file_name large_stringlengths 4 140 | prefix large_stringlengths 0 39k | suffix large_stringlengths 0 36.1k | middle large_stringlengths 0 29.4k | fim_type large_stringclasses 4
values |
|---|---|---|---|---|
utpgo.go | // Copyright (c) 2021 Storj Labs, Inc.
// Copyright (c) 2010 BitTorrent, Inc.
// See LICENSE for copying information.
package utp
import (
"context"
"crypto/tls"
"errors"
"fmt"
"io"
"net"
"os"
"runtime/pprof"
"sync"
"syscall"
"time"
"github.com/go-logr/logr"
"storj.io/utp-go/buffers"
"storj.io/utp-go/... | a []byte, destAddr *net.UDPAddr) {
sm.baseConnLock.Lock()
defer sm.baseConnLock.Unlock()
sm.mx.IsIncomingUTP(gotIncomingConnectionCallback, packetSendCallback, sm, data, destAddr)
}
func (sm *socketManager) checkTimeouts() {
sm.baseConnLock.Lock()
defer sm.baseConnLock.Unlock()
sm.mx.CheckTimeouts()
}
func (sm ... | essIncomingPacket(dat | identifier_name |
utpgo.go | // Copyright (c) 2021 Storj Labs, Inc.
// Copyright (c) 2010 BitTorrent, Inc.
// See LICENSE for copying information.
package utp
import (
"context"
"crypto/tls"
"errors"
"fmt"
"io"
"net"
"os"
"runtime/pprof"
"sync"
"syscall"
"time"
"github.com/go-logr/logr"
"storj.io/utp-go/buffers"
"storj.io/utp-go/... | func (u *utpSocket) LocalAddr() net.Addr {
return (*Addr)(u.localAddr)
}
type socketManager struct {
mx *libutp.SocketMultiplexer
logger logr.Logger
udpSocket *net.UDPConn
// this lock should be held when invoking any libutp functions or methods
// that are not thread-safe or which themselves might in... | close(c.connectChan)
}
}
| random_line_split |
utpgo.go | // Copyright (c) 2021 Storj Labs, Inc.
// Copyright (c) 2010 BitTorrent, Inc.
// See LICENSE for copying information.
package utp
import (
"context"
"crypto/tls"
"errors"
"fmt"
"io"
"net"
"os"
"runtime/pprof"
"sync"
"syscall"
"time"
"github.com/go-logr/logr"
"storj.io/utp-go/buffers"
"storj.io/utp-go/... | func (c *Conn) WriteContext(ctx context.Context, buf []byte) (n int, err error) {
c.stateLock.Lock()
if c.writePending {
c.stateLock.Unlock()
return 0, buffers.WriterAlreadyWaitingErr
}
c.writePending = true
deadline := c.writeDeadline
c.stateLock.Unlock()
if err != nil {
if err == io.EOF {
// remote s... | return c.WriteContext(context.Background(), buf)
}
| identifier_body |
chain_spec.rs | // Copyright 2018-2019 Parity Technologies (UK) Ltd.
// This file is part of Substrate.
// Substrate is free software: you can redistribute it and/or modify
// it under the terms of the GNU General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
// (at your option) a... |
/// IceFrog testnet config generator
pub fn gen_icefrog_testnet_config() -> ChainSpec {
fn icefrog_config_genesis() -> GenesisConfig {
darwinia_genesis(
vec![
(
hex!["be3fd892bf0e2b33dbfcf298c99a9f71e631a57af6c017dc5ac078c5d5b3494b"].into(), //stash
hex!["70bf51d123581d6e51af70b342cac75ae0a0fc71d1... | {
fn icefrog_config_genesis() -> GenesisConfig {
darwinia_genesis(
vec![
get_authority_keys_from_seed("Alice"),
get_authority_keys_from_seed("Bob"),
],
hex!["a60837b2782f7ffd23e95cd26d1aa8d493b8badc6636234ccd44db03c41fcc6c"].into(), // 5FpQFHfKd1xQ9HLZLQoG1JAQSCJoUEVBELnKsKNcuRLZejJR
vec![
he... | identifier_body |
chain_spec.rs | // Copyright 2018-2019 Parity Technologies (UK) Ltd.
// This file is part of Substrate.
// Substrate is free software: you can redistribute it and/or modify
// it under the terms of the GNU General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
// (at your option) a... | ;
const RING_ENDOWMENT: Balance = 20_000_000 * COIN;
const KTON_ENDOWMENT: Balance = 10 * COIN;
const STASH: Balance = 1000 * COIN;
GenesisConfig {
frame_system: Some(SystemConfig {
code: WASM_BINARY.to_vec(),
changes_trie_config: Default::default(),
}),
pallet_indices: Some(IndicesConfig {
ids: en... | {
vec![initial_authorities[0].clone().1, initial_authorities[1].clone().1]
} | conditional_block |
chain_spec.rs | // Copyright 2018-2019 Parity Technologies (UK) Ltd.
// This file is part of Substrate.
// Substrate is free software: you can redistribute it and/or modify
// it under the terms of the GNU General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
// (at your option) a... | stakers: initial_authorities
.iter()
.map(|x| (x.0.clone(), x.1.clone(), STASH, StakerStatus::Validator))
.collect(),
invulnerables: initial_authorities.iter().map(|x| x.0.clone()).collect(),
slash_reward_fraction: Perbill::from_percent(10),
..Default::default()
}),
}
}
/// Staging testnet c... | pallet_staking: Some(StakingConfig {
current_era: 0,
validator_count: initial_authorities.len() as u32 * 2,
minimum_validator_count: initial_authorities.len() as u32, | random_line_split |
chain_spec.rs | // Copyright 2018-2019 Parity Technologies (UK) Ltd.
// This file is part of Substrate.
// Substrate is free software: you can redistribute it and/or modify
// it under the terms of the GNU General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
// (at your option) a... | () -> GenesisConfig {
darwinia_genesis(
vec![
get_authority_keys_from_seed("Alice"),
get_authority_keys_from_seed("Bob"),
],
hex!["a60837b2782f7ffd23e95cd26d1aa8d493b8badc6636234ccd44db03c41fcc6c"].into(), // 5FpQFHfKd1xQ9HLZLQoG1JAQSCJoUEVBELnKsKNcuRLZejJR
vec![
hex!["a60837b2782f7ffd23e95cd2... | icefrog_config_genesis | identifier_name |
mnist_benchmark.py | # Copyright 2017 PerfKitBenchmarker Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... |
return samples
def MakeSamplesFromEvalOutput(metadata, output, elapsed_seconds):
"""Create a sample containing evaluation metrics.
Args:
metadata: dict contains all the metadata that reports.
output: string, command output
elapsed_seconds: float, elapsed seconds from saved checkpoint.
Example o... | global_step_sec = get_mean(regex_util.ExtractAllMatches(
r'global_step/sec: (\S+)', output))
samples.append(sample.Sample(
'Global Steps Per Second', global_step_sec,
'global_steps/sec', metadata_copy))
examples_sec = global_step_sec * metadata['train_batch_size']
if 'examples/sec: '... | conditional_block |
mnist_benchmark.py | # Copyright 2017 PerfKitBenchmarker Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | metadata_with_index = copy.deepcopy(metadata)
metadata_with_index['index'] = index
samples.append(sample.Sample(metric, float(value), unit,
metadata_with_index))
return samples
def MakeSamplesFromTrainOutput(metadata, output, elapsed_seconds, step):
"""Create a sample ... | """
matches = regex_util.ExtractAllMatches(regex, output)
samples = []
for index, value in enumerate(matches): | random_line_split |
mnist_benchmark.py | # Copyright 2017 PerfKitBenchmarker Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | (benchmark_spec):
"""Update the benchmark_spec with supplied command line flags.
Args:
benchmark_spec: benchmark specification to update
"""
benchmark_spec.data_dir = FLAGS.mnist_data_dir
benchmark_spec.iterations = FLAGS.tpu_iterations
benchmark_spec.gcp_service_account = FLAGS.gcp_service_account
b... | _UpdateBenchmarkSpecWithFlags | identifier_name |
mnist_benchmark.py | # Copyright 2017 PerfKitBenchmarker Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... |
def Run(benchmark_spec):
"""Run MNIST on the cluster.
Args:
benchmark_spec: The benchmark specification. Contains all data that is
required to run the benchmark.
Returns:
A list of sample.Sample objects.
"""
_UpdateBenchmarkSpecWithFlags(benchmark_spec)
vm = benchmark_spec.vms[0]
if ... | """Create a sample containing evaluation metrics.
Args:
metadata: dict contains all the metadata that reports.
output: string, command output
elapsed_seconds: float, elapsed seconds from saved checkpoint.
Example output:
perfkitbenchmarker/tests/linux_benchmarks/mnist_benchmark_test.py
Returns:... | identifier_body |
ext.rs | //! Safe wrapper around externalities invokes.
use wasm_std::{
self,
types::{H256, U256, Address}
};
/// Generic wasm error
#[derive(Debug)]
pub struct Error;
mod external {
extern "C" {
// Various call variants
/// Direct/classic call.
/// Corresponds to "CALL" opcode in EVM
... | /// Get the block's timestamp
///
/// It can be viewed as an output of Unix's `time()` function at
/// current block's inception.
pub fn timestamp() -> u64 {
unsafe { external::timestamp() as u64 }
}
/// Get the block's number
///
/// This value represents number of ancestor blocks.
/// The genesis block has a num... | unsafe { fetch_address(|x| external::coinbase(x) ) }
}
| identifier_body |
ext.rs | //! Safe wrapper around externalities invokes.
use wasm_std::{
self,
types::{H256, U256, Address}
};
/// Generic wasm error
#[derive(Debug)]
pub struct Error;
mod external {
extern "C" {
// Various call variants
/// Direct/classic call.
