pragma solidity ^0.4.24;
import "zos-lib/contracts/Initializable.sol";
import "../validation/TimedCrowdsale.sol";
import "../../math/SafeMath.sol";
/**
* @title IncreasingPriceCrowdsale
* @dev Extension of Crowdsale contract that increases the price of tokens linearly in time.
* Note that what should be provided to the constructor is the initial and final _rates_, that is,
* the amount of tokens per wei contributed. Thus, the initial rate must be greater than the final rate.
*/
contract IncreasingPriceCrowdsale is Initializable, TimedCrowdsale {
using SafeMath for uint256;
uint256 private _initialRate;
uint256 private _finalRate;
/**
* @dev Constructor, takes initial and final rates of tokens received per wei contributed.
* @param initialRate Number of tokens a buyer gets per wei at the start of the crowdsale
* @param finalRate Number of tokens a buyer gets per wei at the end of the crowdsale
*/
function initialize(uint256 initialRate, uint256 finalRate) public initializer {
assert(TimedCrowdsale._hasBeenInitialized());
require(finalRate > 0);
require(initialRate >= finalRate);
_initialRate = initialRate;
_finalRate = finalRate;
}
/**
* @return the initial rate of the crowdsale.
*/
function initialRate() public view returns(uint256) {
return _initialRate;
}
/**
* @return the final rate of the crowdsale.
*/
function finalRate() public view returns (uint256) {
return _finalRate;
}
/**
* @dev Returns the rate of tokens per wei at the present time.
* Note that, as price _increases_ with time, the rate _decreases_.
* @return The number of tokens a buyer gets per wei at a given time
*/
function getCurrentRate() public view returns (uint256) {
// solium-disable-next-line security/no-block-members
uint256 elapsedTime = block.timestamp.sub(openingTime());
uint256 timeRange = closingTime().sub(openingTime());
uint256 rateRange = _initialRate.sub(_finalRate);
return _initialRate.sub(elapsedTime.mul(rateRange).div(timeRange));
}
/**
* @dev Overrides parent method taking into account variable rate.
* @param weiAmount The value in wei to be converted into tokens
* @return The number of tokens _weiAmount wei will buy at present time
*/
function _getTokenAmount(uint256 weiAmount)
internal view returns (uint256)
{
uint256 currentRate = getCurrentRate();
return currentRate.mul(weiAmount);
}
uint256[50] private ______gap;
}
|


#BigLipstickEnergy: The 3 Lip Products I'm Obsessed With Right Now
by Maya AllenI'm a serial lipstick dater. So many lip products slide onto my desk. Some I double-tap and have all the heart eyes for. Others I ghost and leave on seen. This is #BigLipstickEnergy, an honest breakdown of how I feel about the latest lip launches. Read on for the three lipstick flings I'm keeping in rotation for now. Next week, I'll have a new roster.
This Ritzy Red
Rouge Pur Couture Stud Edition Collector Lipstick in 01 Le Rouge
Yves Saint Laurent nordstrom.com
$38.00
SHOP IT
THE DETAILS:
If you're equal parts bougie and badass (it me), it'll be hard for you to pass up this fire-red, studded lipstick bullet. Once you get over the gorgeous packaging, which is a Nordstrom exclusive I peeped at its New York store opening a few weeks ago, you'll enjoy how this satin texture boasts the most beautifully pigmented finish in just one glide.
WHY I'M OBSESSED:
I'm in a gifty mood because it's the holidays and this is the prettiest little present. Except, um, I'm keeping it for myself. Besides the bottle being super hawt, the shade is also super hawt. It's a blue-based cherry color, which means it looks incredible on your skin tone and your friends' skin tones.
This Ethereal Gloss
Beauty Boss Lip Gloss in In The Black
Stila sephora.com
$15.00
SHOP IT
THE DETAILS:
In a world full of lip glosses, what makes you need a new one? Well, I bet you don't have a light-reflecting, iridescent pearl-packed gloss that makes you look like the coolest witch alive. Thought so. Plus, this fun one is made with hyaluronic filling spheres, which naturally plump up your lips.
WHY I'M OBSESSED:
I know, I know—this purple gloss looks like what your middle school dreams were made of. But I ask that you trust my 27-year-old judgement would not steer you wrong when it comes to beauty. Actually, the purple packaging is a bit deceiving because it's more of a translucent, mauve shade that reads like a mysterious hybrid of gray and plum with brown undertones. It's quite mystical and makes me feel like an ethereal diva. It's getting me through retrograde.
This Winter-Proof Balm
Rejuvenating Lip Balm
Blue Lagoon Iceland bluelagoon.com
$37.00
SHOP IT
THE DETAILS:
Every season, we all forget what winter feels like. It's suddenly surprising and downright rude that the second we walk outside our lips are literally going to crack, shrivel, and fall tf off. Okay, that may be a bit dramatic (except if you live in New York), but what isn't is that it's impossible to go without a really good lip balm. This one is filled with the brand's patented Blue Lagoon algae, which hydrates and nourishes the lips from within for long-lasting hydration.
WHY I'M OBSESSED:
I love my big, full, round, and plump lips, but they're so high-maintenance. I have to literally baby them with lip balm all the time. Therefore, I appreciate a formula that doesn't feel fleeting. This one stays put and is moisturizing for longer than usual. I plan to keep it in my top five lineup of favorite balms all winter.
For more stories like this, including celebrity news, beauty and fashion advice, savvy political commentary, and fascinating features, sign up for the Marie Claire newsletter.
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RunningAchilles.Rmd
In this vignette we cover how to run the Achilles package on your Common Data Model (CDM) database in order to characterize the dataset and run data quality (DQ) checks. The characterizations and DQ results can help you learn more about your dataset’s features and limitations, and can then be consumed graphically using AchillesWeb or Atlas Data Sources.
It is a best practice for all OHDSI sites to run Achilles on their CDM datasets to ensure researchers can evaluate study feasibility and contextualize study results.
The Achilles package consists of:
The Achilles package should be run sequentially. That is, achilles should be run first to generate the achilles_results and achilles_results_dist tables, and then optionally, achillesHeel should be run next to generate the achilles_heel_results and achilles_results_derived tables.
In most Achilles functions, you can specify sqlOnly = TRUE
in order to produce the SQL without executing it, which can be useful if you’d like to examine the SQL closely or debug something. The SQL files are stored in the outputFolder
.
File and console logging is enabled across most Achilles functions. The status of each step is logged into files in the outputFolder
. You can review the files in a common text editor, or use the Shiny Application from the ParallelLogger
package to view them more interactively.
ParallelLogger::launchLogViewer(logFileName = "output/log_achilles.txt")
The verboseMode
parameter can be set to FALSE if you’d like less details about the function execution to appear in the console. Either way, all details are written to the log files. By default, this is set to TRUE.
In order to run the package, you will need to determine if you’d like the Achilles tables and staging tables to be stored in schemas that are separate from your CDM’s schema (recommended), or within the same schema as the CDM.
As the achilles and most of the achillesHeel functions can run independently, we have added a multi-threaded mode to allow for more than 1 SQL script to execute at a time. This is particularly useful for massively parallel processing (MPP) platforms such as Amazon Redshift and Microsoft PDW. It may not be beneficial for traditional SQL platforms, so only use the multi-threaded mode if confident it can be useful.
Further, while multiple threads can help performance in MPP platforms, there can be diminishing returns as the cluster has a finite number of concurrency slots to handle the queries. A rule of thumb: most likely you should not use more than 10.
In the multi-threaded mode, all scripts produce permanent staging tables, whereas in the single-threaded mode, the scripts produce temporary staging tables. In both, the staging tables are merged to produce the final Achilles tables.
The following sub-sections describe the optional parameters in achilles that can be configured, regardless of whether you run the function in single- or multi-threaded mode.
To keep the staging tables organized, the achilles function will use a table prefix of “tmpach” by default, but you can choose a different one using the tempAchillesPrefix
parameter. This is useful for database platforms like Oracle, which limit the length of table names.
The sourceName
parameter is used to assign the name of the dataset to the Achilles results. It is used in the Dashboard page in AchillesWeb and Atlas Data Sources. If you set this to NULL
, the achilles function will try to obtain the source name from the CDM_SOURCE table.
The createTable
parameter, when set to TRUE
, drops any existing Achilles results tables and builds new ones. If set to FALSE
, these tables will persist, and the achilles function will just insert new data to them.
By default, the achilles function runs all analyses detailed in the getAnalysisDetails
function. However, it may be useful to focus on a subset of analyses rather than running the whole set. This can be accomplished by specifying analysis Ids in the analysisIds
parameter.
By default, the achilles function does not run analyses on the COST table(s), as they can be very time-consuming, and are not critical to most OHDSI studies. However, you can choose to run these analyses by setting runCostAnalysis
to TRUE
. The cost analyses are conditional on the CDM version. If using CDM v5.0, then the older cost tables are queried. If using any version after 5.0, the unified cost table is queried.
To avoid patient identification, you can establish the minimum cell size that should be kept in the Achilles tables. Cells with small counts (less than or equal to the value of the smallCellCount
parameter) are deleted. By default, this is set to 5. Set to 0 for complete summary without small cell count restrictions.
See the Post-Processing section to read about how to run this step separately
This parameter is only necessary if running in multi-threaded mode
The dropScratchTables
parameter, if set to TRUE
, will drop all staging tables created during the execution of achilles in multi-threaded mode.
See the Post-Processing section to read about how to run this step separately
The createIndices
parameter, if set to TRUE
, will result in indices on the Achilles results tables to be created in order to improve query performance.
When running achilles, the return value, if you assign a variable to the function call, is a list object in which metadata about the execution and all of the SQL scripts executed are attributes. You can also run the function call without assigning a variable to it, so that no values are printed or returned.
In single-threaded mode, there is no need to set a scratchDatabaseSchema
, as temporary tables will be used. Here we will focus only on achilles execution and skip running Heel.
connectionDetails <- createConnectionDetails(dbms = "postgresql",
server = "localhost/synpuf",
user = "cdm_user",
password = "cdm_password")
achilles(connectionDetails = connectionDetails,
cdmDatabaseSchema = "cdm",
resultsDatabaseSchema = "results",
vocabDatabaseSchema = "vocab",
sourceName = "Synpuf",
cdmVersion = 5.3,
numThreads = 1,
runHeel = FALSE)
In multi-threaded mode, you need to specify scratchDatabaseSchema
and use > 1 for numThreads
. Here we will focus only on achilles execution and skip running Heel.
connectionDetails <- createConnectionDetails(dbms = "postgresql",
server = "localhost/synpuf",
user = "cdm_user",
password = "cdm_password")
achilles(connectionDetails = connectionDetails,
cdmDatabaseSchema = "cdm",
resultsDatabaseSchema = "results",
scratchDatabaseSchema = "scratch",
vocabDatabaseSchema = "vocab",
sourceName = "Synpuf",
cdmVersion = 5.3,
numThreads = 5,
runHeel = FALSE)
To keep the staging tables organized, the achillesHeel function will use a table prefix of “tmpheel” by default, but you can choose a different one using the tempHeelPrefix
parameter. This is useful for database platforms like Oracle, which limit the length of table names.
See the Post-Processing section to read about how to run this step separately
This parameter is only necessary if running in multi-threaded mode
The dropScratchTables
parameter, if set to TRUE
will drop all staging tables created during the execution of achillesHeel in multi-threaded mode.
The ThresholdAgeWarning
, ThresholdOutpatientVisitPerc
, and ThresholdMinimalPtMeasDxRx
parameters can be used to configure DQ thresholds in achillesHeel.
ThresholdAgeWarning
refers to the maximum age to allow in the dataset; by default, this is 125 years of age.ThresholdOutpatientVisitPerc
refers to the maximum percentage of outpatient visits allowed among all visits. This is by default set to 0.43.ThresholdMinimalPtMeasDxRx
refers to the minimum percentage required of patients with at least 1 measurement, 1 condition, and 1 drug exposure. This is by default set to 20.5%.In single-threaded mode, there is no need to set a scratchDatabaseSchema
, as temporary tables will be used.
connectionDetails <- createConnectionDetails(dbms = "postgresql",
server = "localhost/synpuf",
user = "cdm_user",
password = "cdm_password")
achillesHeel(connectionDetails = connectionDetails,
cdmDatabaseSchema = "cdm",
resultsDatabaseSchema = "results",
vocabDatabaseSchema = "vocab",
cdmVersion = 5.3,
numThreads = 1,
outputFolder = "output")
In multi-threaded mode, you need to specify scratchDatabaseSchema
and use > 1 for numThreads
.
connectionDetails <- createConnectionDetails(dbms = "postgresql",
server = "localhost/synpuf",
user = "cdm_user",
password = "cdm_password")
achillesHeel(connectionDetails = connectionDetails,
cdmDatabaseSchema = "cdm",
resultsDatabaseSchema = "results",
vocabDatabaseSchema = "vocab",
cdmVersion = 5.3,
numThreads = 5,
outputFolder = "output",
scratchDatabaseSchema = "scratch")
This section describes the usage of standalone functions for post-processing that can be invoked if you did not use them in the achilles function call.
Not supported by Amazon Redshift or IBM Netezza; function will skip this step if using those platforms
To improve query performance of the Achilles results tables, run the createIndices function.
connectionDetails <- createConnectionDetails(dbms = "postgresql",
server = "localhost/synpuf",
user = "cdm_user",
password = "cdm_password")
createIndices(connectionDetails = connectionDetails,
resultsDatabaseSchema = "results",
outputFolder = "output")
If the achilles or achillesHeel execution has errors, or if you did not enable this step in the call to these functions, use the dropAllScratchTables
function.
The tableTypes
parameter can be used to specify which batch of staging tables to drop (“achilles”, “heel”). The default value is to drop them all.
connectionDetails <- createConnectionDetails(dbms = "postgresql",
server = "localhost/synpuf",
user = "cdm_user",
password = "cdm_password")
dropAllScratchTables(connectionDetails = connectionDetails,
scratchDatabaseSchema = "scratch", numThreads = 5)
To view the Heel results, you can use the fetchAchillesHeelResults() function or the launchHeelResultsViewer() function. The former produces an R data frame that you can then export to various formats. The latter launches a Shiny application that renders the results in an easy to consume HTML file that can be viewed in your internet browser.
Heel Results are warnings split into 3 categories:
Once achillesHeel is run, you can fetch the results into a data frame for further consumption into whichever format you like using the fetchAchillesHeelResults function.
connectionDetails <- createConnectionDetails(dbms = "postgresql",
server = "localhost/synpuf",
user = "cdm_user",
password = "cdm_password")
fetchAchillesHeelResults(connectionDetails = connectionDetails,
resultsDatabaseSchema = "results")
The Heel Results Shiny Application can be useful in interacting with the Heel Results. The Heel warnings are color-coded based on severity (“ERROR”, “WARNING”, “NOTIFICATION”), and are searchable. You can also click on a row to see the associated Analysis and Heel SQL scripts to try to debug the root cause. Results can be downloaded to CSV using the “Download Heel Results” button.
When calling launchHeelResultsViewer, use the same parameters you used to execute achilles and achillesHeel. The Shiny app will use the parameters to render and translate the associated SQL scripts so that you can copy and run them separately to debug issues.
connectionDetails <- DatabaseConnector::createConnectionDetails(dbms = "postgresql",
server = "localhost/synpuf",
user = "cdm_user",
password = "cdm_password")
launchHeelResultsViewer(connectionDetails = connectionDetails,
cdmDatabaseSchema = "cdm",
resultsDatabaseSchema = "results",
scratchDatabaseSchema = "scratch",
outputFolder = "output",
numThreads = 5)
AchillesWeb is a lightweight web application that can be used to consume the Achilles and Heel results graphically. It is no longer actively updated, as development priorities have shifted towards Atlas Data Sources, but AchillesWeb can still be utilized. To connect Achilles results to AchillesWeb, the Achilles results need to be exported to JSON files and the AchillesWeb JSON file needs to point to those JSON files.
Please refer to AchillesWeb for more information.
The exportToJson
function can export all of the Achilles results to JSON files that AchillesWeb can consume.
compressIntoOnFile
parameter, if set to TRUE
, will compress all of the files into one zip file for easier portability.reports
parameter can be used to export specific reports rather than all. Use the showReportTypes
function to see all possible reports.
connectionDetails <- createConnectionDetails(dbms = "postgresql",
server = "localhost/synpuf",
user = "cdm_user",
password = "cdm_password")
exportToJson(connectionDetails = connectionDetails,
cdmDatabaseSchema = "cdm",
resultsDatabaseSchema = "results",
outputPath = "output",
vocabDatabaseSchema = "vocab")
AchillesWeb relies upon a JSON file to point to CDM Achilles result JSON files.
addDataSource(jsonFolderPath = "output",
dataSourcePath = "achillesWeb")
Considerable work has been dedicated to provide the Achilles
package.
citation("Achilles")
#>
#> To cite package 'Achilles' in publications use:
#>
#> Patrick Ryan, Martijn Schuemie, Vojtech Huser, Chris Knoll, Ajit
#> Londhe and Taha Abdul-Basser (2019). Achilles: Creates Descriptive
#> Statistics Summary for an Entire OMOP CDM Instance. R package version
#> 1.6.7.
#>
#> A BibTeX entry for LaTeX users is
#>
#> @Manual{,
#> title = {Achilles: Creates Descriptive Statistics Summary for an Entire OMOP CDM Instance},
#> author = {Patrick Ryan and Martijn Schuemie and Vojtech Huser and Chris Knoll and Ajit Londhe and Taha Abdul-Basser},
#> year = {2019},
#> note = {R package version 1.6.7},
#> }


