To complete this exercise, edit your main.js
file. You'll demonstrate a strong familiarity with D3
data binding. Rather than provide you with a set of step-by-step instructions, below you'll find a list of requirements that describe the behavior of the applicaiton you're building.
draw
function that takes in a dataset as a parameter and properly manages the data-join process between the dataset and the DOM, including enter
, update
, and exit
. You'll have to perform a data-join for both rect
and text
elements. The width of your rect
elements should simply correspond to the score on each exam (we'll go beyond this in later modules).Sandbox section: you'll add elements here


Jeremy Corbyn says monarchy 'needs a bit of improvement'
Jeremy Corbyn has said the monarchy ‘needs a bit of improvement’ after being asked on tonight’s ITV election debate if it was fit for purpose.
However Boris Johnson said the monarchy was ‘beyond reproach’.
It comes after Prince Andrew gave what many labelled a ‘car crash interview’ to the BBC, as he denied having sex with Virginia Roberts when she was 17.
He was also grilled on his links to convicted paedophile Jeffrey Epstein, who died in prison earlier this year.
Both Mr Corbyn and Mr Johnson were taking part in the first leader’s debate before the general election on December 12.
ITV’s Julie Etchingham then asked the party leaders if Prince Andrew was fit for purpose, to which Mr Corbyn said: ‘Before we discuss Prince Andrew I think we should discuss the victims that are there because of what (Jeffrey) Epstein was doing.
‘I think there are very, very serious questions that must be answered and nobody should be above the law, but the primary position ought to be the proper treatment of those people who were victims of the most appalling behaviour by apparently Epstein and many others.’
Advertisement Advertisement
Mr Johnson said ‘all our sympathies’ should be with the victims of Epstein, adding: ‘The law must certainly take its course.’
Got a story for Metro.co.uk?
Get in touch with our news team by emailing us at<EMAIL_ADDRESS>For more stories like this, check our news page.


A list of rare edge cases where Prism highlights code incorrectly.
There are certain edge cases where Prism will fail. There are always such cases in every regex-based syntax highlighter.
However, Prism dares to be open and honest about them. If a failure is listed here, it doesn’t mean it will never be fixed. This is more of a “known bugs” list, just with a certain type of bug.
(* Nested block
(* comments
(* on more than
2 levels *)
are *)
not supported *)
#cs
#cs
foo()
#ce
#ce
{
if($1) {
if($2) {
}
}
} // <- Broken
%%
%%
/+ /+ /+ this does not work +/ +/ +/
q{ q{ q{ this does not work } } }
'#{:atom} <- this should not be highligted'
2 / 3 / 4
The box 1A is a container
`${ /* } */ a + b }`
`${ '}' }`
`${foo({ a: { b: { c: true } } })}`
@import "some file.less";
@import<EMAIL_ADDRESS>nav ul {
&:extend(.inline);
background: blue;
}
.a:extend(.b) {}
foobar"param";
mov ax,1100_1000b
mov ax,1100_1000y
mov ax,0b1100_1000
mov ax,0y1100_1000
dd 1.222_222_222
# Doesn't work
# Does work
# Does work when prefixed with a space
^if(
$age>=4 # not too young
&& $age<=80 # and not too old
)
halt.
trace.
:- if(test1).
section_1.
:- elif(test2).
section_2.
:- elif(test3).
section_3.
:- else.
section_else.
:- endif.
"Foobar ${foo({
bar => {baz => 42}
baz => 42
})} <- broken"
{
or }
f"{'}'}"
\d .
+---------------+----------+
| column 1 | column 2 |
+--------------+-----------+
| **bold**? | *italic*? |
+--------------+-----------+
No inline markup should be highlighted in the following code.
2 * x a ** b (* BOM32_* ` `` _ __ |
"*" '|' (*) [*] {*} <*> ‘*’ ‚*‘ ‘*‚ ’*’ ‚*’ “*” „*“ “*„ ”*” „*” »*« ›*‹ «*» »*» ›*›
/* Nested block
/* comments
are */
not supported */
|x| x + 1i;
.page
color = 5px + 9px
!width = 13px
.icon
width = !width
a:hover
text-decoration: underline
/* Nested block
/* comments
are */
not supported */
/* Nested block
/* comments
are */
not supported */
But Textile inside HTML should be just fine.
This _should_ work properly.
*But this is definitely broken.*

{{#switch:{{PAGENAME}}
| L'Aquila = No translation
| L = Not OK
| L'Aquila = Entity escaping
| L'Aquila = Numeric char encoding
}}
''Italic with '''bold''' inside''


Class jaws.Animation
Manages an animation with a given list of frames. "Field Summary" contains options for the Animation()-constructor.
- Defined in: animation.js
| Constructor Attributes | Constructor Name and Description |
|---|---|
|
jaws.Animation(options)
|
| Field Attributes | Field Name and Description |
|---|---|
|
Rewind the animation frame by frame when end is reached
|
|
|
-1 for backwards animation.
|
|
|
How long should each frame be displayed
|
|
|
Containing width/height, eg.
|
|
|
Images/canvaselements
|
|
|
Start on this frame
|
|
|
Restart animation when end is reached
|
|
|
When cutting out frames from a sprite sheet, start at this frame
|
|
|
Function to call when animation ends.
|
|
|
How to cut out frames frmo sprite sheet, possible values are "down" or "right"
|
Method Summary
| Method Attributes | Method Name and Description |
|---|---|
|
returns true if animation is at the very first frame
|
|
|
returns true if animation is at the very last frame
|
|
|
returns the current frame
|
|
|
next()
Moves animation forward by calling update() and then return the current frame
|
|
|
slice(start, stop)
works like Array.slice but returns a new Animation-object with a subset of the frames
|
|
|
toString()
Debugstring for Animation()-constructor
|
|
|
update()
Propells the animation forward by counting milliseconds and changing this.index accordingly
Supports looping and bouncing animations
|
Class Detail
jaws.Animation(options)
// in setup() anim = new jaws.Animation({sprite_sheet: "droid_11x15.png", frame_size: [11,15], frame_duration: 100}) player = new jaws.Sprite({y:300, anchor: "center_bottom"}) // in update() player.setImage( anim.next() ) // in draw() player.draw()
- Parameters:
- options
Field Detail
{bool}
bounce
Rewind the animation frame by frame when end is reached
{int}
frame_direction
-1 for backwards animation. 1 is default
{milliseconds}
frame_duration
How long should each frame be displayed
{array}
frame_size
Containing width/height, eg. [32, 32]
{array}
frames
Images/canvaselements
{int}
index
Start on this frame
{bool}
loop
Restart animation when end is reached
{int}
offset
When cutting out frames from a sprite sheet, start at this frame
{function}
on_end
Function to call when animation ends. triggers only on non-looping, non-bouncing animations
{string}
orientation
How to cut out frames frmo sprite sheet, possible values are "down" or "right"
Method Detail
-
atFirstFrame()returns true if animation is at the very first frame
-
atLastFrame()returns true if animation is at the very last frame
-
currentFrame()returns the current frame
-
next()Moves animation forward by calling update() and then return the current frame
-
slice(start, stop)works like Array.slice but returns a new Animation-object with a subset of the frames
- Parameters:
- start
- stop
-
toString()Debugstring for Animation()-constructor
var anim = new Animation(...) console.log(anim.toString())
-
update()Propells the animation forward by counting milliseconds and changing this.index accordingly Supports looping and bouncing animations


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What do our alumni say about us..?
Thanks to the club for everything. Being student president for the session 2018-19, we reimagined the whole way of doing things. We launched around 20+ projects, initiated ProSang, connected club projects to the companies, and launched my startup TSAW Drones during the event. The time at the club, with the members, transformed me a lot, taught me to dare things & do it uniquely, being fearless.
I joined the club in the first year thinking ki "Kuch to kar lete hain!" but it never left me. I have learned many things, from joining two wires to handle the disappointment that you get after working too hard on a project. It will not just teach you robotics; it will help you develop the most fundamental problem-solving ability and handle pressure and loss, which is natural in life.
I had never thought that an arbitrary decision of joining the Robotics club could tweak me by teaching such interdisciplinary things. Apart from the technical stuff, I could learn team management and the bliss of working altogether in a team. Participating in organizing them and being a team member to mentoring a team has played a crucial role in brushing me up to become a better version of myself. My reassuring seniors and ever-supportive colleagues made my journey even more beautiful. Indeed I am lucky enough to find my best friends for life through this platform. Of course, I had to go through some edgy, restless nights, but that's all that defines your current position. Hence I would never step back from owing the Robotics club for everything.


Phone:<PHONE_NUMBER>
Email<EMAIL_ADDRESS>Hours: Monday - Saturday, 8:00 AM to 9:00 PM (EST)
GitHub: github.com/JoshuaStover
LinkedIn: linkedin.com/joshua-stover


Focos is a navigation library that tracks elements on the screen defined in a grid of a certain size. You can navigate through the grid by using different keys. For navigation Focos uses arrow keys by default, but different bindings may be provided. Multiple bindings to the same action are allowed. You may navigate through the grid below using the bindings defined on the code snippet. Works best with a keyboard, a controller, or any device that triggers key events.
Get it via jsDelivr or download it from the repository. Links below.

Item 1

Item 2

Item 3

Item 4

...


