file_name large_stringlengths 4 140 | prefix large_stringlengths 0 12.1k | suffix large_stringlengths 0 12k | middle large_stringlengths 0 7.51k | fim_type large_stringclasses 4
values |
|---|---|---|---|---|
printtips.js | turn LODOP.GET_PRINTER_COUNT();
};
//获取打印机
function getPrinterName(LODOP,iPrinterNO) {
return LODOP.GET_PRINTER_NAME(iPrinterNO);
};
/** 小票打印 */
//no,name,vac,price,pay,time,insurance
function printtips(data){
if(!data){
layer.msg("参数异常，打印失败",{icon:1});
return false;
}
var pinstr;
if(data.pin=="1"){
pin... | t(LODOP) {
re | identifier_name | |
printtips.js | ,vac,price,pay,time,insurance
function printtips(data){
if(!data){
layer.msg("参数异常，打印失败",{icon:1});
return false;
}
var pinstr;
if(data.pin=="1"){
pinstr = "第一剂次"
}
if(data.pin=="2"){
pinstr = "第二剂次"
}
if(data.pin=="3"){
pinstr = "第三剂次"
}
if(data.pin=="4"){
pinstr = "第四剂次"
}
if(data.pin=="5"){
... | NTER_NAME(iPrinterNO);
};
/** 小票打印 */
//no,name | identifier_body | |
printtips.js | layer.msg("参数异常，打印失败",{icon:1});
return false;
}
var pinstr;
if(data.pin=="1"){
pinstr = "第一剂次"
}
if(data.pin=="2"){
pinstr = "第二剂次"
}
if(data.pin=="3"){
pinstr = "第三剂次"
}
if(data.pin=="4"){
pinstr = "第四剂次"
}
if(data.pin=="5"){
pinstr = "第五剂次"
}
if(data.impart.group == '17' && data.pin=="1")... | /** 小票打印 */
//no,name,vac,price,pay,time,insurance
function printtips(data){
if(!data){ | random_line_split | |
Rs.js | _v;
if (latest_v) {
me.store_rs.load({
scope: this,
synchronous: true,
params: {
version_id: latest_v.get('id')
},
callback: function() {
me.columns = me.store_rs.getAt(0).get('columModle');
me.ds = n... | view.cellSelector,
innerSelector = view.innerSelector;
| me.view,
cellSelector = | conditional_block |
Rs.js | : 0xf093,
scope: this,
handler: function() {
var win = Ext.create('widget.rs.rsimport', {
listeners: {
scope: this
},
document_id: me.document.id,
document: me.document,
project: me.project,
vstore: me.versions,
type: ... | me.getSelectionModel().deselectAll();
} | random_line_split | |
experiment_util.py | _distribution_fn: Callable[[PRNGKey], Tuple[NDArray, NDArray]]
coupling_loss_matrix_fn: Callable[[NDArray, NDArray], NDArray]
inner_num_samples: int
batch_size: int
use_transpose: bool
tx: Any
num_steps: int
print_every: int = 100
metadata: Any = None
def loss_and_metrics_one_pair(self, params, rng):... | (self, rng):
"""Training loop entry point.
Calling this method runs the experiment described by this config, and
returns various results collected during training.
Args:
rng: PRNGKey to use to initialize model and draw training examples.
Returns:
types.SimpleNamespace containing vario... | train | identifier_name |
experiment_util.py | _1=None,
logits_2=None,
num_joint_samples=10_000_000,
logit_kwargs=None):
"""Computes couplings for a collection of experiments.
All experiments should have the same logit_pair_distribution_fn.
Args:
experiments: List of experi... | eval_results.update(
evaluate_experiment(ex, res, seed, num_pairs, samples_per_pair,
loop_size)) | conditional_block | |
experiment_util.py | _distribution_fn: Callable[[PRNGKey], Tuple[NDArray, NDArray]]
coupling_loss_matrix_fn: Callable[[NDArray, NDArray], NDArray]
inner_num_samples: int
batch_size: int
use_transpose: bool
tx: Any
num_steps: int
print_every: int = 100
metadata: Any = None
def loss_and_metrics_one_pair(self, params, rng):... |
return sampler
def get_coupling_estimates(experiments,
results,
seed,
logits_1=None,
logits_2=None,
num_joint_samples=10_000_000,
logit_kwargs=None):
... | q_kwargs = dict(transpose=True) if self.use_transpose else {}
x = self.model.bind(params).sample(logits_1, key)
y = self.model.bind(params).sample(logits_2, key, **q_kwargs)
return jnp.zeros([10, 10]).at[x, y].set(1.) | identifier_body |
experiment_util.py | NDArray, NDArray]]
coupling_loss_matrix_fn: Callable[[NDArray, NDArray], NDArray]
inner_num_samples: int
batch_size: int
use_transpose: bool
tx: Any
num_steps: int
print_every: int = 100
metadata: Any = None
def loss_and_metrics_one_pair(self, params, rng):
"""Samples a pair of logits, and comput... | _, axs = plt.subplots(nrows=1, ncols=ncols, figsize=(4 * ncols, 4))
axs[0].imshow(jnp.exp(logits_1)[:, None], vmin=0)
axs[1].imshow(jnp.exp(logits_2)[None, :], vmin=0)
for j, (name, coupling) in enumerate(couplings.items()):
axs[j + 2].imshow(coupling, vmin=0) | random_line_split | |
gesture_recognition_3.4.py | print(datetime.datetime.now())
# ! LJP
# 手势O，位置1
filepath_O_1 = filepath + 'LJP/O/gresture_O_location_1_'
csi_LJP_O_1 = mul_subcarries(filepath_O_1, feature_number, 0)
# 手势X，位置1
filepath_X_1 = filepath + 'LJP/X/gresture_X_location_1_'
csi_LJP_X_1 = mul_subcarries(filepath_X_1, feature_numbe... | csi_1 = np.array((csi_LJP_1, csi_DX_1))
csi_1 = np.reshape(csi_1, (-1, feature_number + 1))
csi_1 = np.append(csi_1, csi_MYW_1, axis=0)
csi_1 = np.reshape(csi_1, (-1, feature_number + 1))
# 分割特征和标签
train_feature, train_label = np.split(csi_1, (feature_number,), axis=1)
test_feature, test_lab... | print(datetime.datetime.now())
# * 整合所有样本，乱序，分割
# 整理数据集 | random_line_split |
gesture_recognition_3.4.py | (datetime.datetime.now())
# ! LJP
# 手势O，位置1
filepath_O_1 = filepath + 'LJP/O/gresture_O_location_1_'
csi_LJP_O_1 = mul_subcarries(filepath_O_1, feature_number, 0)
# 手势X，位置1
filepath_X_1 = filepath + 'LJP/X/gresture_X_location_1_'
csi_LJP_X_1 = mul_subcarries(filepath_X_1, feature_number, 1)
... | # 定义一层全连接层，输出维度是10
self.fc1 = nn.Linear(in_features=2880, out_features=96
)
# 定义一层全连接层，输出维度是10
self.fc2 = nn.Linear(in_features=96, out_features=3)
# 定义网络前向计算过程，卷积后紧接着使用池化层，最后使用全连接层计算最终输出
# 卷积层激活函数使用Relu，全连接层激活函数使用softmax
def forward(self, inputs):
x = self.conv1(inp... | en(imgs_list)的mini-batch
if len(imgs_list) > 0:
yield np.array(imgs_list), np.array(labels_list)
return data_generator
# 定义模型结构
class CNN(nn.Module):
def __init__(self):
super(CNN, self).__init__()
# 定义卷积层，输出特征通道out_channels设置为20，卷积核的大小kernel_size为5，卷积步长stride=1，padding=2... | identifier_body |
gesture_recognition_3.4.py | print(datetime.datetime.now())
# ! LJP
# 手势O，位置1
filepath_O_1 = filepath + 'LJP/O/gresture_O_location_1_'
csi_LJP_O_1 = mul_subcarries(filepath_O_1, feature_number, 0)
# 手势X，位置1
filepath_X_1 = filepath + 'LJP/X/gresture_X_location_1_'
csi_LJP_X_1 = mul_subcarries(filepath_X_1, feature_numbe... | .array(labels_list)
# 清空数据缓存列表
imgs_list = []
labels_list = []
# 如果剩余数据的数目小于BATCHSIZE，
# 则剩余数据一起构成一个大小为len(imgs_list)的mini-batch
if len(imgs_list) > 0:
yield np.array(imgs_list), np.array(labels_list)
return data_generator
# 定义模... | :
yield np.array(imgs_list), np | conditional_block |
gesture_recognition_3.4.py | (datetime.datetime.now())
# ! LJP
# 手势O，位置1
filepath_O_1 = filepath + 'LJP/O/gresture_O_location_1_'
csi_LJP_O_1 = mul_subcarries(filepath_O_1, feature_number, 0)
# 手势X，位置1
filepath_X_1 = filepath + 'LJP/X/gresture_X_location_1_'
csi_LJP_X_1 = mul_subcarries(filepath_X_1, feature_number, 1)
... | 余数据一起构成一个大小为len(imgs_list)的mini-batch
if len(imgs_list) > 0:
yield np.array(imgs_list), np.array(labels_list)
return data_generator
# 定义模型结构
class CNN(nn.Module):
def __init__(self):
super(CNN, self).__init__()
# 定义卷积层，输出特征通道out_channels设置为20，卷积核的大小kernel_size为5，卷积步长strid... | ，
# 则剩 | identifier_name |
pit.rs | //! let (_, _, _, mut pit) = ral::pit::PIT::take()
//! .map(PIT::new)
//! .unwrap();
//!
