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 |
|---|---|---|---|---|
ethereum-block.ts | import {toBigIntBE, toBufferBE} from 'bigint-buffer';
import {RlpEncode, RlpList} from 'rlp-stream';
import * as secp256k1 from 'secp256k1';
declare var process: {browser: boolean;};
const keccak = require('keccak');
interface NativeInterface {
recoverFromAddress(verifyBlock: Buffer, signature: Buffer, recovery: bo... | : EthereumHeader, transactions: RlpList,
uncleList: EthereumHeader[]): Buffer {
const asRlpList: RlpList = [
encodeHeaderAsRLP(header), transactions,
uncleList.map(uncle => encodeHeaderAsRLP(uncle))
];
return RlpEncode(asRlpList);
}
/**
* Get the public address of a given private key.
*
* @param p... |
header | identifier_name |
ethereum-block.ts | import {toBigIntBE, toBufferBE} from 'bigint-buffer';
import {RlpEncode, RlpList} from 'rlp-stream';
import * as secp256k1 from 'secp256k1';
declare var process: {browser: boolean;};
const keccak = require('keccak');
interface NativeInterface {
recoverFromAddress(verifyBlock: Buffer, signature: Buffer, recovery: bo... |
const TRANSACTION_NONCE = 0;
const TRANSACTION_GASPRICE = 1;
const TRANSACTION_STARTGAS = 2;
const TRANSACTION_TO = 3;
const TRANSACTION_VALUE = 4;
const TRANSACTION_DATA = 5;
const TRANSACTION_V = 6;
const TRANSACTION_R = 7;
const TRANSACTION_S = 8;
/**
* Given a RLP-serialized list with an Ethereum transaction, de... | extraData: (header[HEADER_EXTRADATA] as Buffer),
mixHash: toBigIntBE(header[HEADER_MIXHASH] as Buffer),
nonce: toBigIntBE(header[HEADER_NONCE] as Buffer)
};
} | random_line_split |
ethereum-block.ts | import {toBigIntBE, toBufferBE} from 'bigint-buffer';
import {RlpEncode, RlpList} from 'rlp-stream';
import * as secp256k1 from 'secp256k1';
declare var process: {browser: boolean;};
const keccak = require('keccak');
interface NativeInterface {
recoverFromAddress(verifyBlock: Buffer, signature: Buffer, recovery: bo... | pList: RlpList = [
removeNullPrefix(toBufferBE(transaction.nonce, 32)),
removeNullPrefix(toBufferBE(transaction.gasPrice, 32)),
removeNullPrefix(toBufferBE(transaction.gasLimit, 32)),
transaction.to === CONTRACT_CREATION ? Buffer.from([]) :
toBufferBE(transacti... | identifier_body | |
test_service.py | #!/usr/bin/env python
#
# Copyright 2011-2015 Splunk, 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... | def test_default_app(self):
kwargs = self.opts.kwargs.copy()
kwargs.update({'app': None, 'owner': "admin"})
service_ns = client.connect(**kwargs)
service_ns.apps.list()
def test_app_wildcard(self):
kwargs = self.opts.kwargs.copy()
kwargs.update({'app': "-", 'owne... | random_line_split | |
test_service.py | #!/usr/bin/env python
#
# Copyright 2011-2015 Splunk, 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... | (self):
kwargs = self.opts.kwargs.copy()
kwargs.update({'app': "search", 'owner': None})
service_ns = client.connect(**kwargs)
service_ns.apps.list()
def test_owner_wildcard(self):
kwargs = self.opts.kwargs.copy()
kwargs.update({'app': "search", 'owner': "-"})
... | test_app_namespace | identifier_name |
test_service.py | #!/usr/bin/env python
#
# Copyright 2011-2015 Splunk, 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... |
def _create_unauthenticated_service(self):
return Service(**{
'host': self.opts.kwargs['host'],
'port': self.opts.kwargs['port'],
'scheme': self.opts.kwargs['scheme']
})
# To check the HEC event endpoint using Endpoint instance
@pytest.mark.smoke
de... | raise | conditional_block |
test_service.py | #!/usr/bin/env python
#
# Copyright 2011-2015 Splunk, 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... |
def test_login_with_cookie(self):
self.service.login()
self.assertIsNotNone(self.service.get_cookies())
# Use the cookie from the other service as the only auth param (don't need user/password)
service2 = client.Service(**{"cookie": "%s=%s" % list(self.service.get_cookies().items()... | self.assertIsNotNone(self.service.get_cookies())
self.assertEqual(len(self.service.get_cookies()), 0)
self.service.login()
self.assertIsNotNone(self.service.get_cookies())
self.assertNotEqual(self.service.get_cookies(), {})
self.assertEqual(len(self.service.get_cookies()), 1) | identifier_body |
completion.rs | use std::{borrow::Cow, path::PathBuf, str::FromStr, sync::Arc};
use floem::{
peniko::kurbo::Rect,
reactive::{ReadSignal, RwSignal, Scope},
};
use lapce_core::{buffer::rope_text::RopeText, movement::Movement};
use lapce_rpc::{plugin::PluginId, proxy::ProxyRpcHandler};
use lsp_types::{
CompletionItem, Comple... | (&mut self) {
let count = self.display_count();
let active = self.active.get_untracked();
let new = Movement::Up.update_index(
active,
self.filtered_items.len(),
count,
false,
);
self.active.set(new);
}
/// The currently se... | previous_page | identifier_name |
completion.rs | use std::{borrow::Cow, path::PathBuf, str::FromStr, sync::Arc};
use floem::{
peniko::kurbo::Rect,
reactive::{ReadSignal, RwSignal, Scope},
};
use lapce_core::{buffer::rope_text::RopeText, movement::Movement};
use lapce_rpc::{plugin::PluginId, proxy::ProxyRpcHandler};
use lsp_types::{
CompletionItem, Comple... | // TODO: Possibly handle the 'is_incomplete' field on List.
CompletionResponse::List(list) => &list.items,
};
let items: im::Vector<ScoredCompletionItem> = items
.iter()
.map(|i| ScoredCompletionItem {
item: i.to_owned(),
pl... | random_line_split | |
completion.rs | use std::{borrow::Cow, path::PathBuf, str::FromStr, sync::Arc};
use floem::{
peniko::kurbo::Rect,
reactive::{ReadSignal, RwSignal, Scope},
};
use lapce_core::{buffer::rope_text::RopeText, movement::Movement};
use lapce_rpc::{plugin::PluginId, proxy::ProxyRpcHandler};
use lsp_types::{
CompletionItem, Comple... |
fn all_items(&self) -> im::Vector<ScoredCompletionItem> {
self.input_items
.get(&self.input)
.cloned()
.filter(|items| !items.is_empty())
.unwrap_or_else(move || {
self.input_items.get("").cloned().unwrap_or_default()
})
}
... | {
if self.status == CompletionStatus::Inactive {
return;
}
self.input = input;
// TODO: If the user types a letter that continues the current active item, we should
// try keeping that item active. Possibly give this a setting.
// ex: `p` has `print!` and `pri... | identifier_body |
feature_engineer.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import logging
logger = logging.getLogger('code_submission')
import random
import numpy as np
import pandas as pd
from pandas import Series
import torch
import time
from torch_geometric.data import Data
from s... | return data
pca=PCA(n_components=pca_threshold, svd_solver ='full')
data = pca.fit_transform(data)
return data
def _check_file_exist(file_path, flag_directed_graph):
if flag_directed_graph and os.path.exists(os.path.join(file_path,'NR_EB/STRAP_strap_frpca_d_U.npy')) and os.path.exists(os.path.j... | import os
def _pca_processing(data, pca_threshold=0.75):
if data.shape[1] == 0: | random_line_split |
feature_engineer.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import logging
logger = logging.getLogger('code_submission')
import random
import numpy as np
import pandas as pd
from pandas import Series
import torch
import time
from torch_geometric.data import Data
from s... | (edge_index, edge_weight, num_nodes):
row, col = edge_index
in_deg = scatter_add(edge_weight, col, dim_size=num_nodes).numpy()
out_deg = scatter_add(edge_weight, row, dim_size=num_nodes).numpy()
degree = np.concatenate([np.expand_dims(in_deg,-1), np.expand_dims(out_deg,-1)], axis=-1)
return degree... | get_node_degree | identifier_name |
feature_engineer.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import logging
logger = logging.getLogger('code_submission')
import random
import numpy as np
import pandas as pd
from pandas import Series
import torch
import time
from torch_geometric.data import Data
from s... |
node_embed = np.concatenate([node_embed_u, node_embed_v], axis=1)
else:
node_embed = np.load(os.path.join(file_path, 'NR_EB/STRAP_strap_frpca_u_U.npy'))
if np.isnan(node_embed).any():
node_embed[np.isnan(node_embed)] = 0.0
... | node_embed_v[np.isnan(node_embed_v)] = 0.0
logger.info('find nan in node_embed_V') | conditional_block |
feature_engineer.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import logging
logger = logging.getLogger('code_submission')
import random
import numpy as np
import pandas as pd
from pandas import Series
import torch
import time
from torch_geometric.data import Data
from s... |
def normalize(x):
norm_time = time.time()
tol = min(int(1e-3*x.shape[1]), 5)
normal_funs = ['l2', 'minmax', 'z-score']
normal_fun = normal_funs[0]
cont_feature_idx = [i for i in range(len(x)) if len(np.unique(x[i])) > 5 and check_continuous(x[i], tol)]
cate_feature_idx = [i for i in rang... | if len(np.unique(x)) > len(x) * 0.5:
return True
x = get_value_counts_with_moving_average(x)
max_index = np.argmax(x)
min_index = np.argmax(-np.array(x))
if check_monotony(x, tol):
return True
elif check_monotony(x[:max_index+1], tol) and check_monotony(x[max_index:], tol):
r... | identifier_body |
lib.rs | // lib.rs -- RUST wasm interface for Conways game of life
mod utils;
use quad_rand;
use js_sys;
use wasm_bindgen::prelude::*;
// When the `wee_alloc` feature is enabled, use `wee_alloc` as the global
// allocator.
