|
| generic | init => initDefault, fromComponents, fromFile |
| |
| procedure | initdefault |
| |
| procedure | fromcomponents |
| |
| procedure | fromarray |
| |
| procedure | fromfile |
| |
| generic | assignment => copyGrid2D |
| |
| procedure | copygrid2d |
| |
| final | destroygrid2d |
| |
| procedure | isequalto |
| |
| procedure | isequallyspaced |
| |
| procedure | checkequallyspaced |
| |
| procedure | addition |
| |
| procedure | subtraction |
| |
| procedure | multiplication |
| |
| procedure | division |
| |
| procedure | exponentiation |
| |
| procedure | additionfc |
| |
| procedure | subtractionfc |
| |
| procedure | multiplicationfc |
| |
| procedure | divisionfc |
| |
| procedure | exponentiationfc |
| |
| generic | operator => addition, additionFC |
| |
| generic | operator => subtraction, subtractionFC |
| |
| generic | operator => multiplication, multiplicationFC |
| |
| generic | operator => division, divisionFC |
| |
| generic | operator => exponentiation, exponentiationFC |
| |
| procedure | str |
| |
| procedure | show |
| |
| procedure | tofstream |
| |
| procedure | setunits |
| |
| generic | npoints => nPointsInCoord, nPointsVec |
| |
| procedure | npointsincoord |
| |
| procedure | npointsvec |
| |
| generic | min => minInCoord, minVec |
| |
| procedure | minincoord |
| |
| procedure | minvec |
| |
| generic | max => maxInCoord, maxVec |
| |
| procedure | maxincoord |
| |
| procedure | maxvec |
| |
| generic | stepsize => stepSizeInCoord, stepSizeVec |
| |
| procedure | stepsizeincoord |
| |
| procedure | stepsizevec |
| |
| generic | resize => resize1, resize2 |
| |
| procedure | resize1 |
| |
| procedure | resize2 |
| |
| procedure | x |
| |
| procedure | y |
| |
| procedure | at |
| |
| procedure | dv |
| |
| procedure | set |
| |
Definition at line 44 of file Grid2D.f90.
| procedure grid2d::grid2d::addition |
( |
| ) |
|
| procedure grid2d::grid2d::additionfc |
( |
| ) |
|
| generic grid2d::grid2d::assignment |
( |
| ) |
|
| procedure grid2d::grid2d::at |
( |
| ) |
|
| procedure grid2d::grid2d::checkequallyspaced |
( |
| ) |
|
| procedure grid2d::grid2d::copygrid2d |
( |
| ) |
|
| final grid2d::grid2d::destroygrid2d |
( |
| ) |
|
|
final |
| procedure grid2d::grid2d::division |
( |
| ) |
|
| procedure grid2d::grid2d::divisionfc |
( |
| ) |
|
| procedure grid2d::grid2d::dv |
( |
| ) |
|
| procedure grid2d::grid2d::exponentiation |
( |
| ) |
|
| procedure grid2d::grid2d::exponentiationfc |
( |
| ) |
|
| procedure grid2d::grid2d::fromarray |
( |
| ) |
|
| procedure grid2d::grid2d::fromcomponents |
( |
| ) |
|
| procedure grid2d::grid2d::fromfile |
( |
| ) |
|
| generic grid2d::grid2d::init |
( |
| ) |
|
| procedure grid2d::grid2d::initdefault |
( |
| ) |
|
| procedure grid2d::grid2d::isequallyspaced |
( |
| ) |
|
| procedure grid2d::grid2d::isequalto |
( |
| ) |
|
| generic grid2d::grid2d::max |
( |
| ) |
|
| procedure grid2d::grid2d::maxincoord |
( |
| ) |
|
| procedure grid2d::grid2d::maxvec |
( |
| ) |
|
| generic grid2d::grid2d::min |
( |
| ) |
|
| procedure grid2d::grid2d::minincoord |
( |
| ) |
|
| procedure grid2d::grid2d::minvec |
( |
| ) |
|
| procedure grid2d::grid2d::multiplication |
( |
| ) |
|
| procedure grid2d::grid2d::multiplicationfc |
( |
| ) |
|
| generic grid2d::grid2d::npoints |
( |
| ) |
|
| procedure grid2d::grid2d::npointsincoord |
( |
| ) |
|
| procedure grid2d::grid2d::npointsvec |
( |
| ) |
|
| generic grid2d::grid2d::operator |
( |
| ) |
|
| generic grid2d::grid2d::operator |
( |
| ) |
|
| generic grid2d::grid2d::operator |
( |
| ) |
|
| generic grid2d::grid2d::operator |
( |
| ) |
|
| generic grid2d::grid2d::operator |
( |
| ) |
|
| generic grid2d::grid2d::resize |
( |
| ) |
|
| procedure grid2d::grid2d::resize1 |
( |
| ) |
|
| procedure grid2d::grid2d::resize2 |
( |
| ) |
|
| procedure grid2d::grid2d::set |
( |
| ) |
|
| procedure grid2d::grid2d::setunits |
( |
| ) |
|
| procedure grid2d::grid2d::show |
( |
| ) |
|
| generic grid2d::grid2d::stepsize |
( |
| ) |
|
| procedure grid2d::grid2d::stepsizeincoord |
( |
| ) |
|
| procedure grid2d::grid2d::stepsizevec |
( |
| ) |
|
| procedure grid2d::grid2d::str |
( |
| ) |
|
| procedure grid2d::grid2d::subtraction |
( |
| ) |
|
| procedure grid2d::grid2d::subtractionfc |
( |
| ) |
|
| procedure grid2d::grid2d::tofstream |
( |
| ) |
|
| procedure grid2d::grid2d::x |
( |
| ) |
|
| procedure grid2d::grid2d::y |
( |
| ) |
|
| type(grid), dimension(2) grid2d::grid2d::component |
The documentation for this type was generated from the following file:


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To create a custom search adapter you will need to subclass the BaseSearch class. Then create an instance of the new class and pass that as the search keyword argument when you create the WebSupport object:
support = WebSupport(srcdir=srcdir,
builddir=builddir,
search=MySearch())
For more information about creating a custom search adapter, please see the documentation of the BaseSearch class below.
The following methods are defined in the BaseSearch class. Some methods do not need to be overridden, but some (add_document() and handle_query()) must be overridden in your subclass. For a working example, look at the built-in adapter for whoosh.
Called by the builder to initialize the search indexer. changed is a list of pagenames that will be reindexed. You may want to remove these from the search index before indexing begins.
| Parameters: | changed – a list of pagenames that will be re-indexed |
|---|
Called by the builder when writing has been completed. Use this to perform any finalization or cleanup actions after indexing is complete.
Called by the builder to add a doctree to the index. Converts the doctree to text and passes it to add_document(). You probably won’t want to override this unless you need access to the doctree. Override add_document() instead.
| Parameters: |
|
|---|
Called by feed() to add a document to the search index. This method should should do everything necessary to add a single document to the search index.
pagename is name of the page being indexed. It is the combination of the source files relative path and filename, minus the extension. For example, if the source file is “ext/builders.rst”, the pagename would be “ext/builders”. This will need to be returned with search results when processing a query.
| Parameters: |
|
|---|
Called by the web support api to get search results. This method compiles the regular expression to be used when extracting context, then calls handle_query(). You won’t want to override this unless you don’t want to use the included extract_context() method. Override handle_query() instead.
| Parameters: | q – the search query string. |
|---|
Called by query() to retrieve search results for a search query q. This should return an iterable containing tuples of the following format:
(<path>, <title>, <context>)
path and title are the same values that were passed to add_document(), and context should be a short text snippet of the text surrounding the search query in the document.
The extract_context() method is provided as a simple way to create the context.
| Parameters: | q – the search query |
|---|


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"WOOL "one of the first material used for making woven cloth (Leviticus 13:47, 48, 52, 59; 19:19). The first-fruit of wool was to be offered to the priests (Deuteronomy 18:4). The law prohibiting the wearing of a garment“of divers sorts, as of woollen and linen together” (Deuteronomy 22:11) may, like some other laws of a similar character, have been intended to express symbolically the separateness and simplicity of God’s covenant people. The wool of Damascus, famous for its whiteness, was of great repute in the Tyrian market (Ezekiel 27:18).
"WOOL "one of the first material used for making woven cloth (Leviticus 13:47, 48, 52, 59; 19:19). The first-fruit of wool was to be offered to the priests (Deuteronomy 18:4). The law prohibiting the wearing of a garment“of divers sorts, as of woollen and linen together” (Deuteronomy 22:11) may, like some other laws of a similar character, have been intended to express symbolically the separateness and simplicity of God’s covenant people. The wool of Damascus, famous for its whiteness, was of great repute in the Tyrian market (Ezekiel 27:18).