Class PhotoInfo
Store photo information
Namespace: Anki.Vector.Types
Assembly: Anki.Vector.dll
Syntax
public class PhotoInfo
Properties
| Improve this Doc View SourceDateTime
Gets the photo taken on date and time.
public DateTime DateTime { get; }
Property Type
| DateTime |
PhotoCopiedToApp
Gets a value indicating whether photo was copied to application.
public bool PhotoCopiedToApp { get; }
Property Type
| Boolean |
PhotoId
Gets the photo identifier.
public uint PhotoId { get; }
Property Type
| UInt32 |
ThumbCopiedToApp
Gets a value indicating whether thumb was copied to application.
public bool ThumbCopiedToApp { get; }
Property Type
| Boolean |


---
layout: post
title: 1/6
date: '2013-01-06T21:35:00.001-07:00'
author: Jacob .
tags:
modified_time: '2013-01-06T21:35:29.476-07:00'
blogger_id: tag:blogger.com,1999:blog-6400085873105072120.post-6251843416285812147
blogger_orig_url: http://www.svlark.com/2013/01/16.html
---
Worked on the last of the office shelving mess and made it worse in the process.


deepmatcher.word_aggregators¶
Pool¶
AttentionWithRNN¶
-
class
deepmatcher.word_aggregators.
AttentionWithRNN
(hidden_size=None, input_dropout=0, rnn='gru', rnn_pool_style='birnn-last', score_dropout=0, input_context_comparison_network='1-layer-highway', value_transform_network=None, transform_dropout=0, input_size=None)[source]¶ Attention and RNN based Word Aggregator. This class can be used when the aggregation on the primary input also needs the information from the context. Specifically, the
Hybrid
attribute summarizer uses this aggregation approach by default. This module takes a primary input sequence and a context input sequence and computes a single summary vector for the primary input sequence based on the information in the context input. To do so, it does the following:- Applies an RNN over the context input.
- Uses a Pool operation over the RNN to obtain a single vector summarizing the information in the context input.
- Based on this context summary vector, uses attention to score the relevance of each vector in the primary input sequence.
- Performs a weighted average of the vectors in the primary input sequence based on the computed scores to obtain a context dependent summary of the primary input sequence.
Parameters: - hidden_size (int) – The default hidden size to use for the RNN, input_context_comparison_network, and the value_transform_network.
- input_dropout (float) – If non-zero, applies dropout to the input to this module. Dropout probability must be between 0 and 1.
- rnn (string or
RNN
or callable) – The RNN used in Step 1 described above. Argument must specify an RNN operation. - rnn_pool_style (string) – The pooling operation used in Step 2 described above. Argument must specify a Pool operation.
- score_dropout (float) – If non-zero, applies dropout to the attention scores computed in Step 3 described above. Dropout probability must be between 0 and 1.
- input_context_comparison_network (string or
Transform
or callable) – The neural network that takes each vector in the primary input sequence concatenated with the context summary vector to obtain a hidden vector representing the primary vector’s relevance to the context input. Argument must specify a Transform operation. - value_transform_network (string or
Transform
or callable) – The neural network to transform the primary input sequence before taking its weighted average in Step 4 described above. Argument must be None or specify a Transform operation. - transform_dropout (float) – If non-zero, applies dropout to the output of the value_transform_network, if applicable. Dropout probability must be between 0 and 1.
- input_size (int) – The number of features in the input to the module. This parameter will be
automatically specified by
LazyModule
.


Smart Finance
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Select an environment
localhost
development
production
Click Here To Start!
1. Add begin location
{{point.index}}
{{point.latlon}}
{{startgeocode}}
{{start_mapInstruction}}
Next >
2. Add locations
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Preparation time
over 2 hours
Cooking time
30 mins to 1 hour
Serves
Makes 2 loaves
Dietary
This focaccia recipe is easy to make and easy to adapt. Try adding herbs such as rosemary or thyme, or perhaps some chopped chilli.
Place the flour, salt, yeast, olive oil and 300ml/10½fl oz of the water into a large bowl. Gently stir with your hand or a wooden spoon to form a dough then knead the dough in the bowl for five minutes, gradually adding the remaining water.
Stretch the dough by hand in the bowl, tuck the sides into the centre, turn the bowl 80 degrees and repeat the process for about five minutes.
Tip the dough onto an oiled work surface and continue kneading for five more minutes. Return the dough to the bowl, cover and leave to rise until doubled in size.
Line two large baking sheets with baking paper. Tip the dough out of the bowl and divide into two portions. Flatten each portion onto a baking sheet, pushing to the corners, then leave to prove for one hour.
Preheat the oven to 220C/425F/Gas 7. Drizzle the loaves with oil, sprinkle with fine sea salt then bake in the oven for 20 minutes. When cooked, drizzle with a little more olive oil and serve hot or warm.


Virtual Resource Design Patterns
Referencing an entity from more than one place.
About Virtual Resources
By default, any resource you describe in a client’s Puppet config will get sent to the client and be managed by that client. However, resources can be specified in a way that marks them as virtual, meaning that they will not be sent to the client by default. You mark a resource as virtual by prefixing @ to the resource specification; for instance, the following code defines a virtual user:
@user { luke: ensure => present }
If you include this code (or something similar) in your configuration then the user will never get sent to your clients without some extra effort.
How This Is Useful
Puppet enforces configuration normalization, meaning that a given resource can only be specified in one part of your configuration. You can’t configure user johnny in both the solaris and freebsd classes.
For most cases, this is fine, because most resources are distinctly related to a single Puppet class — they belong in the webserver class, mailserver class, or whatever. Some resources can not be cleanly tied to a specific class, though; multiple otherwise-unrelated classes might need a specific resource. For instance, if you have a user who is both a database administrator and a Unix sysadmin, you want the user installed on all machines that have either database administrators or Unix administrators.
You can’t specify the user in the dba class nor in the sysadmin class, because that would not get the user installed for all cases that matter.
In these cases, you can specify the user as a virtual resource, and then mark the user as real in both classes. Thus, the user is still specified in only one part of your configuration, but multiple parts of your configuration verify that the user will be installed on the client.
The important point here is that you can take a virtual resource and mark it non-virtual as many times as you want in a configuration; it’s only the specification itself that must be normalized to one specific part of your configuration.
How to Realize Resources
There are two ways to mark a virtual resource so that it gets sent to the agent: You can use a special syntax called a collection, or you can use the realize function.
Collections provide a simple syntax (sometimes referred to as the “spaceship” operator) for marking virtual objects as real, such that they should be sent to the agent. Collections require the type of resource you are collecting and zero or more attribute comparisons to specifically select resources. For instance, to find our mythical user, we would use:
User <| title == luke |>
As promised, we’ve got the user type (capitalized, because we’re performing a type-level operation), and we’re looking for the user whose title is luke. “Title” is special here — it is the value before the colon when you specify the user. This is somewhat of an inconsistency in Puppet, because this value is often referred to as the name, but many types have a name parameter and they could have both a title and a name.
If no comparisons are specified, all virtual resources of that type will be marked real.
This attribute querying syntax is currently very simple. The only comparisons available are equality and non-equality (using the == and != operators, respectively), and you can join these comparisons using or and and. You can also parenthesize these statements, as you might expect. So, a more complicated collection might look like:
User <| (groups == dba or groups == sysadmin) or title == luke |>
Realizing Resources
Puppet provides a simple form of syntactic sugar for marking resource non-virtual by title, the realize function:
realize User[luke]
realize(User[johnny], User[billy])
The function follows the same syntax as other functions in the language, except that only resource references are valid values.
Virtual Define-Based Resources
Since version 0.23, define-based resources may also be made virtual. For example:
define msg($arg) {
notify { "$name: $arg": }
}
@msg { test1: arg => arg1 }
@msg { test2: arg => arg2 }
With the above definitions, neither of the msg resources will be applied to a node unless it realizes them, e.g.:
realize( Msg[test1], Msg[test2] )
Remember that when referencing an instance of a namespaced defined type, or when specifying such a defined type for the collection syntax, you have to capitalize all segments of the type’s name (e.g. Apache::Vhost['wordpress']
or Apache::Vhost <| |>
).
Keep in mind that resources inside virtualized define-based
resources must have unique names. The following example will
fail, complaining that File[foo]
is defined twice:
define basket($arg) {
file{'foo':
ensure => present,
content => "$arg",
}
}
@basket { 'fruit': arg => 'apple' }
@basket { 'berry': arg => 'watermelon' }
realize( Basket[fruit], Basket[berry] )
Here’s a working example:
define basket($arg) {
file{"$name":
ensure => present,
content => "$arg",
}
}
@basket { 'fruit': arg => 'apple' }
@basket { 'berry': arg => 'watermelon' }
realize( Basket[fruit], Basket[berry] )
Note that the working example will result in two File resources, named fruit
and berry
.


Watch an extremely pure video of Post Malone dancing joyfully during Shania Twain's performance at the 2019 AMAs, Business Insider - Business Insider Singapore
by Callie Ahlgrim- The 2019 American Music Awards ended with a powerful performance from Shania Twain.
- An extremely pure video shows Post Malone, who was sitting front row, dancing joyfully as she sang her iconic hit “Man! I Feel Like A Woman.”
- The video, originally shared by @PortalPostBR, was reposted with the caption: “Not a phone in sight. Just Post Malone vibing to Shania Twain at The #AMAs.”
- It’s racked up tens of thousands of likes.
- Watch the video below.
- Visit Insider’s homepage for more stories.


You are limited to two occupational changes.
Judging by your strength, I feel that your faith is stronger than others. Keep this faith always, and constantly move forward. May the will of Einhasad guide you on path of righteousness.


