any field of MeshingParameters is... | # -*- coding: utf-8 -*-
"""
This Python module provides various service functions.
Updated since version 1.1:
1. Added support for postprocess and visualization.
2. Added file path validation for parameters of all related methods.
Updated since version 1.2: Merge Code and Update GUI
1. Integrate New Nemoh... | def generate_mesh(meshing_dir, params):
'''
Launch Mesh Generator to generate mesh.
@param meshing_dir: the meshing directory
@param params: the meshing parameters
@return: the mesh generation log content
@raise TypeError: if any input parameter is not of required type
@raise ValueError: if... | 81 | 132 | # -*- coding: utf-8 -*-
"""
This Python module provides various service functions.
Updated since version 1.1:
1. Added support for postprocess and visualization.
2. Added file path validation for parameters of all related methods.
Updated since version 1.2: Merge Code and Update GUI
1. Integrate ... |
simulate | Run simulation.
@param simulation_dir: the simulation directory
@param params: the simulation parameters
@return: the simulation log content
@raise TypeError: if any input parameter is not of required type
@raise ValueError: if any input parameter is None/empty, or any field of SimulationParameters is not
... | # -*- coding: utf-8 -*-
"""
This Python module provides various service functions.
Updated since version 1.1:
1. Added support for postprocess and visualization.
2. Added file path validation for parameters of all related methods.
Updated since version 1.2: Merge Code and Update GUI
1. Integrate New Nemoh... | def simulate(simulation_dir, params):
'''
Run simulation.
@param simulation_dir: the simulation directory
@param params: the simulation parameters
@return: the simulation log content
@raise TypeError: if any input parameter is not of required type
@raise ValueError: if any input parameter i... | 134 | 242 | # -*- coding: utf-8 -*-
"""
This Python module provides various service functions.
Updated since version 1.1:
1. Added support for postprocess and visualization.
2. Added file path validation for parameters of all related methods.
Updated since version 1.2: Merge Code and Update GUI
1. Integrate ... |
postprocess | Run post-processing.
@param simulation_dir: the simulation directory
@param params: the post-processing parameters
@return: the post-processing log content
@raise TypeError: if any input parameter is not of required type
@raise ValueError: if any input parameter is None/empty, or any field of PostprocessingParameters ... | # -*- coding: utf-8 -*-
"""
This Python module provides various service functions.
Updated since version 1.1:
1. Added support for postprocess and visualization.
2. Added file path validation for parameters of all related methods.
Updated since version 1.2: Merge Code and Update GUI
1. Integrate New Nemoh... | def postprocess(simulation_dir, params):
'''
Run post-processing.
@param simulation_dir: the simulation directory
@param params: the post-processing parameters
@return: the post-processing log content
@raise TypeError: if any input parameter is not of required type
@raise ValueError: if any... | 244 | 315 | # -*- coding: utf-8 -*-
"""
This Python module provides various service functions.
Updated since version 1.1:
1. Added support for postprocess and visualization.
2. Added file path validation for parameters of all related methods.
Updated since version 1.2: Merge Code and Update GUI
1. Integrate ... |
run_thread | Run a python function in a thread and wait for it to complete.
Redirect its output to fd
Args:
func: A python function to run
args: A tuple containing argument for the function
fd: a file descriptor | # -*- coding: utf-8 -*-
"""
This Python module provides various service functions.
Updated since version 1.1:
1. Added support for postprocess and visualization.
2. Added file path validation for parameters of all related methods.
Updated since version 1.2: Merge Code and Update GUI
1. Integrate New Nemoh... | def run_thread(func, args, fd):
"""
Run a python function in a thread and wait for it to complete.
Redirect its output to fd
Args:
func: A python function to run
args: A tuple containing argument for the function
fd: a file descriptor
"""
manager = Manager()
return_d... | 470 | 487 | # -*- coding: utf-8 -*-
"""
This Python module provides various service functions.
Updated since version 1.1:
1. Added support for postprocess and visualization.
2. Added file path validation for parameters of all related methods.
Updated since version 1.2: Merge Code and Update GUI
1. Integrate ... |
__enter__ | Enter the context
Args:
self: The class itself | # -*- coding: utf-8 -*-
"""
This Python module provides various service functions.
Updated since version 1.1:
1. Added support for postprocess and visualization.
2. Added file path validation for parameters of all related methods.
Updated since version 1.2: Merge Code and Update GUI
1. Integrate New Nemoh... | def __enter__(self):
"""
Enter the context
Args:
self: The class itself
"""
import sys
self.sys = sys
# save previous stdout/stderr
self.saved_streams = saved_streams = sys.__stdout__, sys.__stderr__
self.fds = fds = [s.fileno() for... | 403 | 429 | # -*- coding: utf-8 -*-
"""
This Python module provides various service functions.
Updated since version 1.1:
1. Added support for postprocess and visualization.
2. Added file path validation for parameters of all related methods.
Updated since version 1.2: Merge Code and Update GUI
1. Integrate ... |
__exit__ | Exit the context
Args:
self: The class itself
args: other arguments | # -*- coding: utf-8 -*-
"""
This Python module provides various service functions.
Updated since version 1.1:
1. Added support for postprocess and visualization.
2. Added file path validation for parameters of all related methods.
Updated since version 1.2: Merge Code and Update GUI
1. Integrate New Nemoh... | def __exit__(self, *args):
"""
Exit the context
Args:
self: The class itself
args: other arguments
"""
sys = self.sys
# flush any pending output
for s in self.saved_streams: s.flush()
# restore original streams and file descript... | 431 | 447 | # -*- coding: utf-8 -*-
"""
This Python module provides various service functions.
Updated since version 1.1:
1. Added support for postprocess and visualization.
2. Added file path validation for parameters of all related methods.
Updated since version 1.2: Merge Code and Update GUI
1. Integrate ... |
cutouts | Custom version to extract stars cutouts
Parameters
----------
Parameters
----------
image: np.ndarray or path
stars: np.ndarray
stars positions with shape (n,2)
size: int
size of the cuts around stars (in pixels), by default 15
Returns
-------
np.ndarray of shape (size, size) | from scipy.optimize import minimize
import warnings
import numpy as np
from astropy.io import fits
from astropy.table import Table
from astropy.nddata import NDData
from photutils.psf import extract_stars
from astropy.stats import gaussian_sigma_to_fwhm
from ..core import Block
import matplotlib.pyplot as plt
from coll... | def cutouts(image, stars, size=15):
"""Custom version to extract stars cutouts
Parameters
----------
Parameters
----------
image: np.ndarray or path
stars: np.ndarray
stars positions with shape (n,2)
size: int
size of the cuts around stars (in pixels), by default 15
... | 43 | 77 | from scipy.optimize import minimize
import warnings
import numpy as np
from astropy.io import fits
from astropy.table import Table
from astropy.nddata import NDData
from photutils.psf import extract_stars
from astropy.stats import gaussian_sigma_to_fwhm
from ..core import Block
import matplotlib.pyplot as plt
from coll... |
_parse_github_path | Parse the absolute github path.
Args:
path: The full github path.
Returns:
repo: The repository identifiant.
branch: Repository branch.
subpath: The inner path.
Raises:
ValueError: If the path is invalid | # coding=utf-8
# Copyright 2021 The TensorFlow Datasets Authors.
#
# 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 appl... | def _parse_github_path(path: str) -> Tuple[str, str, str]:
"""Parse the absolute github path.
Args:
path: The full github path.
Returns:
repo: The repository identifiant.
branch: Repository branch.
subpath: The inner path.
Raises:
ValueError: If the path is invalid
"""
err_msg = (f'In... | 328 | 358 | # coding=utf-8
# Copyright 2021 The TensorFlow Datasets Authors.
#
# 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 appl... |
copy | Copy the current file to the given destination.
Args:
dst: Target file. It can be any PathLike compatible path (e.g. `gs://...`)
overwrite: Whether the file should be overwritten or not
Returns:
The new created file.
Raises:
FileExistsError: If `overwrite` is false and destination exists. | # coding=utf-8
# Copyright 2021 The TensorFlow Datasets Authors.
#
# 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 appl... | def copy(
self,
dst: utils.PathLike,
overwrite: bool = False,
) -> utils.ReadWritePath:
"""Copy the current file to the given destination.
Args:
dst: Target file. It can be any PathLike compatible path (e.g. `gs://...`)
overwrite: Whether the file should be overwritten or not
... | 303 | 325 | # coding=utf-8
# Copyright 2021 The TensorFlow Datasets Authors.
#
# 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 appl... |
commandstats | Shows command stats.
Use a negative number for bottom instead of top.
This is only for the current session. | from discord.ext import commands, tasks
from collections import Counter, defaultdict
from .utils import checks, db, time, formats
from .utils.paginator import CannotPaginate
import pkg_resources
import logging
import discord
import textwrap
import datetime
import traceback
import itertools
import typing
import asyncp... | @commands.command(hidden=True)
@commands.is_owner()
async def commandstats(self, ctx, limit=20):
"""Shows command stats.
Use a negative number for bottom instead of top.
This is only for the current session.
"""
counter = self.bot.command_stats
width = len(ma... | 181 | 200 | from discord.ext import commands, tasks
from collections import Counter, defaultdict
from .utils import checks, db, time, formats
from .utils.paginator import CannotPaginate
import pkg_resources
import logging
import discord
import textwrap
import datetime
import traceback
import itertools
import typing
import asyncp... |
prepare | Create a 1-node cluster, start it, create a keyspace, and if
<table_name>, create a table in that keyspace. If <cdc_enabled_table>,
that table is created with CDC enabled. If <column_spec>, use that
string to specify the schema of the table -- for example, a valid value
is 'a int PRIMARY KEY, b int'. The <configuration... | from __future__ import division
import errno
import os
import re
import shutil
import time
import uuid
from collections import namedtuple
from itertools import repeat
from pprint import pformat
import pytest
from cassandra import WriteFailure
from cassandra.concurrent import (execute_concurrent,
... | def prepare(self, ks_name,
table_name=None, cdc_enabled_table=None,
gc_grace_seconds=None,
column_spec=None,
configuration_overrides=None,
table_id=None):
"""
Create a 1-node cluster, start it, create a keyspace, and if
... | 244 | 290 | from __future__ import division
import errno
import os
import re
import shutil
import time
import uuid
from collections import namedtuple
from itertools import repeat
from pprint import pformat
import pytest
from cassandra import WriteFailure
from cassandra.concurrent import (execute_concurrent,
... |
create_group | Create new group in account.
