A sequence of nodes.
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#include <nodeseq.h>
A sequence of nodes.
Definition at line 19 of file nodeseq.h.
◆ ~nodeseq_t()
| nodeseq_t::~nodeseq_t |
( |
void |
| ) |
|
|
inline |
destructor
Definition at line 32 of file nodeseq.h.
void clean(void)
clean up: delete all nodes, reset globals
◆ add()
add node p; take as parent the node holding ball a. the deme of p is changed to match that of a
Definition at line 167 of file nodeseq.h.
name_t deme(void) const
view deme
ball_t * green_ball(void) const
pointer to my green ball
name_t deme(void) const
view deme
void swap(ball_t *a, ball_t *b)
swap balls a and b, wherever they lie
◆ bytesize()
| size_t nodeseq_t::bytesize |
( |
void |
| ) |
const |
|
inline |
size of serialized binary form
Definition at line 40 of file nodeseq.h.
41 size_t s =
sizeof(size_t);
42 for (
node_it i = begin(); i != end(); i++)
43 s += (*i)->bytesize();
std::list< node_t * >::const_iterator node_it
◆ clean()
| void nodeseq_t::clean |
( |
void |
| ) |
|
|
inlineprivate |
clean up: delete all nodes, reset globals
Definition at line 24 of file nodeseq.h.
25 for (
node_it i = begin(); i != end(); i++)
delete *i;
◆ colored()
Get all balls of a color.
Definition at line 133 of file nodeseq.h.
135 for (
node_it i = begin(); i != end(); i++) {
136 for (
ball_it j = (*i)->begin(); j != (*i)->end(); j++) {
137 if ((*j)->is(col)) p->insert(*j);
A pocket is a set of balls.
std::set< ball_t *, ball_order >::const_iterator ball_it
◆ comb()
| void nodeseq_t::comb |
( |
void |
| ) |
|
|
inline |
pass through the sequence, dropping superfluous nodes i.e., those holding just one ball that is green.
Definition at line 200 of file nodeseq.h.
201 for (
node_rev_it i = crbegin(); i != crend(); i++) {
202 if ((*i)->size() == 1 && (*i)->holds(
green)) {
203 swap((*i)->last_ball(),(*i)->green_ball());
208 if ((*j)->dead_root()) {
void destroy_node(node_t *p)
remove a dead root node
std::list< node_t * >::const_reverse_iterator node_rev_it
std::list< node_t * >::iterator node_nit
◆ compare()
Order relation among nodes. Nodes should be ordered by time, then by unique name.
Definition at line 101 of file nodeseq.h.
◆ dawn()
| slate_t nodeseq_t::dawn |
( |
void |
| ) |
const |
|
inlineprivate |
Earliest time in the sequence.
Definition at line 122 of file nodeseq.h.
123 return (empty()) ? R_NaReal : front()->slate;
◆ describe()
| std::string nodeseq_t::describe |
( |
void |
| ) |
const |
|
inline |
human-readable info
Definition at line 254 of file nodeseq.h.
256 for (
node_it p = begin(); p != end(); p++) {
257 o += (*p)->describe();
◆ destroy_node()
| void nodeseq_t::destroy_node |
( |
node_t * |
p | ) |
|
|
inline |
remove a dead root node
Definition at line 192 of file nodeseq.h.
194 err(
"in '%s': invalid call.",__func__);
bool dead_root(void) const
◆ drop()
| void nodeseq_t::drop |
( |
ball_t * |
a | ) |
|
|
inline |
drop the black ball 'a' and the node if either (1) the node becomes thereby a dead root, or (2) the node's pocket becomes thereby empty.
Definition at line 175 of file nodeseq.h.
177 err(
"in '%s': inconceivable! (color: %s)",__func__,colores[a->
color]);
bool is(color_t c) const
is a given ball of the given color?
node_t * holder(void) const
in whose pocket do I lie?
Encodes a genealogical node.
◆ dusk()
| slate_t nodeseq_t::dusk |
( |
void |
| ) |
const |
|
inlineprivate |
Latest time in the sequence.
Definition at line 126 of file nodeseq.h.
127 return (empty()) ? R_NaReal : back()->slate;
◆ newick()
| std::string nodeseq_t::newick |
( |
slate_t |
t | ) |
const |
|
inline |
put genealogy at time t
into Newick format.
Definition at line 282 of file nodeseq.h.
285 for (
node_it i = begin(); i != end(); i++) {
286 if ((*i)->is_root()) {
287 o += (*i)->newick(t,te) +
";";
slate_t dawn(void) const
Earliest time in the sequence.
◆ ntime()
| size_t nodeseq_t::ntime |
( |
slate_t |
t | ) |
const |
|
inline |
Number of distinct timepoints.
Definition at line 143 of file nodeseq.h.
145 for (
node_it i = begin(); i != end(); i++) {
146 if (t < (*i)->slate) {
◆ operator+=()
merge two node sequences
Definition at line 109 of file nodeseq.h.
static bool compare(node_t *p, node_t *q)
◆ repair_owners()
| void nodeseq_t::repair_owners |
( |
std::unordered_map< name_t, ball_t * > & |
names | ) |
|
|
inlineprivate |
Needed in deserialization. This function repairs the links green balls and their names.
Definition at line 82 of file nodeseq.h.
83 std::unordered_map<name_t,ball_t*>::const_iterator n;
84 for (
node_it i = begin(); i != end(); i++) {
86 n = names.find(p->
uniq);
87 if (n != names.end()) {
91 err(
"in '%s': cannot find node %ld",__func__,p->
uniq);
Balls function as pointers.
◆ sort()
| void nodeseq_t::sort |
( |
void |
| ) |
|
|
inline |
order nodes in order of increasing time
Definition at line 115 of file nodeseq.h.
116 std::list<node_t*>::sort(
compare);
◆ structure()
| SEXP nodeseq_t::structure |
( |
void |
| ) |
const |
|
inline |
R list description.
Definition at line 271 of file nodeseq.h.
273 PROTECT(Nodes = NEW_LIST(size()));
275 for (
node_it i = begin(); i != end(); i++) {
276 SET_ELEMENT(Nodes,k++,(*i)->structure());
◆ swap()
swap balls a and b, wherever they lie
Definition at line 157 of file nodeseq.h.
161 p->erase(a); q->insert(a); a->
holder() = q;
162 q->erase(b); p->insert(b); b->
holder() = p;
◆ trace_lineage()
trace back a single lineage. this results in the deme slot for all green balls along the lineage of 'b' begin replaced by the lineage of 'b'.
Definition at line 221 of file nodeseq.h.
223 while (p->
lineage() == null_lineage) {
name_t lineage(void) const
view lineage
node_t * parent(void) const
◆ trace_lineages()
| void nodeseq_t::trace_lineages |
( |
void |
| ) |
|
|
inline |
trace back all sample lineages. this results in the deme slots of all green balls being replaced by the unique names of the lineages they trace.
Definition at line 234 of file nodeseq.h.
239 for (
node_it i = begin(); i != end(); i++) {
241 for (
ball_it j = p->begin(); j != p->end(); j++) {
void trace_lineage(ball_t *b, name_t u)
◆ yaml()
| virtual std::string nodeseq_t::yaml |
( |
std::string |
tab = "" | ) |
const |
|
inlinevirtual |
human- & machine-readable info
Reimplemented in genealogy_t.
Definition at line 262 of file nodeseq.h.
264 std::string t = tab +
" ";
265 for (
node_it p = begin(); p != end(); p++) {
266 o += tab +
"- " + (*p)->yaml(t);
◆ operator>> [1/2]
binary serialization
Definition at line 47 of file nodeseq.h.
48 size_t nnode = G.size();
49 memcpy(o,&nnode,
sizeof(
size_t)); o +=
sizeof(size_t);
50 for (
node_it i = G.begin(); i != G.end(); i++) {
◆ operator>> [2/2]
binary deserialization
Definition at line 56 of file nodeseq.h.
58 std::unordered_map<name_t,node_t*> node_names;
59 std::unordered_map<name_t,ball_t*> ball_names;
61 memcpy(&nnode,o,
sizeof(
size_t)); o +=
sizeof(size_t);
62 node_names.reserve(nnode);
63 ball_names.reserve(nnode);
64 for (
size_t i = 0; i < nnode; i++) {
68 node_names.insert({p->
uniq,p});
70 for (
node_it i = G.begin(); i != G.end(); i++) {
void repair_owners(std::unordered_map< name_t, ball_t * > &names)
void trace_lineages(void)
The documentation for this class was generated from the following file:


Rendered Math URL Generator
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Input the formula on the left, the rendered formula will be displayed on the right. The renderer used ("render.githubusercontent.com") is quite slow so don't expect instant updates.


IIT Mandi has established modern technological laboratories for BTech,PG, and PhD students. The technology and equipment are implemented with our student’s needs in mind as they pursue a world-class education supplemented by superior learning methods. All year long, our amphitheatre auditoriums are filled with fresh competitions, celebrations, and activities for our ...students. The libraries of IIT Mandi, which is located on both the North and South Campuses, provides books, periodicals, magazines, and other materials to staff and students. There are multiple Reading rooms on campus which provide the perfect environment for our students to delve into their reading and studying, especially during challenging exam times.
The cornerstone of our prestigious institution was laid in Kamand, the home of IIT Mandi's permanent campus, on February 24, 2009. Since then it has always been a path to development and achievement of new goals. IIT Mandi is located in the Kamand Valley. The area of IIT Mandi is 538 hectares, of which about 200 hectares are flat ... land while the rest are mountainous. IIT Campus is spread over North and South campuses in Kamand. North and south campuses are contiguous and interconnected with roads and walkways. The innovative avant-garde architecture is designed with landscape volatility in mind. There are separate dormitories for girls and boys with up-to-date maintenance along with a sports room, swimming pool, 24/7 wifi and electricity. We at IIT Mandi are always committed to building sustainable and environmentally friendly initiatives. The Botanical Gardens managed by our experienced and motivated team have housed several species of flora and fauna such as apples, deodars, Himalayan Yew, lychees.
The mess halls at IIT Mandi offer meals three times a day along with scrumptious snacks in between for the students, staff and faculty who subscribe to the mess facility. There are four mess halls, Pine and Oak at North campus, Cedar and Maple at south campus. The menu is determined by the student mess committee taking into account the nutrient intake of the people at the IIT Mandi. Locally available vegetables not only support our hunger, but also the nearby community.


