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| Packages that use ModeMatrix | |
|---|---|
| de.iabg.mode | |
| de.iabg.mode.io |
| Uses of ModeMatrix in de.iabg.mode |
|---|
| Fields in de.iabg.mode declared as ModeMatrix | |
|---|---|
protected ModeMatrix |
ModeTableModel.modes_
The ModeMatrix that this TableModel represents |
| Methods in de.iabg.mode that return ModeMatrix | |
|---|---|
ModeMatrix |
DefaultModeModel.getModes()
|
ModeMatrix |
JModePanel.getModes()
Returns the currently stored modes. |
ModeMatrix |
ModeModel.getModes()
Returns the currently stored modes. |
ModeMatrix |
ModeTableModel.getModes()
Returns the currently stored ModeMatrix . |
| Methods in de.iabg.mode with parameters of type ModeMatrix | |
|---|---|
ModeCorrelationMatrix |
ModeMatrix.computeDotProduct(ModeMatrix modes)
Computes a matrix of the dot products of each mode in this ModeMatrix and the given ModeMatrix . |
ModeCorrelationMatrix |
ModeMatrix.computeGeneralizedMass(MassMatrix masses,
ModeMatrix modes)
Computes a matrix of the generalized mass of each mode in this ModeMatrix and the given ModeMatrix . |
ModeCorrelationMatrix |
ModeMatrix.computeModalAssuranceCriterion(ModeMatrix modes)
Computes a matrix of the Modal Assurance Criterion of each mode in this ModeMatrix and the given ModeMatrix . |
ModeCorrelationMatrix |
ModeMatrix.computeOrthogonalityCheck(MassMatrix masses,
ModeMatrix modes)
Computes a matrix of the normalized Orthogonality Check of each mode in this ModeMatrix and the given ModeMatrix . |
ModeCorrelationMatrix |
ModeMatrix.getReducedDotProduct(ModeMatrix modes,
KeyList firstModeKeys,
KeyList firstNodeKeys,
KeyList lastModeKeys,
KeyList lastNodeKeys)
Makes a copy of this ModeMatrix and the given one, sorts each by
the corresponding given mode names and node names, and computes the
resulting ModeCorrelationMatrix from
computeDotProduct(de.iabg.mode.ModeMatrix) . |
ModeCorrelationMatrix |
ModeMatrix.getReducedGeneralizedMass(MassMatrix masses,
ModeMatrix modes,
KeyList firstModeKeys,
KeyList firstNodeKeys,
KeyList lastModeKeys,
KeyList lastNodeKeys)
Makes a copy of this ModeMatrix and the given one, sorts each by
the corresponding given mode names and node names, and computes the
resulting ModeCorrelationMatrix from
computeGeneralizedMass(de.iabg.mode.MassMatrix,
de.iabg.mode.ModeMatrix) . |
ModeCorrelationMatrix |
ModeMatrix.getReducedModalAssuranceCriterion(ModeMatrix modes,
KeyList firstModeKeys,
KeyList firstNodeKeys,
KeyList lastModeKeys,
KeyList lastNodeKeys)
Makes a copy of this ModeMatrix and the given one, sorts each by
the corresponding given mode names and node names, and computes the
resulting ModeCorrelationMatrix from
computeModalAssuranceCriterion(de.iabg.mode.ModeMatrix) . |
ModeCorrelationMatrix |
ModeMatrix.getReducedOrthogonalityCheck(MassMatrix masses,
ModeMatrix modes,
KeyList firstModeKeys,
KeyList firstNodeKeys,
KeyList lastModeKeys,
KeyList lastNodeKeys)
Makes a copy of this ModeMatrix and the given one, sorts each by
the corresponding given mode names and node names, and computes the
resulting ModeCorrelationMatrix from
computeOrthogonalityCheck(de.iabg.mode.MassMatrix,
de.iabg.mode.ModeMatrix) . |
void |
ModeReader.importModes(ModeMatrix modes)
Clears the given modes and replaces them with the data parsed from the internally stored file. |
void |
ModeConnectionWriter.setFirstModes(ModeMatrix firstModes)
Internally saves the First Modes to be written with any exported
data. |
void |
ModeConnectionWriter.setLastModes(ModeMatrix lastModes)
Internally saves the Last Modes to be written with any exported
data. |
| Constructors in de.iabg.mode with parameters of type ModeMatrix | |
|---|---|
ModeMatrix(ModeMatrix modes)
Constructs a copy of the given ModeMatrix . |
| Uses of ModeMatrix in de.iabg.mode.io |
|---|
| Fields in de.iabg.mode.io declared as ModeMatrix | |
|---|---|
protected ModeMatrix |
ModalAssuranceCriterionUpdateWriter.firstModes_
Storage for the First Mode matrix |
protected ModeMatrix |
OrthogonalityCheckUpdateWriter.firstModes_
Storage for the First Mode matrix |
protected ModeMatrix |
ModalAssuranceCriterionUpdateWriter.lastModes_
Storage for the Last Mode matrix |
protected ModeMatrix |
OrthogonalityCheckUpdateWriter.lastModes_
Storage for the Last Mode matrix |
protected ModeMatrix |
NastranPunchReader.modes_
Storage for the modes |
protected ModeMatrix |
UniversalModeReader.modes_
Storage for the modes |
| Methods in de.iabg.mode.io with parameters of type ModeMatrix | |
|---|---|
void |
NastranPunchReader.importModes(ModeMatrix modes)
|
void |
UniversalModeReader.importModes(ModeMatrix modes)
|
void |
ModalAssuranceCriterionUpdateWriter.setFirstModes(ModeMatrix firstModes)
|
void |
OrthogonalityCheckUpdateWriter.setFirstModes(ModeMatrix firstModes)
|
void |
ModalAssuranceCriterionUpdateWriter.setLastModes(ModeMatrix lastModes)
|
void |
OrthogonalityCheckUpdateWriter.setLastModes(ModeMatrix lastModes)
|
|
||||||||||
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| I l@ve RuBoard |
13.2 The PyMailCgi Web SiteNear the end of Chapter 11, we built a program called PyMailGui that implemented a complete Python+Tk email client GUI (if you didn't read that section, you may want to take a quick look at it now). Here, we're going to do something of the same, but on the Web: the system presented in this section, PyMailCgi, is a collection of CGI scripts that implement a simple web-based interface for sending and reading email in any browser. Our goal in studying this system is partly to learn a few more CGI tricks, partly to learn a bit about designing larger Python systems in general, and partly to underscore the trade-offs between systems implemented for the Web (PyMailCgi) and systems written to run locally (PyMailGui). This chapter hints at some of these trade-offs along the way, and returns to explore them in more depth after the presentation of this system. 13.2.1 Implementation OverviewAt the top level, PyMailCgi allows users to view incoming email with the POP interface and to send new mail by SMTP. Users also have the option of replying to, forwarding, or deleting an incoming email while viewing it. As implemented, anyone can send email from the PyMailCgi site, but to view your email, you generally have to install PyMailCgi at your own site with your own mail server information (due to security concerns described later). Viewing and sending email sounds simple enough, but the interaction involved involves a number of distinct web pages, each requiring a CGI script or HTML file of its own. In fact, PyMailCgi is a fairly linear system -- in the most complex user interaction scenario, there are six states (and hence six web pages) from start to finish. Because each page is usually generated by a distinct file in the CGI world, that also implies six source files. To help keep track of how all of PyMailCgi's files fit into the overall system, I wrote the file in Example 13-1 before starting any real programming. It informally sketches the user's flow through the system and the files invoked along the way. You can certainly use more formal notations to describe the flow of control and information through states such as web pages (e.g., dataflow diagrams), but for this simple example this file gets the job done. Example 13-1. PP2E\Internet\Cgi-Web\PyMailCgi\pageflow.txtfile or script creates -------------- ------- [pymailcgi.html] Root window => [onRootViewLink.cgi] Pop password window => [onViewPswdSubmit.cgi] List window (loads all pop mail) => [onViewListLink.cgi] View Window + pick=del|reply|fwd (fetch) => [onViewSubmit.cgi] Edit window, or delete+confirm (del) => [onSendSubmit.cgi] Confirmation (sends smtp mail) => back to root => [onRootSendLink.cgi] Edit Window => [onSendSubmit.cgi] Confirmation (sends smtp mail) => back to root This file simply lists all the source files in the system, using => and indentation to denote the scripts they trigger. For instance, links on the pymailcgi.html root page invoke onRootViewLink.cgi and onRootSendLink.cgi, both executable scripts. The script onRootViewLink.cgi generates a password page, whose Submit button in turn triggers onViewPswdSubmit.cgi, and so on. Notice that both the view and send actions can wind up triggering onSendSubmit.cgi to send a new mail; view operations get there after the user chooses to reply to or forward an incoming mail. In a system like this, CGI scripts make little sense in isolation, so it's a good idea to keep the overall page flow in mind; refer to this file if you get lost. For additional context, Figure 13-1 shows the overall contents of this site, viewed on Windows with the PyEdit "Open" function. Figure 13-1. PyMailCgi contentsThe temp directory was used only during development. To install this site, all the files you see here are uploaded to a PyMailCgi subdirectory of my public_html web directory. Besides the page-flow HTML and CGI script files invoked by user interaction, PyMailCgi uses a handful of utility modules as well:
PyMailCgi also reuses parts of the pymail.py and mailconfig.py modules we wrote in Chapter 11; on my web server, these are installed in a special directory that is not necessarily the same as their location in the examples distribution (they show up in another server directory, not shown in Figure 13-1). As usual, PyMailCgi also uses a variety of standard Python library modules: smtplib, poplib, rfc822, cgi, urllib, time, rotor, and the like.
13.2.2 Presentation OverviewPyMailCgi is a challenge to present in a book like this, because most of the "action" is encapsulated in shared utility modules (especially one called commonhtml.py ); the CGI scripts that implement user interaction don't do much by themselves. This architecture was chosen deliberately, to make scripts simple and implement a common look-and-feel. But it means you must jump between files to understand how the system works. To make this example easier to digest, we're going to explore its code in two chunks: page scripts first, and then the utility modules. First, we'll study screen shots of the major web pages served up by the system and the HTML files and top-level Python CGI scripts used to generate them. We begin by following a send mail interaction, and then trace how existing email is processed. Most implementation details will be presented in these sections, but be sure to flip ahead to the utility modules listed later to understand what the scripts are really doing. I should also point out that this is a fairly complex system, and I won't describe it in exhaustive detail; be sure to read the source code along the way for details not made explicit in the narrative. All of the system's source code appears in this section (and also at http://examples.oreilly.com/python2), and we will study the key concepts in this system here. But as usual with case studies in this book, I assume that you can read Python code by now and will consult the example's source code for more details. Because Python's syntax is so close to executable pseudocode, systems are sometimes better described in Python than in English. |
| I l@ve RuBoard |