◄ People's Republic of China ►
Individual results
| Year | Contestant | Rank | Award |
|---|---|---|---|
| 2023 | Bowen Yu | 1 | Gold Medal |
| 2023 | Zhuoli Ding | 2 | Gold Medal |
| 2023 | Xiangchen Tian | 2 | Gold Medal |
| 2023 | Hanhong Zhao | 4 | Gold Medal |
| 2023 | Daibing Jiang | 6 | Gold Medal |
| 2022 | Guowei Xu | 1 | Gold Medal |
| 2022 | Mingxuan Yang | 2 | Gold Medal |
| 2022 | Zirui Liu | 3 | Gold Medal |
| 2022 | Qiancheng Li | 4 | Gold Medal |
| 2022 | Yuqi Ren | 5 | Gold Medal |
| 2021 | Zhihan Zhang | 2 | Gold Medal |
| 2021 | Ming Jian | 3 | Gold Medal |
| 2021 | Xiang Li | 4 | Gold Medal |
| 2021 | Yinghao Ma | 5 | Gold Medal |
| 2021 | Jingzhe Shi | 10 | Gold Medal |
| 2019 | Xiangkai Sun | 1 | Gold Medal |
| 2019 | Yifan Sun | 2 | Gold Medal |
| 2019 | Xiaoxun Gong | 4 | Gold Medal |
| 2019 | Yongkang Li | 8 | Gold Medal |
| 2019 | Junhao Chen | 13 | Gold Medal |
| 2018 | Yang Tianhua | 1 | Gold Medal |
| 2018 | Chen Shiqi | 6 | Gold Medal |
| 2018 | Xue Zeyang | 9 | Gold Medal |
| 2018 | Li Xingqiao | 11 | Gold Medal |
| 2018 | Dong Zehao | 13 | Gold Medal |
| 2017 | Haoyang Gao | ≥1 | Gold Medal |
| 2017 | Pinyuan Wang | ≥1 | Gold Medal |
| 2017 | Qiantan Hong | ≥1 | Gold Medal |
| 2017 | Xiquan Zheng | ≥1 | Gold Medal |
| 2017 | Zhun Wang | ≥1 | Gold Medal |
| 2016 | Chenkai Mao | 1 | Gold Medal |
| 2016 | Hongyi Luan | 2 | Gold Medal |
| 2016 | Yuxiang Chen | 7 | Gold Medal |
| 2016 | Wei Wang | 13 | Gold Medal |
| 2016 | Zihao Wang | 15 | Gold Medal |
| 2015 | Jingyu Zhao | 2 | Gold Medal |
| 2015 | Deng Pan | 3 | Gold Medal |
| 2015 | Chenxing Zhang | 6 | Gold Medal |
| 2015 | Xinyu Wang | 12 | Gold Medal |
| 2015 | Lingbang Zhu | 18 | Gold Medal |
| 2014 | Xiaoyu Xu | 1 | Gold Medal |
| 2014 | Haoyu Guo | 2 | Gold Medal |
| 2014 | Zijin Shi | 4 | Gold Medal |
| 2014 | Jiawei Dai | 6 | Gold Medal |
| 2014 | Jiayu Li | 12 | Gold Medal |
| 2013 | Zhang Chengkai | 2 | Gold Medal |
| 2013 | Zhang Zhengxing | 3 | Gold Medal |
| 2013 | Yu Yue | 9 | Gold Medal |
| 2013 | Wang Sizhen | 23 | Gold Medal |
| 2013 | Jiang Jiaqi | 27 | Gold Medal |
| 2012 | Hengyun Zhou | 2 | Gold Medal |
| 2012 | Yijun Jiang | 3 | Gold Medal |
| 2012 | Siyuan Wei | 9 | Gold Medal |
| 2012 | Chi Shu | 10 | Gold Medal |
| 2012 | Wenzhuo Huang | 12 | Gold Medal |
| 2011 | Lanqing Li | 5 | Gold Medal |
| 2011 | Chongyuan Xiang | 9 | Gold Medal |
| 2011 | Kexin Yi | 14 | Gold Medal |
| 2011 | Yifei Wang | 21 | Gold Medal |
| 2011 | Fan Yang | 23 | Gold Medal |
| 2010 | Yichao Yu | 1 | Gold Medal |
| 2010 | Jundong Wu | 2 | Gold Medal |
| 2010 | Qian Yu | 9 | Gold Medal |
| 2010 | Li Jing | 10 | Gold Medal |
| 2010 | Yongliang Zhang | 16 | Gold Medal |
| 2009 | Handuo Shi | 1 | Gold Medal |
| 2009 | Qian Lin | 4 | Gold Medal |
| 2009 | Jin Lei | 5 | Gold Medal |
| 2009 | Zhaoxi Xiong | 14 | Gold Medal |
| 2009 | Zixuan Guan | 18 | Gold Medal |
| 2008 | Longzhi Tan | 1 | Gold Medal |
| 2008 | Biao Lian | 2 | Gold Medal |
| 2008 | Quan Zhou | 3 | Gold Medal |
| 2008 | Zhuoran He | 20 | Gold Medal |
| 2008 | Zhen Bi | 39 | Gold Medal |
| 2007 | Xingyue Peng | 2 | Gold Medal |
| 2007 | Jiazhong Hu | 4 | Gold Medal |
| 2007 | Bingxi Qian | 16 | Gold Medal |
| 2007 | Chaoming Jian | 22 | Gold Medal |
| 2007 | Aoxi Li | 61 | Silver Medal |
| 2006 | Yang Shuolong | 2 | Gold Medal |
| 2006 | Wang Xingze | 4 | Gold Medal |
| 2006 | Zhu Li | 6 | Gold Medal |
| 2006 | Zhang Hongkai | 14 | Gold Medal |
| 2006 | Pei Dongfei | 16 | Gold Medal |
| 2005 | Mingjie Dai | 5 | Gold Medal |
| 2005 | Hanhan Li | 6 | Gold Medal |
| 2005 | An Li | 22 | Gold Medal |
| 2005 | Jianglei Yu | 37 | Gold Medal |
| 2005 | Wujie Huang | 41 | Gold Medal |
| 2004 | Kang Gao | ≥2 | Gold Medal |
| 2004 | Ruitian Lang | ≥2 | Gold Medal |
| 2004 | Yali Miao | ≥2 | Gold Medal |
| 2004 | Yeming Shi | ≥2 | Gold Medal |
| 2004 | Zhen Li | ≥2 | Gold Medal |
| 2002 | Xiangjun Fan | 2 | Gold Medal |
| 2002 | Chunhui Gu | 4 | Gold Medal |
| 2002 | Yang Chen | 12 | Gold Medal |
| 2002 | Huan Yang | 15 | Gold Medal |
| 2002 | Jun Gao | 70 | Silver Medal |
| 2001 | Chenbo Shi | 6 | Gold Medal |
| 2001 | Yang Qi | 7 | Gold Medal |
| 2001 | Yan Liu | 13 | Gold Medal |
| 2001 | Yimin Wei | 22 | Gold Medal |
| 2001 | Bin Wu | 29 | Silver Medal |
| 2000 | Lu Ying | 1 | Gold Medal |
| 2000 | Xiao Jing | 3 | Gold Medal |
| 2000 | Chen Xiaosheng | 5 | Gold Medal |
| 2000 | Song Junliang | 10 | Gold Medal |
| 2000 | Zhang Chi | 11 | Gold Medal |
| 1999 | Tao Ji | 7 | Gold Medal |
| 1999 | Liang Jiang | 18 | Gold Medal |
| 1999 | Xuefeng Duan | 36 | Silver Medal |
| 1999 | Xun Jia | 43 | Silver Medal |
| 1999 | Zhipeng Zhang | 62 | Silver Medal |
| 1998 | Yuao Chen | 1 | Gold Medal |
| 1998 | Zhifeng Deng | 2 | Gold Medal |
| 1998 | Xiaofeng Li | 4 | Gold Medal |
| 1998 | Xinan Wu | 6 | Gold Medal |
| 1998 | Yuan Liu | 10 | Gold Medal |
| 1997 | Keji Lai | 5 | Gold Medal |
| 1997 | Chenyang Wang | 8 | Gold Medal |
| 1997 | Qiao Lian | 11 | Gold Medal |
| 1997 | Xinyuan Wang | 20 | Silver Medal |
| 1997 | Xinlai Ni | 32 | Silver Medal |
| 1996 | Yurun Liu | 1 | Gold Medal |
| 1996 | Rui Zhang | 2 | Gold Medal |
| 1996 | Kaiwen Xu | 4 | Gold Medal |
| 1996 | Huigang Chen | 8 | Gold Medal |
| 1996 | Zheng Ni | 9 | Gold Medal |
| 1995 | Yu Haitao | 1 | Gold Medal |
| 1995 | Mao Wei | 4 | Gold Medal |
| 1995 | Ni Bin | 5 | Gold Medal |
| 1995 | Xie Xiaolin | 7 | Gold Medal |
| 1995 | Jiang Zhi | 14 | Gold Medal |
| 1994 | Yang Liang | 1 | Gold Medal |
| 1994 | Han Yan | 2 | Gold Medal |
| 1994 | Tian Tao | 4 | Gold Medal |
| 1994 | Rao Jingxiang | 6 | Gold Medal |
| 1994 | Huang Ying | 7 | Silver Medal |
| 1993 | Junan Zhang | 1 | Gold Medal |
| 1993 | Linbo Li | 3 | Gold Medal |
| 1993 | Zhanfeng Jia | 20 | Silver Medal |
| 1993 | Tao Wei | 31 | Silver Medal |
| 1993 | Zhining Huang | 50 | Bronze Medal |
| 1992 | Chen Han | 1 | Gold Medal |
| 1992 | Li Yi | 3 | Gold Medal |
| 1992 | Shi Changchun | 4 | Gold Medal |
| 1992 | Zhang Lintao | 7 | Gold Medal |
| 1992 | Luo Weidong | 12 | Gold Medal |
| 1991 | Tairan Wang | 4 | Gold Medal |
| 1991 | Yu Xiang Ren | 5 | Gold Medal |
| 1991 | Pei Qi Xuan | 9 | Gold Medal |
| 1991 | Lei Xia | 11 | Gold Medal |
| 1991 | Qiang Lu | 12 | Gold Medal |
| 1990 | Min-Yang Wu | 5 | Gold Medal |
| 1990 | Gang Zhou | 6 | Gold Medal |
| 1990 | Wei Yang | 9 | Silver Medal |
| 1990 | Bo-You Chen | 22 | Bronze Medal |
| 1990 | Zhi-Yong Duan | 34 | Bronze Medal |
| 1989 | Yan Jing | 13 | Silver Medal |
| 1989 | Mao Yong | 16 | Silver Medal |
| 1989 | Qiu Dong Yu | 22 | Silver Medal |
| 1989 | Ge Ning | 23 | Silver Medal |
| 1989 | Lin Xiao Fan | 55 | Bronze Medal |
| 1988 | Yangsong Chen | 4 | Gold Medal |
| 1988 | Jianbo Xu | 15 | Silver Medal |
| 1988 | Feng Chen | 23 | Silver Medal |
| 1988 | Aidong Ding | 54 | Bronze Medal |
| 1988 | Jian Chen | 67 | Honourable Mention |
| 1987 | Chen Xun | 4 | Silver Medal |
| 1987 | Li Jin Hui | 11 | Silver Medal |
| 1987 | Tang Peng Fei | 33 | Bronze Medal |
| 1987 | Wu Aj Hua | 41 | Bronze Medal |
| 1987 | Zhang Yan Ping | 42 | Bronze Medal |
| 1986 | Lin Chen | 9 | Silver Medal |
| 1986 | Wei Xing | 21 | Bronze Medal |
| 1986 | Zang Ming | 33 | Honourable Mention |
Results may be incomplete or incorrect.
Please send the relevant information to the webmaster:
<EMAIL_ADDRESS>If you are a participant you can send a personal page URL to be attached to your name.
If you are a participant you can send a personal page URL to be attached to your name.