#[cfg(feature = "wee_alloc")]
#[global_allocator]
static ALLOC: wee_alloc::WeeAlloc = wee_alloc::WeeA... | {
width: u32, // width of each row
height: u32, // number of rows
cells: Vec<Cell>, // width*height cells, each one byte
prevcells: Vec<Cell>, // cells from previous tick
mousedown: bool // set when shift-click event, so that associated click ignored
}
// methods for Universe, but not exposed... | Universe | identifier_name |
lib.rs | // lib.rs -- RUST wasm interface for Conways game of life
mod utils;
use quad_rand;
use js_sys;
use wasm_bindgen::prelude::*;
// When the `wee_alloc` feature is enabled, use `wee_alloc` as the global
// allocator.
#[cfg(feature = "wee_alloc")]
#[global_allocator]
static ALLOC: wee_alloc::WeeAlloc = wee_alloc::WeeA... |
}
// impl Universe block w/o wasm_bindgen attribute
// Needed for testing -- don't expose to our JS.
// Rust-generated WebAsm functions cannot return borrowed references.
// NOTE/SUGGEST: Try compiling the Rust-generated WebAsm with
// the wasm_bindgen attribute and examine errors.
// NOTE: get_cells returns b... | {
log!("reset_board() : {:?}", pattern);
let width = self.width();
let height = self.height();
self.prevcells = self.cells.clone(); // current grid, needed for correct redraw
self.cells = generate_cells(width, height, pattern);
} | identifier_body |
lib.rs | // lib.rs -- RUST wasm interface for Conways game of life
mod utils;
use quad_rand;
use js_sys;
use wasm_bindgen::prelude::*;
// When the `wee_alloc` feature is enabled, use `wee_alloc` as the global
// allocator.
#[cfg(feature = "wee_alloc")]
#[global_allocator]
static ALLOC: wee_alloc::WeeAlloc = wee_alloc::WeeA... |
+ if self.cells[self.get_index(down,right)] == Cell::Alive { 1 } else { 0 };
neighbors
}
}
// standalone method, not part of Universe directly
fn generate_cells(width: u32, height: u32, _pattern: InitialPattern) -> Vec<Cell> {
// expression generating Vec<Cell>
let cells = (0..width... | { 0 } | conditional_block |
lib.rs | // lib.rs -- RUST wasm interface for Conways game of life
mod utils;
use quad_rand;
use js_sys;
use wasm_bindgen::prelude::*;
// When the `wee_alloc` feature is enabled, use `wee_alloc` as the global
// allocator.
#[cfg(feature = "wee_alloc")]
#[global_allocator]
static ALLOC: wee_alloc::WeeAlloc = wee_alloc::WeeA... | }).collect();
inverted_cells
}
// Public methods, exposed to JS
#[wasm_bindgen]
impl Universe
{
pub fn width(&self) -> u32 {
self.width
}
pub fn height(&self) -> u32 {
self.height
}
// set_width -- set width of Universe, set all cells to Dead state
pub fn set_width(&m... | let inverted_cells = (0..count).map(|i|
{
if cells[i] == Cell::Alive { Cell::Dead } else { Cell::Alive } | random_line_split |
mod.rs | //! Drop range analysis finds the portions of the tree where a value is guaranteed to be dropped
//! (i.e. moved, uninitialized, etc.). This is used to exclude the types of those values from the
//! generator type. See `InteriorVisitor::record` for where the results of this analysis are used.
//!
//! There are three ph... | use crate::FnCtxt;
use hir::def_id::DefId;
use hir::{Body, HirId, HirIdMap, Node};
use rustc_data_structures::unord::{UnordMap, UnordSet};
use rustc_hir as hir;
use rustc_index::bit_set::BitSet;
use rustc_index::IndexVec;
use rustc_middle::hir::map::Map;
use rustc_middle::hir::place::{PlaceBase, PlaceWithHirId};
use ru... |
use self::cfg_build::build_control_flow_graph;
use self::record_consumed_borrow::find_consumed_and_borrowed; | random_line_split |
mod.rs | //! Drop range analysis finds the portions of the tree where a value is guaranteed to be dropped
//! (i.e. moved, uninitialized, etc.). This is used to exclude the types of those values from the
//! generator type. See `InteriorVisitor::record` for where the results of this analysis are used.
//!
//! There are three ph... | (&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
f.debug_struct("DropRanges")
.field("hir_id_map", &self.tracked_value_map)
.field("post_order_maps", &self.post_order_map)
.field("nodes", &self.nodes.iter_enumerated().collect::<BTreeMap<_, _>>())
.fi... | fmt | identifier_name |
mod.rs | //! Drop range analysis finds the portions of the tree where a value is guaranteed to be dropped
//! (i.e. moved, uninitialized, etc.). This is used to exclude the types of those values from the
//! generator type. See `InteriorVisitor::record` for where the results of this analysis are used.
//!
//! There are three ph... | else {
match self {
Self::Variable(hir_id) => write!(f, "Variable({hir_id:?})"),
Self::Temporary(hir_id) => write!(f, "Temporary({hir_id:?})"),
}
}
})
}
}
impl TrackedValue {
fn hir_id(&self) -> HirId {
match s... | {
write!(f, "{}", tcx.hir().node_to_string(self.hir_id()))
} | conditional_block |
mod.rs | //! Drop range analysis finds the portions of the tree where a value is guaranteed to be dropped
//! (i.e. moved, uninitialized, etc.). This is used to exclude the types of those values from the
//! generator type. See `InteriorVisitor::record` for where the results of this analysis are used.
//!
//! There are three ph... |
fn node_mut(&mut self, id: PostOrderId) -> &mut NodeInfo {
let size = self.num_values();
self.nodes.ensure_contains_elem(id, || NodeInfo::new(size))
}
fn add_control_edge(&mut self, from: PostOrderId, to: PostOrderId) {
trace!("adding control edge from {:?} to {:?}", from, to);
... | {
self.tracked_value_map.len()
} | identifier_body |
forward_chain_bandaid.py | #!/usr/bin/python
# -*- coding: utf-8 -*-
# vim: expandtab:tabstop=4:shiftwidth=4
#FIXME: This script is not packaged. That goes against team policy.
#FIXME: This script must be removed or packaged.
# Script added in violation of policy because:
# 1. we're in a hurry to get it rolled out because of a related, current... |
# assume that source_chain already exists
# flush the source_chain since we're about to recreate its rules
in_data += "-F %s\n" % self.source_chain
in_data += ("\n".join(updated_rules))+"\n"
in_data += "COMMIT\n"
cmd = self._build_restore_cmd()
# as seen on http:... | in_data += ":%s - [0:0]\n" % self.jump_chain | conditional_block |
forward_chain_bandaid.py | #!/usr/bin/python
# -*- coding: utf-8 -*-
# vim: expandtab:tabstop=4:shiftwidth=4
#FIXME: This script is not packaged. That goes against team policy.
#FIXME: This script must be removed or packaged.
# Script added in violation of policy because:
# 1. we're in a hurry to get it rolled out because of a related, current... |
# pylint: enable=too-few-public-methods
# pylint: disable=too-many-instance-attributes
# pylint: disable=too-many-arguments
class TopRule(object):
'''A single rule that should be at the top of the chain'''
def __init__(self, table, source_chain, jump_chain, ver, top_rule, noop_rule):
'''Create the To... | '''A dummy context manager that does nothing so that a 'with' can conditionally do nothing'''
def __enter__(self):
return None
def __exit__(self, exc_type, exc_value, traceback_):
return False | identifier_body |
forward_chain_bandaid.py | #!/usr/bin/python
# -*- coding: utf-8 -*-
# vim: expandtab:tabstop=4:shiftwidth=4
#FIXME: This script is not packaged. That goes against team policy.