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MISSION: IMPOSSIBLE A film review by Christopher Null Copyright 1996 Christopher Null
You heard it here first: When big "Mission: Impossible" fans leave the theater after seeing the film version of their favorite TV show, the most common opinion will be, "I'm pissed off."
Telling you why would spoil what little plot MISSION: IMPOSSIBLE actually has, so I won't. Instead, let me try to shed a little light on what is a messy, uneven production that had so much promise but delivers so little.
Tom Cruise, surprisingly, is not to blame. The only A-list name in the production, Cruise stars as Ethan Hunt, the disguise expert in the IMF gang. Something of a rebel in the bunch, Hunt finds himself embroiled in a mission-gone-wrong that should have been a cakewalk. With the whereabouts of his crew unknown (including Emmanuelle Beart, Kristin Scott-Thomas, an uncredited Emilio Estevez, and Jon Voight as boss-man Jim Phelps), Hunt finds himself the target of a "molehunt" from IMF bigwig Kittridge (Henry Czerny). Hunt then tries to play cat and mouse to expose the real mole and the bad guys and save his skin in the process.
But not before blowing up a lot of stuff!
And getting to the blowing up of stuff is director Brian De Palma's primary goal here. In the process, he lets the story fall into new realms of ridiculousness and "What the hell is going on?" Syndrome. Respected writers David Koepp (JURASSIC PARK), Robert Towne (CHINATOWN), and Steven Zaillian (SCHINDLER'S LIST) appear to be running on fumes.  (And there are many fewer of these than the trailer would have you believe.)
MISSION: IMPOSSIBLE's success (or lack thereof) hinges on two big scenes: the big break-in scene (in the trailer, where Cruise is hanging from a wire in a computer room), and the big finish (in the trailer, where Cruise is propelled from an exploding helicopter onto a train). While both scenes are good, there's nothing new in them. In fact, the break-in is virtually identical to a similar scene in SNEAKERS. Yawn.
The free and inaccurate use of high-technobabble makes the production look worse than it is, and Danny Elfman's score is surprisingly flat. While the acting is on-target, never getting too far over-the-top, the movie simply starts with a whimper... and, you guessed it... self-destructs.
RATING: **1/2
|------------------------------| \ ***** Perfection \ \ **** Good, memorable film \ \ *** Average, hits and misses \ \ ** Sub-par on many levels \ \ * Unquestionably awful \ |------------------------------|
-Christopher Null /<EMAIL_ADDRESS>-Screenwriter-Producer / Novelist-Publisher -Visit the Movie Emporium at http://www.filmcritic.com/ -and e-mail requests to join the movie review mailing list
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
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Moksha Basics
Moksha isn't your average desktop. Here are some quick pointers.
Ecomorph
Extra desktop effects for Moksha.
Quick FAQ
Answers to a few Frequently Asked Questions.
Resources
Links through which you can find more information.
Colophon
Credits/ Revisions/ License For QuickStart Guide.


Fallen (1998)
Director: Gregory Hoblit Cast: Denzel Washington, Donald Sutherland, John Goodman, Embeth Davidtz, Elias Koteas, James Gandolfini Rated R: violence, language
by Nathaniel R. Atcheson<EMAIL_ADDRESS>I've got to give the makers of Fallen credit for trying something high-minded and going through with it for the most part. The film is composed of appealing ideas and characters, and often times it even works, but after hearing about this story, I would have handled the execution completely differently. This could have been a deeply disturbing film, moving and profound on multiple levels. Too bad, because it waters down its own dark themes, and shifts with unnatural tonal changes. The result is an original, well-acted film that tiptoes around greatness and ends up falling far short of the mark.
Denzel Washington stars as John Hobbes, the New York detective who narrates the story. In the beginning, we find that he has just put away serial killer Edgar Reese (Elias Koteas in a brief but energetic performance). It doesn't take long for Hobbes to find out that the spirit of the killer is being passed around from body to body by means of touch--in one frantic sequence, he watches on the street as each passerby stares him in the eye with a demonic grin. He enlists the help of theologian Gretta Milano (Embeth Davidtz); as it turns out, her father went through the exact same situation that Hobbes is going through at the time of the film.
Fallen is a strange case. I immediately knew there was something wrong when the lively '60s tune Time is on My Side (I think that's what it's called...) began blaring during the credits. Credits, for me, set the tone of the film, and this is not what I'd expect from a film called Fallen about serial killers and spirits gone awry. This isn't a severe misstep, however--the narration is a far bigger problem. Washington is a terrific actor, and this is a great performance, but his voice is just not good for narration. He sounds too happy, too nice for it to be a foreboding element. It's not really comical, but with his voice in there all along, there isn't really any doubt that he's going to be okay. In that case, a central element of suspense in the film is lost.
This leads right into another striking problem with the film--it isn't scary enough. This is a story that sent a tingle down my spine when I saw the preview. The ideas here have so much promise--just the thought of a killer who can pass from person to person so easily is utterly unnerving. The execution, though, could have been so much more eerie. It's creepy just in nature, but it could have been downright out of control. The director, Gregory Hoblit, is not entirely to blame for this: I think the fatal error here is the fact that the audience knows what's going on far too early--this is dramatic irony at its most extreme. We get to find out what's going on just from seeing the trailer, but Hobbes doesn't get in on the secret until halfway through the film.
With the central idea behind the film let out so early, it's truly hard to be afraid of it. Another big mistake is the usage of first-person from the eyes of the spirit. There is something about seeing what it sees that totally eliminates all suspense from the situation. There is one truly breathtaking moment, involving the basement of a lonely cabin and a lot of spider webs, but most of the film lacks this kind of intense uncertainty.
Still, there is a lot to like about this film. The performances, for one, are all great. Washington is always convincing as the cop who is seemingly at the center of this supernatural joke. John Goodman, who plays Hobbes' partner, manages to create an interesting character in the limited screen time he's given, and Donald Sutherland is good as always as Hobbes' boss. I also liked Davidtz--she displayed the same kind of strength that she did as Helen Hirsch in Schindler's List.
It's a decent film, but you'll know when you watch it that it's been tested and toned down from what it was originally supposed to be. The ending, too, feels like a major cheat. The ideas behind this film are superb--highly imaginative and ultimately convincing. As far as the execution is from what I wanted, the film still engaged me. I liked the characters enough, and the situation is extremely interesting.
It's pretty rare that films take on this religious, demonic tone. Last year I went into The Devil's Advocate not expecting much, and I got a forceful, extremely moving and often disturbing picture. Fallen promises as much but didn't deliver--this film should have been directed by David Fincher. Had it been darker and more ominous, Fallen would have been a truly great film. It takes the easier path, though, and ends up just making you wish that someone in the production had thought that we could have handled something more hard-hitting.
>From 0-10: 6 Grade: C+
Visit FILM PSYCHOSIS at http://www.pyramid.net/natesmovies
Nathaniel R. Atcheson
The review above was posted to the
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Driver wounded in shooting on Indianapolis highway
INDIANAPOLIS (AP) - Authorities say man was wounded in the face in a shooting that happened while he was driving on Interstate 465 on the southeast side of Indianapolis.
Indiana State Police say investigators were searching for whoever fired at the man about 7:30 p.m. Saturday in the highway’s southbound lanes near I-74. Police say the man was taken to a hospital in stable condition and he’s expected to recover.
Police say the gunfire came from a car that pulled alongside the driver’s car. Two other people inside the car that was fired upon weren’t injured.
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Investigators didn’t immediately say what led up to the shooting but said they didn’t believe it was a random attack.
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Climate Change Indicators: Leaf and Bloom Dates
Key Points
- First leaf and bloom dates in lilacs and honeysuckles in the contiguous 48 states show a great deal of year-to-year variability, which makes it difficult to determine whether a statistically meaningful change has taken place. Earlier dates appear more prevalent in the last few decades, however (see Figure 1).
- Leaf and bloom events are generally happening earlier throughout the North and West but later in much of the South (see Figures 2 and 3). This observation is generally consistent with regional differences in temperature change (see the U.S. and Global Temperature indicator).
- Other studies have looked at trends in leaf and bloom dates across all of North America and the entire Northern Hemisphere. These studies have also found a trend toward earlier spring events—some more pronounced than the trends seen in just the contiguous 48 states.4
Background
The timing of natural events, such as flower blooms and animal migration, can be influenced by changes in climate. Phenology is the study of such important seasonal events. Phenological events are influenced by a combination of environmental factors, including temperature, light, rainfall, and humidity. Different plant and animal species respond to different cues.
Scientists have high confidence that the earlier arrival of spring events is linked to recent warming trends in global climate.1 Disruptions in the timing of these events can have a variety of impacts on ecosystems and human society. For example, an earlier spring might lead to longer growing seasons (see the Length of Growing Season indicator), more abundant invasive species and pests, and earlier and longer allergy seasons. Unusually warm weather in late winter can create a “false spring” that triggers the new growth of plants to begin too early, leaving them vulnerable to any subsequent frosts.
Because of their close connection with climate, the timing of phenological events can be used as an indicator of the sensitivity of ecological processes to climate change. Two particularly useful indicators of the timing of spring events are the first leaf dates and the first bloom dates of lilacs and honeysuckles, which have an easily monitored flowering season, a relatively high survival rate, and a large geographic distribution. The first leaf date in these plants relates to the timing of events that occur in early spring, while the first bloom date is consistent with the timing of later spring events, such as the start of growth in forest vegetation.2
About the Indicator
This indicator shows trends in the timing of first leaf dates and first bloom dates in lilacs and honeysuckles across the contiguous 48 states. Because many of the phenological observation records in the United States are less than 40 years long, and because these records may have gaps in time or space, computer models have been used to provide a more complete understanding of long-term trends nationwide.
The models for this indicator were developed using data from the USA National Phenology Network, which collects ground observations from a network of federal agencies, field stations, educational institutions, and citizens who have been trained to log observations of leaf and bloom dates. For consistency, observations were limited to a few specific types of lilacs and honeysuckles. Next, models were created to relate actual leaf and bloom observations with records from nearby weather stations. Once scientists were able to determine the relationship between climate factors (particularly temperatures) and leaf and bloom dates, they used this knowledge to estimate leaf and bloom dates for earlier years based on historical weather records. They also used the models to estimate how leaf and bloom dates would have changed in a few areas (mostly in the far South) where lilacs and honeysuckles are not widespread.
This indicator uses data from nearly 3,000 weather stations throughout the contiguous 48 states. The exact number of stations varies from year to year. For each year, the timing of first leaf and first bloom at each station was compared with the 1981 to 2010 average to determine the number of days’ “deviation from normal.” This indicator presents the average deviation across all stations, along with maps that compare the most recent 10-year period (2006–2015) with a mid-20th-century baseline (1951–1960) at individual stations. These time periods were chosen to match published studies.3
Indicator Notes
Plant phenological events are studied using several data collection methods, including satellite images, models, and direct observations. Locational differences, the use of varying data collection methods, and different phenological indicators (such as leaf or bloom dates for different types of plants) can lead to a range of estimates of the arrival of spring.
Climate is not the only factor that can affect phenology. Observed variations can also reflect plant genetics, changes in the surrounding ecosystem, and other factors. This indicator minimizes the influence of genetic variations by relying on cloned plants (that is, plants with no genetic differences).
Data Sources
Leaf and bloom observations were compiled by the USA National Phenology Network and are available at: www.usanpn.org. This indicator is also based on temperature data from the National Oceanic and Atmospheric Administration’s National Centers for Environmental Information, which maintains a large collection of climate data online at: www.ncei.noaa.gov. Data for this indicator were analyzed using methods described by Schwartz et al. (2013).8
Technical Documentation
References
1 IPCC (Intergovernmental Panel on Climate Change). 2014. Climate change 2014: Impacts, adaptation, and vulnerability. Working Group II contribution to the IPCC Fifth Assessment Report. Cambridge, United Kingdom: Cambridge University Press. www.ipcc.ch/report/ar5/wg2.
2 Schwartz, M.D., R. Ahas, and A. Aasa. 2006. Onset of spring starting earlier across the Northern Hemisphere. Glob. Chang. Biol. 12:343–351.
3 Schwartz, M.D., T.R. Ault, and J.L. Betancourt. 2013. Spring onset variations and trends in the continental United States: Past and regional assessment using temperature-based indices. Int. J. Climatol. 33:2917–2922.
4 For example, see: Schwartz, M.D., R. Ahas, and A. Aasa. 2006. Onset of spring starting earlier across the Northern Hemisphere. Glob. Chang. Biol. 12:343–351.
5 Schwartz, M.D. 2016 update to data originally published in: Schwartz, M.D., T.R. Ault, and J.L. Betancourt. 2013. Spring onset variations and trends in the continental United States: Past and regional assessment using temperature-based indices. Int. J. Climatol. 33:2917–2922.
6 Schwartz, M.D. 2016 update to data originally published in: Schwartz, M.D., T.R. Ault, and J.L. Betancourt. 2013. Spring onset variations and trends in the continental United States: Past and regional assessment using temperature-based indices. Int. J. Climatol. 33:2917–2922.
7 Schwartz, M.D. 2016 update to data originally published in: Schwartz, M.D., T.R. Ault, and J.L. Betancourt. 2013. Spring onset variations and trends in the continental United States: Past and regional assessment using temperature-based indices. Int. J. Climatol. 33:2917–2922.
8 Schwartz, M.D., T.R. Ault, and J.L. Betancourt. 2013. Spring onset variations and trends in the continental United States: Past and regional assessment using temperature-based indices. Int. J. Climatol. 33:2917–2922.


