- getConnection() - Static method in class model.DatabaseConnection
-
- getDate() - Method in class model.SlideEvent
-
- getEventBorderPane() - Method in class view.Layout
-
Gets the event from the database and adds them to a grid.
- getEventOverview() - Method in class view.Layout
-
The event overview shows all the events and enables you to insert them into your presentation
- getHeader() - Method in class model.SlideEvent
-
- getHeader() - Method in class model.SlideHappyHour
-
- getImagePath() - Method in class model.Slide
-
- getImagePath() - Method in class model.SlideEvent
-
- getImagePath() - Method in class model.SlideHappyHour
-
- getImagePath() - Method in class model.SlidePicture
-
- getImageView() - Method in class model.TabNodeEvent
-
- getImageView() - Method in class model.TabNodeHappyHour
-
- getLocalDate() - Method in class model.SlideEvent
-
- getMenuBar() - Method in class view.Layout
-
Is called at program launch and initializes the MenuBar.
- getNewTabPane() - Method in class controller.TabController
-
- getNode() - Method in interface model.TabNode
-
- getNode() - Method in class model.TabNodeEvent
-
- getNode() - Method in class model.TabNodeHappyHour
-
- getNode() - Method in class model.TabNodePicture
-
- getPassphrase() - Method in class model.PortForwardingL.MyUserInfo
-
- getPassword() - Method in class model.PortForwardingL.MyUserInfo
-
- getPresentationDates() - Static method in class model.DatabaseSaveAndGet
-
Used for colour coding dates in the DatePicker.
- getRootLayout() - Method in class view.Layout
-
Builds the BorderPane that the main window of the program runs on.
- getSession() - Static method in class model.PortForwardingL
-
- getSlide() - Method in interface model.TabNode
-
- getSlide() - Method in class model.TabNodeEvent
-
- getSlide() - Method in class model.TabNodeHappyHour
-
- getSlide() - Method in class model.TabNodePicture
-
- getSlideType() - Method in class model.Slide
-
- getStartTime() - Method in class model.SlideEvent
-
- getTabCollectionSize() - Method in class controller.TabController
-
Is used for checking whether there is anything to save, if this method returns zero.
- getTabPane() - Method in class controller.TabController
-
- getText() - Method in class model.SlideEvent
-
- getText() - Method in class model.SlideHappyHour
-


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|
SSD1306 OLED display driver
1.8.2
This library is developed to control SSD1306/SSD1331/SSD1351/IL9163/PCD8554 RGB i2c/spi LED displays
|
LCD direct draw functions only for color display. More...
Functions | |
| void | ssd1306_setColor (uint16_t color) |
| Sets default color, generated by RGB_COLOR8 or RGB_COLOR16 macros. More... | |
| void | ssd1306_setRgbColor (uint8_t r, uint8_t g, uint8_t b) |
| Sets default color. More... | |
| void | ssd1306_setRgbColor8 (uint8_t r, uint8_t g, uint8_t b) |
| Sets default color. More... | |
| void | ssd1306_drawMonoBuffer8 (lcdint_t xpos, lcdint_t ypos, lcduint_t w, lcduint_t h, const uint8_t *bitmap) |
| void | ssd1306_drawBufferFast8 (lcdint_t x, lcdint_t y, lcduint_t w, lcduint_t h, const uint8_t *data) |
| void | ssd1306_drawBufferEx8 (lcdint_t x, lcdint_t y, lcduint_t w, lcduint_t h, lcduint_t pitch, const uint8_t *data) |
| void | ssd1306_fillScreen8 (uint8_t fill_Data) |
| void | ssd1306_clearScreen8 (void) |
| void | ssd1306_putPixel8 (lcdint_t x, lcdint_t y) |
| void | ssd1306_putColorPixel8 (lcdint_t x, lcdint_t y, uint8_t color) |
| void | ssd1306_drawVLine8 (lcdint_t x1, lcdint_t y1, lcdint_t y2) |
| void | ssd1306_drawHLine8 (lcdint_t x1, lcdint_t y1, lcdint_t x2) |
| void | ssd1306_drawLine8 (lcdint_t x1, lcdint_t y1, lcdint_t x2, lcdint_t y2) |
| void | ssd1306_drawRect8 (lcdint_t x1, lcdint_t y1, lcdint_t x2, lcdint_t y2) |
| void | ssd1306_fillRect8 (lcdint_t x1, lcdint_t y1, lcdint_t x2, lcdint_t y2) |
| void | ssd1306_drawMonoBitmap8 (lcdint_t xpos, lcdint_t ypos, lcduint_t w, lcduint_t h, const uint8_t *bitmap) |
| void | ssd1306_drawBitmap8 (lcdint_t xpos, lcdint_t ypos, lcduint_t w, lcduint_t h, const uint8_t *bitmap) |
| void | ssd1306_clearBlock8 (uint8_t x, uint8_t y, uint8_t w, uint8_t h) |
| void | ssd1306_setCursor8 (lcduint_t x, lcduint_t y) |
| void | ssd1306_printChar8 (uint8_t c) |
| size_t | ssd1306_write8 (uint8_t ch) |
| Prints single character to display at current cursor position. More... | |
| size_t | ssd1306_print8 (const char ch[]) |
| Prints null-terminated string to display at current cursor position. More... | |
| uint8_t | ssd1306_printFixed8 (lcdint_t x, lcdint_t y, const char *ch, EFontStyle style) |
LCD direct draw functions only for color display.
LCD direct draw functions are applicable for color display types. These functions will NOT work in ssd1306 compatible mode. Use ssd1306_setMode() function to change display mode to NORMAL. You can combine combine NanoEngine capabilities with these functions. Direct draw functions draw directly in GDRAM and do not use any double-buffering.
| void ssd1306_clearBlock8 | ( | uint8_t | x, |
| uint8_t | y, | ||
| uint8_t | w, | ||
| uint8_t | h | ||
| ) |
Clears block, filling it with black pixels, directly in OLED display GDRAM.
| x | start horizontal position in pixels |
| y | start vertical position in pixels |
| w | block width in pixels |
| h | block height in pixels |
Definition at line 281 of file ssd1306_8bit.c.
| void ssd1306_clearScreen8 | ( | void | ) |
Fills screen with zero-byte
Definition at line 127 of file ssd1306_8bit.c.
| void ssd1306_drawBitmap8 | ( | lcdint_t | xpos, |
| lcdint_t | ypos, | ||
| lcduint_t | w, | ||
| lcduint_t | h, | ||
| const uint8_t * | bitmap | ||
| ) |
Draw 8-bit color bitmap, located in Flash, directly to OLED display GDRAM. Each pixel of the bitmap is expected in 3-3-2 format.
| xpos | start horizontal position in pixels |
| ypos | start vertical position in pixels |
| w | bitmap width in pixels |
| h | bitmap height in pixels |
| bitmap | pointer to Flash data, containing 8-bit color bitmap. |
Definition at line 269 of file ssd1306_8bit.c.
| void ssd1306_drawBufferEx8 | ( | lcdint_t | x, |
| lcdint_t | y, | ||
| lcduint_t | w, | ||
| lcduint_t | h, | ||
| lcduint_t | pitch, | ||
| const uint8_t * | data | ||
| ) |
Draws 8-bit bitmap, located in SRAM, on the display, taking into account pitch parameter. Each byte represents separate pixel: refer to RGB_COLOR8 to understand RGB scheme, being used. pitch parameter specifies, length of single line in bytes.
| x | - horizontal position in pixels |
| y | - vertical position in pixels |
| w | - width of bitmap in pixels |
| h | - height of bitmap in pixels |
| pitch | length of bitmap buffer line in bytes |
| data | - pointer to data, located in SRAM. |
Definition at line 111 of file ssd1306_8bit.c.
| void ssd1306_drawBufferFast8 | ( | lcdint_t | x, |
| lcdint_t | y, | ||
| lcduint_t | w, | ||
| lcduint_t | h, | ||
| const uint8_t * | data | ||
| ) |
Draws 8-bit bitmap, located in SRAM, on the display Each byte represents separate pixel: refer to RGB_COLOR8 to understand RGB scheme, being used.
| x | - horizontal position in pixels |
| y | - vertical position in pixels |
| w | - width of bitmap in pixels |
| h | - height of bitmap in pixels |
| data | - pointer to data, located in SRAM. |
Definition at line 106 of file ssd1306_8bit.c.
Draw horizontal line directly in OLED display GDRAM.
| x1 | - left position in pixels |
| y1 | - vertical vertical position in pixels |
| x2 | - right position in pixels |
Definition at line 157 of file ssd1306_8bit.c.
Draw line directly in OLED display GDRAM. This is software implementation. Some OLED controllers have hardware implementation. Refer to datasheet.
| x1 | - start horizontal position in pixels |
| y1 | - start vertical position in pixels |
| x2 | - end horizontal position in pixels |
| y2 | - end vertical position in pixels |
Definition at line 168 of file ssd1306_8bit.c.
| void ssd1306_drawMonoBitmap8 | ( | lcdint_t | xpos, |
| lcdint_t | ypos, | ||
| lcduint_t | w, | ||
| lcduint_t | h, | ||
| const uint8_t * | bitmap | ||
| ) |
Draw monochrome bitmap, located in Flash, directly to OLED display GDRAM. The bitmap should be in ssd1306 format (each byte represents 8 vertical pixels)
| xpos | start horizontal position in pixels |
| ypos | start vertical position in pixels |
| w | bitmap width in pixels |
| h | bitmap height in pixels |
| bitmap | pointer to Flash data, containing monochrome bitmap. |
Definition at line 238 of file ssd1306_8bit.c.
| void ssd1306_drawMonoBuffer8 | ( | lcdint_t | xpos, |
| lcdint_t | ypos, | ||
| lcduint_t | w, | ||
| lcduint_t | h, | ||
| const uint8_t * | bitmap | ||
| ) |
Draws 1-bit bitmap, located in SRAM, on the display Each bit represents separate pixel: refer to ssd1306 datasheet for more information.
| xpos | horizontal position in pixels |
| ypos | vertical position in pixels |
| w | width of bitmap in pixels |
| h | height of bitmap in pixels |
| bitmap | pointer to data, located in SRAM. |
Definition at line 59 of file ssd1306_8bit.c.
Draw rectangle directly in OLED display GDRAM. This is software implementation. Some OLED controllers have hardware implementation. Refer to datasheet.
| x1 | - start horizontal position in pixels |
| y1 | - start vertical position in pixels |
| x2 | - end horizontal position in pixels |
| y2 | - end vertical position in pixels |
Definition at line 211 of file ssd1306_8bit.c.
Draw vertical line directly in OLED display GDRAM.
| x1 | - horizontal position in pixels |
| y1 | - top vertical position in pixels |
| y2 | - bottom vertical position in pixels |
Definition at line 146 of file ssd1306_8bit.c.
Fill rectangle directly in OLED display GDRAM. This is software implementation. Some OLED controllers have hardware implementation. Refer to datasheet.
| x1 | - start horizontal position in pixels |
| y1 | - start vertical position in pixels |
| x2 | - end horizontal position in pixels |
| y2 | - end vertical position in pixels |
Definition at line 219 of file ssd1306_8bit.c.
| void ssd1306_fillScreen8 | ( | uint8_t | fill_Data | ) |
Fills screen with pattern byte
| fill_Data | pattern color to fill screen with |
Definition at line 116 of file ssd1306_8bit.c.
| size_t ssd1306_print8 | ( | const char | ch[] | ) |
Prints null-terminated string to display at current cursor position.
Prints null-terminated string to display at current cursor position Cursor position can be set by ssd1306_setCursor8().
| ch | - string to print to the display. 'LF' and 'CR' are skipped |
Definition at line 360 of file ssd1306_8bit.c.
| void ssd1306_printChar8 | ( | uint8_t | c | ) |
Draws single character to canvas. Cursor position is defined by ssd1306_setCursor8(). Do not changes cursor position
| c | - character code to print |
Definition at line 298 of file ssd1306_8bit.c.
| uint8_t ssd1306_printFixed8 | ( | lcdint_t | x, |
| lcdint_t | y, | ||
| const char * | ch, | ||
| EFontStyle | style | ||
| ) |
Prints text to screen using fixed font.
| x | horizontal position in pixels |
| y | vertical position in pixels |
| ch | NULL-terminated string to print |
| style | font style (EFontStyle), normal by default (not implemented). |
Definition at line 371 of file ssd1306_8bit.c.
Puts single color point directly in OLED display GDRAM.
| x | - horizontal position in pixels |
| y | - vertical position in pixels |
| color | color in RGB8 format (2-3-2) |
Definition at line 139 of file ssd1306_8bit.c.
Puts single color point directly in OLED display GDRAM.
| x | - horizontal position in pixels |
| y | - vertical position in pixels |
Definition at line 132 of file ssd1306_8bit.c.
| void ssd1306_setColor | ( | uint16_t | color | ) |
Sets default color, generated by RGB_COLOR8 or RGB_COLOR16 macros.
Sets color generated by RGB_COLOR8 or RGB_COLOR16 macros.
| color | - new color to use for monochrome-specific operations on color display. |
Definition at line 44 of file ssd1306_8bit.c.
Set cursor position for text functions
| x | horizontal position in pixels. |
| y | vertical position in pixels. |
Definition at line 292 of file ssd1306_8bit.c.
| void ssd1306_setRgbColor | ( | uint8_t | r, |
| uint8_t | g, | ||
| uint8_t | b | ||
| ) |
Sets default color.
Sets default color for monochrome operations. For now this function supports only 8-bit RGB mode. To work with RGB colors in 16-bit mode, please refer to ssd1306_setColor() function and RGB_COLOR16 macros.
| r | - red in 0-255 range. |
| g | - green in 0-255 range. |
| b | - blue in 0-255 range. |
Definition at line 49 of file ssd1306_8bit.c.
| void ssd1306_setRgbColor8 | ( | uint8_t | r, |
| uint8_t | g, | ||
| uint8_t | b | ||
| ) |
Sets default color.
Sets default color for monochrome operations. For now this function supports only 8-bit RGB mode. To work with RGB colors in 16-bit mode, please refer to ssd1306_setColor() function and RGB_COLOR16 macros.
| r | - red in 0-255 range. |
| g | - green in 0-255 range. |
| b | - blue in 0-255 range. |
Definition at line 54 of file ssd1306_8bit.c.
| size_t ssd1306_write8 | ( | uint8_t | ch | ) |
Prints single character to display at current cursor position.
Prints single character to display at current cursor position. Cursor position can be set by ssd1306_setCursor8().
| ch | - character to print to the display. 'LF' and 'CR' are skipped |
Definition at line 311 of file ssd1306_8bit.c.