Accessible Rich Internet Applications (ARIA) defines ways to make Web content and Web applications (especially those developed with AJAX and JavaScript) more accessible to people with disabilities.
Have you gone to your favorite sites, closed your eyes, and turned on Voiceover (or other screenreaders)?
How did you feel? Did you feel like you got the same context as a sighted user? Did you feel confused? Irritated? Happy?
Are there elements of my page that rely on Visual Cues to communicate Meaning?
Are there categories on a page that need context of what they are categorizing?
Are you forced to use
's
in your CMS?
role

's
article, banner, button, form, main, navigation, region
role
example
 ...
aria-describedby
aria-labelledby

This is additional label info

<form action="">
Normal Label Example
<input id="basic" name="basic">
...
Labelled By Example
<input id="labelled" name="labelled" aria-labelledby="labelled-label additional-label">
...
Described By Example
<input id="described" name="described" aria-describedby="described-note">
This is a note about the field
...
Labelled By and Described By Example
<input id="labelled-described" name="labelled-described" aria-labelledby="labelled-described-label additional-label" aria-describedby="labelled-described-note">
This is a note about the field
</form>
aria-expanded
true, false
aria-expanded
example
<input class="search-input" type="text" id="search-query" placeholder="Search Twitter" name="q" autocomplete="off" spellcheck="false" aria-autocomplete="list" aria-expanded="true" aria-owns="typeahead-dropdown-1" dir="ltr" style="direction: ltr; text-align: left;">
aria-expanded
example
<input class="search-input" type="text" id="search-query" placeholder="Search Twitter" name="q" autocomplete="off" spellcheck="false" aria-autocomplete="list" aria-expanded="false" aria-owns="typeahead-dropdown-1" dir="ltr" style="direction: ltr; text-align: left;">
aria-haspopup
true, false
aria-haspopup
example
 ...
aria-hidden
true, false
aria-hidden
example
Home
Home
Home, current page.
New Tweets available.
aria-label
aria-label
example

 ...

aria-required
required
attribute.true, false


Performance of gateways.
Active Classifiers.
Registered Instances.
Exposed Classifiers.
Active Clients.
Registered Content.
Host Health Status.


[ArXiv'21] Zhuangbin Chen, Jinyang Liu, Wenwei Gu, Yuxin Su, and Michael R. Lyu. Experience Report: Deep Learning-based System Log Analysis for Anomaly Detection, arXiv preprint, arXiv:2107.05908 (2021).
[ASE'19] Jinyang Liu, Jieming Zhu, Shilin He, Pinjia He, Zibin Zheng, Michael R. Lyu. Logzip: Extracting Hidden Structures via Iterative Clustering for Log Compression, in Proc. of IEEE/ACM International Conference on Automated Software Engineering (ASE), 2019.
[ICSE'19] Jieming Zhu, Shilin He, Jinyang Liu, Pinjia He, Qi Xie, Zibin Zheng, Michael R. Lyu. Tools and Benchmarks for Automated Log Parsing, in Proc. of International Conference on Software Engineering (ICSE), 2019.
[FSE'18] Shilin He, Qingwei Lin, Jian-Guang Lou, Hongyu Zhang, Michael R.Lyu, Dongmei Zhang. Identifying Impactful Service System Problems via Log Analysis, in Proc. of the 26th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE), 2018.
[ASE'18] Pinjia He, Zhuangbin Chen, Shilin He, Michael R. Lyu. Characterizing the Natural Language Descriptions in Software Logging Statements, in Proc. of the 33rd ACM/IEEE International Conference on Automated Software Engineering (ASE), 2018.
[TDSC'18] Pinjia He, Jieming Zhu, Shilin He, Jian Li, Michael R. Lyu, Towards Automated Log Parsing for Large-Scale Log Data Analysis, IEEE Transactions on Dependable and Secure Computing (TDSC), 2018.
[ICWS'17] Pinjia He, Jieming Zhu, Zibin Zheng, and Michael R. Lyu. Drain: An Online Log Parsing Approach with Fixed Depth Tree, in Proc. of the 24th International Conference on Web Services (ICWS), 2017.
[DSN'16] Pinjia He, Jieming Zhu, Shilin He, Jian Li, Michael R. Lyu. An Evaluation Study on Log Parsing and Its Use in Log Mining, in Proc. of IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), 2016.
[ISSRE'16] Shilin He, Jieming Zhu, Pinjia He, Michael R. Lyu. Experience Report: System Log Analysis for Anomaly Detection, in Proc. of IEEE International Symposium on Software Reliability Engineering (ISSRE), 2016.
[ICSE'15] Jieming Zhu, Pinjia He, Qiang Fu, Hongyu Zhang, Michael R. Lyu, Dongmei Zhang. Learning to Log: Helping Developers Make Informed Logging Decisions, in Proc. of International Conference on Software Engineering (ICSE), 2015.
The ultimate goal of LogPAI is to build an open-source AI platform for automated log analysis. Towards this goal, we benchmark a set of research work as well as release open datasets and tools for log analysis research. With both datasets and source code available, we hope that our LogPAI project could benefit both researchers and practitioners in the community.
Professor, CUHK
ACM Fellow, IEEE Fellow, AAAS Fellow
Researcher, Huawei Noah's Ark Lab
Ph.D., CUHK
Assistant Professor, CUHKSZ
Ph.D., CUHK
Researcher, MSRA
Ph.D., CUHK
Ph.D. Candidate, CUHK
Ph.D. Candidate, CUHK
Ph.D. Candidate, CUHK
Assistant Professor, Sun Yat-Sen University
Ph.D., CUHK
Professor,
Sun Yat-Sen University
Ph.D., CUHK


Adding the First Term (Hierarchical Vocabulary)
How to add the first term to a hierarchical vocabulary using the Taxonomy Manager module. Important. It is recommended that you name this first term the same as the Vocabulary name. This allows you to create a hierarchical tree of terms. Failure to set up terms in this way will restrict you to only one top level parent term.
- Navigate to Admin > Advanced Settings > Taxonomy - OR - Go to a Taxonomy Manager module.
- Click the Edit link beside the vocabulary for the new terms. This opens the Edit Vocabulary page.
- Click the Add New button. This displays the Create New Term section.
- In the Create New Term section, complete these fields:
- In the Name text box, enter the vocabulary name.
- In the Description text box, enter a description for this term. Tip: Copying the Vocabulary description is suitable.
- Click the Save button.
- The newly added term is now displayed in the Terms section. You can now add additional terms. See "Adding Additional Terms (Hierarchical Vocabulary)"
The newly added first hierarchical term


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Our project is opensource here.


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You will begin to realise why this exercise is called the Dickens Pattern with reference to the ghost showing Scrooge some different futures.
Discover nowHere, I focus on a range of items and features that we use in life without giving them a second thought. such as Coca Cola. Dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco.
View full detailsAt about this time of year, some months after New Year’s resolutions have been made and kept, or made and neglected.
Who are in extremely love with eco friendly system.
It is very easy to start smoking but it is an uphill task to quit it. Ask any chain smoker or even a person.
When someone does something that they know that they shouldn’t do, did they.
For the individuals
You may be a skillful, effective employer but if you don’t trust your personnel and the opposite, then the chances of improving and expanding the business


Sadness expressed as historic 129-year-old Clackmannanshire golf club is to shut
by Chris MarzellaA dwindling membership has caused the closure of Clackmannanshire’s oldest golf club.
Dollar Golf Club members voted at their annual general meeting on Monday to wind up the club and it will shut on December 31.
A drop in the number of members and an aging membership prompted the move.
A full membership at the 129-year-old club currently costs £364 and the club has around 120 members.
Sadness was expressed following Monday’s decision.
Finance convener Scott Maxwell, who is in his 70s and has been a member of the club for more than 40 years, said: “It’s a hugely sad day.
“The lack of membership means we have not been financially viable and are losing money.
“A lack of interest in golf and an aging membership are the main reasons why the decision was taken.
“Dollar is a notoriously difficult and hilly golf course and I think a lot of the older members have found it quite hard on their knees.
“There are also several other golf clubs in Clackmannanshire and just not enough players in the area.”
Two jobs are to be lost as a result of the closure.
Full time greenkeepers Tony Leech and Willie Glass will be left without work. Mr Maxwell added: “Unfortunately two people will lose their jobs. Tony and Willie have been with us for a number of years and have worked very hard at the club so that’s unfortunate.”
All other positions at the club are filled by volunteers.
Dollar Golf Club was founded by a group of local men in 1890, when they opened up a nine-hole course at Market Park.
With the annual subscription for its 19 members set at 7/6d, it was on fairly flat low-lying ground which is in marked contrast to its present hillside layout.
Dollar Ladies was founded in 1893, sharing the course with the men.
That lasted for four years before the men moved to a new nine-hole course on Gloom Hill near Castle Campbell.
They joined again in 1906 and it was a woman, the Countess of Mar and Kellie, who drove off to open the first 18-hole course in Clackmannanshire.
Several big name golfers have played the course over the years.
In June 1910 a professional match was held featuring Open winner Sandy Herd; Open winner and Ryder Cup captain Ted Ray; Open runner-up Tom Ball ; and Open winner and Ryder Cup captain George Duncan.
In October this year, the Observer reported on the last week of the 2019 summer season with the gents’ closing meeting with the traditional match between teams of the Captain and Vice-Captain.
With both officials being unavailable on the day, acting captain Drew Ure and acting vice-captain Charlie Murray stepped in.