Table 6.3. Historical-Cost Net Stock of Private Fixed Assets by Industry Group and Legal Form of Organization bea.gov
# [Private fixed assets](#Private_fixed_assets)
```javascript
var Private_fixed_assets_chart = new Multi_chart([["data.csv",["Private_fixed_assets"]]],function(data){return data;},"#Private_fixed_assets","billions");
```
# [By legal form of organization Corporate](#By_legal_form_of_organization_Corporate)
```javascript
var By_legal_form_of_organization_Corporate_chart = new Multi_chart([["data.csv",["By_legal_form_of_organization_Corporate"]]],function(data){return data;},"#By_legal_form_of_organization_Corporate","billions");
```
# [By legal form of organization Financial](#By_legal_form_of_organization_Financial)
```javascript
var By_legal_form_of_organization_Financial_chart = new Multi_chart([["data.csv",["By_legal_form_of_organization_Financial"]]],function(data){return data;},"#By_legal_form_of_organization_Financial","billions");
```
# [By legal form of organization Nonfinancial](#By_legal_form_of_organization_Nonfinancial)
```javascript
var By_legal_form_of_organization_Nonfinancial_chart = new Multi_chart([["data.csv",["By_legal_form_of_organization_Nonfinancial"]]],function(data){return data;},"#By_legal_form_of_organization_Nonfinancial","billions");
```
# [By legal form of organization Noncorporate](#By_legal_form_of_organization_Noncorporate)
```javascript
var By_legal_form_of_organization_Noncorporate_chart = new Multi_chart([["data.csv",["By_legal_form_of_organization_Noncorporate"]]],function(data){return data;},"#By_legal_form_of_organization_Noncorporate","billions");
```
# [By legal form of organization Sole proprietorships](#By_legal_form_of_organization_Sole_proprietorships)
```javascript
var By_legal_form_of_organization_Sole_proprietorships_chart = new Multi_chart([["data.csv",["By_legal_form_of_organization_Sole_proprietorships"]]],function(data){return data;},"#By_legal_form_of_organization_Sole_proprietorships","billions");
```
# [By legal form of organization Partnerships](#By_legal_form_of_organization_Partnerships)
```javascript
var By_legal_form_of_organization_Partnerships_chart = new Multi_chart([["data.csv",["By_legal_form_of_organization_Partnerships"]]],function(data){return data;},"#By_legal_form_of_organization_Partnerships","billions");
```
# [By legal form of organization Nonprofit institutions](#By_legal_form_of_organization_Nonprofit_institutions)
```javascript
var By_legal_form_of_organization_Nonprofit_institutions_chart = new Multi_chart([["data.csv",["By_legal_form_of_organization_Nonprofit_institutions"]]],function(data){return data;},"#By_legal_form_of_organization_Nonprofit_institutions","billions");
```
# [By legal form of organization Households](#By_legal_form_of_organization_Households)
```javascript
var By_legal_form_of_organization_Households_chart = new Multi_chart([["data.csv",["By_legal_form_of_organization_Households"]]],function(data){return data;},"#By_legal_form_of_organization_Households","billions");
```
# [By legal form of organization Tax exempt cooperatives](#By_legal_form_of_organization_Tax_exempt_cooperatives)
```javascript
var By_legal_form_of_organization_Tax_exempt_cooperatives_chart = new Multi_chart([["data.csv",["By_legal_form_of_organization_Tax_exempt_cooperatives"]]],function(data){return data;},"#By_legal_form_of_organization_Tax_exempt_cooperatives","billions");
```
# [For selected industry groups Farms](#For_selected_industry_groups_Farms)
```javascript
var For_selected_industry_groups_Farms_chart = new Multi_chart([["data.csv",["For_selected_industry_groups_Farms"]]],function(data){return data;},"#For_selected_industry_groups_Farms","billions");
```
# [For selected industry groups Manufacturing](#For_selected_industry_groups_Manufacturing)
```javascript
var For_selected_industry_groups_Manufacturing_chart = new Multi_chart([["data.csv",["For_selected_industry_groups_Manufacturing"]]],function(data){return data;},"#For_selected_industry_groups_Manufacturing","billions");
```
# [For selected industry groups Nonfarm nonmanufacturing nonresidential fixed assets only](#For_selected_industry_groups_Nonfarm_nonmanufacturing_nonresidential_fixed_assets_only)
```javascript
var For_selected_industry_groups_Nonfarm_nonmanufacturing_nonresidential_fixed_assets_only_chart = new Multi_chart([["data.csv",["For_selected_industry_groups_Nonfarm_nonmanufacturing_nonresidential_fixed_assets_only"]]],function(data){return data;},"#For_selected_industry_groups_Nonfarm_nonmanufacturing_nonresidential_fixed_assets_only","billions");
```
```data
year,Private_fixed_assets,By_legal_form_of_organization_Corporate,By_legal_form_of_organization_Financial,By_legal_form_of_organization_Nonfinancial,By_legal_form_of_organization_Noncorporate,By_legal_form_of_organization_Sole_proprietorships,By_legal_form_of_organization_Partnerships,By_legal_form_of_organization_Nonprofit_institutions,By_legal_form_of_organization_Households,By_legal_form_of_organization_Tax_exempt_cooperatives,For_selected_industry_groups_Farms,For_selected_industry_groups_Manufacturing,For_selected_industry_groups_Nonfarm_nonmanufacturing_nonresidential_fixed_assets_only
1925,147.9,70.4,2.2,68.1,77.5,18.6,6.1,5.3,47.6,0.0,6.8,13.5,70.0
1926,157.4,73.5,2.3,71.2,83.9,20.3,6.5,6.1,51.0,0.0,6.9,14.0,74.1
1927,166.0,76.2,2.4,73.8,89.8,21.9,6.9,6.8,54.1,0.0,7.1,14.5,77.6
1928,174.0,79.0,2.6,76.4,95.1,23.4,7.3,7.5,56.8,0.0,7.3,15.2,81.0
1929,181.6,82.5,2.7,79.7,99.2,24.6,7.8,8.1,58.8,0.0,7.4,16.3,84.6
1930,185.4,84.5,2.9,81.6,101.0,24.8,7.9,8.5,59.7,0.0,7.5,16.7,86.9
1931,185.4,84.1,2.9,81.3,101.3,24.5,7.8,8.8,60.2,0.0,7.2,16.5,86.8
1932,182.2,82.3,2.8,79.5,99.9,23.7,7.5,8.8,59.8,0.0,6.8,15.9,85.1
1933,178.8,80.5,2.7,77.7,98.3,23.0,7.3,8.7,59.4,0.0,6.5,15.6,83.0
1934,176.8,79.4,2.7,76.7,97.4,22.5,7.1,8.6,59.3,0.0,6.3,15.5,81.6
1935,176.2,78.8,2.7,76.2,97.4,22.3,7.0,8.6,59.4,0.1,6.3,15.6,80.8
1936,177.4,79.3,2.7,76.6,98.2,22.4,7.1,8.6,59.9,0.1,6.4,15.9,81.0
1937,180.6,80.9,2.7,78.2,99.7,22.8,7.3,8.7,60.6,0.2,6.6,16.8,82.3
1938,182.0,81.2,2.7,78.5,100.8,22.9,7.4,8.8,61.4,0.3,6.7,17.0,82.5
1939,184.7,81.8,2.7,79.1,103.0,23.3,7.5,8.9,63.0,0.3,6.8,17.3,83.0