QNativeGestureEvent Class
The QNativeGestureEvent class contains parameters that describe a gesture event. More...
| Header: | #include <QNativeGestureEvent> |
| qmake: | QT += gui |
| Since: | Qt 5.2 |
| Inherits: | QInputEvent |
Public Functions
| QNativeGestureEvent(Qt::NativeGestureType type, const QPointF &localPos, const QPointF &windowPos, const QPointF &screenPos, qreal realValue, ulong sequenceId, quint64 intValue) | |
| Qt::NativeGestureType | gestureType() const |
| const QPoint | globalPos() const |
| const QPointF & | localPos() const |
| const QPoint | pos() const |
| const QPointF & | screenPos() const |
| qreal | value() const |
| const QPointF & | windowPos() const |
- 2 public functions inherited from QInputEvent
- 6 public functions inherited from QEvent
Additional Inherited Members
- 1 property inherited from QEvent
- 1 static public member inherited from QEvent
- 2 protected variables inherited from QEvent
Detailed Description
The QNativeGestureEvent class contains parameters that describe a gesture event.
Native gesture events are generated by the operating system, typically by interpreting touch events. Gesture events are high-level events such as zoom or rotate.
| Event Type | Description | Touch equence |
|---|---|---|
| Qt::ZoomNativeGesture | Magnification delta in percent. | macOS: Two-finger pinch. |
| Qt::SmartZoomNativeGesture | Boolean magnification state. | macOS: Two-finger douple tap (trackpad) / One-finger douple tap (magic mouse). |
| Qt::RotateNativeGesture | Rotation delta in degrees. | macOS: Two-finger rotate. |
In addition, BeginNativeGesture and EndNativeGesture are sent before and after gesture event streams:
BeginNativeGesture ZoomNativeGesture ZoomNativeGesture ZoomNativeGesture EndNativeGesture
See also Qt::NativeGestureType and QGestureEvent.
Member Function Documentation
QNativeGestureEvent::QNativeGestureEvent(Qt::NativeGestureType type, const QPointF &localPos, const QPointF &windowPos, const QPointF &screenPos, qreal realValue, ulong sequenceId, quint64 intValue)
Constructs a native gesture event of type type.
The points localPos, windowPos and screenPos specify the gesture position relative to the receiving widget or item, window, and screen, respectively.
realValue is the macOS event parameter, sequenceId and intValue are the Windows event parameters.
Qt::NativeGestureType QNativeGestureEvent::gestureType() const
Returns the gesture type.
This function was introduced in Qt 5.2.
const QPoint QNativeGestureEvent::globalPos() const
Returns the position of the gesture as a QPointF in screen coordinates
This function was introduced in Qt 5.2.
const QPointF &QNativeGestureEvent::localPos() const
Returns the position of the gesture as a QPointF, relative to the widget or item that received the event.
This function was introduced in Qt 5.2.
const QPoint QNativeGestureEvent::pos() const
Returns the position of the mouse cursor, relative to the widget or item that received the event.
This function was introduced in Qt 5.2.
const QPointF &QNativeGestureEvent::screenPos() const
Returns the position of the gesture as a QPointF in screen coordinates.
This function was introduced in Qt 5.2.
qreal QNativeGestureEvent::value() const
Returns the gesture value. The value should be interpreted based on the gesture type. For example, a Zoom gesture provides a scale factor while a Rotate gesture provides a rotation delta.
This function was introduced in Qt 5.2.
See also QNativeGestureEvent and gestureType().
const QPointF &QNativeGestureEvent::windowPos() const
Returns the position of the gesture as a QPointF, relative to the window that received the event.
This function was introduced in Qt 5.2.


Module: Vertx::ReadStream
- Included in:
- AsyncFile, HttpClientResponse, HttpServerFileUpload, HttpServerRequest, NetSocket, SockJSSocket, WebSocket
- Defined in:
- src/main/api_shim/core/streams.rb
Overview
A mixin module which represents a stream of data that can be read from.
Any class that mixes in this module can be used by a Pump to pump data from a ReadStream to it.
Instance Method Summary (collapse)
-
- (Object) data_handler(&hndlr)
Set a data handler.
-
- (Object) end_handler(&hndlr)
Set an end handler on the stream.
-
- (Object) exception_handler(&hndlr)
Set an execption handler on the stream.
-
- (Object) pause
Pause the ReadStream.
-
- (Object) resume
Resume reading.
Instance Method Details
- (Object) data_handler(&hndlr)
Set a data handler. As data is read, the handler will be called with the data.
84 85 86 87 88 89 |
# File 'src/main/api_shim/core/streams.rb', line 84 def data_handler(&hndlr) @j_del.dataHandler(Proc.new { |j_buff| hndlr.call(Buffer.new(j_buff)) }) self end |
- (Object) end_handler(&hndlr)
Set an end handler on the stream. Once the stream has ended, and there is no more data to be read, this handler will be called.
112 113 114 115 |
# File 'src/main/api_shim/core/streams.rb', line 112 def end_handler(&hndlr) @j_del.endHandler(hndlr) self end |
- (Object) exception_handler(&hndlr)
Set an execption handler on the stream.
105 106 107 108 |
# File 'src/main/api_shim/core/streams.rb', line 105 def exception_handler(&hndlr) @j_del.exceptionHandler(hndlr) self end |
- (Object) pause
Pause the ReadStream. After calling this, the ReadStream will aim to send no more data to the #data_handler
92 93 94 95 |
# File 'src/main/api_shim/core/streams.rb', line 92 def pause @j_del.pause self end |
- (Object) resume
Resume reading. If the ReadStream has been paused, reading will recommence on it.
98 99 100 101 |
# File 'src/main/api_shim/core/streams.rb', line 98 def resume @j_del.resume self end |


[gecode-users] Parallel conditional combinator
Guido Tack
tack at ps.uni-sb.de
Thu Apr 24 11:41:04 CEST 2008
Mauricio Toro wrote:
> I am thinking about implementing the
> parallel conditional combinator as a
> Gecode propagator. Any ideas about
> how to do this efficiently?
I guess by parallel conditional you mean something like (if b1 then a1
|| if b2 then a2 || ...), where || means parallel composition, and
with a short-circuit semantics that the first b that is determined to
be true "wins" and all other branches are discarded?
I think you could just extend the conditional that you already have.
As soon as one guard is determined, you execute that branch and remove
the conditional propagator (by returning ES_SUBSUMED). You have to be
very careful, though: you can easily program non-monotonic propagators
this way, which are not allowed in Gecode! E.g., if you wait for two
conditions, it may depend on the order of propagation which condition
is satisfied first, so the constraints added by the parallel
conditional can be different, depending on the order of propagator
execution. Don't do this unless you know exactly what you're doing (I
cannot see how to use this in a reasonable way).
Remember that Gecode is meant for solving constraint problems, not for
executing cc programs!
> By the way, where can I find examples
> about using the reflection post and spec
> propagator methods?
Here:
http://www.gecode.org/gecode-doc-latest/PageReflection.html
Cheers,
Guido
More information about the gecode-users
mailing list


The course will explore the principles of emerging blockchain technologies. The course will first cover basic data structures and cryptographic building blocks in blockchain such as distributed systems, cryptographic primitives including cryptographic hash functions, asymmetric cryptography, digital signatures. The course will then focus on critical blockchain components and infrastructures such as distributed ledger, consensus protocols, cryptocurrencies and smart contracts. The course will also cover several recent advancements in blockchains such as privacy-preserving blockchain, decentralized applications. The successful students are expected to obtain a good understanding of cryptographic primitives and blockchain essentials, which will be a unique skill for competitive R&D positions in industry.
Time: Tuesday and Thursday @ 5:00 PM - 6:10 PM (EST)
Location: Online via Zoom (link announced on Canvas)
Lecturer: Dr. Thang Hoang (@thanghoang)
| Homework | 30% |
| Presentation | 25% |
| Research Project | 40% |
| Class participation | 5% |
| Total | 100% |
A(90+) B(81-89) C(71-80) D(61-70) E (51-60) F(50-)
This course strictly follows the VT code of conduct.
| Week | Date | Topic | Material/Slide |
|---|---|---|---|
| 1 | Jan 19 (Tue) | Introduction | |
| Jan 21 (Thu) | Blockchain Overview | ||
| 2 | Jan 26 (Tue) | Blockchain Overview (cont.) Distributed System | PDF |
| Jan 28 (Thu) | Distributed Algorithms | ||
| 3 | Feb 02 (Tue) | Cryptographic Hash | |
| Feb 04 (Thu) | Cryptographic Hash (cont.) | ||
| 4 | Feb 09 (Tue) | Merkle Tree RSA | |
| Feb 11 (Thu) | RSA (cont), DSA and Elliptic Curve Crypto Homework 1 (Due Mar 05, 2021) | PDF HW1 |
|
| 5 | Feb 16 (Tue) | Elliptic Curve Crypto (cont) Bitcoin (Network and Wallet) | PDF |
| Feb 18 (Thu) | Bitcoin (cont.) | ||
| 6 | Feb 23 (Tue) | Bitcoin (cont.) | |
| Feb 25 (Thu) | Spring break (no class) | ||
| 7 | Mar 02 (Tue) | Bitcoin (cont.) | |
| Mar 04 (Thu) | Bitcoin (cont.) | ||
| 8 | Mar 09 (Tue) | Bitcoin (cont.) | |
| Mar 11 (Thu) | Bitcoin (cont.) Virtual mining Homework 2 (Due Apr 02, 2021) | PDF HW2 |
|
| 9 | Mar 16 (Tue) | Virtual mining (cont.) | |
| Mar 18 (Thu) | Virtual mining (cont.) Programmable blockchain (Ethreum) | PDF |
|
| 10 | Mar 23 (Tue) | Ethereum and smart contract | |
| Mar 25 (Thu) | Smart contract (cont.) and distributed applications | ||
| 11 | Apr 30 (Tue) | Distributed applications (cont.) Privacy-preserving blockchain | PDF |
| Apr 01 (Thu) | Anonymity and Deanonymization in Bitcoin | ||
| 12 | Apr 06 (Tue) | Spring break (no class) | |
| Apr 08 (Thu) | Zerocoin Homework 3 (Due Apr 30, 2021) | PDF HW3 |
|
| 13 | Apr 13 (Tue) | Zerocash | |
| Apr 15 (Thu) | Verifiable Computation (SNARK, STARK) | ||
| 14 | Apr 20 (Tue) | Sam Sklopan Ming Cheng |
|
| Apr 22 (Thu) | Yang Hu Peng Tan Asha R Cheruvu | ||
| 15 | Apr 27 (Tue) | Mohit Bhasi Thazhath Eric Roth Fengjiao Li | |
| Apr 29 (Thu) | Zhongdong Liu Cameron Joseph Knight Satish Venkatesan |
||
| 16 | May 04 (Tue) |
Matthew Harrington Wyatt Joel Sweat Wenjia Song |
|
| May 06 (Thu) | (Backup) |
(announced) see above for the schedule.
See here for information about the final project.