:param api: api fixture
:param account: account fixture
:yields: create_group function | """Account, user fixtures."""
import json
import logging
from time import monotonic, sleep
from typing import List, NamedTuple, Optional, Tuple
import pytest
from box import Box
from dynaconf import settings
from ambra_sdk.exceptions.service import DuplicateName, NotEmpty
from ambra_sdk.models import Group
from ambr... | @pytest.fixture
def create_group(api, account):
"""Create new group in account.
:param api: api fixture
:param account: account fixture
:yields: create_group function
"""
groups = []
group_counter = 0
def _create_group(name: Optional[str] = None):
nonlocal group_counter
... | 310 | 348 | """Account, user fixtures."""
import json
import logging
from time import monotonic, sleep
from typing import List, NamedTuple, Optional, Tuple
import pytest
from box import Box
from dynaconf import settings
from ambra_sdk.exceptions.service import DuplicateName, NotEmpty
from ambra_sdk.models import Group
from ambr... |
encode | Encodes the CID using a given multibase. If :obj:`None` is given,
the CID's own multibase is used by default.
Example usage:
>>> s = "zb2rhe5P4gXftAwvA4eXQ5HJwsER2owDyS9sKaQRRVQPn93bA"
>>> cid = CID.decode(s)
>>> cid.encode() # default: cid.base
'zb2rhe5P4gXftAwvA4eXQ5HJwsER2owDyS9sKaQRRVQPn93bA'
>>> cid.encode("base... | """
Implementation of the `CID spec <https://github.com/multiformats/cid>`_.
This module differs from other modules of :mod:`~multiformats`, in that the functionality is completely
encapsulated by a single class :class:`CID`, which is imported from top level instead
of the module itself:
>>> from ... | def encode(self, base: Union[None, str, Multibase] = None) -> str:
"""
Encodes the CID using a given multibase. If :obj:`None` is given,
the CID's own multibase is used by default.
Example usage:
>>> s = "zb2rhe5P4gXftAwvA4eXQ5HJwsER2owDyS9sKaQRRVQPn93bA"
... | 346 | 377 | """
Implementation of the `CID spec <https://github.com/multiformats/cid>`_.
This module differs from other modules of :mod:`~multiformats`, in that the functionality is completely
encapsulated by a single class :class:`CID`, which is imported from top level instead
of the module itself:
>>> from ... |
set | Returns a new CID obtained by setting new values for one or more of:
``base``, ``version``, or ``codec``.
Example usage:
>>> s = "zb2rhe5P4gXftAwvA4eXQ5HJwsER2owDyS9sKaQRRVQPn93bA"
>>> cid = CID.decode(s)
>>> cid
CID('base58btc', 1, 'raw',
'12206e6ff7950a36187a801613426e858dce686cd7d7e3c0fc42ee0330072d245c95')
>>> ci... | """
Implementation of the `CID spec <https://github.com/multiformats/cid>`_.
This module differs from other modules of :mod:`~multiformats`, in that the functionality is completely
encapsulated by a single class :class:`CID`, which is imported from top level instead
of the module itself:
>>> from ... | def set(self, *,
base: Union[None, str, Multibase] = None,
version: Union[None, int] = None,
codec: Union[None, str, int, Multicodec] = None
) -> "CID":
"""
Returns a new CID obtained by setting new values for one or more of:
``base``, `... | 379 | 449 | """
Implementation of the `CID spec <https://github.com/multiformats/cid>`_.
This module differs from other modules of :mod:`~multiformats`, in that the functionality is completely
encapsulated by a single class :class:`CID`, which is imported from top level instead
of the module itself:
>>> from ... |
onerror | Error handler for ``shutil.rmtree``.
If the error is due to an access error (read only file)
it attempts to add write permission and then retries.
If the error is for another reason it re-raises the error.
Usage : ``shutil.rmtree(path, onerror=onerror)`` | import os
import shutil
from thlib.side.Qt import QtWidgets as QtGui
from thlib.side.Qt import QtGui as Qt4Gui
from thlib.side.Qt import QtCore
from thlib.environment import env_inst, env_tactic, cfg_controls, env_read_config, env_write_config, dl
import thlib.global_functions as gf
import thlib.tactic_classes as tc
fr... | def onerror(func, path, exc_info):
"""
Error handler for ``shutil.rmtree``.
If the error is due to an access error (read only file)
it attempts to add write permission and then retries.
If the error is for another reason it re-raises the error.
... | 317 | 332 | import os
import shutil
from thlib.side.Qt import QtWidgets as QtGui
from thlib.side.Qt import QtGui as Qt4Gui
from thlib.side.Qt import QtCore
from thlib.environment import env_inst, env_tactic, cfg_controls, env_read_config, env_write_config, dl
import thlib.global_functions as gf
import thlib.tactic_classes as tc
fr... |
pressure | Calculate pressure at specified loading.
For the TemkinApprox model, the pressure will
be computed numerically as no analytical inversion is possible.
Parameters
----------
loading : float
The loading at which to calculate the pressure.
Returns
-------
float
Pressure at specified loading. | """Temkin Approximation isotherm model."""
import numpy
import scipy
from ..utilities.exceptions import CalculationError
from .base_model import IsothermBaseModel
class TemkinApprox(IsothermBaseModel):
r"""
Asymptotic approximation to the Temkin isotherm.
.. math::
n(p) = n_m \frac{K p}{1 + K ... | def pressure(self, loading):
"""
Calculate pressure at specified loading.
For the TemkinApprox model, the pressure will
be computed numerically as no analytical inversion is possible.
Parameters
----------
loading : float
The loading at which to ... | 72 | 99 | """Temkin Approximation isotherm model."""
import numpy
import scipy
from ..utilities.exceptions import CalculationError
from .base_model import IsothermBaseModel
class TemkinApprox(IsothermBaseModel):
r"""
Asymptotic approximation to the Temkin isotherm.
.. math::
n(p) = n_m \frac{K p}{1 + K ... |
initial_guess | Return initial guess for fitting.
Parameters
----------
pressure : ndarray
Pressure data.
loading : ndarray
Loading data.
Returns
-------
dict
Dictionary of initial guesses for the parameters. | """Temkin Approximation isotherm model."""
import numpy
import scipy
from ..utilities.exceptions import CalculationError
from .base_model import IsothermBaseModel
class TemkinApprox(IsothermBaseModel):
r"""
Asymptotic approximation to the Temkin isotherm.
.. math::
n(p) = n_m \frac{K p}{1 + K ... | def initial_guess(self, pressure, loading):
"""
Return initial guess for fitting.
Parameters
----------
pressure : ndarray
Pressure data.
loading : ndarray
Loading data.
Returns
-------
dict
Dictionary of i... | 133 | 159 | """Temkin Approximation isotherm model."""
import numpy
import scipy
from ..utilities.exceptions import CalculationError
from .base_model import IsothermBaseModel
class TemkinApprox(IsothermBaseModel):
r"""
Asymptotic approximation to the Temkin isotherm.
.. math::
n(p) = n_m \frac{K p}{1 + K ... |
collect_potential_dependencies | Collect all potential dependencies of a job. These might contain
ambiguities. The keys of the returned dict represent the files to be considered. | __author__ = "Johannes Köster"
__copyright__ = "Copyright 2015-2019, Johannes Köster"
__email__ = "koester@jimmy.harvard.edu"
__license__ = "MIT"
import html
import os
import shutil
import textwrap
import time
import tarfile
from collections import defaultdict, Counter
from itertools import chain, filterfalse, groupby... | def collect_potential_dependencies(self, job):
"""Collect all potential dependencies of a job. These might contain
ambiguities. The keys of the returned dict represent the files to be considered."""
dependencies = defaultdict(list)
# use a set to circumvent multiple jobs for the same... | 1,423 | 1,458 | __author__ = "Johannes Köster"
__copyright__ = "Copyright 2015-2019, Johannes Köster"
__email__ = "koester@jimmy.harvard.edu"
__license__ = "MIT"
import html
import os
import shutil
import textwrap
import time
import tarfile
from collections import defaultdict, Counter
from itertools import chain, filterfalse, groupby... |
archive | Archives workflow such that it can be re-run on a different system.
Archiving includes git versioned files (i.e. Snakefiles, config files, ...),
ancestral input files and conda environments. | __author__ = "Johannes Köster"
__copyright__ = "Copyright 2015-2019, Johannes Köster"
__email__ = "koester@jimmy.harvard.edu"
__license__ = "MIT"
import html
import os
import shutil
import textwrap
import time
import tarfile
from collections import defaultdict, Counter
from itertools import chain, filterfalse, groupby... | def archive(self, path):
"""Archives workflow such that it can be re-run on a different system.
Archiving includes git versioned files (i.e. Snakefiles, config files, ...),
ancestral input files and conda environments.
"""
if path.endswith(".tar"):
mode = "x"
... | 1,856 | 1,926 | __author__ = "Johannes Köster"
__copyright__ = "Copyright 2015-2019, Johannes Köster"
__email__ = "koester@jimmy.harvard.edu"
__license__ = "MIT"
import html
import os
import shutil
import textwrap
import time
import tarfile
from collections import defaultdict, Counter
from itertools import chain, filterfalse, groupby... |
_min_norm_2d | Find the minimum norm solution as combination of two points
This is correct only in 2D
ie. min_c |\sum c_i x_i|_2^2 st. \sum c_i = 1 , 1 >= c_1 >= 0
for all i, c_i + c_j = 1.0 for some i, j | # Credits to Ozan Sener
# https://github.com/intel-isl/MultiObjectiveOptimization
import numpy as np
import torch
class MGDASolver:
MAX_ITER = 250
STOP_CRIT = 1e-5
@staticmethod
def _min_norm_element_from2(v1v1, v1v2, v2v2):
"""
Analytical solution for min_{c} |cx_1 + (1-c)x_2|_2^2
... | @staticmethod
def _min_norm_2d(vecs: list, dps):
"""
Find the minimum norm solution as combination of two points
This is correct only in 2D
ie. min_c |\sum c_i x_i|_2^2 st. \sum c_i = 1 , 1 >= c_1 >= 0
for all i, c_i + c_j = 1.0 for some i, j
"""
dmin = 1e... | 36 | 70 | # Credits to Ozan Sener
# https://github.com/intel-isl/MultiObjectiveOptimization
import numpy as np
import torch
class MGDASolver:
MAX_ITER = 250
STOP_CRIT = 1e-5
@staticmethod
def _min_norm_element_from2(v1v1, v1v2, v2v2):
"""
Analytical solution for min_{c} |cx_1 + (1-c)x_2|_2^2
... |
refresh | Refresh materialized views.
First, this method finds the namespaces being replicated, by referring to the
config for schemas and tables.
Then it finds any materialized views in the namespaces.
Then it refreshes the materialized views. | """This module contains logic for refreshing materialized views.