//! # async {
//! pit.delay(250_000).await;
//! # };
//! ```
use crate::ral;
use core::{
future::Future,
marker::PhantomPinned,
pin::Pin,
sync::atomic,
task::{Context, Poll, Waker},
};
/// Periodic in... | //! // Select 24MHz crystal oscillator, divide by 24 == 1MHz clock
//! ral::modify_reg!(ral::ccm, ccm, CSCMR1, PERCLK_PODF: DIVIDE_24, PERCLK_CLK_SEL: 1);
//! // Enable PIT clock gate
//! ral::modify_reg!(ral::ccm, ccm, CCGR1, CG6: 0b11); | random_line_split | |
pit.rs | pit::PIT::take()
//! .map(PIT::new)
//! .unwrap();
//!
//! # async {
//! pit.delay(250_000).await;
//! # };
//! ```
use crate::ral;
use core::{
future::Future,
marker::PhantomPinned,
pin::Pin,
sync::atomic,
task::{Context, Poll, Waker},
};
/// Periodic interrupt timer (PIT)
///
/// See th... | () -> Self {
Self::new(PIT_CHANNEL_3_ADDRESS, 3)
}
}
/// Timer Load Value Register
pub mod LDVAL {
/// Timer Start Value
pub mod TSV {
/// Offset (0 bits)
pub const offset: u32 = 0;
/// Mask (32 bits: 0xffffffff << 0)
pub ... | three | identifier_name |
pit.rs | pit::PIT::take()
//! .map(PIT::new)
//! .unwrap();
//!
//! # async {
//! pit.delay(250_000).await;
//! # };
//! ```
use crate::ral;
use core::{
future::Future,
marker::PhantomPinned,
pin::Pin,
sync::atomic,
task::{Context, Poll, Waker},
};
/// Periodic interrupt timer (PIT)
///
/// See th... | else {
// Neither complete nor active; prepare to run
ral::write_reg!(register, channel, LDVAL, count);
unsafe {
WAKERS[channel.index()] = Some(cx.waker().clone());
}
atomic::compiler_fence(atomic::Ordering::SeqCst);
ral::modify_reg!(register, channel, TCTRL,... | {
// We're active; do nothing
Poll::Pending
} | conditional_block |
pit.rs | pit::PIT::take()
//! .map(PIT::new)
//! .unwrap();
//!
//! # async {
//! pit.delay(250_000).await;
//! # };
//! ```
use crate::ral;
use core::{
future::Future,
marker::PhantomPinned,
pin::Pin,
sync::atomic,
task::{Context, Poll, Waker},
};
/// Periodic interrupt timer (PIT)
///
/// See th... |
}
static mut WAKERS: [Option<Waker>; 4] = [None, None, None, None];
/// A future that yields once the PIT timer elapses
pub struct Delay<'a> {
channel: &'a mut register::ChannelInstance,
_pin: PhantomPinned,
count: u32,
}
impl<'a> Future for Delay<'a> {
type Output = ();
fn poll(self: Pin<&mut ... | {
Delay {
channel: &mut self.channel,
count,
_pin: PhantomPinned,
}
} | identifier_body |
transform_provider.go | .ProviderName()}
g.Add(closer)
cpm[p.ProviderName()] = closer
}
// Close node depends on the provider itself
// this is added unconditionally, so it will connect to all instances
// of the provider. Extra edges will be removed by transitive
// reduction.
g.Connect(dag.BasicEdge(closer, p))
// conn... | transform | identifier_name | |
transform_provider.go | for i := 1; target == nil; i++ {
path := normalizeModulePath(sp.Path())
if len(path) < i {
break
}
key = ResolveProviderName(p, path[:len(path)-i])
target = m[key]
if target != nil {
break
}
}
if target == nil {
err = multierror.Append(err, fmt.Errorf(
"%s: conf... |
func (n *graphNodeCloseProvider) CloseProviderName() string {
return n.ProviderNameValue
}
// GraphNodeDotter impl.
func (n *graphNodeCloseProvider) DotNode(name string, opts *dag.DotOpts) *dag.DotNode {
if !opts.Verbose {
return nil
}
return &dag.DotNode{
Name: name,
Attrs: map[string]string{
"label": ... | {
return []string{n.Name()}
} | identifier_body |
transform_provider.go | for i := 1; target == nil; i++ {
path := normalizeModulePath(sp.Path())
if len(path) < i {
break
}
key = ResolveProviderName(p, path[:len(path)-i])
target = m[key]
if target != nil {
break
}
}
if target == nil {
err = multierror.Append(err, fmt.Errorf(
"%s: conf... |
log.Printf("[DEBUG] resource %s using provider %s", dag.VertexName(pv), key)
pv.SetProvider(key)
g.Connect(dag.BasicEdge(v, target))
}
}
return err
}
// CloseProviderTransformer is a GraphTransformer that adds nodes to the
// graph that will close open provider connections that aren't needed anymore.
/... | {
g.Remove(p)
target = p.Target()
key = target.(GraphNodeProvider).Name()
} | conditional_block |
transform_provider.go | for i := 1; target == nil; i++ {
path := normalizeModulePath(sp.Path())
if len(path) < i {
break
}
key = ResolveProviderName(p, path[:len(path)-i])
target = m[key]
if target != nil {
break
}
}
if target == nil {
err = multierror.Append(err, fmt.Errorf(
"%s: conf... | parts := strings.SplitAfter(p, "provider.")