1940,189.3,83.4,2.7,80.7,105.8,23.7,7.7,9.1,65.0,0.4,6.8,18.2,84.3
1941,196.0,86.3,2.8,83.5,109.7,24.4,8.0,9.3,67.5,0.5,7.2,19.8,86.2
1942,198.0,87.5,2.8,84.7,110.5,24.3,7.9,9.2,68.5,0.5,7.2,20.7,86.2
1943,198.3,87.8,2.7,85.1,110.5,24.1,7.9,9.1,68.8,0.5,7.2,21.0,86.0
1944,200.6,89.5,2.7,86.8,111.1,24.2,7.9,9.0,69.3,0.6,7.5,21.9,86.7
1945,205.9,93.3,2.6,90.6,112.7,24.8,8.3,9.1,69.8,0.7,7.8,23.6,89.7
1946,222.8,100.7,2.9,97.8,122.2,26.7,9.2,9.5,75.9,0.8,8.7,27.0,95.8
1947,248.8,111.1,3.1,108.0,137.7,30.0,10.6,10.1,86.0,1.1,10.4,31.5,104.9
1948,280.0,122.6,3.4,119.2,157.4,34.0,12.2,11.1,98.7,1.4,12.5,35.4,116.1
1949,306.6,131.5,3.7,127.8,175.1,37.5,13.5,12.2,110.3,1.6,14.4,37.5,126.1
1950,340.5,141.4,4.0,137.4,199.1,41.4,15.0,13.7,127.3,1.8,16.2,39.7,137.7
1951,374.7,154.4,4.4,149.9,220.3,44.5,16.3,15.2,142.2,2.0,17.8,44.3,149.8
1952,408.0,167.9,4.8,163.1,240.1,46.9,17.3,16.6,157.1,2.2,19.2,49.2,161.3
1953,444.1,183.0,5.4,177.7,261.1,49.6,18.5,18.1,172.3,2.5,20.4,54.1,175.2
1954,479.5,196.4,5.9,190.5,283.1,52.0,19.6,19.9,188.9,2.7,21.2,58.4,187.9
1955,521.3,211.3,6.7,204.7,309.9,55.1,21.2,21.9,208.9,2.9,22.0,62.9,203.5
1956,565.9,231.4,7.6,223.8,334.5,57.7,22.6,24.1,227.0,3.1,22.5,70.4,220.9
1957,610.1,252.7,8.4,244.3,357.4,60.5,23.9,26.5,243.2,3.3,23.0,78.0,239.5
1958,647.5,267.7,9.0,258.7,379.8,63.8,25.0,29.2,258.4,3.4,23.7,82.3,254.9
1959,692.8,284.5,9.8,274.7,408.3,66.6,26.5,32.0,279.7,3.6,24.9,86.1,272.6
1960,737.7,303.7,10.7,293.0,434.0,69.2,27.8,35.3,297.9,3.8,25.8,91.7,290.8
1961,780.9,321.5,11.6,309.9,459.4,71.7,29.1,38.9,315.6,4.0,26.6,96.5,308.2
1962,829.0,341.0,12.6,328.4,488.0,74.8,30.7,43.1,335.2,4.3,27.8,102.0,327.6
1963,881.0,361.0,13.6,347.4,520.0,78.2,32.5,46.7,358.2,4.5,29.4,107.9,347.2
1964,939.7,385.1,15.1,370.0,554.6,81.9,34.6,50.8,382.5,4.7,31.0,115.7,369.9
1965,1007.4,416.6,16.8,399.8,590.7,86.2,37.4,55.6,406.6,4.9,33.0,126.8,398.6
1966,1080.0,455.3,18.5,436.8,624.7,91.3,40.4,60.6,427.3,5.2,35.3,141.4,430.8
1967,1150.1,492.6,20.4,472.1,657.5,95.6,43.0,65.1,448.4,5.5,37.6,155.0,461.7
1968,1230.0,533.5,23.2,510.3,696.5,104.0,45.4,69.9,471.3,5.9,39.4,168.6,497.0
1969,1320.5,579.6,26.0,553.6,741.0,115.3,48.7,75.7,495.1,6.2,41.3,183.7,538.0
1970,1408.1,623.8,28.6,595.2,784.3,126.5,52.1,81.5,517.5,6.6,43.6,198.0,578.3
1971,1509.6,667.7,31.8,635.9,841.9,140.2,55.7,88.0,550.9,7.1,45.9,210.4,620.9
1972,1633.8,719.9,35.1,684.8,913.9,158.2,59.6,96.3,592.2,7.6,48.4,224.8,671.3
1973,1780.9,785.9,40.1,745.8,995.0,176.8,64.9,104.6,640.6,8.1,53.2,242.4,734.7
1974,1927.7,863.5,46.7,816.8,1064.2,196.3,69.4,112.6,677.1,8.7,58.8,268.4,799.1
1975,2067.3,937.5,53.6,883.9,1129.8,208.9,73.9,119.4,717.8,9.8,66.0,293.7,859.5
1976,2237.1,1021.3,60.8,960.6,1215.8,221.9,78.9,126.3,777.7,10.9,73.3,320.3,930.6
1977,2459.1,1127.0,68.4,1058.5,1332.1,239.0,85.1,134.7,860.9,12.4,81.4,351.5,1022.5
1978,2739.4,1263.3,79.2,1184.1,1476.1,263.6,94.5,144.2,960.6,13.2,90.8,390.3,1144.4
1979,3065.8,1430.3,93.3,1337.0,1635.5,295.7,108.9,154.7,1061.4,14.8,101.9,435.0,1298.5
1980,3381.3,1609.0,110.5,1498.5,1772.3,323.7,124.3,165.6,1143.0,15.7,109.2,486.9,1459.9
1981,3735.0,1815.7,130.7,1685.0,1919.3,356.3,146.8,177.6,1221.8,16.9,116.3,547.1,1655.4
1982,4051.9,2008.7,152.1,1856.6,2043.2,380.8,168.8,191.6,1284.8,17.2,118.5,594.9,1850.9
1983,4389.7,2183.9,174.9,2008.9,2205.8,406.0,185.5,207.6,1389.4,17.3,119.9,632.8,2030.6
1984,4810.3,2405.2,204.3,2200.9,2405.1,437.0,208.6,225.0,1517.1,17.4,122.2,685.6,2251.9
1985,5249.1,2634.8,237.6,2397.1,2614.4,469.2,236.6,242.2,1647.0,19.4,121.3,743.3,2485.0
1986,5683.1,2835.1,273.1,2561.9,2848.0,502.8,261.3,261.3,1801.9,20.7,119.5,787.8,2697.7
1987,6110.8,3015.5,307.2,2708.3,3095.3,533.4,287.1,283.6,1969.9,21.2,118.0,827.9,2899.5
1988,6558.2,3209.7,344.0,2865.7,3348.5,563.9,314.6,307.0,2141.2,21.7,119.6,869.4,3116.2
1989,7018.6,3425.3,385.5,3039.8,3593.3,593.3,339.9,332.3,2305.6,22.2,122.6,926.1,3336.2
1990,7458.0,3656.0,421.2,3234.8,3802.0,614.2,353.7,358.5,2452.3,23.3,126.3,985.4,3552.5
1991,7829.7,3852.2,446.1,3406.1,3977.6,628.5,361.6,382.2,2581.0,24.2,128.1,1041.3,3729.7
1992,8214.9,4041.9,468.4,3573.5,4173.0,641.2,364.9,405.8,2735.9,25.2,127.9,1095.1,3898.0
1993,8667.1,4261.0,493.6,3767.4,4406.1,661.6,373.9,426.3,2917.8,26.4,131.2,1142.8,4106.7
1994,9177.6,4507.2,522.4,3984.7,4670.4,686.4,384.4,446.3,3125.9,27.3,136.9,1204.1,4330.2
1995,9746.3,4808.7,549.5,4259.2,4937.5,718.2,398.4,467.5,3324.9,28.5,143.5,1289.4,4589.5
1996,10380.8,5144.1,583.5,4560.6,5236.8,750.5,414.3,490.4,3551.5,29.9,150.6,1388.6,4873.0
1997,11072.3,5511.4,619.3,4892.1,5560.8,786.9,433.5,524.3,3784.9,31.4,160.0,1486.1,5203.0
1998,11837.7,5901.4,670.9,5230.4,5936.3,822.1,462.1,566.7,4052.3,33.0,168.0,1581.7,5576.3
1999,12671.8,6319.6,726.2,5593.3,6352.2,858.0,500.2,611.4,4347.7,35.1,170.8,1665.4,6003.3
2000,13572.9,6777.5,775.0,6002.6,6795.4,892.2,547.4,661.7,4655.4,38.7,175.5,1756.7,6474.6
2001,14373.6,7127.3,808.5,6318.8,7246.3,920.7,592.5,712.4,4977.6,43.1,181.2,1833.7,6843.1
2002,15077.0,7346.4,838.8,6507.6,7730.5,948.1,636.1,767.7,5332.1,46.6,188.8,1869.7,7120.5
2003,15833.4,7560.1,862.1,6698.0,8273.3,978.8,675.0,824.0,5745.7,49.8,197.0,1893.8,7398.0
2004,16729.8,7819.2,898.6,6920.6,8910.6,1014.1,719.0,880.8,6244.4,52.3,207.2,1925.8,7717.9
2005,17786.9,8164.8,932.3,7232.6,9622.1,1053.7,772.1,936.6,6804.4,55.3,217.4,1983.0,8109.6
2006,18960.4,8614.6,968.6,7646.0,10345.8,1097.6,838.2,999.8,7350.9,59.2,225.2,2057.8,8614.4
2007,20051.6,9122.7,1019.0,8103.7,10928.9,1137.6,916.5,1070.0,7739.7,65.0,234.0,2171.0,9161.5
2008,20920.9,9590.8,1049.7,8541.1,11330.1,1172.5,991.7,1141.5,7953.3,71.2,247.7,2282.8,9667.2
2009,21327.4,9772.3,1046.6,8725.7,11555.1,1186.7,1030.1,1200.2,8060.3,77.9,259.7,2326.0,9900.1
2010,21743.9,9992.7,1046.1,8946.6,11751.3,1194.6,1064.2,1243.4,8165.3,83.8,271.0,2375.4,10147.5
2011,22289.1,10323.9,1058.6,9265.3,11965.2,1207.8,1104.0,1289.5,8273.7,90.3,286.4,2454.0,10484.2
2012,23006.8,10759.1,1089.1,9669.9,12247.7,1234.1,1155.4,1337.5,8422.1,98.7,313.2,2550.2,10918.8
2013,23817.0,11218.7,1127.1,10091.6,12598.3,1267.8,1209.2,1381.8,8634.3,105.2,340.4,2668.1,11351.8
2014,24738.4,11746.5,1172.3,10574.2,12991.9,1306.8,1268.7,1428.9,8875.4,112.1,362.5,2806.1,11847.4
```