Write a function map_search_pred(Map, Pred) that returns the first element {Key,Value} in the map for which Pred(Key, Value) is true.
map_search_pred(Map, Pred) -> M = [{Key, Value} || {Key, Value} <- maps:to_list(Map), Pred(Key, Value) =:= true], case length(M) of 0 -> {}; _ -> lists:nth(1, M) end.
make(0, M, _) -> M; make(K, M, I) -> make(K-1,maps:put(I,I+1,M),I+2).
test(K) -> Map = make(K, #{}, 1), Map1 = Map#{0 => 0}, Map2 = Map#{123456789 => 123456789}, List1 = maps:to_list(Map1), List2 = maps:to_list(Map2), J1 = timer:tc(?MODULE, map_search_pred,[Map1,fun(X,Y) -> X =:= Y end]), J2 = timer:tc(?MODULE, map_search_pred,[Map2,fun(X,Y) -> X =:= Y end]), ...
> The results of this first test puzzled me at first. But hang on, I > know that a) > **performance measurement is difficult** b) **My intuition > about performance is always wrong**.
J3 = timer:tc(?MODULE, map_search_pred1, [Map2, fun(X, Y) when X =:= Y -> throw({X,Y}); (_,_) -> false end]),
map_search_pred1(A, B) -> (catch map_search_pred(A,B)).
{length,20000}, {maps_at_start,{6479,{0,0}}}, {maps_at_end,{2327,{123456789,123456789}}}, <- 1) should be the same maps_at_start {maps_thrown,{1814,{123456789,123456789}}}, <- 2) it is faster {maps_foldl,{2486,{123456789,123456789}}}, {lists_start,{2,{0,0}}}, {lists_end,{1221,{123456789,123456789}}}}
> The notion of ``order'' in a map is unclear. I know that maps are > printed in lexical order, but I don't know if they are stored > internally in the same order as which they are printed. > And they might perform differently if the maps have > a small or large number of elements.
> and lists in Erlang aren't even `lists`. They are really `stacks` - > but that's another story, and changing the name would not be a good > idea.
fold(Fun, In it, Map) when is_function(Fun,3), is_map(Map) -> lists:fold(fun({K,V},A) -> Fun(K,V,A) end,In it,maps:to_list(Map)).
find_first([H|T], Pred) -> case Pred(H) of true -> H; false -> find_first(T, Pred) end; find_first([], _) -> {}.
> p1:test(20000). {length,20000}, {maps_at_start,{6215,{0,0}}}, {maps_at_end,{2253,{123456789,123456789}}}, {maps_thrown,{1827,{123456789,123456789}}}, {maps_fold,{2698,{123456789,123456789}}}, {lists_start,{3,{0,0}}}, {lists_end,{1229,{123456789,123456789}}}}
-module(maps_timings). -compile(export_all). map_search_pred(Map, Pred) -> M = [{Key, Value} || {Key, Value} <- maps:to_list(Map), Pred(Key, Value) =:= true], case length(M) of 0 -> {}; _ -> lists:nth(1, M) end. map_search_pred1(A, B) -> (catch map_search_pred(A,B)). test(K) -> Map = make(K, #{}, 1), Map1 = Map#{0 => 0}, Map2 = Map#{123456789 => 123456789}, List1 = maps:to_list(Map1), List2 = maps:to_list(Map2), J1 = timer:tc(?MODULE, map_search_pred,[Map1,fun(X,Y) -> X =:= Y end]), J2 = timer:tc(?MODULE, map_search_pred,[Map2,fun(X,Y) -> X =:= Y end]), J3 = timer:tc(?MODULE, map_search_pred1, [Map2, fun(X, Y) when X =:= Y -> throw({X,Y}); (_,_) -> false end]), J4 = timer:tc(?MODULE, faster, [Map2, fun(X, Y, _) when X =:= Y -> throw({X,Y}); (_,_, A) -> A end]), J5 = timer:tc(?MODULE, find_first, [List1, fun({X, Y}) -> X =:= Y end]), J6 = timer:tc(?MODULE, find_first, [List2, fun({X, Y}) -> X =:= Y end]), { {length,K}, {maps_at_start,J1}, {maps_at_end,J2}, {maps_thrown,J3}, {maps_foldl,J4}, {lists_start,J5}, {lists_end,J6}}. make(0, M, _) -> M; make(K, M, I) -> make(K-1,maps:put(I,I+1,M),I+2). faster(Map, Fun) -> case catch (maps:fold(Fun, [], Map)) of [] -> {}; Other -> Other end. find_first([H|T], Pred) -> case Pred(H) of true -> H; false -> find_first(T, Pred) end; find_first([], _) -> {}.


Version Control
After making the website, we were tasked to document how to retract/extract lost data using git.
Process
When you accidentally delete a paragraph of text or want to “undo” whatever mistake you did but have already pushed it to the repository, you can follow these steps:
|
Here is the recovered text as of shown in the picture below:


AAA Jokes - Mailing List and archives
Effective Daily Affirmations
As I let go of my shoulds and feelings of guilt, I can get in touch with my Inner Sociopath.
I have the power to channel my imagination into ever-soaring levels of suspicion and paranoia.
I assume full responsibility for my actions, except the ones that are someone else's fault.
I no longer need to punish, deceive or compromise myself. Unless, of course, I want to stay employed.
In some cultures what I do would be considered normal.
Having control over myself is nearly as good as having control over others.
My intuition nearly makes up for my lack of good judgment.
I can change any thought that hurts into a reality that hurts even more.
I honor my personality flaws, for without them I would have no personality at all.
Joan of Arc heard voices too.

I need not suffer in silence while I can still moan, whimper and complain.
As I learn the innermost secrets of the people around me, they reward me in many ways to keep me quiet.
When someone hurts me, forgiveness is cheaper than a lawsuit. But not nearly as gratifying.
The first step is to say nice things about myself. The second, to do nice things for myself. The third, to find someone to buy me nice things.

I am at one with my duality.
I will strive to live each day as if it were my 40th birthday.
Only a lack of imagination saves me from immobilizing myself with imaginary fears.
I honor and express all facets of my being, regardless of state and local laws.
Today I will gladly share my experience and advice, for there are no sweeter words than "I told you so."
False hope is nicer than no hope at all.
A good scapegoat is nearly as welcome as a solution to the problem.
Just for today, I will not sit in my living room all day watching TV. Instead I will move my TV into the bedroom.
Why should I waste my time reliving the past when I can spend it worrying about the future?
The complete lack of evidence is the surest sign that the conspiracy is working.
I am learning that criticism is not nearly as effective as sabotage.
Becoming aware of my character defects leads me to the next step - blaming my parents.
To have a successful relationship I must learn to make it look like I'm giving as much as I'm getting.
To understand all is to fear all.
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New S.F. Cable Car Introduced
SAN FRANCISCO (AP) -- They just don't make cable cars like they
used to -- except, of course, in San Francisco.
Working from dog-eared blueprints and plans kept only in their
heads, four carpenters spent 3,000 hours making a brand-new cable
car that's set to hit the rails Monday.
The new, green and white No. 9 car was crafted by hand, from its
bronze-alloy bell to its Alaskan cedar roof. It will carry its
first passengers exactly 100 years after the death of the father of
cable cars, Andrew Hallidie.
One hundred also is the car's life expectancy because the San
Francisco cable cars are so solid, made almost entirely of oak, and
are so painstakingly maintained.
''I think the number one reason they last longer than street
cars is that they're hand made,'' says 45-year-old Bob Harris, a
carpenter who has crafted cable cars for 22 years. ''There's
special care in everything. Plus, they have no motor parts to wear
out.''
San Francisco's first cable cars started wearing out in the
1980s, and the Municipal Railway workshop has been crafting new
ones just about every other year.
According to the San Francisco Cable Car museum, Hallidie
hatched upon the innovative idea of making street cars that grab
constantly moving underground cables for power after seeing a
horse-drawn streetcar accident in 1869 in which five horses were
killed.
In the following years, cable car systems bloomed in cities all
over the world, only to be eclipsed in the 1940s by electrical
street cars, subways and buses. While San Francisco's routes shrank
to just two -- crisscrossing the hilly city on the California and
Powell lines -- the cable car and its clanging bell has become a
city landmark.
Locals tend to shy away from the cable cars since the admission
price is double that of buses, but tourists line up by the hundreds
for the thrill of hanging perilously off a lurching, old-fashioned
machine.
According to legend, the original blueprints were destroyed in
the fires that followed the 1906 earthquake, and since then
craftsmen have been drawing up patterns on the fly and passing the
craft down through the generations.
''We have bits and pieces of plans, but a lot of it is just in
the carpenters' heads,'' says Harris. ''It's like putting a puzzle
back together. That's what I really like about working here, it's
such a challenge.''
Each 7-ton car costs about $275,000. Constant maintenance is
needed to replace the wooden brake shoes and grips that grab the
underground cable, which moves at a constant speed of 9 mph. Both
the shoes and grips are crafted at the Municipal Railway workshop
and must be replaced every three days.