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Rests
Two types of rest symbols are supported. Normal rests and long rests.
Normal rests are rests of which duration is not more than one measure and is specified by small letter "r" followed by duration indictor.
Long rests are rests of which duration is multiple of one measure and is specified by number of measures to rest enclosed within hyphens.
| Markdown | note |
|---|---|
| r:1 r:2 r:4 r:8 r:16 r:32 r:64 | Normal rests of whote rest, half rest, quarter rest, eighth rest, sixteenth rest thirty-second rest and six-forth rest. Please see duration indicator for the detail of duration indicator syntax. |
| -2- | Long rests with duration of 2 measures. Arbitral integer can be specified within hyphens. |


This tests that plug-ins can access objects in other frames as allowed by the security model enforced in WebCore.
FAILURE


Whincup ends first Newcastle 500 day on top by just 0.0057s
by James PaveyJamie Whincup and the Red Bull Holden Racing Team have combined to land the first blow on the streets of Newcastle, with the seven-time champion ousting Cameron Waters and teammate Shane van Gisbergen in a hotly-contested Practice 2.
Whincup launched to P1 at the death in the 30-minute session to set a session-best 1:10.3173s – but Waters’ #5 Monster Energy Mustang was just 0.0057s down the road, with van Gisbergen a further 0.0549s down.
The top eight were separated by a scant 0.1301s, with Practice 1 fast man Scott McLaughlin fourth in the session, just 0.0666s down on Whincup’s benchmark.
Stream the 2019 Coates Hire Newcastle 500. Live & Ad-Break Free During Racing on KAYO SPORTS. Get your 14 day free trial >
READ MORE
Illness strikes: Pye hospitalised, ruled out of Friday Supercars action
‘Very difficult’: Drivers grapple with tough Newcastle circuit, weather conditions
Drama: McLaughlin fastest in opening Newcastle practice despite hairy moment
‘That’s our full focus’: The ‘other’ championship up for grabs
David Reynolds – who brought out an early red flag due to an off – was fifth in the #9 Penrite Racing ZB Commodore, ahead of Mark Winterbottom (#18 IRWIN Racing ZB Commodore), James Courtney (#22 Walkinshaw Andretti United) and Fabian Coulthard (#12 Shell V-Power Racing Mustang).
Todd Hazelwood continued his strong Friday pace to drop the #35 SS Signs ZB Commodore into ninth, with Lee Holdsworth (#5 The Bottle-O Racing Mustang) rounding out the top 10.
The tight margins, although skewed somewhat by the changeable weather conditions, have set up the top two teams for a weekend-long battle for the teams’ championship.
LISTEN TO THE LATEST PODCAST: Mark Skaife l Post-Bathurst Controversy Mkii l Bairdo’s bungle l Triple Eight Turnaround
SUBSCRIBE TO THE SHOW: iTUNES | SPOTIFY | STITCHER
McLaughlin has already sealed the drivers’ title, but just 116 points separate Shell V-Power Racing and the Red Bull Holden squad in the battle for pit lane priority, with 576 points on offer this weekend in Newcastle.
Both factory Holdens need to be up the front to keep their hopes alive, and they did so on Friday. However, Whincup admitted there’s more in his car, but was happy to set the fastest time on his final lap.
“My car didn’t feel that flash then on good tyres, but it’s clearly quick,” said Whincup.
“I think our drive is okay, we’re just struggling with a bit of turn. We’ll work on getting them to turn through that change of direction a little bit faster.
“If we can do that, I think we’ll improve for tomorrow.”
Full results here.