#FIXME: This script must be removed or packaged.
# Script added in violation of policy because:
# 1. we're in a hurry to get it rolled out because of a related, current... | # 2. this script should go away within a few weeks when it gets obsoleted by
# https://github.com/openshift/origin/pull/13465
'''
This entire script is a band-aid that needs to be in place until
https://github.com/openshift/origin/pull/13465 is merged and
backported to 3.4 and 3.5 and the hotfix that contains it ... | random_line_split | |
forward_chain_bandaid.py | #!/usr/bin/python
# -*- coding: utf-8 -*-
# vim: expandtab:tabstop=4:shiftwidth=4
#FIXME: This script is not packaged. That goes against team policy.
#FIXME: This script must be removed or packaged.
# Script added in violation of policy because:
# 1. we're in a hurry to get it rolled out because of a related, current... | (self, *args):
'''
Create an iptables-restore or ip6tables-restore command
Return a list of command args suitable for use with subprocess.*
'''
cmd = 'iptables-restore' if self.ver == 'ipv4' else 'ip6tables-restore'
retval = ["/usr/sbin/%s" % cmd, '--noflush', '--table', ... | _build_restore_cmd | identifier_name |
jobOptions_TileLasMon.py | #
# Copyright (C) 2002-2020 CERN for the benefit of the ATLAS collaboration
#
#*****************************************************************
#
# """topOptions file for Tile Laser Reconstruciton and Monitoring in Athena"""
# """This topOptions is intended to test the monitoring code"""
#==========================... | (path, runinput):
run = str(runinput)
while len(run) < 7:
run = '0' + run
files = []
fullname = []
if path.startswith("/castor") :
for f in popen('nsls %(path)s | grep %(run)s' % {'path': path, 'run':run }):
files.append(f)
elif path.startswith("/eos") :
... | FindFile | identifier_name |
jobOptions_TileLasMon.py | #
# Copyright (C) 2002-2020 CERN for the benefit of the ATLAS collaboration
#
#*****************************************************************
#
# """topOptions file for Tile Laser Reconstruciton and Monitoring in Athena"""
# """This topOptions is intended to test the monitoring code"""
#==========================... | print(topSequence.TileLasMon)
import os
# -- use root histos --
# THistService for native root in Athena
if not athenaCommonFlags.isOnline() or storeHisto or athenaCommonFlags.isOnlineStateless():
#theApp.HistogramPersistency = "ROOT"
if not hasattr(svcMgr,"THistSvc"):
from GaudiSvc.GaudiSvcConf impo... |
topSequence.TileLasMon.AthenaMonTools += [ TileLasDQFragMon ];
print(TileLasDQFragMon) | random_line_split |
jobOptions_TileLasMon.py | #
# Copyright (C) 2002-2020 CERN for the benefit of the ATLAS collaboration
#
#*****************************************************************
#
# """topOptions file for Tile Laser Reconstruciton and Monitoring in Athena"""
# """This topOptions is intended to test the monitoring code"""
#==========================... |
if not 'FileNameVec' in dir():
if not 'FileName' in dir():
tmp = FindFile(InputDirectory,RunNumber)
FileNameVec = tmp[0]
FormattedRunNumber = tmp[1]
else:
FileNameVec = [ InputDirectory+'/'+FileName ]
FormattedRunNumber ... | if InputDirectory=="." or RunNumber<10:
RunFromLocal=True
else:
RunFromLocal=False | conditional_block |
jobOptions_TileLasMon.py | #
# Copyright (C) 2002-2020 CERN for the benefit of the ATLAS collaboration
#
#*****************************************************************
#
# """topOptions file for Tile Laser Reconstruciton and Monitoring in Athena"""
# """This topOptions is intended to test the monitoring code"""
#==========================... |
# include Flags jobOption
include( "TileMonitoring/TileRec_FlagOptions.py" )
## get a handle to the default top-level algorithm sequence
from AthenaCommon.AlgSequence import AlgSequence
topSequence = AlgSequence()
# Get a handle to the ServiceManager
from AthenaCommon.AppMgr import ServiceMgr as svcMgr
from AthenaC... | run = str(runinput)
while len(run) < 7:
run = '0' + run
files = []
fullname = []
if path.startswith("/castor") :
for f in popen('nsls %(path)s | grep %(run)s' % {'path': path, 'run':run }):
files.append(f)
elif path.startswith("/eos") :
for f in popen(... | identifier_body |
trainer.py | import logging
import os.path as osp
import queue
import sys
import threading
import time
from collections import OrderedDict
import torch
from det3d import torchie
from . import hooks
from .checkpoint import load_checkpoint, save_checkpoint
from .hooks import (
CheckpointHook,
Hook,
IterTimerHook,
Lr... |
else:
return model(example, return_loss=False)
def train(self, data_loader, epoch, **kwargs):
self.model.train()
self.mode = "train"
self.data_loader = data_loader
self.length = len(data_loader)
self._max_iters = self._max_epochs * self.length
s... | losses = model(example, return_loss=True)
self.call_hook("after_forward")
loss, log_vars = parse_second_losses(losses)
del losses
outputs = dict(
loss=loss, log_vars=log_vars, num_samples=-1 # TODO: FIX THIS
)
self.call_hook("afte... | conditional_block |
trainer.py | import logging
import os.path as osp
import queue
import sys
import threading
import time
from collections import OrderedDict
import torch
from det3d import torchie
from . import hooks
from .checkpoint import load_checkpoint, save_checkpoint
from .hooks import (
CheckpointHook,
Hook,
IterTimerHook,
Lr... | self,
model,
batch_processor,
optimizer=None,
lr_scheduler=None,
work_dir=None,
log_level=logging.INFO,
logger=None,
**kwargs,
):
assert callable(batch_processor)
self.model = model
self.optimizer = optimizer
sel... | random_line_split | |
trainer.py | import logging
import os.path as osp
import queue
import sys
import threading
import time
from collections import OrderedDict
import torch
from det3d import torchie
from . import hooks
from .checkpoint import load_checkpoint, save_checkpoint
from .hooks import (
CheckpointHook,
Hook,
IterTimerHook,
Lr... | (self, optimizer):
"""Init the optimizer
Args:
optimizer (dict or :obj:`~torch.optim.Optimizer`)
Returns:
:obj:`~torch.optim.Optimizer`
Examples:
>>> optimizer = dict(type='SGD', lr=0.01, momentum=0.9)
>>> type(runner.init_optimizer(opti... | init_optimizer | identifier_name |
trainer.py | import logging
import os.path as osp
import queue
import sys
import threading
import time
from collections import OrderedDict
import torch
from det3d import torchie
from . import hooks
from .checkpoint import load_checkpoint, save_checkpoint
from .hooks import (
CheckpointHook,
Hook,
IterTimerHook,
Lr... | """ A training helper for PyTorch
Args:
model:
batch_processor:
optimizer:
workdir:
log_level:
logger:
"""
def __init__(
self,
model,
batch_processor,
optimizer=None,
lr_scheduler=None,
work_dir=None,
l... | identifier_body | |
path_planning.py | #!/usr/bin/python2
# -*- coding: UTF-8 -*-
# coding: utf-8
#!/usr/bin/env python
'''
发布轨迹信息
path.x; path.y; c_speed;
'''
import numpy as np
import matplotlib.pyplot as plt
import copy
import math
from cubic_spline import Spline2D
from polynomials import QuarticPolynomial, QuinticPolynomial
import time
import... | GPS_y = GPS_y - zero_cord_y
plt.plot(GPS_x,GPS_y, "-r", label="GPS point ")
plt.plot()
plt.show()
return GPS_x, GPS_y
class Info(object):
def __init__(self):
self.CurrGPS_lat = float(-1)
self.CurrGPS_lon = float(-1)
self.CurrentVelocity = float(-1)
self.Targ... | #print("cy:",cy)
zero_cord_x = GPS_x[0]
zero_cord_y = GPS_y[0]
GPS_x = GPS_x - zero_cord_x | random_line_split |
path_planning.py | #!/usr/bin/python2
# -*- coding: UTF-8 -*-
# coding: utf-8
#!/usr/bin/env python
'''
发布轨迹信息
path.x; path.y; c_speed;
'''
import numpy as np
import matplotlib.pyplot as plt
import copy
import math
from cubic_spline import Spline2D
from polynomials import QuarticPolynomial, QuinticPolynomial
import time
import... | ##############################
def load_global_path():
global zero_cord_x,zero_cord_y
bet = 0.1
blank = [] #buffer
white = [] #buffer
yellow = [] ... | .cos(csp.calc_yaw(i_s)+math.pi / 2.0)
road_right_iy = iy - MAX_ROAD_WIDTH/2 * math.sin(csp.calc_yaw(i_s)+math.pi / 2.0)
road_left_x.append(road_left_ix)
road_left_y.append(road_left_iy)
road_right_x.append(road_right_ix)
road_right_y.append(road_right_iy)
return road_left_x, ... | identifier_body |
path_planning.py | #!/usr/bin/python2
# -*- coding: UTF-8 -*-
# coding: utf-8
#!/usr/bin/env python
'''
发布轨迹信息
path.x; path.y; c_speed;
'''
import numpy as np
import matplotlib.pyplot as plt
import copy
import math
from cubic_spline import Spline2D
from polynomials import QuarticPolynomial, QuinticPolynomial
import time
import... | gnss_message', GNSS_CAN, self.FeedbackCallbackGPSIMU,queue_size = 10) #订阅GPS数据
rospy.Subscriber("Motor_Feedback_mssage", Motor_Feedback,self.RVcallback,queue_size = 10)
def FeedbackCallbackGPSIMU(self, msg):
self.CurrGPS_lat = msg.latitude
self.Curr... | criber(' | identifier_name |
path_planning.py | #!/usr/bin/python2
# -*- coding: UTF-8 -*-
# coding: utf-8
#!/usr/bin/env python
'''
发布轨迹信息
path.x; path.y; c_speed;
'''
import numpy as np
import matplotlib.pyplot as plt
import copy
import math
from cubic_spline import Spline2D
from polynomials import QuarticPolynomial, QuinticPolynomial
import time
import... | #buffer
GPS_x = [] #所采集预描点的x
GPS_y = [] #所采集预描点的x
#读取预描点
nums, ber = np.loadtxt("/home/robot/Robot/Smart_robot_ws/sr... | #buffer
white = [] #buffer
yellow = [] | conditional_block |
pyNN_target_sim.py | # -*- coding: utf-8 -*-
"""
Building and simulating spiking neural networks using
`pyNN <http://neuralensemble.org/docs/PyNN/>`_.