About
Contact
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🇹🇷
Muhammed Enes Karaca
Software Engineer, Researcher
I love working on software.
Contact
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| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final int |
NEW_NODE_ENDPOINT_FIELD_NUMBER |
2 |
public static final int |
NODE_ENDPOINTS_FIELD_NUMBER |
1 |
| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final int |
LEADER_HINT_FIELD_NUMBER |
2 |
public static final int |
STATUS_FIELD_NUMBER |
1 |
| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final int |
NEW_SERVER_FIELD_NUMBER |
1 |
| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final int |
RPC_MESSAGE_ID_FIELD_NUMBER |
1 |
public static final int |
SUCCESS_FIELD_NUMBER |
3 |
public static final int |
TERM_FIELD_NUMBER |
2 |
| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final int |
ENTRIES_FIELD_NUMBER |
7 |
public static final int |
LEADER_COMMIT_FIELD_NUMBER |
6 |
public static final int |
LEADER_ID_FIELD_NUMBER |
3 |
public static final int |
MESSAGE_ID_FIELD_NUMBER |
1 |
public static final int |
PREV_LOG_INDEX_FIELD_NUMBER |
4 |
public static final int |
PREV_LOG_TERM_FIELD_NUMBER |
5 |
public static final int |
TERM_FIELD_NUMBER |
2 |
| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final int |
COMMAND_FIELD_NUMBER |
4 |
public static final int |
INDEX_FIELD_NUMBER |
2 |
public static final int |
KIND_FIELD_NUMBER |
1 |
public static final int |
TERM_FIELD_NUMBER |
3 |
| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final int |
TERM_FIELD_NUMBER |
1 |
| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final int |
DATA_FIELD_NUMBER |
7 |
public static final int |
DONE_FIELD_NUMBER |
8 |
public static final int |
LAST_CONFIG_FIELD_NUMBER |
5 |
public static final int |
LAST_INDEX_FIELD_NUMBER |
3 |
public static final int |
LAST_TERM_FIELD_NUMBER |
4 |
public static final int |
LEADER_ID_FIELD_NUMBER |
2 |
public static final int |
OFFSET_FIELD_NUMBER |
6 |
public static final int |
TERM_FIELD_NUMBER |
1 |
| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final int |
HOST_FIELD_NUMBER |
2 |
public static final int |
ID_FIELD_NUMBER |
1 |
public static final int |
PORT_FIELD_NUMBER |
3 |
| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final int |
NODE_ENDPOINTS_FIELD_NUMBER |
1 |
public static final int |
NODE_TO_REMOVE_FIELD_NUMBER |
2 |
| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final int |
LEADER_HINT_FIELD_NUMBER |
2 |
public static final int |
STATUS_FIELD_NUMBER |
1 |
| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final int |
OLD_SERVER_FIELD_NUMBER |
1 |
| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final int |
TERM_FIELD_NUMBER |
1 |
public static final int |
VOTE_GRANTED_FIELD_NUMBER |
2 |
| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final int |
CANDIDATE_ID_FIELD_NUMBER |
2 |
public static final int |
LAST_LOG_INDEX_FIELD_NUMBER |
3 |
public static final int |
LAST_LOG_TERM_FIELD_NUMBER |
4 |
public static final int |
TERM_FIELD_NUMBER |
1 |
| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final int |
LAST_CONFIG_FIELD_NUMBER |
3 |
public static final int |
LAST_INDEX_FIELD_NUMBER |
1 |
public static final int |
LAST_TERM_FIELD_NUMBER |
2 |
| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final int |
ALL_ENTRIES |
-1 |
| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final int |
KIND_ADD_NODE |
3 |
public static final int |
KIND_GENERAL |
1 |
public static final int |
KIND_NO_OP |
0 |
public static final int |
KIND_REMOVE_NODE |
4 |
| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final int |
VOTES_COUNT_NOT_SET |
-1 |
| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final java.lang.String |
FILE_NAME |
"node.bin" |
| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final int |
MSG_TYPE_APPEND_ENTRIES_RESULT |
4 |
public static final int |
MSG_TYPE_APPEND_ENTRIES_RPC |
3 |
public static final int |
MSG_TYPE_INSTALL_SNAPSHOT_PRC |
5 |
public static final int |
MSG_TYPE_INSTALL_SNAPSHOT_RESULT |
6 |
public static final int |
MSG_TYPE_NODE_ID |
0 |
public static final int |
MSG_TYPE_REQUEST_VOTE_RESULT |
2 |
public static final int |
MSG_TYPE_REQUEST_VOTE_RPC |
1 |


Jeremiah 9:14
But have walked after the imagination of their own heart, and after Baalim, which their fathers taught them:


Please pick your Server to continue...
Whisperwind Karazhan Lightbringer Northshire Valley Daggerspine


Disclaimer: This is not a feminist manifesto, recitals of struggles and complaints, our “version” of story or a matrimony portal. Just making sure you are not on the wrong (web)page. :p
So, as you might all know, (some of you out of experience and some out of the memes that circulate)
the girl boy ratio in an IIT on an average is, unfortunately, still 1:10. The reasons for this are deep rooted in our society and bound by shackles of our education system, so I would rather not go there. But, I would go to this skewed ratio, and the persistent skewness it brings along.
I have never found the memes regarding girls in engineering funny.
I have never understood the stereotypes that are associated with a girl if she can talk Python and Java. I have never felt more judged when I am told
“How difficult can it be, there are ten boys for you to choose from”. Excuse me, I didn’t know I was shopping for furniture.
I have met some of the most remarkable, brilliant, resilient and beautiful women here, while studying in an IIT with them. As I talked to more and more of them, I realised how each one of us bring uniqueness to the melange, but also how similar we are on the grounds that unify us. While we have been privileged, to be surrounded by progressive people who respect our personalities and give us a fair platform to compete, I realise not all girls out there are as privileged as us. We still fight that underlying current of gender stereotypes, which mistake me not, strikes us only once in a while, but it does strike us.
This one here, it’s just a light hearted account to capture our essence and stories. The theories we have, our loses (
you lose all your fashion sense when the species around you wears the same t-shirt for over a week), our struggles (
proxying in an 8AM class which has only one girl and that is you), our talents (
we know when you have bathed in water and when in deodrant), our dreams and aspirations (
well, I am gonna do it, stop me if you can).
The thing I learned from taking these interviews is it's easy to get people talk about giving their opinions on a product you built or you would have them to use. It takes a lot to get them to open them about themselves, about their lives. To kindle he conversations, I gave them a few words as sparks and full liberty to light it up. Though leading, these words were not binding.
This project, which started just as a class assignment, became so close to my heart in no time. You can find bits and pieces of me when you click on every thumbnail. For every person I interviewed, they presented to me a kaleidoscope of their life to me. It was shimmering and colorful. I hope to make this an ongoing project in my free time. Here is just a sneak peak for you.
-
Chhavi :)