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Mother of 3👩🏾🎤 part time moon dancer part time IT tech


File System Shell Guide
Overview
The File System (FS) shell includes various shell-like commands that directly interact with the Hadoop Distributed File System (HDFS) as well as other file systems that Hadoop supports, such as Local FS, HFTP FS, S3 FS, and others. The FS shell is invoked by:
bin/hdfs dfs <args>
All FS shell commands take path URIs as arguments. The URI format is scheme://autority/path. For HDFS the scheme is hdfs, and for the Local FS the scheme is file. The scheme and authority are optional. If not specified, the default scheme specified in the configuration is used. An HDFS file or directory such as /parent/child can be specified as hdfs://namenodehost/parent/child or simply as /parent/child (given that your configuration is set to point to hdfs://namenodehost).
Most of the commands in FS shell behave like corresponding Unix commands. Differences are described with each of the commands. Error information is sent to stderr and the output is sent to stdout.
cat
Usage: hdfs dfs -cat URI [URI …]
Copies source paths to stdout.
Example:
- hdfs dfs -cat hdfs://nn1.example.com/file1 hdfs://nn2.example.com/file2
- hdfs dfs -cat file:///file3 /user/hadoop/file4
Exit Code:
Returns 0 on success and -1 on error.
chgrp
Usage: hdfs dfs -chgrp [-R] GROUP URI [URI …]
Change group association of files. With -R, make the change recursively through the directory structure. The user must be the owner of files, or else a super-user. Additional information is in the Permissions Guide.
chmod
Usage: hdfs dfs -chmod [-R] <MODE[,MODE]... | OCTALMODE> URI [URI …]
Change the permissions of files. With -R, make the change recursively through the directory structure. The user must be the owner of the file, or else a super-user. Additional information is in the Permissions Guide.
chown
Usage: hdfs dfs -chown [-R] [OWNER][:[GROUP]] URI [URI ]
Change the owner of files. With -R, make the change recursively through the directory structure. The user must be a super-user. Additional information is in the Permissions Guide.
copyFromLocal
Usage: hdfs dfs -copyFromLocal <localsrc> URI
Similar to put command, except that the source is restricted to a local file reference.
copyToLocal
Usage: hdfs dfs -copyToLocal [-ignorecrc] [-crc] URI <localdst>
Similar to get command, except that the destination is restricted to a local file reference.
count
Usage: hdfs dfs -count [-q] <paths>
Count the number of directories, files and bytes under the paths that match the specified file pattern.
The output columns with -count are:
DIR_COUNT, FILE_COUNT, CONTENT_SIZE FILE_NAME
The output columns with -count -q are:
QUOTA, REMAINING_QUATA, SPACE_QUOTA, REMAINING_SPACE_QUOTA,
DIR_COUNT, FILE_COUNT, CONTENT_SIZE, FILE_NAME
Example:
- hdfs dfs -count hdfs://nn1.example.com/file1 hdfs://nn2.example.com/file2
- hdfs dfs -count -q hdfs://nn1.example.com/file1
Exit Code:
Returns 0 on success and -1 on error.
cp
Usage: hdfs dfs -cp URI [URI …] <dest>
Copy files from source to destination. This command allows multiple sources as well in which case the destination must be a directory.
Example:
- hdfs dfs -cp /user/hadoop/file1 /user/hadoop/file2
- hdfs dfs -cp /user/hadoop/file1 /user/hadoop/file2 /user/hadoop/dir
Exit Code:
Returns 0 on success and -1 on error.
du
Usage: hdfs dfs -du [-s] [-h] URI [URI …]
Displays sizes of files and directories contained in the given directory or the length of a file in case its just a file.
Options:
- The -s option will result in an aggregate summary of file lengths being displayed, rather than the individual files.
- The -h option will format file sizes in a "human-readable" fashion (e.g 64.0m instead of 67108864)
Example:
hdfs dfs -du /user/hadoop/dir1 /user/hadoop/file1 hdfs://nn.example.com/user/hadoop/dir1
Exit Code:
Returns 0 on success and -1 on error.
dus
Usage: hdfs dfs -dus <args>
Displays a summary of file lengths. This is an alternate form of hdfs dfs -du -s.
expunge
Usage: hdfs dfs -expunge
Empty the Trash. Refer to the HDFS Architecture Guide for more information on the Trash feature.
get
Usage: hdfs dfs -get [-ignorecrc] [-crc] <src> <localdst>
Copy files to the local file system. Files that fail the CRC check may be copied with the -ignorecrc option. Files and CRCs may be copied using the -crc option.
Example:
- hdfs dfs -get /user/hadoop/file localfile
- hdfs dfs -get hdfs://nn.example.com/user/hadoop/file localfile
Exit Code:
Returns 0 on success and -1 on error.
getmerge
Usage: hdfs dfs -getmerge <src> <localdst> [addnl]
Takes a source directory and a destination file as input and concatenates files in src into the destination local file. Optionally addnl can be set to enable adding a newline character at the end of each file.
ls
Usage: hdfs dfs -ls <args>
For a file returns stat on the file with the following format:
permissions number_of_replicas userid groupid filesize modification_date modification_time filename
For a directory it returns list of its direct children as in unix.A directory is listed as:
permissions userid groupid modification_date modification_time dirname
Example:
hdfs dfs -ls /user/hadoop/file1
Exit Code:
Returns 0 on success and -1 on error.
lsr
Usage: hdfs dfs -lsr <args>
Recursive version of ls. Similar to Unix ls -R.
mkdir
Usage: hdfs dfs -mkdir <paths>
Takes path uri's as argument and creates directories. The behavior is much like unix mkdir -p creating parent directories along the path.
Example:
- hdfs dfs -mkdir /user/hadoop/dir1 /user/hadoop/dir2
- hdfs dfs -mkdir hdfs://nn1.example.com/user/hadoop/dir hdfs://nn2.example.com/user/hadoop/dir
Exit Code:
Returns 0 on success and -1 on error.
moveFromLocal
Usage: dfs -moveFromLocal <localsrc> <dst>
Similar to put command, except that the source localsrc is deleted after it's copied.
moveToLocal
Usage: hdfs dfs -moveToLocal [-crc] <src> <dst>
Displays a "Not implemented yet" message.
mv
Usage: hdfs dfs -mv URI [URI …] <dest>
Moves files from source to destination. This command allows multiple sources as well in which case the destination needs to be a directory.
Moving files across file systems is not permitted.
Example:
- hdfs dfs -mv /user/hadoop/file1 /user/hadoop/file2
- hdfs dfs -mv hdfs://nn.example.com/file1 hdfs://nn.example.com/file2 hdfs://nn.example.com/file3 hdfs://nn.example.com/dir1
Exit Code:
Returns 0 on success and -1 on error.
put
Usage: hdfs dfs -put <localsrc> ... <dst>
Copy single src, or multiple srcs from local file system to the destination file system.
Also reads input from stdin and writes to destination file system.
- hdfs dfs -put localfile /user/hadoop/hadoopfile
- hdfs dfs -put localfile1 localfile2 /user/hadoop/hadoopdir
- hdfs dfs -put localfile hdfs://nn.example.com/hadoop/hadoopfile
-
hdfs dfs -put - hdfs://nn.example.com/hadoop/hadoopfile
Reads the input from stdin.
Exit Code:
Returns 0 on success and -1 on error.
rm
Usage: hdfs dfs -rm [-skipTrash] URI [URI …]
Delete files specified as args. Only deletes non empty directory and files. If the -skipTrash option
is specified, the trash, if enabled, will be bypassed and the specified file(s) deleted immediately. This can be
useful when it is necessary to delete files from an over-quota directory.
Refer to rmr for recursive deletes.
Example:
- hdfs dfs -rm hdfs://nn.example.com/file /user/hadoop/emptydir
Exit Code:
Returns 0 on success and -1 on error.
rmr
Usage: hdfs dfs -rmr [-skipTrash] URI [URI …]
Recursive version of delete. If the -skipTrash option
is specified, the trash, if enabled, will be bypassed and the specified file(s) deleted immediately. This can be
useful when it is necessary to delete files from an over-quota directory.
Example:
- hdfs dfs -rmr /user/hadoop/dir
- hdfs dfs -rmr hdfs://nn.example.com/user/hadoop/dir
Exit Code:
Returns 0 on success and -1 on error.
setrep
Usage: hdfs dfs -setrep [-R] <path>
Changes the replication factor of a file. -R option is for recursively increasing the replication factor of files within a directory.
Example:
- hdfs dfs -setrep -w 3 -R /user/hadoop/dir1
Exit Code:
Returns 0 on success and -1 on error.
stat
Usage: hdfs dfs -stat URI [URI …]
Returns the stat information on the path.
Example:
- hdfs dfs -stat path
Exit Code:
Returns 0 on success and -1 on error.
tail
Usage: hdfs dfs -tail [-f] URI
Displays last kilobyte of the file to stdout. -f option can be used as in Unix.
Example:
- hdfs dfs -tail pathname
Exit Code:
Returns 0 on success and -1 on error.
test
Usage: hdfs dfs -test -[ezd] URI
Options:
-e check to see if the file exists. Return 0 if true.
-z check to see if the file is zero length. Return 0 if true.
-d check to see if the path is directory. Return 0 if true.
Example:
- hdfs dfs -test -e filename
text
Usage: hdfs dfs -text <src>
Takes a source file and outputs the file in text format. The allowed formats are zip and TextRecordInputStream.
touchz
Usage: hdfs dfs -touchz URI [URI …]
Create a file of zero length.
Example:
- hadoop -touchz pathname
Exit Code:
Returns 0 on success and -1 on error.


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Hello.
I think it would be handy have an option to enable automatic server refresh when filter was changed (don't need press "refresh and save filter" button.
In addition a separate option to auto save filter would be nice too.
Thanks.
BrainFooLong
Administrator
It's possible, i noticed it to my todo list.
Keep watchin for updates.
Sorry, not the place to post other addon versions here.
You could make modified versions, as the license allow it.
But please not post it in request tracker, its definitly the wrong place.
Thanks for the work, but this feature is already implemented in the bblog svn trunk.
BrainFooLong
Administrator
PS: When you would help developing this addon we need to talk outside of the tracker to prevent this "double" work. You can contact me with the mail in "contact".
BrainFooLong
Administrator
Is now included since version 1.1
Topicstarter
Guest
Please add to the filter window when pressed enter key while in a input field it should be treated as pressing "ok" button