@author: rbodo
"""
import os
import sys
import time
import warnings
import numpy as np
from six.moves import cPickle
from snntoolbox.utils.utils import confirm_overwrite, is_module_insta... | elf, path, filename):
"""Load the populations in an assembly.
Loads the populations in an assembly that was saved with the
`save_assembly` function.
The term "assembly" refers to pyNN internal nomenclature, where
``Assembly`` is a collection of layers (``Populations``), which i... | ad_assembly(s | identifier_name |
pyNN_target_sim.py | # -*- coding: utf-8 -*-
"""
Building and simulating spiking neural networks using
`pyNN <http://neuralensemble.org/docs/PyNN/>`_.
@author: rbodo
"""
import os
import sys
import time
import warnings
import numpy as np
from six.moves import cPickle
from snntoolbox.utils.utils import confirm_overwrite, is_module_insta... |
def save_connections(self, path):
"""Write parameters of a neural network to disk.
The parameters between two layers are saved in a text file.
They can then be used to connect pyNN populations e.g. with
``sim.Projection(layer1, layer2, sim.FromListConnector(filename))``,
w... | """Write layers of neural network to disk.
The size, structure, labels of all the population of an assembly are
stored in a dictionary such that one can load them again using the
`load_assembly` function.
The term "assembly" refers to pyNN internal nomenclature, where
``Assembl... | identifier_body |
pyNN_target_sim.py | # -*- coding: utf-8 -*-
"""
Building and simulating spiking neural networks using
`pyNN <http://neuralensemble.org/docs/PyNN/>`_.
@author: rbodo
"""
import os
import sys
import time
import warnings
import numpy as np
from six.moves import cPickle
from snntoolbox.utils.utils import confirm_overwrite, is_module_insta... |
def end_sim(self):
self.sim.end()
def save(self, path, filename):
print("Saving model to {}...".format(path))
self.save_assembly(path, filename)
self.save_connections(path)
self.save_biases(path)
print("Done.\n")
def load(self, path, filename):
... | print("Resetting simulator...")
self.sim.reset()
print("Done.") | conditional_block |
pyNN_target_sim.py | # -*- coding: utf-8 -*-
"""
Building and simulating spiking neural networks using
`pyNN <http://neuralensemble.org/docs/PyNN/>`_.
@author: rbodo
"""
import os
import sys
import time
import warnings
import numpy as np
from six.moves import cPickle
from snntoolbox.utils.utils import confirm_overwrite, is_module_insta... | ----------
path: str
Path to directory where connections are saved.
Return
------
Text files containing the layer connections. Each file is named
after the layer it connects to, e.g. ``layer2.txt`` if connecting
layer1 to layer2.
... | NEST.
Parameters | random_line_split |
models.py | # DeerTrees (Django App)
# By Natasha L.
# www.lupinia.net | github.com/lupinia
#
# =================
# Models
# =================
from django.conf import settings
from django.contrib.sites.models import Site
from django.core.exceptions import ValidationError
from django.core.urlresolvers import reverse
from django.d... |
else:
return False
@property
def is_old(self):
if self.cat.always_fresh or not self.admin_owned:
return False
else:
if self.timestamp_mod < (timezone.now() - timedelta(days=365*10)):
return True
elif (self.timestamp_post < (timezone.now() - timedelta(days=365*10))) and (self.timestamp_mod < (... | return True | conditional_block |
models.py | # DeerTrees (Django App)
# By Natasha L.
# www.lupinia.net | github.com/lupinia
#
# =================
# Models
# =================
from django.conf import settings
from django.contrib.sites.models import Site
from django.core.exceptions import ValidationError
from django.core.urlresolvers import reverse
from django.d... |
def save(self, *args, **kwargs):
if self.parent:
self.cached_url = '%s/%s' % (self.parent.cached_url, self.slug)
else:
self.cached_url = self.slug
super(category, self).save(*args, **kwargs)
def can_edit(self, request=False):
if not request:
return (False,'access_norequest')
else:
canview = ... | return self.summary_short | random_line_split |
models.py | # DeerTrees (Django App)
# By Natasha L.
# www.lupinia.net | github.com/lupinia
#
# =================
# Models
# =================
from django.conf import settings
from django.contrib.sites.models import Site
from django.core.exceptions import ValidationError
from django.core.urlresolvers import reverse
from django.d... | (self):
return '%s%s' % (reverse('category', kwargs={'cached_url':self.cat.cached_url,}), self.url)
def __unicode__(self):
return self.title
def get_summary(self,length=255):
if length > 255:
return summarize(body=self.desc, length=length, prefer_long=True)
else:
return summarize(body=self.desc, len... | get_absolute_url | identifier_name |
models.py | # DeerTrees (Django App)
# By Natasha L.
# www.lupinia.net | github.com/lupinia
#
# =================
# Models
# =================
from django.conf import settings
from django.contrib.sites.models import Site
from django.core.exceptions import ValidationError
from django.core.urlresolvers import reverse
from django.d... |
# ALIAS
@property
def rss_description(self):
return self.summary_short
class Meta:
ordering = ['slug',]
class tag_synonym(models.Model):
parent = models.ForeignKey(tag, on_delete=models.CASCADE, related_name='synonyms')
slug = models.SlugField(max_length=200,unique=True)
timestamp_mod = models.DateTime... | return self.get_summary(512) | identifier_body |
util.py | # Copyright (c) 2019-2020 SAP SE or an SAP affiliate company. All rights reserved. This file is
# licensed under the Apache Software License, v. 2 except as noted otherwise in the LICENSE file
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the L... |
def _filter_single_tar(
in_file: tarfile.TarFile,
remove_entries,
):
temp_fh = tempfile.TemporaryFile()
temptar = tarfile.TarFile(fileobj=temp_fh, mode='w')
for tar_info in in_file:
if not tar_info.isfile():
temptar.addfile(tar_info)
continue
if tar_info.... | layer_paths = set(manifest['Layers'])
changed_layer_hashes = [] # [(old, new),]
# copy everything that does not need to be patched
for tar_info in in_tarfile:
if not tar_info.isfile():
out_tarfile.addfile(tar_info)
continue
# cfg needs to be rewritten - so do not cp... | identifier_body |
util.py | # Copyright (c) 2019-2020 SAP SE or an SAP affiliate company. All rights reserved. This file is
# licensed under the Apache Software License, v. 2 except as noted otherwise in the LICENSE file
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the L... | (
image_file,
out_file,
remove_entries,
):
ci.util.existing_file(image_file)
if not remove_entries:
raise ValueError('remove_entries must not be empty')
# allow absolute paths
remove_entries = [e.lstrip('/') for e in remove_entries]
with tarfile.open(image_file) as tf:
m... | filter_container_image | identifier_name |
util.py | # Copyright (c) 2019-2020 SAP SE or an SAP affiliate company. All rights reserved. This file is
# licensed under the Apache Software License, v. 2 except as noted otherwise in the LICENSE file
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the L... | image_reference=target_ref,
digest=(layer_digest := 'sha256:' + layer_hash.hexdigest()),
octets_count=leng,
data=f,
)
# update copy of layers-list with new layer
new_layer = dataclasses.replace(layer, digest=layer_diges... | f.write(chunk)
f.seek(0)
oci_client.put_blob( | random_line_split |
util.py | # Copyright (c) 2019-2020 SAP SE or an SAP affiliate company. All rights reserved. This file is
# licensed under the Apache Software License, v. 2 except as noted otherwise in the LICENSE file
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the L... |
if tar_info.name.lstrip('./') in remove_entries:
logging.debug(f'purging entry: {tar_info.name}')
continue
# copy entry
entry = in_file.extractfile(tar_info)
temptar.addfile(tar_info, fileobj=entry)
size = temp_fh.tell()
temp_fh.flush()
temp_fh.see... | temptar.addfile(tar_info)
continue | conditional_block |
kibana.py | # -*- coding: utf-8 -*-
"""Kibana module."""