Materialized views don't get refreshed automatically after a bucardo initial
sync. This module detects them and refreshes them.
Classes exported:
MatViews: Identify materialized views and refresh them on the secondary database.
"""
import psycopg2
from... | def refresh(self):
"""Refresh materialized views.
First, this method finds the namespaces being replicated, by referring to the
config for schemas and tables.
Then it finds any materialized views in the namespaces.
Then it refreshes the materialized views.
"""
... | 41 | 73 | """This module contains logic for refreshing materialized views.
Materialized views don't get refreshed automatically after a bucardo initial
sync. This module detects them and refreshes them.
Classes exported:
MatViews: Identify materialized views and refresh them on the secondary database.
"""
import psycopg2
from... |
get_scattering_phase_function | Return the scattering phase function in function of wavelength for the
corresponding dust type (SMC or MW). The scattering phase
function gives the angle at which the photon scatters.
Parameters
----------
x: float
expects either x in units of wavelengths or frequency
or assumes wavelengths in [micron]
inter... | # -*- coding: utf-8 -*-
import numpy as np
import astropy.units as u
import pkg_resources
from astropy.io import ascii
from astropy.modeling.tabular import tabular_model
from .baseclasses import BaseAtttauVModel
from .helpers import _test_valid_x_range
__all__ = ["WG00"]
x_range_WG00 = [0.1, 3.0001]
class WG00(... | def get_scattering_phase_function(self, x):
"""
Return the scattering phase function in function of wavelength for the
corresponding dust type (SMC or MW). The scattering phase
function gives the angle at which the photon scatters.
Parameters
----------
x: fl... | 619 | 735 | # -*- coding: utf-8 -*-
import numpy as np
import astropy.units as u
import pkg_resources
from astropy.io import ascii
from astropy.modeling.tabular import tabular_model
from .baseclasses import BaseAtttauVModel
from .helpers import _test_valid_x_range
__all__ = ["WG00"]
x_range_WG00 = [0.1, 3.0001]
class WG00(... |
load_raster_tile_lookup | Load in the preprocessed raster tile lookup.
Parameters
----------
iso3 : string
Country iso3 code.
Returns
-------
lookup : dict
A lookup table containing raster tile boundary coordinates
as the keys, and the file paths as the values. | """
Extract CLOS / NLOS lookup.
Written by Ed Oughton.
March 2021
"""
import os
import configparser
import json
import math
import glob
import random
import numpy as np
import pandas as pd
import geopandas as gpd
import pyproj
from shapely.geometry import Point, Polygon, box, LineString
from shapely.ops import trans... | def load_raster_tile_lookup(iso3):
"""
Load in the preprocessed raster tile lookup.
Parameters
----------
iso3 : string
Country iso3 code.
Returns
-------
lookup : dict
A lookup table containing raster tile boundary coordinates
as the keys, and the file paths as... | 44 | 72 | """
Extract CLOS / NLOS lookup.
Written by Ed Oughton.
March 2021
"""
import os
import configparser
import json
import math
import glob
import random
import numpy as np
import pandas as pd
import geopandas as gpd
import pyproj
from shapely.geometry import Point, Polygon, box, LineString
from shapely.ops import trans... |
find_tile | Parameters
----------
polygon : tuple
The bounds of the modeling region.
tile_lookup : dict
A lookup table containing raster tile boundary coordinates
as the keys, and the file paths as the values.
Return
------
output : list
Contains the file path to the correct raster tile. Note:
only the first e... | """
Extract CLOS / NLOS lookup.
Written by Ed Oughton.
March 2021
"""
import os
import configparser
import json
import math
import glob
import random
import numpy as np
import pandas as pd
import geopandas as gpd
import pyproj
from shapely.geometry import Point, Polygon, box, LineString
from shapely.ops import trans... | def find_tile(polygon, tile_lookup):
"""
Parameters
----------
polygon : tuple
The bounds of the modeling region.
tile_lookup : dict
A lookup table containing raster tile boundary coordinates
as the keys, and the file paths as the values.
Return
------
output : ... | 132 | 168 | """
Extract CLOS / NLOS lookup.
Written by Ed Oughton.
March 2021
"""
import os
import configparser
import json
import math
import glob
import random
import numpy as np
import pandas as pd
import geopandas as gpd
import pyproj
from shapely.geometry import Point, Polygon, box, LineString
from shapely.ops import trans... |
test_jlock_init_and_delete | Tests initialization and deleting a ``JLock``.
Args:
self (TestJLock): the ``TestJLock`` instance
Returns:
``None`` | # Copyright 2017 Square, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,... | @mock.patch('tempfile.tempdir', new='tmp')
def test_jlock_init_and_delete(self):
"""Tests initialization and deleting a ``JLock``.
Args:
self (TestJLock): the ``TestJLock`` instance
Returns:
``None``
"""
serial_no = 0xdeadbeef
lock = jlock.J... | 54 | 69 | # Copyright 2017 Square, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,... |
test_jlock_acquire_exists | Tests trying to acquire when the lock exists for an active process.
Args:
self (TestJLock): the ``TestJLock`` instance
mock_open (Mock): mocked built-in open method
mock_util (Mock): mocked ``psutil`` module
mock_rm (Mock): mocked os remove method
mock_wr (Mock): mocked os write method
mock_op (Mock): mock... | # Copyright 2017 Square, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,... | @mock.patch('tempfile.tempdir', new='tmp')
@mock.patch('os.close')
@mock.patch('os.path.exists')
@mock.patch('os.open')
@mock.patch('os.write')
@mock.patch('os.remove')
@mock.patch('pylink.jlock.psutil')
@mock.patch('pylink.jlock.open')
def test_jlock_acquire_exists(self, mock_open, ... | 71 | 117 | # Copyright 2017 Square, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,... |
test_jlock_acquire_os_error | Tests trying to acquire the lock but generating an os-level error.
Args:
self (TestJLock): the ``TestJLock`` instance
mock_open (Mock): mocked built-in open method
mock_util (Mock): mocked ``psutil`` module
mock_rm (Mock): mocked os remove method
mock_wr (Mock): mocked os write method
mock_op (Mock): mocke... | # Copyright 2017 Square, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,... | @mock.patch('tempfile.tempdir', new='tmp')
@mock.patch('os.close')
@mock.patch('os.path.exists')
@mock.patch('os.open')
@mock.patch('os.write')
@mock.patch('os.remove')
@mock.patch('pylink.jlock.psutil')
@mock.patch('pylink.jlock.open')
def test_jlock_acquire_os_error(self, mock_open... | 119 | 162 | # Copyright 2017 Square, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,... |
test_jlock_acquire_bad_file | Tests acquiring the lockfile when the current lockfile is invallid.
Args:
self (TestJLock): the ``TestJLock`` instance
mock_open (Mock): mocked built-in open method
mock_util (Mock): mocked ``psutil`` module
mock_rm (Mock): mocked os remove method
mock_wr (Mock): mocked os write method
mock_op (Mock): mock... | # Copyright 2017 Square, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,... | @mock.patch('tempfile.tempdir', new='tmp')
@mock.patch('os.close')
@mock.patch('os.path.exists')
@mock.patch('os.open')
@mock.patch('os.write')
@mock.patch('os.remove')
@mock.patch('pylink.jlock.psutil')
@mock.patch('pylink.jlock.open')
def test_jlock_acquire_bad_file(self, mock_open... | 164 | 211 | # Copyright 2017 Square, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,... |
test_jlock_acquire_invalid_pid | Tests acquiring the lockfile when the pid in the lockfile is invalid.
Args:
self (TestJLock): the ``TestJLock`` instance
mock_open (Mock): mocked built-in open method
mock_util (Mock): mocked ``psutil`` module
mock_rm (Mock): mocked os remove method
mock_wr (Mock): mocked os write method
mock_op (Mock): mo... | # Copyright 2017 Square, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,... | @mock.patch('tempfile.tempdir', new='tmp')
@mock.patch('os.close')
@mock.patch('os.path.exists')
@mock.patch('os.open')
@mock.patch('os.write')
@mock.patch('os.remove')
@mock.patch('pylink.jlock.psutil')
@mock.patch('pylink.jlock.open')
def test_jlock_acquire_invalid_pid(self, mock_o... | 213 | 258 | # Copyright 2017 Square, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,... |
test_jlock_acquire_old_pid | Tests acquiring when the PID in the lockfile does not exist.
Args:
self (TestJLock): the ``TestJLock`` instance
mock_open (Mock): mocked built-in open method
mock_util (Mock): mocked ``psutil`` module
mock_rm (Mock): mocked os remove method
mock_wr (Mock): mocked os write method
mock_op (Mock): mocked os o... | # Copyright 2017 Square, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,... | @mock.patch('tempfile.tempdir', new='tmp')
@mock.patch('os.close')
@mock.patch('os.path.exists')
@mock.patch('os.open')
@mock.patch('os.write')
@mock.patch('os.remove')
@mock.patch('pylink.jlock.psutil')
@mock.patch('pylink.jlock.open')
def test_jlock_acquire_old_pid(self, mock_open,... | 260 | 306 | # Copyright 2017 Square, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,... |
test_jlock_release_acquired | Tests releasing a held lock.
Args:
self (TestJLock): the ``TestJLock`` instance
mock_remove (Mock): mock file removal method
mock_close (Mock): mocked close method
mock_exists (Mock): mocked path exist method
Returns:
``None`` | # Copyright 2017 Square, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,... | @mock.patch('tempfile.tempdir', new='tmp')
@mock.patch('os.path.exists')
@mock.patch('os.close')
@mock.patch('os.remove')
def test_jlock_release_acquired(self, mock_remove, mock_close, mock_exists):
"""Tests releasing a held lock.
Args:
self (TestJLock): the ``TestJLock`` ... | 308 | 336 | # Copyright 2017 Square, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,... |
distance_p2p | Computes minimal distances of each point in points_src to points_tgt.
Args:
points_src (numpy array): source points
normals_src (numpy array): source normals
points_tgt (numpy array): target points
normals_tgt (numpy array): target normals | import logging
import numpy as np
import trimesh
from src.common import compute_iou
# from scipy.spatial import cKDTree
from src.utils.libkdtree import KDTree
from src.utils.libmesh import check_mesh_contains
# Maximum values for bounding box [-0.5, 0.5]^3
EMPTY_PCL_DICT = {
'completeness': np.sqrt(3),
'accu... | def distance_p2p(points_src, normals_src, points_tgt, normals_tgt):
""" Computes minimal distances of each point in points_src to points_tgt.