| Overview | Module | Use | Devguide | Index |
| Services' Summary | Interfaces' Summary | Properties' Summary | Services' Details | Interfaces' Details | Properties' Details |
| service DataPointProperties |
| Included Services - Summary | |
| ::com::sun::star::beans::PropertySet | to give acces to the properties required by this service. |
| Properties' Summary | |
| long Color |
This is the main color of a data point. |
| short Transparency |
This is the main transparency value of a data point. |
| ::com::sun::star::drawing::FillStyle FillStyle |
This enumeration selects the style with which the area will be filled. |
| ::com::sun::star::awt::Gradient TransparencyGradient |
[ OPTIONAL ] This describes the transparency of the fill area as a gradient. |
| ::com::sun::star::awt::Gradient Gradient |
[ OPTIONAL ] |
| ::com::sun::star::drawing::Hatch Hatch |
[ OPTIONAL ] |
| string TransparencyGradientName |
|
| string GradientName |
|
| string HatchName |
|
| string FillBitmapName |
|
| boolean FillBackground |
If true, fills the background of a hatch with the color given in the Color property. |
| long BorderColor |
Is used for borders around filled objects. See
LineColor .
|
| ::com::sun::star::drawing::LineStyle BorderStyle |
Is used for borders around filled objects. See
LineStyle .
|
| long BorderWidth |
Is used for borders around filled objects. See
LineWidth .
|
| ::com::sun::star::drawing::LineDash BorderDash |
Is used for borders around filled objects. See
LineDash .
|
| string BorderDashName |
[ OPTIONAL ] The name of a dash that can be found in the ::com::sun::star::container::XNameContainer "com.sun.star.drawing.LineDashTable", that can be created via the com::sun::star::uno::XMultiServiceFactory of the ChartDocument. |
| short BorderTransparency |
[ OPTIONAL ] Is used for borders around filled objects. See LineTransparence .
|
| ::com::sun::star::drawing::LineStyle LineStyle |
|
| long LineWidth |
Is only used for line-chart types. |
| ::com::sun::star::drawing::LineDash LineDash |
Is only used for line-chart types. |
| string LineDashName |
[ OPTIONAL ] The name of a dash that can be found in the ::com::sun::star::container::XNameContainer "com.sun.star.drawing.LineDashTable", that can be created via the com::sun::star::uno::XMultiServiceFactory of the ChartDocument. |
| short FillBitmapOffsetX |
This is the horizontal offset where the tile starts. |
| short FillBitmapOffsetY |
This is the vertical offset where the tile starts. It is given in percent in relation to the width of the bitmap. |
| short FillBitmapPositionOffsetX |
Every second line of tiles is moved the given percent of the witdh of the bitmap. |
| short FillBitmapPositionOffsetY |
Every second row of tiles is moved the given percent of the width of the bitmap. |
| ::com::sun::star::drawing::RectanglePoint FillBitmapRectanglePoint |
The RectanglePoint specifies the position inside of the bitmap to use as the top left position for rendering. |
| boolean FillBitmapLogicalSize |
specifies if the size is given in percentage or as an absolute value. |
| long FillBitmapSizeX |
This is the width of the tile for filling. |
| long FillBitmapSizeY |
This is the height of the tile for filling. |
| ::com::sun::star::drawing::BitmapMode FillBitmapMode |
this enum selects how a area is filled with a single bitmap. |
| Symbol Symbol |
[ OPTIONAL ] |
| double Offset |
[ OPTIONAL ] describes a value by which a data point is moved from its default position in percent of the maximum allowed distance. |
| long Geometry3D |
[ OPTIONAL ] describes the geometry of a 3 dimensional datapoint. Number is one of constant group DataPointGeometry3D. |
| DataPointLabel Label |
|
| string LabelSeparator |
[ OPTIONAL ] specifies a string that is used to separate the parts of a data label (caption) |
| long NumberFormat |
[ OPTIONAL ] specifies a number format for the display of the value in the data label |
| long PercentageNumberFormat |
[ OPTIONAL ] specifies a number format for the display of the percentage value in the data label |
| long LabelPlacement |
[ OPTIONAL ] specifies a relative position for the data label |
| [ maybevoid ] ::com::sun::star::awt::Size ReferencePageSize |
The size of the page at the moment when the font size for data labels was set. |
| [ maybevoid ] ::com::sun::star::beans::XPropertySet ErrorBarX |
[ OPTIONAL ] If void, no error bars are shown for the data point in x-direction. |
| [ maybevoid ] ::com::sun::star::beans::XPropertySet ErrorBarY |
[ OPTIONAL ] If void, no error bars are shown for the data point in y-direction. |
| [ maybevoid ] boolean ShowErrorBox |
[ OPTIONAL ] In case ErrorBarX and ErrorBarY both are set, and error bars are shown, a box spanning all error-indicators is rendered. |
| [ maybevoid ] short PercentDiagonal |
[ OPTIONAL ] A value between 0 and 100 indicating the percentage how round an edge should be. |
| Included Services - Details | |
::com::sun::star::beans::PropertySet
|
| Properties' Details | |
Color
|
|
Transparency
|
|
FillStyle
|
|
TransparencyGradient
|
|
Gradient
|
|
Hatch
|
|
TransparencyGradientName
|
|
GradientName
|
|
HatchName
|
|
FillBitmapName
|
|
FillBackground
|
|
BorderColor
|
|
BorderStyle
|
|
BorderWidth
|
|
BorderDash
|
|
BorderDashName
|
|
BorderTransparency
|
|
LineStyle
|
|
LineWidth
|
|
LineDash
|
|
LineDashName
|
|
FillBitmapOffsetX
|
|
FillBitmapOffsetY
|
|
FillBitmapPositionOffsetX
|
|
FillBitmapPositionOffsetY
|
|
FillBitmapRectanglePoint
|
|
FillBitmapLogicalSize
|
|
FillBitmapSizeX
|
|
FillBitmapSizeY
|
|
FillBitmapMode
|
|
Symbol
|
|
Offset
|
|
Geometry3D
|
|
Label
|
|
LabelSeparator
|
|
NumberFormat
|
|
PercentageNumberFormat
|
|
LabelPlacement
|
|
ReferencePageSize
|
|
ErrorBarX
|
|
ErrorBarY
|
|
ShowErrorBox
|
|
PercentDiagonal
|
Copyright © 2013, The Apache Software Foundation, Licensed under the Apache License, Version 2.0. Apache, the Apache feather logo, Apache OpenOffice and OpenOffice.org are trademarks of The Apache Software Foundation. Other names may be trademarks of their respective owners.


In this project, you'll use generative adversarial networks to generate new images of faces.
You'll be using two datasets in this project:
Since the celebA dataset is complex and you're doing GANs in a project for the first time, we want you to test your neural network on MNIST before CelebA. Running the GANs on MNIST will allow you to see how well your model trains sooner.
If you're using FloydHub, set data_dir
to "/input" and use the FloydHub data ID "R5KrjnANiKVhLWAkpXhNBe".
data_dir = './data'
# FloydHub - Use with data ID "R5KrjnANiKVhLWAkpXhNBe"
#data_dir = '/input'
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import helper
helper.download_extract('mnist', data_dir)
helper.download_extract('celeba', data_dir)
show_n_images = 25
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
%matplotlib inline
import os
from glob import glob
from matplotlib import pyplot
mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'mnist/*.jpg'))[:show_n_images], 28, 28, 'L')
pyplot.imshow(helper.images_square_grid(mnist_images, 'L'), cmap='gray')
The CelebFaces Attributes Dataset (CelebA) dataset contains over 200,000 celebrity images with annotations. Since you're going to be generating faces, you won't need the annotations. You can view the first number of examples by changing show_n_images
.
show_n_images = 25
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'img_align_celeba/*.jpg'))[:show_n_images], 28, 28, 'RGB')
pyplot.imshow(helper.images_square_grid(mnist_images, 'RGB'))
Since the project's main focus is on building the GANs, we'll preprocess the data for you. The values of the MNIST and CelebA dataset will be in the range of -0.5 to 0.5 of 28x28 dimensional images. The CelebA images will be cropped to remove parts of the image that don't include a face, then resized down to 28x28.