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What is this?
This page will generate a BibTEX file from your LibraryThing data in three easy steps!
- Download your LibraryThing data.
- Upload the LibraryThing_TD.xls file.
- Click on the Generate BibTeX button below.
Upload your LibraryThing library
Need help?
If you have any problems uploading your LibraryThing file, or if you have problems using the resulting file, please email me. Please attach a copy of your LibraryThing_TD.xls file to your email so I can use it when troubleshooting your problem.
Also, please let me know if you have any suggestions for improvements.
My To Do List
Here is a list of known bugs and feature requests that I'm working on:
- Find a better way to deal with missing data (e.g., if the author and editor are both missing).
- Parse editors, volumes, and editions.


Here we use a for loop for a list
We can also add if/else statements
Found you in the list of puppies Stray!
Hmm, Rufus isn't in this list.


--- layout: post status: publish published: true title: Your Belated I-Cubs Preview author: display_name: Sean Clement login: Sean email<EMAIL_ADDRESS>url: '' author_login: Sean author_email<EMAIL_ADDRESS>wordpress_id: 11136 wordpress_url: http://ivyenvy.com/?p=11136 date: '2015-04-11 22:29:13 +0000' date_gmt: '2015-04-12 03:29:13 +0000' categories: - Infield - Minor Leagues - Outfield - Relief Pitching - Starting Pitching - Prospects tags: - Iowa Cubs - Javier Baez - Kris Bryant - Addison Russell comments: - id: 17943 author: costa rican chata author_email: '' author_url: '' date: '2015-04-14 05:06:11 +0000' date_gmt: '2015-04-14 10:06:11 +0000' content: |- john lester is quite possibly the best SP-3 in the majors . cubs should put 25 cent coin slots on those port-o-johns , and go out and get two of price / cueto / zimmerman for the 2016 season . - id: 17953 author: Cubbieslover author_email: '' author_url: '' date: '2015-04-14 21:45:45 +0000' date_gmt: '2015-04-15 02:45:45 +0000' content: This is the best article I have ever read! Very informative and super attractive author. Double win. Gooooooo cubs! :) - id: 17987 author: PaulDChapman author_email: '' author_url: '' date: '2015-04-16 17:34:23 +0000' date_gmt: '2015-04-16 22:34:23 +0000' content: Well done. - id: 18018 author: Gma Ruth author_email: '' author_url: '' date: '2015-04-17 14:13:02 +0000' date_gmt: '2015-04-17 19:13:02 +0000' content: |- I agree..."Well done". Over the years I have personally learned and continue to learn about players, trades and MLB from Sean. Keep up the good work.... Love Gma ---
This is a little late as the I-Cubs are already three games into their season, but for at least the next month, the Iowa Cubs will again boast the most exciting roster in MiLB. The talent roaming the infield is unmatched with three guys poised to terrorize Pacific Coast League pitching in Bryant, Baez, Russell (all have been named top-5 prospects in baseball within the last two years) until Chicago and the Big Leagues come calling.
There’s not much left unsaid about All-World third baseman Kris Bryant at this point, but he is a must-see talent in PCL action until service time rules are satisfied he gets enough defensive reps at the hot corner and in left field to be ‘Big League Ready.' Once he's called up, it wont be long before you're checking this page daily.
The length of Javier Baez’ return trip to Des Moines will be dependent on his ability to improve the contact issues that led to him batting well under the Mendoza Line during his stint in The Show last year. The other tools are all where they need to be but until the hit tool comes around, the speed, power, and glove will be on display at Principal Park instead of Wrigley Field.

The Iowa infield will be rounded out by organizational depth in Jonathan Mota and Chris Valiaka.
As for the outfield, Junior Lake is the headliner for now and he will look to continue the progress he made over the winter in regards to plate discipline and pitch recognition in the hopes that this development will allow him to reach some of his yet untapped potential. Other outfielders will include John Andreoli and Rubi Silva, plus depth guys in Mike Baxter and Adron Chambers. More prospecty excitement is on the way to Iowa in short order with CF Albert Almora and LF (and part-time catcher) Kyle Schwarber tabbed as short-timers for Tennessee.
Speaking of catchers, Rafael Lopez won’t offer a ton by way of the bat but he has a major-league-caliber glove and is ready whenever the Cubs may call upon him. He will be backed-up by Taylor Davis.
Pierce Johnson and Eric Jokisch, both pitchers capable of having Kyle Hendricks-esque seasons, if things break right, headline the arms in Iowa to start the year. Johnson wields more upside, but Jokisch has the polish to fill in for Chicago now if they develop a need. Zac Rosscup is a reliever who pitched well enough this spring to earn an MLB bullpen spot but the roster just didn’t shake out in his favor, though he will be up before long.
Armando Rivera is yet another power arm who may well be the heir to ‘Closer of the Future’ title, though guys like Neil Ramirez, Hector Rondon, and Justin Grimm aren’t going anywhere soon. Either way, the train of high leverage RHP coming from the Chicago bullpen won’t be slowing down anytime soon.
Drake Britton is another former Oriole pitcher who the Cubs hope to turn into the player scouts hoped he would be, and although Jake Arrieta he is not, Britton has a chance to be a quality big league arm.
Other intriguing pitchers include Blake Parker, Joe Ortiz, Carlos Pimintel and Barret Loux but once again there is more fire-power on the way- CJ Edwards is starting his 2015 campaign in AA, but will be joining the squad in Iowa before long.
This year’s edition of the Iowa Cubs once again looks poised to be the most talked about minor league team in baseball, and even as top names like Bryant, Russell, and Baez graduate, there are high quality prospects in AA-Tennessee who will be champing at the bit to take their places in the minor league spotlight.


From the death certificate
for Alva Baldwin Stickle
Marlboro, Stark Co., OH
#83025
PERSONAL AND STATISTICAL
PARTICULARS
male, white, married, stone
mason
birth: Sept. 30, 1848, Ohio
age at death: 70 yrs. 1 mos. 10 da.
father: Samuel Stickle, born Ohio
mother: Lucy Smith, born Ohio
informant: Chas. Stickle, Marlboro, O.
MEDICAL CERTIFICATE OF DEATH
date of death: Nov. 18, 1918
statement: I hereby certify that I attended deceased
from Oct. 19, 1918, to Nov. 10, 1918 and that death occurred, on the date above
at 10 a.m.
cause: Chronic Bronchitis (non-tubercular); duration:
10 years
contributory: Cardiac-Vascular degeneration:
duration: 2 years
signed: L. B. Santee,* M.D., Nov. 12, 1918,
Louisville,** Ohio
burial: Marlboro, O., Nov. 12, 1918
undertaker: Cassady-Turner, Alliance
* Submitter's notes: The writing was difficult to read and this
may not be correct.
** This LOUISVILLE is the one in Stark County, Ohio.
Provided by Betty Latta Kitchen
Click here for the Short-Cut Table of Contents


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The main classes for the MindTerm applications. There are two
different main applications. MindTerm, which is the full blown
application, and MindTermLite which has a smaller footprint and a much
more limited interface.
The modules provide different extra functionalities.