/// Corresponds to "CALL" opcode in EVM
... | else {
Err(Error)
}
}
}
/// Returns hash of the given block or H256::zero()
///
/// Only works for 256 most recent blocks excluding current
/// Returns H256::zero() in case of failure
pub fn block_hash(block_number: u64) -> H256 {
let mut res = H256::zero();
unsafe {
external::... | {
Ok(())
} | conditional_block |
ext.rs | //! Safe wrapper around externalities invokes.
use wasm_std::{
self,
types::{H256, U256, Address}
};
/// Generic wasm error
#[derive(Debug)]
pub struct Error;
mod external {
extern "C" {
// Various call variants
/// Direct/classic call.
/// Corresponds to "CALL" opcode in EVM
... | if external::create(
endowment_arr.as_ptr(),
code.as_ptr(),
code.len() as u32,
(&mut result).as_mut_ptr()
) == 0 {
Ok(result)
} else {
Err(Error)
}
}
}
#[cfg(feature = "kip4")]
/// Create a new account with the ... | random_line_split | |
ext.rs | //! Safe wrapper around externalities invokes.
use wasm_std::{
self,
types::{H256, U256, Address}
};
/// Generic wasm error
#[derive(Debug)]
pub struct Error;
mod external {
extern "C" {
// Various call variants
/// Direct/classic call.
/// Corresponds to "CALL" opcode in EVM
... | -> u64 {
unsafe { external::blocknumber() as u64 }
}
/// Get the block's difficulty.
pub fn difficulty() -> U256 {
unsafe { fetch_u256(|x| external::difficulty(x) ) }
}
/// Get the block's gas limit.
pub fn gas_limit() -> U256 {
unsafe { fetch_u256(|x| external::gaslimit(x) ) }
}
#[cfg(feature = "kip6")... | ock_number() | identifier_name |
networking.py | from __future__ import division
import struct
from cStringIO import StringIO
#import pyraknet
#from pyraknet import PacketTypes, PacketReliability, PacketPriority
import socket, traceback, os, sys, threading
from Queue import Queue
from unit import Unit
from buildings.igloo import Igloo
from player import Player
im... | (self):
w = Writer()
w.single("H", self.dmo_id)
w.string(self.image_name)
w.single("HH", *self.position)
w.single("B", (self.hidden << 0) + (self.obstruction << 1))
w.string(self.minimapimage)
return w.data.getvalue()
@classmethod
def from_stream(cls, stre... | pack | identifier_name |
networking.py | from __future__ import division
import struct
from cStringIO import StringIO
#import pyraknet
#from pyraknet import PacketTypes, PacketReliability, PacketPriority
import socket, traceback, os, sys, threading
from Queue import Queue
from unit import Unit
from buildings.igloo import Igloo
from player import Player
im... | type_id = 116
# TODO
class MResourceQuantity(Message):
type_id = 117
struct_format = "!hhh"
attrs = ("tx", "ty", "q")
# Player/connection stuff
class MNewPlayer(Message):
type_id = 120
attrs = ("player_id", "name", "color", "loading")
def pack(self):
w = Writer()
w.s... | type_id = 115
struct_format = "!HB"
attrs = ("dmo_id", "hidden")
class MDMOPosition(Message): | random_line_split |
networking.py | from __future__ import division
import struct
from cStringIO import StringIO
#import pyraknet
#from pyraknet import PacketTypes, PacketReliability, PacketPriority
import socket, traceback, os, sys, threading
from Queue import Queue
from unit import Unit
from buildings.igloo import Igloo
from player import Player
im... |
self.data.write(struct.pack(format, *values))
def multi(self, format, values):
self.single("!H", len(values))
if len(format.strip("@=<>!")) > 1:
for v in values:
self.single(format, *v)
else:
for v in values:
self.single(forma... | format = "!"+format | conditional_block |
networking.py | from __future__ import division
import struct
from cStringIO import StringIO
#import pyraknet
#from pyraknet import PacketTypes, PacketReliability, PacketPriority
import socket, traceback, os, sys, threading
from Queue import Queue
from unit import Unit
from buildings.igloo import Igloo
from player import Player
im... |
def values(self):
l = []
for a in self.attrs:
l.append(getattr(self, a))
return l
@classmethod
def from_stream(cls, stream):
res = struct.unpack(cls.struct_format,
stream.read(struct.calcsize(cls.struct_format)))
return cls(*res)
de... | attrs = list(self.attrs)
for arg in pargs:
n = attrs.pop(0)
setattr(self, n, arg)
for n in attrs:
setattr(self, n, kwargs.pop(n))
if kwargs:
raise TypeError("unexpected keyword argument '%s'" %
kwargs.keys()[0]) | identifier_body |
async_await_basics.rs | use futures::executor::block_on;
use std::thread::Thread;
use std::sync::mpsc;
use futures::join;
use {
std::{
pin::Pin,
task::Waker,
thread,
},
};
use {
futures::{
future::{FutureExt, BoxFuture},
task::{ArcWake, waker_ref},
},
std::{
future::Future,
... | {
shared_state: Arc<Mutex<SharedState>>,
}
/// Shared state between the future and the waiting thread
struct SharedState {
/// Whether or not the sleep time has elapsed
completed: bool,
/// The waker for the task that `TimerFuture` is running on.
/// The thread can use this after setting `complet... | TimerFuture | identifier_name |
async_await_basics.rs | use futures::executor::block_on;
use std::thread::Thread;
use std::sync::mpsc;
use futures::join;
use {
std::{
pin::Pin,
task::Waker,
thread,
},
};
use {
futures::{
future::{FutureExt, BoxFuture},
task::{ArcWake, waker_ref},
},
std::{
future::Future,
... | // function, but we omit that here to keep things simple.
shared_state.waker = Some(cx.waker().clone());
Poll::Pending
}
}
}
impl TimerFuture {
/// Create a new `TimerFuture` which will complete after the provided
/// timeout.
pub fn new(duration: Duration) -... | //
// N.B. it's possible to check for this using the `Waker::will_wake` | random_line_split |
async_await_basics.rs | use futures::executor::block_on;
use std::thread::Thread;
use std::sync::mpsc;
use futures::join;
use {
std::{
pin::Pin,
task::Waker,
thread,
},
};
use {
futures::{
future::{FutureExt, BoxFuture},
task::{ArcWake, waker_ref},
},
std::{
future::Future,
... |
async fn learn_and_sing() {
let song = learn_song().await;
sing_song(song).await;
}
async fn async_main() {
let f2 = dance();
let f1 = learn_and_sing();
futures::join!(f2, f1);
}
// Each time a future is polled, it is polled as part of a "task". Tasks are the top-level futures
// that have been... | {
println!("Dance!!")
} | identifier_body |
async_await_basics.rs | use futures::executor::block_on;
use std::thread::Thread;
use std::sync::mpsc;
use futures::join;
use {
std::{
pin::Pin,
task::Waker,
thread,
},
};
use {
futures::{
future::{FutureExt, BoxFuture},
task::{ArcWake, waker_ref},
},
std::{
future::Future,
... |
}
}
}
}
// In practice, this problem is solved through integration with an IO-aware system blocking primitive,
// such as epoll on Linux, kqueue on FreeBSD and Mac OS, IOCP on Windows, and ports on Fuchsia (all
// of which are exposed through the cross-platform Rust crate mio). These primitive... | {
// We're not done processing the future, so put it
// back in its task to be run again in the future.
*future_slot = Some(future);
} | conditional_block |
controller.py | """
Venter på innkommende meldinger som enten gir oppgaver å jobbe med, eller etterspør et rom å søke gjennom
Tar inn "Kode" som skal knekkes, samt rom det skal søkes i, (muligens størrelse på hver enkelt arbeidoppgave?) og eventuell hashing-algoritme.
Fordeler arbeidoppgaver ved å motta en forespørsel, og sende... | int, end_point, keyword, chars, searchwidth, algorithm, id):
self.start_point = start_point # Where to start searching
self.end_point = end_point # Where to end the search
self.keyword = keyword # What you're searching for
self.chars = chars # Characters t... | start_po | identifier_name |
controller.py | """
Venter på innkommende meldinger som enten gir oppgaver å jobbe med, eller etterspør et rom å søke gjennom
Tar inn "Kode" som skal knekkes, samt rom det skal søkes i, (muligens størrelse på hver enkelt arbeidoppgave?) og eventuell hashing-algoritme.
Fordeler arbeidoppgaver ved å motta en forespørsel, og sende... | conditional_block | ||
controller.py | """
Venter på innkommende meldinger som enten gir oppgaver å jobbe med, eller etterspør et rom å søke gjennom
Tar inn "Kode" som skal knekkes, samt rom det skal søkes i, (muligens størrelse på hver enkelt arbeidoppgave?) og eventuell hashing-algoritme.
Fordeler arbeidoppgaver ved å motta en forespørsel, og sende... | k_id(tasks):
task_id_unique = False
temp_id = floor(random()*10000)
while not task_id_unique:
task_id_unique = True
temp_id = floor(random()*10000)
for task in tasks:
if task.id == temp_id:
task_id_unique = False
return temp_id
class Task:
... | ps(get_next_job())
def gen_tas | identifier_body |
controller.py | """
Venter på innkommende meldinger som enten gir oppgaver å jobbe med, eller etterspør et rom å søke gjennom
Tar inn "Kode" som skal knekkes, samt rom det skal søkes i, (muligens størrelse på hver enkelt arbeidoppgave?) og eventuell hashing-algoritme.
Fordeler arbeidoppgaver ved å motta en forespørsel, og sende... |
self.current_point = self.start_point # Will be increased as workers are given blocks to search through
self.finished = False
self.keyword_found = ""
def get_task(self):
return {
'id':self.id,
'finished':self.finished,
'algorithm':self.a... | random_line_split | |
main.rs | //! # Basic Subclass example
//!