You'll build the components necessary to build a GANs by implementing the following functions below:
model_inputs
discriminator
generator
model_loss
model_opt
train
This will check to make sure you have the correct version of TensorFlow and access to a GPU
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
from distutils.version import LooseVersion
import warnings
import tensorflow as tf
# Check TensorFlow Version
assert LooseVersion(tf.__version__) >= LooseVersion('1.0'), 'Please use TensorFlow version 1.0 or newer. You are using {}'.format(tf.__version__)
print('TensorFlow Version: {}'.format(tf.__version__))
# Check for a GPU
if not tf.test.gpu_device_name():
warnings.warn('No GPU found. Please use a GPU to train your neural network.')
else:
print('Default GPU Device: {}'.format(tf.test.gpu_device_name()))
Implement the model_inputs
function to create TF Placeholders for the Neural Network. It should create the following placeholders:
image_width
, image_height
, and image_channels
.z_dim
.Return the placeholders in the following the tuple (tensor of real input images, tensor of z data)
import problem_unittests as tests
def model_inputs(image_width, image_height, image_channels, z_dim):
"""
Create the model inputs
:param image_width: The input image width
:param image_height: The input image height
:param image_channels: The number of image channels
:param z_dim: The dimension of Z
:return: Tuple of (tensor of real input images, tensor of z data, learning rate)
"""
# TODO: Implement Function
real_inputs = tf.placeholder(tf.float32, (None, image_width, image_height, image_channels), 'real_inputs')
z_inputs = tf.placeholder(tf.float32, (None, z_dim), 'z_inputs')
learning_rate = tf.placeholder(tf.float32, name='learning_rate')
return real_inputs, z_inputs, learning_rate
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_inputs(model_inputs)
Implement discriminator
to create a discriminator neural network that discriminates on images
. This function should be able to reuse the variabes in the neural network. Use tf.variable_scope
with a scope name of "discriminator" to allow the variables to be reused. The function should return a tuple of (tensor output of the discriminator, tensor logits of the discriminator).
def discriminator(images, reuse=False):
"""
Create the discriminator network
:param image: Tensor of input image(s)
:param reuse: Boolean if the weights should be reused
:return: Tuple of (tensor output of the discriminator, tensor logits of the discriminator)
"""
# TODO: Implement Function
with tf.variable_scope('discriminator', reuse=reuse):
alpha = 0.2
# Conv 1
h1 = tf.layers.conv2d(images, 64, 5, 2, 'same')
h1 = tf.maximum(alpha * h1, h1)
# Conv 2
h2 = tf.layers.conv2d(h1, 128, 5, 2, 'same')
h2 = tf.layers.batch_normalization(h2, training=True)
h2 = tf.maximum(alpha * h2, h2)
# Conv 3
h3 = tf.layers.conv2d(h2, 256, 5, 2, 'same')
h3 = tf.layers.batch_normalization(h3, training=True)
h3 = tf.maximum(alpha * h3, h3)
# Flatten
flat = tf.reshape(h3, (-1, 4*4*256))
# Logits
logits = tf.layers.dense(flat, 1)
# Output
out = tf.sigmoid(logits)
return out, logits
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_discriminator(discriminator, tf)
Implement generator
to generate an image using z
. This function should be able to reuse the variabes in the neural network. Use tf.variable_scope
with a scope name of "generator" to allow the variables to be reused. The function should return the generated 28 x 28 x out_channel_dim
images.
def generator(z, out_channel_dim, is_train=True):
"""
Create the generator network
:param z: Input z
:param out_channel_dim: The number of channels in the output image
:param is_train: Boolean if generator is being used for training
:return: The tensor output of the generator
"""
# TODO: Implement Function
with tf.variable_scope('generator', reuse=not is_train):
alpha = 0.2
h1 = tf.layers.dense(z, 2*2*512)
h1 = tf.reshape(h1, (-1, 2, 2, 512))
h1 = tf.layers.batch_normalization(h1, training=is_train)
h1 = tf.maximum(alpha * h1, h1)
h2 = tf.layers.conv2d_transpose(h1, 256, 5, 2, 'valid')
h2 = tf.layers.batch_normalization(h2, training=is_train)
h2 = tf.maximum(alpha * h2, h2)
h3 = tf.layers.conv2d_transpose(h2, 128, 5, 2, 'same')
h3 = tf.layers.batch_normalization(h3, training=is_train)
h3 = tf.maximum(alpha * h3, h3)
logits = tf.layers.conv2d_transpose(h3, out_channel_dim, 5, 2, 'same')
out = tf.tanh(logits)
return out
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_generator(generator, tf)
Implement model_loss
to build the GANs for training and calculate the loss. The function should return a tuple of (discriminator loss, generator loss). Use the following functions you implemented:
discriminator(images, reuse=False)
generator(z, out_channel_dim, is_train=True)
def model_loss(input_real, input_z, out_channel_dim):
"""
Get the loss for the discriminator and generator
:param input_real: Images from the real dataset
:param input_z: Z input
:param out_channel_dim: The number of channels in the output image
:return: A tuple of (discriminator loss, generator loss)
"""
# TODO: Implement Function
g_model = generator(input_z, out_channel_dim)
d_model_real, d_logits_real = discriminator(input_real)
d_model_fake, d_logits_fake = discriminator(g_model, reuse=True)
d_loss_real = tf.reduce_mean(
tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_real, labels=tf.ones_like(d_model_real)))
d_loss_fake = tf.reduce_mean(tf.nn.sigmoid_cross_entropy_with_logits(
logits=d_logits_fake, labels=tf.zeros_like(d_model_fake)))
g_loss = tf.reduce_mean(tf.nn.sigmoid_cross_entropy_with_logits(
logits=d_logits_fake, labels=tf.ones_like(d_model_fake)))
d_loss = d_loss_real + d_loss_fake
return d_loss, g_loss
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_loss(model_loss)
Implement model_opt
to create the optimization operations for the GANs. Use tf.trainable_variables
to get all the trainable variables. Filter the variables with names that are in the discriminator and generator scope names. The function should return a tuple of (discriminator training operation, generator training operation).
def model_opt(d_loss, g_loss, learning_rate, beta1):
"""
Get optimization operations
:param d_loss: Discriminator loss Tensor
:param g_loss: Generator loss Tensor
:param learning_rate: Learning Rate Placeholder
:param beta1: The exponential decay rate for the 1st moment in the optimizer
:return: A tuple of (discriminator training operation, generator training operation)
"""
# TODO: Implement Function
t_vars = tf.trainable_variables()
d_vars = [var for var in t_vars if var.name.startswith('discriminator')]
g_vars = [var for var in t_vars if var.name.startswith('generator')]
d_train_opt = tf.train.AdamOptimizer(
learning_rate, beta1=beta1).minimize(d_loss, var_list=d_vars)
ops = tf.get_collection(tf.GraphKeys.UPDATE_OPS)
g_updates = [opt for opt in ops if opt.name.startswith('generator')]
with tf.control_dependencies(g_updates):
g_train_opt = tf.train.AdamOptimizer(
learning_rate, beta1).minimize(g_loss, var_list=g_vars)
return d_train_opt, g_train_opt
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_opt(model_opt, tf)
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import numpy as np
def show_generator_output(sess, n_images, input_z, out_channel_dim, image_mode):
"""
Show example output for the generator
:param sess: TensorFlow session
:param n_images: Number of Images to display
:param input_z: Input Z Tensor
:param out_channel_dim: The number of channels in the output image
:param image_mode: The mode to use for images ("RGB" or "L")
"""
cmap = None if image_mode == 'RGB' else 'gray'
z_dim = input_z.get_shape().as_list()[-1]
example_z = np.random.uniform(-1, 1, size=[n_images, z_dim])
samples = sess.run(
generator(input_z, out_channel_dim, False),
feed_dict={input_z: example_z})
images_grid = helper.images_square_grid(samples, image_mode)
pyplot.imshow(images_grid, cmap=cmap)
pyplot.show()
Implement train
to build and train the GANs. Use the following functions you implemented:
model_inputs(image_width, image_height, image_channels, z_dim)
model_loss(input_real, input_z, out_channel_dim)
model_opt(d_loss, g_loss, learning_rate, beta1)
Use the show_generator_output
to show generator
output while you train. Running show_generator_output
for every batch will drastically increase training time and increase the size of the notebook. It's recommended to print the generator
output every 100 batches.
def train(epoch_count, batch_size, z_dim, learning_rate, beta1, get_batches, data_shape, data_image_mode):
"""
Train the GAN
:param epoch_count: Number of epochs
:param batch_size: Batch Size
:param z_dim: Z dimension
:param learning_rate: Learning Rate
:param beta1: The exponential decay rate for the 1st moment in the optimizer
:param get_batches: Function to get batches
:param data_shape: Shape of the data
:param data_image_mode: The image mode to use for images ("RGB" or "L")
"""
# TODO: Build Model
_, img_width, img_height, img_channels = data_shape
real_input, z_input, lr = model_inputs(
img_width, img_height, img_channels, z_dim)
d_loss, g_loss = model_loss(real_input, z_input, img_channels)
d_opt, g_opt = model_opt(d_loss, g_loss, learning_rate, beta1)
steps = 0
print_every = 10
show_every = 100
losses = []
n_images = 25
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
for epoch_i in range(epoch_count):
for batch_images in get_batches(batch_size):
# TODO: Train Model
steps += 1
batch_images *= 2.0
z_sample = np.random.uniform(-1, 1, (batch_size, z_dim))
_ = sess.run(d_opt, feed_dict={
real_input: batch_images, z_input: z_sample, lr: learning_rate})
_ = sess.run(g_opt, feed_dict={
z_input: z_sample, lr: learning_rate})
if steps % print_every == 0:
train_loss_d = d_loss.eval({z_input: z_sample, real_input: batch_images})
train_loss_g = g_loss.eval({z_input: z_sample})
print("Epoch {}/{}...".format(epoch_i+1, epoch_count),
"Discriminator Loss: {:.4f}...".format(train_loss_d),
"Generator Loss: {:.4f}".format(train_loss_g))
losses.append((train_loss_d, train_loss_g))
if steps % show_every == 0:
show_generator_output(sess, n_images, z_input, img_channels, data_image_mode)
Test your GANs architecture on MNIST. After 2 epochs, the GANs should be able to generate images that look like handwritten digits. Make sure the loss of the generator is lower than the loss of the discriminator or close to 0.
batch_size = 64
z_dim = 100
learning_rate = 0.001
beta1 = 0.5
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 2
mnist_dataset = helper.Dataset('mnist', glob(os.path.join(data_dir, 'mnist/*.jpg')))
with tf.Graph().as_default():
train(epochs, batch_size, z_dim, learning_rate, beta1, mnist_dataset.get_batches,
mnist_dataset.shape, mnist_dataset.image_mode)
Run your GANs on CelebA. It will take around 20 minutes on the average GPU to run one epoch. You can run the whole epoch or stop when it starts to generate realistic faces.
batch_size = 64
z_dim = 100
learning_rate = 0.0001
beta1 = 0.5
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 1
celeba_dataset = helper.Dataset('celeba', glob(os.path.join(data_dir, 'img_align_celeba/*.jpg')))
with tf.Graph().as_default():
train(epochs, batch_size, z_dim, learning_rate, beta1, celeba_dataset.get_batches,
celeba_dataset.shape, celeba_dataset.image_mode)
When submitting this project, make sure to run all the cells before saving the notebook. Save the notebook file as "dlnd_face_generation.ipynb" and save it as a HTML file under "File" -> "Download as". Include the "helper.py" and "problem_unittests.py" files in your submission.


Onomatopoeia = sound example >> Woof! Woof!
Personification = Inhuman item having human characteristics. example >> The wind whistled through the day.
Simile = Compare with As or Like. example >> Slept like a log.
Metaphor = Compare without As or like. example >> Love is a fruit.
Alliteration = Repeatsa speech sound in a sequece of words. example >> Peter Piper Picked a Pack...
Hyperbole = Exaggeration. example >> My shoes are killing me.
Imagery = Helph us create a mental picture. Used in poetry. example >> His coat felt like a velvet curtain.
Symbolism = Practice of using a word to represent an abstract idea. example >> four-leaf clover–symbolizes good luck or fortune.
Oxymoron = self-contradicting word or group of words. example >> original copy , walking dead , seriously funny.


{% dnd_section %} {% dnd_column %} {% dnd_row %} {% dnd_module path="@hubspot/rich_text", html={{ context.heading or '
For individuals or team just getting started with sales.
" }}, features=[ "Ad management", "Live chat", "Conversational bots", "Forms", "Pop-up forms", "Contact website activity", "List segmentation", "Email marketing", "Ad retargeting" ], offset=0, price={{ context.card_one_price or "$0" }}, tier={{ context.card_one_tier or "For teams that need to create sales plans with confidence.
" }}, features=[ "Marketing automation", "Smart content", "Content creation tools", "SEO & content strategy", "Social media", "A/B testing", "Landing pages", "Calls-to-action", "Video hosting" ], offset=4, price={{ context.card_two_price or "$1200" }}, tier={{ context.card_two_tier or "For teams that need additional security, control, and support.
" }}, features=[ "Content partitioning", "Hierarchical teams", "Single sign-on", "Social permissions", "Additional domains", "Email send frequency cap", "Calculated properties", "CMS membership", "Filtered analytics view" ], offset=8, price={{ context.card_three_price or "$3200" }}, tier={{ context.card_three_tier or "


Contact Us


class type cilPrinter = object
.. end
A printer interface for CIL trees. Create instantiations of
this type by specializing the class Cil.defaultCilPrinterClass
.
method setCurrentFormals : varinfo list -> unit
method setPrintInstrTerminator : string -> unit
method getPrintInstrTerminator : unit -> string
method pVDecl : unit -> varinfo -> Pretty.doc
Invoked for each variable declaration. Note that variable
declarations are all the GVar
, GVarDecl
, GFun
, all the varinfo
in formals of function types, and the formals and locals for function
definitions.
method pVar : varinfo -> Pretty.doc
Invoked on each variable use.
method pLval : unit -> lval -> Pretty.doc
Invoked on each lvalue occurrence
method pOffset : Pretty.doc -> offset -> Pretty.doc
Invoked on each offset occurrence. The second argument is the base.
method pInstr : unit -> instr -> Pretty.doc
Invoked on each instruction occurrence.
method pLabel : unit -> label -> Pretty.doc
Print a label.
method pStmt : unit -> stmt -> Pretty.doc
method dStmt : out_channel -> int -> stmt -> unit
Dump a control-flow statement to a file with a given indentation.
This is used by
Cil.dumpGlobal
.
method dBlock : out_channel -> int -> block -> unit
Dump a control-flow block to a file with a given indentation.
This is used by
Cil.dumpGlobal
.
method pBlock : unit -> block -> Pretty.doc
Print a block.
method pGlobal : unit -> global -> Pretty.doc
method dGlobal : out_channel -> global -> unit
Dump a global to a file with a given indentation. This is used by
Cil.dumpGlobal
method pFieldDecl : unit -> fieldinfo -> Pretty.doc
A field declaration
method pType : Pretty.doc option -> unit -> typ -> Pretty.doc
Use of some type in some declaration. The first argument is used to print
the declared element, or is None if we are just printing a type with no
name being declared. Note that for structure/union and enumeration types
the definition of the composite type is not visited. Use vglob
to
visit it.
method pAttr : attribute -> Pretty.doc * bool
Attribute. Also return an indication whether this attribute must be
printed inside the __attribute__ list or not.
method pAttrParam : unit -> attrparam -> Pretty.doc
Attribute parameter
method pAttrs : unit -> attributes -> Pretty.doc
Attribute lists
method pLineDirective : ?forcefile:bool -> location -> Pretty.doc
Print a line-number. This is assumed to come always on an empty line.
If the forcefile argument is present and is true then the file name
will be printed always. Otherwise the file name is printed only if it
is different from the last time time this function is called. The last
file name is stored in a private field inside the cilPrinter object.
method pStmtKind : stmt -> unit -> stmtkind -> Pretty.doc
Print a statement kind. The code to be printed is given in the
Cil.stmtkind
argument. The initial
Cil.stmt
argument
records the statement which follows the one being printed;
Cil.defaultCilPrinterClass
uses this information to prettify
statement printing in certain special cases.
method pExp : unit -> exp -> Pretty.doc
Print expressions
method pInit : unit -> init -> Pretty.doc
method dInit : out_channel -> int -> init -> unit
Dump a global to a file with a given indentation. This is used by
Cil.dumpGlobal