Args:
points_src (numpy array): source points
normals_src (numpy array): source normals
points_tgt (numpy array): target points
normals_t... | 173 | 194 | import logging
import numpy as np
import trimesh
from src.common import compute_iou
# from scipy.spatial import cKDTree
from src.utils.libkdtree import KDTree
from src.utils.libmesh import check_mesh_contains
# Maximum values for bounding box [-0.5, 0.5]^3
EMPTY_PCL_DICT = {
'completeness': np.sqrt(3),
'accu... |
add_descriptor | Add a descriptor to this index.
Adding the same descriptor multiple times should not add multiple
copies of the descriptor in the index.
:param descriptor: Descriptor to index.
:type descriptor: smqtk.representation.DescriptorElement
:param no_cache: Do not cache the internal table if a file cache was
provided. ... | import six
from smqtk.representation import DescriptorIndex, get_data_element_impls
from smqtk.utils import merge_dict, plugin, SimpleTimer
try:
from six.moves import cPickle as pickle
except ImportError:
import pickle
class MemoryDescriptorIndex (DescriptorIndex):
"""
In-memory descriptor index wit... | def add_descriptor(self, descriptor, no_cache=False):
"""
Add a descriptor to this index.
Adding the same descriptor multiple times should not add multiple
copies of the descriptor in the index.
:param descriptor: Descriptor to index.
:type descriptor: smqtk.represe... | 161 | 179 | import six
from smqtk.representation import DescriptorIndex, get_data_element_impls
from smqtk.utils import merge_dict, plugin, SimpleTimer
try:
from six.moves import cPickle as pickle
except ImportError:
import pickle
class MemoryDescriptorIndex (DescriptorIndex):
"""
In-memory descriptor index wit... |
add_many_descriptors | Add multiple descriptors at one time.
:param descriptors: Iterable of descriptor instances to add to this
index.
:type descriptors:
collections.Iterable[smqtk.representation.DescriptorElement] | import six
from smqtk.representation import DescriptorIndex, get_data_element_impls
from smqtk.utils import merge_dict, plugin, SimpleTimer
try:
from six.moves import cPickle as pickle
except ImportError:
import pickle
class MemoryDescriptorIndex (DescriptorIndex):
"""
In-memory descriptor index wit... | def add_many_descriptors(self, descriptors):
"""
Add multiple descriptors at one time.
:param descriptors: Iterable of descriptor instances to add to this
index.
:type descriptors:
collections.Iterable[smqtk.representation.DescriptorElement]
"""
... | 181 | 197 | import six
from smqtk.representation import DescriptorIndex, get_data_element_impls
from smqtk.utils import merge_dict, plugin, SimpleTimer
try:
from six.moves import cPickle as pickle
except ImportError:
import pickle
class MemoryDescriptorIndex (DescriptorIndex):
"""
In-memory descriptor index wit... |
__init__ | Set up jailer fields.
This plays the role of a default constructor as it populates
the jailer's fields with some default values. Each field can be
further adjusted by each test even with None values. | # Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: Apache-2.0
"""Define a class for creating the jailed context."""
import os
import shutil
from subprocess import run, PIPE
from retry.api import retry_call
from framework.defs import API_USOCKET_NAME, FC_BINARY_NAME,... | def __init__(
self,
jailer_id,
exec_file,
numa_node=0,
uid=1234,
gid=1234,
chroot_base=JAILER_DEFAULT_CHROOT,
netns=None,
daemonize=True,
seccomp_level=2
):
"""Set up jailer fields.
... | 33 | 59 | # Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: Apache-2.0
"""Define a class for creating the jailed context."""
import os
import shutil
from subprocess import run, PIPE
from retry.api import retry_call
from framework.defs import API_USOCKET_NAME, FC_BINARY_NAME,... |
_kill_crgoup_tasks | Simulate wait on pid.
Read the tasks file and stay there until /proc/{pid}
disappears. The retry function that calls this code makes
sure we do not timeout. | # Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: Apache-2.0
"""Define a class for creating the jailed context."""
import os
import shutil
from subprocess import run, PIPE
from retry.api import retry_call
from framework.defs import API_USOCKET_NAME, FC_BINARY_NAME,... | def _kill_crgoup_tasks(self, controller):
"""Simulate wait on pid.
Read the tasks file and stay there until /proc/{pid}
disappears. The retry function that calls this code makes
sure we do not timeout.
"""
tasks_file = '/sys/fs/cgroup/{}/{}/{}/tasks'.format(
... | 208 | 233 | # Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: Apache-2.0
"""Define a class for creating the jailed context."""
import os
import shutil
from subprocess import run, PIPE
from retry.api import retry_call
from framework.defs import API_USOCKET_NAME, FC_BINARY_NAME,... |
__init__ | Constructor for :class:`.RepTaxonomy`
Parameters
----------
taxonomy
Data containing feature taxonomy
taxonomy_columns
Column(s) containing taxonomy data
kwargs
Passed to :func:`~pandas.read_csv` or :mod:`biome` loader. | import warnings
warnings.simplefilter("ignore", category=FutureWarning)
from pmaf.biome.essentials._metakit import EssentialFeatureMetabase
from pmaf.biome.essentials._base import EssentialBackboneBase
from pmaf.internal._constants import (
AVAIL_TAXONOMY_NOTATIONS,
jRegexGG,
jRegexQIIME,
BIOM_TAXONOMY... | def __init__(
self,
taxonomy: Union[pd.DataFrame, pd.Series, str],
taxonomy_columns: Union[str, int, Sequence[Union[int, str]]] = None,
**kwargs: Any
) -> None:
"""Constructor for :class:`.RepTaxonomy`
Parameters
----------
taxonomy
Da... | 33 | 107 | import warnings
warnings.simplefilter("ignore", category=FutureWarning)
from pmaf.biome.essentials._metakit import EssentialFeatureMetabase
from pmaf.biome.essentials._base import EssentialBackboneBase
from pmaf.internal._constants import (
AVAIL_TAXONOMY_NOTATIONS,
jRegexGG,
jRegexQIIME,
BIOM_TAXONOMY... |
__load_biom | Actual private method to process :mod:`biom` file.
Parameters
----------
filepath
:mod:`biom` file path.
kwargs
Compatibility | import warnings
warnings.simplefilter("ignore", category=FutureWarning)
from pmaf.biome.essentials._metakit import EssentialFeatureMetabase
from pmaf.biome.essentials._base import EssentialBackboneBase
from pmaf.internal._constants import (
AVAIL_TAXONOMY_NOTATIONS,
jRegexGG,
jRegexQIIME,
BIOM_TAXONOMY... | @classmethod
def __load_biom(cls, filepath: str, **kwargs: Any) -> Tuple[pd.DataFrame, dict]:
"""Actual private method to process :mod:`biom` file.
Parameters
----------
filepath
:mod:`biom` file path.
kwargs
Compatibility
"""
biom... | 166 | 200 | import warnings
warnings.simplefilter("ignore", category=FutureWarning)
from pmaf.biome.essentials._metakit import EssentialFeatureMetabase
from pmaf.biome.essentials._base import EssentialBackboneBase
from pmaf.internal._constants import (
AVAIL_TAXONOMY_NOTATIONS,
jRegexGG,
jRegexQIIME,
BIOM_TAXONOMY... |
_merge_features_by_map | Merge features and ratify action.
Parameters
----------
map_dict
Map to use for merging
done
Whether merging was completed or not. Compatibility.
kwargs
Compatibility | import warnings
warnings.simplefilter("ignore", category=FutureWarning)
from pmaf.biome.essentials._metakit import EssentialFeatureMetabase
from pmaf.biome.essentials._base import EssentialBackboneBase
from pmaf.internal._constants import (
AVAIL_TAXONOMY_NOTATIONS,
jRegexGG,
jRegexQIIME,
BIOM_TAXONOMY... | def _merge_features_by_map(
self, map_dict: Mapper, done: bool = False, **kwargs: Any
) -> Optional[Mapper]:
"""Merge features and ratify action.
Parameters
----------
map_dict
Map to use for merging
done
Whether merging was completed or n... | 219 | 241 | import warnings
warnings.simplefilter("ignore", category=FutureWarning)
from pmaf.biome.essentials._metakit import EssentialFeatureMetabase
from pmaf.biome.essentials._base import EssentialBackboneBase
from pmaf.internal._constants import (
AVAIL_TAXONOMY_NOTATIONS,
jRegexGG,
jRegexQIIME,
BIOM_TAXONOMY... |
get_taxonomy_by_id | Get taxonomy :class:`~pandas.DataFrame` by feature `ids`.
Parameters
----------
ids
Either feature indices or None for all.
Returns
-------
class:`pandas.DataFrame` with taxonomy data | import warnings
warnings.simplefilter("ignore", category=FutureWarning)
from pmaf.biome.essentials._metakit import EssentialFeatureMetabase
from pmaf.biome.essentials._base import EssentialBackboneBase
from pmaf.internal._constants import (
AVAIL_TAXONOMY_NOTATIONS,
jRegexGG,
jRegexQIIME,
BIOM_TAXONOMY... | def get_taxonomy_by_id(
self, ids: Optional[AnyGenericIdentifier] = None
) -> pd.DataFrame:
"""Get taxonomy :class:`~pandas.DataFrame` by feature `ids`.
Parameters
----------
ids
Either feature indices or None for all.
Returns
-------
... | 261 | 282 | import warnings
warnings.simplefilter("ignore", category=FutureWarning)
from pmaf.biome.essentials._metakit import EssentialFeatureMetabase
from pmaf.biome.essentials._base import EssentialBackboneBase
from pmaf.internal._constants import (
AVAIL_TAXONOMY_NOTATIONS,
jRegexGG,
jRegexQIIME,
BIOM_TAXONOMY... |
drop_features_without_ranks | Remove features that do not contain `ranks`
Parameters
----------
ranks
Ranks to look for
any
If True removes feature with single occurrence of missing rank.
If False all `ranks` must be missing.
kwargs
Compatibility | import warnings
warnings.simplefilter("ignore", category=FutureWarning)
from pmaf.biome.essentials._metakit import EssentialFeatureMetabase
from pmaf.biome.essentials._base import EssentialBackboneBase
from pmaf.internal._constants import (
AVAIL_TAXONOMY_NOTATIONS,
jRegexGG,
jRegexQIIME,
BIOM_TAXONOMY... | def drop_features_without_ranks(
self, ranks: Sequence[str], any: bool = False, **kwargs: Any
) -> Optional[AnyGenericIdentifier]: # Done
"""Remove features that do not contain `ranks`
Parameters
----------
ranks
Ranks to look for
any
If ... | 374 | 400 | import warnings
warnings.simplefilter("ignore", category=FutureWarning)
from pmaf.biome.essentials._metakit import EssentialFeatureMetabase
from pmaf.biome.essentials._base import EssentialBackboneBase
from pmaf.internal._constants import (
AVAIL_TAXONOMY_NOTATIONS,
jRegexGG,
jRegexQIIME,
BIOM_TAXONOMY... |
merge_features_by_rank | Merge features by taxonomic rank/level.