p = parts[len(parts)-1]
key := ResolveProviderName(p, nil)
provider := m[key]
// we already have it
if provider != nil {
continue
}
// we don't implicitly create aliased providers
if strings.Contains(p, ".") {
log.Println("[DEBUG] not adding missing... | random_line_split | |
predata_externals.go | (extTableDef)
metadataFile.MustPrintf("\n\nCREATE %s TABLE %s (\n", tableTypeStrMap[extTableDef.Type], table.FQN())
printColumnDefinitions(metadataFile, table.ColumnDefs, "")
metadataFile.MustPrintf(") ")
PrintExternalTableStatements(metadataFile, table.FQN(), extTableDef)
if extTableDef.Writable {
metadataFile.... | (formatOpts string) []string {
inString := false
resultList := make([]string, 0)
currString := ""
for i := 0; i < len(formatOpts); i++ {
switch formatOpts[i] {
case '\'':
if inString {
/*
* Escape apostrophes *within* the string. If the
* apostrophe is at the end of the source string or is
... | tokenizeAndEscapeFormatOpts | identifier_name |
predata_externals.go | (extTableDef)
metadataFile.MustPrintf("\n\nCREATE %s TABLE %s (\n", tableTypeStrMap[extTableDef.Type], table.FQN())
printColumnDefinitions(metadataFile, table.ColumnDefs, "")
metadataFile.MustPrintf(") ")
PrintExternalTableStatements(metadataFile, table.FQN(), extTableDef)
if extTableDef.Writable {
metadataFile.... |
}
if extTableDef.Type == READABLE_WEB || extTableDef.Type == WRITABLE_WEB {
if extTableDef.Command != "" {
metadataFile.MustPrint(generateExecuteStatement(extTableDef))
}
}
metadataFile.MustPrintln()
metadataFile.MustPrint(GenerateFormatStatement(extTableDef))
metadataFile.MustPrintln()
metadataFile.Must... | {
metadataFile.MustPrintf(" ON COORDINATOR")
} | conditional_block |
predata_externals.go | toc.AddMetadataEntry(section, entry, start, metadataFile.ByteCount)
}
}
func DetermineExternalTableCharacteristics(extTableDef ExternalTableDefinition) (int, int) {
isWritable := extTableDef.Writable
var tableType int
tableProtocol := -1
if !extTableDef.Location.Valid ||
extTableDef.Location.String == "" { /... | {
start := metadataFile.ByteCount
tableTypeStrMap := map[int]string{
READABLE: "READABLE EXTERNAL",
READABLE_WEB: "READABLE EXTERNAL WEB",
WRITABLE: "WRITABLE EXTERNAL",
WRITABLE_WEB: "WRITABLE EXTERNAL WEB",
}
extTableDef := table.ExtTableDef
extTableDef.Type, extTableDef.Protocol = DetermineExter... | identifier_body | |
predata_externals.go |
"github.com/greenplum-db/gpbackup/toc"
"github.com/greenplum-db/gpbackup/utils"
)
const (
// Type of external table
READABLE = iota
READABLE_WEB
WRITABLE
WRITABLE_WEB
// Protocol external table is using
FILE
GPFDIST
GPHDFS
HTTP
S3
)
type ExternalTableDefinition struct {
Oid uint32
Type ... |
import (
"database/sql"
"fmt"
"strings" | random_line_split | |
dashboard.py | will not be
# refreshed by us but need to do that themselves.
if "url" in dashlet:
refresh_dashlets.append([nr, dashlet.get("refresh", 0),
str(add_wato_folder_to_url(dashlet["url"], wato_folder))])
# Paint the dashlet's HTML code
render_dashlet(nr, dashlet, wa... | bottom = abs_position[1]
top = bottom - used_size[1] | conditional_block | |
dashboard.py | 0px; position: relative;">
""" % (dashlet["title"], nr))
# # The content is rendered only if it is fixed. In the
# # other cases the initial (re)-size will paint the content.
if "content" in dashlet: # fixed content
html.write(dashlet["content"])
elif "iframe" in dashlet: # fixed content co... | shlet_overview() | identifier_name | |
dashboard.py | -50" id="content">""")
result = """
<!-- PAGE HEADER-->
<div class="row">
<div class="col-sm-12">
<div class="page-header">
<!-- STYLER -->
<!-- /STYLER -->
<!... |
# Compute the initial size of the dashlet. If MAX is used,
# then the dashlet consumes all space in its growing direction,
# regardless of any other dashlets.
def initial_size(self, position, rastersize):
n = []
for i in [0, 1]:
if self._data[i] ... | n = []
for i in [0, 1]:
if self._data[i] < 0:
n.append(size[i] + self._data[i] + 1) # Here was a bug fixed by Markus Lengler
else:
n.append(self._data[i] - 1) # make begin from 0
return vec(n) | identifier_body |
dashboard.py | dashlet_mk_logo():
html.write('<a href="http://mathias-kettner.de/check_mk.html">'
'<img style="margin-right: 30px;" src="images/check_mk.trans.120.png"></a>')
def dashlet_hoststats():
table = [
( _("Up"), "#0b3",
"searchhost&is_host_scheduled_downtime_depth=0&hst0=on",
"Stats: s... | img_url = base_url + "image" + var_part | random_line_split | |
update.go | In {
node.Country = tryGetCountry(gdb, gdb6, node.Host, true)
nodesOut <- node
}
close(nodesOut)
}()
}
for i := 0; i < numWorkers; i++ {
go func() {
defer worker.Done()
for node := range rawNodesIn {
node.Country = tryGetCountry(gdb, gdb6, node.Host, false)
rawNodesOut <- node
}
... | err := network.ListenOn("0.0.0.0", sslDir+"/ca/chia_ca.crt", sslDir+"/ca/chia_ca.key", nil, connHandler) | random_line_split | |
update.go |
item := l.start
l.delItemNoLock(item)
return item
}
type NodeAddr struct {
Host string
Port uint16
Country *string
}
type Node struct {
ID []byte
Host string
Port uint16
ProtocolVersion string
SoftwareVersion string
NodeType string
Country *string
... | {
return nil
} | conditional_block | |
update.go | utils.IsPGDeadlock(err) {
return nil
}
if err != nil {
return merry.Wrap(err)
}
if len(nodes) == 0 {
return nil
}
stt = time.Now().UnixNano()
_, err = tx.Exec(`
UPDATE nodes SET checked_at = NOW() WHERE id IN (?)`,
NodeListAsPGIDs(nodes))
updDur = time.Now().Uni... | {
worker := utils.NewSimpleWorker(2 * numWorkers)
for i := 0; i < numWorkers; i++ {
go func() {
defer worker.Done()
for node := range nodesIn {
node.Country = tryGetCountry(gdb, gdb6, node.Host, true)
nodesOut <- node
}
close(nodesOut)
}()
}
for i := 0; i < numWorkers; i++ {
go func() {
... | identifier_body | |
update.go | () (string, error) {
resp, err := http.Get("https://checkip.amazonaws.com/")
if err != nil {
return "", merry.Wrap(err)
}
defer resp.Body.Close()
body, err := io.ReadAll(resp.Body)
if err != nil {
return "", merry.Wrap(err)
}
return strings.TrimSpace(string(body)), nil
}
type ConnListItem struct {
prev *C... | askIP | identifier_name | |
cadastro_orcamento_emp.js |
$("#servicoRefIn").focus();
}
getRowMonted = function (value) {
var seletorTabela = document.getElementById("tabelaIn");
var seletorSetor = document.getElementById("setorIn");
if ((seletorTabela.value == "") || (seletorSetor.value == "")
|| ($("#servicoRefIn").val() == "") || ($("#servicoIn").val() ==... | {
$('#tabelaIn').removeAttr("disabled", "disabled");
} | conditional_block | |
cadastro_orcamento_emp.js | return "";
}
var htm = "<tr class=\"gridRow\" id=\"line" + value + "\" name=\"line" + value +
"\" ><td><label id=\"rowSetor" + value + "\" name=\"rowSetor" + value + "\" >";
switch (seletorSetor.value) {
case 'o':
htm += "Odontológica</label></td>";
break;
case 'l':
htm += "Labor... | return htm;
}
getRowForDel = function (value, indexRow) {
var htm = "<tr class=\"gridRow\" id=\"line" + value + "\" name=\"line" + value +
"\" ><td><label id=\"rowSetor" + value + "\" name=\"rowSetor" + value + "\" >" +
$("#rowSetor" + indexRow).text() + "</label></td>";
htm += "<td><label id=\"rowE... | htm += "<td style=\"width: 10px;\"><input id=\"checkrowTabela" + value +
"\" name=\"checkrowTabela" + value + "\" type=\"checkbox\"/></td></tr>";
| random_line_split |
toolchain_tester.py | tmp files is intentionally hardcoded, so you
can only run one instance of this at a time.
"""
from __future__ import print_function
import getopt
import glob
import multiprocessing
import os
import shlex
import subprocess
import sys
import time
import toolchain_config
# =============================================... | 'concurrency='])
except getopt.GetoptError as err:
Print(str(err)) # will print something like 'option -a not recognized'
sys.exit(-1)
for o, a in opts:
# strip the leading '--'
o = o[2:]
if o == 'verbose':
VERBOSE = 1
elif o == 'show_console':
S... | 'tmp=', | random_line_split |
toolchain_tester.py | files is intentionally hardcoded, so you
can only run one instance of this at a time.
"""
from __future__ import print_function
import getopt
import glob
import multiprocessing
import os
import shlex
import subprocess
import sys
import time
import toolchain_config
# =================================================... |
# ======================================================================
def Banner(message):
Print('=' * 70)
Print(message)
Print('=' * 70)
# ======================================================================
def RunCommand(cmd, always_dump_stdout_stderr):
"""Run a shell command given as an argv style ... | for s in REPORT_STREAMS:
print(message, file=s) | identifier_body |
toolchain_tester.py | files is intentionally hardcoded, so you
can only run one instance of this at a time.