1942 - Born in Oxford, England to Frank and Isobel Hawking.
1950 - Family moves to St Albans, Hertfordshire. He attends St Albans school.
1959 - Gets rewarded scholarship at Oxford University and he finishes his undergraduate studies in just 4 years.
1962 - Begins his Graduate work at Trinity College, Cambridge
1965 - Married Jane Wilde, whom he had met shortly before his diagnosis with motor neurone disease, continued to develop.
1966 - Obtained his PhD degree in applied mathematics and theoretical physics, specialising in general relativity and cosmology, in March 1966; and his essay titled "Singularities and the Geometry of Space-Time" shared top honours with one by Penrose to win that year's prestigious Adams Prize.
1970 - Hawkings and Penrose, published a proof that if the universe obeys the general theory of relativity and fits any of the models of physical cosmology developed by Alexander Friedmann, then it must have begun as a singularity. With James M. Bardeen and Brandon Carter, he proposed the four laws of black hole mechanics, drawing an analogy with thermodynamics.
1973 - Hawking's first book, The Large Scale Structure of Space-Time, written with George Ellis, was published.
1975 - Moves back to Cambridge to a more academically senior post, as reader in gravitational physics. He was awarded both the Eddington Medal and the Pius XI Gold Medal.
1979 - Hawking's speech deteriorated, and by the late 1970s he could be understood by only his family and closest friends. To communicate with others, someone who knew him well would translate his speech into intelligible speech.
1982 - Hawking and Gary Gibbons organised a three-week Nuffield Workshop on "The Very Early Universe" at Cambridge University, which focused mainly on inflation theory. Hawking also began a new line of quantum theory research into the origin of the universe.
1984 - Completed first draft of the book, called A Brief History of Time. It is a popular-science book on cosmology.e discusses two major theories, general relativity and quantum mechanics, that modern scientists use to describe the universe. Sold over 9 million copies.
1985 - Hawking contracted pneumonia, which in his condition was life-threatening; he was so ill that Jane was asked if life support should be terminated. She refused, but the consequence was a tracheotomy, which would require round-the-clock nursing care and remove what remained of his speech.
1988 - Received prestigious Wolf Prize.
1993 - Hawking pursued his work in physics: he co-edited a book on Euclidean quantum gravity with Gary Gibbons and published a collected edition of his own articles on black holes and the Big Bang.
1995 - Divorces Jane Hawking and married Mason in September.
1997 - Six-part television series Stephen Hawking's Universe and a companion book appeared.
2002 - UK-wide vote, the BBC included Hawking in their list of the 100 Greatest Britons.
2005 - Hawking gradually lost the use of his hand, and he began to control his communication device with movements of his cheek muscles, with a rate of about one word per minute.
2009 - Receives Presidential Medal of Freedom, which is America's highest civilian honor.
2015 - Hawking said that not all information is lost when something enters a black hole and there might be a possibility to retrieve information from a black hole according to his theory.
2017 - Received Honorary Doctorate from Imperial College London.
"I have noticed that even people who claim everything is predetermined and that we can do nothing to change it, look before they cross the road."
- Dr.Stephen Hawking
If you are interested in reading more about the 'Master of Universe' - Read it here on his Wikipedia entry.


Love who you are and what you do.
I have a hunger for learning new technologies as a way to operate more efficiently
and I am passionate about revolutionizing how big data is used to drive cost and performance improvements.
I recently finished my Bachelor's degree in Applied Mathematics at SFSU and I am looking to continue my growth as a data engineer with a focus on designing scalable, high-impact software solutions.


Protobuf and WebGL demo
Custom protobuf schema, JS protobuf reader and WebGL renderer.
Example tile
- In this example, 10 channels of data are served per tile, and this slider selects the channel displayed:
Custom protobuf schema, JS protobuf reader and WebGL renderer.


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porcelain horse with lady
What do critics say about the Ecuadorian film, The Porcelain Horse?
I just witnessed the world premiere of The Porcelain Horse from Ecuadorian . Paco is shacked up with Lucia (Leovanna Orlandini), the gorgeous girl he's loved .
http://world-independent-film.yoexpert.com/movie-reviews/what-do-critics-say-about-the-ecuadorian-film-the-32829.html
Lladró porcelain figurines. WOMAN ON HORSE
3D MODE. 01004516. WOMAN ON HORSE. Issue Year: 1970. Sculptor: Fulgencio García. Size: 17¾x14½ ". Price: $1,000.00. Available. RETAILERS LOCATOR .
http://www.lladro.com/figurines/01004516-WOMAN_ON_HORSE/
Porcelain Horses
The porcelain horse featured here is a beautiful hand painted sculpture of the real thing. . Lladro Porcelain Figurine Woman On Horse White Re Deco .
http://www.squidoo.com/porcelain-horses
Things You'll Need
- Certified copies of public records evidence in your case
Instructions
-
-
1
Porcelain Figurine (Y21003-Horse with Girl) - Made-in-China.com
Porcelain Figurine (Y21003-Horse with Girl), Find Details about Home decoration ,figurine from Porcelain Figurine (Y21003-Horse with Girl) - Chaozhou Qunyi .
http://www.made-in-china.com/showroom/qunyialex/product-detailBqyncWaEJGVp/China-Porcelain-Figurine-Y21003-Horse-with-Girl-.html -
2
Miami International Film Festival - 2012 Films
In Javier Andrade's startling debut,two brothers steal a porcelain horse from their . a sensual melodrama of a beautiful woman caught in an unstable situation .
http://www.miamifilmfestival.com/program/2012films.aspxPinkiePorcelain - porcelain-horse-horselain - Tumblr
Nov 1, 2012 . hellbentforleather: theuppitynegras: porcelain-horse-horselain: . famous feminism symbol 'Rosie The Riveter' a lady who is giving up on her .
http://porcelain-horse-horselain.tumblr.com/post/34753159834/hellbentforleather-theuppitynegras -
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Porcelain horse figurine - TheFind
Porcelain horse figurine - Find the largest selection of porcelain horse figurine on sale. Shop by . Cosmos 80051 Fine Porcelain Girl on Rocking Horse... $35 .
http://www.thefind.com/gifts/info-porcelain-horse-figurinePORCELAIN - BORSATO, CYBIS, BOEHM & MEISSEN
Mar 9, 2013 . White horse head with... 150 - 300. 43066. Lot 43066. LOT OF 2 CYBIS PORCELAIN BOY AND GIRL CLOWN HEADS Two porcelain clown .
http://www.liveauctioneers.com/catalog/37697_porcelain-borsato-cybis-boehm-and-meissen/page2 -
4
A hobby horse, a mysterious porcelain figurine, and more: Attic ...
May 26, 2011 . Our antique expert appraises a hobby horse, a porcelain figurine, Disney wall . of the house, the other with a lower profile was for the lady.
http://www.cleveland.com/insideout/index.ssf/2011/05/a_hobby_horse_a_mysterious_por.html
-
1
References
Resources
- Photo Credit Justice image by MVit from could ghosts cause global warming


The purpose of this method is to create a copy to be included in a larger graph such that port identity clashes are avoided.
The purpose of this method is to create a copy to be included in a larger graph such that port identity clashes are avoided. Where a full copy is not possible or desirable, use a CopiedModule. The shape of the resulting module MUST NOT contain the same ports as this module’s shape.
Creates a new Module which is this
Module composed with that
Module,
using the given function f
to compose the materialized value of this
with
the materialized value of that
.
Creates a new Module which is this
Module composed with that
Module,
using the given function f
to compose the materialized value of this
with
the materialized value of that
.
the type of the materialized value of this
the type of the materialized value of that
the type of the materialized value of the returned Module
a Module to be composed with (cannot be itself)
a function which combines the materialized values
a Module that represents the composition of this
and that
Creates a new Module which is this
Module composed with that
Module.
Creates a new Module which is this
Module composed with that
Module.
a Module to be composed with (cannot be itself)
a Module that represents the composition of this
and that
Creates a new Module which is this
Module composed with that
Module.
Creates a new Module which is this
Module composed with that
Module.
The difference to compose(that) is that this version completely ignores the materialized value
computation of that
while the normal version executes the computation and discards its result.
This means that this version must not be used for user-provided that
modules because users may
transform materialized values only to achieve some side-effect; it can only be
used where we know that there is no meaningful computation to be done (like for
MaterializedValueSource).
a Module to be composed with (cannot be itself)
a Module that represents the composition of this
and that
Fuses this Module to that
Module by wiring together from
and to
,
transforming the materialized values of this
and that
using the
provided function f
Fuses this Module to that
Module by wiring together from
and to
,
transforming the materialized values of this
and that
using the
provided function f
a Module to fuse with
the data source to wire
the data sink to wire
the function to apply to the materialized values
a Module representing the fusion of this
and that
Fuses this Module to that
Module by wiring together from
and to
,
retaining the materialized value of this
in the result
Fuses this Module to that
Module by wiring together from
and to
,
retaining the materialized value of this
in the result
a Module to fuse with
the data source to wire
the data sink to wire
a Module representing the fusion of this
and that
Verify that the given Shape has the same ports and return a new module with that shape.
Verify that the given Shape has the same ports and return a new module with that shape. Concrete implementations may throw UnsupportedOperationException where applicable.
Please note that this method MUST NOT be implemented using a CopiedModule since the purpose of replaceShape can also be to rearrange the ports (as in BidiFlow.reversed) and that purpose would be defeated.
Creates a new Module based on the current Module but with the given OutPort wired to the given InPort.
Creates a new Module based on the current Module but with the given OutPort wired to the given InPort.
the OutPort to wire
the InPort to wire
a new Module with the ports wired


WATCH | 'This man can start a mini war': raid exposes arms cache, 'dagga lab'
by Iavan PijoosGauteng police swooped on a home in Wierdapark near Pretoria and discovered an arms cache and "dagga laboratory" inside.
Home affairs minister Aaron Motsoaledi, standing in for minister of police Bheki Cele, national police commissioner Gen Khehla Sitole and Gauteng MEC for community safety MEC Faith Mazibuko visited the house on Wednesday.
Motsoaledi said the owner of the house, a 50-year-old man, had been arrested after the raid on Tuesday.
Motsoaledi said officers from the Pretoria and Soshanguve K9 unit pounced on the property after getting a tip-off from someone who allegedly used to buy drugs there.
He said upon searching the premises, officers found a dagga laboratory operating “under optimal conditions of production”.
“They widened their search and found hidden rooms in the house. The rooms contained several guns.”
The firearms included AK47s, R1 rifles, hand guns, rocket launchers and ammunition boxes.
Motsoaledi said the man claimed to be an arms dealer and collector "but investigations had revealed otherwise".
“Some firearms that should have been deactivated as collectors' items were in fact not deactivated.
“It is worrying us, because this man can start a mini war if he wishes. Why do you keep launchers that can shoot helicopters? That is for war.”
“If you are a collector, the arms must be deactivated, but officers found active arms here.”
Motsoaledi said the man's dealership licence had been placed on suspension and his firearm licences would be revoked should he be found guilty.
The house, which appeared to be under construction and was surrounded by an electric fence, is in a quiet suburb. The garden was full of construction materials including wood pallets, scaffolding, plastic pipes and tools.
In the front yard were three trailers and a small boat. At the back of the house were shipping containers full of construction equipment and tools.
Behind the carport was a Russian Lada SUV.
Chemicals and blue drums were found in the living room. The house was packed with boxes, fans, tables and other furnishings, making it difficult to move around.
In one of the rooms was a large dagga crop and several firearms.
Motsoaledi said the amount of dagga was enough to “supply a whole village”.
In a different room were various military items, including uniforms. Motsoaledi said this would form part of the police investigation.
“It is things which soldiers wear when they are in battle, but they still need to be analysed.”
Sitole commended the junior police officers who swooped on the house.
“They have showed a very high level of determination. They could have easily been bribed in this particular operation and they did not accept that.”