Parameters
----------
level
Taxonomic rank/level to use for merging.
kwargs
Compatibility | import warnings
warnings.simplefilter("ignore", category=FutureWarning)
from pmaf.biome.essentials._metakit import EssentialFeatureMetabase
from pmaf.biome.essentials._base import EssentialBackboneBase
from pmaf.internal._constants import (
AVAIL_TAXONOMY_NOTATIONS,
jRegexGG,
jRegexQIIME,
BIOM_TAXONOMY... | def merge_features_by_rank(self, level: str, **kwargs: Any) -> Optional[Mapper]:
"""Merge features by taxonomic rank/level.
Parameters
----------
level
Taxonomic rank/level to use for merging.
kwargs
Compatibility
"""
ret = {}
... | 425 | 458 | import warnings
warnings.simplefilter("ignore", category=FutureWarning)
from pmaf.biome.essentials._metakit import EssentialFeatureMetabase
from pmaf.biome.essentials._base import EssentialBackboneBase
from pmaf.internal._constants import (
AVAIL_TAXONOMY_NOTATIONS,
jRegexGG,
jRegexQIIME,
BIOM_TAXONOMY... |
get_subset | Get subset of the :class:`.RepTaxonomy`.
Parameters
----------
rids
Feature identifiers.
args
Compatibility
kwargs
Compatibility
Returns
-------
class:`.RepTaxonomy` | import warnings
warnings.simplefilter("ignore", category=FutureWarning)
from pmaf.biome.essentials._metakit import EssentialFeatureMetabase
from pmaf.biome.essentials._base import EssentialBackboneBase
from pmaf.internal._constants import (
AVAIL_TAXONOMY_NOTATIONS,
jRegexGG,
jRegexQIIME,
BIOM_TAXONOMY... | def get_subset(
self, rids: Optional[AnyGenericIdentifier] = None, *args, **kwargs: Any
) -> "RepTaxonomy":
"""Get subset of the :class:`.RepTaxonomy`.
Parameters
----------
rids
Feature identifiers.
args
Compatibility
kwargs
... | 474 | 502 | import warnings
warnings.simplefilter("ignore", category=FutureWarning)
from pmaf.biome.essentials._metakit import EssentialFeatureMetabase
from pmaf.biome.essentials._base import EssentialBackboneBase
from pmaf.internal._constants import (
AVAIL_TAXONOMY_NOTATIONS,
jRegexGG,
jRegexQIIME,
BIOM_TAXONOMY... |
export | Exports the taxonomy into the specified file.
Parameters
----------
output_fp
Export filepath
args
Compatibility
_add_ext
Add file extension or not.
sep
Delimiter
kwargs
Compatibility | import warnings
warnings.simplefilter("ignore", category=FutureWarning)
from pmaf.biome.essentials._metakit import EssentialFeatureMetabase
from pmaf.biome.essentials._base import EssentialBackboneBase
from pmaf.internal._constants import (
AVAIL_TAXONOMY_NOTATIONS,
jRegexGG,
jRegexQIIME,
BIOM_TAXONOMY... | def export(
self,
output_fp: str,
*args,
_add_ext: bool = False,
sep: str = ",",
**kwargs: Any
) -> None:
"""Exports the taxonomy into the specified file.
Parameters
----------
output_fp
Export filepath
args
... | 526 | 553 | import warnings
warnings.simplefilter("ignore", category=FutureWarning)
from pmaf.biome.essentials._metakit import EssentialFeatureMetabase
from pmaf.biome.essentials._base import EssentialBackboneBase
from pmaf.internal._constants import (
AVAIL_TAXONOMY_NOTATIONS,
jRegexGG,
jRegexQIIME,
BIOM_TAXONOMY... |
__init_internal_taxonomy | Main method to initialize taxonomy.
Parameters
----------
taxonomy_data
Incoming parsed taxonomy data
taxonomy_notation
Taxonomy lineage notation style. Can be one of
:const:`pmaf.internals._constants.AVAIL_TAXONOMY_NOTATIONS`
order_ranks
List with the target rank order. Default is set to None.
... | import warnings
warnings.simplefilter("ignore", category=FutureWarning)
from pmaf.biome.essentials._metakit import EssentialFeatureMetabase
from pmaf.biome.essentials._base import EssentialBackboneBase
from pmaf.internal._constants import (
AVAIL_TAXONOMY_NOTATIONS,
jRegexGG,
jRegexQIIME,
BIOM_TAXONOMY... | def __init_internal_taxonomy(
self,
taxonomy_data: Union[pd.Series, pd.DataFrame],
taxonomy_notation: Optional[str] = "greengenes",
order_ranks: Optional[Sequence[str]] = None,
**kwargs: Any
) -> None:
"""Main method to initialize taxonomy.
Parameters
... | 590 | 645 | import warnings
warnings.simplefilter("ignore", category=FutureWarning)
from pmaf.biome.essentials._metakit import EssentialFeatureMetabase
from pmaf.biome.essentials._base import EssentialBackboneBase
from pmaf.internal._constants import (
AVAIL_TAXONOMY_NOTATIONS,
jRegexGG,
jRegexQIIME,
BIOM_TAXONOMY... |
get_share | Represents a share on the Data Box Edge/Gateway device.
:param str device_name: The device name.
:param str name: The share name.
:param str resource_group_name: The resource group name. | # coding=utf-8
# *** WARNING: this file was generated by the Pulumi SDK Generator. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from ... import _utilities
fro... | def get_share(device_name: Optional[str] = None,
name: Optional[str] = None,
resource_group_name: Optional[str] = None,
opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetShareResult:
"""
Represents a share on the Data Box Edge/Gateway device.
:param str... | 202 | 238 | # coding=utf-8
# *** WARNING: this file was generated by the Pulumi SDK Generator. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from ... import _utilities
fro... |
get | Get an existing DataCollectionRule resource's state with the given name, id, and optional extra
properties used to qualify the lookup.
:param str resource_name: The unique name of the resulting resource.
:param pulumi.Input[str] id: The unique provider ID of the resource to lookup.
:param pulumi.ResourceOptions opts: ... | # coding=utf-8
# *** WARNING: this file was generated by the Pulumi SDK Generator. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union
from ... import _utilities, _tables
from... | @staticmethod
def get(resource_name: str,
id: pulumi.Input[str],
opts: Optional[pulumi.ResourceOptions] = None) -> 'DataCollectionRule':
"""
Get an existing DataCollectionRule resource's state with the given name, id, and optional extra
properties used to qualify ... | 90 | 116 | # coding=utf-8
# *** WARNING: this file was generated by the Pulumi SDK Generator. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union
from ... import _utilities, _tables
from... |
get_zones | Method to fetch zones for given region or all the regions if none specified.
Args:
region (str): Name of region to get zones of.
Returns:
zones (obj): Map of zone -> subnet | #!/usr/bin/env python
#
# Copyright 2019 YugaByte, Inc. and Contributors
#
# Licensed under the Polyform Free Trial License 1.0.0 (the "License"); you
# may not use this file except in compliance with the License. You
# may obtain a copy of the License at
#
# https://github.com/YugaByte/yugabyte-db/blob/master/licenses... | def get_zones(region, dest_vpc_id=None):
"""Method to fetch zones for given region or all the regions if none specified.
Args:
region (str): Name of region to get zones of.
Returns:
zones (obj): Map of zone -> subnet
"""
result = {}
filters = get_filters("state", "available")
... | 363 | 389 | #!/usr/bin/env python
#
# Copyright 2019 YugaByte, Inc. and Contributors
#
# Licensed under the Polyform Free Trial License 1.0.0 (the "License"); you
# may not use this file except in compliance with the License. You
# may obtain a copy of the License at
#
# https://github.com/YugaByte/yugabyte-db/blob/master/licenses... |
create_subnet | Method to create subnet based on cidr and tag name.
Args:
client (boto client): Region specific boto client
vpc (VPC object): VPC object to create subnet.
zone (str): Availability zone name
cidr (str): CIDR string
tag_name (str): Tag name for subnet.
Returns:
subnet: Newly created subnet object. | #!/usr/bin/env python
#
# Copyright 2019 YugaByte, Inc. and Contributors
#
# Licensed under the Polyform Free Trial License 1.0.0 (the "License"); you
# may not use this file except in compliance with the License. You
# may obtain a copy of the License at
#
# https://github.com/YugaByte/yugabyte-db/blob/master/licenses... | def create_subnet(client, vpc, zone, cidr, tag_name):
"""Method to create subnet based on cidr and tag name.
Args:
client (boto client): Region specific boto client
vpc (VPC object): VPC object to create subnet.
zone (str): Availability zone name
cidr (str): CIDR string
t... | 416 | 433 | #!/usr/bin/env python
#
# Copyright 2019 YugaByte, Inc. and Contributors
#
# Licensed under the Polyform Free Trial License 1.0.0 (the "License"); you
# may not use this file except in compliance with the License. You
# may obtain a copy of the License at
#
# https://github.com/YugaByte/yugabyte-db/blob/master/licenses... |
create_igw | Method to create Internet Gateway based on tag_name in given VPC. If the gateway
already exists, it would return that object. If the object doesn't have a tag, we
would tag it accordingly.
Args:
client (boto client): Region specific boto client
tag_name (str): Tag name for internet gateway.
vpc (VPC object)... | #!/usr/bin/env python
#
# Copyright 2019 YugaByte, Inc. and Contributors
#
# Licensed under the Polyform Free Trial License 1.0.0 (the "License"); you
# may not use this file except in compliance with the License. You
# may obtain a copy of the License at
#
# https://github.com/YugaByte/yugabyte-db/blob/master/licenses... | @get_or_create(get_igw)
def create_igw(client, tag_name, vpc):
"""Method to create Internet Gateway based on tag_name in given VPC. If the gateway
already exists, it would return that object. If the object doesn't have a tag, we
would tag it accordingly.
Args:
client (boto client): Region specif... | 486 | 509 | #!/usr/bin/env python
#
# Copyright 2019 YugaByte, Inc. and Contributors
#
# Licensed under the Polyform Free Trial License 1.0.0 (the "License"); you
# may not use this file except in compliance with the License. You
# may obtain a copy of the License at
#
# https://github.com/YugaByte/yugabyte-db/blob/master/licenses... |
create_route_table | Method to create route table based on tag_name in given VPC. It will first
query for the tag name to see if the route table already exists or if one is already
attached to the VPC, if so it will return that route table.