|
F´ Flight Software - C/C++ Documentation
NASA-v1.5.0
A framework for building embedded system applications to NASA flight quality standards.
|
Auto-generated base for LinuxSpiDriver component. More...
#include <build-fprime-automatic-native/F-Prime/Drv/LinuxSpiDriver/LinuxSpiDriverComponentAc.hpp>
Public Types | |
| enum | { NUM_SPIREADWRITE_INPUT_PORTS = 1 } |
| enum | { NUM_TLM_OUTPUT_PORTS = 1, NUM_LOG_OUTPUT_PORTS = 1, NUM_LOGTEXT_OUTPUT_PORTS = 1, NUM_TIME_OUTPUT_PORTS = 1 } |
| enum | { EVENTID_SPI_WRITEERROR_THROTTLE = 5 } |
Friends | |
| class | LinuxSpiDriverComponentBaseFriend |
Additional Inherited Members | |
| Protected Member Functions inherited from Fw::ObjBase | |
| ObjBase (const char *name) | |
| ObjBase constructor. More... | |
| virtual | ~ObjBase () |
| Destructor. More... | |
| void | init (void) |
| Object initializer. More... | |
Auto-generated base for LinuxSpiDriver component.
Definition at line 40 of file LinuxSpiDriverComponentAc.hpp.
| anonymous enum |
| Enumerator | |
|---|---|
| NUM_SPIREADWRITE_INPUT_PORTS |
Definition at line 217 of file LinuxSpiDriverComponentAc.hpp.
| anonymous enum |
| Enumerator | |
|---|---|
| NUM_TLM_OUTPUT_PORTS | |
| NUM_LOG_OUTPUT_PORTS | |
| NUM_LOGTEXT_OUTPUT_PORTS | |
| NUM_TIME_OUTPUT_PORTS |
Definition at line 254 of file LinuxSpiDriverComponentAc.hpp.
| anonymous enum |
| Enumerator | |
|---|---|
| EVENTID_SPI_WRITEERROR_THROTTLE | Throttle reset count for SPI_WriteError |
Definition at line 318 of file LinuxSpiDriverComponentAc.hpp.
|
virtual |
Destroy a LinuxSpiDriverComponentBase object
Definition at line 279 of file LinuxSpiDriverComponentAc.cpp.
| Drv::InputSpiReadWritePort * Drv::LinuxSpiDriverComponentBase::get_SpiReadWrite_InputPort | ( | NATIVE_INT_TYPE | portNum | ) |
Get input port at index
| portNum | The port number |
Definition at line 28 of file LinuxSpiDriverComponentAc.cpp.
| NATIVE_INT_TYPE Drv::LinuxSpiDriverComponentBase::getNum_Log_OutputPorts | ( | void | ) |
Get the number of Log output ports
Definition at line 300 of file LinuxSpiDriverComponentAc.cpp.
| NATIVE_INT_TYPE Drv::LinuxSpiDriverComponentBase::getNum_Time_OutputPorts | ( | void | ) |
Get the number of Time output ports
Definition at line 326 of file LinuxSpiDriverComponentAc.cpp.
| void Drv::LinuxSpiDriverComponentBase::init | ( | NATIVE_INT_TYPE | instance = 0 | ) |
Initialize a LinuxSpiDriverComponentBase object
| instance | The instance number |
Definition at line 151 of file LinuxSpiDriverComponentAc.cpp.
| bool Drv::LinuxSpiDriverComponentBase::isConnected_Log_OutputPort | ( | NATIVE_INT_TYPE | portNum | ) |
Check whether port Log is connected
| portNum | The port number |
Definition at line 348 of file LinuxSpiDriverComponentAc.cpp.
| bool Drv::LinuxSpiDriverComponentBase::isConnected_Time_OutputPort | ( | NATIVE_INT_TYPE | portNum | ) |
Check whether port Time is connected
| portNum | The port number |
Definition at line 370 of file LinuxSpiDriverComponentAc.cpp.
| void Drv::LinuxSpiDriverComponentBase::log_ACTIVITY_HI_SPI_PortOpened | ( | I32 | device, |
| I32 | select | ||
| ) |
Log event SPI_PortOpened
| device | The device |
| select | The chip select |
Definition at line 845 of file LinuxSpiDriverComponentAc.cpp.
| void Drv::LinuxSpiDriverComponentBase::log_WARNING_HI_SPI_ConfigError | ( | I32 | device, |
| I32 | select, | ||
| I32 | error | ||
| ) |
Log event SPI_ConfigError
| device | The device |
| select | The chip select |
| error | The error code |
Definition at line 567 of file LinuxSpiDriverComponentAc.cpp.
| void Drv::LinuxSpiDriverComponentBase::log_WARNING_HI_SPI_WriteError | ( | I32 | device, |
| I32 | select, | ||
| I32 | error | ||
| ) |
Log event SPI_WriteError
| device | The device |
| select | The chip select |
| error | The error code |
Definition at line 701 of file LinuxSpiDriverComponentAc.cpp.
| void Drv::LinuxSpiDriverComponentBase::log_WARNING_HI_SPI_WriteError_ThrottleClear | ( | void | ) |
Definition at line 840 of file LinuxSpiDriverComponentAc.cpp.
| void Drv::LinuxSpiDriverComponentBase::set_Log_OutputPort | ( | NATIVE_INT_TYPE | portNum, |
| Fw::InputLogPort * | port | ||
| ) |
Connect port to Log[portNum]
| portNum | The port number |
| port | The port |
Definition at line 49 of file LinuxSpiDriverComponentAc.cpp.
| void Drv::LinuxSpiDriverComponentBase::set_Time_OutputPort | ( | NATIVE_INT_TYPE | portNum, |
| Fw::InputTimePort * | port | ||
| ) |
Connect port to Time[portNum]
| portNum | The port number |
| port | The port |
Definition at line 71 of file LinuxSpiDriverComponentAc.cpp.
| void Drv::LinuxSpiDriverComponentBase::set_Tlm_OutputPort | ( | NATIVE_INT_TYPE | portNum, |
| Fw::InputTlmPort * | port | ||
| ) |
Connect port to Tlm[portNum]
| portNum | The port number |
| port | The port |
Definition at line 39 of file LinuxSpiDriverComponentAc.cpp.
|
friend |
Friend class for white-box testing
Definition at line 50 of file LinuxSpiDriverComponentAc.hpp.
| PROTECTED Drv::LinuxSpiDriverComponentBase::__pad0__ |
Definition at line 142 of file LinuxSpiDriverComponentAc.hpp.
| PRIVATE Drv::LinuxSpiDriverComponentBase::__pad10__ |
Definition at line 405 of file LinuxSpiDriverComponentAc.hpp.
| PRIVATE Drv::LinuxSpiDriverComponentBase::__pad11__ |
Definition at line 415 of file LinuxSpiDriverComponentAc.hpp.
| PRIVATE Drv::LinuxSpiDriverComponentBase::__pad12__ |
The component instance
Definition at line 439 of file LinuxSpiDriverComponentAc.hpp.
| PRIVATE Drv::LinuxSpiDriverComponentBase::__pad13__ |
throttle for SPI_WriteError
Definition at line 455 of file LinuxSpiDriverComponentAc.hpp.
| PROTECTED Drv::LinuxSpiDriverComponentBase::__pad1__ |
The port number
Definition at line 170 of file LinuxSpiDriverComponentAc.hpp.
| PROTECTED Drv::LinuxSpiDriverComponentBase::__pad2__ |
The port number
Definition at line 184 of file LinuxSpiDriverComponentAc.hpp.
| PROTECTED Drv::LinuxSpiDriverComponentBase::__pad3__ |
Definition at line 200 of file LinuxSpiDriverComponentAc.hpp.
| PROTECTED Drv::LinuxSpiDriverComponentBase::__pad4__ |
Definition at line 221 of file LinuxSpiDriverComponentAc.hpp.
| PROTECTED Drv::LinuxSpiDriverComponentBase::__pad5__ |
Definition at line 261 of file LinuxSpiDriverComponentAc.hpp.
| PROTECTED Drv::LinuxSpiDriverComponentBase::__pad6__ |
Definition at line 301 of file LinuxSpiDriverComponentAc.hpp.
| PROTECTED Drv::LinuxSpiDriverComponentBase::__pad7__ |
The device
Definition at line 322 of file LinuxSpiDriverComponentAc.hpp.
| PROTECTED Drv::LinuxSpiDriverComponentBase::__pad8__ |
Channel ID for SPI_Bytes.
Definition at line 369 of file LinuxSpiDriverComponentAc.hpp.
| PROTECTED Drv::LinuxSpiDriverComponentBase::__pad9__ |
Definition at line 392 of file LinuxSpiDriverComponentAc.hpp.
| PROTECTED I32 I32 Drv::LinuxSpiDriverComponentBase::error |
< The error code
Definition at line 334 of file LinuxSpiDriverComponentAc.hpp.
| PROTECTED Drv::LinuxSpiDriverComponentBase::EVENTID_SPI_CONFIGERROR = 1 |
Definition at line 309 of file LinuxSpiDriverComponentAc.hpp.
| PROTECTED Drv::LinuxSpiDriverComponentBase::EVENTID_SPI_PORTOPENED = 4 |
Definition at line 311 of file LinuxSpiDriverComponentAc.hpp.
| PROTECTED Drv::LinuxSpiDriverComponentBase::EVENTID_SPI_WRITEERROR = 2 |
Definition at line 310 of file LinuxSpiDriverComponentAc.hpp.
| Fw::OutputLogPort Drv::LinuxSpiDriverComponentBase::m_Log_OutputPort[NUM_LOG_OUTPUT_PORTS] |
Output port Log
Definition at line 427 of file LinuxSpiDriverComponentAc.hpp.
| Fw::OutputTimePort Drv::LinuxSpiDriverComponentBase::m_Time_OutputPort[NUM_TIME_OUTPUT_PORTS] |
Output port Time
Definition at line 437 of file LinuxSpiDriverComponentAc.hpp.
| PRIVATE NATIVE_INT_TYPE Drv::LinuxSpiDriverComponentBase::portNum |
The port number
Definition at line 449 of file LinuxSpiDriverComponentAc.hpp.
| PROTECTED Drv::LinuxSpiDriverComponentBase::PROTECTED |
Definition at line 379 of file LinuxSpiDriverComponentAc.hpp.
| PROTECTED Fw::Buffer Fw::Buffer & Drv::LinuxSpiDriverComponentBase::readBuffer = 0 |
Definition at line 181 of file LinuxSpiDriverComponentAc.hpp.
| PRIVATE NATIVE_INT_TYPE Fw::Buffer Fw::Buffer& Drv::LinuxSpiDriverComponentBase::readBuffer |
Definition at line 451 of file LinuxSpiDriverComponentAc.hpp.
| PROTECTED I32 Drv::LinuxSpiDriverComponentBase::select |
The chip select
Definition at line 333 of file LinuxSpiDriverComponentAc.hpp.
| PROTECTED Fw::Buffer & Drv::LinuxSpiDriverComponentBase::writeBuffer |
Definition at line 180 of file LinuxSpiDriverComponentAc.hpp.
| PRIVATE NATIVE_INT_TYPE Fw::Buffer& Drv::LinuxSpiDriverComponentBase::writeBuffer |
Definition at line 450 of file LinuxSpiDriverComponentAc.hpp.