"""
from __future__ import print_function
import getopt
import glob
import multiprocessing
import os
import shlex
import subprocess
import sys
import time
import toolchain_config
# =================================================... | (args):
num, total, config, test, extra_flags = args
base_test_name = os.path.basename(test)
extra_flags = extra_flags.copy()
toolchain_config.AppendDictionary(extra_flags,
APPEND_PER_TEST.get(base_test_name, {}))
Print('Running %d/%d: %s' % (num + 1, total, base_test_name)... | RunTest | identifier_name |
toolchain_tester.py | files is intentionally hardcoded, so you
can only run one instance of this at a time.
"""
from __future__ import print_function
import getopt
import glob
import multiprocessing
import os
import shlex
import subprocess
import sys
import time
import toolchain_config
# =================================================... |
else:
test = line
if test in EXCLUDE:
Print('ERROR: duplicate exclude: [%s]' % line)
EXCLUDE[test] = excludefile
f.close()
Print('Size of excludes now: %d' % len(EXCLUDE))
def ParseAppendFiles():
"""Parse the file contain a list of test + CFLAGS to append for that test."""... | attributes = set(tokens[1].split(','))
if not attributes.issubset(config_attributes):
continue
test = tokens[0] | conditional_block |
cipher_handout.py | content.append(contentLine)
return content
def block_to_content(contentBlock, block_height=8, block_length=8):
content = []
for contentLine in contentBlock:
for contentItem in contentLine:
content.append(contentItem)
return content
def hill_encrypt_block_array(content... | for contentLine in contentBlock: | random_line_split | |
cipher_handout.py |
def padding_content(content, blocksize=64):
for i in range(int((len(content) - 1) / blocksize + 1) * blocksize - len(content)):
content.append(0)
return content
def drop_padding(content):
for i in range(len(content)):
if content[i] == 0:
return content[:i]
return content... | str = ""
for item in list:
str += chr(item)
return str | identifier_body | |
cipher_handout.py | Array, keyArray) % field)
return cipherBlock
def hill_decrypt_block(contentBlock, keyBlock, field):
plainBlock = []
contentArray = np.array(contentBlock)
keyArray = np.array(keyBlock)
plainBlock = np.ndarray.tolist(np.dot(contentArray, keyArray) % field)
return plainBlock
def des_string_proc... | 34, 26, 18, 10, 2, 59, 51, 43, 35, 27, 19, 11, 3, 60, 52, 44, 36, 63, 55, 47, 39, 31, 23, 15, 7, 62, 54, 46, 38, 30, 22, 14, 6, 61, 53, 45, 37, 29,
21, 13, 5, 28, 20, 12, 4
]
return [keyList[PC[i] - 1] for i in range(56)]
def des_key_do_shift_pc_2(keyList):
'''在DES的每一轮中，从56位密钥产生出不同的48位子密钥'''
... | 1, 58, 50, 42, | identifier_name |
cipher_handout.py |
return content
def des_block_array_to_content(contentBlockArray):
content = []
for contentBlock in contentBlockArray:
for contentLine in contentBlock:
content.append(contentLine)
return content
def block_to_content(contentBlock, block_height=8, block_length=8):
content = []
... | content.append(contentItem) | conditional_block | |
K2400.py | current measurement function.
if set_compl != 0:
port_write(ser, ":SENS:CURR:PROT " + str(set_compl)) # Set compliance limit to 10mA.
port_write(ser, ":SENS:CURR:RANG " + str(set_compl)) # Select the 10mA measurement range.
else:
port_write(ser, ":SENS:CURR:PROT AUTO") # Set complian... | (PortUSB):
signal.signal(signal.SIGINT, signal_handler)
ser = serial.Serial(
port=PortUSB,
baudrate=9600,
parity=serial.PARITY_NONE,
stopbits=serial.STOPBITS_ONE,
bytesize=serial.EIGHTBITS,
timeout=1,
xonxoff=0,
rtscts=1)
if ser.isOpen():
... | init_port | identifier_name |
K2400.py | (ser, ":MEASure?")
# port_write(ser,":DISPlay:ENABle OFF")
except Exception, e1:
print ":: ERROR: problem with communicating ...: " + str(e1)
else:
print ":: ERROR: Can not open serial port: ", ser
logging.info("INIT_CONTROLER_PIC")
return 0
def port_close(ser):
p... | x+=0.5
y=2*x*x-2*x+1
txt=str(x)+" "+str(y)
log_save(txt)
t1=time.time()
print t1-t0
if x>=20: break | conditional_block | |
K2400.py | Select current measurement function.
if set_compl != 0:
port_write(ser, ":SENS:CURR:PROT " + str(set_compl)) # Set compliance limit to 10mA.
port_write(ser, ":SENS:CURR:RANG " + str(set_compl)) # Select the 10mA measurement range.
else:
port_write(ser, ":SENS:CURR:PROT AUTO") # Set c... |
with open(PATH + "/log/FName_Last", 'r') as f: LastFName = str(f.readline())
with open(PATH + "/log/FName_Last", 'w') as f: f.write(FName)
with open(PATH + "/FName", 'w') as f: f.write(FName)
shutil.move(str(PATH) + "/raw.txt", LastFName + ".raw")
with open(str(PATH) + "/raw.txt", 'aw+') as the_fi... | print "====================================="
print FName
print "=====================================" | random_line_split |
K2400.py | Select current measurement function.
if set_compl != 0:
port_write(ser, ":SENS:CURR:PROT " + str(set_compl)) # Set compliance limit to 10mA.
port_write(ser, ":SENS:CURR:RANG " + str(set_compl)) # Select the 10mA measurement range.
else:
port_write(ser, ":SENS:CURR:PROT AUTO") # Set c... |
def signal_handler(signal, frame):
K2400.log_save("#::::: ABORT ::::::")
print "\n:: You pressed Ctrl+C!"
print "::Programm will be TERMINATED ... \n . . . . . . . . . ."
with open(FILE_SWITCH, 'w+') as the_file: the_file.write("OFF")
def init():
global ser_VGS
global ser... | logging.info("CHECK FILE: " + path)
path = os.path.expanduser(path)
root, ext = os.path.splitext(os.path.expanduser(path))
dir = os.path.dirname(root)
fname = os.path.basename(root)
candidate = fname + ext
index = 1
ls = set(os.listdir(dir))
while candidate in ls:
candidate = "{0... | identifier_body |
maneuver_spreadsheet_support.py | 0.140402890291, max 44.1715921604.
# distfact = 2
# Mean logspline error is 5.13227646421, median 1.11771126799, max 64.1222831046. Mean linspline error is 15.9565636692, median 1.12503901849, max 632.523260832.
# distfact = 5
# Mean logspline error is 5.95691325441, median 3.00161632168, max 82.3370962708. Mean linsp... | filedata = np.genfromtxt(file_to_interpolate, delimiter=',')
xs = filedata[1:,0] # In sample data, x should go from -24 to 15
ys = filedata[0,1:-1] # In sample data, y should go from .001 to 18
data = filedata[1:,1:-1] # We have to trim off the last element of each row (nan) because of the trailing ... | identifier_body | |
maneuver_spreadsheet_support.py | 6,15)]))
for fl in fork_lengths:
size_appropriate_velocities = [v for v in all_velocities if v < 3.0 * fl + 50]
for v in size_appropriate_velocities:
|
total_bytes *= 2 # because there are 2 response variables
time_per_sheet = total_time / total_sheets
real_time = (total_time / 3600) / max_instances
print("Total calculation predicted to generate {0} sheets in {1:.1f} cpu-hours ({2:.1f} min/sheet, {4:.1f} hours for {5} instances) taking {3:.1f} mb of space.".format(to... | total_sheets += 1
total_bytes += bytes_per_number * numbers_per_sheet
total_time += time_per_number * numbers_per_sheet
queries.append(f"INSERT INTO maneuver_model_tasks (fork_length, velocity) VALUES ({fl:.1f}, {v:.1f})") | conditional_block |
maneuver_spreadsheet_support.py | 0.176547064472.
# NEXT TEST: Increase resolution to 312 pts, and start using percent errors instead of regular errors, cover full realistic ranges
# distfact = 1
# Mean logspline error is 6.61230781457, median 2.52211224078, max 81.438706048. Mean linspline error is 2.70886911207, median 0.140402890291, max 44.1715921... | maneuver_cost_interpolation | identifier_name | |
maneuver_spreadsheet_support.py | 6318184.