Suresh Kumaar Jayaraman
Robotics Institute . Carnegie Mellon University . Postdoctoral researcher at TBD2
I will be joining Carnegie Mellon Univerity as a postdoc with Prof. Aaron Steinfeld, Prof. Reid Simmons, and Prof. Henny Admoni. Previously, I was a postdoc at Cornell Univerity working with Prof. Guy Hoffman. I completed my Ph.D in Mechanical Engineering at the University of Michigan, Ann Arbor, advised by Professor Dawn Tilbury. My research motivation is in developing safe and trustworthy human-AI interactions, whether the human and AI agents are operating together as a team or as individuals. My research focuses on (i) identifying and examining the effects of various antecedents of trust, (ii) developing computational models of human behaviors and their interaction behaviors with autonomous systems, and (iii) developing adaptive autonomous systems that can calibrate and maintain human trust to improve safety and performance.
Current position
Postdoctoral associate at Carnegie Mellon University working with Prof. Aaron Steinfeld.
Prior education
- Ph.D. in Mechanical Engineering at UM, Ann Arbor, in 2021.
- M.S. in Mechanical Engineering at UM, Ann Arbor, in 2018.
- B.E. in Production Engineering at Anna University , India in 2013.
Research Interests
group human-AI interactions, trust in AI/robots, human behavior modeling, interaction-aware control, socially intelligent agents
Clubs and Recreation
Apart from research, I have been part of Graduate Rackham International as the co-chair of the Mentorship team (2019 - 2021) to help international graduate students find appropriate support and mentorship. When not working, I enjoy cooking, playing board games, and watching movies/series.News
| Aug 2021 | Started my postdoc position at the HRC2 lab at Cornell University with Prof. Guy Hoffman. |
|---|---|
| Jul 2021 | Defended my Ph.D. thesis titled “Human behavior modeling and human beahvior-aware control of automated vehicles”. |
| Feb 2021 | Our recent paper on multimodal pedestrian behavior modeling got published in IEEE Access. |
| Dec 2020 | Our paper, “Analysis and Prediction of Pedestrian Crosswalk Behavior during Automated Vehicle Interactions”, was recently listed on SSRN’s Top Ten download list for: InfoSciRN: Robotics (Topic). |
| Jul 2020 | Our paper on behavior-aware automated vehicle control was presented at the American Control Conference (ACC). |
Selected publications
- Multimodal Hybrid Pedestrian: A Hybrid Automaton Model of Urban Pedestrian Behavior for Automated Driving ApplicationsIEEE Access 2021
- Efficient Behavior-aware Control of Automated Vehicles at Crosswalks using Minimal Information Pedestrian Prediction ModelIn 2020 American Control Conference (ACC) 2020
- Pedestrian Trust in Automated Vehicles: Role of Traffic Signal and AV Driving BehaviorFrontiers in Robotics and AI 2019


In the last two posts about “clean tests”, we talked about the structure of a test, how to eliminate duplication, and how to make intent clear when using mocks. We left off with a question of magic values: Why do we seem to use them in our tests, when we know they are wrong in production code? Let’s explore that and see how to eliminate their use in our tests without making the tests hard to understand.
In non-test code, pretty much any literal that isn’t 0, 1, -1, the empty string, nil
/null
, or some universal constant like 60 (number of seconds in a minute), is a magic value. A naked literal just sitting out there with no context makes code hard to understand, and we usually whisk them away inside a constant or injected value. Suppose we come across this code:
1 2 3 4 5 |
|
We want to know what 0.75
actually means. If we’d used a constant, it would be clearer, like so:
1 2 3 4 5 |
|
Now we know that we’re comparing our percentage against a threshold and not some arbitrary value.
Tests, on the other hand, require a lot of literals, because we tend to be setting up very specific conditions, and that’s much easier with an example of some input. Here’s a test for our Saluation
class that we’ve seen before:
1 2 3 4 5 6 7 8 9 |
|
We have four magic values:
"David"
"Copeland"
:male
"Hello, David!"
Do these all need to be in there? Which ones are actually relevant, and which are true magic values that we should eliminate?
You’ll recall that in the first post on clean tests, we made this test clearer via method extraction, like so:
1 2 3 4 5 6 7 8 9 10 11 |
|
Essentially, we’ve hidden the fact that the last name and gender don’t matter inside the person_with_full_name
method. Some developers would object to this, preferring to have each test method stand on its own, without chasing down lots of helpers. This is a fair point, so let’s get rid of some irrelevant magic strings another way:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 |
|
We’ve still got helper methods (any_string
and any_gender
), but they’re tiny and they convey some information: the last name and the gender can be anything; they don’t matter. If you aren’t familiar with faker, it’s a handy gem for generating nonsense within certain parameters. This is perfect for creating values that don’t matter.
Does “David” matter? It matters more than the last name and gender, since it will show up in our greeting, but the first name could just as easily be “Mark” or “Mary”. So, let’s eliminate this magic value as well:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 |
|
Now, we’re talking! Read the test, in English: “first name is any string, a person has that as their first name, with any string as their last and any gender as their gender. Make a salutation for that person, and get the greetting. The greeting should equal ‘Hello’ plus the first name”. We’ve come very close to encoding a specification of our Salutation
class without using a special test framework or magic values, and the entire test is in the test method.
Just to hammer this home, lets port over the test that handles the case when you have no first name:
1 2 3 4 5 6 7 8 9 |
|
Here, :male
is very relevant, but "Copeland"
doesn’t particularly matter:
1 2 3 4 5 6 7 8 9 10 |
|
With syntax highlighing, the relevant parts of the test literally jump out at you. :male
and nil
are the only literals in this test, and they are therefore important.
By removing as many magic values as possible, and replacing them with the most general possible value to satisfy the test, we can make it crystal clear what’s going on in each test.
Can we carry this concept further? Consider the variable person
in the last test. Is this variable relevant? Somewhat. It is as relevant as salutation
or greeting
? No. salutation
is the object under test, and greeting
is the value we’re testing. Further, last_name
is a value that’s part of the expected result. To make this distinction clear, we can take advantage of Ruby’s ability to define fields on the fly:
1 2 3 4 5 6 7 8 9 10 |
|
This might seem superfluous in such a small test, but in a larger, more complex test (especially one dealing with a lot of mocks), this can be really helpful. You know that so-called “at” variables are important, and their values are meaningful across the “Given/When/Then” of the test, however local variables or short-lived and can be skimmed over when first understanding the test.
Setup/Teardown
Let’s have a brief word on setup and teardown methods. I’ve seen a lot of tests use the setup
method to set up various mock expectations, or do other test-specific setup. A problem arises when you need to add a test that doesn’t require that setup, or perhaps requires some additional setup. This causes two problems:
- You must now piece together what the “Givens” of a particular test are
- You are setting up conditions that aren’t relevant to all tests
Using nested contexts in tools like RSpec exacerbates this greatly, and it’s not uncommon to have setup code littered throughout the file.
I would suggest you keep all test-specific setup out of the setup
method entirely. Ideally, you won’t even have one. Occasionally, you’ll need to set up something around global variables that can’t be easily injected into your code. More commonly, you’ll have a teardown
method to make sure the next test has a clean slate (e.g. clean up temp files, restore configuration to default, etc.). These are OK. What you want to avoid is having any “Givens” or “Thens” inside these methods.
Conclusion
This brings us to the end of my whirlwind tour of clean tests. The overall goal is to prioritize comprehensibility of tests without sacrificing too much ease of creation. Your tests are going to be read and modified a lot more than written. In summary:
- Structure your tests in three parts: Given (setup), When (action), Then (assertions).
- Mock expectations are assertions, so put them in the “Then” block, and repeat the Given/When/Then if you need to due to your mocking framework.
- Don’t duplicate test code that’s the same by design, but do duplicate it if it’s the same by happenstance.
- Values important to a test should be variables.
- Values irrelevant to a test should be hidden in “any” style methods.
- If these rules muddy your tests, break them.
Afterword
I’ve been working this way for several months, and developed the clean_test gem to help. I’ll introduce that in a future blog post, but look at some of the tests written using these techniques. I tend to prefer knowledge be stored digitally, and not in my brain, so these techniques really help. Try writing your next set of tests like this and see what you think!


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Created from boredom and a need for inspiration in games development, The JamJar is a Discord bot designed to help Game developers and Game Jam enthusiasts easily generate game ideas or themes for inspiration or motivation in their development. No need to think or use external sites, generate a random game idea right in discord with your team. Once installed use ?info to get started!


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Baobab - A graphical tool to analyse disk usage
baobab is able to scan either specific folders or the whole filesystem (local and remote), in order to give the user a graphical tree representation including each directory size or percentage in the branch. It also auto-detects in real-time any change made to your home directory as far as any mounted/unmounted device. A graphical treemap window is also provided for any selected folder.
A detailed documentation on the program could be read at: http://www.mate.org/projects/baobab
Fabio s-1MARZOCCAs0 <thesaltydog@gmail.com>


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3 overrides of ProcessBreakpoint
Microsoft.PowerShell.Commands.Utility (3)
commands\utility\Disable-PSBreakpoint.cs (1)
31
protected override void
ProcessBreakpoint
(Breakpoint breakpoint)
commands\utility\Enable-PSBreakpoint.cs (1)
31
protected override void
ProcessBreakpoint
(Breakpoint breakpoint)
commands\utility\Remove-PSBreakpoint.cs (1)
20
protected override void
ProcessBreakpoint
(Breakpoint breakpoint)
10 references to ProcessBreakpoint
Microsoft.PowerShell.Commands.Utility (10)
commands\utility\Disable-PSBreakpoint.cs (1)
37
base.
ProcessBreakpoint
(breakpoint);
commands\utility\Enable-PSBreakpoint.cs (1)
37
base.
ProcessBreakpoint
(breakpoint);
commands\utility\Get-PSBreakpoint.cs (1)
208
ProcessBreakpoint
(b);
commands\utility\PSBreakpointUpdaterCommandBase.cs (2)
65
ProcessBreakpoint
(breakpoint);
81
ProcessBreakpoint
(breakpoint);
commands\utility\Set-PSBreakpoint.cs (5)
177
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183
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Why Make Maps?
- Visualize complex data
- Track information over distance and time
- Teach students a new way to engage with data and digital scholarship
- Give students a chance interact with primary source material directly
MapsEngine
- Google product - works with any Google ID (no extra credentials required)
- Make layers, change colours/shape of pins, add images, directions, etc.
- Easy and intuitive
Export Data and Manipulate!
- From MapsEngine, export data as KML
- Keyhole Markup Language - for geographical data
- Convert to geoJSON using ogr2ogr
- Import into complex mapping software, like Leaflet.js
Leaflet.js
- Open source, maintained by community
- Uses Javascript
- Mobile friendly
- Highly customizable: community built plugins and code your own additional features
Quick Start
- Start an html document
- Link to external leaflet JS files
- Add css
- Adding a div container for your map
- Add the javascript