Args:
client (boto client): Region specific boto client
tag_name (str): Route table tag name... | #!/usr/bin/env python
#
# Copyright 2019 YugaByte, Inc. and Contributors
#
# Licensed under the Polyform Free Trial License 1.0.0 (the "License"); you
# may not use this file except in compliance with the License. You
# may obtain a copy of the License at
#
# https://github.com/YugaByte/yugabyte-db/blob/master/licenses... | @get_or_create(get_route_table)
def create_route_table(client, tag_name, vpc):
"""Method to create route table based on tag_name in given VPC. It will first
query for the tag name to see if the route table already exists or if one is already
attached to the VPC, if so it will return that route table.
Ar... | 524 | 545 | #!/usr/bin/env python
#
# Copyright 2019 YugaByte, Inc. and Contributors
#
# Licensed under the Polyform Free Trial License 1.0.0 (the "License"); you
# may not use this file except in compliance with the License. You
# may obtain a copy of the License at
#
# https://github.com/YugaByte/yugabyte-db/blob/master/licenses... |
cleanup_igw | Method to cleanup Internet Gateway matching the tag name. And also remove any vpc
that is attached to the Internet Gateway.
Args:
igw: Instance of Internet Gateway matching tag_name. | #!/usr/bin/env python
#
# Copyright 2019 YugaByte, Inc. and Contributors
#
# Licensed under the Polyform Free Trial License 1.0.0 (the "License"); you
# may not use this file except in compliance with the License. You
# may obtain a copy of the License at
#
# https://github.com/YugaByte/yugabyte-db/blob/master/licenses... | @get_and_cleanup(get_igw)
def cleanup_igw(igw, **kwargs):
"""Method to cleanup Internet Gateway matching the tag name. And also remove any vpc
that is attached to the Internet Gateway.
Args:
igw: Instance of Internet Gateway matching tag_name.
"""
for vpc in igw.attachments:
igw.deta... | 557 | 566 | #!/usr/bin/env python
#
# Copyright 2019 YugaByte, Inc. and Contributors
#
# Licensed under the Polyform Free Trial License 1.0.0 (the "License"); you
# may not use this file except in compliance with the License. You
# may obtain a copy of the License at
#
# https://github.com/YugaByte/yugabyte-db/blob/master/licenses... |
create_vpc | Method to create vpc based on the cidr and tag with tag_name.
Args:
client (boto client): Region specific boto client
tag_name (str): VPC tag name
cidr (str): CIDR string.
Returns:
VPC(Object): Newly created VPC object. | #!/usr/bin/env python
#
# Copyright 2019 YugaByte, Inc. and Contributors
#
# Licensed under the Polyform Free Trial License 1.0.0 (the "License"); you
# may not use this file except in compliance with the License. You
# may obtain a copy of the License at
#
# https://github.com/YugaByte/yugabyte-db/blob/master/licenses... | @get_or_create(get_vpc)
def create_vpc(client, tag_name, cidr):
"""Method to create vpc based on the cidr and tag with tag_name.
Args:
client (boto client): Region specific boto client
tag_name (str): VPC tag name
cidr (str): CIDR string.
Returns:
VPC(Object): Newly created V... | 589 | 602 | #!/usr/bin/env python
#
# Copyright 2019 YugaByte, Inc. and Contributors
#
# Licensed under the Polyform Free Trial License 1.0.0 (the "License"); you
# may not use this file except in compliance with the License. You
# may obtain a copy of the License at
#
# https://github.com/YugaByte/yugabyte-db/blob/master/licenses... |
set_yb_sg_and_fetch_vpc | Method to bootstrap vpc and security group, and enable vpc peering
with the host_instance vpc.
Args:
metadata (obj): Cloud metadata object with cidr prefix and other metadata.
region (str): Region name to create the vpc in.
dest_vpc_id (str): Id of the VPC that yugabyte machines will reside in.
Returns:
... | #!/usr/bin/env python
#
# Copyright 2019 YugaByte, Inc. and Contributors
#
# Licensed under the Polyform Free Trial License 1.0.0 (the "License"); you
# may not use this file except in compliance with the License. You
# may obtain a copy of the License at
#
# https://github.com/YugaByte/yugabyte-db/blob/master/licenses... | def set_yb_sg_and_fetch_vpc(metadata, region, dest_vpc_id):
"""Method to bootstrap vpc and security group, and enable vpc peering
with the host_instance vpc.
Args:
metadata (obj): Cloud metadata object with cidr prefix and other metadata.
region (str): Region name to create the vpc in.
... | 605 | 626 | #!/usr/bin/env python
#
# Copyright 2019 YugaByte, Inc. and Contributors
#
# Licensed under the Polyform Free Trial License 1.0.0 (the "License"); you
# may not use this file except in compliance with the License. You
# may obtain a copy of the License at
#
# https://github.com/YugaByte/yugabyte-db/blob/master/licenses... |
vpc_components_as_json | Method takes VPC, Security Group and Subnets and returns a json data format with ids.
Args:
vpc (VPC Object): Region specific VPC object
sgs (List of Security Group Object): Region specific Security Group object
subnets (subnet object map): Map of Subnet objects keyed of zone.
Retuns:
json (str): A Json... | #!/usr/bin/env python
#
# Copyright 2019 YugaByte, Inc. and Contributors
#
# Licensed under the Polyform Free Trial License 1.0.0 (the "License"); you
# may not use this file except in compliance with the License. You
# may obtain a copy of the License at
#
# https://github.com/YugaByte/yugabyte-db/blob/master/licenses... | def vpc_components_as_json(vpc, sgs, subnets):
"""Method takes VPC, Security Group and Subnets and returns a json data format with ids.
Args:
vpc (VPC Object): Region specific VPC object
sgs (List of Security Group Object): Region specific Security Group object
subnets (subnet object map... | 688 | 703 | #!/usr/bin/env python
#
# Copyright 2019 YugaByte, Inc. and Contributors
#
# Licensed under the Polyform Free Trial License 1.0.0 (the "License"); you
# may not use this file except in compliance with the License. You
# may obtain a copy of the License at
#
# https://github.com/YugaByte/yugabyte-db/blob/master/licenses... |
get_vpc_peerings | Method to fetch all the VPC peerings against given VPC. If host_vpc is provided
it will check if there is a peering against that vpc.
Args:
vpc(VPC object): VPC Object to search for peerings
host_vpc (Host VPC object): Can be Null as well, to check if specific host_vpc
peering is... | #!/usr/bin/env python
#
# Copyright 2019 YugaByte, Inc. and Contributors
#
# Licensed under the Polyform Free Trial License 1.0.0 (the "License"); you
# may not use this file except in compliance with the License. You
# may obtain a copy of the License at
#
# https://github.com/YugaByte/yugabyte-db/blob/master/licenses... | def get_vpc_peerings(vpc, host_vpc, **kwargs):
"""Method to fetch all the VPC peerings against given VPC. If host_vpc is provided
it will check if there is a peering against that vpc.
Args:
vpc(VPC object): VPC Object to search for peerings
host_vpc (Host VPC object): Can be Null as well, to... | 774 | 795 | #!/usr/bin/env python
#
# Copyright 2019 YugaByte, Inc. and Contributors
#
# Licensed under the Polyform Free Trial License 1.0.0 (the "License"); you
# may not use this file except in compliance with the License. You
# may obtain a copy of the License at
#
# https://github.com/YugaByte/yugabyte-db/blob/master/licenses... |
__init__ | Keyword args:
transmitted_bytes_per_sec (float): Total bytes transmitted per second.
received_bytes_per_sec (float): Total bytes received per second. | # coding: utf-8
"""
FlashBlade REST API
A lightweight client for FlashBlade REST API 2.3, developed by Pure Storage, Inc. (http://www.purestorage.com/).
OpenAPI spec version: 2.3
Generated by: https://github.com/swagger-api/swagger-codegen.git
"""
import pprint
import re
import six
import typ... | def __init__(
self,
transmitted_bytes_per_sec=None, # type: float
received_bytes_per_sec=None, # type: float
):
"""
Keyword args:
transmitted_bytes_per_sec (float): Total bytes transmitted per second.
received_bytes_per_sec (float): Total bytes r... | 45 | 58 | # coding: utf-8
"""
FlashBlade REST API
A lightweight client for FlashBlade REST API 2.3, developed by Pure Storage, Inc. (http://www.purestorage.com/).
OpenAPI spec version: 2.3
Generated by: https://github.com/swagger-api/swagger-codegen.git
"""
import pprint
import re
import six
import typ... |
debug_identity | Debug Identity Op.
Provides an identity mapping of the non-Ref type input tensor for debugging.
Args:
input: A `Tensor`. Input tensor, non-Reference type.
device_name: An optional `string`. Defaults to `""`.
tensor_name: An optional `string`. Defaults to `""`.
Name of the input tensor.
debug_urls: An opti... | """Python wrappers around TensorFlow ops.
This file is MACHINE GENERATED! Do not edit.
"""
import collections as _collections
import six as _six
from tensorflow.python import pywrap_tensorflow as _pywrap_tensorflow
from tensorflow.python.eager import context as _context
from tensorflow.python.eager import core as _c... | @tf_export('debug_identity')
def debug_identity(input, device_name="", tensor_name="", debug_urls=[], gated_grpc=False, name=None):
r"""Debug Identity Op.
Provides an identity mapping of the non-Ref type input tensor for debugging.
Args:
input: A `Tensor`. Input tensor, non-Reference type.
device_name: ... | 224 | 302 | """Python wrappers around TensorFlow ops.
This file is MACHINE GENERATED! Do not edit.
"""
import collections as _collections
import six as _six
from tensorflow.python import pywrap_tensorflow as _pywrap_tensorflow
from tensorflow.python.eager import context as _context
from tensorflow.python.eager import ... |
debug_nan_count | Debug NaN Value Counter Op
Counts number of NaNs in the input tensor, for debugging.
Args:
input: A `Tensor`. Input tensor, non-Reference type.
device_name: An optional `string`. Defaults to `""`.
tensor_name: An optional `string`. Defaults to `""`.
Name of the input tensor.
debug_urls: An optional list o... | """Python wrappers around TensorFlow ops.
This file is MACHINE GENERATED! Do not edit.
"""
import collections as _collections
import six as _six
from tensorflow.python import pywrap_tensorflow as _pywrap_tensorflow
from tensorflow.python.eager import context as _context
from tensorflow.python.eager import core as _c... | @tf_export('debug_nan_count')
def debug_nan_count(input, device_name="", tensor_name="", debug_urls=[], gated_grpc=False, name=None):
r"""Debug NaN Value Counter Op
Counts number of NaNs in the input tensor, for debugging.