BART Trip
- Select Source Station & Destination Station.
- We will get you all the scheduled routes with real-time updates.
- Select Source Station & Destination Station.
- We will get you all the scheduled routes with real-time updates.


|
Generated by JDiff |
|||||||
| FRAMES NO FRAMES |
The percent change statistic reported for all elements in each API is defined recursively as follows:
Percentage difference = 100 * (added + removed + 2*changed) ----------------------------------- sum of public elements in BOTH APIsWhereadded
is the number of packages added,removed
is the number of packages removed, andchanged
is the number of packages changed. This definition is applied recursively for the classes and their program elements, so the value for a changed package will be less than 1, unless every class in that package has changed. The definition ensures that if all packages are removed and all new packages are added, the change will be 100%. Values are rounded here, so a value of 0% indicates a percentage difference of less than 0.5%.The overall difference between the two APIs is approximately 11%.
| Percentage Difference |
Frequency | Percentage Frequency |
| 2 | 0.043478260869565216 | |
| 3 | 0.08695652173913043 | |
| 5 | 0.13043478260869565 | |
| 7 | 0.043478260869565216 | |
| 8 | 0.043478260869565216 | |
| 9 | 0.043478260869565216 | |
| 10 | 0.08695652173913043 | |
| 11 | 0.08695652173913043 | |
| 12 | 0.08695652173913043 | |
| 17 | 0.043478260869565216 | |
| 18 | 0.043478260869565216 | |
| 20 | 0.043478260869565216 | |
| 25 | 0.043478260869565216 | |
| 29 | 0.043478260869565216 | |
| 37 | 0.043478260869565216 | |
| 57 | 0.043478260869565216 | |
| 100 | 0.043478260869565216 |
| Percentage Difference |
Frequency | Percentage Frequency |
| 1 | 0.075 | |
| 2 | 0.0375 | |
| 3 | 0.0375 | |
| 4 | 0.025 | |
| 5 | 0.05 | |
| 6 | 0.025 | |
| 7 | 0.0125 | |
| 8 | 0.0125 | |
| 9 | 0.0125 | |
| 10 | 0.025 | |
| 11 | 0.025 | |
| 12 | 0.0125 | |
| 14 | 0.0125 | |
| 15 | 0.0125 | |
| 25 | 0.025 | |
| 33 | 0.0125 | |
| 37 | 0.025 | |
| 40 | 0.0125 | |
| 47 | 0.0125 | |
| 50 | 0.475 | |
| 72 | 0.0125 | |
| 83 | 0.025 | |
| 100 | 0.025 |
The numbers of program elements (packages, classes. constructors, methods and fields) which are recorded as removed, added or changed includes only the highest-level program elements. That is, if a class with two methods was added, the number of methods added does not include those two methods, but the number of classes added does include that class.
| Number of Differences | ||||
| Removals | Additions | Changes | Total | |
| Packages | 1 | 4 | 23 | 28 |
| Classes and Interfaces | 0 | 18 | 80 | 98 |
| Constructors | 0 | 2 | 0 | 2 |
| Methods | 2 | 87 | 177 | 266 |
| Fields | 0 | 29 | 0 | 29 |
| Total | 3 | 140 | 280 | 423 |


| OpCode(decimal) |
Mnemonic |
Operand |
Scope |
Example |
Description |
| 1 |
LDA |
immediate |
b32 |
LDA #100 |
load value into register A |
| 2 |
LDX |
immediate |
b32 |
LDX #100 |
load value into register X |
| 3 |
STA, X |
|
b32 |
|
store value in register A into memory location specified by register X |
| 4 |
END |
label |
b32 |
END #Start |
terminate the program |
| 5 |
CMPA |
immediate |
b32 |
CMPA #100 |
compares value in register A, and sets register FLAG |
| 6 |
CMPB |
immediate |
b32 |
CMPB #100 |
compares value in register B, and sets register FLAG |
| 7 |
CMPX |
immediate |
b32 |
CMPX #100 |
compares value in register X, and sets register FLAG |
| 8 |
CMPY |
immediate |
b32 |
CMPY #100 |
compares value in register Y, and sets register FLAG |
| 9 |
CMPD |
immediate |
b32 |
CMPD #100 |
compares value in register D, and sets register FLAG |
| 10 |
JMP |
label |
b32 |
JMP #Loop |
jump to the address of the label |
| 11 |
JEQ |
label |
b32 |
JEQ #Loop |
jump to the address of the label only if the EQ is set on the register FLAG |
| 12 |
JNE |
label |
b32 |
JNE #Loop |
jump to the address of the label only if the NE is set on the register FLAG |
| 13 |
JGT |
label |
b32 |
JGT #Loop |
jump to the address of the label only if the GT is set on the register FLAG |
| 14 |
JLT |
label |
b32 |
JLT #Loop |
jump to the address of the label only if the LT is set on the register FLAG |
| 15 |
INCA |
|
b32 |
|
add one to the value in register A |
| 16 |
INCB |
|
b32 |
|
add one to the value in register B |
| 17 |
INCX |
|
b32 |
|
add one to the value in register X |
| 18 |
INCY |
|
b32 |
|
add one to the value in register Y |
| 19 |
INCD |
|
b32 |
|
add one to the value in register D |
| 20 |
DECA |
|
b32 |
|
subtract one from the value in register A |
| 21 |
DECB |
|
b32 |
|
subtract one from the value in register B |
| 22 |
DECX |
|
b32 |
|
subtract one from the value in register X |
| 23 |
DECY |
|
b32 |
|
subtract one from the value in register Y |
| 24 |
DECD |
|
b32 |
|
subtract one from the value in register D |
| 25 |
ROLA |
|
b32 |
|
rotate the value in register A to the left |
| 26 |
ROLB |
|
b32 |
|
rotate the value in register B to the left |
| 27 |
RORA |
|
b32 |
|
rotate the value in register A to the right |
| 28 |
RORB |
|
b32 |
|
rotate the value in register B to the right |
| 29 |
ADCA |
|
b32 |
|
add one to the value of register A only if the CARRY is set on the register FLAG |
| 30 |
ADCB |
|
b32 |
|
add one to the value of register B only if the CARRY is set on the register FLAG |
| 31 |
ADDA |
immediate |
b32 |
ADDA #100 |
add the value to register A |
| 32 |
ADDB |
immediate |
b32 |
ADDB #100 |
add the value to register B |
| 33 |
ADDAB |
|
b32 |
|
add the values of register A and register B, and then store the result into register D |
| 34 |
LDB |
immediate |
starterVM |
LDB #100 |
load value into register B |
| 35 |
LDY |
immediate |
starterVM |
LDY #100 |
load value into register Y |
| 36 |
INT |
immediate |
starterVM |
INT #1 |
trigger one interruption |
| 37 |
STB, X |
|
starterVM |
|
store value in register B into memory location specified by register X |
| 38 |
LDX |
address |
starterVM |
LDX [#100] |
load value stored at memory address into register X |
| 39 |
STY, X |
|
starterVM |
|
store value in register Y into memory location specified by register X |
| 40 |
LDY |
address |
starterVM |
LDY [#100] |
load value stored at memory address into register Y |
| 41 |
LDA |
address |
starterVM |
LDA [#100] |
load value stored at memory address into register A |


Agri media has ‘greatest influence on farmer tech decisions’ – IFA
by Sylvester PhelanAgricultural related media has a strong influence on farmers when it comes to the adoption of farming technologies, according to a research project conducted by the Irish Farmers’ Association (IFA).
The research project focused on the adoption and attitudes towards digital technology in Irish agriculture; findings from it were launched by Farm Business Skillnet, in conjunction with the IFA.
The report ‘Digital Agriculture: Adoption and Attitudes’ was completed from the project, which featured consultation with 750 farmers, focus groups and industry stakeholders.
In the report it was found that agri media “had the greatest influence on farmers’ decisions to use farming technologies, being referred to by 42% when participants were asked about key influences”.
This rose to 52% for the under-35 age group, the study found.
Face-to-face environments had been particularly influential on many: farm advisor or agent, other farmers or farm discussion groups.
Following agri media’s 42% finding; 34% of farmers overall said farm advisors or agents influenced their decision, with an equivalent percentage saying another farmer influenced them.
31% of respondents highlighted farm discussion groups, while 24% namechecked trade shows as an influence. 19% referenced classroom education as an influence.
Suppliers, no one and family/friends were also mentioned, highlighted by 12%, 6% and 3% respectively.
Meanwhile, 60% of Irish farmers say they are likely to invest in digital technology on their farm in the future, the study details.
Discussion groups
Farm discussion groups were also highlighted as being a strong potential route for future skills development under a separate part of the study, which focused on education and training.
While classroom classroom based is the most common training environment, and full day courses and evening courses are most common time-frames for those who have undertaken training and development, 41% had participated in on-farm discussion groups, according to the report.
Those using technology on their farm are more likely to have completed on-farm discussion groups and evening classes than those not using technology, emphasising the importance of learning and of peer-to-peer knowledge sharing.
In an ideal situation, farmers feel on-farm discussion groups are a better learning environment, with evening classes the most suitable time, the study found.
Those who are likely to invest in technology are more likely to feel that on-farm discussion groups are an ideal learning environment when compared with those who are unlikely to invest, the research project concluded.


It was a long journey through the heart of the Beast. Full force with traffic, smog and heat…and stray dogs – who knew there were so many?
The cabbie who took us to a friend’s house and gave a great speech on the way there. It was another version of the ones I so often hear from cabbies in the Beast. They usually talk about how the country won’t go forward despite natural resources and it’s all because of the politicians and thieves and cheats and the uneducated, and on and on and on.
“I decline to vote,” he tells me, proudly.
Blah blah blah, I hear. Words are tossed about like leaves in the park – corruption, villainy, thievery – but it’s always on someone else.
It was a good one.
Humble, honest, well-informed and near insanity with the traffic due to the City. It could be worse, though, even for a taxi driver in this city. He tells me he drives 15-17 hours a day.
“But I’m glad to have the work,” he says from the front seat, his eyes mostly focused on the car in front of him. I nod in the backseat, waiting for him to tell me why.
“When I was a boy, around 12, I left home. I didn’t have a job so I came to São Paulo by foot all the way from Piauí.” I’m impressed. That’s, like, 1700 kilometers.
“It took around 3 years,” he recalls to me in a pensive voice, and I’m not sure he’s really talking to me anymore. He goes on to say, radiantly, how proud he is that he can put, not just food on his family’s table, but that they can have ground beef, and chicken in the fridge.
Think of that.
Word, man. Motherfucking word.
–
The city, the heart of it anyways, is sadistically glorious. A compilation of a few hundred years of colonial history shows in the architecture but contemporary times have begun to take over the concrete jungle. Graffiti climbing the sides of buildings like ivy, scattered filth on the greasy roads, mold around the worn edges on every thing capable of absorbing humidity. It gives the suffocated section of town an ancient but futuristic feel, sort of like Blade Runner meets Gotham City, if that makes any sense.
At night the streets are wet, though no one remembers when it rained. I want to look up, but I know that will give my foreignness away and then I will be haunted by the street children. This, I cannot have.
Youth here, does not last. Here, nothing has been young for a long, long time.