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Meet the team!
Here at Dunder Mifflin our team is dedicated to delivering the best of the best to all customers and clients that come our way. In order to do this we only hire the best employees the industry has to offer and here you can view how exactly they affect our workplace.
Michael Scott
Regional Manager
Michael is an extremely capable boss who can handle any problem efficiently as well as a high achieving salesperson which allowed him to get to where he is.
<EMAIL_ADDRESS>Dwight Schrute
Assistant (to the) Regional Manager
Dwight is extremely passionate about paper and is also the leading salesman in the Scranton office. .
<EMAIL_ADDRESS>Stanley Hudson
Salesman
Stanley is a successive paper salesman as well as a professional crossword puzzle solver.
<EMAIL_ADDRESS>Jim Halpert
Salesman
Laid back and easy to get along with, Jim is a motivated paper salesman as well as a professional prankster on the side.
<EMAIL_ADDRESS>Pam Beasley
Secretary
The anchor of the office, Pam helps to keep other employees on track to meeting their goals and is well on her way to a higher position.
<EMAIL_ADDRESS>Angela Martin
Lead Accountant
Angela is a no nonsense cat lover who's personality and work help to balance out everyone else.
Amartin@gmail.com


Setup a basic pipeline (use Jenkins) for generating a security report for DVNA.
The DVNA code should be downloaded from Github and then undergo static analysis.
As part of the project understand what is the tech stack for DVNA hence what potential static analysis tools can be applied here.
Once a static analysis is done the report should be saved.
Next, the DVNA should get deployed in a server.
Setup the infrastructure, required for the task, on 2 virtual machines running locally on a laptop. One VM contains the Jenkins and related infrastructure, and the second VM is for deploying the DVNA using the pipeline.
Do document extensively in markdown and deploy the documentation in a MkDocs website on the second VM.
Additionally, there was some inferred task to address in the problem statement:
To create a comparative report about how various SAST tools performed.
To create a webhook to trigger the build when a push event occurs on the project repository on GitHub.
Task 2
Add onto Task 1 by implementing DAST in the pipeline for DVNA with OWASP ZAP and W3AF.
Make a report on the performance of the tools used to perform DAST by doing a comparative analysis of the results they provide.
Implement and use Semantic Versioning to tag versions of the documentation created as part of the tasks.
Append content for the task to the existing documentation from first task.
Task 3
Perform commit-based checks on the source code for linting errors to improve code quality and generate quality report.
Generate software bill of materials for all dependencies.
Task 4
Move the setup from the local machine to Cloud (AWS).
Store required secrets separately with a Secrets Management Service.
Task 5
Identify assumptions made while creating the pipeline for DVNA by implementing a similar setup for another application (SuiteCRM).


Question 58, Section 10.4
David Dobor
We want the length of the shortest path from a to c in the graph for question 2 on page 689. Here's that directed graph:
First, write down the adjacency matrix. (Here a is the first vertex, b second, and so on, in alphabetical order. Thus the (3, 2)-th entry in in the adjacency matrix signifies the presence of an edge from c, vertex 3, to b, vertex 2):
A = [0 1 0 1 0; 1 0 0 0 1; 0 1 0 0 0; 1 0 0 0 0; 0 0 1 1 0]
A = 0 1 0 1 0 1 0 0 0 1 0 1 0 0 0 1 0 0 0 0 0 0 1 1 0
What would the number of different paths of length 2 from a to c? That would be the entry (1, 3) in the adjacency matrix squared. So we compute and look at its (1, 3) entry.
A_squared = A^2
A_squared = 2 0 0 0 1 0 1 1 2 0 1 0 0 0 1 0 1 0 1 0 1 1 0 0 0
We see that entry (1, 3) is zero, meaning that there is no path of any length from a to c.
Bonus question: How many paths of length 2 from b to d are there according to this matrix? Trace all these paths on the above graph.
How about paths of length 3? We need :
A_cubed = A^3
A_cubed = 0 2 1 3 0 3 1 0 0 1 0 1 1 2 0 2 0 0 0 1 1 1 0 1 1
The entry in is now 1, meaning there is one path from a to c. Since we had to take the 3-d power of A to get the first non-zero entry in the (1, 3)-d position, we conclude that the length of that path is 3, and that no shorter paths from a to c exist in this graph (since all the lower powers of had zeros as entries in that position).


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Tamawashi's January victory among sumo's biggest shocks
by John GunningRoughly half of sumo’s recent first-time champions have been rikishi on the way up.
Takakeisho, Mitakeumi and Asanoyama are young guns who should all win titles again in the future.
The other half are rikishi like Tochinoshin and the now-retired Kisenosato — veterans whose Emperor’s Cup wins only confirmed the potential many had seen in them for years.
Tamawashi, while also an older wrestler, is the outlier.
The Mongolian needed seven years in the top division before making the sanyaku ranks below yokozuna and two more before he managed a winning record at that level.
While he held his own among sumo’s elite in 2017 and 2018, it seemed like Tamawashi had maxed out his potential and, given his age, would tread water before starting his inevitable decline.
When he lost to Mitakeumi on day five of the January meet this year to fall to 3-2, no one could have foreseen what would happen next.
Ten straight wins — including the downing of two ozeki and then a tournament-leading Hakuho to draw even with the yokozuna — Tamawashi pulled away to take the title.
There have been a lot of surprising championships recently, but none more so than the Kataonami man’s triumph.
It’s all the more remarkable when you remember that he only fell into sumo by accident.
Tamawashi had no real background in sumo when, as a university student learning cooking and hotel management in his home country, he decided to visit his sister who was studying at the University of Tokyo.
On that trip he met Kakuryu. One introduction led to another and he found himself in professional sumo shortly afterward.
Tamawashi has kept his love of cooking, though, and is well known for his ability to bake — and talk at length about — all kinds of cookies, cakes and sweets.
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CFA Textbook
--------------------
Study Session 3 Quantitative Methods :
Application
--------------------
Reading 10 Common Probability Distributions
--------------------
Summary
- A probability distribution specifies the probabilities of the
possible outcomes of a random variable.
- The two basic types of random variables are discrete random
variables and continuous random variables. Discrete random variables
take on at most a countable number of possible outcomes that we can
list as x1, x2, … In contrast, we cannot describe the possible
outcomes of a continuous random variable Z with a list z1, z2, …
because the outcome (z1 + z2)/2, not in the list, would always be
possible.
- The probability function specifies the probability that the
random variable will take on a specific value. The probability
function is denoted p(x) for a discrete random variable and f(x) for
a continuous random variable. For any probability function p(x), 0 ≤
p(x) ≤ 1, and the sum of p(x) over all values of X equals 1.
- The cumulative distribution function, denoted F(x) for both
continuous and discrete random variables, gives the probability that
the random variable is less than or equal to x.
- The discrete uniform and the continuous uniform distributions
are the distributions of equally likely outcomes.
- The binomial random variable is defined as the number of
successes in n Bernoulli trials, where the probability of success, p,
is constant for all trials and the trials are independent. A
Bernoulli trial is an experiment with two outcomes, which can
represent success or failure, an up move or a down move, or another
binary (two-fold) outcome.
- A binomial random variable has an expected value or mean
equal to np and variance equal to np(1 − p).
- A binomial tree is the graphical representation of a model of
asset price dynamics in which, at each period, the asset moves up
with probability p or down with probability (1 − p). The binomial
tree is a flexible method for modeling asset price movement and is
widely used in pricing options.
- The normal distribution is a continuous symmetric probability
distribution that is completely described by two parameters: its
mean, μ, and its variance, σ2.
- A univariate distribution specifies the probabilities for a
single random variable. A multivariate distribution specifies the
probabilities for a group of related random variables.
- To specify the normal distribution for a portfolio when its
component securities are normally distributed, we need the means,
standard deviations, and all the distinct pairwise correlations of
the securities. When we have those statistics, we have also specified
a multivariate normal distribution for the securities.
- For a normal random variable, approximately 68 percent of all
possible outcomes are within a one standard deviation interval about
the mean, approximately 95 percent are within a two standard
deviation interval about the mean, and approximately 99 percent are
within a three standard deviation interval about the mean.
- A normal random variable, X, is standardized using the
expression Z = (X − μ)/σ, where μ and σ are the mean and standard
deviation of X. Generally, we use the sample mean X as an estimate of μ and
the sample standard deviation s as an estimate of σ in this
expression.
- The standard normal random variable, denoted Z, has a mean
equal to 0 and variance equal to 1. All questions about any normal
random variable can be answered by referring to the cumulative
distribution function of a standard normal random variable, denoted
N(x) or N(z).
- Shortfall risk is the risk that portfolio value will fall
below some minimum acceptable level over some time horizon.
- Roy’s safety-first criterion, addressing shortfall risk,
asserts that the optimal portfolio is the one that minimizes the
probability that portfolio return falls below a threshold level.
According to Roy’s safety-first criterion, if returns are normally
distributed, the safety-first optimal portfolio P is the one that
maximizes the quantity [E(RP) − RL]/σP,
where RL is the minimum acceptable level of return.
- A random variable follows a lognormal distribution if the
natural logarithm of the random variable is normally distributed. The
lognormal distribution is defined in terms of the mean and variance
of its associated normal distribution. The lognormal distribution is
bounded below by 0 and skewed to the right (it has a long right
tail).
- The lognormal distribution is frequently used to model the
probability distribution of asset prices because it is bounded below
by zero.
- Continuous compounding views time as essentially continuous
or unbroken; discrete compounding views time as advancing in discrete
finite intervals.
- The continuously compounded return associated with a holding
period is the natural log of 1 plus the holding period return, or
equivalently, the natural log of ending price over beginning price.
- If continuously compounded returns are normally distributed,
asset prices are lognormally distributed. This relationship is used
to move back and forth between the distributions for return and
price. Because of the central limit theorem, continuously compounded
returns need not be normally distributed for asset prices to be
reasonably well described by a lognormal distribution.
- Monte Carlo simulation involves the use of a computer to
represent the operation of a complex financial system. A
characteristic feature of Monte Carlo simulation is the generation of
a large number of random samples from specified probability
distribution(s) to represent the operation of risk in the system.
Monte Carlo simulation is used in planning, in financial risk
management, and in valuing complex securities. Monte Carlo simulation
is a complement to analytical methods but provides only statistical
estimates, not exact results.
- Historical simulation is an established alternative to Monte
Carlo simulation that in one implementation involves repeated
sampling from a historical data series. Historical simulation is
grounded in actual data but can reflect only risks represented in the
sample historical data. Compared with Monte Carlo simulation,
historical simulation does not lend itself to “what if” analyses.
中文手册整理
- 离散分布
- 离散均匀分布（discrete uniform distribution）
- 二项分布（binomial distribution）
- 伯努利随机变量 Bernoulli random variable（零一分布），期望p，方差p(1-p)
- 二项随机变量（n次伯努利随机），期望np，方差np(1-p)
- 连续分布
- 连续均匀分布（continuous uniform distribution）
- 正态分布，normal distribution
- 正态分布可以由均值和方差完全描述 正态随机变量经线性组合得到的新随机变量仍然正态
- 正态分布是对称分布，偏度为零，超额峰度为0
- 正态随机变量经线性组合得到的新随机变量仍然正态
- 置信区间（confidence interval）
- 68% ~ [X-s,X+s]
- 90% ~ [X-1.65s,X+1.65s]
- 95% ~ [X-1.96s,X+1.96s]
- 99% ~ [X-2.58s,X+2.58s]
- 标准正态分布 standard normal distribution，X ~ N(0,1)
- E(aX+b) = aE(X)+b
- Var(aX+b) = a²×Var(X)
- 超亏风险和罗伊第一安全比率（SFR）
- 如果收益率服从正态分布，SFR就等于(X-u)/s，变相等于置信区间
- 当SFR的利率等于无风险利率时，SFR就是夏普比率
- 计算步骤
- 计算每个投资组合的SFR
- 选择最高的投资组合
- 对数正态分布
- 如果X的自然对数服从正态分布，那么X服从对数正态分布
- 对数正态分布取值范围大于零
- 对数正态分布是右偏的
- t分布
- 峰度小于正态分布
- 参数称为自由度，每个自由度对应一个t分布
- 当自由度n-1增加时，t分布逼进正态分布
- 离散复利收益和连续复利收益
- r=ln(1+R)，其中，r是连续复利收益率，R是离散复利收益率
- 连续复利收益的好处是，多期连续复利收益率等于单期连续复利收益的和
- 计算
- 给定持有期收益HPR，计算连续复利收益率
- r=ln(期末价格/期初价格)
- 跟踪误差（tracking error = total return - benchmark return）
- 蒙特卡罗模拟和历史模拟
- what if的问题 - 蒙特卡罗模拟的优势
- 真实分析的结果 - 历史模拟的优势
--------------------
Next Reading