---
layout: post
title: Christo on Aligning ASM Disks on Linux
date: '2007-04-15T10:21:00.000-05:00'
author: Don Seiler
tags:
- asm
- oracle
- i/o
modified_time: '2010-11-19T22:48:46.833-06:00'
blogger_id: tag:blogger.com,1999:blog-7032512792942232766.post-5250317330068495538
blogger_orig_url: http://www.seiler.us/2007/04/christo-on-aligning-asm-disks-on-linux.html
---
As I sit here on a Sunday morning waiting for some disk issues to be resolved in my datacenter, I took the time to catch up on some pages I had marked for later reading. One was a post by Christo Kutrovsky from the Pythian Group, about aligning ASM disks on linux, to avoid misalignments due to odd default offsets in linux that might cause I/O for relatively small amounts of data to be inefficiently split across disks.
Also now I can't help but look at "Christo Kutrovsky" and think of Krusty the Clown, a.k.a. Herschel Krustofski.


ImageRequestConvertible
public protocol ImageRequestConvertible
A type that can be used to construct URL requests. String, URL, and URLRequest are conform to ImageRequestConvertible protocol.
-
Convert this value into a URLRequest object.
Declaration
Swift
func asURLRequest() -> URLRequest?
-
Convert this value into an absolute url string.
Declaration
Swift
func asURLString() -> String?


Issue 121
Welcome to another issue of Haskell Weekly!  This is a weekly summary of what’s going on in its community.
Featured
-
Since GHC 8.6 is almost released it’s time to start thinking about our goals for 8.8, which will branch in November. I have added the items that I know are in-flight to the 8.8 status page. If you have a project that you would like to see present in 8.8 then please do add it as well.
-
Featuring reproducible builds,
base-<IP_ADDRESS>
, and Backpack. The Eta team is happy to announce a new version of Eta — v0.8.6! Etlas v1.5.0 is also released and is required to use the newer features. -
Small assets without the headache: Minification made easy with Elm 0.19
I am excited to finally share this release publicly! I hope it will help you out, whether you are learning your first programming language or on your way to 300k lines of code at work. As folks with 50k+ lines upgrade to Elm 0.19, I encourage you to share your new asset sizes and compile times.
-
The Joy of Haskell: What is happening
Lately, we’ve been looking at all we have to write — the partially finished parts as well as the bare stubs populating the book repository and have made a decision: Joy of Haskell is properly two books, not one.
-
Announcing Haskell From Scratch beginners course
This week we have a huge announcement we’ve been working towards for a long time. One of the main goals of this blog has been to create content to make it easy for newcomers to learn Haskell. We’ve now reached the culmination of that goal with our brand new Haskell From Scratch course.
-
I want to bind keyboard shortcuts to GHCi commands. GHCi makes use of the Haskeline package for performing line input. As an example, I’m going to show you how to bind
F7
to the GHCi:reload
command. -
This summer, I worked on a Google Summer of Code project intended to implement automatic differentiation for Haskell’s accelerate vector programming EDSL, using a new method of automatic differentiation.
-
What I did on my summer vacation
This year, I took part in Google Summer of Code, with a project to attempt to finish bringing Cabal;s Nix-style local builds (the
new-
commands, at least for now) up to parity with the old stateful methodology of usingcabal-install
. -
Why doesn’t GHCi on Windows find my DLL
Why is GHCi looking for
my-cool-library.dll
instead ofmy-cool-library-7.dll
. You rename the file and things seem to work. This is actually quite dangerous and wrong. Unfortunately this is also often suggested as what to do.
Jobs
Are you looking to hire a Haskell developer? You should advertise with us!
In brief
- A very small SAT solver
cio
: Cached HTTP requests for a smooth Jupyter experience- Elm 0.19 brings better collections
- How to get into machine learning for a Haskeller
- How to Hakyll CircleCI 2.0
- How to turn a Dromedary camel into a Bactrian camel
- Lenses for philosophers
- Picnic: Put containers into a backpack
- RealWorld example with Haskell Yesod
- Solving the mystery behind the abstract algorithm’s magical optimizations
- Water jug rewrite with Haskell
Package of the week
This week’s package of the week is Bins, a library that bins continuous values into discrete containers in an interval, useful for histograms.
Call for participation
Events
- 2018-08-23 in Durham, NC, USA by Durham Haskell Meetup: Morning Haskell coding session
- 2018-08-23 in Raleigh, NC, USA by Raleigh Haskell Meetup: (hack . yack)
- 2018-08-23 in Las Vegas, NV, USA by Las Vegas Functional Programming User Group: Functional Programming Meetup
- 2018-08-23 in Denver, CO, USA by DenverFP: Property-Based Testing with QuickCheck
- 2018-08-23 in Seattle, USA by Seattle Area Haskell Users’ Group: Category Theory for Programmers Part 3
- 2018-08-23 in Eindhoven, Netherlands by Eindhoven Haskell Meetup: Let’s code a sea battle game!
- 2018-08-23 in Gdańsk, Poland by Functional Tricity: Join our new HQ - Functional Tricity #13
- 2018-08-24 in Austin, TX, USA by Austin Types, Theorems, and Programming Languages: Going through Software Foundations by Benjamin Pierce et al
- 2018-08-25 in Chilliwack, BC, Canada by ChilliHask Haskell User Group: Weekly Haskell Coding Meetup
- 2018-08-25 in San Diego , CA, USA by San Diego Software Development Deep Dive: Diving deeper into software development discussions
- 2018-08-25 in Boston, MA, USA by Weekly Functional Programming Meetup: Hang out, chat FP, work on some code
- 2018-08-25 in Bangalore, India by Papers we love, Bangalore: A tutorial on the universality and expressiveness of fold
- 2018-08-27 in Irvine, CA by Orange Combinator - Functional Programming In OC: Combinating - The Weekly Function
- 2018-08-27 in Sydney, Australia by Sydney Type Theory: Separation logic
- 2018-08-27 in Plano, TX, USA by Dallas Functional Programmers: Generative Art with Elm
- 2018-08-27 in Melbourne, Australia by Melbourne Haskell Users Group: Compose :: Melbourne 2018
- 2018-08-28 in Santa Monica, CA, USA by Santa Monica Haskell Users Group: Haskell Study Group: Parametric Polymorphism
- 2018-08-28 in Auckland, New Zealand by Functional Programming Auckland: Learn Haskell Hands-on
- 2018-08-28 in Copenhagen, Denmark by Mødegruppe for F#unktionelle Københavnere: [hands-on] We will solve random exercises from HackerRank in FP languages
- 2018-08-28 in Ann Arbor, MI, USA by Ann Arbor Functional Programming User Group: A2FP – August Meetup
- 2018-08-28 in San Francisco, CA, USA by Bay Area Haskell Users Group: Haskell Talks at SwiftNav
- 2018-08-29 in Gainesville, FL, USA by Gainesville functional programming: August meetup
- 2018-08-29 in Oslo, Norway by Osλo Haskell: Haskell in production at FINN.no
- 2018-08-29 in Quito, Ecuador by Quito Lambda: Clasificando algoritmos recursivos
- 2018-08-30 in Seattle, USA by Seattle Area Haskell Users’ Group: Category Theory for Programmers Part 3
- 2018-08-30 in Melbourne, Australia by Melbourne Haskell Users Group: Melbourne Haskell Users Group Meetup
- 2018-08-30 in Zürich, Switzerland by HaskellerZ: Bring Your Own Coding Problem #3
- 2018-08-30 in Chicago, IL, USA by The Project Euler Sprint: Project Euler Sprint
- 2018-08-30 in Sheung Wan, Hong Kong by Hong Kong Functional Programming: Fractalide


Tool Tips:
Please fill all required fields to save information from this page. A red asterisk indicates a required field.


Thank you for completing the survey.
If you wish to proceed to the optional component of this epidemiologic study, please click on the link below.
A compensation of 50-150$ will be offered for your time.
Please enter an email address and a password in order to continue to the next session. The email and password will be used to save and resume the survey.


MyMoneyKarma Front-end Assignment
If rolls a 1 on either die, they add nothing to your total score and it becomes the next player’s turn
Your total score goes to 0, and your turn ends... Good luck next time
The sum of the dice rolled is added to the turn total, as with any roll, and you must roll again
Number of players
there's always room to growth
It is not a good idea to share your personal information through a website!
Contribute to this project: https://github.com/mejiafabiandj/Pig-Game


Tailored solutions, with a fixed fee approach.
The majority of our clients are small and medium sized companies and they all rely upon precise and insightful data to run their day to day operations. At Acorn Consultants, we have experts on hand to help with any aspect of your accounting.
We offer a full range of accounting services to our clients ensuring full compliance with current law, including:
Our focus is ensuring we have a full understanding of your business as our combined approach ensures we are there to help your business grow and prosper. Our clients appreciate our high quality advice that is timely and accurate, always tailored to each of their specific business needs.
Our fixed fee approach ensures that even though our services are bespoke, there are no fee surprises. We are always there to provide advice throughout the development of your business, enabling you to focus on your business.


Useful constants for the AdWords API.
Located in /adwords/src/Google/Api/Ads/AdWords/Lib/AdWordsConstants.php (line 35)
The number of micros in a dollar (or equivalent curreny unit).
The number of micro degrees in a degree.
Recommended page size for most services.
Documentation generated by phpDocumentor 1.4.4


TileCode
App for designing, coding, and playing video games on low-cost arcade gaming handhelds.
Microsoft TileCode is an app for designing, coding, and playing video games directly on low-cost MakeCode Arcade gaming handhelds, as well as in the web browser. With TileCode, we are using the medium of video games to explore the combination of:
- Natural language for informally specifying games goals, rules, and mechanics;
- Physical computational models that foreground concepts such as data parallelism, pattern matching, and conflict resolution;
- Testing and debugging of programs to establish confidence in their behavior and to refine specifications;
- Machine learning to help bridge the gap between natural language and programs, as well as to generate non-player character behavior in games.
Our ultimate goal is to provide a sandbox in which students can express and refine their game ideas, while learning about computation, programming, and machine learning.
During the summer of 2020, I designed and ran user studies with 15 families in North America to better understand how children talk about the behavior of video games and evaluate how their informal descriptions of video games aided them in the development of TileCode games. A Microsoft Research Webinar about our initial findings took place on November 18, 2020 and is available here.