The idea of pyro-config is the offer the simplest solution to load, validate and access your apps's configuration, following The 12-factor App standards.
It's built with TypeScript and outputs the configuration 100% typed and validated.
Using yarn
yarn add pyro-config
Using npm
npm install pyro-config --save
We create a Config instance by calling the static create
class member with our configuration schema.
This will load the config from process.env
then validate it.
import Config from 'pyro-config'
const config = Config.create({
booleanValue: {
type: Boolean,
default: true,
description: 'Test description',
},
stringValue: {
type: String,
nullable: true,
description: 'Test description',
},
numberValue: {
type: Number,
description: 'Test description',
env: 'ANOTHER_NUMBER_VALUE',
},
})
const booleanValue = config.get('booleanValue')
const stringValue = config.get('stringValue')
const numberValue = config.get('numberValue')
Access the docs here.
Generated using TypeDoc


''Be the person your dog thinks you are''
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{% load staticfiles %}
We want your presence rather than your presents, but if you must, we are registered at The Bay.


Edit Ticket
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Rating about employee's attitudeMask as resolveSaved changes Are you sure you wish to save and hide modal?You have unsaved changes Are you sure you wish to hide modal?Remove ticket
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Veuillez patienter...
{{ date | date:'longDate'}}
activityRunsheet_Packways_{{activityRunsheet.ref}}
{{activityRunsheet.status}} - Driver: {{(!!activityRunsheet.driver) ? activityRunsheet.driver.nameDriver + " " + activityRunsheet.driver.surnameDriver : "n'est pas assigné"}}
Date de confirmation : {{activityRunsheet.confirmedDate | date:'medium'}}
Date de confirmation : {{activityRunsheet.confirmedDate | date:'medium'}} | Date de clôture : {{activityRunsheet.closedDate | date:'medium'}}
Closed by : {{activityRunsheet.closedByName}}
Confirmed by : {{activityRunsheet.confirmedByName}}
Confirmé le {{ activityRunsheet.confirmedDate | date:'dd/MM/yyyy'}}
2}" class="mt-2"> {{ calculateDiff(activityRunsheet.confirmedDate)}} Jours
Clôturé le {{ activityRunsheet.closedDate | date:'dd/MM/yyyy'}}
2}" class="mt-2"> {{ calculateDiff(activityRunsheet.closedDate)}} Jours


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John Kennedy not approached by Hibs as Celtic No.2 focuses on Parkhead success
We revealed the Hoops would have demanded £300,000 in compensation if an offer from the Leith side was forthcoming.
by Michael Gannon, https://www.dailyrecord.co.uk/authors/michael-gannon/Celtic assistant manager John Kennedy will be Hibs' next manager as the Leith side's hunt for the next boss continues.
Record Sport understands the Hoops' No.2 was not approached by the Easter Road side over the prospect of becoming their next boss.
We revealed the Hoops would have demanded £300,000 in compensation if an offer from the Leith side was forthcoming.
But Hibs' search for their next boss continues with chief executive Leeann Dempster heading up the search to find Paul Heckingbottom's successor.
Kennedy is Neil Lennon's trusted No.2 and enjoyed a close relationship with previous bosses Brendan Rodgers and Ronny Deila.
Celtic defender Christopher Jullien admits Kennedy's guidance has been vital since £7million arrival from Toulouse in the summer.
He said: “Since I arrived he’s been there for me. When you arrive somewhere new it’s sometimes difficult.
“You can have some tough times to settle and things like that. He was always there and showed me the good stuff I was doing as well as the bad stuff.
“I’m so happy to have this guy close to me. He made me learn some things about the club and how to play. I’m really happy to have him on my side.
“I talked about how his career went but not with him. But I just see he’s in a really good place right now.
“What he’s teaching and doing for us on the field is really good."


LightBlue Bean - Basic
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CONNECT
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Temperature
N/A
C°
LED control


Default IDs
Sign out
Sign in with How are you?
Default IDs
User ID (for
/users
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Patient ID (for
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Use your
your own keys
or the
demo keys
.
Close


This is an example of the filled range chart being used to create a "Fan" chart. Fan charts are used to illustrate growing uncertainty of future values (eg currency).
This goes in the documents header:<script src="RGraph.common.core.js"></script> <script src="RGraph.common.dynamic.js"></script> <script src="RGraph.common.tooltips.js"></script> <script src="RGraph.line.js"></script>Put this where you want the chart to show up:
<canvas id="cvs" width="600" height="250"> [No canvas support] </canvas>This is the code that generates the chart - it should be placed AFTER the canvas tag(s):


Sprint 2. Assessor view completion
Applicant
-
INFUND-650
(Based on user journey from INFUND-643) As an applicant (lead) I want to create a new application so that I can submit an entry into a relevant competition.
-
INFUND-650
(Based on user journey from INFUND-642) As an applicant (collaborator) I want to create a new application so that I can submit an entry into a relevant competition.
-
INFUND-650
WHEN USER'S ORG IS ALREADY REGISTERED (Based on user journey from INFUND-642) As an applicant (collaborator) I want to create a new application so that I can submit an entry into a relevant competition.
- INFUND-642 Confirm registered organisation is correct
- INFUND-642 When user already has an IFS account, and they confirm org details before reaching the application overview
-
INFUND-986
As a research applicant I need to inform Innovate UK what type of organisation I am so that this can inform how I provide my finances
-
INFUND-985
(Based on user journey from INFUND-631) As an applicant (collaborator) I need to provide details of any other public funding I have received for this project so that Innovate UK can provide accurate funding
-
INFUND-985
(Based on user journey from INFUND-631) As an applicant (lead) I need to provide details of any other public funding I have received for this project so that Innovate UK can provide accurate funding
- INFUND-1023 - Add % grant question to individual org finances page
- INFUND-1024 - Other public funding question addition
- INFUND-1025 - Mark as done styling for finance overview table
- INFUND-1025 - Mark as done styling for finance overview table - (showing warning on participation levels)
- INFUND-1026 - Finances overview table presented in review and submit page (showing complete finances)
- INFUND-1026 - Finances overview table presented in review and submit page (showing incomplete finances)
- INFUND-1113 - Change 'overheads' to 'admin support costs'
- INFUND-1124 - Move organisation size question into the finances page
-
INFUND-830
As an applicant I want to upload documents to the system, so I can share this information with my collaborators and innovateuk
- File already uploaded example (collaborator)
- File not uploaded (collaborator)
- INFUND-756 - As an applicant I should understand when/why an upload has failed so i can retry uploading the file. (wrong file type)
- INFUND-756 - As an applicant I should understand when/why an upload has failed so i can retry uploading the file. (filesize too large)
- INFUND-776 - As an applicant I need to understand the types of file I can upload so I can support my application
- INFUND-755 - As an applicant I must understand the maximum file size that can be submitted so I can provide supporting documentation to my application (information in dropdown)
-
INFUND-675
As an applicant I want to have an applicant profile where I can edit my company details so that I can update my details (e.g. phone number)
Assessor
-
INFUND-984
Assessment form style changes
- INFUND-1039 - Break out questions per page
- INFUND-1031 - Amend headers in assessment
- INFUND-1033 - Redesign assessment overview
-
INFUND-864
As an Assessor I want to be notified by email that I have been invited to assess on a competition so that I can be aware of the assignment
- INFUND-1034 - Create email holding page
- INFUND-1035 - Revised assessor dashboard for invites
-
INFUND-865
As an Assessor I want to be given the option to accept or decline a competition so I may be correctly assigned to the assessor allocation process
- INFUND-1036 - Invitation to assess page with layout tweaks
- INFUND-1037 - Show accepted comp on assessor dashboard
- INFUND-1038 - Implement a/r buttons
-
INFUND-871
As an Assessor I want to be given the full application and financial summaries I have agreed to assess so that I can fully assess the application
- INFUND-1133 - Create mock email copy for applications allocated
- INFUND-1134 - Amends to comp dashboard
-
INFUND-869
As an Assessor I want to be given the option to accept or decline assessing an application based on my review of the summary details so I can be correctly assigned to the assessment
- INFUND-1135 - Restyle accept/reject state
-
INFUND-868
As an Assessor I want to be given summary details of each application I have been chosen to assess so I can carry out the assessment process
-
INFUND-872
As an Assessor having received the full application, I want to be given a further option to decline assessing any application I consider may reflect a conflict of interest so that I may be correctly assigned to the application
-
INFUND-994
** As an assessor I want to be able to review and submit my assessments individually or in a batch upload so that I can return my assessments to Innovate UK
-
INFUND-996
As an assessor I need to be informed when deadlines are upcoming or have passed so that I can complete my assessments
Carried over from sprint 1
-
INFUND-634
As an applicant I want to review the function to print/download my application for review, so I can review offline.
-
INFUND-648
(Subtask INFUND-1119) As an applicant/collaborator/assessor I always want easy access to innovate uk contact information no matter what screen I’m on, so that I can contact the support team if I have an issue, so I can review the user journey
-
INFUND-649
As the service delivery manager for IFS I want the applicant/collaborator/assessor to feedback any issues they have with a specific page, so that we can investigate and rectify as quickly as possible, so I can review the user journey
-
INFUND-636
As a UX team member I want to make refinements to the components we already have for accessibility, code validity and usability, so we can make small improvements which don't fit in a specific user story.


{% extends '../common/_base.html' %} {% block title %}{% endblock %} {% block content %}
Black and color belts
Institutions, coaches, and instructors


{% extends "base.html" %} {% block title %}BikeFlow | Home{% endblock %} {% block body %}
Here you can check the realtime status of a Citibike station, observe the average bike traffic in and out of that station, and get a recommendation for rebalancing that station. Click enter to check it out.