//! This file creates a `GtkApplication` and a `GtkApplicationWindow` subclass
//! and showcases how you can override virtual funcitons such as `startup`
//! and `activate` and how to interact with the GObjects and their private
//! structs.
extern crate gstreamer as gst;
extern crate ... |
}
use std::time::Duration;
use std::io::Seek;
use std::io::SeekFrom;
fn main() {
gtk::init().expect("Failed to initialize gtk");
let app = SimpleApplication::new();
let args: Vec<String> = std::env::args().collect();
app.run(&args);
} | {
glib::Object::new(
Self::static_type(),
&[
("application-id", &"org.gtk-rs.SimpleApplication"),
("flags", &ApplicationFlags::empty()),
],
)
.expect("Failed to create SimpleApp")
.downcast()
.expect("Created sim... | identifier_body |
main.rs | //! # Basic Subclass example
//!
//! This file creates a `GtkApplication` and a `GtkApplicationWindow` subclass
//! and showcases how you can override virtual funcitons such as `startup`
//! and `activate` and how to interact with the GObjects and their private
//! structs.
extern crate gstreamer as gst;
extern crate ... | audio_player_clone.pause_music();
});
// Connect our method `on_increment_clicked` to be called
// when the increment button is clicked.
increment.connect_clicked(clone!(@weak self_ => move |_| {
let priv_ = SimpleWindowPrivate::from_instance(&self_);
... | pause_button.connect_clicked(move |_| { | random_line_split |
main.rs | //! # Basic Subclass example
//!
//! This file creates a `GtkApplication` and a `GtkApplicationWindow` subclass
//! and showcases how you can override virtual funcitons such as `startup`
//! and `activate` and how to interact with the GObjects and their private
//! structs.
extern crate gstreamer as gst;
extern crate ... | (&self) {
self.counter.set(self.counter.get() + 1);
let w = self.widgets.get().unwrap();
w.label
.set_text(&format!("Your life has {} meaning", self.counter.get()));
}
fn on_decrement_clicked(&self) {
self.counter.set(self.counter.get().wrapping_sub(1));
let w... | on_increment_clicked | identifier_name |
configfunction.js | //验证数据有效性
function validationData(types,data){
//if(types=="1"||types=="整型"){
if(types=="1"||types=="\u6574\u578B"){
var re=/^-?[0-9]\d*$/;
if(!data.match(re)){
//return "类型为整型的数据值必须是整数。<br>";
return "\u7C7B\u578B\u4E3A\u6574\u578B\u7684\u6570\u636E\u503C\u5FC5\u987B\u662F\u6574\u6570\u3002<br>";
}
//}el... | obj.className = "input_mouseout";
} | eBorder(obj){
| identifier_name |
configfunction.js | //验证数据有效性
function validationData(types,data){
//if(types=="1"||types=="整型"){
if(types=="1"||types=="\u6574\u578B"){
var re=/^-?[0-9]\d*$/;
if(!data.match(re)){
//return "类型为整型的数据值必须是整数。<br>";
return "\u7C7B\u578B\u4E3A\u6574\u578B\u7684\u6570\u636E\u503C\u5FC5\u987B\u662F\u6574\u6570\u3002<br>";
}
//}el... | var tempValues = td.getElementsByTagName("INPUT")[0].value;
if(trimSpace(tempValues)!=""){
//校验数据值是否含有不允许的特殊字符
var validateDataRegexInfo = validateDataRegex(trimSpace(tempValues));
if(validateDataRegexInfo){
msg += "\u6570\u636E\u503C\u533A\u57DF\u7B2C"+i+"\u884C\u002C\u7B2C"+(j+1)+"\u5217"... | if(td){ | random_line_split |
configfunction.js | //验证数据有效性
function validationData(types,data){
//if(types=="1"||types=="整型"){
if(types=="1"||types=="\u6574\u578B"){
var re=/^-?[0-9]\d*$/;
if(!data.match(re)){
//return "类型为整型的数据值必须是整数。<br>";
return "\u7C7B\u578B\u4E3A\u6574\u578B\u7684\u6570\u636E\u503C\u5FC5\u987B\u662F\u6574\u6570\u3002<br>";
}
//}el... | 40D\u79F0\u4E0D\u80FD\u4E3A\u7A7A<br>";
}
if(trimSpace(attrCode).length==0){
//msg+="属性编码不能为空<br>";
msg+="\u5C5E\u6027\u7F16\u7801\u4E0D\u80FD\u4E3A\u7A7A<br>";
}else{
msg += isRepeat(attrCode,temp);
}
if(msg.length>0){
cui.alert(msg);
return;
}
//var info = "名称:"+trimSpace(attrName)+",编码:"+trimSpace(a... | eDataRegexInfo;
}
flag = false;
//只有值不为空时才进行验证
//验证输入的值是否合法
var attributeType = trimSpace(jsonHead[j-1].attributeType);
var vInfo = validationData(attributeType,trimSpace(tempValues));
if(vInfo!=""){
//msg += "数据值区域第"+i+"行,第"+(j+1)+"列"+vInfo;
msg += "\u6570\u636E\u503C\u53... | conditional_block |
configfunction.js | //验证数据有效性
function validationData(types,data){
//if(types=="1"||types=="整型"){
if(types=="1"||types=="\u6574\u578B"){
var re=/^-?[0-9]\d*$/;
if(!data.match(re)){
//return "类型为整型的数据值必须是整数。<br>";
return "\u7C7B\u578B\u4E3A\u6574\u578B\u7684\u6570\u636E\u503C\u5FC5\u987B\u662F\u6574\u6570\u3002<br>";
}
//}el... | identifier_body | ||
lstm.py |
import pandas as pd
from sklearn import model_selection, preprocessing, linear_model, metrics
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.feature_extraction.text import TfidfTransformer
from sklearn.metrics import classification_report, confusion_matrix, accuracy_score
import seaborn as sn... | (self, x, hidden):
"""
Perform a forward pass of our model on some input and hidden state.
"""
batch_size = x.size(0)
# embeddings and lstm_out
embeds = self.embedding(x)
lstm_out, hidden = self.lstm(embeds, hidden)
# stack up lstm outputs
... | forward | identifier_name |
lstm.py |
import pandas as pd
from sklearn import model_selection, preprocessing, linear_model, metrics
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.feature_extraction.text import TfidfTransformer
from sklearn.metrics import classification_report, confusion_matrix, accuracy_score
import seaborn as sn... |
# Get test data loss and accuracy
# = [] # track loss
num_correct = 0
# init hidden state
h = net.init_hidden(batch_size, train_on_gpu)
counter=0
net.eval()
all_prediction = []
# iterate over test data
for inputs, labels in test_loader:
counter += 1
print('epoce: {e}, batch: {b}'.format(e=e, b=counter)... | h = net.init_hidden(batch_size, train_on_gpu)
counter = 0
# batch loop
for inputs, labels in train_loader:
counter += 1
#print('epoce: {e}, batch: {b}'.format(e=e, b=counter))
if (labels.shape[0] != batch_size):
continue
inputs = inputs.type(torch.LongTensor)
... | conditional_block |
lstm.py |
import pandas as pd
from sklearn import model_selection, preprocessing, linear_model, metrics
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.feature_extraction.text import TfidfTransformer
from sklearn.metrics import classification_report, confusion_matrix, accuracy_score
import seaborn as sn... |
def forward(self, x, hidden):
"""
Perform a forward pass of our model on some input and hidden state.
"""
batch_size = x.size(0)
# embeddings and lstm_out
embeds = self.embedding(x)
lstm_out, hidden = self.lstm(embeds, hidden)
# stack up lst... | """
Initialize the model by setting up the layers.