--- layout: page ---
Legal Notice / Imprint
CNSS
<EMAIL_ADDRESS>email
© cnss
Copyright
{% include mention.html %}


| DOSE: |
55 mg |
oral |
2C-D |
(capsule) |
55mg of 2C-D is carefully measured and placed into a gel capsule. I'm in a neutral mood, not depressed or sad, but also not blissful or enthusiastic either.
2:35 - Capsule ingested on an empty stomach.
3:22 - Went off to play a game in order to occupy myself, stopped just now and my head feels a little weird, slight effects, I put on some Infected Mushroom, some of my favorite music to listen to while experimenting with psychedelics. The music is nice and attractive, doesn't bring upon major effects so I'll guess that the 2c-d is still coming up.
3:35 - Music (even relaxed music such as The Police) seems too much, kind of intrusive and uncomfortable, so I turn it off. Effects are intensifying, but I can't really put my finger on what kind of effects are present.
I felt more emotional and slightly speedy until maybe 6-7 o'clock. Effects never really came, I felt like I was tripping in a way, definitely a ++, but effects were never really pronounced. Very, very light visual waving, and a little bit of an empathetic feel, but definitely nothing strong at all. I had thought about combining with 2c-b once the trip had gotten started, but after the 2C-D kicked in, I didn't feel any desire to take anything else.
2C-D seemed like it would be a great potentiator of other psychedelics, or good to extend the duration of them, at least. Taking some a while after taking another drug would probably extend it without adding much in the way of other effects, since 2c-d doesn't seem to possess many effects to start with, but just a theory.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


Treats all common medical conditions. Combines physical, psychological and social aspects of a person.
Dr.Caroline Kanuthu Dr.Jackline KimorgoProblems with skin, hair, nails? Do you have moles, scars, acne or skin allergies? Demartologist can help.
Dr.Maurine Jepchumba Dr.Sheila NangilaThese are experts on heart and blood vessels. You can see them for any heart related failures or blood pressure issues.

Dr.Prudence Chepkoech Dr.Carol LanoiSpecialises in illness, injuries or diseases of the female reproductive system such as breast & hormonal problems and cervical cancers among others.
Dr.Betty Wambui Dr.Lenora Wairimu


$urlRouter
(service in module ui.router.router
)
Triggers an update; the same update that happens when the address bar url changes, aka $locationChangeSuccess
.
This method is useful when you need to use preventDefault()
on the $locationChangeSuccess
event,
perform some custom logic (route protection, auth, config, redirection, etc) and then finally proceed
with the transition by calling $urlRouter.sync()
.
angular.module('app', ['ui.router']); .run(function($rootScope, $urlRouter) { $rootScope.$on('$locationChangeSuccess', function(evt) { // Halt state change from even starting evt.preventDefault(); // Perform custom logic var meetsRequirement = ... // Continue with the update and state transition if logic allows if (meetsRequirement) $urlRouter.sync(); }); });


Isotope Mass Abundance Spin Mag Moment
45Sc 44.955910 100% 7/2 +4.756
Sc I Ground State 1s22s22p63s23p63d4s2 2D3/2 Ionization energy 52922.0 cm-1 (6.56149 eV) Ref. SC85 Sc II Ground State 1s22s22p63s23p63d4s 3D1 Ionization energy 103237.1 cm-1 (12.79977 eV) Ref. SC85


Posted by Matt Witman on September 10, 2019
Posted by Matt Witman on June 1, 2019
Posted by Matt Witman on April 1, 2019
Posted by Matt Witman on March 1, 2019
Posted by Matt Witman on December 28, 2018
Posted by Matt Witman on October 4, 2018
Posted by Matt Witman on August 11, 2018
Posted by Matt Witman on July 30, 2018
Posted by Matt Witman on July 10, 2018
Posted by Matt Witman on May 30, 2018
Posted by Matt Witman on March 30, 2018
Posted by Matt Witman on August 8, 2017
Posted by Matt Witman on July 21, 2017


The linear models we tested were less predictive than we hoped so we decided to try a neural network model using the neuralnet package in R. For this model we decided again to lag the independent variables using the Hmisc package and create indicator variables for each month.
To begin with, we used the same 6 predictor variables that produced the lowest RMSE in the best subsets and k-fold analysis from our linear model. After playing around with including other predictor variables in the neural network we decided to add 2 more for a total of 8 predictor variables. We also adjusted the number of hidden layers and neurons in the neural network.
We found the neural network with 1 hidden layer and 4 neurons produced the lowest RMSE. Once we determined the number of hidden layers to use, we adjusted the size of the sample training data and test data. We found that dividing the sample into 80% training data and holding out 20% for the test data allowed the model to produce the lowest RMSE.


File System
This file system example demonstrates how cortex works with arbitrarily nested data structure. In this case, we use only a single React component type: a node, which can either be a folder or file. Double click on the name of a file/folder to edit and press enter when done.


People procrastinate and sometimes not even complete online course because there they are just delivered one way information. Here we teach that information in a way that shows the practicality and real-life examples of things. Moreover here they are writing the code as we teach so the exchange of information is also two way.
These tags are enclosed within angle braces < Tag Name >
Except few tags, most of the tags have their corresponding closing tags.
< !DOCTYPE... > : This tag defines the document type and HTML version.
 This tag represents the document's header which can keep other HTML tags like <title>, <link> etc.
Any document starts with a heading.
You can use different sizes for your headings..
HTML also has six levels of headings, which use the elements
,
,
,
,
, and
.
While displaying any heading, browser adds one line before and one line after that heading.
Happy Practising
An HTML element is defined by a starting tag. If the element contains other content, it ends with a closing tag, where the element name is preceded by a forward slash as shown below with few tags
So here
....
 is an HTML element,
...
 is another HTML element. There are some HTML elements which don't need to be closed, such as ,
 and
 elements. These are known as void elements.
HTML also has six levels of headings, which use the elements
,
,
,
,
, and
.
HTML documents consists of a tree of these elements and they specify how HTML documents should be built, and what kind of content should be placed in what part of an HTML document.
HTML Tag vs. Element : An HTML element is defined by a starting tag. If the element contains other content, it ends with a closing tag. For example,
 is starting tag of a paragraph and
 is closing tag of the same paragraph but
This is paragraph
 is a paragraph element.
NOW TRY PRINTING THIS IN THE EDITOR BELOW
Happy Practising


We are CodeWeekend. We developer, we share and we learn.


Damien Delaney Calls For Kenny To Replace McCarthy Before Euro 2020 Playoffs
by Robert RedmondDamien Delaney has called for Stephen Kenny to immediately replace Mick McCarthy as the Republic of Ireland manager following the team’s failure to qualify automatically for Euro 2020.
Kenny, the Ireland Under-21 coach, will succeed McCarthy as the senior team manager in August 2020.
However, following the 1-1 draw with Denmark on Monday night, which confirmed Ireland’s place in a playoff and saw the Danes secure their spot at the tournament next summer, Delaney called for an immediate regime change.
The former Crystal Palace defender, who earned nine caps for Ireland, said that the time has come to “start the process” of a managerial change and that McCarthy should be replaced by Kenny ahead of the next round of games in March.
Ireland were spirited, aggressive and committed in the match against Denmark, and produced possibly their best performance of the qualification campaign.
However, despite Matt Doherty’s equaliser late in the game, they largely struggled to create goal-scoring chances.
Delaney said Ireland’s performance against Denmark was the best one could expect from Ireland under the current coach.
“I think Mick’s got as much out as he’s going to get out of the players with the way we’re going about it,” he said on Off The Ball.
“Okay, it was a decent performance but it wasn’t fantastic. We lacked a little bit of quality but we’ve been saying that for how long now?
“Look, I don’t think you can ask any more of Mick McCarthy. He did what he said he was going to do. He got us there. We were within five minutes of clinching a winner and getting us there. I think he’s done all he can do if I’m being honest with you.”
Delaney went on to say that Ireland must “move away” from the direct style of play McCarthy and previous managers have adopted as it is “just not good enough.” The former Cork City defender said the gap with other sides is “only going to keep getting bigger.”
“I like Mick I really do,” he continued.
“I think he’s a fantastic fella and all that but we’ve tried this way and we’ve been trying it for a long time and yeah we’ve had a little bit of success with it.
“But let’s start the process now. Let’s just go, man.”


We're an interactive design and developement studio focusing on building content for cartoons. We understand how much work goes into cartoons to make them as life-live as possble, and we strive to bring that same principle to our products. When someone views the website, app, or even a web banner for your cartoon - they can expect the same lively experience.


The object of this game is to guide the moust cursor throught the start area and get to the end area. Be sure to avoid the walls:
Good luck!


If you are interested in contributing to the overall data mesh community and/or Data Mesh Learning, welcome! The easiest/best way to contribute is probably just being active in the Slack community, connecting people to resources and being helpful. There are many other ways you could contribute so if you have an idea, we would love to hear it, email us or message Scott Hirleman in the Slack community. That said, there are some things we've come up with below:
Community promotion: generally, just telling people about the community. If you find value from it and want others to experience the same, tell them! :D The easiest way to sign up is to send them here: https://launchpass.com/data-mesh-learning
Content review (prior to publishing): we want to offer people creating content (user stories, blog posts, presentations, videos, etc.) a chance for others to review and give feedback before publishing. If you want to volunteer to review content before it gets published, please sign up using this Google Form. Contact information provided will only be used for the purpose of content review.
Content classification: we are attempting to build a repository of data mesh and data mesh tangential content. Thus far, it is quite, quite early days... Not experts on data classification and management over here so some friendly guidance on how to handle would be great. The plan is for an information resource AND a relatively easy way to find good links to put into newly created content. Links like that are good for informational purposes but also help drive up SEO and trust rankings.
Slack community management: Once we've seen you in action in the Slack channel, we are happy to share the load of managing the data mesh community. We don't believe communities should be controlled by a single person and we want to be able to bring many people in who share the same goals of collaboration and communication and a committment to be excellent to each other.
Website management: this "website" in it's current form is a bit of a hot mess, based off a single great tutorial on GitHub Pages. No really, it was great, it just isn't really for what this morphed into. So, as the community picks up steam, it is likely to get moved to a formal website with a WordPress system and everything. If you want to be part of that, it would be greatly, greatly appreciated ;)
Other ideas? as we said, let us know in Slack or via email.