I'm a web developer currently living in the Nashville Metro area. I specialize in developing responsive web applications using mobile-first design principles. I've been doing some freelance work, but I would really like to find a full-time web development position. If you're looking to hire, then please contact me!
• Visit my GitHub page to view some of my former and current projects.
• Find me on LinkedIn!
University of North Alabama
• Studied Computer Science and completed 4 years of college coursework.
Mars Hill Bible School
• Received High School Diploma
CompTIA A+ certification
CompTIA Security+ certification
Microsoft Technology Associate in Networking Fundamentals
HTML & HTML5
CSS & CSS3
PHP
MySQL
JavaScript & jQuery
Apache Web Server (Linux)
Adobe Photoshop
Adobe Illustrator
Search Engine Optimization (SEO)
Git Version Control (GitHub)
Bootstrap Framework
iOS Development
Freelance Web Design
Dates Employed: 11/2014 - Present
• I utilized open-source tools to hand code all of my web projects.
• I developed all of my web projects using mobile-first design principles.
Dell Services Federal Government - Help Desk Technician
Dates Employed: 11/2014 - 03/2015
• I worked as a contractor on the Army Enterprise Service Desk.
• I provided over-the-phone IT support to US Army personnel.
Forsythe & Long Engineering – IT Department
Dates Employed: 12/2013 - 05/2014
• I was responsible for upkeep and maintenance of all employee PCs.
• I worked in a primarily Windows desktop environment.
TNT Fireworks – Credit Card Department
Dates Employed: 05/2013 - 08/2013
• I assisted stand operators with their credit card machines over the phone.
• I audited the accounts of several stand operators.
Mars Hill Bible School - Maintenance Department
Dates Employed: 05/2008 - 08/2011
• I provided regular maintenance and repair on the school building and grounds.
• I also assisted the Director of Technology with various IT-related tasks.
Copyright © Clay Boren 2015


| ZDUMP(8) | System Manager's Manual | ZDUMP(8) |
Dates are in yyyy-mm-dd format and times are in 24-hour hh:mm:ss format where hh<24. Times are in local time immediately after the transition. A time interval description consists of a UT offset in signed ±hhmmss format, a time zone abbreviation, and an isdst flag. An abbreviation that equals the UT offset is omitted; other abbreviations are double-quoted strings unless they consist of one or more alphabetic characters. An isdst flag is omitted for standard time, and otherwise is a decimal integer that is unsigned and positive (typically 1) for daylight saving time and negative for unknown.
In times and in UT offsets with absolute value less than 100 hours, the seconds are omitted if they are zero, and the minutes are also omitted if they are also zero. Positive UT offsets are east of Greenwich. The UT offset -00 denotes a UT placeholder in areas where the actual offset is unspecified; by convention, this occurs when the UT offset is zero and the time zone abbreviation begins with “-” or is “zzz”.
In double-quoted strings, escape sequences represent unusual characters. The escape sequences are \s for space, and \", \\, \f, \n, \r, \t, and \v with their usual meaning in the C programming language. E.g., the double-quoted string “"CET\s\"\\"” represents the character sequence “CET "\”.
Here is an example of the output, with the leading empty line omitted. (This example is shown with tab stops set far enough apart so that the tabbed columns line up.)
Here, local time begins 10 hours, 31 minutes and 26 seconds west of UT, and is a standard time abbreviated LMT. Immediately after the first transition, the date is 1896-01-13 and the time is 12:01:26, and the following time interval is 10.5 hours west of UT, a standard time abbreviated HST. Immediately after the second transition, the date is 1933-04-30 and the time is 03:00:00 and the following time interval is 9.5 hours west of UT, is abbreviated HDT, and is daylight saving time. Immediately after the last transition the date is 1947-06-08 and the time is 02:30:00, and the following time interval is 10 hours west of UT, a standard time abbreviated HST.
TZ="Pacific/Honolulu" - - -103126 LMT 1896-01-13 12:01:26 -1030 HST 1933-04-30 03 -0930 HDT 1 1933-05-21 11 -1030 HST 1942-02-09 03 -0930 HWT 1 1945-08-14 13:30 -0930 HPT 1 1945-09-30 01 -1030 HST 1947-06-08 02:30 -10 HST
Here are excerpts from another example:
This time zone is east of UT, so its UT offsets are positive. Also, many of its time zone abbreviations are omitted since they duplicate the text of the UT offset.
TZ="Europe/Astrakhan" - - +031212 LMT 1924-04-30 23:47:48 +03 1930-06-21 01 +04 1981-04-01 01 +05 1 1981-09-30 23 +04 ... 2014-10-26 01 +03 2016-03-27 03 +04
In the -v and -V output, “UT” denotes the value returned by gmtime(3), which uses UTC for modern timestamps and some other UT flavor for timestamps that predate the introduction of UTC. No attempt is currently made to have the output use “UTC” for newer and “UT” for older timestamps, partly because the exact date of the introduction of UTC is problematic.


Documentation
This is an experimental version of Documentation.
It is integrated directly
into source code file system tree and should consist mainly of readme.htm files.
Introduction
Project structure
Blocks and controls
Tutorials
Creating blocks
Team guidelines
Our coding guidelines
Our documentation guidelines


|
RedWolfEngine 0.4.0
C++20 library for creating console and GUI applications.
|
Class for handling a single file. More...
#include <File.hpp>
Public Types | |
| enum class | Format { bin , bmp , cab , dll , exe , ini , jpg , msi , png , sh , txt , xml , zip , unknown } |
| Different file formats for I/O operations. | |
Public Member Functions | |
| File (std::string_view filePath, Format format=Format::unknown) | |
| Constructor. More... | |
| std::string | extension () const |
| Extract the extension of the file. More... | |
| Format | format () const |
| Get the file format. | |
| std::string | readAll () const |
| Read all file contents and store them in a string. More... | |
| template<typename T > | |
| T | readAllBinary () const |
| Read all file contents as binary data and cast them to a given object type. More... | |
Static Public Attributes | |
| static constexpr rw::cont::ConstexprMap< std::string_view, Format, 32U > | extension_map |
| Map for associating file extensions with their corresponding formats. More... | |
| static constexpr char | extension_separator { '.' } |
Class for handling a single file.
| rw::io::File::File | ( | std::string_view | filePath, |
| Format | format = Format::unknown |
||
| ) |
Constructor.
| filePath | Path to the file. |
| format | Format of the file. If unknown, the class will try to deduce it from the file extension. |
| std::string rw::io::File::extension | ( | ) | const |
Extract the extension of the file.
| std::string rw::io::File::readAll | ( | ) | const |
Read all file contents and store them in a string.
|
inline |
Read all file contents as binary data and cast them to a given object type.
| T | Data type to read. |
|
staticconstexpr |
Map for associating file extensions with their corresponding formats.
|
staticconstexpr |
Separator character for determining the file extension.


Every story has a beginning. This one is no different. My story begins in my early childhood, when I got my first Nintendo Entertainment System (NES) console. To be completely frank, though it was not the original NES overhyped in those shoddy TV commercials (an image of a perfect American family, mom and dad, two kids, both ecstatically gaming on a NES disconnected from the TV set). It was a genuine (pun intended) Famiclone resembling the Batmobile.
I opened it up a few years later and noticed how shabby the wiring had been. Surprising it even worked! Nevertheless, I was excited to had gotten it for my birthday as a toddler. It came with 2 pads, a knock-off NES zapper and one of those infamous 128-in-1 cartridges (10-20 unique games, repeated as hacked varieties). Today that doesn't sound like much, but back then it was paradise. My favourites were Yi Er Kung Fu and Duck Hunt. I didn't like Super Mario Bros as much, because I sucked at it. I know, embarrassing... Anyway, I spent entire days gaming on my Famiclone and in time acrued several cool gaming titles, like Darkwing Duck, Duck Tales 1 & 2, Ghost Busters 2, and Tom and Jerry. Then, things changed a bit and my adventures with personal computers (PCs) finally began...
My father is a retired electronics engineer and a hobbyist tinkerer. Incidentally, he is extremely deft at assembling PCs. The first computer I ever owned was built from scratch by him. Thinking about it today makes me incredibly proud of him, but also quite jealous! He had the opportunity to grow up along the very first personal computers and gaming consoles, like Atari 2600 or Commodore 64 (not to mention the Silicon Graphics SGI workstations and SPARC servers from Sun Microsystems...). My first computer was a Pentium I P5 (P54C of the 80502 architecture, to be exact). It was clocked at 100 MHz and had 32 MB RAM on the motherboard, as far as I remember. I write was, but I think my parents still keep it somewhere in the basement. The PC sported the amazing for its time Matrox 3D graphics card and the Sound Blaster Pro sound card. On this beast of a machine I played titles such as Electro Body, The Incredible Machine, Commander Keen, Cosmo's Cosmic Adventures and other great games from the DOS era. Apogee used to make fantastic platformers for the DOS and I remember many of them very fondly. Good old Windows 3.11 also sported some relaxing office games.
Alas, no hardware lasts forever, especially when it's maintained by a curious and adventurous teenager. It so happened that I accidentally overclocked my graphics card and literally burnt it to a crisp. This is no joke. Nowadays, graphics drivers have a lot of safety mechanisms baked in. Any attempts at changing the suggested clock speed are met with a huge red warning button with a label that says at your own risk. Back then configuring sound and graphics was a bit of an ordeal and one could easily mess things up. Zero hand-holding whatsoever. Since the graphics card had to be replaced anyway, we upgraded the machine with extra RAM and installed Windows 98 on it. It is arguably the second best operating system from Microsoft - a joy to work with and a joy to game on. Absolutely seminal in user-friendly OS design. I received my next computer much much later, when in high school. It was a real powerhouse, though. The pinnacle of its generation, in fact. Pentium IV (with hyper-threading), 2 GB RAM and a GeForce 2 MX graphics card (later upgraded to GeForce 7100). The operating system was Windows XP. Windows 98 was great, but it had its limitations.  The best GUI-centric operating system ever. It was so good that many companies still have support contracts with Microsoft (extended-post-end-of-life-something-something). The later Windows 7 came close, but was not able to repeat that success. For unexplainable reasons since then Microsoft was not able to produce anything equally usable. I really don't want to be harsh, but everything after Windows 7 was a complete disaster from a UX and feature set standpoint. Anyway, my Pentium IV PC still stands at my parents' place, in my former bedroom.
Fast-forward a couple of years. Pentium IV and 2 GB RAM are not strong enough anymore. For my university work I need something faster. My parents decided it's time for a laptop. They bought me one of those consumer multimedia laptops with a discrete nVidia graphics card (GeForce 520 MX). It came with a one-time gift of free bloatware. Horrible practice, really. I wish laptop vendors would stop polluting their products with trial licenses of software no one actually ever uses. Once I learned the ins and outs of my OS (it required 2 clean installations and several DVDs to get things running properly), it finally struck me – I was not happy with it at all. Windows 7 was not for me. It was packed with countless features I would never use, and I could not disable without potentially breaking the system. Each consecutive update added more bloat, seizing more and more memory. I managed to stop it at 1.5-2 out of 4 GB, though I couldn’t go lower. Surprisingly, a fresh install of Windows 7 64-bit used only around 500-700 MB RAM. Not so much according to current standards. However, I was still a bit unhappy. I needed something to change. Windows 8 was obviously out of the question with its godawful desktop environment. Windows 10 was on the horizon, but previews showed a bizarre combination of Windows 7’s functionality with an improved Windows 8 UI environment. Unfortunately, neither was quite my cup of tea...
The reflection was painful yet refreshing – I had to take a different route, a brave step into the unknown. Into Linux...