import pandas
import requests
import json
from . import util
class Kibana(object):
def __init__(self, host='localhost', port=5601, protocol='http',
verify_certs=True, **kwargs):
self._host = host
self._port = port
self._protoco... | # },
# 'title': title,
# 'type': visType,
# }
assert isinstance(viz, Visualization)
visState = viz.visState(title)
searchSourceJSON = {
"index":indexPatternUID,
"filter":[],
"query":{"language":"kuery","query":""}
... | # ],
# 'params': {
# 'type': 'histogram' | random_line_split |
kibana.py | # -*- coding: utf-8 -*-
"""Kibana module."""
import pandas
import requests
import json
from . import util
class Kibana(object):
def __init__(self, host='localhost', port=5601, protocol='http',
verify_certs=True, **kwargs):
self._host = host
self._port = port
self._protoco... |
def agg2(self):
return {
"id": "2",
"enabled": True,
"type": "histogram",
"schema": "segment",
"params": {
"field": self.field,
"interval": self.interval,
"extended_bounds": {}
}
... | super(Histogram, self).__init__(field)
self.visType = 'histogram'
self.interval = interval | identifier_body |
kibana.py | # -*- coding: utf-8 -*-
"""Kibana module."""
import pandas
import requests
import json
from . import util
class Kibana(object):
def __init__(self, host='localhost', port=5601, protocol='http',
verify_certs=True, **kwargs):
self._host = host
self._port = port
self._protoco... |
how = how if isinstance(how, list) else [how]
url = self.kibanaUrl(*args, **kwargs)
if 'print' in how:
print(f"Open: {url}")
if 'webbrowser' in how:
import webbrowser
webbrowser.open(url)
if 'jupyter' in how or 'ipython' in how:
fr... | how = 'jupyter' if util.__IS_JUPYTER else 'webbrowser'
# TODO can we figure out "non-interactive" to put how='print' then? | conditional_block |
kibana.py | # -*- coding: utf-8 -*-
"""Kibana module."""
import pandas
import requests
import json
from . import util
class Kibana(object):
def __init__(self, host='localhost', port=5601, protocol='http',
verify_certs=True, **kwargs):
self._host = host
self._port = port
self._protoco... | (HorizontalBar):
def __init__(self, field, size=20):
super(TagCloud, self).__init__(field, size)
self.visType = 'tagcloud'
self.params = {
"scale": "linear",
"orientation": "single",
"minFontSize": 18,
"maxFontSize": 72,
"showLabel... | TagCloud | identifier_name |
mod.rs | //! Code to compute example inputs given a backtrace.
use crate::grammar::repr::*;
use crate::message::builder::InlineBuilder;
use crate::message::Content;
use crate::style::Style;
use crate::tls::Tls;
use ascii_canvas::AsciiView;
use std::{
cmp::Ordering,
fmt::{Debug, Error, Formatter},
};
#[cfg(test)]
mod t... |
fn starting_positions(&self, lengths: &[usize]) -> Vec<usize> {
lengths
.iter()
.scan(0, |counter, &len| {
let start = *counter;
// Leave space for "NT " (if "NT" is the name
// of the nonterminal).
*counter = start +... | {
let lengths = self.lengths();
let positions = self.positions(&lengths);
InlineBuilder::new()
.push(Box::new(ExamplePicture {
example: self,
positions,
styles,
}))
.indented()
.end()
} | identifier_body |
mod.rs | //! Code to compute example inputs given a backtrace.
use crate::grammar::repr::*;
use crate::message::builder::InlineBuilder;
use crate::message::Content;
use crate::style::Style;
use crate::tls::Tls;
use ascii_canvas::AsciiView;
use std::{
cmp::Ordering,
fmt::{Debug, Error, Formatter},
};
#[cfg(test)]
mod t... | (&self) -> Vec<::ascii_canvas::Row> {
let this = self.clone();
let content = this.into_picture(ExampleStyles::default());
let min_width = content.min_width();
let canvas = content.emit_to_canvas(min_width);
canvas.to_strings()
}
fn paint_on(&self, styles: &ExampleStyles,... | paint_unstyled | identifier_name |
mod.rs | //! Code to compute example inputs given a backtrace.
use crate::grammar::repr::*;
use crate::message::builder::InlineBuilder;
use crate::message::Content;
use crate::style::Style;
use crate::tls::Tls;
use ascii_canvas::AsciiView;
use std::{
cmp::Ordering,
fmt::{Debug, Error, Formatter},
};
#[cfg(test)]
mod t... | ///
/// The top-line is the `symbols` vector. The groupings below are
/// stored in the `reductions` vector, in order from smallest to
/// largest (they are always properly nested). The `cursor` field
/// indicates the current lookahead token.
///
/// The `symbols` vector is actually `Option<Symbol>` to account
/// for... | /// ``` | random_line_split |
install.go | // Copyright 2021 Ross Light
//
// 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
//
// https://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in ... |
func sortedStringDictKeys(d starlark.StringDict) []string {
keys := make([]string, 0, len(d))
for k := range d {
keys = append(keys, k)
}
sort.Strings(keys)
return keys
}
| {
return sortedStringDictKeys(mod.attrs)
} | identifier_body |
install.go | // Copyright 2021 Ross Light
//
// 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
//
// https://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in ... | return err
}
return nil
}
const threadContextKey = "zombiezen.com/go/biome.Context"
func threadContext(t *starlark.Thread) context.Context {
ctx, _ := t.Local(threadContextKey).(context.Context)
if ctx == nil {
ctx = context.Background()
}
return ctx
}
type envValue struct {
vars *starlark.Dict
pr... | return fmt.Errorf("install return value: %w", err)
}
if err := writeBiomeEnvironment(db, rec.id, rec.env.Merge(installEnv)); err != nil { | random_line_split |
install.go | // Copyright 2021 Ross Light
//
// 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
//
// https://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in ... |
return starlark.String(biome.JoinPath(bio.Describe(), stringArgs...)), nil
}),
"exists": starlark.NewBuiltin("path.exists", func(thread *starlark.Thread, fn *starlark.Builtin, args starlark.Tuple, kwargs []starlark.Tuple) (starlark.Value, error) {
var path string
if err := starlark.UnpackArgs(fn.Name... | {
arg, ok := starlark.AsString(args.Index(i))
if !ok {
return nil, fmt.Errorf("%s: could not convert arg[%d] to string", fn.Name(), i)
}
stringArgs = append(stringArgs, arg)
} | conditional_block |
install.go | // Copyright 2021 Ross Light
//
// 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
//
// https://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in ... | () []string {
return sortedStringDictKeys(mod.attrs)
}
func sortedStringDictKeys(d starlark.StringDict) []string {
keys := make([]string, 0, len(d))
for k := range d {
keys = append(keys, k)
}
sort.Strings(keys)
return keys
}
| AttrNames | identifier_name |
mod.rs | /* File_config_functionalities_pmz */
// conditions:
/*
exec trait: [alias:(file/any)] [operations] [path/name] [parameters/--options]
Read:Content _ none
Write:Content _ String : if use multi line content ->
check len()::Enum -> i32|&str
Update:Content _ String
... | println!(
"test {:?} ",
(match_inside_brac.is_match(test), test.trim_matches(x))
);
} | println!("t {}", test);
let x: &[_] = &['[', ']']; | random_line_split |
mod.rs | /* File_config_functionalities_pmz */
// conditions:
/*
exec trait: [alias:(file/any)] [operations] [path/name] [parameters/--options]
Read:Content _ none
Write:Content _ String : if use multi line content ->
check len()::Enum -> i32|&str
Update:Content _ String
... | {
let match_inside_brac = regex::Regex::new(r"^\[(.*)\]$").unwrap();
let test = "[Apple sauce bananan ba;;;a]";
println!("t {}", test);
let x: &[_] = &['[', ']'];
println!(
"test {:?} ",
(match_inside_brac.is_match(test), test.trim_matches(x))
);
} | identifier_body | |
mod.rs | /* File_config_functionalities_pmz */
// conditions:
/*
exec trait: [alias:(file/any)] [operations] [path/name] [parameters/--options]
Read:Content _ none
Write:Content _ String : if use multi line content ->
check len()::Enum -> i32|&str
Update:Content _ String
... | (result: &str) -> OriResult<String> {
if result.is_empty() {
let empty_err = FileError::new().set_message("The Folder is Empty inside");
Err(empty_err)
} else {
Ok(result.trim().to_string())
}
}
impl Operation for Fileconfig {
fn read(&self) -> OriResult<String> {
let fil... | checkempty | identifier_name |
sketch.js | //playerSprite
let pharahSprite;
//crosshair
let crosshairSprite;
//player
let pharah;
//enemies!!!!!