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IFXNeighborMesh Class ReferenceInheritance diagram for IFXNeighborMesh:
List of all members.
Constructor & Destructor Documentation
| IFXNeighborMesh::IFXNeighborMesh |
( |
|
) |
[inline, protected] |
|
| virtual IFXNeighborMesh::~IFXNeighborMesh |
( |
|
) |
[inline, protected, virtual] |
|
Member Function Documentation
| virtual IFXRESULT IFXAPI IFXNeighborMesh::Allocate |
( |
IFXMeshGroup & |
rMeshGroup |
) |
[pure virtual] |
|
|
|
Allocates memory for NeighborMesh in a parallel array according to the sizes in IFXMeshGroup.
- Returns:
- IFX_E_OUT_OF_MEMORY if a memory allocation fails.
Implemented in CIFXNeighborMesh. |
|
|
Builds the NeighborMesh from the specified Meshgroup and vertex map.
Implemented in CIFXNeighborMesh. |
| virtual void IFXAPI IFXNeighborMesh::Deallocate |
( |
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) |
[pure virtual] |
|
| IFXINLINE void IFXNeighborMesh::GetCornerIter |
( |
U32 |
meshIndex, |
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|
U32 |
faceIndex, |
|
|
U32 |
cornerIndex, |
|
|
IFXCornerIter & |
rCornerIter |
|
) |
[virtual] |
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|
|
Gets the lightweight corner iterator for a corner of a face on a mesh.
The corner iterator is used for moving from one face to its neighbor faces.
Call GetNumMeshes() to determine maximum meshIndex. - Parameters:
-
| meshIndex |
in |
| faceIndex |
in |
| cornerIndex |
in |
| rCornerIter |
in-out |
|
| IFXINLINE void IFXNeighborMesh::GetFatCornerIter |
( |
U32 |
textureLayer, |
|
|
U32 |
meshIndex, |
|
|
U32 |
faceIndex, |
|
|
U32 |
cornerIndex, |
|
|
IFXFatCornerIter & |
rCornerIter |
|
) |
[virtual] |
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|
Gets the general purpose corner iterator for a corner of a face on a mesh.
This iterator provides methods that access face and vertex attribute information on the mesh. For performance reasons, you must specify which texture layer you want access to.
Calls GetNumMeshes() to determine maximum meshIndex. - Parameters:
-
| textureLayer |
in |
| meshIndex |
in |
| faceIndex |
in |
| cornerIndex |
in |
| rCornerIter |
in-out |
|
| IFXINLINE IFXNeighborFace * IFXNeighborMesh::GetNeighborFaceArray |
( |
U32 |
meshIndex |
) |
[virtual] |
|
| IFXINLINE U32 IFXNeighborMesh::GetNumMeshes |
( |
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) |
[virtual] |
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Returns the number of meshes (partitions) in attached IFXMeshGroup.
- Returns:
- 0 if Allocate() has not been called.
|
| IFXINLINE BOOL IFXNeighborMesh::IsAllocated |
( |
|
) |
[virtual] |
|
|
|
- Returns:
- TRUE if Allocate() has been successfully called.
|
| IFXINLINE BOOL IFXNeighborMesh::IsValid |
( |
|
) |
[virtual] |
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|
- Returns:
- TRUE if NeighborMesh connectivity is current.
FALSE if the NeighborMesh connectivity does not match the connectivity in the IFXMeshGroup. (Also known as the dirty flag.)
|
| virtual IFXRESULT IFXAPI IFXNeighborMesh::MarkAttributeDiscontinuities |
( |
IFXMeshGroup & |
rMeshGroup |
) |
[pure virtual] |
|
| IFXINLINE void IFXNeighborMesh::SetValid |
( |
BOOL |
state |
) |
[virtual] |
|
|
|
- Returns:
- TRUE if the NeighborMesh is current.
FALSE if a mesh was added/deleted from IFXMeshGroup, or if an associated IFXMesh has had a change in connectivity (if the faces have been changed/added/deleted).
|
Member Data Documentation
© 1999 - 2006 Intel Corporation. All rights reserved.
* Other names and brands may be claimed as the property of others.
|
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LG Patents Handset With Extendable Display That Doubles Screen Surface
LG has submitted a new patent, and this one is really interesting. This new LG patent shows off a smartphone with an extendable display. In its starting position, you have a smartphone, but when its display extends, you get a tablet with a 100-percent larger display.
LG patented devices with extendable displays in the past
This is not the first LG patent of a device with an extendable display, by the way. At the end of 2017, such a patent was spotted, and the same goes for a patent that popped up earlier this year.
In any case, this new patent has been registered with the WIPO (World Intellectual Property Office). This patent was published on November 15, and it includes some sketches, along with a brief description.
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In its phone state, this device is really narrow. The device does not include a display notch or a display hole, though, which makes us wonder where is its front-facing camera. When you extend this display, you end up with a considerably larger panel. When expanded, this device offers 100-percent larger surfaced than when in the phone state.
The description of this patent clearly states that this is not an eReader, so we're probably looking at a smartphone here. The device does not include any cameras. This is perhaps just the first stage of the development, so that could be why.
One thing is for sure, this device won't be released in its current form. LG almost certainly will not release a phone without cameras, that would just be odd.
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We're still not 100-percent sure how will this function. When you pull out the display, its middle portion will appear from within the phone, it seems. The smaller display then separates into two parts, and becomes the left and right side of the large display.
We're also not sure what will keep this phone in place when the display is retracted. The only thing that comes to mind are magnets, powerful ones.
Samsung patented a somewhat similar device in the past
LG is not the only company to have patented a device with an expandable display, though. Samsung did something similar, though Samsung's device expands from the right, not from the middle.
Advertisement
Patents like this make us wonder are expandable smartphones the new trend? Well, it is possible, but foldable smartphones just arrived, and we believe that foldables will take the spotlight in the coming years.
The Galaxy Fold and Mate X do suffer from first-gen issues, as those are first-gen products of a completely new form factor. Foldables will probably become better in time, though.
The Motorola Razr is quite a compelling smartphone as well, in terms of the design. That phone has its downsides as well, though. Foldable smartphones could become quite compelling in a couple of years, when the companies hit the sweet spot when it comes to the design and everything else.
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An explosion of peppermint taste combined with candy cane pieces.
Bourbon-spiked espresso ice cream swirled with bittersweet chocolate chunks.
Sweet birthday cake-flavored ice cream with swirls of blue frosting and heaps of colorful confetti sprinkles.
Non-dairy, non-fat and bursting with sweet, tangy flavor with real carrot (yes, we said carrot!) and fruit juices.
Non-dairy, non-fat, sweet raspberry-flavored Italian ice.
Can you say pucker up? You will after this classic southern pie flavor.
Two cotton candy flavored ice creams swirled together for that carnival sensation.
No sugar added vanilla ice cream swirled with delicious, sugar-free blueberry and pomegranate ripples.
Creamy vanilla ice cream with EVERYTHING! Chocolate, caramel, brownies, oreos, pecans, and cookie dough.
Almond ice cream with real pistachio nuts.
Rich vanilla ice cream with cookie dough pieces, liquid chocolate chips, and swirls of creamy peanut butter ripple.
Creamy buttery pecan ice cream with lighty roasted amd salted pecans.
A creamy cheesecake based ice cream with swirls of strawberry ripple.
Smooth salted caramel ice cream brimming with rich sea salt fudge and salted cashews.
Espresso ice cream with a caramel and fudge ripple, chocolate covered caramel cups and soft chocolate chunks.
Zanzibar ice cream swirled with mint ice cream.
Deep chocolate ice cream with swirls of marshmellow ice cream and whole broken almonds.
A fun fruity flavor with Superman red, yellow, and blue colors.
Oreo crumb base ice cream with lots of real Oreos.
All-natural chocolate ice cream made with three kinds of cocoa for a rich, frudge brownie taste!
Zanzibar ice cream with a marshmellow ripple, Oreos, and soft chocolate chips.
Soft cookie dough, crunchy chocolate covered pretzels, and a gooey salted caramel ripple all swirled into our rich chocolate ice cream.
Our sweet cherry based ice cream loaded with whole black cherries.
Fresh ice cream with natural green tea flavorings.