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Attacking EVM Resource Metering (2019-02-19)
Transcript By: Bryan Bishop
Category: Conference
Broken Metre: Attacking resource metering in EVM
Daniel Perez, Benjamin Livshits
https://twitter.com/kanzure/status/1230222221110468609
https://arxiv.org/abs/1909.07220
Abstract
Metering is an approach developed to assign cost to smart contract execution in blockchain systems such as Ethereum. This paper presents a detailed investigation of the metering approach based on gas taken by the Ethereum blockchain. We discover a number of discrepancies in the metering model such as significant inconsistencies in the pricing of the instructions. We further demonstrate that there is very little correlation between the gas and resources such as CPU and memory. We find that the main reason for this is that the gas price is dominated by the amount of storage that is used.
Based on the observations above, we present a new type of DoS attack we call Resource Exhaustion Attack, which uses these imperfections to generate low-throughput contracts. Using this method, we show that we are able to generate contracts with a throughput on average 50 times slower than typical contracts. These contracts can be used to prevent nodes with lower hardware capacity from participating in the network, thereby artificially reducing the level of decentralization the network can deliver.
Introduction
I have been working on this paper with my supervisor, Benjamin Livshits, about Broken Metre: attacking resource metering in the ethereum VM. It talks about gas and how to attack this on ethereum. This paper will also be presented next week.
Background
First some quick background. I think most people here will be familiar with smart contracts, but I will go through this anyway so that we’re all on the same page to continue to the paper.
There’s a lifecycle to a smart contract. It’s a program running on the blockchain. For Ethereum, these contracts are usually written in a high-level language called Solidity which can be converted into bytecode which are sequences of instructions. In Ethereum, there’s a stack-based VM which executes the instructions. These contracts get deployed to ethereum through transactions. Once the contract has an address, users can send a transaction to this contract. It can run, execute, call other contracts in ethereum, do pretty much anything. That’s pretty much how smart contracts work on ethereum at least.
Gas metering
One more important thing here is that this will be run on every single node on the network. So we can’t run programs forever or have any infinite loops since this would completely open up many attacks on the network, so as a result ethereum has a concept of gas which is a way to compute how computationally intensive a program is.
Each instruction uses a certain amount of gas, which was originally specified in the yellow paper, but was hard-forked a few times to be modified. When you want to compute the cost of a program, a whole smart contract, then there’s a base cost and then there’s a cost of each instruction in this program. Something important here is that each transaction has a gas budget. As soon as this gas budget is reached and the smart contract goes over it, it will stop with an out-of-gas exception and this prevents infinite loops and other issues like that.
The transaction sender also needs to pay a fee for executing this transaction on the network. This gas cost is multiplied by the gas price which is how much the sender is willing to pay for a single unit of this gas, and this multiplication is a transaction fee. The more computationally intensive the contract, the higher the cost of the contract.
Arithmetic instructions are very low cost. As soon as we touch input/output or state or the disk, then it becomes fairly expensive. EXTCODESIZE used to see how big the code of a contract is, this actually requires access storage usually, and so therefore it’s much more expensive. The most expensive thing is usually storing something on the blockchain since this is replicated on every single node and it’s something expensive. It’s 20,000 which is orders of magnitude more than these other operations.
Previous attacks on metering
Up to here, all good. But it’s obviously very hard to get this pricing right. If the pricing is not right, then it means it’s possible to perform denial of service attacks- by creating contracts that are very slow but not particularly expensive to execute. This has happened a few times in the past. Both of these attacks were from 2016 if I remember correctly.
One of the attacks was based on EXTCODESIZE which is very IO intensive. An attacker can spam this operation and he could generate very slow contracts for a very slow cost. To fix this, they simply increased the cost of the operation which is much closer now to how computationally intensive this operation is.
There was a similar attack a bit later, called the SUICIDE attack. This was based on the SUICIDE operation. It was an instruction whose purpose is to remove smart contracts from a blockchain. All the money that was on the contract is then sent to whatever address is specified by the instruction. At the time of the attack, it was free to execute to incentivize people to free up storage if they aren’t using it anymore. If they would send this money to a non-existing address, then this address gets created for free. So given these two things, it was very cheap for an attacker to create a slow contract using this method. As a result, SUICIDE price was changed to 5000 and creating a contract now consumes gas.
There have been a few more attacks, but I think these were the most important ones for attacks on the gas mechanism. In our paper, we wanted to check if this was perfectly fixed or if there are other attack vectors. We can still find some contracts which are very slow and still fairly cheap to execute.
Empirical analysis
So we tried to analyze transactions on ethereum, and look at price, gas, and contracts, and try to get some insights on those. What we did for this is we first forked aleth (C++ client) and we instrumente the CPU to measure instruction execution time and aggregate this information over 1,00 instructions. We also instrumented memory so that we can see how much memory gets allocated and freed when contracts execute, and how that correlates to gas price. We also replayed transactions and then analyzed some of the statistics and metrics.
Arithmetic instructions
First we started by looking at arithmetic instructions which we thought would be fairly predictable. But we found that even for something simple like arithmetic like adding or exponentiating, we found a lot of variance. Multiplication and division both with the same cost in gas, have an order of 5x times difference in terms of speed. It’s 5x faster to multiply than to divide. Even worse for exponential, which is about on average 10x more expensive than division and it’s still almost twice faster. For these arithmetic instructions themselves, there’s a throughput measured in gas per microsecond here.
Gas and resource correlation
So next we wanted to look at gas price and resource allocation like how much storage is used, or CPU execution time, etc. Given the pricing I showed before, we were expecting that it would be mostly correlated with storage since this is what’s most expensive operationally in terms of gas. But we are also hoping that if we added memory, and CPU, to these correlations then maybe we could get more correlated so that all the different resources that a node uses are included in this pricing.
What we saw is that when we added the allocation of memory, like corresponding to log operations, or anyhting that the ethereum node needs to be keeping in memory… this correlation increases quite a bit. There’s a fairly good correlation once including memory, like post EIP-150. The main correlation though was CPU. It decreases the correlation. Adding CPU decreases the correlation with gas.
High-variance instructions
We figured this is happening because of high-variance instructions where the instructions are sometimes fast to execute and sometimes slow to execute. When we looked at this, we found that operations that use IO and reading state are often having a very high variance. EXTCODESIZE has a standard deviation is higher than the man in terms of operation time in milliseconds.
Effect of cache on execution time
The next thing we wanted to look at is that given this high variance, we’re expecting the main reason for the variation is the caching or whether it’s in the cache which wouldn’t be reflected in pricing. When we looked at the effect of caching, we saw that on average—… we focused on the OS page cache, we generated random programs and measured speed with and without cache, we found that the programs are about 28x times faster with cache which is fairly important given that the gas price wouldn’t change.
Analysis summary
With gas cost, we saw many inconsistencies. IO operations have very high variance in execution time. Cache has a very important effect on speed. Overall, cannot model IO operations on pricing.
Attacking EVM metering: Resource exhaustion attacks
So we thought, maybe we could attack this and create cache misses and things like that. We had a goal of finding programs which minimize throughput (gas per second). Our search space is the set of all the possible valid program on ethereum. We had a function or metric to optimize, which was minimizing throughput. We also didn’t want programs to be too big, because it has to be able to be included in a transaction and get into an ethereum block.
Obviously this search space is big and we can’t look at everything, so we looked at a genetic algorithm to approximate a solution and find slow contracts.
Generated programs using genetic algorithm
All the details are in the paper. Generally speaking, a few things that we cared about is that first we only generate valid programs so that we don’t further increase the search space. For each instruction, there needs to be enough elements on the stack to be executed. There must not be any stack overflows, and we can only access “reasonable” memory locations. So these are a few constraints we had on generating programs so that each program generated would fulfill these conditions.
Since it’s a genetic algorithm, we also need mutation and cross-over, and we made sure that this would only produce valid programs. We also took a shortcut with generated programs, we specified that they must not have any loops or conditional jumps because it wouldn’t make any difference for throughput and makes program generation logic much simpler.
Initial program construction
Another important point here is the initializer values for the initial program construction. Since we have a large search space, if we want to converge in a reasonable amount of time, we need a reasonable program to start with. The good thing is that we had plenty of data from our previous measurements. So we basically got the average throughput per instruction, so the idea is to randomly sample and take an instruction to include it into the initial program and we would assign a higher probability to instructions which were already slow, and we assign a lower probability to each instruction that is quite fast- so we don’t completely ignore fast instructions, but we still try to get an initial program which is relatively slow and start with something that is easier to optimize for our algorithm.
Genetic algorithm results
At initial program throughput we already had an average of 3 million gas/second. The average on the same exact machine was 20 million gas/second when we were playing the transactions. So we already have a 6-7x slower initial program, before running the optimization. So that made it clear that our initialization strategy is acceptable.
In this graph, you can see the performance decreases reasonably, but then it levels out after around generation 200 where we plateau at 100,000 gas/second. To see how bad this is, it’s basically 200x slower than the average contract which would be running on the same exact machine. This is a really, really high number.
Evaluation on different clients
We had been running all of this on our forked C++ client, so the next thing we wanted to look at was how does this behave on other clients. Is this still very slow it is just a problem inherent to our forked C++ client? In our results, we found that all the clients were vulnerable. Aleth, parity and geth were all slow. Parity bare metal was about 2x faster than parity.
Given that in ethereum a block is produced once every 30 seconds, well this is way too slow because these contracts were taking more than 18 seconds. We tested this on the cloud with a large computer with dozens of cores and an ssd hard drive. We also tested with a bare metal server and a faster ssd, and even there it took 18 seconds which is still too slow for this node to be able to keep up with the network if this attack were to be performed.
We talked with Ethereum Foundation and the gas developers, and right now the current version on mainnet which has been fixed, is now much faster and now it takes only 3 seconds or so to execute the exact same contracts. So on the current network this is mostly fixed.
DoS potential
What about the potential for these contracts to be used for denial of service attacks? Slow nodes won’t be able to keep up with the network, and this will result in decreased throughput and a longer time for block production. We have seen selfish mining behaviors in ethereum, because they can prevent other miners from starting at the same time, and this is financially viable for the attacker. There can be parties hostile to ethereum that want to attack the blockchain.
The thing is that this is cheap to perform. It would cost only $0.70 to keep commodity hardware node out-of-sync for 1 block (with 2 million gas/block). The problem is that we don’t know which nodes are running what hardware, so we don’t know how many nodes are going to be effected. So it looks like this would be pretty bad for the network.
Responsible disclosure
We disclosed this to Ethereum Foundation in October 2019. We talked with them and helped them figure out how to fix this. Thanks to Matthas Egli and Hubert Ritzdorf from PwC Switzerland. Ethereum Foundation confirmed our reward in November.
Improving metering
Let me talk about short-term and long-term fixes. For short-term fixes, it’s two-fold. The main goal is to improve throughput of IO operations. The cost and speed of the operation… one thing is to increase the cost, which has been done in a few proposals before, and another one is making IO operations more expensive, and another one is to reduce number of required IO accesses.
In the long-term, there’s the idea of making stateless clients where the client do not need to keep track of all the state. The necessary data would be sent with the transaction. Alternatively, sharding isn’t a direct solution but it does require less state per node.
Sponsorship: These transcripts are sponsored by Blockchain Commons.
Disclaimer: These are unpaid transcriptions, performed in real-time and in-person during the actual source presentation. Due to personal time constraints they are usually not reviewed against the source material once published. Errors are possible. If the original author/speaker or anyone else finds errors of substance, please email me at<EMAIL_ADDRESS>for corrections or contribute online via github/git. I sometimes add annotations to the transcription text. These will always be denoted by a standard editor’s note in parenthesis brackets ((like this)), or in a numbered footnote. I welcome feedback and discussion of these as well.
Tweet: Transcript: “Broken Metre: Attacking resource metering in EVM” https://diyhpl.us/wiki/transcripts/stanford-blockchain-conference/2020/attacking-evm-resource-metering/ @danhper @convoluted_code @CBRStanford #SBC20