let enemy1sprite;
let enemy2sprite;
let enemy3sprite;
//enemy array
let enemyArr;
//enemyImage array
let images;
let enemyNum;
let bulletSprite;
//gamestate, 0 = menu, 1 = gameplay
let state;
//boring initializer... | {
score += 1;
if (score >= 6)
{
state = 2;
}
}
//Pharah takes damage if she touches people
if(pharah.detectHit(enemyArr[i].xPos, enemyArr[i].yPos))
{
pharah.health -= 10;
}
}
}
}
//standard gameov... | random_line_split | |
sketch.js | //playerSprite
let pharahSprite;
//crosshair
let crosshairSprite;
//player
let pharah;
//enemies!!!!!
let enemy1sprite;
let enemy2sprite;
let enemy3sprite;
//enemy array
let enemyArr;
//enemyImage array
let images;
let enemyNum;
let bulletSprite;
//gamestate, 0 = menu, 1 = gameplay
let state;
//boring initializer... |
//preload assets
function preload()
{
pharahSprite = loadImage("images/pharahSprite_small.png");
bg = loadImage("images/bg.png");
crosshairSprite = loadImage("images/crosshair.png");
bulletSprite = loadImage("images/bullet.png");
soundFormats("mp3");
shotSound = loadSound("sounds/exp.mp3");
//enemies, p... | {
// grab the range data as an integer
rangeData = int(clickedRange.value);
} | identifier_body |
sketch.js | //playerSprite
let pharahSprite;
//crosshair
let crosshairSprite;
//player
let pharah;
//enemies!!!!!
let enemy1sprite;
let enemy2sprite;
let enemy3sprite;
//enemy array
let enemyArr;
//enemyImage array
let images;
let enemyNum;
let bulletSprite;
//gamestate, 0 = menu, 1 = gameplay
let state;
//boring initializer... | ()
{
//contain logic within borders
if (this.xPos + this.sprite.width > width)
{
this.xSpeed = 0;
this.collided = true;
this.xPos = width - this.sprite.width
}
if (this.xPos < 0)
{
this.xSpeed = 0;
this.collided = true;
this.xPos = 0;
}
if (this.yPos... | move | identifier_name |
sketch.js | //playerSprite
let pharahSprite;
//crosshair
let crosshairSprite;
//player
let pharah;
//enemies!!!!!
let enemy1sprite;
let enemy2sprite;
let enemy3sprite;
//enemy array
let enemyArr;
//enemyImage array
let images;
let enemyNum;
let bulletSprite;
//gamestate, 0 = menu, 1 = gameplay
let state;
//boring initializer... |
else if (this.left)
{
this.xSpeed += this.gravity;
if (this.xSpeed > 0)
{
this.right = true;
this.left = false;
}
}
//the standard movement. Add gravity, speed to position
this.ySpeed += this.gravity;
this.xPos += this.xSpeed;
this.yPos += this.ySpee... | {
this.xSpeed -= this.gravity;
if (this.xSpeed < 0)
{
this.right = false;
this.left = true;
}
} | conditional_block |
FactorPropertyController.js | Ext.define('Factor.controller.panel.FactorPropertyController', {
extend: 'Factor.controller.Base',
stores: [
"FactorPropertyStore",
"FactorDataStore"
],
models: [
"FactorPropertyModel"
],
views: [
// 'window.FactorWindow'
],
controller... | Ext.MessageBox.alert('提示', '您选中的属性包含固有属性，因子固有属性不能删除！');
return;
}
}
Ext.MessageBox.confirm('确认', '确定要删除选中因子属性?', function(btn){
if('yes'===btn){
Store.remove(sm.getSelection());
if (Store.getCount() > 0) {
sm.select(0);
}
var delstores= Store.get... | if("1"===(sm.getSelection()[i].get('prototype')+"")){ | random_line_split |
FactorPropertyController.js | Ext.define('Factor.controller.panel.FactorPropertyController', {
extend: 'Factor.controller.Base',
stores: [
"FactorPropertyStore",
"FactorDataStore"
],
models: [
"FactorPropertyModel"
],
views: [
// 'window.FactorWindow'
],
controller... | (deleteJson)
},
success: function(response, options) {
var factorSelectModel = me.getFactorGrid().selModel;
if(0 < factorSelectModel.selected.length){
parentUuid = factorSelectModel.selected.items[0].get('uuid');
}
Factor.App.getPanelFactorPropertyControllerController(... | }
Ext.Ajax.request({
url: '../work-platform/deleteFactorInstances.do',
params: {
deleteFactorInstances:Ext.encode | conditional_block |
train_ibp.py | import numpy as np
import keras.backend as K
from keras.optimizers import Adam
from keras.preprocessing.image import ImageDataGenerator
from keras.utils import to_categorical
from keras.callbacks import EarlyStopping, LearningRateScheduler, ModelCheckpoint, \
ReduceLROnPlateau, TensorBoard
... | (y_true, y_pred):
return model.robust_accuracy
if config.load_weights_from is not None:
model.load_weights(config.load_weights_from)
metrics = ["accuracy", robust_acc]
model.compile(loss=loss, optimizer=Adam(lr=config.lr), metrics=metrics)
model.summary()
##################
# Setup training #
#############... | robust_acc | identifier_name |
train_ibp.py | import numpy as np
import keras.backend as K
from keras.optimizers import Adam
from keras.preprocessing.image import ImageDataGenerator
from keras.utils import to_categorical
from keras.callbacks import EarlyStopping, LearningRateScheduler, ModelCheckpoint, \
ReduceLROnPlateau, TensorBoard
... |
else:
mean, std = None, None
if config.model_name == "SmallCNN":
model = SmallCNN(input_shape=input_shape)
elif config.model_name == "MediumCNN":
model = MediumCNN(input_shape=input_shape)
elif config.model_name == "LargeCNN":
model = LargeCNN(input_shape=input_shape)
elif config.model_name == "LargeC... | mean, std = x_train.mean(axis=(0, 1, 2)), x_train.std(axis=(0, 1, 2)) + 1e-6
x_train = (x_train - mean) / std
x_valid = (x_valid - mean) / std
print("Normalising channels with values", mean, std) | conditional_block |
train_ibp.py | import numpy as np
import keras.backend as K
from keras.optimizers import Adam
from keras.preprocessing.image import ImageDataGenerator
from keras.utils import to_categorical
from keras.callbacks import EarlyStopping, LearningRateScheduler, ModelCheckpoint, \
ReduceLROnPlateau, TensorBoard
... |
if config.load_weights_from is not None:
model.load_weights(config.load_weights_from)
metrics = ["accuracy", robust_acc]
model.compile(loss=loss, optimizer=Adam(lr=config.lr), metrics=metrics)
model.summary()
##################
# Setup training #
##################
# Prepare model model saving directory
mode... | return model.robust_accuracy | identifier_body |
train_ibp.py | import numpy as np
import keras.backend as K
from keras.optimizers import Adam
from keras.preprocessing.image import ImageDataGenerator
from keras.utils import to_categorical
from keras.callbacks import EarlyStopping, LearningRateScheduler, ModelCheckpoint, \
ReduceLROnPlateau, TensorBoard
... | batch_size=config.batch_size,
callbacks=callbacks)
else:
print('Using real-time data augmentation.')