"""
super(SentimentRNN, self).__init__()
self.output_size = output_size
self.n_layers = n_layers
self.hidden_dim = hidden_dim
# embedding and LSTM layers
self.embedding = nn.Embedding(vocab_size,... | identifier_body |
lstm.py | import pandas as pd
from sklearn import model_selection, preprocessing, linear_model, metrics
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.feature_extraction.text import TfidfTransformer
from sklearn.metrics import classification_report, confusion_matrix, accuracy_score
import seaborn as sns... | print(type(text))
label=[]
for item in stars:
if item>= 4:
y=1
else:
y=0
label.append(y)
label=np.array(label)
#we can get punctuation from string library
from string import punctuation
print(punctuation)
all_reviews=[]
for item in text:
item = item.lower()
item = "".join([ch for ch in... | text=list(df_filtered['text'])
stars=list(df_filtered['stars'])
| random_line_split |
Master Solution.py | #!/usr/bin/env python
# coding: utf-8
# # Background
#
# - 1 The adjacent 3 tabs contain a data dump of search strings used by EXP clients to access relevant content available on Gartner.com for the months of August, September and October in the year 2018. Every row mentions if the EXP client is "P... | (data):
#convert text to lower-case
data['processed_text'] = data['Query Text'].apply(lambda x:' '.join(x.lower() for x in x.split()))
#remove punctuations, unwanted characters
data['processed_text_1']= data['processed_text'].apply(lambda x: "".join([char for char in x if char not in string.punctu... | text_preprocessing | identifier_name |
Master Solution.py | #!/usr/bin/env python
# coding: utf-8
# # Background
#
# - 1 The adjacent 3 tabs contain a data dump of search strings used by EXP clients to access relevant content available on Gartner.com for the months of August, September and October in the year 2018. Every row mentions if the EXP client is "P... |
# In[9]:
df.isnull().sum()
# In[10]:
df.drop_duplicates(subset ="Query Text",
keep = 'last', inplace = True)
# In[11]:
df.info()
# In[12]:
# check the length of documents
document_lengths = np.array(list(map(len, df['Query Text'].str.split(' '))))
print("The average number of wor... | random_line_split | |
Master Solution.py | #!/usr/bin/env python
# coding: utf-8
# # Background
#
# - 1 The adjacent 3 tabs contain a data dump of search strings used by EXP clients to access relevant content available on Gartner.com for the months of August, September and October in the year 2018. Every row mentions if the EXP client is "P... |
# In[15]:
#pre-processing or cleaning data
text_preprocessing(df)
df.head()
# In[16]:
#create tokenized data for LDA
df['final_tokenized'] = list(map(nltk.word_tokenize, df.final_text))
df.head()
# ## LDA training
# In[17]:
# Create Dictionary
id2word = corpora.Dictionary(df['final_tokenized'])
tex... | data['processed_text'] = data['Query Text'].apply(lambda x:' '.join(x.lower() for x in x.split()))
#remove punctuations, unwanted characters
data['processed_text_1']= data['processed_text'].apply(lambda x: "".join([char for char in x if char not in string.punctuation]))
#remove numbers
data['processed... | identifier_body |
Master Solution.py | #!/usr/bin/env python
# coding: utf-8
# # Background
#
# - 1 The adjacent 3 tabs contain a data dump of search strings used by EXP clients to access relevant content available on Gartner.com for the months of August, September and October in the year 2018. Every row mentions if the EXP client is "P... | nique labels for entities : ", Counter(ent_label))
print("Top 3 frequent tokens : ", Counter(ent_common).most_common(3))
# In[40]:
sentences = []
for i, doc in enumerate(corpus):
for ent in doc.sents:
sentences.append(ent)
print(sentences[0])
# In[41]:
# Most popular ents
import operator
sor... | nt.label_)
ent_common.append(ent.text)
print("U | conditional_block |
helpers.go | package en
import (
"bytes"
"fmt"
"log"
"regexp"
"strconv"
"strings"
"time"
"github.com/golang-collections/collections/stack"
"golang.org/x/net/html"
)
// Tag string type that corresponds to the html tags
type Tag struct {
Tag string
Attrs map[string]string
}
const (
iTag string = "i"
bTag ... | if mrHr := reHr.FindAllStringSubmatch(res, -1); len(mrHr) > 0 {
for _, item := range mrHr {
res = regexp.MustCompile(item[0]).ReplaceAllLiteralString(res, "\n")
}
}
if mrP := reP.FindAllStringSubmatch(res, -1); len(mrP) > 0 {
for _, item := range mrP {
res = regexp.MustCompile(regexp.QuoteMeta(item[0])).
... | for _, item := range mrBr {
res = regexp.MustCompile(item[0]).ReplaceAllLiteralString(res, "\n")
}
}
| conditional_block |
helpers.go | package en
import (
"bytes"
"fmt"
"log"
"regexp"
"strconv"
"strings"
"time"
"github.com/golang-collections/collections/stack"
"golang.org/x/net/html"
)
// Tag string type that corresponds to the html tags
type Tag struct {
Tag string
Attrs map[string]string
}
const (
iTag string = "i"
bTag ... |
// ReplaceCommonTags deprecated - should be removed!!!
func ReplaceCommonTags(text string) string {
log.Print("Replace html tags")
var (
reBr = regexp.MustCompile("<br\\s*/?>")
reHr = regexp.MustCompile("<hr.*?/?>")
reP = regexp.MustCompile("<p>([^ ]+?)</p>")
reBold = regexp.MustCompile("<b.*... | {
var (
parser = html.NewTokenizer(strings.NewReader(text))
tagStack = stack.New()
textToTag = map[int]string{}
)
for {
node := parser.Next()
switch node {
case html.ErrorToken:
result := strings.Replace(textToTag[0], " ", " ", -1)
return result
case html.TextToken:
t := string(parse... | identifier_body |
helpers.go | package en
import (
"bytes"
"fmt"
"log"
"regexp"
"strconv"
"strings"
"time"
"github.com/golang-collections/collections/stack"
"golang.org/x/net/html"
)
// Tag string type that corresponds to the html tags
type Tag struct {
Tag string
Attrs map[string]string
}
const (
iTag string = "i"
bTag ... | reCenter = regexp.MustCompile("<center>((?s:.*?))</center>")
reFont = regexp.MustCompile("<font.+?color\\s*=\\\\?[\"«]?#?(\\w+)\\\\?[\"»]?.*?>((?s:.*?))</font>")
reA = regexp.MustCompile("<a.+?href=\\\\?\"(.+?)\\\\?\".*?>(.+?)</a>")
res = text
)
res = strings.Replace(text, "_", "\\_", -1)
if mrB... | reStrong = regexp.MustCompile("<strong.*?>(.*?)</strong>")
reItalic = regexp.MustCompile("<i>((?s:.+?))</i>")
reSpan = regexp.MustCompile("<span.*?>(.*?)</span>") | random_line_split |
helpers.go | package en
import (
"bytes"
"fmt"
"log"
"regexp"
"strconv"
"strings"
"time"
"github.com/golang-collections/collections/stack"
"golang.org/x/net/html"
)
// Tag string type that corresponds to the html tags
type Tag struct {
Tag string
Attrs map[string]string
}
const (
iTag string = "i"
bTag ... | (text string, re *regexp.Regexp) (string, Coordinates) {
var (
result = text
mr = re.FindAllStringSubmatch(text, -1)
coords = Coordinates{}
)
if len(mr) > 0 {
for _, item := range mr {
lon, _ := strconv.ParseFloat(item[1], 64)
lat, _ := strconv.ParseFloat(item[2], 64)
if len(item) > 3 {
coor... | extractCoordinates | identifier_name |
trainPredictor.py | #!/usr/bin/env python3
from builtins import zip
from builtins import str
from builtins import range
import sys
import os
import json
import pickle
import traceback
import numpy as np
import time
import datetime as dtime
from progressbar import ProgressBar, ETA, Bar, Percentage
from sklearn.base import clone
from skle... |
pathjoin = os.path.join
pathexists = os.path.exists
mdy = dtime.datetime.now().strftime('%m%d%y')
product_type = 'interferogram'
cache_dir = 'cached'
train_folds = np.inf # inf = leave-one-out, otherwise k-fold cross validation
train_state = 42 # random seed
train_verbose = 0
train_jobs = -1
cv_type... | print(process,exitv,message) | identifier_body |
trainPredictor.py | #!/usr/bin/env python3
from builtins import zip
from builtins import str
from builtins import range
import sys
import os
import json
import pickle
import traceback
import numpy as np
import time
import datetime as dtime
from progressbar import ProgressBar, ETA, Bar, Percentage
from sklearn.base import clone
from skle... | (usertags,classmap):
'''
return dictionary of matched (tag,label) pairs in classmap for all tags
returns {} if none of the tags are present in classmap
'''
labelmap = {}
for tag in usertags:
tag = tag.strip()
for k,v in list(classmap.items()):
if tag.count(k):
... | usertags2label | identifier_name |
trainPredictor.py | #!/usr/bin/env python3
from builtins import zip
from builtins import str
from builtins import range
import sys
import os
import json
import pickle
import traceback
import numpy as np
import time
import datetime as dtime
from progressbar import ProgressBar, ETA, Bar, Percentage
from sklearn.base import clone
from skle... |
else:
print("invalid clf_type")
return {}
clf = clone(model_clf)
if model_tuned is not None and len(model_tuned) != 0 and \
len(model_tuned[0]) != 0:
cv = GridSearchCV(clf,model_tuned,cv=gridcv_folds,scoring=gridcv_score,
n_jobs=gridcv_jobs,ver... | model_clf = RandomForestClassifier(**rf_defaults)
model_tuned = [rf_tuned] | conditional_block |
trainPredictor.py | #!/usr/bin/env python3
from builtins import zip
from builtins import str
from builtins import range
import sys
import os
import json
import pickle
import traceback
import numpy as np
import time
import datetime as dtime
from progressbar import ProgressBar, ETA, Bar, Percentage
from sklearn.base import clone
from skle... | return url.replace(product_type,'features').replace('features__','features_'+product_type+'__')
def fdict2vec(featdict,clfinputs):
'''
extract feature vector from dict given classifier parameters
specifying which features to use
'''
fvec = []
try:
featspec = clfinputs['feature... | - feature id for url
""" | random_line_split |
photcalibration.py | #from __future__ import absolute_import, division, print_function, unicode_literals
import matplotlib
from longtermphotzp import photdbinterface
matplotlib.use('Agg')
import matplotlib.pyplot as plt
plt.style.use('ggplot')
import numpy as np
import argparse
import re
import glob
import os
import math
import sys
impo... |
def crawlSiteCameraArchive(site, camera, args, date=None):
'''
Process in the archive
:param site:
:param camera:
:param args:
:param date:
:return:
'''
if date is None:
date = '*'
if site is None:
_logger.error ("Must define a site !")
exit (1)
... | search = "%s/*-[es][19]1.fits.fz" % (directory)
inputlist = glob.glob(search)
initialsize = len (inputlist)
rejects = []
if not args.redo:
for image in inputlist:
if db.exists(image):
rejects.append (image)
for r in rejects:
inputlist.remove (r)... | identifier_body |
photcalibration.py | #from __future__ import absolute_import, division, print_function, unicode_literals
import matplotlib
from longtermphotzp import photdbinterface
matplotlib.use('Agg')
import matplotlib.pyplot as plt
plt.style.use('ggplot')
import numpy as np
import argparse
import re
import glob
import os
import math
import sys
impo... |
select_from_cat = (cat_ra_shifted > min_ra) & (cat_ra_shifted < max_ra) & (cat_dec > min_dec) & (
cat_dec < max_dec)
array_to_add = cat_full[select_from_cat]
_logger.debug("Read %d sources from %s" % (array_to_add.shape[0], catalogname))
if (full_catal... | cat_ra_shifted[cat_ra > 180] -= 360 | conditional_block |
photcalibration.py | #from __future__ import absolute_import, division, print_function, unicode_literals
import matplotlib
from longtermphotzp import photdbinterface
matplotlib.use('Agg')
import matplotlib.pyplot as plt
plt.style.use('ggplot')
import numpy as np
import argparse
import re
import glob
import os
import math
import sys
impo... | :param args:
:param date:
:return:
'''
if date is None:
date = '*'
if site is None:
_logger.error ("Must define a site !")