Logging data¶
Apart from printing loss, accuracy and other metrics during training it is
often useful to log these numbers to a file. nuts-ml provides logging
functionality within and outside of data pipelines via LogToFile
.
The following example demonstrates the basics. We have a list of samples
that we log to a CSV file:
>>> filepath = 'tests/data/temp_logfile.csv'
>>> samples = [(1, 2, 3), (4, 5, 6)]
>>> with LogToFile(filepath) as logtofile:
... samples >> logtofile >> Consume()
>>> open(filepath).read()
1,2,3
4,5,6
LogToFile
allows to extract sample columns to log and to
specify column names for the log file. In this next example we also show
how to manually close and delete a created log file:
>>> logtofile = LogToFile(filepath, cols=(2, 0), colnames=['A', 'B'])
>>> samples >> logtofile >> Consume()
>>> open(filepath).read()
A,B
3,1
6,4
>>> logtofile.close()
>>> logtofile.delete()
In this more complex code sketch we will use LogToFile
within a training a loop
and log loss and accuracy per batch, and epoch, mean loss and mean accuracy per
epoch:
log_batch = LogToFile('batchlog.csv', colnames=['loss', 'acc'])
log_epoch = LogToFile('epochlog.csv', colnames=['epoch', 'loss', 'acc'])
mean = Mean()
for epoch in range(EPOCHS):
t_loss, t_acc = (train_samples >> ... >> build_batch >>
network.train() >> log_batch >> Unzip())
log_epoch( (epoch, mean(t_loss), mean(t_acc) )
log_batch.close()
log_epoch.close()
The output of network.train()
is a NumPy array, containing
the loss and accuracy per mini-batch (these are the outputs that Keras produces
during training). Note that we call log_epoch
explicitly (outside of the pipeline)
and can simply provide the values to log as a tuple, list or array. Of course,
the number of values must match the number column names defined.
The same syntactical feature is used for Mean
here. For instance, the following
three constructs are equivalent:
>>> [1, 2, 3] >> Mean()
2.0
>>> Mean()([1, 2, 3])
2.0
>>> mean = Mean()
>>> mean([1, 2, 3])
2.0
Similar to logging we can also plot data. This is the topic of the next section.


Sale To Patient
Consumption
Error...
Ward Not Found
Boo, looks like a ghost stole this page!
New Consumption
Select Ward:
All
{{v.WardName}}


A cross compiler is a compiler that runs in a certain processor architecture (host architecture) but is able to generate executable code to a different processor architecture (target architecture) 1.
The Advance Toolchain provides cross compilers that run on x86 and generate code for Power which help teams to start developing for Power without having immediate access to a POWER server. A cross compiler doesn't completely remove the dependency on the target processor because users still have to test and run the executable code on a different processor.
GNU wget 2 is a small program that highlights the important problems when cross compiling a certain software: it depends on libraries provided by the Advance Toolchain cross compiler and external libraries.
In this example, we'll build GNU wget for POWER little-endian, using a x86 computer with the Advance Toolchain cross compiler.
Firstly, it is necessary to copy all necessary libraries and headers to a certain directory. In this example I'll use:
In this case, ${HOME} is a shell variable holding the path of my home directory.
For GNU wget, we need to provide some OpenSSL libraries and Zlib. Both of them are available in the Advance Toolchain native compiler. However, the list of necessary libraries may vary according to the project. If you don't know well the project you can use the following tools in order to identify the list of libraries they use:
ldd <executable> rpm -q --requires -p <package.rpm> dpkg-deb -f <package.deb> | grep "Depends:"
Usually the list of libraries necessary to build a project is the same across all processor architectures. So, you may use the above commands against an executable or package compiled for another processor.
This is the list of files required in order to build wget:
$ ls -1 ${HOME}/wget/include/ openssl/ zconf.h zlib.h $ ls -1 ${HOME}/wget/lib/ libcrypto.so libcrypto.so.1.0.0 libssl.so libssl.so.1.0.0 libz.so libz.so.1 libz.so.1.2.6
Make sure the libraries are really compiled for the target processor. If they don't match, you won't be able to use them. You may use 'readelf -h' to verify this information:
$ /opt/at7.1/bin/powerpc64le-linux-gnu-readelf -h ${HOME}/wget/lib/libz.so.1.2.6 ... Data: 2's complement, little endian ... Machine: PowerPC64 ...
With the header files and libraries in place, the system is ready to start the build. So, create a separate build directory:
mkdir ${HOME}/wget/build && cd ${HOME}/wget/build
After entering the separate build directory, it's possible to configure the build by running:
CC=/opt/at7.1/bin/powerpc64le-linux-gnu-gcc \ CFLAGS="-I${HOME}/wget/include" \ LDFLAGS="-L${HOME}/wget/lib" \ ../wget-1.15/configure \ --host=powerpc64le-linux \ --with-ssl=openssl
Where:
Finally, build wget:
make
After running this you'll find the program available at ${HOME}/wget/build/src/wget.
You can now copy it to a POWER little endian system with the Advance Toolchain runtime package installed and run it.
Not necessarily. It depends on the code being built and the level of optimization in use.
No. There are some differences in the metadata of the binaries, but it will run at the same speed.
In this case, it isn't possible to pass -I to the compiler or -L to linker and the only possible solution is to save the headers and libraries in one of the Advance Toolchain directories:
1 Wikipedia - Definition of cross compilers: http://en.wikipedia.org/wiki/Cross_compiler
2 GNU wget project page: https://www.gnu.org/software/wget/


Working with Texts
Analytics Zoo provides a series of text related APIs for end-to-end text processing pipeline, including text loading, pre-processing, training and inference, etc.
TextSet
TextSet
is a collection of TextFeatures where each TextFeature
keeps information of a single text record.
TextSet
can either be a DistributedTextSet
consisting of text RDD or a LocalTextSet
consisting of text array.
Read texts as TextSet
Read texts from a directory
Read texts with labels from a directory.
Under this specified directory path, there are supposed to be several subdirectories, each of which contains a number of text files belonging to this category. Each category will be a given a label (starting from 0) according to its position in the ascending order sorted among all subdirectories. Each text will be a given a label according to the directory where it is located.
Scala
textSet = TextSet.read(path, sc = null, minPartitions = 1)
path
: String. Folder path to texts. Local or distributed file system (such as HDFS) are supported. If you want to read from HDFS, sc needs to be specified.sc
: An instance of SparkContext. If specified, texts will be read as a DistributedTextSet. Default is null and in this case texts will be read as a LocalTextSet.minPartitions
: Integer. A suggestion value of the minimal partition number for input texts. Only need to specify this when sc is not null. Default is 1.
Python
text_set = TextSet.read(path, sc=None, min_partitions=1)
path
: String. Folder path to texts. Local or distributed file system (such as HDFS) are supported. If you want to read from HDFS, sc needs to be defined.sc
: An instance of SparkContext. If specified, texts will be read as a DistributedTextSet. Default is None and in this case texts will be read as a LocalTextSet.min_partitions
: Int. A suggestion value of the minimal partition number for input texts. Only need to specify this when sc is not None. Default is 1.
Read texts from csv file
Read texts with id from csv file.
Each record is supposed to contain id(String) and text(String) in order.
Note that the csv file should be without header.
Scala
textSet = TextSet.readCSV(path, sc = null, minPartitions = 1)
path
: String. The path to the csv file. Local or distributed file system (such as HDFS) are supported. If you want to read from HDFS, sc needs to be specified.sc
: An instance of SparkContext. If specified, texts will be read as a DistributedTextSet. Default is null and in this case texts will be read as a LocalTextSet.minPartitions
: Integer. A suggestion value of the minimal partition number for input texts. Only need to specify this when sc is not null. Default is 1.
Python
text_set = TextSet.read_csv(path, sc=None, min_partitions=1)
path
: String. The path to the csv file. Local or distributed file system (such as HDFS) are supported. If you want to read from HDFS, sc needs to be defined.sc
: An instance of SparkContext. If specified, texts will be read as a DistributedTextSet. Default is None and in this case texts will be read as a LocalTextSet.min_partitions
: Int. A suggestion value of the minimal partition number for input texts. Only need to specify this when sc is not None. Default is 1.
Read texts from parquet file
Read texts with id from parquet file with schema id(String) and text(String). Return a DistributedTextSet.
Scala
textSet = TextSet.readParquet(path, sqlContext)
path
: The path to the parquet file.sqlContext
: An instance of SQLContext.
Python
text_set = TextSet.read_parquet(path, sc)
path
: The path to the parquet file.sc
: An instance of SparkContext.
Build Text Transformation Pipeline
You can easily call transformation methods of a TextSet one by one to build the text transformation pipeline. Please refer to here for more details.
Scala Example
transformedTextSet = textSet.tokenize().normalize().word2idx().shapeSequence(len).generateSample()
Python Example
transformed_text_set = text_set.tokenize().normalize().word2idx().shape_sequence(len).generate_sample()
Text Training
After doing text transformation, you can directly feed the transformed TextSet into the model for training.
Scala
model.fit(transformedTextSet, batchSize, nbEpoch)
Python
model.fit(transformed_text_set, batch_size, nb_epoch)
Word Index Save and Load
Save word index
After training the model, you can save the word index correspondence to text file, which can be used for future inference. Each separate line will be "word id".
For LocalTextSet, save txt to a local file system.
For DistributedTextSet, save txt to a local or distributed file system (such as HDFS).
Scala
transformedTextSet.saveWordIndex(path)
Python
transformed_text_set.save_word_index(path)
Load word index
During text prediction, you can load the saved word index back, so that the prediction TextSet uses exactly the same word index as the training process. Each separate line should be "word id".
For LocalTextSet, load txt to a local file system.
For DistributedTextSet, load txt to a local or distributed file system (such as HDFS).
Scala
textSet.loadWordIndex(path)
Python
text_set.load_word_index(path)
Text Prediction
Given a raw TextSet to do prediction, you need to first load the saved word index back as instructed above and go through the same transformation
process as what you did in your training. Note that here you do not need to specify any argument when calling word2idx
in the preprocessing pipeline as now you are using exactly
the loaded word index.
Then you can directly feed the transformed TextSet into the model for prediction and the prediction result will be stored in each TextFeature.
Scala
predictionTextSet = model.predict(transformedTextSet)
Python
prediction_text_set = model.predict(transformed_text_set)
Examples
You can refer to our TextClassification example for TextSet transformation, training and inference.
See here for the Scala example.
See here for the Python example.