{% comment %} * * This include lets you easily embed a gallery into your post. * To use the gallery include you... * * 1. ...need two images: a thumbnail and a big image. * 2. Name the thumbnail gallery-image-thumb.jpg and... * 3. ...name the big gallery-image.jpg * 4. Define the big version in frontmatter, * * gallery: * - image_url: gallery-image.jpg * * 5. Give your image a caption – works without captions, too. * * gallery: * - image_url: gallery-image.jpg * caption: Starting Page with huge One Logo * * 6. Add the include whereever you want in your content like this: * * {% include gallery.html %} * * Check out the example page › http://phlow.github.io/feeling-responsive/design/gallery/ * {% endcomment %}


Reference¶
Core¶
-
ActionTree.
execute
(action, cpu_cores=None, keep_going=False, do_raise=True, hooks=None)¶ Recursively execute an
Action
’s dependencies then the action.- Parameters
action (Action) – the action to execute.
cpu_cores (int or None or
UNLIMITED
) – number of CPU cores to use in parallel. PassNone
(the default value) to let ActionTree choose. PassUNLIMITED
to execute an unlimited number of actions in parallel (make sure your system has the necessary resources). Note: CPU cores are managed like any otherResource
, and this parameter sets the availability ofCPU_CORE
for this execution.keep_going (bool) – if
True
, then execution does not stop on first failure, but executes as many dependencies as possible.do_raise (bool) – if
False
, then exceptions are not re-raised asCompoundException
but only included in theExecutionReport
.hooks (Hooks) – its methods will be called when execution progresses.
- Raises
CompoundException – when
do_raise
isTrue
and dependencies raise exceptions.- Return type
-
class
ActionTree.
Action
(label, dependencies=[], resources_required={}, accept_failed_dependencies=False)¶ The main class of ActionTree. An action to be started after all its dependencies are finished. Pass it to
execute()
.This is a base class for your custom actions. You must define a
do_execute(self, dependency_statuses)
method that performs the action. Thedependency_statuses
argument is a dictionary whose keys areself.dependencies
and values are theirActionStatus
. Outputs and side-effects describes how its return values, the exceptions it may raise and what it may print is handled.Actions, return values and exceptions raised must be picklable.
- Parameters
label (str or None) – A string used to represent the action in
GanttChart
andDependencyGraph
. Can be retrieved bylabel
.dependencies (list(Action)) – see
add_dependency()
resources_required (dict(Resource, int)) – see
require_resource()
accept_failed_dependencies (bool) – if
True
, then the action will execute even after some of its dependencies failed.
-
property
label
¶ The label passed to the constructor.
-
add_dependency
(dependency)¶ Add a dependency to be executed before this action. Order of insertion of dependencies is not important.
- Parameters
dependency (Action) –
- Raises
DependencyCycleException – when adding the new dependency would create a cycle.
-
property
dependencies
¶ The list of this action’s direct dependencies.
-
require_resource
(resource, quantity=1)¶ Set the quantity of a certain
Resource
required to run this action.Note that an action that requires more than a resource’s availability will be executed anyway. It will just not be executed in parallel with any other action that requires the same resource.
-
property
resources_required
¶ The list of this action’s required resources and quantities required.
-
property
accept_failed_dependencies
¶ True
if the action will execute even if some of its dependencies failed.- Return type
-
get_possible_execution_order
(seen_actions=None)¶ Return the list of all this action’s dependencies (recursively), in an order that is suitable for linear execution. Note that this order is not unique. The order chosen is not specified.
-
class
ActionTree.
Resource
(availability)¶ A resource that an
Action
can require for its execution. You can use resources to protect stuff that must not be used by more than N actions at the same time, à la semaphore. Like semaphorees, with an availability of 1, they become mutexes.Resources Describes how to use this class.
- Parameters
availability (int or
UNLIMITED
) – the number of instances available for this resource
-
ActionTree.
CPU_CORE
= <ActionTree._CpuCoreResource object>¶ A special
Resource
representing a processing unit. You can pass it toAction.require_resource()
if your action will execute on more than one core.- Type
-
class
ActionTree.
Hooks
¶ Base class to derive from when defining your hooks.
execute()
will call its methods when execution progresses.-
action_pending
(time, action)¶ Called when an action is considered for execution, i.e. at the beginning of
execute()
.- Parameters
time (datetime.datetime) – the time at which the action was considered for execution.
action (Action) – the action.
-
action_ready
(time, action)¶ Called when an action is ready to be executed, i.e. when all its dependencies have succeeded.
- Parameters
time (datetime.datetime) – the time at which the action was ready.
action (Action) – the action.
-
action_canceled
(time, action)¶ Called when an action’s execution is canceled, i.e. when some of its dependencies has failed.
- Parameters
time (datetime.datetime) – the time at which the action was canceled.
action (Action) – the action.
-
action_started
(time, action)¶ Called when an action’s execution starts.
- Parameters
time (datetime.datetime) – the time at which the action was started.
action (Action) – the action.
-
action_printed
(time, action, data)¶ Called when an action prints something.
- Parameters
time (datetime.datetime) – the time at which the action printed the data.
action (Action) – the action.
data (str) – the data printed.
-
action_successful
(time, action, return_value)¶ Called when an action completes without error.
- Parameters
time (datetime.datetime) – the time at which the action completed.
action (Action) – the action.
return_value – the value returned by the action.
-
action_failed
(time, action, exception)¶ Called when an action completes with an exception.
- Parameters
time (datetime.datetime) – the time at which the action completed.
action (Action) – the action.
exception – the exception raised by the action
-
-
exception
ActionTree.
DependencyCycleException
¶ Exception thrown by
Action.add_dependency()
when adding the new dependency would create a cycle.
-
exception
ActionTree.
CompoundException
(exceptions, execution_report)¶ Exception thrown by
execute()
when dependencies raise exceptions.-
property
exceptions
¶ The list of exceptions raised.
-
property
execution_report
¶ The
ExecutionReport
of the failed execution.
-
property
-
class
ActionTree.
ExecutionReport
¶ Execution report, returned by
execute()
.-
class
ActionStatus
(pending_time)¶ Status of a single
Action
.-
property
status
¶ The status of the action:
SUCCESSFUL
if the action succeeded,FAILED
if the action failed, andCANCELED
if the action was canceled because some of its dependencies failed.
-
property
pending_time
¶ The time when this action was considered for execution.
- Return type
-
property
ready_time
¶ The time when this action was ready to execute. (
None
if it was canceled before being ready).- Return type
-
property
cancel_time
¶ The time when this action was canceled. (
None
if it was started).- Return type
-
property
start_time
¶ The time at the beginning of the execution of this action. (
None
if it was never started).- Return type
-
property
success_time
¶ The time at the successful end of the execution of this action. (
None
if it was never started or if it failed).- Return type
-
property
return_value
¶ The value returned by this action (
None
if it failed or was never started).
-
property
failure_time
¶ The time at the successful end of the execution of this action. (
None
if it was never started or if it succeeded).- Return type
-
property
exception
¶ The exception raised by this action (
None
if it succeeded or was never started).
-
property
-
get_action_status
(action)¶ Get the
ActionStatus
of an action.- Parameters
action (Action) –
- Return type
-
get_actions_and_statuses
()¶ Get a list of actions and their statuses.
- Return type
-
class
-
ActionTree.
SUCCESSFUL
= 'SUCCESSFUL'¶ The
ActionStatus.status
after a successful execution.
-
ActionTree.
FAILED
= 'FAILED'¶ The
ActionStatus.status
after a failed execution where this action raised an exception.
-
ActionTree.
CANCELED
= 'CANCELED'¶ The
ActionStatus.status
after a failed execution where a dependency raised an exception.
-
class
ActionTree.
DependencyGraph
(action)¶ A visual representation of the dependency graph, using Graphviz.
-
write_to_png
(filename)¶ Write the graph as a PNG image to the specified file.
See also
get_graphviz_graph()
if you want to draw the graph somewhere else.
-
get_graphviz_graph
()¶ Return a
graphviz.Digraph
of this dependency graph.See also
write_to_png()
for the simplest use-case.
-
-
class
ActionTree.
GanttChart
(report)¶ A visual representation of the timing of an execution.
-
write_to_png
(filename)¶ Write the Gantt chart as a PNG image to the specified file.
See also
get_mpl_figure()
andplot_on_mpl_axes()
if you want to draw the report somewhere else.
-
get_mpl_figure
()¶ Return a
matplotlib.figure.Figure
of this Gantt chart.See also
plot_on_mpl_axes()
if you want to draw the Gantt chart on your own matplotlib figure.See also
write_to_png()
for the simplest use-case.
-
plot_on_mpl_axes
(ax)¶ Plot this Gantt chart on the provided
matplotlib.axes.Axes
.See also
write_to_png()
andget_mpl_figure()
for the simpler use-cases.
-
Stock actions¶
Stock actions are predefined common tasks (manipulating the filesystem, calling an external program, etc.)
They all specialize Action
.
-
class
ActionTree.stock.
NullAction
(label=None, *args, **kwds)¶ A stock action that does nothing. Useful as a placeholder for several dependencies.
@todoc
-
class
ActionTree.stock.
CallSubprocess
(command, kwargs={}, label=<object object>, *args, **kwds)¶ A stock action that calls a subprocess.
@todoc
-
class
ActionTree.stock.
CreateDirectory
(name, label=<object object>, *args, **kwds)¶ A stock action that creates a directory. No error will be raised if the directory already exists. If the directory to create is nested, intermediate directories will be created as well.
- Parameters
name (str) – the directory to create, passed to
os.makedirs()
.
@todoc
-
class
ActionTree.stock.
DeleteFile
(name, label=<object object>, *args, **kwds)¶ A stock action that deletes a file. No error will be raise if the file doesn’t exist.
- Parameters
name (str) – the name of the file to delete, passed to
os.unlink()
.
@todoc
-
class
ActionTree.stock.
DeleteDirectory
(name, label=<object object>, *args, **kwds)¶ A stock action that deletes a directory (recursively). No error will be raise if the directory doesn’t exist.
- Parameters
name (str) – the name of the directory to delete, passed to
shutil.rmtree()
.
@todoc
-
class
ActionTree.stock.
CopyFile
(src, dst, label=<object object>, *args, **kwds)¶ A stock action that copies a file. Arguments are passed to
shutil.copy()
.@todoc
-
class
ActionTree.stock.
TouchFile
(name, label=<object object>, *args, **kwds)¶ A stock action that touches a file. If the file already exists, its modification time will be modified. Else, it will be created, empty.
Note that the containing directory must exist. You might want to ensure that by adding a
CreateDirectory
as a dependency.- Parameters
name (str) – the name of the file to touch. Passed to
open()
and/oros.utime()
.
@todoc
-
class
ActionTree.stock.
Sleep
(secs, label=<object object>, *args, **kwds)¶ A stock action that sleeps for a certain duration.
- Parameters
secs (float) – seconds to sleep, passed to
time.sleep()
.
@todoc