exit (1)
imagedb = photdbinterface(args.imagedbPrefix)
searchdir = "%s/%s/%s/%s/%s" % (args.rootdir, site, camera, date, args.processstat... |
:param site:
:param camera: | random_line_split |
photcalibration.py | #from __future__ import absolute_import, division, print_function, unicode_literals
import matplotlib
from longtermphotzp import photdbinterface
matplotlib.use('Agg')
import matplotlib.pyplot as plt
plt.style.use('ggplot')
import numpy as np
import argparse
import re
import glob
import os
import math
import sys
impo... | (directory, db, args):
search = "%s/*-[es][19]1.fits.fz" % (directory)
inputlist = glob.glob(search)
initialsize = len (inputlist)
rejects = []
if not args.redo:
for image in inputlist:
if db.exists(image):
rejects.append (image)
for r in rejects:
... | crawlDirectory | identifier_name |
genetic.py | import copy
import random
import time
import sys
# TODO: accept user args for states, give up, etc
# TODO: set up signal handler for Ctrl-C
DEBUG = True
history = [] # a record of states
GIVE_UP = 1000 # give up after x iterations
POOL_SIZE = 10
NUM_VARS = 0
NUM_CLAUSES = 0
CNF = [] #TODO: fix evaluate function
... | flips = 0
while counter < GIVE_UP:
if rand_restarts and counter>0 and not (counter % restart): # random restarts
if not tb: print("restarting: (" + str(new_vals[0]) + "/" + str(NUM_CLAUSES) + ")")
initialize_states(gene_pool, gene_pool[0])
if not tb: print("iteration", ... | restart = int(tries/5) | random_line_split |
genetic.py | import copy
import random
import time
import sys
# TODO: accept user args for states, give up, etc
# TODO: set up signal handler for Ctrl-C
DEBUG = True
history = [] # a record of states
GIVE_UP = 1000 # give up after x iterations
POOL_SIZE = 10
NUM_VARS = 0
NUM_CLAUSES = 0
CNF = [] #TODO: fix evaluate function
... |
# not currently using
def flip_heuristic(safe, new_pool, evaluations):
for i in range(safe, POOL_SIZE):
flipped = flip_bits(new_pool[i])
value = evaluate(flipped)
if value >= evaluations[i]:
evaluations[i] = value
new_pool[i] = flipped
def flip_bits(string):
n... | new_str = string[:index] + ("1" if string[index]=="0" else "0") + string[(index+1):]
new_eval = evaluate(new_str)
if new_eval > evaluation:
return (new_str, new_eval)
return (None, None) | identifier_body |
genetic.py | import copy
import random
import time
import sys
# TODO: accept user args for states, give up, etc
# TODO: set up signal handler for Ctrl-C
DEBUG = True
history = [] # a record of states
GIVE_UP = 1000 # give up after x iterations
POOL_SIZE = 10
NUM_VARS = 0
NUM_CLAUSES = 0
CNF = [] #TODO: fix evaluate function
... |
for i in range(num):
res[i][i] = inf
return res
def calc_dist(a, b):
return ((a[0]-b[0])**2 + (a[1]-b[1])**2)**.5
def closest(a, adj):
return min(adj[a][:])
def find_closest(a, others, adj):
min_dist = 1000
closest = -1
for i in others:
if adj[a][i] < min_dist:
... | for j in range(num):
res[i][j] = calc_dist(cities[i][1], cities[j][1])
res[j][i] = res[i][j] | conditional_block |
genetic.py | import copy
import random
import time
import sys
# TODO: accept user args for states, give up, etc
# TODO: set up signal handler for Ctrl-C
DEBUG = True
history = [] # a record of states
GIVE_UP = 1000 # give up after x iterations
POOL_SIZE = 10
NUM_VARS = 0
NUM_CLAUSES = 0
CNF = [] #TODO: fix evaluate function
... | (safe, new_pool):
for i in range(safe, POOL_SIZE):
if flip_coin(.9):
mutant = ""
for j in range(len(new_pool[i])):
if flip_coin():
mutant += str(1 - int(new_pool[i][j]))
else:
mutant += new_pool[i][j]
... | mutate | identifier_name |
Data_Exploration.py | from __future__ import print_function, division, unicode_literals
from datetime import date, datetime
import simplejson
from flask import Flask, request, jsonify
from www.archive.datasources import AsterixDataSource
from www.archive.datasources import SolrDataSource
from www.archive.datasources import convertToIn
fr... |
l.append(d)
#
theresult_json = json.dumps(l, default=json_serial)
conn.close()
return theresult_json
@app.route("/api/correlation/<col1>/<col2>")
def Correlation(col1, col2):
engine = create_engine('postgresql+psycopg2://student:123456@132.249.238.27:5432/bookstore_dp')
conn = engi... | c = request.args[item]
print (c)
d[c] = result[c] | conditional_block |
Data_Exploration.py | from __future__ import print_function, division, unicode_literals
from datetime import date, datetime
import simplejson
from flask import Flask, request, jsonify
from www.archive.datasources import AsterixDataSource
from www.archive.datasources import SolrDataSource
from www.archive.datasources import convertToIn
fr... |
@app.route("/api/web_method/<format>")
def api_web_method(format):
engine = create_engine('postgresql+psycopg2://student:123456@132.249.238.27:5432/bookstore_dp')
conn = engine.connect()
sql = """
select *
from orderlines o, products p
where o.productid = p.productid
LIMIT 10
"""
... | """JSON serializer for objects not serializable by default json code"""
if isinstance(obj, (datetime, date)):
return obj.isoformat()
raise TypeError ("Type %s not serializable" % type(obj)) | identifier_body |
Data_Exploration.py | from __future__ import print_function, division, unicode_literals
from datetime import date, datetime
import simplejson
from flask import Flask, request, jsonify
from www.archive.datasources import AsterixDataSource
from www.archive.datasources import SolrDataSource
from www.archive.datasources import convertToIn
fr... | (obj):
"""JSON serializer for objects not serializable by default json code"""
if isinstance(obj, (datetime, date)):
return obj.isoformat()
raise TypeError ("Type %s not serializable" % type(obj))
@app.route("/api/web_method/<format>")
def api_web_method(format):
engine = create_engine('postg... | json_serial | identifier_name |
Data_Exploration.py | from __future__ import print_function, division, unicode_literals
from datetime import date, datetime
import simplejson
from flask import Flask, request, jsonify
from www.archive.datasources import AsterixDataSource
from www.archive.datasources import SolrDataSource
from www.archive.datasources import convertToIn
fr... |
app = Flask(__name__)
@app.route("/")
def Hello():
return "Hello World!"
@app.route('/api/service', methods=['POST'])
def api_service():
query = request.get_json(silent=True)
# needs to change to reading from xml file
xml = VirtualIntegrationSchema()
web_session = WebSession(xml)
return j... | from json import loads
import psycopg2
from sqlalchemy import create_engine, text
import pysolr
from textblob import TextBlob as tb | random_line_split |
ConfiguredResourceUploader.js | /*
* web: ConfiguredResourceUploader.js
* XNAT http://www.xnat.org
* Copyright (c) 2005-2017, Washington University School of Medicine and Howard Hughes Medical Institute
* All Rights Reserved
*
* Released under the Simplified BSD.
*/
/*
* resource dialog is used to upload resources at any level
*... | if(tempConfigs.length>0){
if(value.dontHide){
$(value).color(value.defaultColor);
$(value).css('cursor:pointer');
}
$(this).click(function(){
XNAT.app.crUploader.show(this);
return false;
});
$(this).show();
}else{
if(!value.dontHide){
$(this).hid... |
var tempConfigs=XNAT.app.crConfigs.getAllConfigsByType(type,props)
| random_line_split |
ConfiguredResourceUploader.js | /*
* web: ConfiguredResourceUploader.js
* XNAT http://www.xnat.org
* Copyright (c) 2005-2017, Washington University School of Medicine and Howard Hughes Medical Institute
* All Rights Reserved
*
* Released under the Simplified BSD.
*/
/*
* resource dialog is used to upload resources at any level
*... |
this.dialog.hide();
},
confirm : function (header, msg, handleYes, handleNo) {
var dialog = new YAHOO.widget.SimpleDialog('widget_confirm', {
visible:false,
width: '20em',
zIndex: 9998,
close: false,
fixedcenter: true,
modal: true,
draggable: true,
constraintoviewport: tru... | {
showMessage("page_body","Failed upload.",response.responseText);
} | conditional_block |
extractdicom.go | package bulkprocess
import (
"archive/zip"
"fmt"
"image"
"image/color"
"io"
"log"
"math"
"strconv"
"cloud.google.com/go/storage"
"github.com/suyashkumar/dicom"
"github.com/suyashkumar/dicom/dicomtag"
"github.com/suyashkumar/dicom/element"
)
// ExtractDicomFromGoogleStorage fetches a dicom from within a z... | }
// Draw the overlay
if opts.IncludeOverlay && img != nil && overlayPixels != nil {
// Iterate over the bytes. There will be 1 value for each cell.