# Now using data from actual fish within the range where they're really doing stuff (N=300 for calculating these stats)
# Mean logspline error is 6.22782654855, median 3.72433730964, max 42.6818144461. Mean linspline error is 15.4806385555, median 4.82063948279, max 323.389534253
# That is, dare I say, tolerab... | testpt = (-15, 5, 3)
interp_ec = maneuver_cost_interpolation("/Users/Jason/Dropbox/Drift Model Project/Calculations/driftmodeldev/maneuvermodel/sample_data/interpolation_sample_data_energy_cost.csv")
interpolate_maneuver_cost(testpt, interp_ec)
| random_line_split | |
tools.js | Url: "http://eh3.uc.edu/pilincs/#/api",
shortDesc: "Interface to panoramaweb.org"
},
{
title: "LINCS Joint Project - Breast Cancer Network Browser",
description: "LJP-BCNB visualizes thousands of signatures from six breast cancer cell lines treated with ~100 single molecule ... | title: "Harmonizome",
description: "Built on top of information about genes and proteins from 114 datasets, the Harmonizome is a knowledge engine for a diverse set of integrated resources.",
url: "http://amp.pharm.mssm.edu/Harmonizome",
target: "_blank",
image... | { | random_line_split |
test_pessismistic_multi_tables.go | const batchSize = 100
func LoadData(db *sql.DB, maxSize uint64) error {
for i := 0; i < *tables; i++ {
tableName := fmt.Sprintf("t%d", i)
log.Printf("loading table: %s\n", tableName)
if _, err := db.Exec(fmt.Sprintf("drop table if exists %s", tableName)); err != nil {
return nil
}
createTableStmt := fmt.... | }
}
se.commitStart = time.Now()
_, err = se.conn.ExecContext(ctx, "commit")
if err != nil {
se.handleError(ctx, err, true)
} else {
atomic.AddUint64(&successTxn, 1)
}
return nil
}
func getErrorCode(err error) int {
var code int
_, err1 := fmt.Sscanf(err.Error(), "Error %d:", &code)
if err1 != nil {
... | {
se.reset()
ctx, cancel := context.WithTimeout(parent, time.Minute)
defer cancel()
beginSQL := "begin /*!90000 optimistic */"
if se.isPessimistic {
beginSQL = "begin /*!90000 pessimistic */"
}
_, err := se.conn.ExecContext(ctx, beginSQL)
if err != nil {
return err
}
numStmts := 1 + se.ran.uniform.Intn(5)... | identifier_body |
test_pessismistic_multi_tables.go | essimistic {
ignoreCodes = ignoreCodesP
}
for _, ignoreCode := range ignoreCodes {
if ignoreCode == code {
return
}
}
txnMode := "optimistic"
if se.isPessimistic {
txnMode = "pessimistic"
}
if isCommit {
log.Println(txnMode, "txnDur", time.Since(se.txnStart), "commitDur", time.Since(se.commitStart),... | statsLoop | identifier_name | |
test_pessismistic_multi_tables.go |
if !*insertDelete {
go checkLoop(db)
}
go statsLoop()
wg.Wait()
}
const batchSize = 100
func LoadData(db *sql.DB, maxSize uint64) error {
for i := 0; i < *tables; i++ {
tableName := fmt.Sprintf("t%d", i)
log.Printf("loading table: %s\n", tableName)
if _, err := db.Exec(fmt.Sprintf("drop table if exists ... | {
se, err := NewSession(db, uint64(i), *tableSize, numPartitions)
if err != nil {
log.Fatal(err)
}
go se.Run(wg)
} | conditional_block | |
test_pessismistic_multi_tables.go | const batchSize = 100
func LoadData(db *sql.DB, maxSize uint64) error {
for i := 0; i < *tables; i++ {
tableName := fmt.Sprintf("t%d", i)
log.Printf("loading table: %s\n", tableName)
if _, err := db.Exec(fmt.Sprintf("drop table if exists %s", tableName)); err != nil {
return nil
}
createTableStmt := fmt.... | }
_, err := se.conn.ExecContext(ctx, beginSQL)
if err != nil {
return err
}
numStmts := 1 + se.ran.uniform.Intn(5)
for i := 0; i < numStmts; i++ {
stmtType := se.ran.uniform.Intn(len(se.stmts))
f := se.stmts[stmtType]
err = f(ctx)
if err != nil {
se.handleError(ctx, err, false)
return nil
}
}
... | defer cancel()
beginSQL := "begin /*!90000 optimistic */"
if se.isPessimistic {
beginSQL = "begin /*!90000 pessimistic */" | random_line_split |
backbone2.py | 2, 512, "M"],
13: [64, 64, "M", 128, 128, "M", 256, 256, "M", 512, 512, "M", 512, 512, "M"],
16: [64, 64, "M", 128, 128, "M", 256, 256, 256, "M", 512, 512, 512, "M", 512, 512, 512, "M"],
19: [64,64,"M",128,128,"M",256,256,256,256,"M",512,512,512,512,"M",512,512,512,512,"M"],
}
class Conv2d2(Conv2d):
""... | self.out_channels = out_channels
self.kernel_size = _pair(kernel_size)
self.stride = _pair(stride)
self.padding = _pair(padding)
self.dilation = _pair(dilation)
self.groups = groups
self.deformable_groups = deformable_groups
self.norm = norm
self.a... | """
Deformable convolution from :paper:`deformconv`.
Arguments are similar to :class:`Conv2D`. Extra arguments:
Args:
deformable_groups (int): number of groups used in deformable convolution.
norm (nn.Module, optional): a normalization layer
activation (call... | identifier_body |
backbone2.py | 2, 512, "M"],
13: [64, 64, "M", 128, 128, "M", 256, 256, "M", 512, 512, "M", 512, 512, "M"],
16: [64, 64, "M", 128, 128, "M", 256, 256, 256, "M", 512, 512, 512, "M", 512, 512, 512, "M"],
19: [64,64,"M",128,128,"M",256,256,256,256,"M",512,512,512,512,"M",512,512,512,512,"M"],
}
class Conv2d2(Conv2d):
""... |
if isinstance(x,tuple):
x,_=x
if self.num_classes is not None:
x = self.avgpool(x)
x = self.classifier(x)
if "classifer" in self._out_features:
outputs["classifer"] = x
return outputs
def output_shape(self):
r... | outputs[name] = x | conditional_block |
backbone2.py | , 512, "M"],
13: [64, 64, "M", 128, 128, "M", 256, 256, "M", 512, 512, "M", 512, 512, "M"],
16: [64, 64, "M", 128, 128, "M", 256, 256, 256, "M", 512, 512, 512, "M", 512, 512, 512, "M"],
19: [64,64,"M",128,128,"M",256,256,256,256,"M",512,512,512,512,"M",512,512,512,512,"M"],
}
class Conv2d2(Conv2d):
"""... | (self):
tmpstr = "in_channels=" + str(self.in_channels)
tmpstr += ", out_channels=" + str(self.out_channels)
tmpstr += ", kernel_size=" + str(self.kernel_size)
tmpstr += ", stride=" + str(self.stride)
tmpstr += ", padding=" + str(self.padding)
tmpstr += ", dilation=" + st... | extra_repr | identifier_name |
backbone2.py | 2, 512, "M"],
13: [64, 64, "M", 128, 128, "M", 256, 256, "M", 512, 512, "M", 512, 512, "M"],
16: [64, 64, "M", 128, 128, "M", 256, 256, 256, "M", 512, 512, 512, "M", 512, 512, 512, "M"],
19: [64,64,"M",128,128,"M",256,256,256,256,"M",512,512,512,512,"M",512,512,512,512,"M"],
}
class Conv2d2(Conv2d):
""... | self.deformable_groups = deformable_groups
self.norm = norm
self.activation = activation
self.weight = nn.Parameter(
torch.Tensor(out_channels, in_channels // self.groups, *self.kernel_size)
)
if bias:
self.bias = nn.Parameter(torch.Tensor(out_cha... | self.stride = _pair(stride)
self.padding = _pair(padding)
self.dilation = _pair(dilation)
self.groups = groups | random_line_split |
transactions_reader.rs | ::HashMap,
io::{BufRead, BufReader},
path::Path,
};
use anyhow::Context;
use crossbeam_channel::{Receiver, Sender};
use csv::{ByteRecord, ReaderBuilder, Trim};
use crate::records::TransactionRecord;
use log::*;
/// A type that represents a stream of transactions arriving into the system