About Luxury Shop
_____________________________________________________________________________________
The Luxury Shop is a new buisness created by Ben Nanadze. The goal of the shop is to get more people in the world to wear watches and to take more interest in this beautiful luxury world. The shop is not done yet we will upgrade more and more and add more watches. The watches we are showing for now are the world top brands.
For calls or buisness offers:
Phone -<PHONE_NUMBER>
Email - benchuk2004@gmail.com


Here is an example stub for PHP build script:
<?php
/**
* @file
* An example PHP hook file.
*/
namespace AKlump\WebPackage;
if ($little_problem) {
throw new \AKlump\WebPackage\HookException("Hook failed, but the build must go on.");
}
elseif ($big_problem) {
throw new \AKlump\WebPackage\BuildFailException("Stop the build!");
}
echo "The hook worked as expected";
AKlump\WebPackage
.echo
or print
to write to the screen.caution
and danger
to write dramatic output while continuing the flow.$build
objectYou may want to leverage the $build
instance in your PHP hook files as it contains a growing amount of common use case functionality. Refer to \AKlump\WebPackage\HookService for more info.
displayMessages()
as the last chained method (see example below).Add configuration to $build
inside of bootstrap.php, which will apply to every PHP hook file thereafter, e.g.,
<?php
/**
* @file
* Loaded before running PHP hooks.
*/
$build->setDistributionDir('dist');
Then inside your hook file do something with it, e.g.,
<?php
/**
* @file
* Load a source file, replace tokens and save to dist folder.
*/
namespace AKlump\WebPackage;
$build
->loadFile('src/smart-images.js')
->replaceTokens()
->saveToDist()
->displayMessages();
$build
Methods| HookService ||---| | addFilesToScm (array $files) | | addMessage ($message) | | addToDemo ($path, $to_relative_path = NULL) | | addTokens (array $additional_token_map = Array) | | boostrapPhpUnit () | | caution ($message) | | danger ($message) | | displayMessages () | | endMessageClause () | | generateDemoTo ($path_to_generated_demo = 'dist/demo') | | generateDocumentation ($path_to_generated_docs = 'docs') | | generateDocumentationTo ($path_to_generated_docs = 'docs') | | getSourceCode () | | isUsingGit () | | loadFile ($filepath, callable or NULL $mutator = NULL) | | minifyFile ($source) | | prepareTokenMap ($prefix, array $additional_token_map = Array) | | processWithTwig (array $additional_token_map = Array) | | publish () | | relativize (string $path) | | replaceTokens (array $additional_token_map = Array) | | resolve ($filepath) | | runTests (string $path_to_testrunner) | | saveReplacingSourceFile () | | saveTo (string $dir = 'dist', $force = false) | | saveToDist () | | setBashExecutable (string $program_name, string $path_to_executable) | | setDemoSource ($source_dir) | | setDistributionDir (string $dist) | | setDocumentationSource ($source_dir) | | setPhp (string $php) | | setPhpUnit (string $phpunit) | | setSourceCode (string $code) | | startMessageClause ($message) |
These are deprecated, you should only use them as a last resort.
| data | build.php |
|---|---|
| prev version | $argv[1] |
| new version | $argv[2] |
| package name | $argv[3] |
| description | $argv[4] |
| homepage | $argv[5] |
| author | $argv[6] |
| path to root | $argv[7] |
| date/time | $argv[8] |
| path to info file | $argv[9] |
| dir of the script | $argv[10] |
| dir of functions.php/.sh | $argv[11] |
| root dir of web_package | $argv[12] |
| path to hooks dir | $argv[13] |


University at Buffalo | Computer Science BS
Future Software Engineer
I was born and raised in New York City. I am currently a junior at University at Buffalo pursuing a Computer Science career. I strive to build robust programs, design clean user interface, and learn new technologies. Being a Software Engineer, I believe that leveraging technology is the best way to create societal impact.
网站和系统开发建设
网站服务器的提供者
提高搜索引擎的好感度
云平台和云服务建设
云平台和云服务建设


00 Boiler plate
In this sample we are going to setup the basic plumbing to "build" our project and launch it in a dev server.
Highlights
The most interesting parts worth to take a look
-
package.json: check packages installed.
-
webpack.config.js: check the build process and ts-loader to handle typescript.
-
tsd.json: typescript definitions.
-
src: javascript using imports.


---
layout: default
---
About Me
I am a motivated developer who can learn new technologies really fast and am always motivated to learn more. I practice good standards when it comes to my code and create clean and maintainable code. I also am an avid Linux power user and have been for years and am able to debug my way out of issues swiftly.
My Skills
{{ post.content | strip_html | truncatewords:20 }}


Ummm, Oh Ya Sooo... What do you think about my Pens .... You Like Them ???


Resolving Merge Conflicts in Git

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Lesson Goals

In this lesson we will demonstrate how to create and resolve a merge conflict.

Introduction

When working collaboratively, sometimes we tend to step on each other's toes. What this means is that sometimes we and other developers happen to edit the same code at the same time. While we might try to keep our changes isolated with branching, this does not prevent editing the same lines of code by two different people.

It is crucial that we learn how to resolve these conflicts as simply as possible. This is because the thing that scares away developers from Git the most is merge conflicts. We would like you to have strong Git Fu so we think you should tackle this problem head on. Let's start by setting up a merge conflict and then resolving it.

Creating a Merge Conflict

In order to create a merge conflict, we will create a Python file in PyCharm, create a new branch and change the code in the file. We will then change the code in the main branch and then proceed to merge the new branch with the main branch.

Adding a file to the repo

We open PyCharm and open the data-labs folder.

In our data-labs repo, we will add a python file to this current module (module 1) and name the file git-fu.py. We right click the module-1 folder and select Python file.

When PyCharm prompts you to add the file to Git, make sure to choose yes. You can also add it manually by typing this in the terminal:

git add .

We will add one line of code to the file for the sake of simplicity. The file contains only this line of code:

print("this is the original message")

Now we commit and push the repository using the following commands:

$ git commit -am "adding git-fu file"
[conflict fdbdb3c] adding git-fu file
1 file changed, 24 insertions(+), 1 deletion(-)
$ git push
Enumerating objects: 18, done.
Counting objects: 100% (17/17), done.
Delta compression using up to 8 threads.
Compressing objects: 100% (10/10), done.
Writing objects: 100% (12/12), 31.53 KiB | 10.51 MiB/s, done.
Total 12 (delta 3), reused 0 (delta 0)
remote: Resolving deltas: 100% (3/3), completed with 2 local objects.
To https://github.com/ironhack/data-labs.git
7f7f613..8b37c4f master -> master

Now we will create a new branch and switch to this branch. We do this using the following command:

$ git checkout -b conflict-branch

We can also create a new branch in the git menu on the bottom right in PyCharm.