Request to Join
Name
Contact Information (Email or Phone)
Please Introduce Yourself
BandUp
/
Get Some Recommendation
Carach Angren
New York
Post-Rock
Year formed: 2019
We're Looking for muscians who can play:
Guitar, Piano
Check out our demos!
Request to join!
Band Description:


Code for model cloning, plus model-related API entries.
class Model
: Model
groups layers into an object with training and inference features.
class Sequential
: Linear stack of layers.
clone_model(...)
: Clone any Model
instance.
load_model(...)
: Loads a model saved via save_model
.
model_from_config(...)
: Instantiates a Keras model from its config.
model_from_json(...)
: Parses a JSON model configuration file and returns a model instance.
model_from_yaml(...)
: Parses a yaml model configuration file and returns a model instance.
save_model(...)
: Saves a model as a TensorFlow SavedModel or HDF5 file.


The NYTimes app allows you to enjoy the award-winning journalism of The New York Times on your Windows Phone, wherever you are. The app has been specifically designed for browsing and navigating articles, features and video on the Windows Phone platform. Download and sync the latest news directly to your device via Wi-Fi or cellular network to take it with you wherever you go. Share articles, photos and videos with your friends through Facebook, Twitter and e-mail and be the first to read about events as soon as they occur with breaking news alerts.
Available in the Windows Marketplace for Mobile.
Note: This FAQ applies to the NYTimes app for Windows Phone 7.5 or later. If you are using Windows Phone 7, you can find more information on the NYTimes app in our Windows Phone 7 FAQ.
The NYTimes application for Windows Phone allows you to browse articles, blogs, videos and more. You can save articles and pin sections for easy access.
The NYTimes application is free to download and install, and includes some free content. However, to get unlimited access to all sections, you must become a digital subscriber. For more information, please see the Digital Subscriptions and Premium Products FAQ.
Please note that in the absence of a Wi-Fi connection, the NYTimes app uses your phone's cellular network connection to access and download content. Please check with your carrier to see whether you will be charged for usage, especially while traveling.
The app will work on any Windows Phone running the Windows Phone 7.5 O.S.
To determine your phone’s O.S., from the Windows Phone Start page, flick to the app list and tap settings. From the systems page, tap about. The device O.S. is listed under Software.
For more information on the NYTimes app for Windows Phone 7, see the Windows Phone 7 FAQ.
The NYTimes app for Windows Phone is available in the Windows Marketplace for Mobile. By default, you can access the Marketplace from the Start page of your phone.
You can navigate to the Saved section by flicking over from any page in the main area of the app. From Saved, you can view your saved articles. For more information, see "How do I save an article?"
You can save an article by adding it to the Saved section.
First, open the full article view by tapping any headline on a page. Select the ellipses in the lower-right corner and tap save. You must be logged in with an NYTimes.com account to save articles.
You can pin the sections you frequently access to your Windows Phone Start page. That way, you can jump right into your favorite NYTimes section from your phone's Start page.
To pin a section, flick to the Sections area of the New York Times app. Tap the name of the section you wish to pin. Once you are in the section, select the ellipses in the lower-right corner and tap pin this section. The section you are in will be added to the Start page of your Windows Phone.
Navigate to the Saved section. Tap and hold any article title. Select remove from the pop-up menu that appears. You can also remove from the article itself: select the ellipses in the lower-right corner while reading a saved article and then tap remove.
To share an article, open the full article view. Select the ellipses in the lower-right corner and then tap the e-mail, message, or share icon. In each case, a summary and a link to the article will be filled in automatically as the body of your message.
A new sync automatically begins each time you open the app. To manually initiate a sync, select the ellipses in the lower-right corner of any section front and then tap refresh.
Select the ellipses in the lower-right corner and tap settings. Flick to My Account. You can change the font size in the Settings area.
If you are a digital subscriber with a package that includes smartphone apps, you will have access to the latest articles from all sections of NYTimes.com, which reflects all content published in The New York Times newspaper. You will also have access to blog posts, slide shows and videos from NYTimes.com.
If you are not a subscriber you will only have limited access to some content on the app. For more information about the digital subscriber packages, please see the Digital Subscriptions and Premium Products FAQ.
Select the ellipses in the lower-right corner and tap settings. In the My Account area of Settings, you can log in or create an account.
Yes, but note that in the absence of a Wi-Fi connection, the NYTimes application uses your phone’s cellular network connection to access and download content. Normal network data rates apply, and you may incur roaming charges while traveling. Check with your local carrier.
To remove the NYTimes application, follow the same procedure that you'd use for any Windows Phone app. From the Windows Phone Start page, flick to the App list. Tap and hold the NYTimes application and choose uninstall.
No. You can download the NYTimes application and access some content without registering. However, full access requires registration and a subscription. If you have already registered with NYTimes.com, you can use the same user name and password to log in to the app. For full access, you must subscribe to a digital package that includes smartphone apps.
We are very interested in hearing from our readers. Please submit feedback and questions to windowsphone@nytimes.com.


"Confused" - Training Set A
This is a set of training images for the Machine Learning for Kids project "
Confused
".
Instructions for how to use it are in the
project worksheet
.
Display thumbnails (instead of full-size pictures)
Grapefruits
Lemons


Core
API Keys
You will need keys to work with the APIs.
- Application ID: Identifies your Application for analytics and quota limits.
- Campus Keys: A Token Key Moniker (TKM), Shared Secret, and Client String identifies the LearningStudio campus where your data comes from.
You can get an Application ID for your app and campus keys for our Sandbox Campus by creating an app on the PDN. Learn more here.
Introduction
LearningStudio Course APIs are REST-based services, and all calls must be authenticated with either an OAuth 1 signature or with an OAuth 2 user token. While not difficult to create your own tools for making these requests, the Core library simplifies the effort by automatically handling authentication.
This library uses the Authentication library, so you need to provide the same configuration information as described there. However, Core will do the heavy lifting of generating and managing signatures and tokens for the requests.
Using Core
Setup
To begin, import the learningstudio.oauth.service
, learningstudio.oauth.config
, and learningstudio.core.service
resources to your script
from learningstudio.oauth.service import *
from learningstudio.oauth.config import *
from learningstudio.core.service import *
Authentication
You'll need to provide your authentication details (keys, client string, etc) so the Core library can handle authentication. The OAuthConfig
class is a generic carrier for the configuration information for all authentication methods. You'll add the information you need using the following methods.
config = oauth_config(application_id = APPID,
application_name = APPNAME,
client_string = CLIENT_STRING,
consumer_key = KEY,
consumer_secret = SECRET)
There are differences in what values are needed between the different OAuth methods. Generally, adding all five pieces of information is most flexible, but you can leave out the pieces you don't need. For example, if using OAuth 1 only (System to System calls), you don't need the Application Name or Client String.
The OAuthServiceFactory
object instantiates the appropriate service for the authentication method you want to use. When using core, you only need to create the Factory and pass it to the Core library.
factory = OAuthServiceFactory(config)
Requests
Next, you'll instantiate the Core library's BasicService
, which handles all the work of making an API call. When creating the object, pass the OAuth Factory as the only parameter:
basic_service = BasicService(factory)
Before making an API call, set the service to the OAuth method you'll use. If using OAuth 2 for a user token, pass the user's username, and if using Password grant type, also send the password.
# OAuth 1
basic_service.useOAuth1()
# OAuth 2 Assertion Grant Type
basic_service.useOAuth2(STUDENT_USERNAME)
# OAuth 2 Password Grant Type
basic_service.useOAuth2(STUDENT_USERNAME, STUDENT_PASSWORD)
Finally, use the doMethod
method to make the request. This method has the following signature:
doMethod(http_method , api_endpoint [, extraHeaders [, body]])
| Parameter | Description |
|---|---|
http_method |
Any of GET , POST , PUT , or DELETE , depending on the operation you're performing. Required for all requests. |
api_endpoint |
The URI of the API endpoint you're calling; this is only the "path" portion of the request. Required for all requests. Example: /me/courses |
extraHeaders |
A dictionary of any additional headers you need to send with the request. The key should be the header name, and the value the header value. This is used primarily by the other LearningStudio libraries. Example: {'Content-Type': 'application/json'} |
body |
The body of the API request. Required for POST and PUT operations only. |
Results
When you call doMethod
, it will return a Response
object. This object has these methods:
| Method | Description |
|---|---|
getContentType() |
Returns the type of response, either json or xml if it's text-based, or the MIME type of the content if binary content. |
getContent() |
Returns the text-based body of the response from the API. It is returned as a string of either JSON or XML, and is not parsed into a native object. |
getBinaryContent() |
Returns the binary-based body of the response from the API, if isBinaryContent() returns true . |
isBinaryContent() |
Returns either true or false as to whether the body of the API response is binary data (for example, if downloading a document or threaded discussion attachment). |
| About the API Request | |
getHeaders() |
Returns the headers used in the request. |
getMethod() |
Returns the HTTP method that was used. |
getStatusCode() |
Returns the HTTP Status Code from the API request. Example:200 , 201 , 400 , etc. |
getStatusMessage() |
Returns the HTTP Status message from the API request. Example:Created or Not Found . |
getUrl() |
Returns the URL that was called to make the request. |
isError() |
Returns either true or false as to whether there was a problem with the API request. |
Example
from learningstudio.oauth.service import *
from learningstudio.oauth.config import *
from learningstudio.core.service import *
APPID = # Identifies your Application
APPNAME = # No spaces for best results (e.g., MyAppName)
TOKEN_KEY_MONIKER =
SHARED_SECRET =
CLIENT_STRING =
USERNAME =
API_URI = # e.g., /users/{userID}
config = oauth_config(application_id = APPID,
application_name = APPNAME, # Needed only for OAuth 2 Assertion
client_string = CLIENT_STRING, # Needed only for OAuth 2
consumer_key = KEY,
consumer_secret = SECRET) # Needed only for OAuth 1 & OAuth 2 Assertion
factory = OAuthServiceFactory(config)
basic_service = BasicService(factory)
basic_service.useOAuth2(STUDENT_USERNAME)
try:
response = basic_service.doMethod('GET', API_URI)
except (Exception):
# process exception
print "Ruh roh!"
if response.isError():
response_body = response.getContent()