I am an optimistic spirit ready to face any challenge that comes my way. My unique background makes me equipped to perservere through any endeavor!
Learned technical skills like HTML, JavaScript, CSS, and entrepreneurship in Tel Aviv, Israel.
Utilized finance and accounting skills to help create monthly and quarterly reports.
Help design a curriculum for classes on cost-effective analysis and vaccine economics for EPI managers in developing nations.
I enjoy creativity. I create websites, draw, dance, and love expressing myself. I combine this my love for youth empowerment and development .


{% extends "asn/base.html" %} {% load url from future %} {% block content %}
The social network where everyone hates you.
Give it a go.
Stroke your ego
Log out


Table 1: Summary Statistics
Count, mean, std. dev., minimum and quartile summary data for the entire dataset.
{% extends "layout.html" %} {% block body %}
EDA and Plots
Table 1: Summary Statistics
Count, mean, std. dev., minimum and quartile summary data for the entire dataset.
One can see from our summary statistics of continuous variables that the average person from this sample is 38, almost 39 years old. They work 40 hours a week. They have not completed high school. Twenty four percent of these American persons (US citizens and permanent residents) make more than $50,000 per year.
Seventy five percent of people in this sample work 45 hours or less with a tight distribution of hours around 40 for most adults.
Table 2: Sample Data Grouped by Over 50K, Married and Race
Notes:
Over 50K
signifies whether the census respondent makes more than
$50k per year.Married
consolidates multiple Marital Status
categories
into a single binary variable.Race
denotes the respondents race.Hours Per Week
is the hours per week the respondent works.Education Num
: how many years of education the repondent completed.In the second table, I have grouped the continuous data variables by those who make over $50K, whether they are married or not, and their race.
The first thing to notice about our data is those who make more than $50K have more education than those who don't. About two years more generally.
In the group that makes less than $50K, there are comparitively fewer married census respondents than unmarried. One suspects that this is younger, unmarried people making less money and the mean, age of these groups agrees with the unmarried group who makes less than $50K being about 10 years younger on average.
In the less than $50K group, the hours worked and education levels are similar.
The over $50K group is the opposite with respect to being married and age. There are more married people who make over $50K while they are still older but less so than those who are not married. Those unmarried respondents who make more than $50K also work the longest hours and have some of the highest education levels in the sample.


Globs are ignored in [[ ]]
except right of =/!=. Use a loop.
[[ current.log -nt backup/*.log ]] && echo "This is the latest file"
newerThanAll=true
for log in backup/*.log
do
[[ current.log -nt "$log" ]] || newerThanAll=false
done
[[ "$newerThanAll" = "true" ]] && echo "This is the latest file"
Globs in [[ ]]
will not filename expand, and will be treated literally (or as patterns on the right-hand side of =
, ==
and !=
).
The problematic code is equivalent to [[ current.log -nt 'backup/*.png' ]
, and will look for a file with a literal asterisk in the name.
Instead, you can iterate over the filenames you want with a loop, and apply your condition to each filename.
None.


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interface ObjectMapper<T : GrapheneObject> : Mapper<T>
Encapsulates logic, associated with data mapping to GrapheneObject based object
Author
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DepositMapper |
Json mapper for Withdraw model class DepositMapper : ObjectMapper<Deposit> |
Erc20DepositMapper |
Json mapper for Deposit model class Erc20DepositMapper : ObjectMapper<ERC20Deposit> |
Erc20TokenMapper |
Json mapper for ERC20Token model class Erc20TokenMapper : ObjectMapper<ERC20Token> |
Erc20WithdrawalMapper |
Json mapper for ERC20Withdrawal model class Erc20WithdrawalMapper : ObjectMapper<ERC20Withdrawal> |
WithdrawMapper |
Json mapper for Withdraw model class WithdrawMapper : ObjectMapper<Withdraw> |


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[gecode-users] Gecode 5.0.0 released
Guido Tack
guido.tack at monash.edu
Fri Oct 28 06:27:32 CEST 2016
Hi Carlo,
no idea why I assumed you were using Mac OS, sorry about that! I’ll add the switch to the default options (possibly with a configure switch to turn it off for older compilers). For the time being you can simply pass CXXUSR=-std=c++11 when you invoke make instead of patching the Makefile.
Cheers,
Guido
--
GUIDO TACK
Senior Lecturer
Information Technology
Monash University
Level 6, Room 6.40, Building H, Caulfield Campus
900 Dandenong Road
Caulfield East VIC 3145
Australia
T: +61 3 9903 1214
E: guido.tack at monash.edu <mailto:guido.tack at monash.edu>
http://www.csse.monash.edu/~guidot/ <http://www.csse.monash.edu/~guidot/>
> On 27 Oct. 2016, at 6:00 pm, Carlo Capelli <cc.carlo.cap at gmail.com> wrote:
>
> Dear Christian
>
> Thanks so much for this release.
>
> I'm here just to note 2 small glitches about Qt5 integration (at least, the current 5.7 version):
>
> - when building, the default toolset (configure && make) should probably be extended to handle C++11.
> I just patched Makefile.in, adding CXXUSR=-std=c++11 at line 71, but surely there will be a proper way instead of hardcoding the option.
> Probably CMake already solves this detail, but I have not tested it.
>
> - in MPG Digia should substitute Nokia
>
> Best regards, Carlo
>
>
> 2016-10-26 12:27 GMT+02:00 Christian Schulte <cschulte at kth.se <mailto:cschulte at kth.se>>:
> Dear all,
>
> We are happy to announce that Gecode 5.0.0 has been released on October 25,
> 2016. Here is an excerpt from the changelog:
>
> This release adds a number of new features and fixes many bugs (some rather
> serious), so it is recommended to switch as soon as possible to this
> release. Some highlights are: re-added limited discrepancy search (LDS);
> added sequential and parallel portfolio-based search (PBS); added support
> for groups of propagators and branchers; added extensive tracing
> functionality based on groups; propagators can be disabled and re-enabled;
> support for arbitrary memory allocators; changed the notion of "integer
> consistency level" to the more expressive concept "integer propagation
> level".
>
> Cheers
> Christian
>
> --
> Christian Schulte, www.gecode.org/~schulte <http://www.gecode.org/~schulte>
> Professor of Computer Science, KTH, cschulte at kth.se <mailto:cschulte at kth.se>
> Expert Researcher, SICS, cschulte at sics.se <mailto:cschulte at sics.se>
>
>
> _______________________________________________
> Gecode users mailing list
> users at gecode.org <mailto:users at gecode.org>
> https://www.gecode.org/mailman/listinfo/gecode-users <https://www.gecode.org/mailman/listinfo/gecode-users>
>
>
> _______________________________________________
> Gecode users mailing list
> users at gecode.org
> https://www.gecode.org/mailman/listinfo/gecode-users
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Reports unnecessary
return
statements at the end of constructors and methods returning
void
. These may be safely removed.


Commercial license allows you to use Besley* by indestructible type* for most commercial purposes starting at $50. Read full license here.
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@* * Copyright 2023 HM Revenue & Customs * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. *@ @import play.api.mvc.Request @import uk.gov.hmrc.apidocumentation.models._ @import include.apiMain @import uk.gov.hmrc.apidocumentation.views.html.include._ @import uk.gov.hmrc.apidocumentation.config._ @this(apiMain: apiMain) @(pageAttributes: PageAttributes, api: XmlApiDocumentation)(implicit applicationConfig: ApplicationConfig, request: Request[AnyContent], messagesProvider: MessagesProvider) @apiMain(pageAttributes) {
@Html(api.description)
For more information on how to use XML APIs, see Dealing with HMRC: Software development for HMRC.
}