Args:
input: A `Tensor`. Input tensor, non-Reference type.
device_name: An option... | 338 | 416 | """Python wrappers around TensorFlow ops.
This file is MACHINE GENERATED! Do not edit.
"""
import collections as _collections
import six as _six
from tensorflow.python import pywrap_tensorflow as _pywrap_tensorflow
from tensorflow.python.eager import context as _context
from tensorflow.python.eager import ... |
test_module | Tests a given module's stub against introspecting it at runtime.
Requires the stub to have been built already, accomplished by a call to ``build_stubs``.
:param module_name: The module to test | """Tests for stubs.
Verify that various things in stubs are consistent with how things behave at runtime.
"""
import argparse
import copy
import enum
import importlib
import inspect
import re
import sys
import types
import warnings
from functools import singledispatch
from pathlib import Path
from typing import Any,... | def test_module(module_name: str) -> Iterator[Error]:
"""Tests a given module's stub against introspecting it at runtime.
Requires the stub to have been built already, accomplished by a call to ``build_stubs``.
:param module_name: The module to test
"""
stub = get_stub(module_name)
if stub is... | 157 | 180 | """Tests for stubs.
Verify that various things in stubs are consistent with how things behave at runtime.
"""
import argparse
import copy
import enum
import importlib
import inspect
import re
import sys
import types
import warnings
from functools import singledispatch
from pathlib import Path
from typing import Any,... |
_resolve_funcitem_from_decorator | Returns a FuncItem that corresponds to the output of the decorator.
Returns None if we can't figure out what that would be. For convenience, this function also
accepts FuncItems. | """Tests for stubs.
Verify that various things in stubs are consistent with how things behave at runtime.
"""
import argparse
import copy
import enum
import importlib
import inspect
import re
import sys
import types
import warnings
from functools import singledispatch
from pathlib import Path
from typing import Any,... | def _resolve_funcitem_from_decorator(dec: nodes.OverloadPart) -> Optional[nodes.FuncItem]:
"""Returns a FuncItem that corresponds to the output of the decorator.
Returns None if we can't figure out what that would be. For convenience, this function also
accepts FuncItems.
"""
if isinstance(dec, no... | 806 | 848 | """Tests for stubs.
Verify that various things in stubs are consistent with how things behave at runtime.
"""
import argparse
import copy
import enum
import importlib
import inspect
import re
import sys
import types
import warnings
from functools import singledispatch
from pathlib import Path
from typing import Any,... |
build_stubs | Uses mypy to construct stub objects for the given modules.
This sets global state that ``get_stub`` can access.
Returns all modules we might want to check. If ``find_submodules`` is False, this is equal
to ``modules``.
:param modules: List of modules to build stubs for.
:param options: Mypy options for finding and b... | """Tests for stubs.
Verify that various things in stubs are consistent with how things behave at runtime.
"""
import argparse
import copy
import enum
import importlib
import inspect
import re
import sys
import types
import warnings
from functools import singledispatch
from pathlib import Path
from typing import Any,... | def build_stubs(modules: List[str], options: Options, find_submodules: bool = False) -> List[str]:
"""Uses mypy to construct stub objects for the given modules.
This sets global state that ``get_stub`` can access.
Returns all modules we might want to check. If ``find_submodules`` is False, this is equal
... | 1,005 | 1,060 | """Tests for stubs.
Verify that various things in stubs are consistent with how things behave at runtime.
"""
import argparse
import copy
import enum
import importlib
import inspect
import re
import sys
import types
import warnings
from functools import singledispatch
from pathlib import Path
from typing import Any,... |
_maybe_convert_timedelta | Convert timedelta-like input to an integer multiple of self.freq
Parameters
----------
other : timedelta, np.timedelta64, DateOffset, int, np.ndarray
Returns
-------
converted : int, np.ndarray[int64]
Raises
------
IncompatibleFrequency : if the input cannot be written as a multiple
of self.freq. Note Incompati... | from __future__ import annotations
from datetime import (
datetime,
timedelta,
)
from typing import Hashable
import warnings
import numpy as np
from pandas._libs import (
index as libindex,
lib,
)
from pandas._libs.tslibs import (
BaseOffset,
NaT,
Period,
Resolution,
Tick,
)
from ... | def _maybe_convert_timedelta(self, other):
"""
Convert timedelta-like input to an integer multiple of self.freq
Parameters
----------
other : timedelta, np.timedelta64, DateOffset, int, np.ndarray
Returns
-------
converted : int, np.ndarray[int64]
... | 275 | 309 | from __future__ import annotations
from datetime import (
datetime,
timedelta,
)
from typing import Hashable
import warnings
import numpy as np
from pandas._libs import (
index as libindex,
lib,
)
from pandas._libs.tslibs import (
BaseOffset,
NaT,
Period,
Resolution,
Tick,
)
from ... |
get_loc | Get integer location for requested label.
Parameters
----------
key : Period, NaT, str, or datetime
String or datetime key must be parsable as Period.
Returns
-------
loc : int or ndarray[int64]
Raises
------
KeyError
Key is not present in the index.
TypeError
If key is listlike or otherwise not hashable... | from __future__ import annotations
from datetime import (
datetime,
timedelta,
)
from typing import Hashable
import warnings
import numpy as np
from pandas._libs import (
index as libindex,
lib,
)
from pandas._libs.tslibs import (
BaseOffset,
NaT,
Period,
Resolution,
Tick,
)
from ... | def get_loc(self, key, method=None, tolerance=None):
"""
Get integer location for requested label.
Parameters
----------
key : Period, NaT, str, or datetime
String or datetime key must be parsable as Period.
Returns
-------
loc : int or n... | 393 | 485 | from __future__ import annotations
from datetime import (
datetime,
timedelta,
)
from typing import Hashable
import warnings
import numpy as np
from pandas._libs import (
index as libindex,
lib,
)
from pandas._libs.tslibs import (
BaseOffset,
NaT,
Period,
Resolution,
Tick,
)
from ... |
_maybe_cast_slice_bound | If label is a string or a datetime, cast it to Period.ordinal according
to resolution.
Parameters
----------
label : object
side : {'left', 'right'}
kind : {'loc', 'getitem'}, or None
Returns
-------
bound : Period or object
Notes
-----
Value of `side` parameter should be validated in caller. | from __future__ import annotations
from datetime import (
datetime,
timedelta,
)
from typing import Hashable
import warnings
import numpy as np
from pandas._libs import (
index as libindex,
lib,
)
from pandas._libs.tslibs import (
BaseOffset,
NaT,
Period,
Resolution,
Tick,
)
from ... | def _maybe_cast_slice_bound(self, label, side: str, kind=lib.no_default):
"""
If label is a string or a datetime, cast it to Period.ordinal according
to resolution.
Parameters
----------
label : object
side : {'left', 'right'}
kind : {'loc', 'getitem'... | 487 | 525 | from __future__ import annotations
from datetime import (
datetime,
timedelta,
)
from typing import Hashable
import warnings
import numpy as np
from pandas._libs import (
index as libindex,
lib,
)
from pandas._libs.tslibs import (
BaseOffset,
NaT,
Period,
Resolution,
Tick,
)
from ... |
inference_graph | Constructs a TF graph for evaluating a random forest.
Args:
input_data: A tensor or SparseTensor or placeholder for input data.
data_spec: A list of tf.dtype values specifying the original types of
each column.
Returns:
The last op in the random forest inference graph. | # pylint: disable=g-bad-file-header
# Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENS... | def inference_graph(self, input_data, data_spec=None):
"""Constructs a TF graph for evaluating a random forest.
Args:
input_data: A tensor or SparseTensor or placeholder for input data.
data_spec: A list of tf.dtype values specifying the original types of
each column.
Returns:
... | 389 | 412 | # pylint: disable=g-bad-file-header
# Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENS... |
average_size | Constructs a TF graph for evaluating the average size of a forest.
Returns:
The average number of nodes over the trees. | # pylint: disable=g-bad-file-header
# Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENS... | def average_size(self):
"""Constructs a TF graph for evaluating the average size of a forest.
Returns:
The average number of nodes over the trees.
"""
sizes = []
for i in range(self.params.num_trees):
with ops.device(self.device_assigner.get_device(i)):
sizes.append(self.trees... | 414 | 424 | # pylint: disable=g-bad-file-header
# Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENS... |
average_impurity | Constructs a TF graph for evaluating the leaf impurity of a forest.
Returns:
The last op in the graph. | # pylint: disable=g-bad-file-header
# Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENS... | def average_impurity(self):
"""Constructs a TF graph for evaluating the leaf impurity of a forest.
Returns:
The last op in the graph.
"""
impurities = []
for i in range(self.params.num_trees):
with ops.device(self.device_assigner.get_device(i)):
impurities.append(self.trees[i]... | 433 | 443 | # pylint: disable=g-bad-file-header
# Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENS... |
inference_graph | Constructs a TF graph for evaluating a random tree.
Args:
input_data: A tensor or SparseTensor or placeholder for input data.
data_spec: A list of tf.dtype values specifying the original types of
each column.
Returns:
The last op in the random tree inference graph. | # pylint: disable=g-bad-file-header
# Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENS... | def inference_graph(self, input_data, data_spec):
"""Constructs a TF graph for evaluating a random tree.
Args:
input_data: A tensor or SparseTensor or placeholder for input data.
data_spec: A list of tf.dtype values specifying the original types of
each column.
Returns:
The las... | 777 | 801 | # pylint: disable=g-bad-file-header
# Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENS... |
average_impurity | Constructs a TF graph for evaluating the average leaf impurity of a tree.
If in regression mode, this is the leaf variance. If in classification mode,
this is the gini impurity.
Returns:
The last op in the graph. | # pylint: disable=g-bad-file-header
# Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENS... | def average_impurity(self):
"""Constructs a TF graph for evaluating the average leaf impurity of a tree.
If in regression mode, this is the leaf variance. If in classification mode,
this is the gini impurity.
Returns:
The last op in the graph.
"""
children = array_ops.squeeze(array_ops... | 803 | 827 | # pylint: disable=g-bad-file-header
# Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENS... |
ncc_loss | Computes the normalized cross-correlation (NCC) loss.
Currently, only 4-D inputs are supported.
Parameters
----------
static : tf.Tensor, shape (N, H, W, C)
The static image to which the moving image is aligned.
moving : tf.Tensor, shape (N, H, W, C)
The moving image, the same shape as the static image.
Retu... | # -*- coding: utf-8 -*-
"""poc.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1fTzz1aT2sb8oAXRO1-dr6O_IR6dof36e
A simple example for deep-learning-based non-rigid image registration
with the MNIST dataset.