shift = 4 if config.dataset == "CIFAR10" else 2
# This will do preprocessing and realtime data augmentation:
datagen = ImageDataGenerator(
# randomly rotate images in ... | random_line_split | |
main.rs | use crossterm::{
cursor,
event::{self, DisableMouseCapture, EnableMouseCapture, Event},
queue,
style::{self, Color::Rgb, Colors, Print, SetColors},
terminal,
};
use serde::{Deserialize, Serialize};
use std::{
cmp::min,
collections::HashMap,
env, fs,
io::{self, Write},
iter,
p... |
dir: Direction,
skip: bool,
}
#[derive(Clone)]
enum Direction {
Next,
Prev,
}
pub struct Bk<'a> {
quit: bool,
chapters: Vec<epub::Chapter>,
// position in the book
chapter: usize,
line: usize,
mark: HashMap<char, (usize, usize)>,
links: HashMap<String, (usize, usize)>,
... | archArgs { | identifier_name |
main.rs | use crossterm::{
cursor,
event::{self, DisableMouseCapture, EnableMouseCapture, Event},
queue,
style::{self, Color::Rgb, Colors, Print, SetColors},
terminal,
};
use serde::{Deserialize, Serialize};
use std::{
cmp::min,
collections::HashMap,
env, fs,
io::{self, Write},
iter,
p... | }
false
}
}
}
}
#[derive(argh::FromArgs)]
/// read a book
struct Args {
#[argh(positional)]
path: Option<String>,
/// background color (eg 282a36)
#[argh(option)]
bg: Option<String>,
/// foreground color (eg f8f8f2)
#[argh(option)]
... | self.jump_byte(c, index);
return true;
}
| conditional_block |
main.rs | use crossterm::{
cursor,
event::{self, DisableMouseCapture, EnableMouseCapture, Event},
queue,
style::{self, Color::Rgb, Colors, Print, SetColors},
terminal,
};
use serde::{Deserialize, Serialize};
use std::{
cmp::min,
collections::HashMap,
env, fs,
io::{self, Write},
iter,
p... |
let byte = bk.chapters[bk.chapter].lines[bk.line].0;
state
.save
.files
.insert(state.path.clone(), (bk.chapter, byte));
state.save.last = state.path;
let serialized = ron::to_string(&state.save).unwrap();
fs::write(state.save_path, serialized).unwrap_or_else(|e| {
p... | random_line_split | |
colors.rs | use std::io;
use std::mem;
use std::os::windows::io::AsRawHandle;
use std::str::Bytes;
use windows_sys::Win32::Foundation::HANDLE;
use windows_sys::Win32::System::Console::{
GetConsoleScreenBufferInfo, SetConsoleTextAttribute, CONSOLE_SCREEN_BUFFER_INFO,
FOREGROUND_BLUE as FG_BLUE, FOREGROUND_GREEN as FG_GREEN... | cur_attr: TextAttributes,
}
#[derive(Clone, Copy, Debug)]
enum HandleKind {
Stdout,
Stderr,
}
impl HandleKind {
fn handle(&self) -> HANDLE {
match *self {
HandleKind::Stdout => io::stdout().as_raw_handle() as HANDLE,
HandleKind::Stderr => io::stderr().as_raw_handle() as... | #[derive(Debug)]
pub struct Console {
kind: HandleKind,
start_attr: TextAttributes, | random_line_split |
colors.rs | use std::io;
use std::mem;
use std::os::windows::io::AsRawHandle;
use std::str::Bytes;
use windows_sys::Win32::Foundation::HANDLE;
use windows_sys::Win32::System::Console::{
GetConsoleScreenBufferInfo, SetConsoleTextAttribute, CONSOLE_SCREEN_BUFFER_INFO,
FOREGROUND_BLUE as FG_BLUE, FOREGROUND_GREEN as FG_GREEN... |
}
| {
let attr = "leading bytes \x1b[1m trailing bytes";
let parsed = driver(parse_attr, attr).unwrap();
assert_eq!(parsed, b'1');
} | identifier_body |
colors.rs | use std::io;
use std::mem;
use std::os::windows::io::AsRawHandle;
use std::str::Bytes;
use windows_sys::Win32::Foundation::HANDLE;
use windows_sys::Win32::System::Console::{
GetConsoleScreenBufferInfo, SetConsoleTextAttribute, CONSOLE_SCREEN_BUFFER_INFO,
FOREGROUND_BLUE as FG_BLUE, FOREGROUND_GREEN as FG_GREEN... | () -> io::Result<Console> {
Self::create_for_stream(HandleKind::Stdout)
}
/// Create a new Console to stderr.
///
/// If there was a problem creating the console, then an error is returned.
pub fn stderr() -> io::Result<Console> {
Self::create_for_stream(HandleKind::Stderr)
}
... | stdout | identifier_name |
log.go | package log
import (
"errors"
"github.com/qjpcpu/filelog"
"github.com/qjpcpu/log/logging"
"io"
syslog "log"
"os"
"path/filepath"
"runtime/debug"
"strings"
"sync"
)
type moduleLoggers struct {
loggers map[string]*logWrapper
*sync.RWMutex
}
type logWrapper struct {
*logging.Logger
option *LogOptio... | filename
return lo
}
// SetLevel set log level
func (lo *LogOption) SetLevel(level string) *LogOption {
lo.Level = parseLogLevel(level)
return lo
}
// SetTypedLevel set log level
func (lo *LogOption) SetTypedLevel(level Level) *LogOption {
lo.Level = level
return lo
}
// SetFormat set log format
func (lo *LogO... | gFile = | identifier_name |
log.go | package log
import (
"errors"
"github.com/qjpcpu/filelog"
"github.com/qjpcpu/log/logging"
"io"
syslog "log"
"os"
"path/filepath"
"runtime/debug"
"strings"
"sync"
)
type moduleLoggers struct {
loggers map[string]*logWrapper
*sync.RWMutex
}
type logWrapper struct {
*logging.Logger
option *LogOptio... | count := 0
for i, ch := range stackInfo {
if ch == '\n' {
if count == 0 {
start = i
} else if count == 4 {
stackInfo = append(stackInfo[0:start+1], stackInfo[i+1:]...)
break
}
count++
}
}
var extra string
if len(desc) > 0 && desc[0] != "" {
extra = "[" + desc[0] + "]"
... | func MustNoErr(err error, desc ...string) {
if err != nil {
stackInfo := debug.Stack()
start := 0 | random_line_split |
log.go | package log
import (
"errors"
"github.com/qjpcpu/filelog"
"github.com/qjpcpu/log/logging"
"io"
syslog "log"
"os"
"path/filepath"
"runtime/debug"
"strings"
"sync"
)
type moduleLoggers struct {
loggers map[string]*logWrapper
*sync.RWMutex
}
type logWrapper struct {
*logging.Logger
option *LogOptio... | LogFp, "", 0)
backendInfoFormatter := logging.NewBackendFormatter(backendInfo, format)
backendInfoLeveld := logging.AddModuleLevel(backendInfoFormatter)
backendInfoLeveld.SetLevel(opt.Level.loggingLevel(), "")
leveldBackend = backendInfoLeveld
backends = append(backends, backendInfoLeveld)
opt.files = appen... | ", filename, err)
}
backendInfo := logging.NewLogBackend(info | conditional_block |
log.go | package log
import (
"errors"
"github.com/qjpcpu/filelog"
"github.com/qjpcpu/log/logging"
"io"
syslog "log"
"os"
"path/filepath"
"runtime/debug"
"strings"
"sync"
)
type moduleLoggers struct {
loggers map[string]*logWrapper
*sync.RWMutex
}
type logWrapper struct {
*logging.Logger
option *LogOptio... | ...interface{}) {
if defaultLgr == nil {
return
}
defaultLgr.Fatalf(strings.TrimSpace(strings.Repeat("%+v ", len(args))), args...)
}
// Error write leveled log
func Error(args ...interface{}) {
if defaultLgr == nil {
return
}
defaultLgr.Errorf(strings.TrimSpace(strings.Repeat("%+v ", len(args))), args...)
}... | ltLgr.Criticalf(strings.TrimSpace(strings.Repeat("%+v ", len(args))), args...)
}
// Fatal write leveled log
func Fatal(args | identifier_body |
appendlist.rs | use std::cell::{Cell, UnsafeCell};
use std::fmt::{self, Debug};
use std::iter::FromIterator;
use std::ops::Index;
use crate::common::{chunk_size, chunk_start, index_chunk};
/// A list that can be appended to while elements are borrowed
///
/// This looks like a fairly bare-bones list API, except that it has a `push`
... |
/// Create a new `AppendList`
pub fn new() -> Self {
Self {
chunks: UnsafeCell::new(Vec::new()),
len: Cell::new(0),
}
}
/// Append an item to the end
///
/// Note that this does not require `mut`.
pub fn push(&self, item: T) {
self.check_inv... | {
#[cfg(test)]
{
if self.len.get() > 0 {
// Correct number of chunks
assert_eq!(index_chunk(self.len.get() - 1), self.chunks().len() - 1);
// Every chunk holds enough items
for chunk_id in 0..self.chunks().len() {
... | identifier_body |
appendlist.rs | use std::cell::{Cell, UnsafeCell};
use std::fmt::{self, Debug};
use std::iter::FromIterator;
use std::ops::Index;
use crate::common::{chunk_size, chunk_start, index_chunk};
/// A list that can be appended to while elements are borrowed
///
/// This looks like a fairly bare-bones list API, except that it has a `push`
... | (&self) -> usize {
self.check_invariants();
self.len.get()
}
/// Get an item from the list, if it is in bounds
///
/// Returns `None` if the `index` is out-of-bounds. Note that you can also
/// index with `[]`, which will panic on out-of-bounds.
pub fn get(&self, index: usize) ... | len | identifier_name |
appendlist.rs | use std::cell::{Cell, UnsafeCell};
use std::fmt::{self, Debug};
use std::iter::FromIterator;
use std::ops::Index;
use crate::common::{chunk_size, chunk_start, index_chunk};
/// A list that can be appended to while elements are borrowed
///
/// This looks like a fairly bare-bones list API, except that it has a `push`
... | impl<'l, T> Iterator for Iter<'l, T> {
type Item = &'l T;
fn next(&mut self) -> Option<Self::Item> {
let item = self.list.get(self.index);
self.index += 1;
item
}
fn size_hint(&self) -> (usize, Option<usize>) {
let remaining = self.list.len() - self.index;
(r... | index: usize,
}
| random_line_split |
unified.rs | use std::cmp;
use std::collections::HashSet;
use std::convert::{TryFrom, TryInto};
use std::error::Error;
use std::fmt;
use std::io::Write;
use zcash_encoding::CompactSize;
use crate::kind;
/// The HRP for a Bech32m-encoded mainnet Unified Address.