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Submitted by {{author.contributor}} on {{author.submittedDate|date}}({{author.submittedDate|dateCount}} day(s) ago)
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{% extends "base.html" %}
{% load i18n %}
{% load crispy_forms_tags %}
{% block content %}
lexmapr-django is still in the development phase, and is currently catered towards food and environmental samples.
{% crispy form %}
| {{ val }} | {% endfor %}


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As many other professional sites, choies.com invest on the internet advertisement. Our advertise partners include bing Ads (Yahoo Ads). In order to maximize online advertising ROI and to find target clients, choies.com applied some tracking codes generated by those search engines to record user IPs and page viewing flows.
Business Contact Data
We collect all the business contact data sent through emails or web forms on choies.com from visitors. The visitor identification and contact related data entered will be kept strictly for choies.com’s internal use. Choies.com will ensure the safety and proper usage of those data.
Information Usage
We will only use your personally identifiable information as described below, unless you have specifically consented to another type of use, either at the time the personally identifiable information is collected from you or through some other form of consent from you:
1.We will use personally identifiable information to complete any orders you have placed.
2.We will use personally identifiable information to provide you with the specific services that you have requested, such as to reach a retailer.
3.We will use your personally identifiable information to respond to questions that you send to us.
4.We will use your personally identifiable information to send you emails from time to time, such as newsletters and notices about our promotions.
5.We may disclose personally identifiable information as required by law or legal process.
6.We may disclose personally identifiable information to investigate suspected fraud, harassment or other violations of any law, rule or regulation, or the terms or policies for the Web site.
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When you register, you will be given the option to opt-out of subscribing to our regular update service. We will send you e mail alerts for new products, features, enhancements, special offers, contests, events of interest, and one-off marketing promotions.
At all times, we will offer you the opportunity to unsubscribe out of any service or update to which you have subscribed, if you change your mind. Any e-mail we send you will contain an easy automated unsubscribe link so that you can opt-out of that subscription. Simply follow the indications in the e-mail.
[CompanyName] Choies Co., Ltd
[Address] Third Floor, 207 Regent Street, London, W1B 3HH,United Kingdom
[Email]<EMAIL_ADDRESS>[Contact Number] 44-2032893088


Mother Nornil:
Now, go forth with the power of chaos, the unconquerable free will, centered in your body.
Your adventures have only begun...


Purpose — Why Do We Create a Tech Radar?The E1 Tech Radar is a tool to inspire and support teams to pick the best technologies for new projects; it provides a platform to share knowledge and experience in technologies, to reflect on technology decisions and continuously evolve our technology landscape. Based on the quarterly tech radar produced by ThoughtWorks, our Tech Radar sets out the changes in technologies that are interesting in software development; changes that we think our engineering teams should pay attention to and consider using in their projects. Scope — What Is the Tech Radar?The E1 Tech Radar is a list of technologies, frameworks, tools and methods, complemented by an assessment result, called ring assignment; we use 4 rings with a slightly adapted semantics to fit our purpose:
The Tech Radar is currently maintained by the E1 Solution Architect. It is the intention to have the E1 Technical Leadership group take collective ownership of the Tech Radar. It is also intented that there be a quarterly E1 Tech-Radar release published here. Going forward, the ring assignments will result from the average vote of its members — of course, based on preliminary discussions with the target to achieve high consensus. |
Internals — How Does It Work?The Solution Architect [internal link] maintains the Tech Radar and Compendium, provides a forum for conversations about technologies, shares knowledge on technologies and support the engineering teams with expert knowledge and peer review feedback on their technology selections. Guild members meet monthly to discuss the updates of the Tech Radar assessments [internal link], and upcoming and ongoing issues around the technologies and architectural decisions. Together with the Tech Radar we also maintain the Tech Radar Compendium [internal link] — a collection of summaries of listed technologies, i.e. few sentence descriptions of what, why and risks of the technology supplemented with information which teams used it for what kind of problem. It continuously grows with any Tech Radar changes and hopefully evolves fast as a valuable place for us to share information and get teams connected. The E1 Tech Radar Principles [internal link], of course, will not work without E1 engineering team contributions; so our Technology Rules of Play include obligations for the engineering teams: teams must use the Tech Radar as one input source for their technology decisions. Teams are encouraged to challenge the Tech Radar and provide feedback to the Technology Leadership group. Depending on the current assessment status of the technology candidate, teams should align with their delivery leads, inform or ask the Technology Leadership group for peer review feedback on the purpose and risks and share their knowledge and experience with other teams and the Technology Leadership group. |


End to end solution for sourcing and staffing system with indicidual credibility scorer
Why only employees can give feedback to the employer? With this solution employers can also provide feedback, rating and recommend individuals based on their work relation.


July 7, 2017: Completed my first "project" today. Using JavaScript, I created a Bible verse generator that randomly chooses a verse from an array and displays it on the page each time the code runs (i.e. with each page refresh). While I'm pretty happy functionality-wise (I still want to add a few things in the future), but it doesn't score very high in the responsive design department.


Class MultiGeoPointProperty
A IShowProperty implementation that displays a list of GeoPoints. The communication with the object that owns that list is performed via a IIndexedGeoPoint interface, which must be provided in the constructor. This show property lets the user add and remove GeoPoints to or from the list or modify existing GeoPoints in the list.
Inherited Members
Namespace: CADability.UserInterface
Assembly: CADability.dll
Syntax
public class MultiGeoPointProperty : PropertyEntryImpl, IPropertyEntry, IShowProperty
Constructors
| Improve this Doc View SourceMultiGeoPointProperty(IIndexedGeoPoint, String, IFrame)
Creates a MultiGeoPointProperty. The parameter "controlledObject" provides the owner of the list.
Declaration
public MultiGeoPointProperty(IIndexedGeoPoint controlledObject, string resourceId, IFrame frame)
Parameters
| Type | Name | Description |
|---|---|---|
| IIndexedGeoPoint | controlledObject | owner of the list |
| System.String | resourceId | the resource id to specify a string from the StringTable. ResourceId+".Label": the Label left of the edit box. ResourceId+".ShortInfo": a short tooltip text ResourceId+"DetailedInfo": a longer tooltip text. |
| IFrame | frame |
Fields
| Improve this Doc View SourceGetInsertionPointEvent
When a point is about to be inserted this property needs some initial value. The default initial value is the same point as the first/last point, when inserted before the first or after the last point, and the middle point of the intervall where the point is to be inserted. If you wisch another behaviour add a handler to this event and return the appropriate point.
Declaration
public MultiGeoPointProperty.GetInsertionPointDelegate GetInsertionPointEvent
Field Value
| Type | Description |
|---|---|
| MultiGeoPointProperty.GetInsertionPointDelegate |
Properties
| Improve this Doc View SourceDisplayZComponent
Declaration
public bool DisplayZComponent { get; set; }
Property Value
| Type | Description |
|---|---|
| System.Boolean |
Flags
Declaration
public override PropertyEntryType Flags { get; }
Property Value
| Type | Description |
|---|---|
| PropertyEntryType |
Overrides
| Improve this Doc View SourcePrependContextMenue
Declaration
public MenuWithHandler[] PrependContextMenue { get; set; }
Property Value
| Type | Description |
|---|---|
| MenuWithHandler[] |
SubItems
Declaration
public override IPropertyEntry[] SubItems { get; }
Property Value
| Type | Description |
|---|---|
| IPropertyEntry[] |
Overrides
Methods
| Improve this Doc View SourceAdded(IPropertyPage)
Declaration
public override void Added(IPropertyPage propertyTreeView)
Parameters
| Type | Name | Description |
|---|---|---|
| IPropertyPage | propertyTreeView |
Overrides
| Improve this Doc View SourceAppend(GeoPoint)
Appends a point to the list of points
Declaration
public void Append(GeoPoint initialValue)
Parameters
| Type | Name | Description |
|---|---|---|
| GeoPoint | initialValue | initial value of the new point |
Refresh()
Declaration
public override void Refresh()
Overrides
| Improve this Doc View SourceRefresh(Int32)
Refreshes the display of the point with the given index.
Declaration
public void Refresh(int Index)
Parameters
| Type | Name | Description |
|---|---|---|
| System.Int32 | Index | index of point to refresh |
SetFocusToIndex(Int32)
Declaration
public void SetFocusToIndex(int index)
Parameters
| Type | Name | Description |
|---|---|---|
| System.Int32 | index |
ShowOpen(Boolean)
Opens the subentries in the treeview.
Declaration
public void ShowOpen(bool open)
Parameters
| Type | Name | Description |
|---|---|---|
| System.Boolean | open | true: open, false: close |
Events
| Improve this Doc View SourceGeoPointSelectionChangedEvent
Provide a method here if you need to be notified about when the selection of the points in the subtree changed
Declaration
public event GeoPointProperty.SelectionChangedDelegate GeoPointSelectionChangedEvent
Event Type
| Type | Description |
|---|---|
| GeoPointProperty.SelectionChangedDelegate |
ModifyWithMouseEvent
Provide a method here if you need to notified about modification of any point in this list with the mouse
Declaration
public event MultiGeoPointProperty.ModifyWithMouseIndexDelegate ModifyWithMouseEvent
Event Type
| Type | Description |
|---|---|
| MultiGeoPointProperty.ModifyWithMouseIndexDelegate |


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Story
About Data Set
Question
What are the disparities within early childhood, education, and income, across race and sex in United States?
Combine
Type of Household
Country Centers
Population
Type of Home
Group


Victoria power bills to increase in 2020
by Noel TowellMore than 120,000 Victorian households can expect their electricity bills to increase nearly 8 per cent - or about $110 - next year.
The state's energy regulator signed off on Monday to an increase in the "Victorian Default Offer", which is supposed to act as a price-cap for electricity customers who do not shop around for a better deal.
The picture is even more grim for small businesses on the default offer, which will see average bills soar from $5900 to $6400 next year.
From January, the average domestic bill will jump from around $1410 to about $1520, an increase nearly four times the rate of inflation.
Despite the increases, the Essential Services Commission insists the default offer, which was introduced in July, is saving customers money.
READ MORE: BALLARAT'S COMPLAINTS ABOUT ENERGY BILLS HIGHER THAN STATE AVERAGE
"We estimate that the annual bill for a typical domestic customer on the VDO in 2020 could be around $200 to $330 per year lower than prior to the introduction of the VDO," the commission wrote in its decision.
"The annual bill for a typical small business customer could be around $1000 to $1600 lower than prior to the introduction of the VDO."
The commission said the VDO is often not the best deal and encouraged customers to shop around, or at least read their electricity bill, because retailers are now required by law to tell their customers if there is a better offer out there.
"The VDO does not necessarily reflect the best offer available to customers. Customers may be able to access a market offer with better prices than the VDO," the commission wrote.
"We note that under recent reforms implemented by the commission, a retailer must regularly tell customers whether they are on the retailer's best energy plan, and how much the customer could save by switching."