In the conflict branch we now alter the line of code in the git-fu.py file to this:

print("this is the altered message")

We now commit and push this change:

$ git commit -am "altering git-fu file"
[conflict 775ed66] altering git-fu file
2 files changed, 35 insertions(+), 3 deletions(-)
$ git push --set-upstream origin conflict-branch
Enumerating objects: 11, done.
Counting objects: 100% (11/11), done.
Delta compression using up to 8 threads.
Compressing objects: 100% (5/5), done.
Writing objects: 100% (6/6), 1.08 KiB | 1.08 MiB/s, done.
Total 6 (delta 2), reused 0 (delta 0)
remote: Resolving deltas: 100% (2/2), completed with 2 local objects.
To https://github.com/ironhack/data-labs.git
* [new branch] conflict-branch -> conflict-branch
Branch 'conflict-branch' set up to track remote branch 'conflict-branch' from 'origin'.

Merging the Branches

Now that we have set up the conflict, let's resolve it.

We start by navigating to the master branch and merge the conflict branch into the master branch.

$ git checkout master
$ git merge conflict-branch

Now we go back to the master branch and change the text again and commit and push it.

The idea behind doing this is that the original text was determined in the master branch initially. In order to create a conflict, we must make sure both branches diverged from the original text.

We alter the text to:

print("this is the master message")

We then commit and push this change to the master branch.

Now we head back to the terminal and type:

$ git merge conflict-branch
Auto-merging module-1/git-fu.py
CONFLICT (content): Merge conflict in module-1/git-fu.py
Automatic merge failed; fix conflicts and then commit the result.

Oh no! Our merge failed. Git wants us to fix this. We can head back to PyCharm and find that our git-fu.py file now looks like this:

You will also notice that our master branch is now called master|MERGING.

In order to fix the conflict, we need to select the code we want to keep and erase the conflict boundaries.

In this case, we want to keep the code in the master branch and so what we are left with is this:

We now commit the merged change. We should commit using an informative message and then push our code again.

$ git commit -am "resolving merge conflict"
[master f360c5e] resolving merge conflict
$ git push
Enumerating objects: 14, done.
Counting objects: 100% (14/14), done.
Delta compression using up to 8 threads.
Compressing objects: 100% (6/6), done.
Writing objects: 100% (8/8), 721 bytes | 721.00 KiB/s, done.
Total 8 (delta 4), reused 0 (delta 0)
remote: Resolving deltas: 100% (4/4), completed with 3 local objects.
To https://github.com/ironhack/data-labs.git
8b37c4f..f360c5e master -> master

Now the conflict is resolved and the branches are merged.

Aborting the Merge

Perhaps you did not realize there was a conflict. Now there are hundreds of lines of code that you have to resolve. Maybe it would be better to use a different strategy. If you'd like to abort the merge, first we can check the status:

$ git status
On branch master
Your branch is up to date with 'origin/master'.
You have unmerged paths.
(fix conflicts and run "git commit")
(use "git merge --abort" to abort the merge)

The git status command gives you the correct command to abort the merge. Now we will type it to go back to the pre-merged state

$ git merge --abort

As you can see, the branch name changed back from master|MERGING to master, so everything is back to normal.

Resolving the Conflict Using Ours and Theirs

Instead of resolving the conflict line by line, we can making a sweeping decision to accept a file from our branch as is (so from the master branch) or from their branch as is.
To do this, we use the commands ours and theirs.

In this example, before merging, we would navigate to the master branch. If we wanted to keep the master branch's version of git-fu.py we would type the following command before merging:

$ git checkout --ours -- ./module-1/git-fu.py

Conflicts with Pull Requests

Pull requests are essentially a request to merge to branches on GitHub.

We first push both branches and then create the pull request through the UI.

As we can see in the screen shot above, the pull request will not automatically merge after approval. We still go ahead with creating the request, but we will have to resolve the conflicts after the request is created.

After creating the request, we see the screen below. We click the Resolve conflicts button.

After clicking this button, we get taken to a UI that is very similar to what we see in PyCharm.

We resolve the conflict in the same way we resolved the conflict in PyCharm. The end result should be only the line of code that we want to keep. At this point, we are able to click the Resolve conflict button.

At this point, we go back to the main pull request page and see that the pull request is ready to merge.

We are now able to safely merge the pull request

Conclusion

In this lesson we learned how to resolve pull requests. We learned how to resolve them line by line and also force resolve them using ours or theirs. We also learned how to abort merges. Finally, we learned about resolving conflicts in pull requests on GitHub. Hopefully, you have reached a high level of Git Fu.


Siamese Networks are feature extractors trained to learn an embedding in \(\mathbb{R}^n\) where not the absolute output is important, but the relative one.
The original paper1 was about signature verification. You have one original signature and one that might be the same or might be a different one. Instead of having one output that directly says "same" or "different", they decided to have one network that maps the input to \(\mathbb{R}^{4 \times 19}\) and then use euclidean distance with some threshold2.
Today, the nicest usage I know is DeepFace3. It is a neural network which maps faces to \(\mathbb{R}^{128}\) by combining a lot of clever ideas.
Key Idea
You have one network \(m_1\) which is embedded into another network which combines two inputs of \(m_1\). So for training a triplet \((d_1, d_2, t)\) is used, where \(d_1\) and \(d_2\) are both processed individually by \(m_1\). The two outputs \(d_{1}'\) and \(d_{2}'\) are then combined by another network \(m_2\). \(m_2\) can simply be a merging layer. The loss is then calculated based on the output of \(m_2\).
Applications
- Signature Verification: Given two signatures, do they belong to the same person?
- Face Verification: Given two faces, are they the same person?
- Koch, G., Zemel, R., & Salakhutdinov, R. (2015, July). Siamese neural networks for one-shot image recognition. In ICML deep learning workshop (Vol. 2).
- Leal-Taixé, L., Canton-Ferrer, C., & Schindler, K. (2016). Learning by tracking: Siamese CNN for robust target association. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops (pp. 33-40).
Application: Landmark Distances
Think of autonomous cars. They might know some landmarks and be able to identify them. Then they can measure the distance to those landmarks. And maybe some landmarks are added later. I wondered how well a neural network does in finding coordinates for landmarks, given distances to existing landmarks.
While this problem is better solved with another approach, I was just curious how well a simple neural network would do. The answer was ... underwhelming. I guess I made an error, but at the moment I can't find it:
#!/usr/bin/env python
"""
Train a neural network on distances and see how well it figures out coordinates.
Roughly siamese networks.
The "reference points" are landmarks
"""
# core modules
from itertools import combinations
from functools import partial
# 3rd party modules
import keras.backend as K
from keras.layers import Dense
from keras.layers import Input, Concatenate
from keras.models import Model
from sklearn.metrics.pairwise import euclidean_distances
import numpy as np
from scipy.spatial.distance import euclidean
from sklearn.model_selection import train_test_split
np.random.seed(0)
def main():
import doctest
doctest.testmod()
# Configure Problem
n_reference_points = 11
n_points = n_reference_points + 30
n_dim = 10
# Define Network for mapping distances to landmarks to point coordinates
nn = create_network(n_reference_points, n_dim)
# Make the network trainable
dists1_in = Input(shape=(n_reference_points,))
dists2_in = Input(shape=(n_reference_points,))
point1_out = nn(dists1_in)
point2_out = nn(dists2_in)
merged_vector = Concatenate(axis=-1)([point1_out, point2_out])
model = Model(inputs=[dists1_in, dists2_in], outputs=merged_vector)
model.compile(loss=partial(dual_loss, n_dim=n_dim), optimizer="adam")
# Generate Data
points = generate_data(n_points=n_points, n_dim=n_dim)
print(points[:n_reference_points])
distances = get_distances(points, n_reference_points)
train_points, test_points, train_distances, test_distances = train_test_split(
points, distances
)
distances_p1s, distances_p2s, pair_distances = get_train_data(
train_points, train_distances
)
model.fit(
[distances_p1s, distances_p2s], pair_distances, batch_size=128, epochs=100
)
predicted_points = nn.predict(test_distances)
error = measure_error(test_points, predicted_points)
print("Error: {:0.3f}".format(error))
error = measure_error(test_points, generate_random(predicted_points.shape))
print("Error (random): {:0.3f}".format(error))
def generate_data(n_points, n_dim):
"""
Generate n_points of dimension n_dim.
Examples
--------
>>> generate_data(1, 2).tolist()
[[0.5488135039273248, 0.7151893663724195]]
"""
points = np.random.random((n_points, n_dim))
return points
def generate_random(shape):
"""Generate a random point coordinate prediction."""
return np.random.random(shape)
def get_distances(points, n_reference_points):
"""
Get the distance of points to the n reference points.
This includes the pair-wise distance between the reference points.
"""
ref_points = points[:n_reference_points]
distances = []
for point in points:
distances.append([])
for ref_point in ref_points:
distances[-1].append(euclidean(point, ref_point))
return np.array(distances)
def create_network(n_reference_points, n_dim):
input_ = Input(shape=(n_reference_points,))
x = input_
x = Dense(200, activation="relu")(x)
x = Dense(200, activation="relu")(x)
x = Dense(n_dim, activation="sigmoid")(x)
model = Model(inputs=input_, outputs=x)
return model
def dual_loss(y_true, y_pred, n_dim=2):
"""
Define the loss function based on two points.
Parameters
----------
y_true : ndarray
The real distance
y_pred : ndarray
The first n_dim elements are the first points coordinates,
the seoncd n_dim elements are the second points coordinates
"""
point1 = y_pred[:, 0:n_dim]
point2 = y_pred[:, n_dim:]
# distance between the points
embedding_dist = K.sum(K.square(point1 - point2), axis=1)
# compute loss
loss = K.abs(embedding_dist - y_true)
return loss
def get_train_data(points, distances):
"""
Create training data.
Parameters
----------
points : List
Returns
-------
(distances_p1, distances_p2, pair_distances) : tuple
distances_p1 and distances_p2 have the same structure (point 1 and
point 2) The contens of those two lists are the distances to the
reference points
pair_distances : The i-th entry contains the distance between
distance_pairs[i][0] and distance_pairs[i][1]
"""
distances_p1 = []
distances_p2 = []
pair_distances = []
for pi1, pi2 in combinations(list(range(len(points))), 2):
p1_dist = distances[pi1]
p2_dist = distances[pi2]
distances_p1.append(p1_dist)
distances_p2.append(p2_dist)
pair_distances.append(euclidean(points[pi1], points[pi2]))
return np.array(distances_p1), np.array(distances_p2), np.array(pair_distances)
def measure_error(real_points, predicted_points):
"""
Measure an error between the real points and the predicted points.
This does not punish the points being shifted / rotated.
"""
real_distances = np.tril(euclidean_distances(real_points), 0).reshape(-1)
pred_point_distances = np.tril(euclidean_distances(predicted_points)).reshape(-1)
diff = sum(((real_distances - pred_point_distances) ** 2) ** 0.5)
return diff / len(real_points)
if __name__ == "__main__":
main()
Footnotes
-
Bromley, Jane, et al. "Signature verification using a" siamese" time delay neural network." Advances in neural information processing systems. 1994. ↩
-
I'm actually not sure which metric they used to calculate the distance between to signature feature matrices. Please ping me if you know more. ↩
-
Taigman, Yaniv, et al. "Deepface: Closing the gap to human-level performance in face verification." Proceedings of the IEEE conference on computer vision and pattern recognition. 2014. (summary) ↩