Ray: 0.2 Release
We are pleased to announce the Ray 0.2 release. This release includes the following:
- substantial performance improvements to the Plasma object store
- an initial Jupyter notebook based web UI
- the start of a scalable reinforcement learning library
- fault tolerance for actors
Plasma
Since the last release, the Plasma object store has moved out of the Ray codebase and is now being developed as part of Apache Arrow (see the relevant documentation), so that it can be used as a standalone component by other projects to leverage high-performance shared memory. In addition, our Arrow-based serialization libraries have been moved into pyarrow (see the relevant documentation).
In 0.2, we’ve increased the write throughput of the object store to around 15GB/s for large objects (when writing from a single client). Achieving this performance requires enabling huge pages (to minimize the number of TLB cache misses). Instructions for doing so are here.
The speed at which objects can be written into the object store is a key performance metric. For example, it is the bottleneck for A3C and many other algorithms.
You can benchmark write throughput as follows.
import numpy as np
import ray
ray.init()
x = np.ones(10 ** 9, dtype=np.uint8)
# Measure the time required to write 1GB to the Plasma store.
%time x_id = ray.put(x)
Web UI
We’ve built an initial Jupyter-notebook-based web UI for understanding and debugging application performance. See the instructions for using the UI. The UI includes a task timeline visualization based on Chrome tracing to see where tasks were scheduled, how long they took, and what the dependencies between the tasks were. An example visualization is shown below.
This type of visualization can immediately expose problems with performance, scheduling, and load balancing.
The above visualization can be generated on a single machine by the following script.
import ray
import time
ray.init()
@ray.remote
def f(x):
time.sleep(0.001)
return 1
@ray.remote
def g(*ys):
return 1
time.sleep(1)
x = 1
for _ in range(3):
ys = [f.remote(x) for _ in range(8)]
x = g.remote(*ys)
RLlib
We’ve begun implementing a scalable reinforcement learning library based on Ray. So far it includes implementations of the following algorithms.
- Proximal policy optimization (PPO)
- Deep Q-learning (DQN)
- Asynchronous advantage actor critic (A3C)
- Evolution Strategies (ES)
The DQN, A3C, and ES implementations are based on the OpenAI baselines. Example code for training is available and can be used as follows.
# On a single machine.
python ray/python/ray/rllib/train.py --alg=PPO \
--env=CartPole-v0
# On a cluster.
python ray/python/ray/rllib/train.py --alg=PPO \
--env=CartPole-v0 \
--redis-address=<head-node-ip>:6379
This uses proximal policy optimization to train a policy to control an agent in the CartPole environment.
Running this (on the Humanoid-v1 environment to train a walking humanoid robot) on AWS with a cluster of fifteen m4.16xlarge instances and one p2.16xlarge instance, we achieve a reward of over 6000 in around 35 minutes. The rollouts are parallelized over 512 physical cores and the policy optimization is parallelized over 6 GPUs. Relevant hyperparameters for this experiment are here.
This RL library is under development, and we are looking for contributions including implementations of more algorithms.
Actor fault tolerance
We’ve enabled fault tolerance for actors as follows. If a machine fails, the actors that were running on that machine are recreated on other machines, and the tasks that previously executed on those actors are replayed to recreate the state of the actor. We are working on improving the speed of recovery by enabling actor state to be restored from checkpoints. See an overview of fault tolerance in Ray.


| lesson 30 The death of a ghost |
| For years, villagers believed that Endley Farm was hunted. |
| The farm was owned by two brothers, Joe and Bob Cox. |
| They employed a few farmhands, but no one was willing to work there long. |
| Every time a worker gave up his job, he told the same story. |
| Farm labourers said that they always woke up to find that work had been done overnight. |
| Hay had been cut and cowsheds had been cleaned. |
| A farm worker, who stayed up all night claimed to have seen a figure cutting corn in the moonlight. |
| In time, it became an accepted fact that the Cox brothers employed a conscientious ghost that did most of their work for them. |
| No one suspected that there might be someone else on the farm who had never been seen. |
| This was indeed the case. |
| A short time ago, villagers were astonished to learn that the ghost of Endley had died. |
| Everyone went to the funeral, for the 'ghost' was none other than Eric Cox, a third brother who was supposed to have died as a young man. |
| After the funeral, Joe and Bob revealed a secret which they had kept for over fifty years. |
| Eric had been the eldest son of the family, very much older than his two brothers. |
| He had been obliged to join the army during the Second World War. |
| As he hated army life, he decided to desert his regiment. |
| When he learnt that he would be sent abroad, he returned to the farm and his father hid him until the end of the war. |
| Fearing the authorities, Eric remained in hiding after the war as well. |
| His father told everybody that Eric had been killed in action. |
| The only other people who knew the secret were Joe and Bob. |
| They did not even tell their wives. |
| When their father died, they thought it their duty to keep Eric in hiding. |
| All these years, Eric had lived as a recluse. |
| He used to sleep during the day and work at night, quite unaware of the fact that he had become the ghost of Endley. |
| When he died, however, his brothers found it impossible to keep the secret any longer. |


Points In Circle:
?
Total Points Plotted:
?
Aggregated data 📊
The circle's area is
?
of the square.
?
· (2r)² =
π
· r²
?
· 2² · r² =
π
· r²
π
=
?
· 4
π =
?


|
ERF Variable |
Description |
|
rm_npth |
Reliability margins that are used in DRA calculations For more details regarding reliability margins and DRA
calculations see See
DRA / RM |
|
rm_pth |
|
|
rm_via |
|
|
rm_pad_pth |
|
|
rm_pad_smd |
|
|
rm_sm |
|
|
rm_rout |
|
|
max_line_width |
Maximum line width of lines in line
category |
|
min_line_len |
Minimum line length of lines in line
category, also minimum overlap between lines to report in parallel spacing |
|
len2width_ratio |
Minimum ratio of len to width of a line to be inserted into
the line category |
|
v_report_include_ |
When 0, the distance between the soldermask
clearance that is included inside a silkscreen element is reported as its
real distance in the SM
Clearance category. When 1, the distance segment between the
soldermask clearance that is included inside a silkscreen element becomes a
zero length distance segment, and is therefore reported in the
red severity level of the SM Clearance category. |
|
v_report_arcs_ |
This variable controls in what category arcs and shaved
arcs are reported. No
= arcs are reported in the new ss_arc category. Shaved arcs are reported
in the new ss_shaved_arc
category. Yes
= arcs are reported in the ss_line category with lines reports. Shaved arcs
are reported in the ss_shaved
line category along with shaved lines reports. Note: The
Arcs and Shaved Arcs reports are subject to line reports limitations:
max_line_width, min_line_len, len2width_ratio. |
|
v_check_only_ |
This variable enables you to define what drill holes to
check. Yes
(the default value) = the action checks only exposed drill holes. No
= all drill holes are checked. |
|
v_report_include_ |
This variable enables you to define how to report Silk
Screen elements which are fully included inside drill or rout features. No
(the default value) = the action reports the measured distance. Yes
= the distance will be reported as zero length distance that
will touch the SS element. |


Fitness Tracker
Workout Name:
Create New Workout First
Exercise Name:
Number of Reps:
Add New Exercise Second with Reps


CodePipeline CustomActionType Settings
Settings
is a property of the AWS::CodePipeline::CustomActionType resource that provides URLs
that users can access to view information about the CodePipeline custom action.
Syntax
JSON
{ "EntityUrlTemplate" :
String
, "ExecutionUrlTemplate" :String
, "RevisionUrlTemplate" :String
, "ThirdPartyConfigurationUrl" :String
}
YAML
EntityUrlTemplate:
String
ExecutionUrlTemplate:String
RevisionUrlTemplate:String
ThirdPartyConfigurationUrl:String
Properties
EntityUrlTemplate
-
The URL that is returned to the CodePipeline console that links to the resources of the external system, such as the configuration page for an CodeDeploy deployment group.
Required: No
Type: String
ExecutionUrlTemplate
-
The URL that is returned to the CodePipeline console that links to the top-level landing page for the external system, such as the console page for CodeDeploy.
Required: No
Type: String
RevisionUrlTemplate
-
The URL that is returned to the CodePipeline console that links to the page where customers can update or change the configuration of the external action.
Required: No
Type: String
ThirdPartyConfigurationUrl
-
The URL of a sign-up page where users can sign up for an external service and specify the initial configurations for the service's action.
Required: No
Type: String


MATRIX is an MPC Test Automation Framework developed by
Bar Ilan University Cryptography Research Group.
It automates the tedious process of deploying, running, monitoring and summarizing results.
In order to login use the button above.


How to stay healthy in winter season: Dr Himanshu Chaudhary
by Nagpur Today, Nagpur NewsAs the lovely Cozy season of the year is coming, time to enjoy the indoor activities, hot soups and dishes, gossips sitting near the bonfire and the healthiest season to improve health.
So staying healthy during the winter season is the first step to ensure that you can enjoy your winter, and here are some tips to follow in this season –
1. Dry skin – very common in winter because of low humidity
Keep moisturizing your skin
2. Avoid hot water bath to avoid dry and itchy skin
3. Do not consume chilled out cold water to avoid respiratory ailments
4- Keep yourself covered enough to Avoid cold exposure and cold related medical conditions
4. Stay active – as the weather is Cozy, it demands for more activeness than the normal to keep your metabolism active and fit and to gain excess of weight
5- eat healthy food which require some spices and herbs that keep your metabolism active as well warm
6- keep yourself stress free- keeping self stress free will help you to fight day to day infection, as the stress level makers you more susceptible to catch infections like cold and Flu
7. Drink the optimal amount of water. With the winter season here, it’s more important than ever to consume the right amount of water for your health.
Preferably a glad of Luke warm water in early morning and once at bed time.
8. Get the right amount of sleep every night – The average person needs 6-8 hours of sleep per night. If you’re not getting enough sleep, your body is extremely vulnerable to illness.
9. Eat essential nutrients and oils or supplements that are required to fulfill the body demands to continue functioning and winters and maintain your body temperature and BMR.
10. Wash your hands frequently to avoid infections.
By Dr Himanshu Chaudhary


Classes
Members
(private) black
- Source:
black
Function that returns black queen
- Source:
canAttack
Function that checks if both queens can attack themselves
- Source:
white
Function that returns white queen
- Source:
Methods
toString() → {String}
Function that returns string of the current board
- Source:
Returns:
string of board with those separators
- Type
- String