Updated drug status with transaction Id {{transactionId}}
Could not updated drug status
UPDATE DRUG STATUS
Drug Id
Select Drug Status
AVAILABLE
WITHDRAWN


{% extends "./layouts/base.html" %} {% block header %} {% global_partial path="./partials/header-no-navigation.html" %} {% endblock header %} {% block body %} {% dnd_area "dnd_area" label="Main section", class="body-container body-container--landing-page" %} {# Hero banner #} {% include_dnd_partial path="../sections/hero-banner.html" context={ "content": "
Use this space to tell everyone what your eBook is all about.
" } %} {# Three column image with text #} {% include_dnd_partial path="../sections/multi-column-content.html", context={ "background_color": "#FFFFFF" } %} {% end_dnd_area %} {% endblock body %} {% block footer %} {% endblock footer %}


Dawn reveals solo performance MV for 'Money'
by germainejDawn has dropped his solo performance music video for "Money".
In the new MV, Dawn is solo without any other dancers as he performs his latest track, giving another artistic perspective. "Money" is about not being able to live without something, and it's the former Pentagon member's first release as an artist under P-Nation.
Watch Dawn's "Money" solo performance MV above, his original MV here, and the choreography MV here if you missed them.


Grades for group '
'
Eduction:
Course:
Group name:
Year:
-
Periods
Name
Student number
Grade
Motivation
Export generated at


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- Progressive – so its still usbale on a basic level on old browsers and fully functional on latest
- Discoverable – through any serach engine say for example Google
- Linkable – so that you can share it by simply sending a URL
- Safe -
- Fresh
- App-like
- Responsive
- Re-engageable
- Connectivity independent
Back


Inspired by the blackhole "Gargantua" in the film Interstellar, I built this real-time rendered blackhole using GLSL and C++. Since the blackhole is a form of extreme body in the universe, the light will behave oddily arounded the blackhole, I used ray marching approach to simulate the lighting condition around the blackhole.
There are mainly four parts in the real-time blackhole system I am building. They are
I). Pseudo-Riemannian manifold optics.
II). Ray Marching.
III). The camera system
Since the light ray is bent in this special case, the light might actually circle around the blackhole multiple times. (One can view the entire sphere of the event horizon from any observing angle, that means one can view the north pole and south pole of the event horizon at the same time because the light is bent.)Therefore, a traditional ray tracing approach is not appliable. To solve this problem, we introduced the Ray Marching approach.
In Ray Marching approach, within each iteration, the light will work like a "probe", take a small step through a scence until it intersects objects. Ray Marching allows us to use numerical intergration to model the path of the light. Along that path, one can test for intersection with the accretion disk and the event horizon of the blackhole. The event horizon is a "black" disk around the center of the blackhole. If there is light ever enter the event horizon (depends on the radius of the blackhole), it will never escape, that's why blackhole is called "blackhole". If the light is not collided with any thing throughout our simulation, we can simply sample from the background texture.
This part is comparatively straightfawrd. Thanks for GLUT framework, I am able to bootstrap the GUI system. Everytime when there's an external input from the keyboard, an update function will be called within the display function which is fed into glutDisplayFunc. Within the update, the position of the camera system will be recalculated based on the input value through transformation matrices.
Besides the camera system, I also used an existing CGLShader which already encapusaled a GLSL shading pipeline. Thus I am able to easily use GPU to accelerate the real-time rendering.
In this project, I learned a lot graphics knowledge that related to CS184 or even knowledge that went beyond it. Especially those hands-on knowledge such as using frameworks and shaders in real life. My original goal is implementing a real-time raytracing blackhole that has accretion disk and bloom post processing effects. Due to time constrain I didn't incorporate those functionalites in this submission, but I will continue work on those funtions and eventually present a more physically accurate blackhole. Besides, throughout my researching and developing, I realized that redshift is usually ignored in most exisiting raymarching blackhole simulations and shaders. I will probably add this feature in the future version too.(Also I will proabably use metal to rewrite the simulator and migrate it to VR platfrom so that people an view how light is bent more intuitively.)
Scientific models #1: http://rantonels.github.io/starless/
Scientific models #2: http://spiro.fisica.unipd.it/~antonell/schwarzschild/
Shadertoy bloom effect: https://www.shadertoy.com/view/lstSRS
Minxing Chen: Writing proposal, Researching, Code Implemention, Presentation.


Spend Arcana to increase the effective value of a stat on all crystals. Shift click to buy as many as you can. Right click to remove a level.