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This tutorial focuses on the boto interface to AWS’ Simple Email Service (SES). This tutorial assumes that you have boto already downloaded and installed.
The first step in accessing SES is to create a connection to the service. To do so, the most straight forward way is the following:
>>> import boto.ses
>>> conn = boto.ses.connect_to_region(
'us-west-2',
aws_access_key_id='<YOUR_AWS_KEY_ID>',
aws_secret_access_key='<YOUR_AWS_SECRET_KEY>')
>>> conn
SESConnection:email.us-west-2.amazonaws.com
Bear in mind that if you have your credentials in boto config in your home directory, the two keyword arguments in the call above are not needed. More details on configuration can be fond in Boto Config.
The boto.ses.connect_to_region() functions returns a boto.ses.connection.SESConnection instance, which is a the boto API for working with SES.
It is important to keep in mind that while emails appear to come “from” the address that you specify via Reply-To, the sending is done through Amazon. Some clients do pick up on this disparity, and leave a note on emails.
Before you can send email “from” an address, you must prove that you have access to the account. When you send a validation request, an email is sent to the address with a link in it. Clicking on the link validates the address and adds it to your SES account. Here’s how to send the validation email:
>>><EMAIL_ADDRESS>{
'VerifyEmailAddressResponse': {
'ResponseMetadata': {
'RequestId': '4a974fd5-56c2-11e1-ad4c-c1f08c91d554'
}
}
}
After a short amount of time, you’ll find an email with the validation link inside. Click it, and this address may be used to send emails.
If you’d like to list the addresses that are currently verified on your SES account, use list_verified_email_addresses:
>>> conn.list_verified_email_addresses()
{
'ListVerifiedEmailAddressesResponse': {
'ListVerifiedEmailAddressesResult': {
'VerifiedEmailAddresses': [
<EMAIL_ADDRESS><EMAIL_ADDRESS>]
},
'ResponseMetadata': {
'RequestId': '2ab45c18-56c3-11e1-be66-ffd2a4549d70'
}
}
}
In the event that you’d like to remove an email address from your account, use delete_verified_email_address:
>>><EMAIL_ADDRESS>Sending an email is done via send_email:
>>> conn.send_email(
<EMAIL_ADDRESS>'Your subject',
'Body here',
<EMAIL_ADDRESS>{
'SendEmailResponse': {
'ResponseMetadata': {
'RequestId': '4743c2b7-56c3-11e1-bccd-c99bd68002fd'
},
'SendEmailResult': {
'MessageId': '000001357a177192-7b894025-147a-4705-8455-7c880b0c8270-000000'
}
}
}
If you’re wanting to send a multipart MIME email, see the reference for send_raw_email, which is a bit more of a low-level alternative.
Staying within your quota is critical, since the upper limit is a hard cap. Once you have hit your quota, no further email may be sent until enough time elapses to where your 24 hour email count (rolling continuously) is within acceptable ranges. Use get_send_quota:
>>> conn.get_send_quota()
{
'GetSendQuotaResponse': {
'GetSendQuotaResult': {
'Max24HourSend': '100000.0',
'SentLast24Hours': '181.0',
'MaxSendRate': '28.0'
},
'ResponseMetadata': {
'RequestId': u'8a629245-56c4-11e1-9c53-9d5f4d2cc8d3'
}
}
}
In order to fight spammers and ensure quality mail is being sent from SES, Amazon tracks bounces, rejections, and complaints. This is done via get_send_statistics. Please be warned that the output is extremely verbose, to the point where we’ll just show a short excerpt here:
>>> conn.get_send_statistics()
{
'GetSendStatisticsResponse': {
'GetSendStatisticsResult': {
'SendDataPoints': [
{
'Complaints': '0',
'Timestamp': '2012-02-13T05:02:00Z',
'DeliveryAttempts': '8',
'Bounces': '0',
'Rejects': '0'
},
{
'Complaints': '0',
'Timestamp': '2012-02-13T05:17:00Z',
'DeliveryAttempts': '12',
'Bounces': '0',
'Rejects': '0'
}
]
}
}
}


- Experiment - text (String)
type, contains the experiment name
- Normalisation method - text (String)
type, contains the normalisation method, possible terms:
- log transform - text (String) type,
terms: the log text, or
empty
- Normalisation kind - text (String)
type, the normalisation kind (multiplicative or additive) are the possible values
- Variance adjustment - text (String)
type, variance adjustment, possible terms: no adjustment,
by plate and by experiment
- Scoring method - text (String)
type, scoring method, possible terms:
- none
- zscore
- NPI
- zscoreByPlate
- zscoreNonRobust
- zscoreNonRobustByPlate
- Summarise method - text (String)
type, the summarisation method, possible terms:
- Plate - integral (Integer) type, starting from 1, the plate values
- Position - integral (Integer)
type, starting from 1, the position on the plate, A1 is 1, A12 is 12
- Well - text (String) type, the well identifier, format like: A01
- Replicate - integral (Integer)
type, starting from 1 the replicate values
- final well annotation - text (String)
type, this is the well annotation after applying the screen log file; some wells may be flagged; it may be multiple, depending on the parameters, but it can be on its own (in that case it gets a _null suffix)
- well annotation - text (String)
type, this is the original well annotation like sample, pos, neg, other
- Gene id - text (String) type, an identifier of the gene
- Gene symbol - text (String)
type, the gene symbol
- Gene annotation - text (String)
type, additional gene annotations (any other textual column from the input)
- empty - text (String)
type, empty column
- score - floating point number (Double)
type, does not depend on replicates, but depends on parameters these are the scored values
- mean or diff - floating point number (Double)
type, does not depend on replicates, but depends on parameters; when there are two replicates the result is the raw value from the second replicate minus raw value of the first replicate, otherwise the mean of the replicate values
- median - floating point number (Double)
type, does not depend on replicates, but depends on parameters, the median of the raw replicate values
- raw - floating point number (Double)
type, depends both on replicates and parameters. These are the original values
- normalised - floating point number (Double)
type, depends both on replicates and parameters. These are the normalised values
- raw/(plate, replicate mean) - floating
point number (Double) type, depends both on replicates and parameters. These are the raw value divided by the physical plate mean
In this panel you can set the column order and select which one should be present in the output.
There are four special columns, the
- group by channels start
- group by channels end
- group by replicates start
- group by replicates end
These entries allows you to group the results to your need, but you must have both if the specified columns depend on both channels and replicates too, and only the channels if it depends on the channels. You may have more then one channel in the start-end area, but the start-end intervals may not overlap.
You can set which data should have which colour. Currently you have only one choice for each data option.
See also: Visualisation, colours
The proxy settings are important if you are behind a firewall and want to use nodes accessing services outside of your network.


Depending on the unique design, content and configuration of the target system, various capabilities will be enabled. Some of these are:
– Several ways of invoking services are supported: Web–services, REST–services, JMS MDB, EJB, RMI, as well as CORBA.
– JMS based constructs are generated to implement specific Messaging Architectures.
– Configuration is the key. Defaults are provided and may be customized at generation time, and at runtime.
– JPA based data layer implementation is generated along with SQL schema. Custom relationships and queries may be added in the model.
– Generated service and process components will execute within short-term as well as long-term transactions.
—
— persistence, subscription and monitoring is supported
—


In this page there is some interesting content !
And more of it ...
We will replace this by our navigation!