**README:** If the below error occurs,... | @tf.function
def ncc_loss(static, moving):
"""Computes the normalized cross-correlation (NCC) loss.
Currently, only 4-D inputs are supported.
Parameters
----------
static : tf.Tensor, shape (N, H, W, C)
The static image to which the moving image is aligned.
moving : tf.Tensor, shape (N... | 53 | 94 | # -*- coding: utf-8 -*-
"""poc.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1fTzz1aT2sb8oAXRO1-dr6O_IR6dof36e
A simple example for deep-learning-based non-rigid image registration
with the MNIST dataset.
**README:** If the below error occurs,... |
simple_cnn | Creates a 2-D convolutional encoder-decoder network.
Parameters
----------
input_shape : sequence of ints, optional
Input data shape of the form (H, W, C). Default is (32, 32, 2).
Returns
-------
model
An instance of Keras' Model class.
Notes
-----
Given a concatenated pair of static and moving images as inp... | # -*- coding: utf-8 -*-
"""poc.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1fTzz1aT2sb8oAXRO1-dr6O_IR6dof36e
A simple example for deep-learning-based non-rigid image registration
with the MNIST dataset.
**README:** If the below error occurs,... | def simple_cnn(input_shape=(32, 32, 2)):
"""Creates a 2-D convolutional encoder-decoder network.
Parameters
----------
input_shape : sequence of ints, optional
Input data shape of the form (H, W, C). Default is (32, 32, 2).
Returns
-------
model
An instance of Keras' Model ... | 98 | 178 | # -*- coding: utf-8 -*-
"""poc.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1fTzz1aT2sb8oAXRO1-dr6O_IR6dof36e
A simple example for deep-learning-based non-rigid image registration
with the MNIST dataset.
**README:** If the below error occurs,... |
regular_grid | Returns a batch of 2-D regular grids.
Currently, only 2-D regular grids are supported.
Parameters
----------
shape : sequence of ints, shape (3, )
The desired regular grid shape of the form (N, H, W).
Returns
-------
grid : tf.Tensor, shape (N, H, W, 2)
A batch of 2-D regular grids, values normalized to [-1.... | # -*- coding: utf-8 -*-
"""poc.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1fTzz1aT2sb8oAXRO1-dr6O_IR6dof36e
A simple example for deep-learning-based non-rigid image registration
with the MNIST dataset.
**README:** If the below error occurs,... | @tf.function
def regular_grid(shape):
"""Returns a batch of 2-D regular grids.
Currently, only 2-D regular grids are supported.
Parameters
----------
shape : sequence of ints, shape (3, )
The desired regular grid shape of the form (N, H, W).
Returns
-------
grid : tf.Tensor, s... | 286 | 328 | # -*- coding: utf-8 -*-
"""poc.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1fTzz1aT2sb8oAXRO1-dr6O_IR6dof36e
A simple example for deep-learning-based non-rigid image registration
with the MNIST dataset.
**README:** If the below error occurs,... |
test_step | A generic testing procedure.
Parameters
----------
model
A convolutional encoder-decoder network.
moving : tf.Tensor, shape (N, H, W, C)
A batch of moving images.
static : tf.Tensor, shape (1, H, W, C)
The static image.
criterion
The loss function.
Returns
-------
loss : tf.Tensor, shape ()
The av... | # -*- coding: utf-8 -*-
"""poc.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1fTzz1aT2sb8oAXRO1-dr6O_IR6dof36e
A simple example for deep-learning-based non-rigid image registration
with the MNIST dataset.
**README:** If the below error occurs,... | @tf.function
def test_step(model, moving, static, criterion):
"""A generic testing procedure.
Parameters
----------
model
A convolutional encoder-decoder network.
moving : tf.Tensor, shape (N, H, W, C)
A batch of moving images.
static : tf.Tensor, shape (1, H, W, C)
The ... | 383 | 423 | # -*- coding: utf-8 -*-
"""poc.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1fTzz1aT2sb8oAXRO1-dr6O_IR6dof36e
A simple example for deep-learning-based non-rigid image registration
with the MNIST dataset.
**README:** If the below error occurs,... |
create_process_chain_entry | Create a Actinia process description that uses t.rast.series to create the minimum
value of the time series.
:param input_time_series: The input time series name
:param output_map: The name of the output map
:return: A Actinia process chain description | # -*- coding: utf-8 -*-
from random import randint
import json
from .base import analyse_process_graph, PROCESS_DICT, PROCESS_DESCRIPTION_DICT
from openeo_grass_gis_driver.process_schemas import Parameter, ProcessDescription, ReturnValue
from .actinia_interface import ActiniaInterface
__license__ = "Apache License, Ve... | def create_process_chain_entry(input_name):
"""Create a Actinia process description that uses t.rast.series to create the minimum
value of the time series.
:param input_time_series: The input time series name
:param output_map: The name of the output map
:return: A Actinia process chain description... | 73 | 109 | # -*- coding: utf-8 -*-
from random import randint
import json
from .base import analyse_process_graph, PROCESS_DICT, PROCESS_DESCRIPTION_DICT
from openeo_grass_gis_driver.process_schemas import Parameter, ProcessDescription, ReturnValue
from .actinia_interface import ActiniaInterface
__license__ = "Apache License, Ve... |
__init__ | Create a FeatureImportanceSummarySaver Hook.
This hook creates scalar summaries representing feature importance
for each feature column during training.
Args:
model_dir: model base output directory.
every_n_steps: frequency, in number of steps, for logging summaries.
Raises:
ValueError: If one of the arguments... | # Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | def __init__(self, model_dir, every_n_steps=1):
"""Create a FeatureImportanceSummarySaver Hook.
This hook creates scalar summaries representing feature importance
for each feature column during training.
Args:
model_dir: model base output directory.
every_n_steps: frequency, in number of... | 35 | 52 | # Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... |
with_parent | Add filtering criterion that relates the given instance
to a child object or collection, using its attribute state
as well as an established :func:`.relationship()`
configuration.
The method uses the :func:`.with_parent` function to generate
the clause, the result of which is passed to :meth:`.Query.filter`.
Paramete... | # orm/query.py
# Copyright (C) 2005-2014 the SQLAlchemy authors and contributors
# <see AUTHORS file>
#
# This module is part of SQLAlchemy and is released under
# the MIT License: http://www.opensource.org/licenses/mit-license.php
"""The Query class and support.
Defines the :class:`.Query` class, the central
constru... | def with_parent(self, instance, property=None):
"""Add filtering criterion that relates the given instance
to a child object or collection, using its attribute state
as well as an established :func:`.relationship()`
configuration.
The method uses the :func:`.with_parent` fun... | 924 | 956 | # orm/query.py
# Copyright (C) 2005-2014 the SQLAlchemy authors and contributors
# <see AUTHORS file>
#
# This module is part of SQLAlchemy and is released under
# the MIT License: http://www.opensource.org/licenses/mit-license.php
"""The Query class and support.
Defines the :class:`.Query` class, the central
constru... |
params | add values for bind parameters which may have been
specified in filter().
parameters may be specified using \**kwargs, or optionally a single
dictionary as the first positional argument. The reason for both is
that \**kwargs is convenient, however some parameter dictionaries
contain unicode keys in which case \**kwarg... | # orm/query.py
# Copyright (C) 2005-2014 the SQLAlchemy authors and contributors
# <see AUTHORS file>
#
# This module is part of SQLAlchemy and is released under
# the MIT License: http://www.opensource.org/licenses/mit-license.php
"""The Query class and support.
Defines the :class:`.Query` class, the central
constru... | @_generative()
def params(self, *args, **kwargs):
"""add values for bind parameters which may have been
specified in filter().
parameters may be specified using \**kwargs, or optionally a single
dictionary as the first positional argument. The reason for both is
that \**... | 1,260 | 1,278 | # orm/query.py
# Copyright (C) 2005-2014 the SQLAlchemy authors and contributors
# <see AUTHORS file>
#
# This module is part of SQLAlchemy and is released under
# the MIT License: http://www.opensource.org/licenses/mit-license.php
"""The Query class and support.
Defines the :class:`.Query` class, the central
constru... |
__init__ | Construct a new :class:`.Bundle`.
e.g.::
bn = Bundle("mybundle", MyClass.x, MyClass.y)
for row in session.query(bn).filter(
bn.c.x == 5).filter(bn.c.y == 4):
print(row.mybundle.x, row.mybundle.y)
:param name: name of the bundle.
:param \*exprs: columns or SQL expressions comprising the b... | # orm/query.py
# Copyright (C) 2005-2014 the SQLAlchemy authors and contributors
# <see AUTHORS file>
#
# This module is part of SQLAlchemy and is released under
# the MIT License: http://www.opensource.org/licenses/mit-license.php
"""The Query class and support.
Defines the :class:`.Query` class, the central
constru... | def __init__(self, name, *exprs, **kw):
"""Construct a new :class:`.Bundle`.
e.g.::
bn = Bundle("mybundle", MyClass.x, MyClass.y)
for row in session.query(bn).filter(
bn.c.x == 5).filter(bn.c.y == 4):
print(row.mybundle.x, row.mybundle.y... | 3,299 | 3,322 | # orm/query.py
# Copyright (C) 2005-2014 the SQLAlchemy authors and contributors
# <see AUTHORS file>
#
# This module is part of SQLAlchemy and is released under
# the MIT License: http://www.opensource.org/licenses/mit-license.php
"""The Query class and support.
Defines the :class:`.Query` class, the central
constru... |
create_row_processor | Produce the "row processing" function for this :class:`.Bundle`.
May be overridden by subclasses.
.. seealso::
:ref:`bundles` - includes an example of subclassing. | # orm/query.py
# Copyright (C) 2005-2014 the SQLAlchemy authors and contributors
# <see AUTHORS file>
#
# This module is part of SQLAlchemy and is released under
# the MIT License: http://www.opensource.org/licenses/mit-license.php
"""The Query class and support.
Defines the :class:`.Query` class, the central
constru... | def create_row_processor(self, query, procs, labels):
"""Produce the "row processing" function for this :class:`.Bundle`.
May be overridden by subclasses.
.. seealso::
:ref:`bundles` - includes an example of subclassing.
"""
keyed_tuple = util.lightweight_name... | 3,371 | 3,385 | # orm/query.py
# Copyright (C) 2005-2014 the SQLAlchemy authors and contributors
# <see AUTHORS file>
#
# This module is part of SQLAlchemy and is released under
# the MIT License: http://www.opensource.org/licenses/mit-license.php
"""The Query class and support.
Defines the :class:`.Query` class, the central
constru... |
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