class: center, middle # Horizontally Scalable Relational Databases with Spark<EMAIL_ADDRESS>--- # What is Citus? * Standard Postgres * Sharded across multiple nodes * CREATE EXTENSION citus; -- not a fork of the codebase * Good for live analytics, multi-tenant * Open source, commercial support --- # Where does Citus fit with Spark? 1. Shove your data into Kafka 2. Munge it with Spark 3. ??? 4. Profit! --- # Where does Citus fit with Spark? 1. Shove your data into Kafka 2. Munge it with Spark 3. Serve live traffic using * ML models * Key / Value stores * ? Spark SQL ? * ? Single node database ? 4. Profit! --- # Spark SQL + HDFS pain points * Multi-user * Query latency * Mutable rows * Co-locating related writes for joins --- # Relational database pain points * "Schemaless" data * Scaling out, without giving up * Aggregations * Joins * Transactions --- # "Schemaless" data ```sql master# create table no_schema ( data JSONB); master# create index on no_schema using gin(data); master# insert into no_schema values ('{"user":"cody","cart":["apples","peanut_butter"]}'), ('{"user":"jake","cart":["whiskey"],"drunk":true}'), ('{"user":"omar","cart":["fireball"],"drunk":true}'); master# select data->'user' from no_schema where data->'drunk' = 'true'; ?column? ---------- "jake" "omar" (2 rows) ``` --- # Scaling out ``` +--------------+ SELECT FROM table_1001 | | +-------------------------> | Worker 1 | | | | | | table_1001 | | SELECT FROM table_1003 | table_1003 | +------------+ +-------------------------> | | | | | | | | Master | | +--------------+ SELECT FROM table | | | +-------------------> | table | ---+ | metadata | | +--------------+ | | | SELECT FROM table_1002 | | | | +-------------------------> | Worker 2 | +------------+ | | | | | table_1002 | | SELECT FROM table_1004 | table_1004 | +-------------------------> | | | | +--------------+ ``` --- # Choosing a distribution key * Commonly queried column (e.g. customer id) * 1 master query : 1 worker query * easy join on distribution key * possible hot spots if load is skewed * Evenly distributed column (e.g. event GUID) * 1 master query : # of shards worker queries * hard to join * no hot spots * Can duplicate table with different distribution key if needed --- # Creating distributed tables ```sql master# create table impressions( date date, ad_id integer, site_id integer, total integer); master# set citus.shard_replication_factor = 1; master# set citus.shard_count = 4; master# select create_distributed_table('impressions', 'ad_id', 'hash'); ``` --- Metadata in master tables ```sql master# select * from pg_dist_shard; logicalrelid | shardid | shardminvalue | shardmaxvalue --------------+---------+---------------+--------------- impressions | 102008 | -2147483648 | -1073741825 impressions | 102009 | -1073741824 | -1 impressions | 102010 | 0 |<PHONE_NUMBER> impressions | 102011 |<PHONE_NUMBER> |<PHONE_NUMBER> ``` Data in worker shard tables ```sql worker1# \d List of relations Schema | Name | Type | Owner --------+--------------------+-------+------- public | impressions_102008 | table | cody public | impressions_102010 | table | cody ``` --- # Writing data ```sql master# insert into impressions values (now(), 23, 42, 1337); master# update impressions set total = total + 1 where ad_id = 23 and site_id = 42; master# \copy impressions from '/var/tmp/bogus_impressions'; ``` Can also write directly to worker shards, as long as you hash correctly --- # Aggregations Commutative and associative operations "just work": ```sql master# select site_id, avg(total) from impressions group by 1 order by 2 desc limit 1; site_id | avg ---------+--------------------- 5225 |<PHONE_NUMBER>38461538 (1 row) ``` In worker1's log: ```sql COPY (SELECT site_id, sum(total) AS avg, count(total) AS avg FROM impressions_102010 impressions WHERE true GROUP BY site_id) TO STDOUT COPY (SELECT site_id, sum(total) AS avg, count(total) AS avg FROM impressions_102008 impressions WHERE true GROUP BY site_id) TO STDOUT ``` For other operations, can usually query a subset of data to temp table on master, then use arbitrary SQL --- # Joins Co-located joins of tables with same distribution column work well ```sql master# create table clicks( date date, ad_id integer, site_id integer, price numeric, total integer); master# select create_distributed_table('clicks', 'ad_id', 'hash'); master# select i.ad_id, sum(c.total) / sum(i.total)::float as clickthrough from impressions i inner join clicks c on i.ad_id = c.ad_id and i.date = c.date and i.site_id = c.site_id group by 1 order by 2 desc limit 1; ad_id | clickthrough -------+---------- 814 | 0.1 ``` --- Distributed joins on non-distribution column will work, but are slow ```sql master# create table discounts( date date, amt numeric); master# select create_distributed_table('discounts', 'date', 'hash'); master# select c.ad_id, max(c.price * d.amt) from clicks c inner join discounts d on c.date = d.date group by 1 order by 2 desc limit 1; ERROR: cannot use real time executor with repartition jobs HINT: Set citus.task_executor_type to "task-tracker". master# SET citus.task_executor_type = 'task-tracker'; master# select c.ad_id, max(c.price * d.amt) from clicks c inner join discounts d on c.date = d.date group by 1 order by 2 desc limit 1; ad_id | max -------+----------------------------------- 587 | 67.887149187736200000000000000000 (1 row) Time: 3464.598 ms ``` --- Replicating the join table on every worker is faster ```sql master# SET citus.shard_replication_factor = 2; -- equal to number of nodes master# select create_reference_table('discounts2'); master# select c.ad_id, max(c.price * d.amt) from clicks c inner join discounts2 d on c.date = d.date group by 1 order by 2 desc limit 1; ad_id | max -------+----------------------------------- 587 | 67.887149187736200000000000000000 (1 row) Time: 31.237 ms ``` --- # Transactions * No global transactions (Postgres-XL) * Individual worker transactions are still extremely useful: * If sharded by customer id, each customer sees consistent world * Spark output actions are at-least-once * Transactions allow consistent semantics for failures * Even for non-idempotent updates --- # Transactional writes from Spark to single DB * Table of offset ranges (or batch ids) * Foreach partition, start transaction on DB * insert or update results * update offsets table rows * roll back if offsets weren't as expected * On failure, * begin from minimum offset range * recalculate all results for that range (due to shuffle) --- # Transactional writes from Spark to Citus * **Partition Spark results to match Citus shards** * Table of offset ranges (or batch ids) **on each worker** * Foreach partition, start transaction **on corresponding worker** * insert or update results * update offsets table rows **for that shard** * roll back if offsets weren't as expected * On failure, * begin from minimum offset range across all workers * recalculate all results for that range (due to shuffle) * **skip writes for shards that already have that offset range** --- # Spark custom partitioner ```scala /** same number of Spark partitions as Citus shards */ override def numPartitions: Int /** given a key, which Spark partition */ override def getPartition(key: Any): Int /** given a Spark partition, which worker shard */ def shardPlacement(partitionId: Int): ShardPlacement ``` * Citus uses Postgres hash (**hashfunc.c**) based on Jenkins' 2006 hash * Min / max hash values for a given shard are in **pg_dist_shard** table * Worker nodes for a given shard are in **pg_dist_shard_placement** table * Idea is to query once at partitioner creation time, build a lookup array --- ```sql select (ds.logicalrelid::regclass)::varchar as tablename, ds.shardmaxvalue::integer as hmax, ds.shardid::integer, p.nodename::varchar, p.nodeport::integer from pg_dist_shard ds left join pg_dist_shard_placement p on ds.shardid = p.shardid where (ds.logicalrelid::regclass)::varchar in ('impressions') order by tablename, hmax asc; tablename | hmax | shardid | nodename | nodeport -------------+-------------+---------+-----------+---------- impressions | -1073741825 | 102008 | host1 | 9701 impressions | -1 | 102009 | host2 | 9702 impressions |<PHONE_NUMBER> | 102010 | host1 | 9701 impressions |<PHONE_NUMBER> | 102011 | host2 | 9702 ``` * To find partition, hash key w/Jenkins, walk array until hmax >= hashed * To find worker shard for a partition, index directly by partition # * See github link at end of slides for working code --- # Example offsets table ```sql app | topic | part | shard_table_name | off -------+-------------+------+--------------------+--------- myapp | impressions | 0 | impressions_102008 | 20000 myapp | impressions | 0 | impressions_102009 | 20000 myapp | impressions | 0 | impressions_102010 | 19000 -- behind myapp | impressions | 0 | impressions_102011 | 20000 myapp | impressions | 1 | impressions_102008 | 20001 myapp | impressions | 1 | impressions_102009 | 20001 myapp | impressions | 1 | impressions_102010 | 18000 -- behind myapp | impressions | 1 | impressions_102011 | 20001 ``` * In this case, a failure occurred before writes to **impressions_102010** finished * Restart Spark app from Kafka offset ranges * partition 0 offsets 19000 -> 20000 * partition 1 offsets 18000 -> 20001 * Writes to **impressions_102010** succeed, other shards are skipped --- # Lies, damn lies, and bar charts
--- # Lies, damn lies, and bar charts
--- # General lessons learned * Be conservative with changing anything else when moving to sharded DB * PgBouncer is necessary in front of workers, not just master * especially if you have queries that hit all shards * Some cognitive overhead about which SQL features work * still better than layering SQL on a totally different data model * Would be nice to have hash distribution on top of date-partitioned tables * most of our queries involve date ranges * drop table for expiring data retention rather than delete / vacuum * can be done manually, easy way may be coming with Postgres 10 --- class: center, middle # Questions<EMAIL_ADDRESS>https://github.com/koeninger/spark-citus


Status Ranks Releases Hall of Fame Tournaments Skin Database Downloads Statistics Forum Wiki Brutal Server Quick Tournament #42 This tournament is played on Saturday, 2016-04-02 at 19:00 CET. ↑Brutal Server Lockdownby Aoe, Trax & SpykerDifficulty: ★★★✰✰, Points: 24 2 tees finished (average time: 117:25.64)1 team finished (biggest team: 2) Team Records: 1.23:47iParano & nealson T'nP


This is my portfoilo for web programming. I began learning the basics of programming at Epicodus in August 2019 in the Introduction to Programming Evening class.
In my first week at Epicodus we explored Git, Markdown, and HTML. Below you will find links to my very first projects: Hello World, Goodbye World, and a blog post created using Markdown.
For my second week at Epicodus we dove into the styling with CSS and learned all about Git and how to commit and push to Github. We also covered debugging HTML and CSS as well as making detailed READMEs. We got to practive Divs, Spans and Floats duing this week also.
In the third week at Epicodus we got deeper into the power of CSS and learned about Frameworks, specifiaclly Bootstrap.
I was born and raised in Portland Oregon and have lived here for most of my life. I currently work at AKQA, a digital creative agency, as IT Support.


somename
Any statement for an observable containing "somename"active: *
All active statementsinactive: *
All inactive statementsagents: *
All agentsactive:agents: picture
All active agents triggered by "picture"#drawable
Statements containing the "drawable" hashtagdepends:Circle
Any statement directly dependant on "Circle"determines:myline
All statements that directly or indirectly determine "myline"depends:Line -#library
Any statements using "Line" that are not in the libraryactive: * sort:youngest
All active statements sorted by age* -# sort:name
All untagged statements sorted alphabeticallyhandles: * -#lib
All non-library assignments or definitions with a single literalThe script search box allows you to find definitions, both currently active and inactive, based upon various characteristics such as observable name or dependencies. Typing a word in the box will match all observable names that are similar to that, a drop down box then contains suggestions.
If a definition has a comment with it that contains hashtags, then search for #thathashtag will show only those definitions matching that tag.
The results can be filtered by starting the search with one of the following tokens followed by a space and your query.
active:
- Show only those definitions and agents that are currently activeinactive:
- Show only those that are not activeagents:
- Only display agentshandles:
- Select only assignments or definitions that are just a single literal valueoracles:
- Select definitions that are more complex expressionsdefs:
- Only display definitions and no agentsshared:
- Only display definitions in the cloud that I do not have locally alreadyThese filters can be combined to, for example, select only active agents using "active:agents: ".
Statements can be search based upon what they are dependant on or what is determined by something. Search tokens are added before the observable name to match, with no space between the : and the word to match.
The results can be sorted by several properties such as time or name. This is specified by including one of the following search tokens somewhere in the search.