// So in a 1024x1024 overlay, you will expect 1,048,576 cells.
for i, overlayValue := range overlayPixels {
row := i / nOverlayCols
col := i % nOverlayCols... | random_line_split | |
extractdicom.go | package bulkprocess
import (
"archive/zip"
"fmt"
"image"
"image/color"
"io"
"log"
"math"
"strconv"
"cloud.google.com/go/storage"
"github.com/suyashkumar/dicom"
"github.com/suyashkumar/dicom/dicomtag"
"github.com/suyashkumar/dicom/element"
)
// ExtractDicomFromGoogleStorage fetches a dicom from within a z... |
func ApplyPythonicWindowScaling(intensity, maxIntensity int) uint16 {
if intensity < 0 {
intensity = 0
}
return uint16(float64(math.MaxUint16) * float64(intensity) / float64(maxIntensity))
}
func ApplyNoWindowScaling(intensity int) uint16 {
return uint16(intensity)
}
| {
// 1: StoredValue to ModalityValue
var modalityValue float64
if rescaleSlope == 0 {
// Via https://dgobbi.github.io/vtk-dicom/doc/api/image_display.html :
// For modalities such as ultrasound and MRI that do not have any units,
// the RescaleSlope and RescaleIntercept are absent and the Modality
// Values ... | identifier_body |
extractdicom.go | package bulkprocess
import (
"archive/zip"
"fmt"
"image"
"image/color"
"io"
"log"
"math"
"strconv"
"cloud.google.com/go/storage"
"github.com/suyashkumar/dicom"
"github.com/suyashkumar/dicom/dicomtag"
"github.com/suyashkumar/dicom/element"
)
// ExtractDicomFromGoogleStorage fetches a dicom from within a z... | (zipPath, dicomName string, includeOverlay bool) (image.Image, error) {
return ExtractDicomFromGoogleStorage(zipPath, dicomName, includeOverlay, nil)
}
// ExtractDicomFromZipReader consumes a zip reader of the UK Biobank format,
// finds the dicom of the desired name, and returns that image, with or without
// the ov... | ExtractDicomFromLocalFile | identifier_name |
extractdicom.go | package bulkprocess
import (
"archive/zip"
"fmt"
"image"
"image/color"
"io"
"log"
"math"
"strconv"
"cloud.google.com/go/storage"
"github.com/suyashkumar/dicom"
"github.com/suyashkumar/dicom/dicomtag"
"github.com/suyashkumar/dicom/element"
)
// ExtractDicomFromGoogleStorage fetches a dicom from within a z... |
}
return img, err
}
// See 'Grayscale Image Display' under
// https://dgobbi.github.io/vtk-dicom/doc/api/image_display.html . In addition,
// we also scale the output so that it is appropriate for producing a 16-bit
// grayscale image. E.g., if the native dicom is 8-bit, we still rescale the
// output here for a 1... | {
row := i / nOverlayCols
col := i % nOverlayCols
if overlayValue != 0 {
img.SetGray16(col, row, color.White)
}
} | conditional_block |
lib.rs | //! A thread-safe object pool with automatic return and attach/detach semantics
//!
//! The goal of an object pool is to reuse expensive to allocate objects or frequently allocated objects
//!
//! # Examples
//!
//! ## Creating a Pool
//!
//! The general pool creation looks like this
//! ```
//! let pool: MemPool<T> =... | elf.run_block.lock();
log::trace!("attach started<<<<<<<<<<<<<<<<");
log::trace!("recyled an item ");
let mut wait_list = { self.waiting.lock() };
log::trace!("check waiting list ok :{}", wait_list.len());
if wait_list.len() > 0 && self.len() >= wait_list[0].min_request {
... | _x = s | identifier_name |
lib.rs | //! A thread-safe object pool with automatic return and attach/detach semantics
//!
//! The goal of an object pool is to reuse expensive to allocate objects or frequently allocated objects
//!
//! # Examples
//!
//! ## Creating a Pool
//!
//! The general pool creation looks like this
//! ```
//! let pool: MemPool<T> =... | waiting.lock().len() * 60 + 2 };
log::trace!("try again :{} with retries backoff:{}", str, to_retry);
for i in 0..to_retry {
sleep(std::time::Duration::from_secs(1));
if let Ok(item) = self.objects.1.try_recv() {
log::trace!("get ok:{}", str);
... | );
(Some(Reusable::new(&self, item)), false)
/* } else if (self.pending.lock().len() == 0) {
log::trace!("get should pend:{}", str);
self.pending.lock().push(PendingInfo {
id: String::from(str),
notif... | conditional_block |
lib.rs | //! A thread-safe object pool with automatic return and attach/detach semantics
//!
//! The goal of an object pool is to reuse expensive to allocate objects or frequently allocated objects
//!
//! # Examples
//!
//! ## Creating a Pool
//!
//! The general pool creation looks like this
//! ```
//! let pool: MemPool<T> =... | usize {
self.objects.1.len()
}
#[inline]
pub fn is_empty(&self) -> bool {
self.objects.1.is_empty()
}
#[inline]
pub fn pending(&'static self, str: &str, sender: channel::Sender<Reusable<T>>, releasable: usize) -> (Option<Reusable<T>>, bool) {
log::trace!("pending item:{... | {}", cap);
log::trace!("mempool remains:{}", cap);
let mut objects = channel::unbounded();
for _ in 0..cap {
&objects.0.send(init());
}
MemoryPool {
objects,
pending: Arc::new(Mutex::new(Vec::new())),
waiting: Arc::new(Mutex::new(Ve... | identifier_body |
lib.rs | //! A thread-safe object pool with automatic return and attach/detach semantics
//!
//! The goal of an object pool is to reuse expensive to allocate objects or frequently allocated objects
//!
//! # Examples
//!
//! ## Creating a Pool
//!
//! The general pool creation looks like this
//! ```
//! let pool: MemPool<T> =... | //! some_file.read_to_end(reusable_buff);
//! // reusable_buff is automatically returned to the pool when it goes out of scope
//! ```
//! Pull from pool and `detach()`
//! ```
//! let pool: MemoryPool<Vec<u8>> = MemoryPool::new(32, || Vec::with_capacity(4096));
//! let mut reusable_buff = pool.pull().unwrap(); // retu... | //! let pool: MemoryPool<Vec<u8>> = MemoryPool::new(32, || Vec::with_capacity(4096));
//! let mut reusable_buff = pool.pull().unwrap(); // returns None when the pool is saturated
//! reusable_buff.clear(); // clear the buff before using | random_line_split |
counter.rs | use std::ffi::CString;
use std::io;
use std::sync::{Mutex, Once};
#[cfg(target_os = "freebsd")]
use libc::EDOOFUS;
#[cfg(target_os = "freebsd")]
use pmc_sys::{
pmc_allocate, pmc_attach, pmc_detach, pmc_id_t, pmc_init, pmc_mode_PMC_MODE_SC,
pmc_mode_PMC_MODE_TC, pmc_read, pmc_release, pmc_rw, pmc_start, pmc_sto... | (&mut self) {
unsafe { pmc_stop(self.counter.id) };
}
}
/// An allocated PMC counter.
///
/// Counters are initialised using the [`CounterBuilder`] type.
///
/// ```no_run
/// use std::{thread, time::Duration};
///
/// let instr = CounterConfig::default()
/// .attach_to(vec![0])
/// .allocate("inst... | drop | identifier_name |
counter.rs | use std::ffi::CString;
use std::io;
use std::sync::{Mutex, Once};
#[cfg(target_os = "freebsd")]
use libc::EDOOFUS;
#[cfg(target_os = "freebsd")]
use pmc_sys::{
pmc_allocate, pmc_attach, pmc_detach, pmc_id_t, pmc_init, pmc_mode_PMC_MODE_SC,
pmc_mode_PMC_MODE_TC, pmc_read, pmc_release, pmc_rw, pmc_start, pmc_sto... |
handles.push(AttachHandle { id, pid })
}
c.attached = Some(handles)
}
Ok(c)
}
/// Start this counter.
///
/// The counter stops when the returned [`Running`] handle is dropped.
#[must_use = "counter only runs until handle is dropped"]
... | {
return match io::Error::raw_os_error(&io::Error::last_os_error()) {
Some(libc::EBUSY) => unreachable!(),
Some(libc::EEXIST) => Err(new_os_error(ErrorKind::AlreadyAttached)),
Some(libc::EPERM) => Err(new_os_error(ErrorKind::For... | conditional_block |
counter.rs | use std::ffi::CString;
use std::io;
use std::sync::{Mutex, Once};
#[cfg(target_os = "freebsd")]
use libc::EDOOFUS;
#[cfg(target_os = "freebsd")]
use pmc_sys::{
pmc_allocate, pmc_attach, pmc_detach, pmc_id_t, pmc_init, pmc_mode_PMC_MODE_SC,
pmc_mode_PMC_MODE_TC, pmc_read, pmc_release, pmc_rw, pmc_start, pmc_sto... | // Allocate the PMC
let mut id = 0;
if unsafe {
pmc_allocate(
c_spec.as_ptr(),
pmc_mode,
0,
cpu.unwrap_or(CPU_ANY),
&mut id,
0,
)
} != 0
{
return ma... | let c_spec =
CString::new(event_spec.into()).map_err(|_| new_error(ErrorKind::InvalidEventSpec))?;
| random_line_split |
sync.js | /*
* image sync plugin (September 2, 2018)
* whenever an operation is performed on this image, sync the target images
*/
/*global JS9, $ */
"use strict";
JS9.Sync = {};
JS9.Sync.CLASS = "JS9"; // class of plugins (1st part of div class)
JS9.Sync.NAME = "Sync"; // name of this plugin (2nd part of div class... |
// for each op (colormap, pan, etc.)
for(i=0; i<xops.length; i++){
// current op
xop = xops[i];
this.syncs[xop] = this.syncs[xop] || [];
ims = this.syncs[xop];
// add images not already in the list
for(j=0; j<xlen; j++){
xim = xims[j];
if( $.inArray(xim, ims) < 0 ){
// add to list
ims.push(... | {
delete opts.reverse;
for(i=0; i<xlen; i++){
JS9.Sync.sync.call(xims[i], xops, [this]);
}
return;
} | conditional_block |
sync.js | /*
* image sync plugin (September 2, 2018)
* whenever an operation is performed on this image, sync the target images
*/
/*global JS9, $ */
"use strict";
JS9.Sync = {};
JS9.Sync.CLASS = "JS9"; // class of plugins (1st part of div class)
JS9.Sync.NAME = "Sync"; // name of this plugin (2nd part of div class... | if( xim &&
(xim.id !== this.id || (xim.display.id !== this.display.id)) ){
xims[j++] = xim;
}
}
return xims;
};
// sync image(s) when operations are performed on an originating image
// called in the image context
JS9.Sync.sync = function(...args){
let i, j, xop, xim, xops, xims, xlen;
let ... | } else {
xim = ims[i];
}
// exclude the originating image | random_line_split |
model_sql.go | package mc
import (
"fmt"
"github.com/spf13/cast"
"gorm.io/gorm"
"reflect"
"strings"
)
//kvs查询选项
type KvsQueryOption struct {
DB *gorm.DB //当此项为空的，使用model.db
KvName string //kv配置项名
ExtraWhere []interface{} //额外附加的查询条件
ReturnPath bool //当模型为树型结构时，返回的key是否使用path代替
ExtraFi... | treePathField := m.FieldAddAlias(m.attr.Tree.PathField)
fields = append(append(fields, treePathField), m.ParseTreeExtraField()...)