/// Many channels (s... | while let Ok(true) = csv_reader.read_byte_record(&mut raw_record) {
let record = raw_record.deserialize::<TransactionRecord>(Some(&headers));
if let Ok(record) = record {
transactions.push(record);
}
... | {
for _ in 0..num_threads {
let block_rx = block_rx.clone();
let parsed_tx = parsed_tx.clone();
// For now consider that the headers if read then they're OK and equal to below
let headers = ByteRecord::from(vec!["type", "client", "tx", "amount"]);
std:... | identifier_body |
transactions_reader.rs | ::HashMap,
io::{BufRead, BufReader},
path::Path,
};
use anyhow::Context;
use crossbeam_channel::{Receiver, Sender};
use csv::{ByteRecord, ReaderBuilder, Trim};
use crate::records::TransactionRecord;
use log::*;
/// A type that represents a stream of transactions arriving into the system
/// Many channels (s... | ;
}
waiting_for += 1;
}
} else if block.0 > waiting_for {
queue.insert(block.0, block.1);
}
}
});
}
// Reads a big block until new line alignment
fn read_block(&mut se... | {
return;
} | conditional_block |
transactions_reader.rs | ::HashMap,
io::{BufRead, BufReader},
path::Path,
};
use anyhow::Context;
use crossbeam_channel::{Receiver, Sender};
use csv::{ByteRecord, ReaderBuilder, Trim};
use crate::records::TransactionRecord;
use log::*;
/// A type that represents a stream of transactions arriving into the system
/// Many channels (s... | /// Tests that we can read and parse all transactions
#[test]
fn test_st_bulk_transaction_reader_serde() {
let reader = STBulkReader::new();
test_transaction_reader(reader, "tests/data/test_serde.csv");
}
#[test]
fn test_mt_reader_transaction_reader_serde() {
let reader ... | random_line_split | |
transactions_reader.rs | ::HashMap,
io::{BufRead, BufReader},
path::Path,
};
use anyhow::Context;
use crossbeam_channel::{Receiver, Sender};
use csv::{ByteRecord, ReaderBuilder, Trim};
use crate::records::TransactionRecord;
use log::*;
/// A type that represents a stream of transactions arriving into the system
/// Many channels (s... | {}
impl STBulkReader {
pub fn new() -> Self {
Self {}
}
}
impl TransactionCSVReader for STBulkReader {
fn read_csv<P: AsRef<Path>>(self, path: P) -> anyhow::Result<TransactionsStream> {
let start_time = std::time::Instant::now();
info!("STBulkReader reading the transactions");
... | STBulkReader | identifier_name |
dir.rs | name,
metadata,
}
}
pub fn name(&self) -> &str {
&self.name
}
pub fn metadata(&self) -> &Metadata {
&self.metadata
}
/// Finds the entry named `name` in `self` and returns it. Comparison is
/// case-insensitive.
///
/// # Errors
///
///... |
}).filter_map(|entry| match entry.lfn() {
Some(lfn) if lfn.seqno != 0xE5 => Some(*lfn),
_ => None,
}).collect();
entries.sort_by_key(|lfn| lfn.seqno);
let mut name: Vec<u16> = vec![];
for &lfn in entries.iter() {
name.extend(... | {
false
} | conditional_block |
dir.rs | name,
metadata,
}
}
pub fn name(&self) -> &str {
&self.name
}
pub fn metadata(&self) -> &Metadata {
&self.metadata
}
/// Finds the entry named `name` in `self` and returns it. Comparison is
/// case-insensitive.
///
/// # Errors
///
///... | #[repr(C, packed)]
#[derive(Copy, Clone, Debug)]
pub struct VFatLfnDirEntry {
seqno: u8,
name_1: [u16; 5],
attributes: u8,
_reserved_1: u8,
dos_checksum: u8,
name_2: [u16; 6],
_reserved_2: [u8; 2],
name_3: [u16; 2],
}
#[repr(C, packed)]
#[derive(Copy, Clone)]
pub struct VFatUnknownDirEn... | }
}
| random_line_split |
dir.rs | `name` exists in `self`, an error of `NotFound` is
/// returned.
///
/// If `name` contains invalid UTF-8 characters, an error of `InvalidInput`
/// is returned.
pub fn find<P: AsRef<OsStr>>(&self, name: P) -> io::Result<Entry> {
let name = name.as_ref().to_str().ok_or(io::Error::new(
... | next | identifier_name | |
dir.rs | name,
metadata,
}
}
pub fn name(&self) -> &str {
&self.name
}
pub fn metadata(&self) -> &Metadata {
&self.metadata
}
/// Finds the entry named `name` in `self` and returns it. Comparison is
/// case-insensitive.
///
/// # Errors
///
///... |
fn cluster(&self) -> Cluster {
Cluster::from(((self.cluster_high as u32) << 16) | (self.cluster_low as u32))
}
fn created(&self) -> Timestamp {
let date = Date::from_raw(self.created_date);
let time = Time::from_raw(self.created_time);
Timestamp::new(date, time)
}
... | {
self.name[0] == 0x05 || self.name[0] == 0xE5
} | identifier_body |
mod.rs | fSceneLoaderSystemDesc,
input::{InputBundle, StringBindings},
prelude::*,
renderer::{
plugins::{RenderPbr3D, RenderSkybox, RenderToWindow},
RenderingBundle,
Texture,
types::{DefaultBackend, Mesh, MeshData},
},
ui::{RenderUi, UiBundle},
utils::{
application... | let parent_ent: Entity = parents.get(entity)?.entity;
get_root_cloned(
parents, components,
parent_ent,
)
}
}
pub fn get_root_mut<'s, 'a, T, P, C>(
parents: &P, components: &'a mut C,
entity: Entity,
) -> Option<(&'a mut T, Entity)>
where T: Component, P:... | random_line_split | |
mod.rs | fSceneLoaderSystemDesc,
input::{InputBundle, StringBindings},
prelude::*,
renderer::{
plugins::{RenderPbr3D, RenderSkybox, RenderToWindow},
RenderingBundle,
Texture,
types::{DefaultBackend, Mesh, MeshData},
},
ui::{RenderUi, UiBundle},
utils::{
application... | else {
let parent_ent: Entity = parents.get(entity)?.entity;
get_root_cloned(
parents, components,
parent_ent,
)
}
}
pub fn get_root_mut<'s, 'a, T, P, C>(
parents: &P, components: &'a mut C,
entity: Entity,
) -> Option<(&'a mut T, Entity)>
where T: Compo... | {
Some((component.clone(), entity))
} | conditional_block |
mod.rs | SceneLoaderSystemDesc,
input::{InputBundle, StringBindings},
prelude::*,
renderer::{
plugins::{RenderPbr3D, RenderSkybox, RenderToWindow},
RenderingBundle,
Texture,
types::{DefaultBackend, Mesh, MeshData},
},
ui::{RenderUi, UiBundle},
utils::{
application_... |
pub fn get_root_mut<'s, 'a, T, P, C>(
parents: &P, components: &'a mut C,
entity: Entity,
) -> Option<(&'a mut T, Entity)>
where T: Component, P: GenericReadStorage<Component=Parent>, C: GenericWriteStorage<Component=T> {
if components.get_mut(entity).is_some() {
Some((components.get_mut(entit... | {
if let Some(component) = components.get(entity) {
Some((component.clone(), entity))
} else {
let parent_ent: Entity = parents.get(entity)?.entity;
get_root_cloned(
parents, components,
parent_ent,
)
}
} | identifier_body |
mod.rs | fSceneLoaderSystemDesc,
input::{InputBundle, StringBindings},
prelude::*,
renderer::{
plugins::{RenderPbr3D, RenderSkybox, RenderToWindow},
RenderingBundle,
Texture,
types::{DefaultBackend, Mesh, MeshData},
},
ui::{RenderUi, UiBundle},
utils::{
application... | <'s, 'a, T, P, C>(
parents: &P, components: &'a C,
entity: Entity,
) -> Option<(T, Entity)>
where T: Component + Clone, P: GenericReadStorage<Component=Parent>, C: GenericReadStorage<Component=T> {
if let Some(component) = components.get(entity) {
Some((component.clone(), entity))
} else {