The command-line interface allows advanced users to increase their productivity and performe complex operations that cannot be performed using any of the other elements of the SEXTANTE GUI. Models involving several algorithms can be defined using the command-line interface, and additional operations such as loops and conditional sentences can be added to create more flexible and powerful workflows.
Invoking the command-line interface will make the following dialog appear.
The SEXTANTE command-line interface is based on BeanShell. BeanShell is a Java source interpreter with object scripting language features, that meaning that it dynamically executes standard Java syntax and extends it with common scripting conveniences such as loose types, commands, and method closures like those in Perl and JavaScript.
A detailed description of BeanShell and its usage can be found at the BeanShell website5.1. Refer to it if you want to learn more about generic BeanShell features. This chapter covers only those particular elements which are related to SEXTANTE geoalgorithms.
By using the extension mechanisms of BeanShell, SEXTANTE adds several new commands to it, so you can run geoalgorithms or get information about the geospatial data you are using, among other things.
Java users can create small scripts and programs combining standard elements of Java with SEXTANTE commands. However, those who are not familiar with Java can also use the command-line interface to execute single processes or small sets of them, simply calling the corresponding methods.
A detailed description of all SEXTANTE commands is given next.
Algorithms need data to run. Layers and tables are identified using the name they have in the table of contents of the GIS (and which usually can be modified using GIS tool). To call a geoalgorithm you have to pass it an identifier which represents the data to use for an input.
The data() command prints a list of all data objects available to be used, along with the particular name of each one (i.e. the one you have to use to refer to it). Calling it you will get something like this:
RASTER LAYERS ----------------- mdt25.asc VECTOR LAYERS ----------------- Contour lines TABLES -----------------
Be aware that some GIS allow you two have several layers with the same name. SEXTANTE will just take the first one which matches the specified identifier, so you should make sure you rename your data object so each one of them has a unique name.
To get more information about a particular data object, use the describe(name_of_data_object) command. Here are a few examples of the result you will get when using it to get more information about a vector layer, a raster layer and a table.
>describe points Type: Vector layer - Point Number of entities: 300 Table fields: | ID | X | Y | SAND | SILT | CLAY | SOILTYPE | EXTRAPOLAT | >describe dem25 Type: Raster layer X min:<PHONE_NUMBER>25 X max:<PHONE_NUMBER>25 Y min: 4454025.0 Y max: 4464275.0 Cellsize X: 25.0 Cellsize Y: 0.0 Rows: 410 Cols: 601 >describe spatialCorrelation Type: TableNumber of records: 156 Table fields: | Distance | I_Moran | c_Geary | Semivariance |
Once you know which data you have, it is time to know which algorithms are available and how to use them.
When you execute an algorithm using the toolbox, you use a parameters window with several fields, each one of them corresponding to a single parameter. When you use the command line interface, you must know which parameters are needed, so as to pass the right values to use to the method that runs that algorithm. Of course you do not have to memorize the requirements of all the algorithms, since SEXTANTE has a method to describe an algorithm in detail. But before we see that method, let's have a look at another one, the algs() method. It has no parameters, and it just prints a list of all the available algorithms. Here is a little part of that list as you will see it in your command-line shell.
bsh % algs(); acccost-------------------------------: Accumulated cost(isotropic) acccostanisotropic--------------------: Accumulated cost (anisotropic) acccostcombined-----------------------: Accumulated cost (combined) accflow-------------------------------: Flow accumulation acv-----------------------------------: Anisotropic coefficient of variation addeventtheme-------------------------: Points layer from table aggregate-----------------------------: Aggregate aggregationindex----------------------: Aggregation index ahp-----------------------------------: Analytical Hierarchy Process (AHP) aspect--------------------------------: Aspect buffer--------------------------------: Buffer
On the right you find the name of the algorithm in the current language, which is the same name that identifies the algorithm in the toolbox. However, this name is not constant, since it depends on the current language, and thus cannot be used to call the algorithm. Instead, a command-line is needed. On the left side of the list you will find the command-line name of each algorithm. This is the one you have to use to make a reference to the algorithm you want to use.
Now, let's see how to get a list of the parameters that an algorithms require and the outputs that it will generate. To do it, you can use the describealg(name_of_the_algorithm) method. Use the command-line name of the algorithm, not the full descriptive name.
For example, if we want to calculate a flow accumulation layer from a DEM, we will need to execute the corresponding module, which, according to the list show using the ags() method, is identified as accflow. The following is a description of its inputs and outputs.
>describealg("accflow") Usage: accflow(DEM[Raster Layer] WEIGHTS[Optional Raster Layer] METHOD[Selection] CONVERGENCE[Numerical Value] FLOWACC [output raster layer])
Now you know how to describe data and algorithms, so you have everything you need to run any algorithm. There is only one single command to execute algorithms: runalg. Its syntax is as follows:
> runalg{name_of_the_algorithm, param1, param2, ..., paramN)
The list of parameters to add depends on the algorithm you want to run, and is exactly the list that the describealg method gives you, in the same order as shown.
Depending on the type of parameter, values are introduced differently. The next one is a quick review of how to introduce values for each type of input parameter
For example, for the maxvaluegrid algorithm:
Usage: runalg("maxvaluegrid", INPUT[Multiple Input - Raster Layer] NODATA[Boolean], RESULT[Output raster layer])
The next line shows a valid usage example:
> runalg("maxvaluegrid", "lyr1, lyr2, lyr3", "false", "#")
Of course, lyr1, lyr2 and lyr3 must be valid layers already loaded into your GIS.
When the multiple input is comprised of raster bands, each element is represented by a pair of values (layer, band). For example, for the cluster algorithm
Usage: runalg( "cluster", INPUT[Multiple Input - Band], NUMCLASS[Numerical Value], RESULTLAYER[output raster layer], RESULTTABLE[output table], );
The next line shows a valid usage example:
> runalg("cluster, "lyr1, 1, lyr1, 2, lyr2, 2", 5, "#", "#")
The algorithm will use three bands, two of them from lyr1 (the first and the second ones of that layer) and one from lyr2 (its second band).
runalg("kernelfilter", mdt25.asc, "-1, -1, -1, -1, 9, -1, -1, -1, -1", "#")
Input parameters such as strings or numerical values have default values. To use them, type ``#'' in the corresponding parameter entry instead of a value expression.
For output data objects, type the filepath to be used to save it, just as it is done from the toolbox. If you want to save the result to a temporary file, type ``#''.
Just like when you execute a geoalgorithm from the toolbox, when it generates new raster layers you have to define the extent and cellsize of those layers.
By default, those characteristics are defined based on the input layers. You can toggle this behaviour using the autoextent command.
> autoextent("true"/"false)
If you want to define the output raster characteristics manually or using a supporting layer, you have to use the extent command, which has three different variants.
Usage: extent(raster layer[string]) extent(vector layer[string], cellsize[double]) extent(x min[double], y min[double], x max[double], y max[double], cell size[double]) Type "autoextent" to use automatic extent fitting when possible
When this command is used, the autoextent functionality is automatically deactivated.
Models can be executed from the command-line using the model command, which has a sintax similar to the runalg command. In this case, you must use the filename where the model is stored instead of the name of the algorithm as the first parameters. SEXTANTE will look for that file in the models folder, so make sure that you have saved the model in that folder, or set the corresponding folder using the SEXTANTE preferences window. The remaining parameters depend on the particular model you want to execute, much like in the case of running a simple algorithm with the runalg command.
You can perform some operation with layers from the command-line interface, like the following ones:


| When a child-stealing demon attaches itself to a little girl, her family is thrust into a battle against time in order to save the girl and send the demon back to hell. | |
| Genres: | Horror, Thriller |
| Director: | Ben Jehoshua |
| Writer: | Barry Jay, Ben Jehoshua, Andrew J. Scheppmann |
Cast: | Cameron - Kian Lawley Eliza - Elizabeth Keener Caitlin - Angelica Chitwood Uncle Joey - Chris Gann Aunt Jean - Dayna Devon Officer Jehoshua - Wiley B. Oscar Angie - Mykayla Sohn Randy - Casey James Knight Megan - Emily Killian Nanny - Barbara Goodson Sabrina - Melissa Navia Sabrina's ex-husband - Johnny Alexander Lilith - Stefanie Estes Courtney - Lexi Flores Officer Brady - Brent Alan Henry Grand Dad - Harv Popick Nun - Penelope Richards Missing girl - Hannah Sohn |


Supplemental Information
For more detailed understanding of how StickyEncoding works, please see the supplemental information below.
StickyEncoding Docs (100% documented)
For more detailed understanding of how StickyEncoding works, please see the supplemental information below.


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1605217
Legend -
Level of confidence that token is an accurately-transcribed word
extremely low
very low
low
undetermined
medium
high
very high


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Bestiary
Narrative Illustraions
The World of Nasyita & Naga
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The World of Nasyita & Naga
Narrative Illustraions
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Anything beside images?
January 30th, 2017
Let's talk about this later.