specification module¶
–Development for conceptual design and simulation for aircraft–
Aircraft
- Fuel type
‘jet’, ‘electric’, ‘hybrid’, ‘hydrogen’
- Aircraft type
‘normal’, ‘Blended Wing Body’, ‘drone’, ‘Hyper sonic’, ‘propeller’
- Aircraft shape’s components
[‘main wing’, ‘vertical wing’, ‘horizontal wing’, ‘engine’, ‘nacelle’, ‘winglet’, ‘cabin fuselage’, ‘cockpit fuselage’, ‘after cabin fuselage’, ‘leg’]
- Aircraft Type and Component
- normal
[‘main wing’, ‘vertical wing’, ‘horizontal wing’, ‘engine’, ‘nacelle’, ‘winglet’, ‘cabin fuselage’, ‘cockpit fuselage’, ‘after cabin fuselage’, ‘leg’]
- BWB
normal(without ‘vertical wing’ & ‘horizontal wing’) + different shape definition
- drone(UAV)
[‘main wing’, ‘engine’, ‘propeller’, ‘cockpit fuselage’, ‘cabin fuselage’]
- Hyper sonic
normal(without ‘horizontal wing’) + different wing shape + different aerodynamic performance modules
- propeller
normal + different shape definition
- wing type(airfoil)
cross section(NACA 6), horizontal section(Trapezoid,Delta,Diamond,rectangle)
Engine
- Engine type
‘turbojet’, ‘turbofan’, ‘turboprop’(propeller),’turboelectric’, ‘partialelectric’, ‘allelectric’, ‘serieshybrid’, ‘partialhybrid’, ‘parallelhybrid’
optional engine version: BLI(Boundary Layer Ingestion)
- Engine components
- electric fan
[inlet, fan, nozzle, jet]
- turbofan
[inlet, lpc, hpc, cc, hpt, hptcool, lpt, lptcool, coreout, nozzle, jet, fan, fan_nozzle, fan_jet]
- turbojet
[inlet, lpc, hpc, cc, hpt, hptcool, lpt, lptcool, coreout, nozzle, jet]
- turboprop(propeller)
[inlet, lpc, hpc, cc, hot, hptcool, lpt, lptcool, coreout, nozzle, jet]
- turboelectric
concept => (turboshaft => electric fan)
[core: inlet, lpc, hpc, cc, hpt, hptcool, lpt, lptcool, coreout, nozzle, jet, electric fan: fan_electric_inlet, fan_electric, fan_electric_nozzle, fan_electric_jet]
- partialelectric
concept (turbofan => electric fan)
[core: inlet, lpc, hpc, cc, hpt, hptcool, lpt, lptcool, coreout, nozzle, jet, fan, fan_nozzle, fan_jet, electric fan: fan_electric_inlet, fan_electric, fan_electric_nozzle, fan_electric_jet]
- allelectric
[fan_electric_inlet, fan_electric, fan_electric_nozzle, fan_electric_jet] + [battery](electricity, fuel cell etc)
- serieshybrid
concept => (turboshaft + battery => electric fan)
[core: inlet, lpc, hpc, cc, hpt, hptcool, lpt, lptcool, coreout, nozzle, jet, [battery], electric fan: fan_electric_inlet, fan_electric, fan_electric_nozzle, fan_electric_jet]
- partialhybrid
concept => (turbofan + battery => electric fan) [core: inlet, lpc, hpc, cc, hpt, hptcool, lpt, lptcool, coreout, nozzle, jet, [battery], electric fan: eleinlet, elefan, elenozzle, elejet]
- parallel hybrid
concept => (battery => turbofan) [core: inlet, lpc, hpc, cc, hpt, hptcool, lpt, lptcool, coreout, nozzle, jet, fan, fan_nozzle, fan_jet], [battery]
Initial parameters
aircraft shape parameters + aircraft configuration parameters + aircraft aerodynamic parameters + engine parameters + engine configuration parameters
- Aircraft shape parameters
- Main wing
(wing width, wing thickness, the ratio of thickness and wing span, aspect ratio)
- Vertical wing
(wing width, wing thickness, the ratio of thickness and wing span, aspect ratio)
- Horizontal wing
(wing width, wing thickness, the ratio of thickness and wing span, aspect ratio)}
- Fuselage shape
{‘cabin’:(length, width), ‘cockpit’: (length, width), ‘after cabin’: (length, width)}
- Nacelle
include engine components parameters
- Aircraft configuration parameters
- wing mounting positions
3D coordinates (x, y, z)
- engine mounting positions
3D coordinates (x, y, z)
- aircraft other required args
aircraft weight model
- passenger number
the number of boarding
- cargo weight
the weight of total cargo
- cruise altitude
the height at cruise point
- cruise mach
the mach number at cruise point
- fuel coefficient
where to conduct the estimation of performance of aircraft at design point
- Aircraft aerodynamic parameters
L/D(?)
AOA(attack of angle)
- engine parameters
- BPR
bypass ratio, the ratio of core airflow and fan airflow
- FPR
fan pressure ratio, the ratio of inlet fan pressure and outlet fan pressure
- OPR
overall pressure ratio, the ratio inlet compressor and outlet compressor
- TIT
turbine inlet temperature, the temperature of turbine entrance
- BPRe
bypass ratio for electric fan, the ratio of core airflow and distributed fan airflow
- FPRe
fan pressure ratio for electric fan, the ratio of inlet fan pressure and outlet fan pressure
- Nfan
the number of electric fan
- electric density:
the density for electricity, unit is kW/kg or kg/kw
- electric efficiency
the efficiency of converting heat power generated by jet engine into electricity
- the ratio of electric power and engine generating power
the distributed ratio for supplementing the current power
- engine component efficiency
the heat efficiency which each engine component has
- BLI parameters
the relational variables with Boundary Ingestion Layer
BLI has some options…
various types of setting positions(ex. upper wing, upper body, down wing, upper fuselage, embedding,…)
- <Two case>
1.simplify the effect of boundary layer as constant
- 2.extend the 2D version’s flow field and calculate constant in more complicated and detailed environment
split flow into two parts(lower and higher flow)
lower flow => velocity is equal to hub velocity of electric fan
higher flow => velocity is equal to tip velocity of electric fan
<average operation point method>
fai = fai_distorted * eps / 360 + fai_freeflow * (360 - eps) / 360
(fai = pressure ratio, thermal ratio, efficiency)
- engine configuration parameters
- Nen
the number of engine
- thrust_design_point
thrust of engine at design point
- thrust_off_design_point
thrust of engine at off design point
- quality_engine
engine material quality
- Nlx
stage number of each compressor or turbine
- LFx
stage load factor of each compressor or turbine
- cool_airx
the distribution of cool air for high and low pressure turbine
Design Variables
- <Aircraft>
- fuselage shape:
1d vector(element number = minimum 7, maximum 10)
fuselage length(l0), section x horizontal coefficient(hx(x=1,2,3)), section x vertical coefficient(vx(x=1,2,3))
- wing shape:
1d vector(element number = minimum 15, maximum 20)
wing span(bx), Aspect ratio(ARx), taper ratio(tx), thickness and chord ratio(tcx), retreat angle(theta), x= main wing, vertical wing, horizontal wing
- performance:
1d vector(element number = minimum 6, maximum 10)
attack of angle x (x means phase, please refer to the flight path chapter)
- <Engine>
1d vector(element number = 20)
- core engine:
OPR, TIT, Nen, technical level, engine material quality, cool air rate, x stage number, x load factor
=> x heat efficiency(x = LPC, HPC, HPT, HPTCool, LPT, LPTCool)
- turbofan engine:
BPR, FPR, technical level => x heat efficiency(x= Fan, LPC, HPC, HPT, HPTCool, LPT, LPTCool)
- electric fan engine:
BPRe, FPRe, Nfan, electric efficiency(conversion rate of heat into electricity), electric energy density[kg/KW]
- <Joint>
- engine shape:
1d vector(element number = 5)
- x engine mounting position(x=core engine, distributed electric fan):
coefficient x axis, coefficient y axis(individually, based on module), turnover ratio, upper or down sign(1, -1)
- aircraft shape:
1d vector(element number = minimum 6, maximum 12)
- x wing mounting position(x=main, vertical, horizontal):
coefficient x axis, coefficient z axis(fuselage based)
- <BLI>
1d vector(element number = minimum 1, maximum 3)
distortion angle(epsilon)
- <Electricity>
1d vector(element number = minimum 2, maximum 5)
material level, battery electric energy density([kg/kw] or [kw/kg]), other args
- <Mission>
altitude, mach number, thrust at off design point, L/D, cruise range, max takeoff weight, passenger number, fuel coefficient, cargo weight ot volume
The definition of flight path
warming up => 1. takeoff => 2. climb => 3. cruise => 4. descend(+ loiter) => 5. landing => 6. stop
Fundamental equation
- Breguet formula
- 1.propeller
Range = (propeller efficient / bp ) * (L / D) * ln(W init / W finish), bp => m fuel[N] / propeller Power[W] / s
- 2.jet engine
Range = (jet velocity / SFC) * (L/D) * ln(W init / W finish), SFC => m fuel[N] / T[N] / s
Poll of coding
write design variables into csv file or generate the sets of the design variables at random value
Module
- Physic class(physics.py)
to compute the value of physics(ex. density, Pressure, Temperature,…)
- Design variables controller class(design_variables_controller.py)
to assign design variables into each class and adjust the interaction of design variables
- init:
aircraft type
engine type
design variables name
- method:
- concatenate_design_variables()
to create the vector of design variables for passing the optimization module
- manage_design_variables_by_module()
to clarify the boundary of the meaning of design variables, memorize index and name by dictionary format
- specify_fix_variables()
to determine whether the particular design variable is fixed or not and create such design vectors
- <specification>
deal with only engine design variables(for example, [BPR, OPR, FPR, TIT]) deal with only aircraft design variables(for example, [wing span, aspect ratio, taper ratio, retreat angle]) deal with only electricity(for example, [])
- Mission class(define_mission.py)
to define the mission
- mission_tuning():
change the design variables in order to be equal to the public max takeoff weight
- Aircraft parameters class(aircraft_params.py)
to keep the aircraft parameters
return params => numpy array * Initialize 0 array
- Aircraft performance class(aircraft_performance.py)
to compute aerodynamic performance and weight
- aircraft aerodynamic performance class(aerodynamic_performance.py)
calculate L/D at cruise
- aircraft weight class(aircraft_weight.py)
- class weight params()
set_weight_params()
calculate overall weight return weight results => numpy array * Initialize 0 array
- special aircraft shape class()
Drone class(drone.py)
Blended Wing Body class(bwb.py)
Hyper sonic class(hyper_sonic.py)
Propeller class(propeller.py)
- Aircraft component class(aircraft_component.py)
- base component class format()
- __init__(aircraft_params_class)
weight = 0
aircraft_params_class
(needed?)
(x, y, z) => list
(join equipment index) => list
- run()
feedforward()
return None
- 1: MainWing class()
keep the main wing weight or params and calculate weight
- 2: Horizontal Wing()
keep the horizontal tail wing weight or params and calculate weight
- 3: Vertical Wing()
keep the vertical tail wing weight or params and calculate weight
- 4: Fuselage()
keep the fuselage weight or params and calculate weight
- 5: Main Landing Gear()
keep the main landing gear’s weight or params and calculate weight
- 6: Nose landing Gear()
keep the nose landing gear’s weight or params and calculate weight
- 7: Nacelle()
keep the nacelle’s weight or params and calculate weight
- 8: Engine Control()
keep the engine controller’s weight or params and calculate weight
- 9: Starter()
keep the starter’s weight or params and calculate weight
- 10: Fuel System()
keep the fuel system’s weight or params and calculate weight
- 11: Flight Control()
keep the flight controller’s weight or params and calculate weight
- 12: APU()
keep the APU weight or params and calculate weight
- 13: Instrument()
keep the instrument’s weight or params and calculate weight
- 14: Hydraulics()
keep the hydraulics’s weight or params and calculate weight
- 15: Electric()
keep the electricity weight or params and calculate weight (maybe this class is not needed for electric aircraft)
- 16: Avionic()
keep the avionic’s weight or params and calculate weight
- 17: Furnishing()
keep the furnishing’s weight or params and calculate weight
- 18: AirConditioner()
keep the air conditioner’s weight or params and calculate weight
- 19: Anti Ice()
keep the anti ice’s weight or params and calculate weight
- 20: Handling Gear()
keep the handling gear’s weight or params and calculate weight
- 21: Engine()
keep the engine weight but this class is not needed and designated engine_weight_class().result
- 22: Passenger Equip()
keep the main passenger equipment’s weight or params and calculate weight
- Engine parameters class(engine_params.py)
to keep the engine parameters return params => numpy array * Initialize 0 array
- Engine performance class(engine_performance.py)
to compute thermodynamic performance and weight
- engine thermodynamic class(engine_thermodynamic.py)
calculate SFC and Thrust at cruise and takeoff
- Note:
how to compute SFC and thrust is different between jet engine, propeller engine and electric engine
- <jet engine>
SFC = mf[kg/s] / Thrust Thrust = m[kg/s] * (V jet - V0) + (P jet * A jet - P0 * A inlet)
- <propeller engine>
bp = mf / Power power efficiency(eta p) Thrust = m * (V jet - V0) + (P jet * A jet - P0 * A inlet)
- <electric engine>
if the power for driving electric fan is supplied with jet engine, the computational method is same as jet engine and electric power can be acquired by multiplying the electric efficiency(conversion rate of heat to electricity)
if the power for driving electric fan is battery, the computational method is same as propeller engine and electric power have to be calculated in another module, which is specialized in electric performance
- design point class(engine_design_point.py)
return thermodynamic results at design point => numpy array
- off design point class(engine_off_design_point.py)
return thermodynamic results at off design point => numpy array
- engine weight class(engine_weight.py)
calculate engine weight(core weight, electric fan weight, electricity weight)
- core weight class(core_engine_weight.py)
return core weight results => numpy array * Initialize 0 array
- electric fan weight class(electric_fan_weight.py)
return electric fan weight results => numpy array * Initialize 0 array
- electricity weight class(electricity_weight.py)
- special fuel engine class()
- battery class()
calculate electric efficiency and available electric power(W or KW)
if possible, consider the thermal management
- fuel cell class()
calculate electric efficiency and available electric power(W or KW)
if possible, consider the thermal management
- biological fuel class()
calculate electric efficiency and available electric power(W or KW)
- solar battery class()
calculate electric efficiency and available electric power(W or KW)
return electricity weight => numpy array * Initialize 0 array
- Aircraft view class(view_aircraft.py)
to plot the aircraft’s view based on the given parameters
- class AircraftView(object):
- __init__(aircraft_component_class, engine_component_class, special_air_shape_class):
3D aircraft coordinates array
- construct_x():
compute 3D coordinates at each component and determine the joint position
- show():
describe 3D plot aircraft view with engine
- Engine view class(view_engine.py)
to plot the engine’s view based on given parameters
- class EngineView(object)
- __init__(engine_component_class, special_fuel_engine_class, bli_class):
3D engine coordinates array
- construct_x():
compute 3D coordinates at each component and determine the join position
- show():
describe 3D plot propulsion system’s view
- Baseline Estimation class(estimate_baseline.py)
to define the scale factor for aircraft design(from public value)
- DataBase manage class(DataBase/database_driven.py)
to manage the database values
- Cost Estimation class(cost_estimate.py)
to estimate the flight cost and evaluate the financial effect
Engine Component class(engine_component.py)
Implementation concept
- class EngineComponent():
- __init__(name):
name
component index number
next component index number
- calc_design_point_performance(design_point_result_arr, efficient_arr, settings_arr, *args):
calculate physical values(Pressure, temperature, Area) at design point
return design_point_result_arr
- calc_off_design_point_performance(off_design_point_result_arr, off_efficient_arr, off_settings_arr, *args):
calculate physical values(Pressure, temperature, Area) at off design point
return off_design_point_result_arr
- calc_diameter(engine_diameter_result_arr, design_point_result_arr, engine_settings_arr, *args):
calculate diameter from area at design point
return engine_diameter_result_arr or None
- calc_weight(engine_weight_result_arr, engine_settings_arr, *args):
calculate engine weight fron engine diameter
return engine_weight_result_arr
- –component class index number–
0:Inlet() 10:Fan() 20:LPC() 25:HPC() 30:CC() 40:HPT() 41:HPTCool() 45:LPT() 46:LPTCool() 50:CoreOut() 70:AfterBurner() 80:Nozzle() 90:Jet() 18:FanNozzle() 19:FanJet() 100:FanElectricInlet() 110:FanElectric() 118:FanElectricNozzle() 119:FanElectricJet()
Optimization module
- Gradient descent class()
main function: class object.optimize()
- Evolutionary Algorithm class()
- NSGA2()
Non dominated sort Genetic Algorithm
main function: class object.optimize()
- PSO()
Partial Swarm Optimization
main function: class object.optimize()
- CMAES()
Covariance Matrix Adaptation Evolution Strategy main function: class object.optimize()
Analysis module
plot contour
plot result by jupyter notebook
Self driving module
1.construct the aircraft or drone
2.SLAM or Reinforcement Learning
Engine Performance
- <off design point>
***Low Pressure Part***
0.assume the turnover rate of low pressure compressor compared to that at design point
1.from inlet to lpc, calculate the physics values of all components
***High Pressure Part***
2.assume the turnover rate of high pressure compressor compared to that at design point
3.from hpc to hptcool, calculate their physics values and adjust the turnover rate in order to balance the power of high pressure axis
—End High Pressure Part—
4.from lptcool to nozzle, calculate physics values and adjust the turnover rate in order for nozzle area to be equal to that at design point
—End Low Pressure Part—
5.finish the engine performance part at off design point and record the turnover rates of high and low pressure compressor
Aircraft Performance
Objective: L/D
- 1.static method
polar curve fitting
- 2.accumulative method
compute the lift and the each drag value individually and finally summarize them
- <Lift>
L = 0.5 * rou(density) * V(Velocity of aircraft) ** 2 * S(wing area) * CL(lift coefficient)
constant
AR: aspect ratio(given from input parameters)
beta: sqrt(1 - mach number ** 2)
eta: 0.95
F: cross sectional coefficient, 1.07 * (1.0 + (fuselage diameter / wing width)) ** 2
S_exposed:wing area which is exposed to outer space
S_ref: wing area
subsonic case(Mach number <= 0.9)
CL = (2 * pi * AR) / (2.0 + sqrt(4.0 + AR ** 2 * beta ** 2 / eta ** 2 * (1.0 + tan(theta * pi / 180)) ** 2 / beta ** 2) * (S_exposed / S_ref) * F
mixture of subsonic and hyper sonic case(0.9 <= Mach number <= 1.2)
CL follows the drag curve and In this module, consider it as quadratic function
—Detail—
slope_of_lift_left = 9.158680497060704
slope_of_lift_right = 6.030226891555273
a_coef = -(slope_of_lift_right - slope_of_lift_left) / (0.2 ** 2 - 0.1 ** 2)
b_coef = slope_of_lift_left + 0.1 ** 2 * a_coef
slope_of_lift = -a_coef * (current_mach - 1) ** 2 + b_coef
hyper sonic case(Mach number >= 1.2)
CL = 4.0 / beta(constant)
- <Drag>
- types:
D = 0.5 * rou(density) * V(Velocity) ** 2 * S(wing area) * CD(drag coefficient)
CD = CD0 + CDi
CD0 = sum(Cf(i) * Swet(i) / Sref)
- <induction drag(CDi)>
CDi = CL ** 2 / (pi * e * AR)
*e is dependent on retreat angle
e = 1.78 * (1 - 0.045 * AR ** 0.68) - 0.64(retreat angle < 30)
e = 4.61 * (1.0 - 0.045 * AR ** 0.68) * (np.cos(self.init_airshape_class.theta)) ** 0.15 - 3.1(retreat angle >= 30)
- <wing drag(CD0)>
- 1.shape drag
necessary parameters: Reynold number, surface roughness, representative length, mach number
return Cf(shape drag)
- 2.misc drag
necessary parameters: angle of after fuselage, diameter of after fuselage
return Cf(misc drag)
- 3.L&P drag
necessary parameters: the rate which L&P drag occupies in wing drag
return Cf(L&P drag)
- 4.wave drag(hyper sonic case)
necessary parameters: fuselage diameter, fuselage length, retreat angle of main wing, mach number
return Cf(wave drag)
UseCase for IAEA
- Implementation of aircraft design
tuning the baseline model
input design variables
calculate the objective function
plot the shape parameters at plotter library and save them(csv file)
- Implementation of optimization of aircraft design
tuning the baseline model
decide the optimization method
optimize the objective function
get the optimal solution and save them
plot the shape parameters
- Implementation of aircraft simulation
set the optimal design variables
construct 2D aircraft
set the city obstacle or landmark
apply RL(Reinforcement Learning) or SLAM(Simultaneous Localization and Mapping) in order to find the better path
plot the explored path at graph