| smooth.construct {mgcv} | R Documentation |
Smooth terms in a GAM formula are turned into smooth specification objects of
class xx.smooth.spec
during processing of the formula. Each of these objects is
converted to a smooth object using an appropriate smooth.construct
function. New smooth classes
can be added by writing a new smooth.construct
method function and a corresponding
Predict.matrix
method function (see example code below).
In practice, smooth.construct
is usually called via smooth.construct2
and the wrapper
function smoothCon
, in order to handle by
variables and
centering constraints (see the smoothCon
documentation if
you need to handle these things directly, for a user defined smooth class).
smooth.construct(object,data,knots) smooth.construct2(object,data,knots)
object |
is a smooth specification object, generated by an
If
|
data |
For |
knots |
an optional data frame or list containing the knots relating to |
There are built in methods for objects with the following classes:
tp.smooth.spec
(thin plate regression splines: see tprs
);
ts.smooth.spec
(thin plate regression splines with shrinkage-to-zero);
cr.smooth.spec
(cubic regression splines: see cubic.regression.spline
;
cs.smooth.spec
(cubic regression splines with shrinkage-to-zero);
cc.smooth.spec
(cyclic cubic regression splines);
ps.smooth.spec
(Eilers and Marx (1986) style P-splines: see p.spline
);
cp.smooth.spec
(cyclic P-splines);
ad.smooth.spec
(adaptive smooths of 1 or 2 variables: see adaptive.smooth
);
re.smooth.spec
(simple random effect terms);
mrf.smooth.spec
(Markov random field smoothers for smoothing over discrete districts);
tensor.smooth.spec
(tensor product smooths).
There is an implicit assumption that the basis only depends on the knots and/or the set of unique covariate combinations; i.e. that the basis is the same whether generated from the full set of covariates, or just the unique combinations of covariates.
Plotting of smooths is handled by plot methods for smooth objects. A default mgcv.smooth
method
is used if there is no more specific method available. Plot methods can be added for specific smooth classes, see
source code for mgcv:::plot.sos.smooth
, mgcv:::plot.random.effect
, mgcv:::plot.mgcv.smooth
for example code.
The input argument object
, assigned a new class to indicate what type of smooth it is and with at least the
following items added:
X |
The model matrix from this term. This may have an |
S |
A list of positive semi-definite penalty matrices that apply to this term. The list will be empty if the term is to be left un-penalized. |
rank |
An array giving the ranks of the penalties. |
null.space.dim |
The dimension of the penalty null space (before centering). |
The following items may be added:
C |
The matrix defining any identifiability constraints on the term, for use when fitting. If this is |
Cp |
An optional matrix supplying alternative identifiability constraints for use when predicting. By default the fitting constrants are used. This option is useful when some sort of simple sparse constraint is required for fitting, but the usual sum-to-zero constraint is required for prediction so that, e.g. the CIs for model components are as narrow as possible. |
no.rescale |
if this is non-NULL then the penalty coefficient matrix of the smooth will not be
rescaled for enhaced numerical stability (rescaling is the default, because |
df |
the degrees of freedom associated with this term (when
unpenalized and unconstrained). If this is null then |
te.ok |
|
plot.me |
Set to |
side.constrain |
Set to |
L |
smooths may depend on fewer ‘underlying’ smoothing parameters than there are elements of
|
Usually the returned object will also include extra information required to define the basis, and used by
Predict.matrix
methods to make predictions using the basis. See
the Details
section for links to the information included for the built in smooth classes.
tensor.smooth
returned objects will additionally have each element of
the margin
list updated in the same way. tensor.smooths
also
have a list, XP
, containing re-parameterization matrices for any 1-D marginal terms
re-parameterized in terms of function values. This list will have NULL
entries for marginal smooths that are not re-parameterized, and is only long
enough to reach the last re-parameterized marginal in the list.
User defined smooth objects should avoid having attributes names
"qrc"
or "nCons"
as these are used internally to provide
constraint free parameterizations.
Simon N. Wood<EMAIL_ADDRESS>Wood, S.N. (2003) Thin plate regression splines. J.R.Statist.Soc.B 65(1):95-114
Wood, S.N. (2006) Low rank scale invariant tensor product smooths for generalized additive mixed models. Biometrics 62(4):1025-1036
The code given in the example is based on the smooths advocated in:
Ruppert, D., M.P. Wand and R.J. Carroll (2003) Semiparametric Regression. Cambridge University Press.
However if you want p-splines, rather than splines with derivative based penalties, then the built in "ps" class is probably a marginally better bet. It's based on
Eilers, P.H.C. and B.D. Marx (1996) Flexible Smoothing with B-splines and Penalties. Statistical Science, 11(2):89-121
http://www.maths.bris.ac.uk/~sw15190/
s
,get.var
, gamm
, gam
,
Predict.matrix
,
smoothCon
, PredictMat
## Adding a penalized truncated power basis class and methods ## as favoured by Ruppert, Wand and Carroll (2003) ## Semiparametric regression CUP. (No advantage to actually ## using this, since mgcv can happily handle non-identity ## penalties.) smooth.construct.tr.smooth.spec<-function(object,data,knots) ## a truncated power spline constructor method function ## object$p.order = null space dimension { m <- object$p.order[1] if (is.na(m)) m <- 2 ## default if (m<1) stop("silly m supplied") if (object$bs.dim<0) object$bs.dim <- 10 ## default nk<-object$bs.dim-m-1 ## number of knots if (nk<=0) stop("k too small for m") x <- data[[object$term]] ## the data x.shift <- mean(x) # shift used to enhance stability k <- knots[[object$term]] ## will be NULL if none supplied if (is.null(k)) # space knots through data { n<-length(x) k<-quantile(x[2:(n-1)],seq(0,1,length=nk+2))[2:(nk+1)] } if (length(k)!=nk) # right number of knots? stop(paste("there should be ",nk," supplied knots")) x <- x - x.shift # basis stabilizing shift k <- k - x.shift # knots treated the same! X<-matrix(0,length(x),object$bs.dim) for (i in 1:(m+1)) X[,i] <- x^(i-1) for (i in 1:nk) X[,i+m+1]<-(x-k[i])^m*as.numeric(x>k[i]) object$X<-X # the finished model matrix if (!object$fixed) # create the penalty matrix { object$S[[1]]<-diag(c(rep(0,m+1),rep(1,nk))) } object$rank<-nk # penalty rank object$null.space.dim <- m+1 # dim. of unpenalized space ## store "tr" specific stuff ... object$knots<-k;object$m<-m;object$x.shift <- x.shift object$df<-ncol(object$X) # maximum DoF (if unconstrained) class(object)<-"tr.smooth" # Give object a class object } Predict.matrix.tr.smooth<-function(object,data) ## prediction method function for the `tr' smooth class { x <- data[[object$term]] x <- x - object$x.shift # stabilizing shift m <- object$m; # spline order (3=cubic) k<-object$knots # knot locations nk<-length(k) # number of knots X<-matrix(0,length(x),object$bs.dim) for (i in 1:(m+1)) X[,i] <- x^(i-1) for (i in 1:nk) X[,i+m+1] <- (x-k[i])^m*as.numeric(x>k[i]) X # return the prediction matrix } # an example, using the new class.... require(mgcv) set.seed(100) dat <- gamSim(1,n=400,scale=2) b<-gam(y~s(x0,bs="tr",m=2)+s(x1,bs="ps",m=c(1,3))+ s(x2,bs="tr",m=3)+s(x3,bs="tr",m=2),data=dat) plot(b,pages=1) b<-gamm(y~s(x0,bs="tr",m=2)+s(x1,bs="ps",m=c(1,3))+ s(x2,bs="tr",m=3)+s(x3,bs="tr",m=2),data=dat) plot(b$gam,pages=1) # another example using tensor products of the new class dat <- gamSim(2,n=400,scale=.1)$data b <- gam(y~te(x,z,bs=c("tr","tr"),m=c(2,2)),data=dat) vis.gam(b)


Table of contents, we will explain what is a model, how to and where to write a model for a page, or for a controlled section inside a page.
A controlled section inside a page can be a
Binding, at it's very basic, is the process where one thing is assinged to another thing. Here, we want to assign some attributes from a model to a component.
A model is data used by a program. This may be a database, file, or a simple object.
For now, each model can be defined inside a controller as in the examples found at the page
In our case, the model is JavaScript object ment to handle the form changes (in case of forms), to apply some attributes for some components.
One of the most important feature that a model can provide is the support for internationalization and localization, a feature we target with the models.
This is the easiest way to use a model. You just need to have a
The attributes can be set using the following methods:
Using "@" inside a value of an attribute.
Using "view-model" attribute to assign more attributes.
Using view-model-ATTRIBUTE_NAME to assign a value to ATTRIBUTE_NAME, where ATTRIBUTE_NAME can be any attribute of a component. Similar to first method.
Using "data-view-model" to assign more attributes to more components. This one is used only for
Intuitive examples cand be found on the following pages:
Two-way binding in programming, as minimal definition, is the process where any change made in the view is reflected into the model and any change in the model is reflected into the view.
In time, all the components will be able to have bindings, right now, all the form components have implmented two-way binding (explained in
There is not much to do here, you just need to make sure that the components are binded and the two-way is handled by the components.
Expressions are a way of adding business logic to models. These are plain callbacks which are executed in the context of a model and are bound to Cardinal components using the @
syntax.
This feature was designed to work with the psk-condition
component in order to allow conditional rendering of other components or native HTML elements, nevertheless expressions work just as well as a standalone feature used outside of web components. For more information on how to use expressions with psk-condition
read the
To create an expression use the model.addExpression()
method:
Example
In the above example the totalOrdersAmount
expression will compute the total amount for all orders for a user. If this expression is used in tandem with a web component we will need a way to recompute the total amount if the orders change; in order to accomodate that we can tell the model to watch for changes on specific properties which will in turn trigger the re-evaluation of the expression. This is the purpose of the third argument given to the addExpression
method. It basically tells the model to watch for changes on the orders
property and then re-execute the callback if those changes happen. Multiple chains can be provided either by passing an array of strings as the third argument or by passing the chains as a variable number of string arguments to the addExpression
method.
Example of expression re-evaluation:
Live example
Passing the amount
and currency
chains as parameters to the addExpression
will allow the expression to be re-evaluated and the input component to be re-rendered when those value change.
To see how to use an expression in a web component read the
Using an expression in a controller requires calling the model.evaluateExpression()
method. One advantage of expressions over simple properties is their capability of encapsulating complex logic, including asynchronous operations.
Example


Ohio police: Dad arrested after 'tossing' baby out of door
CINCINNATI (WXIX) -- A North Avondale father in Ohio is under arrest after “tossing” his baby, who was in a car seat, out an apartment door when he became angry during a fight with the baby’s mother, according to court records.
The baby fell out of the car seat but sustained no visible injuries, Cincinnati police wrote in a criminal complaint filed in Hamilton County Municipal Court.
The incident was reported Tuesday in the 1000 block of Dana Avenue.
Daniel Jones, 33, also is accused of pushing and grabbing a domestic violence victim by the neck and body area, causing physical injuries, an affidavit states.
Then, when police took him into custody at his residence, they said he was found with a firearm tucked under his waistband and concealed by his shirt, other court records show.
Jones was booked into the Hamilton County jail Tuesday night on charges of endangering children, domestic violence and carrying concealed weapons.
Officers asked a judge to issue a temporary protection order against him.
Jones made a brief court appearance Wednesday.
His bond was set at $3,000.
The case goes next to Hamilton County Municipal Court Judge Jackie Ginocchio for a pretrial hearing at 9:30 a.m. Friday.


Fluxton Incorporation is a completely FICTIONAL company run by the two of us. It basically serves as a front
from behind which we work on various projects that catch our attention. It helps us strike a balance between
professionalism and keeping things simple. This is however, neither a business venture nor an organization
striving on profits. Our projects and ideas are completely driven by our passion towards technology and software
and we work on these to further strengthen our grasp on various languages and technology. In one line, Fluxton
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If you have any queries or suggestions, please feel free to contact us and we would be more than happy to have a
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suspected to be a mix of Cocker Spaniel and Chihuahua, and perhaps just a little bit of cat.
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