}
// 附加字段
if extraFields != nil {
fields = append(fields, m.FieldsAddAlias(extraFields)...)
}
return
}
// 给字段加表别名
func (m *Model) FieldAddAlias(field string) string {
if field ... | fields = append(fields, keyField, valueField)
// 树型必备字段
if m.attr.IsTree { | random_line_split |
model_sql.go | package mc
import (
"fmt"
"github.com/spf13/cast"
"gorm.io/gorm"
"reflect"
"strings"
)
//kvs查询选项
type KvsQueryOption struct {
DB *gorm.DB //当此项为空的，使用model.db
KvName string //kv配置项名
ExtraWhere []interface{} //额外附加的查询条件
ReturnPath bool //当模型为树型结构时，返回的key是否使用path代替
ExtraFi... | 填字段
func (m *Model) CheckRequiredValues(data map[string]interface{}) (err error) {
fieldTitles := make([]string, 0)
//非自增PK表，检查PK字段
if !m.attr.AutoInc {
if cast.ToString(data[m.attr.Pk]) == "" {
fieldTitles = append(fieldTitles, m.attr.Fields[m.attr.fieldIndexMap[m.attr.Pk]].Title)
}
}
//检查配置中的必填字段
for _, ... | r
} else if total > 0 {
return &Result{Message:fmt.Sprintf("记录已存在：【%s】存在重复", strings.Join(fileTitles, "、"))}
}
return nil
}
// 检查必 | conditional_block |
model_sql.go | package mc
import (
"fmt"
"github.com/spf13/cast"
"gorm.io/gorm"
"reflect"
"strings"
)
//kvs查询选项
type KvsQueryOption struct {
DB *gorm.DB //当此项为空的，使用model.db
KvName string //kv配置项名
ExtraWhere []interface{} //额外附加的查询条件
ReturnPath bool //当模型为树型结构时，返回的key是否使用path代替
ExtraFi... | ", m.attr.Table, m.attr.Pk)
field = make([]string, 3)
//层级字段
field[0] = fmt.Sprintf("CEILING(LENGTH(%s)/%d) AS `__mc_level`", pathField, m.attr.Tree.PathBit)
//父节点字段
field[1] = fmt.Sprintf("(SELECT %s FROM `%s` AS `__mc_%s` WHERE %s=LEFT(%s, LENGTH(%s)-%d) LIMIT 1) AS `__mc_parent`",
__mc_pkField, m.attr.Table,... | t.ToString(data[i][m.attr.Tree.NameField])
}
}
return
}
// 分析树形结构查询必须的扩展字段
func (m *Model) ParseTreeExtraField() (field []string) {
pathField := m.FieldAddAlias(m.attr.Tree.PathField)
__mc_pathField := fmt.Sprintf("`__mc_%s`.`%s`", m.attr.Table, m.attr.Tree.PathField)
__mc_pkField := fmt.Sprintf("`__mc_%s`.`%s... | identifier_body |
model_sql.go | package mc
import (
"fmt"
"github.com/spf13/cast"
"gorm.io/gorm"
"reflect"
"strings"
)
//kvs查询选项
type KvsQueryOption struct {
DB *gorm.DB //当此项为空的，使用model.db
KvName string //kv配置项名
ExtraWhere []interface{} //额外附加的查询条件
ReturnPath bool //当模型为树型结构时，返回的key是否使用path代替
ExtraFi... | lue"])
}
}
}
}
}
//树形
indent := ""
if qo.TreeIndent == nil {
indent = m.attr.Tree.Indent
} else {
indent = *qo.TreeIndent
}
if m.attr.IsTree && indent != "" { //树形名称字段加前缀
for i, _ := range data {
data[i][m.attr.Tree.NameField] = nString(indent, cast.ToInt(data[i]["__mc_level"])-1) + cast.T... | ing]["__mc_va | identifier_name |
script.padrao.js | /**
* Esse script tem dependencia das seguintes bibliotecas:
*
* class.padrao.js
* style.padrao.js
*
* Terceiros:
*
* Bootstrap 5.1 ou superior.
* ChartJS;.
*
* */
const url = new URL(document.URL);
const urlHost = `${url.protocol}//${url.host}`;
const urlAPI = `${urlHost}/api/`;
//const urlAPI = `ht... | alert(error);
}
}
const API = {
/**
*Requisições do tipo GET
* @param {Opções para a definição da requisição} options
*/
GET: (options) => {
try {
if (options == undefined || options == null) {
return false;
}
Ajax(options);
... | }
} catch (error) {
| conditional_block |
script.padrao.js | /**
* Esse script tem dependencia das seguintes bibliotecas:
*
* class.padrao.js
* style.padrao.js
*
* Terceiros:
*
* Bootstrap 5.1 ou superior.
* ChartJS;.
*
* */
const url = new URL(document.URL);
const urlHost = `${url.protocol}//${url.host}`;
const urlAPI = `${urlHost}/api/`;
//const urlAPI = `ht... | var divSpinner = Elements.Create('div', 'divGrowing', null, null, `z-index: 150 !important; color: ${spinnerColor} !important;`, ["spinner-grow", "text-primary"]);
span = Elements.Create('span', 'loadGrowing', "visually-hidden", null);
divSpinner.... | div = Elements.Create('div', 'loadMestre', null, null, style);
| random_line_split |
mod.rs |
use rstd::prelude::*;
use codec::{Encode, Decode};
use support::{
StorageValue, StorageMap, decl_event, decl_storage, decl_module, ensure,
traits::{
Currency, ReservableCurrency,
OnFreeBalanceZero, OnUnbalanced,
WithdrawReason, ExistenceRequirement,
Imbalance, Get,
},
dispatch::Result,
};
use sr_primitives... | //! # Activity Module
//!
#![cfg_attr(not(feature = "std"), no_std)] | random_line_split | |
mod.rs | //! # Activity Module
//!
#![cfg_attr(not(feature = "std"), no_std)]
use rstd::prelude::*;
use codec::{Encode, Decode};
use support::{
StorageValue, StorageMap, decl_event, decl_storage, decl_module, ensure,
traits::{
Currency, ReservableCurrency,
OnFreeBalanceZero, OnUnbalanced,
WithdrawReason, ExistenceReq... | <T: Trait>(#[codec(compact)] BalanceOf<T>);
impl<T: Trait> TakeFees<T> {
/// utility constructor. Used only in client/factory code.
pub fn from(fee: BalanceOf<T>) -> Self {
Self(fee)
}
/// Compute the final fee value for a particular transaction.
///
/// The final fee is composed of:
/// - _length-fee_: Th... | TakeFees | identifier_name |
mod.rs | //! # Activity Module
//!