... | get_root_cloned | identifier_name |
term_evaluation_result.js | M("three_menu_module"),
C.CM("select_assembly"),
C.CM("tuploader")
],
function ($, avalon, layer, html, css, data_center, three_menu_module, select_assembly, tuploader) {
var avalon_define = function () {
var grade_list = [];
var semester_full = [];
var u... |
cloud.add_audit(form, request_after);
}
var vm = avalon.define({
$id: "term_evaluation_result",
//图片是否展开（注：如果数据是循环出来，不能用这种方式）
is_open: false,
// 接口中未返回区县信息， 暂时使用用户所在区县
district: "",
... | {
var is_school_user = cloud.is_school_user();
var distict_id = '';
if (is_school_user) {
distict_id = cloud.school_user_distict_id().district_id;
}
var user = cloud.user_user();
form.district_id = disti... | identifier_body |
term_evaluation_result.js | M("three_menu_module"),
C.CM("select_assembly"),
C.CM("tuploader")
],
function ($, avalon, layer, html, css, data_center, three_menu_module, select_assembly, tuploader) {
var avalon_define = function () {
var grade_list = [];
var semester_full = [];
var u... | //图片是否展开（注：如果数据是循环出来，不能用这种方式）
is_open: false,
// 接口中未返回区县信息， 暂时使用用户所在区县
district: "",
//核查意见
opinion: '',
//更正结果
correct:"",
// 图片显示相关支持
user_photo: cloud.user_... |
var vm = avalon.define({
$id: "term_evaluation_result", | random_line_split |
term_evaluation_result.js | M("three_menu_module"),
C.CM("select_assembly"),
C.CM("tuploader")
],
function ($, avalon, layer, html, css, data_center, three_menu_module, select_assembly, tuploader) {
var avalon_define = function () {
var grade_list = [];
var semester_full = [];
var u... | (form) {
var is_school_user = cloud.is_school_user();
var distict_id = '';
if (is_school_user) {
distict_id = cloud.school_user_distict_id().district_id;
}
var user = cloud.user_user();
form.district_id ... | yy_treat | identifier_name |
MatrixFromWeights_py27.py | except ValueError:
sy_thresh = _FLOAT_EPS_4
r11, r12, r13, r21, r22, r23, r31, r32, r33 = M.flat
sy = math.sqrt(r31 * r31 + r32 * r32)
if sy > sy_thresh:
x2 = math.acos(r33)
z1 = math.atan2(r13, -r23)
z3 = math.atan2(r31, r32)
else:... | try:
sy_thresh = np.finfo(M.dtype).eps * 4 | random_line_split | |
MatrixFromWeights_py27.py | cosz3 = math.cos(z3)
sinz3 = math.sin(z3)
Z3 = np.array(
[[cosz3, -sinz3, 0],
[sinz3, cosz3, 0],
[0, 0, 1]])
return reduce(np.dot, [Z1, X2, Z3])
def _mat2euler(self, M):
M = np.asarray(M)
try:
sy_thresh = np.finfo(M.... | """
* Rotation : provides a representation for 3D space rotations
* using euler angles (ZX'Z'' convention) or rotation matrices
"""
def _euler2mat_z1x2z3(self, z1=0, x2=0, z3=0):
cosz1 = math.cos(z1)
sinz1 = math.sin(z1)
Z1 = np.array(
[[cosz1, -sinz1, 0],
... | identifier_body | |
MatrixFromWeights_py27.py | 0
z3 = 0
z1 = math.atan2(r21, r22)
return (z1, x2, z3)
def _init_from_angles(self, z1, x2, z3):
self._z1, self._x2, self._z3 = z1, x2, z3
self._M = self._euler2mat_z1x2z3(self._z1, self._x2, self._z3)
def _init_from_matrix(self, matrix):
self._M = np.as... |
elif arg1.size == 3:
self._init_from_angles(arg1[0], arg1[1], arg1[2])
else:
self._init_from_matrix(arg1)
def matrix(self, new_matrix=None):
if new_matrix is not None:
self._init_from_matrix(new_matrix)
return self._M
def euler_angles(self, ... | self._init_from_angles(arg1, x2, z3) | conditional_block |
MatrixFromWeights_py27.py | :
"""
* Rotation : provides a representation for 3D space rotations
* using euler angles (ZX'Z'' convention) or rotation matrices
"""
def _euler2mat_z1x2z3(self, z1=0, x2=0, z3=0):
cosz1 = math.cos(z1)
sinz1 = math.sin(z1)
Z1 = np.array(
[[cosz1, -sinz1, 0],
... | Rotation | identifier_name | |
__init__.py | = long
except NameError :
expected_type = int
if type(value) == expected_type:
if value > sys.maxsize:
raise RosParamException("Overflow: Parameter Server integers must be 32-bit signed integers:\n\t-%s <= value <= %s"%(maxint - 1, maxint))
... | """
Process command line for rosparam delete, e.g.::
rosparam delete param
:param cmd: command name, ``str``
:param argv: command-line args, ``str``
"""
parser = OptionParser(usage="usage: %prog delete [options] parameter", prog=NAME)
parser.add_option("-v", dest="verbose", default=False... | identifier_body | |
__init__.py | (node)
exprvalue = value
if exprvalue.startswith("deg("):
exprvalue = exprvalue.strip()[4:-1]
try:
return float(exprvalue) * math.pi / 180.0
except ValueError:
raise RosParamException("invalid degree value: %s"%value)
# utilities
def _get_caller_id():
"""
:returns: cal... |
else:
dump = yaml.dump(v)
# #1617
# newer versions of python-yaml append the '...' document end
# syntax. as YAML functions fine w/o it, and as it is
# confusing to users who are just getting a single scalar, we
# strip it
if ... | print("%s%s: %s"%(indent, k, v)) | conditional_block |
__init__.py | (node)
exprvalue = value
if exprvalue.startswith("deg("):
exprvalue = exprvalue.strip()[4:-1]
try:
return float(exprvalue) * math.pi / 180.0
except ValueError:
raise RosParamException("invalid degree value: %s"%value)
# utilities
def _get_caller_id():
"""
:returns: cal... | # #1617
# newer versions of python-yaml append the '...' document end
# syntax. as YAML functions fine w/o it, and as it is
# confusing to users who are just getting a single scalar, we
# strip it
if dump.endswith('\n...\n'):
dump = dump[:-5]
# #3761... | print(val)
else:
dump = yaml.dump(val) | random_line_split |
__init__.py | (node)
exprvalue = value
if exprvalue.startswith("deg("):
exprvalue = exprvalue.strip()[4:-1]
try:
return float(exprvalue) * math.pi / 180.0
except ValueError:
raise RosParamException("invalid degree value: %s"%value)
# utilities
def _get_caller_id():
"""
:returns: cal... | (params, ns):
"""
Print contents of param dictionary to screen
"""
if type(params) == dict:
for k, v in params.items():
if type(v) == dict:
print_params(v, ns_join(ns, k))
else:
print("%s=%s"%(ns_join(ns, k), v))
else:
print(par... | print_params | identifier_name |
methods.py | ios.index)
+ 1
)
df[numcols] = df[numcols] * ratios
return df
def budget(df, df_hist, harmonize_year="2015"):
r"""
Calculate budget harmonized trajectory.
Parameters
----------
df : pd.DataFrame
model data
df_hist : pd.DataFrame
historic data
harmonize... | kwargs["ratio_method"] = "reduce_ratio_2080" | conditional_block | |
methods.py | , offset, final_year="2050", harmonize_year="2015"):
"""
Calculate linearly interpolated convergence harmonized trajectory.
Parameters
----------
df : pd.DataFrame
model data
offset : pd.DataFrame
offset data
final_year : string, optional
column name of convergence y... | yi, yf = int(harmonize_year), int(final_year)
numcols = utils.numcols(df)
numcols_int = [int(v) for v in numcols]
# get factors that reduce from 1 to 0; factors before base year are > 1
f = lambda year: -(year - yi) / float(yf - yi) + 1
factors = [f(year) if year <= yf else 0.0 for year in numco... | """
Calculate offset convergence harmonized trajectory.