///
/// Defined in [ZIP 316][zip-0316].
///
/// [zip-0316]: https://z... | else {
typecodes.insert(t);
}
}
if typecodes.iter().all(|t| t.is_transparent()) {
Err(ParseError::OnlyTransparent)
} else {
// All checks pass!
Ok(Address(receivers))
}
}
}
impl Address {
/// Returns the raw encod... | {
return Err(ParseError::BothP2phkAndP2sh);
} | conditional_block |
unified.rs | use std::cmp;
use std::collections::HashSet;
use std::convert::{TryFrom, TryInto};
use std::error::Error;
use std::fmt;
use std::io::Write;
use zcash_encoding::CompactSize;
use crate::kind;
/// The HRP for a Bech32m-encoded mainnet Unified Address.
///
/// Defined in [ZIP 316][zip-0316].
///
/// [zip-0316]: https://z... | {
/// The unified address contains both P2PKH and P2SH receivers.
BothP2phkAndP2sh,
/// The unified address contains a duplicated typecode.
DuplicateTypecode(Typecode),
/// The parsed typecode exceeds the maximum allowed CompactSize value.
InvalidTypecodeValue(u64),
/// The string is an inv... | ParseError | identifier_name |
unified.rs | use std::cmp;
use std::collections::HashSet;
use std::convert::{TryFrom, TryInto};
use std::error::Error;
use std::fmt;
use std::io::Write;
use zcash_encoding::CompactSize;
use crate::kind;
/// The HRP for a Bech32m-encoded mainnet Unified Address.
///
/// Defined in [ZIP 316][zip-0316].
///
/// [zip-0316]: https://z... | // Unknown typecodes are treated as not transparent for the purpose of disallowing
// only-transparent UAs, which can be represented with existing address encodings.
matches!(self, Typecode::P2pkh | Typecode::P2sh)
}
}
/// An error while attempting to parse a string as a Zcash address.
#[de... | impl Typecode {
fn is_transparent(&self) -> bool { | random_line_split |
__init__.py | """
Copyright 2015-2016 Christian Fobel and Ryan Fobel
This file is part of dropbot_dx_plugin.
dropbot_dx_plugin 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 optio... |
return wrapped
return wrapper(_lambda)
def get_unique_path(filepath):
'''
Append `-###` to the base name of a file until a file path is found that
does not exist.
Args
----
filepath (str) : Full file path to target file.
Returns
-------
(path) : Full path w... | f(self, *f_args, **f_kwargs) | conditional_block |
__init__.py | """
Copyright 2015-2016 Christian Fobel and Ryan Fobel
This file is part of dropbot_dx_plugin.
dropbot_dx_plugin 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 optio... |
def get_environment_state(self, master=None, i2c_address=0x27):
'''
Acquire temperature and humidity from Honeywell HIH6000 series
sensor.
[1]: http://sensing.honeywell.com/index.php/ci_id/142171/la_id/1/document/1/re_id/0
'''
if master is None:
master ... | '''
Connect to dropbot-dx instrument.
'''
self.has_environment_data = False
self.environment_sensor_master = None
# if the dropbot dx plugin is installed and enabled, try getting its
# reference
try:
service = get_service_instance_by_name('wheelerlab.... | identifier_body |
__init__.py | """
Copyright 2015-2016 Christian Fobel and Ryan Fobel
This file is part of dropbot_dx_plugin.
dropbot_dx_plugin 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 optio... | (Plugin, AppDataController, StepOptionsController):
"""
This class is automatically registered with the PluginManager.
"""
implements(IPlugin)
version = get_plugin_info(path(__file__).parent).version
plugin_name = get_plugin_info(path(__file__).parent).plugin_name
AppFields = Form.of(Float.... | DropBotDxAccessoriesPlugin | identifier_name |
__init__.py | """
Copyright 2015-2016 Christian Fobel and Ryan Fobel
This file is part of dropbot_dx_plugin.
dropbot_dx_plugin 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 optio... |
###########################################################################
# # Plugin signal handlers #
def get_schedule_requests(self, function_name):
"""
Returns a list of scheduling requests (i.e., ScheduleRequest
instances) for the function specified by function_name.
"... |
if valid:
options['dstat_params_file'] = response['dstat_params_file']
self.set_step_values(options) | random_line_split |
Script_graph_data.py | from os import chdir, listdir, mkdir, remove
from urllib.request import urlretrieve
from tkinter import font as tkFont
from datetime import datetime, timedelta, date
import pathlib, time, tkinter
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import matplotlib.colors as colors
im... |
return Countries_to_annotate, Annotations_mask
def Scatter_graph(COVID_data_scatter, Display_annotations_mask = False):
"""
Plots data entered in parameters
Parameters:
- COVID_data_scatter: Reconstructed dictionnary of the 3 columns the user asked to plot throughout ... | Countries_to_annotate[Country] = Points_to_display[Country_inc] # The country has to be annotated
Annotations_mask[Annotation_slice] = True # All the elements in Annotations_mask in this area are set to True to signify there is now an annotation displayed there
| conditional_block |
Script_graph_data.py | from os import chdir, listdir, mkdir, remove
from urllib.request import urlretrieve
from tkinter import font as tkFont
from datetime import datetime, timedelta, date
import pathlib, time, tkinter
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import matplotlib.colors as colors
im... |
def Scatter_graph(COVID_data_scatter, Display_annotations_mask = False):
"""
Plots data entered in parameters
Parameters:
- COVID_data_scatter: Reconstructed dictionnary of the 3 columns the user asked to plot throughout time
- Display_annotations_mask: Boolean indicat... | """
Tells which countries to annotate and which not to. Since the lists in parameters are sorted by descending order of positivity rate, the countries with higher positivity rates will be examined first and thus annotatd with more priority
Parameters:
- Points_to_display: List of X and Y coordi... | identifier_body |
Script_graph_data.py | from os import chdir, listdir, mkdir, remove
from urllib.request import urlretrieve
from tkinter import font as tkFont
from datetime import datetime, timedelta, date
import pathlib, time, tkinter
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import matplotlib.colors as colors
im... |
X_list_frame, Y_list_frame = zip(*Points_to_display) # Separate X and Y axes and plot the points
scatter = ax.scatter(X_list_frame, Y_list_frame, c = Points_colors, s = np.pi * (Marker_ray*72/fig.dpi)**2, linewidth = 0.5, edgecolors = 'black') # Marker ray is the radius of the circle in pixel... | random_line_split | |
Script_graph_data.py | from os import chdir, listdir, mkdir, remove
from urllib.request import urlretrieve
from tkinter import font as tkFont
from datetime import datetime, timedelta, date
import pathlib, time, tkinter
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import matplotlib.colors as colors
im... | (X_axis_inc = 1, Y_axis_inc = 7, Z_axis_inc = 12, Date_start = None, Date_end = None):
"""
Main routine to execute to download, extract, reconstruct and plot COVID data
Parameters:
- X_axis_inc: Integer, data to use for the X axis. Default is 1 (Total cases per million)
- Y_axis_i... | Main_script | identifier_name |
script.js | ///IMPORTS-----------------------------------------
import screens from './components/screens.js'
import PausedTimeout from './functions/pausedTimeout.js'
import map1 from './maps/map1.js'
import map2 from './maps/map2.js'
import map3 from './maps/map3.js'
import map4 from './maps/map4.js'
import map5 from './maps/map... | (){
for(let key in activeKeys){
delete activeKeys[key]
}
}
function handleVictory(){
clearIntervals()
screens({
title:'Goal reached!',
content:"",
button:"Next Level",
})
state.paused=true
state.completed=true
}
var crashListener = setInte... | deleteKeys | identifier_name |
script.js | ///IMPORTS-----------------------------------------
import screens from './components/screens.js'
import PausedTimeout from './functions/pausedTimeout.js'
import map1 from './maps/map1.js'
import map2 from './maps/map2.js'
import map3 from './maps/map3.js'
import map4 from './maps/map4.js'
import map5 from './maps/map... |
}
function checkCrash(){
if(state.paused) return
let ratio = rotationPercentage()
function checkBoundaries(){
if(
(yPosition + (25 * ratio) ) < 0 | //TOP
((yPosition + mycar.offsetHeight) - (25 * ratio) ) > gameArea.offsetHeight | //BOTTOM
(xPosition - (25 * r... | {
return false
} | conditional_block |
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