Jeremiah 32:34
But they set their abominations in the house, which is called by my name, to defile it.


| 1 |
Open App |
Enter incorrect
price per km in a fillup (I entered 102.9 rather than 1.029) |
| 2 |
Tap on "Price per Gallons" Edit Text |
| 3 |
Type "102.9" |
| 4 |
Tap on "Gallons" Edit Text |
| 5 |
Type "12" |
| 6 |
Tap on the "Odometer" Edit Text |
| 7 |
Type "1000" |
| 8 |
Tap the "Save Fillup" button |
| 9 |
Tap on the "Fillup" button |
|
| 10 |
Tap on "Price per Gallons" Edit Text |
|
| 11 |
Type "1.029" |
|
| 12 |
Tap on "Gallons" Edit Text |
|
| 13 |
Type "12" |
|
| 14 |
Tap on the "Odometer" Edit Text |
|
| 15 |
Type "1000" |
|
| 16 |
Tap the "Save Fillup" button |
|
| 17 |
Tap on the "Statistics" button |
switch to statistics view and see calculations |
| 18 |
Tap the "History" button |
Find
the incorrect entry in history and fix the price |
| 19 |
Tap the bottom Fillup item |
| 20 |
Tap on "Price per Gallons" Edit Text |
| 21 |
Type "1.029" |
| 22 |
Tap on the "Save Changes" button |
| 23 |
Tap on the "Statistics" button |
switch to statistics view and see calculations |
|
|
|


Protocols
The following protocols are available globally.
-
Conforming types get
See morecreateTLSParameters:allowInsecure:queue
convenience method.Declaration
Swift
public protocol ICanCreateTLSParams
-
Conforming types where Self: MTSClient, inherit the
See morestateDidChange:to
convenience method.Declaration
Swift
public protocol ICanStateChange : AnyObject, ICanLog, MTSClientDelegate
-
Conforming types can conduct MTS transactions over network connections.
See moreDeclaration
Swift
public protocol MTSClient : ICanCreateTLSParams, ICanStateChange
-
Conformers to this protocol can serve as a delegate for MTSClient conformers.
See moreDeclaration
Swift
public protocol MTSClientDelegate
-
Types conforming to this protocol have convert:from: method signature.
See moreDeclaration
Swift
public protocol ICanConvertFromMtsMessage
-
Conforming types are messages that are able to request MTS transactions over network connections.
See moreDeclaration
Swift
public protocol MTSRequest : ICanConvertFromMtsMessage, ICanLog
-
Types conforming to this protocol can be returned by an MTSRequest’s
convert:from:
method.Declaration
Swift
public protocol MTSRequestType
-
Conforming types can act as an MTS server that an MTS client can attempt to connect with using MTS transactions.
See moreDeclaration
Swift
public protocol MTSServer : ICanCreateTLSParams


Click the 'Push' button to add the value to the array.
Click the 'Pop' button to remove the first element of the array.


HEAD
body
--info
variant--info
variant, with body
--success
variantYour immunisation appointment for August 7, 2017 has been confirmed.
--success
variant, with body
Your immunisation appointment for August 7, 2017 has been confirmed.
--warning
variantThe ATO is warning the public to be aware of a phone scam that is again circulating where fraudsters are intimidating people into paying a fake tax debt over the phone.
We will never contact you in person over the phone to make a payment.
--warning
variant, with body
The ATO is warning the public to be aware of a phone scam that is again circulating where fraudsters are intimidating people into paying a fake tax debt over the phone.
We will never contact you in person over the phone to make a payment.
--error
variant--error
variant, with body


Conor McKoy is a Full Stack Developer based out of New Rochelle, NY. He enjoys coding and problem solving, looking at
any broken or nonworking code as if it was a logic puzzle to be solved. His favorite language to work in is jQuery, preferring figuring
out back end problems.
In his spare time, Conor enjoys activities like Rock Climbing, Hiking, Dungeons & Dragons, Writing Fiction, and Video Games.
HTML | CSS | JavaScript | jQuery | ES6 | Node.js | MySQL | MongoDB | React | Express
An online escape game where the user must solve puzzles and find the way out of the vampire's castle. Designed by me and 4 other Developers,
it's uses React and Context Hooks to change between puzzles. I focused on writing the code for several puzzles and the Context Hook for the main puzzles.
Try it out
View the Repo
A simple Pokemon battling game designed by me and 3 other Developers. Based on the Poke API, users can choose 3 Pokemon
and do battle with a randomly generated computer team. I worked mainly on the battle functions working in the background.
Try it out
View the Repo
A Node.js app that allows Employers to keep track of their employee infrastructure. It utilizes MySQL in
the backend to save the user's data.
View the Repo
Through the use of JavaScript, I created a password generator that allows users to customize their passwords.
Users can decide what kinds of characters are included and the length (minimum of 8 characters) of a new password for use on future accounts.
Check it out!
View the Repo
Using jQuery, I created a simple weather app that allows users to search cities and find their current weather.
Previously searched cities are saved and can be veiwed upon return to the page.
Check it out!
View the Repo


Login Here
Username
:
Password
:
If you haven't account, you can register now as
customer
or
shop
×
User
Shop
Name
Surname
Gender
Male
Female
Birth date
Email
Phone n.
Password
Repeat Pas.
Register
Shop name
Country
Region
City
Email
Phone n.
Password
Reo. pass
Register
Sales-IF
Services
Products
One Product
Admin
through Shop
through Site
search
Join in
Sign in
Sign up
Zarin_Andrii
Profile
Cart
Whishlist
Log Out


The core-hello component supports different languages like English, Spanish, French, Mandarin, and etc. The way you would use this is by adding the lang attribute and assigning its shorthand language names like "hi" for hindi. Note that this only translates only the "Hello World" portion.
English
Chinese
Hindi
The core-hello web component can make the text have a rainbow effect. This is done by including "rainbow" as part of the attributes in the core-hello tag.
without rainbow attribute
With rainbow attribute


Preserving Semantic Relations for Zero-Shot Learning Yashas Annadani, Soma Biswas IEEE Conference on Computer Vision and Pattern Recongition (CVPR), 2018.[arXiv]


Many different types of CPU architectures exist and are used for various applications.
A CPU can have multiple cores, which are simply CPUs which communicate with each other. A developer can make use of extra cores in order to run some intensive operations using multiple cores at once, thus potentially improving performance. However, writing apps to take advantage of multiple cores is very complex, and may even result in worse performance. If software is not optimised to take advantage of a multi-core CPU, then there is no speed advantage over a single-core CPU.
A CPU's clock is what syncronises all operations in a CPU. The higher the clock-speed of a CPU, the more operations the CPU will carry out per second. For example, a 3GHz CPU will perform 3 billion cycles per second. However, the higher the clock-speed of a CPU, the more heat is generated. It is therefore inadvisable to overclock a CPU because this may shorten its life, and may result in corrupted data because the normal speed at which data is handled may not be able to keep up with the speed of the CPU.
The size and amount of Cache available to the CPU will have a great impact on the performance of a CPU. The more fast cache which is available, the higher the chance that a piece of data or instruction will be found in the cache (cache hit).
Processor pipelining can help to improve the performance of a CPU because it can help to reduce to time a CPU sits idle, for example, waiting for the next instruction to arrive. Pipelining means that more things can be done at once, like fetching the next instruction while the current one is being executed.
The type of CPU used can affect the performance. For example, a RISC CPU for complex apps may be slower than a CISC CPU.


GRADIENT
Saturday 14 December 2019
Log in / Sign up / Hello [Susan]
Susan's To Do Lists
WORK
[6]
+
NOW
Bootstrap homework
NEXT
Review James' notes
Do rest of JavaScript on Codeacademy
JavaScript Codewars
SOON
Back end programming
COMPLETED
CSS
HTML
FAMILY
[11]
+
NOW
Wrap Christmas Presents
Post Christmas cards
NEXT
Decorate Felix bedroom
Move furniture in
SOON
Book to visit Manchester family
Pack for Ramsgate
Felix nappies
Plan food for Xmas
Tidy house
COMPLETED
Rub down windowsills
Fill holes in wall
PERSONAL
[10]
+
NOW
Reply to Nikki
NEXT
Contact everyone for birthday drinks
Get bike serviced
SOON
Swimming each week
Charity shop bag
[task text]
[task text]
[task text]
COMPLETED
Book Brenda for 17th
Choose pub for drinks
ERRANDS
[12]
+
NOW
Christmas Tree
Food for Dad
Dad's newspaper renewal
Jumper for Andrew
Milk
Coins for Mum and Tone
NEXT
Take back Sloth
Collect Engel order
SOON
Get van serviced
Duck food
COMPLETED
Christmas presents bought
Christmas cards collected


Deep Bhuller
Senior at SFSU, in CSC 648 - Software Engineering, Team 07
GitHub Master
Front-End & Back-End
Skills
JavaScript, Node.js, HTML & CSS, AWS, Express.js


{% extends "dataset/base.html" %} {% block content %}
If you don't have an account yet, you can create one.


{% extends "base.html" %} {% block content %}
{{ c.description }}
No competencies added to the system yet!


|
|
def | __init__ |
| |
|
def | distinct |
| |
|
def | set_distinct |
| |
|
def | clear_distinct |
| |
|
def | has_distinct |
| |
|
def | kind |
| |
|
def | set_kind |
| |
|
def | clear_kind |
| |
|
def | has_kind |
| |
|
def | ancestor |
| |
|
def | mutable_ancestor |
| |
|
def | clear_ancestor |
| |
|
def | has_ancestor |
| |
|
def | MergeFrom |
| |
|
def | Equals |
| |
|
def | IsInitialized |
| |
|
def | ByteSize |
| |
|
def | ByteSizePartial |
| |
|
def | Clear |
| |
|
def | OutputUnchecked |
| |
|
def | OutputPartial |
| |
|
def | TryMerge |
| |
|
def | __str__ |
| |
|
|
| lazy_init_lock_ |
| |
|
| has_distinct_ |
| |
|
| distinct_ |
| |
|
| has_kind_ |
| |
|
| kind_ |
| |
|
| has_ancestor_ |
| |
|
|
int | has_distinct_ = 0 |
| |
|
int | distinct_ = 0 |
| |
|
int | has_kind_ = 0 |
| |
|
string | kind_ = "" |
| |
|
int | has_ancestor_ = 0 |
| |
|
| ancestor_ = None |
| |
The documentation for this class was generated from the following file:
- code/googleappengine-read-only/python/google/appengine/datastore/datastore_v3_pb.py


“He was of medium height, thin and sallow, with gray whiskers, thick gray hair, bushy eyebrows, and small, pointed and inquiring features which gave him rather the aspect of a prying bird. His eyes were little and sparkling. His mouth, strangely enough, was ecclesiastical. He nearly always wore very light-coloured clothes. Even in winter he was often to be seen clad in yellow-gray tweeds, a yellow silk necktie, and a fawn-colored Homburg hat. And no human being had ever encountered him in a pair of boots unprotected by spats.” — Robert Smythe Hichens, The Dweller On The Threshold


--- layout: page title: About header-img: "img/about-bg.png" ---
Anthony is a web developer who has a passion for problem-solving and creating things. His favorite languages include JavaScript, Python, and Ruby.


= $sales_amount ?>
Last Month: = $sales_lm_amount ?>
= $sales_count ?>
Last Month: = $sales_lm_count ?>
= $products_count ?>
= $products_out_of_stock ?>
= e($error) ?>


Current and Upcoming Events
These are the events currently planned for the semester. The discussions are informal and loosely follow the topic or article specified. In general topics or articles are suggested to by different people each week. Come find us on Fridays at Soma if you are interested or just curious. If you would like to suggest a topic for discussion or a film or would be interested in helping with an event please email SOCS. If you are interested in a list of the most influential works in Cognitive Science take a look at the Millenium Project.
This page was lasted edited on February 19, 2000.
Please address questions and comments to: iusocs@indiana.edu.