Parameters
----------
df : pd.DataFrame
model data
offset : pd.DataFrame
offset data
final_year : string, optional
column name of convergence year
harmonize_year : string, optional
column name of harmoni... | identifier_body |
methods.py | offset, final_year="2050", harmonize_year="2015"):
"""
Calculate linearly interpolated convergence harmonized trajectory.
Parameters
----------
df : pd.DataFrame
model data
offset : pd.DataFrame
offset data
final_year : string, optional
column name of convergence ye... | (df, df_hist, harmonize_year="2015"):
r"""
Calculate budget harmonized trajectory.
Parameters
----------
df : pd.DataFrame
model data
df_hist : pd.DataFrame
historic data
harmonize_year : string, optional
column name of harmonization year
Returns
-------
... | budget | identifier_name |
methods.py | , offset, final_year="2050", harmonize_year="2015"):
"""
Calculate linearly interpolated convergence harmonized trajectory.
Parameters
----------
df : pd.DataFrame
model data
offset : pd.DataFrame
offset data
final_year : string, optional
column name of convergence y... |
df[numcols] = df[numcols] * ratios
return df
def budget(df, df_hist, harmonize_year="2015"):
r"""
Calculate budget harmonized trajectory.
Parameters
----------
df : pd.DataFrame
model data
df_hist : pd.DataFrame
historic data
harmonize_year : string, optional
... | pd.DataFrame(np.outer(ratios - 1, factors), columns=numcols, index=ratios.index)
+ 1
) | random_line_split |
hw.py | try:
with open(out_filename, 'w', encoding=encoding_table) as f:
json.dump(out_dict, f, ensure_ascii=False)
print(f"файл {out_filename} создался успешно!")
except:
print("Ошибка при записи выходного файла JSON")
def get_most_common_object(dict_):
max_ = 0
for key... | d = wine._asdict()
dict_ = dict(d)
return dict_
def out_file(out_dict, out_filename, encoding_table): | random_line_split | |
hw.py | in dict_.items():
if value > max_:
max_ = value
most_common_object = key
return most_common_object
def main():
if os.path.exists(FILE_NAME1):
# Читаем JSON из файла и преобразуем к типу Python
with open(FILE_NAME1, 'r', encoding='UTF-8') as f:
read_d... | pen(out_filename, 'w', encoding=encoding_table) as f:
json.dump(out_dict, f, ensure_ascii=False)
print(f"файл {out_filename} создался успешно!")
except:
print("Ошибка при записи выходного файла JSON")
def get_most_common_object(dict_):
max_ = 0
for key,value | identifier_body | |
hw.py | ла и преобразуем к типу Python
with open(FILE_NAME1, 'r', encoding='UTF-8') as f:
read_data_1 = json.load(f)
else:
print(f"{FILE_NAME1} File not found!")
if os.path.exists(FILE_NAME2):
# Читаем JSON из файла и преобразуем к типу Python
with open(FILE_NAME2, 'r', encod... | фай | identifier_name | |
hw.py | :
read_data_2 = json.load(f)
else:
print(f"{FILE_NAME2} File not found!")
if MODE == 'set_and_namedtuple':
#--убираем дубликаты моим методом
dict_wines = read_data_1 + read_data_2
wines = []
wines = [from_dict_to_namedtuple(dict_wine) for dict_wine in dict_wines]
... | e') #вместо немецких вставить общепринятые символы
sort_wine[variety] = {"average_price":0, "min_price":0, "max_price":0, "most_common_country":0, "most_common_region":0, "average_score":0}
sort_wine[variety]["average_price"] = str(average_price)
sort_wine[variety]["min_price"] = str(min_price)... | iety #.replace('â','ae').replace('ü','u | conditional_block |
brain-gan-parameter-search.py | build_generator_model(self, noise_shape):
model = Sequential()
# This block of code can be a little daunting, but essentially it automatically calculates the required starting
# array size that will be correctly upscaled to our desired image size.
#
# We have 5 Upsample2D layer... |
return(img_array)
def train(self, epochs, image_path, batch_size=32, save_interval=50):
self.build_gan()
X_train = self.load_imgs(image_path)
print("Training Data Shape: ", X_train.shape)
# Rescale images from -1 to 1
X_train = (X_train.astype(np.float32) - 127.5)... | img_array = np.uint8(255*img_array) | conditional_block |
brain-gan-parameter-search.py | # array size that will be correctly upscaled to our desired image size.
#
# We have 5 Upsample2D layers which each double the images width and height, so we can determine the starting
# x size by taking (x / 2^upsample_count) So for our target image size, 256x192, we do the following:
... | def __init__(self, discriminator_path, generator_path, output_directory, img_size, dropout, bn_momentum, adam_lr, adam_beta):
self.img_size = img_size
self.upsample_layers = 5
self.starting_filters = 64
self.kernel_size = 3
self.channels = 1
self.discriminator_path = disc... | identifier_body | |
brain-gan-parameter-search.py | (self, discriminator_path, generator_path, output_directory, img_size, dropout, bn_momentum, adam_lr, adam_beta):
self.img_size = img_size
self.upsample_layers = 5
self.starting_filters = 64
self.kernel_size = 3
self.channels = 1
self.discriminator_path = discriminator_pa... | __init__ | identifier_name | |
brain-gan-parameter-search.py | build_generator_model(self, noise_shape):
model = Sequential()
# This block of code can be a little daunting, but essentially it automatically calculates the required starting
# array size that will be correctly upscaled to our desired image size.
#
# We have 5 Upsample2D layer... |
# Print progress
prog_bar.set_description(("D loss: " + format(d_loss[0], "^-06.3f") + " | D Accuracy: " + format(d_loss[1], "^-06.3f") +" | G loss: " + format(g_loss, | # Train the discriminator (real classified as ones and generated as zeros)
d_loss_real = self.discriminator.train_on_batch(imgs, np.ones((half_batch, 1)))
d_loss_fake = self.discriminator.train_on_batch(gen_imgs, np.zeros((half_batch, 1)))
d_loss = 0.5 * np.add(d_loss_rea... | random_line_split |
revaultd.rs | pub cancel_tx: Option<CancelTransaction>,
pub unvault_emergency_tx: Option<UnvaultEmergencyTransaction>,
}
#[derive(Debug, PartialEq, Copy, Clone)]
pub struct BlockchainTip {
pub height: u32,
pub hash: BlockHash,
}
/// Our global state
pub struct RevaultD {
// Bitcoind stuff
/// Everything we nee... | deposit_address | identifier_name | |
revaultd.rs | ing),
"canceled" => Ok(Self::Canceled),
"emergencyvaulting" => Ok(Self::EmergencyVaulting),
"emergencyvaulted" => Ok(Self::EmergencyVaulted),
"unvaultemergencyvaulting" => Ok(Self::UnvaultEmergencyVaulting),
"unvaultemergencyvaulted" => Ok(Self::UnvaultEmergen... | random_line_split | ||
revaultd.rs | communication keys are (for now) hot, so we just create it ourselves on first run.
fn read_or_create_noise_key(secret_file: PathBuf) -> Result<NoisePrivKey, KeyError> {
let mut noise_secret = NoisePrivKey([0; 32]);
if !secret_file.as_path().exists() {
log::info!(
"No Noise private key at '... | {
let data_dir_str = self
.data_dir
.to_str()
.expect("Impossible: the datadir path is valid unicode");
[data_dir_str, file_name].iter().collect()
} | identifier_body | |
matgen.go | right hand side alternately zero and small.
switch uplo {
case blas.Upper:
b[0] = 0
for i := n - 1; i > 0; i -= 2 {
b[i] = 0
b[i-1] = smlnum
}
case blas.Lower:
for i := 0; i < n-1; i += 2 {
b[i] = 0
b[i+1] = smlnum
}
b[n-1] = 0
}
case 15:
// Make the diagonal elements small... | rthogonal(n int, | identifier_name | |
matgen.go | ] = 1
}
}
}
// Set the right hand side alternately zero and small.
switch uplo {
case blas.Upper:
b[0] = 0
for i := n - 1; i > 0; i -= 2 {
b[i] = 0
b[i-1] = smlnum
}
case blas.Lower:
for i := 0; i < n-1; i += 2 {
b[i] = 0
b[i+1] = smlnum
}
b[n-1] = 0
}
case 15:
//... | nic("testlapack: insufficient matrix slice length")
}
}
// | conditional_block |
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