#![cfg_attr(not(feature = "std"), no_std)]
use rstd::prelude::*;
use codec::{Encode, Decode};
use support::{
StorageValue, StorageMap, decl_event, decl_storage, decl_module, ensure,
traits::{
Currency, ReservableCurrency,
OnFreeBalanceZero, OnUnbalanced,
WithdrawReason, ExistenceReq... |
// PRIVATE MUTABLES
fn charge_for_energy(who: &T::AccountId, value: BalanceOf<T>) -> Result {
// ensure reserve
if !T::Currency::can_reserve(who, value) {
return Err("not enough free funds");
}
// check current_charged
let current_charged = <Charged<T>>::get(who);
let new_charged = current_charged.ch... | {
T::EnergyCurrency::available_free_balance(who)
} | identifier_body |
compile.ts | import fs from "fs";
import { SandboxStatus } from "simple-sandbox";
import objectHash from "object-hash";
import LruCache from "lru-cache";
import winston from "winston";
import { v4 as uuid } from "uuid";
import getLanguage, { LanguageConfig } from "./languages";
import { MappedPath, safelyJoinPath, ensureDirectory... |
public async dereference() {
if (--this.referenceCount === 0) {
await fsNative.remove(this.binaryDirectory);
}
}
async copyTo(newBinaryDirectory: string) {
this.reference();
await fsNative.copy(this.binaryDirectory, newBinaryDirectory);
await this.dereference();
return new Compile... | {
this.referenceCount++;
return this;
} | identifier_body |
compile.ts | import fs from "fs";
import { SandboxStatus } from "simple-sandbox";
import objectHash from "object-hash";
import LruCache from "lru-cache";
import winston from "winston";
import { v4 as uuid } from "uuid";
import getLanguage, { LanguageConfig } from "./languages";
import { MappedPath, safelyJoinPath, ensureDirectory... | () {
if (--this.referenceCount === 0) {
await fsNative.remove(this.binaryDirectory);
}
}
async copyTo(newBinaryDirectory: string) {
this.reference();
await fsNative.copy(this.binaryDirectory, newBinaryDirectory);
await this.dereference();
return new CompileResultSuccess(
this.co... | dereference | identifier_name |
compile.ts | import fs from "fs";
import { SandboxStatus } from "simple-sandbox";
import objectHash from "object-hash";
import LruCache from "lru-cache";
import winston from "winston";
import { v4 as uuid } from "uuid";
import getLanguage, { LanguageConfig } from "./languages";
import { MappedPath, safelyJoinPath, ensureDirectory... | await fsNative.copy(this.binaryDirectory, newBinaryDirectory);
await this.dereference();
return new CompileResultSuccess(
this.compileTaskHash,
this.message,
newBinaryDirectory,
this.binaryDirectorySize,
this.extraInfo
);
}
}
// Why NOT using the task hash as the directo... |
async copyTo(newBinaryDirectory: string) {
this.reference(); | random_line_split |
supervised_ml_(classification)_assignment_(final).py | # -*- coding: utf-8 -*-
"""Supervised_ML_(Classification)_assignment_(final)
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1dt_czoLEqYxIoCA-v7Ynu0XHCWHnFWsB
"""
#import of libraries
import pandas as pd
import glob
import numpy as np
import seaborn as... | f = pd.concat(oob_list, axis=1).T.set_index('n_trees')
ax = rf_oob_df.plot(legend=False, marker='x', figsize=(14, 7), linewidth=5)
ax.set(ylabel='out-of-bag error');
"""The key is to reduce our out-of-bag (OOB) error. We do this by increasing the number of possibilities and finding the possibility which produced the ... | ams(n_estimators=n_trees)
# Fit the model
RF.fit(x_train, y_train)
# Get the oob error
oob_error = 1 - RF.oob_score_
# Store it
oob_list.append(pd.Series({'n_trees': n_trees, 'oob': oob_error}))
rf_oob_d | conditional_block |
supervised_ml_(classification)_assignment_(final).py | # -*- coding: utf-8 -*-
"""Supervised_ML_(Classification)_assignment_(final)
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1dt_czoLEqYxIoCA-v7Ynu0XHCWHnFWsB
"""
#import of libraries
import pandas as pd
import glob
import numpy as np
import seaborn as... | plt.show()
"""---
# Data Engineering/Modelling
Because the data is already in a numerical form (int-type), it will not be required to engineer the data or reencode values. Though, given the tasks ahead, we may require data scaling for input into specific classifier models.
We shall address this problem as we arr... | random_line_split | |
supervised_ml_(classification)_assignment_(final).py | # -*- coding: utf-8 -*-
"""Supervised_ML_(Classification)_assignment_(final)
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1dt_czoLEqYxIoCA-v7Ynu0XHCWHnFWsB
"""
#import of libraries
import pandas as pd
import glob
import numpy as np
import seaborn as... | e, y_pred, label):
return pd.Series({'accuracy':accuracy_score(y_true, y_pred),
'precision': precision_score(y_true, y_pred),
'recall': recall_score(y_true, y_pred),
'f1': f1_score(y_true, y_pred)},
name=label)
train_test_full_... | e_error(y_tru | identifier_name |
supervised_ml_(classification)_assignment_(final).py | # -*- coding: utf-8 -*-
"""Supervised_ML_(Classification)_assignment_(final)
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1dt_czoLEqYxIoCA-v7Ynu0XHCWHnFWsB
"""
#import of libraries
import pandas as pd
import glob
import numpy as np
import seaborn as... | n_test_full_error = pd.concat([measure_error(y_train, y_train_pred, 'train'),
measure_error(y_test, y_test_pred, 'test')],
axis=1)
train_test_full_error
"""The above output shows out accuracy prediction. This is quite low, could it be improved with Grid Sear... | pd.Series({'accuracy':accuracy_score(y_true, y_pred),
'precision': precision_score(y_true, y_pred),
'recall': recall_score(y_true, y_pred),
'f1': f1_score(y_true, y_pred)},
name=label)
trai | identifier_body |
tls.go | package main
import (
"bytes"
"context"
"crypto/md5"
"crypto/rand"
"crypto/tls"
"crypto/x509"
"crypto/x509/pkix"
"encoding/pem"
"errors"
"fmt"
"io"
"io/ioutil"
"log"
"math/big"
"net"
"net/http"
"net/url"
"runtime"
"strings"
"sync"
"time"
"github.com/open-ch/ja3"
"go.starlark.net/starlark"
"gol... |
callStarlarkFunctions("ssl_bump", session)
dialer := &net.Dialer{
Timeout: 30 * time.Second,
KeepAlive: 30 * time.Second,
DualStack: true,
}
if session.SourceIP != nil {
dialer.LocalAddr = &net.TCPAddr{
IP: session.SourceIP,
}
}
session.chooseAction()
logAccess(cr, nil, 0, false, user, tally,... | {
session.PossibleActions = append(session.PossibleActions, "ssl-bump")
} | conditional_block |
tls.go | package main
import (
"bytes"
"context"
"crypto/md5"
"crypto/rand"
"crypto/tls"
"crypto/x509"
"crypto/x509/pkix"
"encoding/pem"
"errors"
"fmt"
"io"
"io/ioutil"
"log"
"math/big"
"net"
"net/http"
"net/url"
"runtime"
"strings"
"sync"
"time"
"github.com/open-ch/ja3"
"go.starlark.net/starlark"
"gol... | (certPath string) error {
if c.ExtraRootCerts == nil {
c.ExtraRootCerts = x509.NewCertPool()
}
pem, err := ioutil.ReadFile(certPath)
if err != nil {
return err
}
if !c.ExtraRootCerts.AppendCertsFromPEM(pem) {
return fmt.Errorf("no certificates found in %s", certPath)
}
return nil
}
| addTrustedRoots | identifier_name |
tls.go | package main
import (
"bytes"
"context"
"crypto/md5"
"crypto/rand"
"crypto/tls"
"crypto/x509"
"crypto/x509/pkix"
"encoding/pem"
"errors"
"fmt"
"io"
"io/ioutil"
"log"
"math/big"
"net"
"net/http"
"net/url"
"runtime"
"strings"
"sync"
"time"
"github.com/open-ch/ja3"
"go.starlark.net/starlark"
"gol... | session.ClientIP = client
}
obsoleteVersion := false
invalidSSL := false
// Read the client hello so that we can find out the name of the server (not
// just the address).
clientHello, err := readClientHello(conn)
if err != nil {
logTLS(user, serverAddr, "", fmt.Errorf("error reading client hello: %v", err)... | client := conn.RemoteAddr().String()
if host, _, err := net.SplitHostPort(client); err == nil {
session.ClientIP = host
} else { | random_line_split |
tls.go | package main
import (
"bytes"
"context"
"crypto/md5"
"crypto/rand"
"crypto/tls"
"crypto/x509"
"crypto/x509/pkix"
"encoding/pem"
"errors"
"fmt"
"io"
"io/ioutil"
"log"
"math/big"
"net"
"net/http"
"net/url"
"runtime"
"strings"
"sync"
"time"
"github.com/open-ch/ja3"
"go.starlark.net/starlark"
"gol... |
var tlsSessionAttrNames = []string{"sni", "server_addr", "user", "client_ip", "acls", "scores", "source_ip", "action", "possible_actions", "header", "misc"}
func (s *TLSSession) AttrNames() []string {
return tlsSessionAttrNames
}
func (s *TLSSession) Attr(name string) (starlark.Value, error) {
switch name {
case... | {
return 0, errors.New("unhashable type: TLSSession")
} | identifier_body |
kek.py | #Импортирование библиотек
import PySimpleGUI as sg
from nltk.tokenize import word_tokenize
from nltk.corpus import stopwords
from nltk.stem import PorterStemmer
import matplotlib.pyplot as plt
from wordcloud import WordCloud
from math import log
import numpy as np
import pandas as pd
import nltk
from sklearn.model_sele... | ие словрей спам и не спам слов
spam_words = ' '.join(list(mails[mails['label'] == 1]['message']))
ham_words = ' '.join(list(mails[mails['label'] == 0]['message']))
trainData.head()
trainData['label'].value_counts()
testData.head()
testData['label'].value_counts()
#Обработка текста сообщений
def process_message(mes... | ts()
#Формирован | conditional_block |
kek.py | #Импортирование библиотек
import PySimpleGUI as sg
from nltk.tokenize import word_tokenize
from nltk.corpus import stopwords
from nltk.stem import PorterStemmer
import matplotlib.pyplot as plt
from wordcloud import WordCloud
from math import log
import numpy as np
import pandas as pd
import nltk
from sklearn.model_sele... | ate(spam_words)
plt.figure(figsize = (10, 8), facecolor = 'k')
plt.imshow(spam_wc)
plt.axis('off')
plt.tight_layout(pad = 0)
plt.show()
#Функция визуализации словаря легетимных слов
def show_ham(ham_words):
ham_wc = WordCloud(width = 512,height = 512).generate(ham_words)
plt.figure(figsize =... | слов
def show_spam(spam_words):
spam_wc = WordCloud(width = 512,height = 512).gener | identifier_body |
kek.py | #Импортирование библиотек
import PySimpleGUI as sg
from nltk.tokenize import word_tokenize
from nltk.corpus import stopwords
from nltk.stem import PorterStemmer
import matplotlib.pyplot as plt
from wordcloud import WordCloud
from math import log
import numpy as np
import pandas as pd
import nltk
from sklearn.model_sele... | = self.spam_mails / self.total_mails, self.ham_mails / self.total_mails
#Вычисление вероятностей
def calc_TF_and_IDF(self):
noOfMessages = self.mails.shape[0]
self.spam_mails, self.ham_mails = self.labels.value_counts()[1], self.labels.value_counts()[0]
self.total_mails = self.spam_mail... | _mail | identifier_name |
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