submodule¶
Integrate¶
Kevin Fung - Github Alias: kkf18
Stage 1: nested class to integrate and clean data. This module contains the integration and cleaning features for messy oil well data. Imported csv data must be in one of two formats:
Format1: |datetime|tagname|value| Format2: |datetime|feature1|feature2|feature3|
-
class
mlflowrate.backend.subclasses.integrate.
Integrate
(dfs)¶ First of nested backend: integrate raw messy data into consistent, cleaned Spark DataFrames.
This class provides the tools for cleaning and reorganising data. The user must understand what the data consists of and these are provided by the plotting and status features.
Users must understand that the imported data initially is in a Spark DataFrame, but a corresponding dictionary format is created upon instantiation of this class. The dictionary format removes the inconsistency sampling of features in Spark DataFrames.
-
_track_org
¶ dictionary of boolean values: if true both Spark DataFrame and Dictionary formats are consistent to each other.
- Type
dict
-
_formats
¶ list of organisational formats
- Type
list
-
add_data
(add_dfs)¶ Add a dictionary of new dfs into the class: {name:df, name:df, name:df etc.}
- Parameters
add_dfs (dict) – Dictionary of Spark DataFrames.
-
clean_data
(data, null_col=None, remove_nulls=False, char_col=None, remove_char=None, zeros_col=None, remove_zeros=False, avg_over=None, is_dict=False)¶ Multi-functional method to clean data.
If column arguments are not specified. Method will assume the entire DataFrame.
- Parameters
data (str) – name of the data to clean.
null_col (str) – name of the column in data to remove null from.
remove_nulls (bool) – option to remove nulls.
char_col (str) – name of the column in data to remove char from.
remove_char (bool) – option to remove char
zeros_col (str) – name of the column in data to remove zeros from.
remove_zeros (bool) – option to remove zeros.
avg_over (str) – periodicity for averaging: “day”, “week”, “month”
is_dict (bool) – special option to select for averaging if Spark DataFrame is inconsistent.
-
drop_col
(data, *features)¶ Remove a number of columns from Spark DataFrame.
- Parameters
data (str) – name of data to drop columns.
*features – argument list of the features to drop in data.
-
edit_col
(data, feature, **kwargs)¶ Multi-functional method to edit a specific column in data.
- Parameters
data (str) – name of the data.
feature (str) – name of the specific column in data.
**kwargs – Options for editing the columns of data: typ, newname, std
-
get_data
()¶ Returns the formatted dictionaries of Spark DataFrames and Dictionaries.
- Returns
Dictionaries of Spark DataFrames and Dictionaries.
-
merge_data
(newname, first, second, axis=0)¶ Append Spark DataFrames vertically or horizontally.
- Parameters
newname (str) – new name of the merged DataFrames
first (str) – name of data to join from.
second (str) – name of data to join to.
axis (int) – Direction of append.
-
organise_data
(name, dfmat, **kwargs)¶ Key method for integrating mixed data into consistent Spark DataFrame formats.
- Users are provided three different options to format the disorganised data:
- date_tag_val_col: If the Spark DataFrame has only three columns |date|tagname|value|, then
the user is provided options to sort data by distinct features, and further categorically by oil wells. An inconsistent Spark DataFrame and corresponding Dictionary format is produced.
mult_col: Make a corresponding Dictionary format from a Spark DataFrame. dict_col: Make a corresponding and consistent Spark DataFrame from a Dictionary format.
- Parameters
name (str) – Name of data to format.
dfmat (str) – Options to format data.
**kwargs – Further args for sorting date, tagname, and value data: distinct_oilwells, change_sensor_names.
-
select_col
(data, *features)¶ Keep a number of columns from Spark DataFrame to be the Spark DataFrame.
- Parameters
data (str) – name of data to keep columns.
*features – argument list of the features to keep in data.
-
set_organised
(name)¶ Data which is organised will be put into the out_dfs/dicts for the next phase.
- Parameters
name (str) – name of data to be set as organised.
-
show
(data)¶ Display the data (Spark DataFrame) contained in Integrate.
- Parameters
data (str) – Name of the data.
-
status
(data=None)¶ Display the status of all the data in the current stage or the status of a specific data
- Parameters
data (str) – Name of data to check the status of.
-


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{% import '/admin/model/inline_list_base.html' as base with context %} {% import '/admin/lib.html' as lib with context %} {% import '_macros.html' as macros %} {% macro render_file_field(field) %} {% set model = field.object_data %}