Below is the information from the current user's ID Token which was obtained during the Implicit Flow and is now stored in local storage.


A line chart with two series comparing GDP for two countries. This is a relatively advanced example that includes a mix of line styles to represent historical versus projected, unique point marks highlighting certain years, support for zoom and pan, and data changes with transitions.


|
Morgenlichtctl
A simple command-line client for morgenlichtd, written in C.
|
This file provides helpers for common protocol functionality and basic queries. More...
Go to the source code of this file.
Enumerations | |
| enum | AlarmCmd { AlarmEnable, AlarmDisable, AlarmDelete } |
| Basic alarm commands. | |
Functions | |
| int | parse_response (char *status, char **payload) |
| Read and parse a response from the server. More... | |
| int | server_info (const char *const hostname, const int port) |
| Print out some basic info about a morgenlichtd server. More... | |
| int | alarm_basic_cmd (const char *const hostname, const int port, const char *const profile, enum AlarmCmd cmd) |
| Perform the most basic alarm commands. More... | |
| int | alarm_list (const char *const hostname, const int port) |
| List all alarms on the server. More... | |
| int | alarm_add (const char *const hostname, const int port, const char *const profile, const int hour, const int minute, const int second, const char *const active_days, const char *const color, const char *const sound) |
| Add a new alarm or update an existing one. More... | |
This file provides helpers for common protocol functionality and basic queries.
| int alarm_add | ( | const char *const | hostname, |
| const int | port, | ||
| const char *const | profile, | ||
| const int | hour, | ||
| const int | minute, | ||
| const int | second, | ||
| const char *const | active_days, | ||
| const char *const | color, | ||
| const char *const | sound | ||
| ) |
Add a new alarm or update an existing one.
| hostname | The hostname of the server |
| port | The port of the server |
| profile | The alarm profile to create or overwrite |
| hour | The trigger hour |
| minute | The trigger minute |
| second | The trigger second |
| active_days | The days on which the profile is active |
| color | The color profile |
| sound | The sound file |
References init_networking(), network_write(), parse_response(), and term_networking().
| int alarm_basic_cmd | ( | const char *const | hostname, |
| const int | port, | ||
| const char *const | profile, | ||
| enum AlarmCmd | cmd | ||
| ) |
Perform the most basic alarm commands.
These only require the profile name as argument and return success or failure, which makes them specially simple to implement.
| hostname | The hostname of the server |
| port | The port of the server |
| profile | The alarm profile to act upon |
| cmd | The command to execute |
References init_networking().
| int alarm_list | ( | const char *const | hostname, |
| const int | port | ||
| ) |
List all alarms on the server.
| hostname | The hostname of the server |
| port | The port of the server |
Print the alarm
References init_networking(), network_write(), and parse_response().
| int parse_response | ( | char * | status, |
| char ** | payload | ||
| ) |
Read and parse a response from the server.
This will print out the warning if the server sent one, parse the status code and payload, write the status code to the given char, and allocate memory for the payload.
| status | Address of a char to which to write the status code. |
| payload | Pointer to a char pointer that will point to the payload. |
References network_read_char(), and term_networking().
Referenced by alarm_add(), alarm_list(), and server_info().
| int server_info | ( | const char *const | hostname, |
| const int | port | ||
| ) |
Print out some basic info about a morgenlichtd server.
| hostname | The hostname of the server |
| port | The port of the server |
References init_networking(), network_write(), parse_response(), and term_networking().


Hello there! My name is Rasel Mia and I'm a front-end + back-end developer & oop programmer.
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class: center, middle, inverse, title-slide # SturcturedPopulations ## Adding demography to population models ### Christopher Moore ### Week 03 --- # An outline of structured population models -- * Age-structured populations * A diversion on matrix math * Stage-structured populations * Sensitivity and elasticity --- background-image: url(https://i.imgflip.com/25i7oj.jpg) class: inverse --- # Age- structured populations -- 1. We have thus far examined how populations have changed assuming **the population is entirely homogeneous** -- 2. For many reasons, we might wish to more precisely model and analyze populations with respect to their age structure. That is, looking at the probabilities of survival and fecundity at each age. -- * For simplifaction, we are working with discrete-time, discrete-age models --- # The simplest case: two age classes * Imagine a species that lives for two years; e.g., a biennial plant. The seeds germinate at the beginning of the first year (age 0), and they leaf out and photosynthesize. During the second year (age 1), the plant flowers, sets seed, and dies. -- * Verbally, the model that I just described could be more concisely written as: `$$\begin{align}\text{zero-year-old plants = (# one-year-old plants)*fecundity} \\ \text{second-year plants = zero-year-old plants that survived} \end{align}$$` -- * Let's play with some simple numbers: * Let's say that the average one-year-old plants `\((x_1)\)` produces 25 seeds `\((f = 25)\)` that germinate the following year * Let's say that, on average, about 20% of zero-year-old plants `\((x_0)\)` survive `\((p_{\text{survive from age class 0 to 1}})\)` to the second year `\((x_1)\)` * Lastly, if we initially had 5 and 2 individuals respectively of `\(x_0\)` and `\(x_1\)` -- * Calculate, by hand, how many individuals would exist at each age after 5 years --- # The simplest case: two age classes ## Results .pull-left[ t | `\(x_0\)` | `\(x_1\)` | --|:-:|:-:| 0 | 5 | 2 1 | 50 | 1 2 | 25 | 10 3 | 250 | 5 4 | 125 | 50 5 | 1250 | 25 ] -- .pull-right[  ] --- # The simplest case: two age classes ## Results, with each age class .pull-left[ t | `\(x_0\)` | `\(x_1\)` | --|:-:|:-:| 0 | 5 | 2 1 | 50 | 1 2 | 25 | 10 3 | 250 | 5 4 | 125 | 50 5 | 1250 | 25 ] .pull-right[  ] --- # The condensed way: matrix operations From a few slides back: * Verbally, the model that I just described could be more concisely written as: `$$\begin{align}\text{zero-year-old plants = (# one-year-old plants)*fecundity} \\ \text{second-year plants = zero-year-old plants that survived} \end{align}$$` -- As a pair of equations, we can write `$$\begin{align} x_0(t+1) &= 25x_1(t) \\ x_1(t+1) &= 0.2x_0(t) \end{align}$$` -- which is the same as `$$\begin{align} x_0(t+1) &= 0x_0(t) + 25x_1(t) \\ x_1(t+1) &= 0.2x_0(t) + 0x_1(t) \end{align}$$` --- # The condensed way: matrix operations `$$\begin{align} x_0(t+1) &= 0x_0(t) + 25x_1(t) \\ x_1(t+1) &= 0.2x_0(t) + 0x_1(t) \end{align}$$` -- Can be represented as `$$\begin{bmatrix} x_0(t+1) \\ x_1(t+1) \end{bmatrix}$$` --- # The condensed way: matrix operations `$$\begin{align} x_0(t+1) &= 0x_0(t) + 25x_1(t) \\ x_1(t+1) &= 0.2x_0(t) + 0x_1(t) \end{align}$$` Can be represented as `$$\begin{gather}\begin{bmatrix} x_0(t+1) \\ x_1(t+1) \end{bmatrix} = \begin{bmatrix} 0 & 25 \\ 0.2 & 0 \end{bmatrix}\end{gather}$$` --- # The condensed way: matrix operations `$$\begin{align} x_0(t+1) &= 0x_0(t) + 25x_1(t) \\ x_1(t+1) &= 0.2x_0(t) + 0x_1(t) \end{align}$$` Can be represented as `$$\begin{gather}\begin{bmatrix} x_0(t+1) \\ x_1(t+1) \end{bmatrix} = \begin{bmatrix} 0 & 25 \\ 0.2 & 0 \end{bmatrix}\begin{bmatrix} x_0(t) \\ x_1(t) \end{bmatrix}\end{gather}$$` -- Symbolically, this is (what would be) equation (1c) in V&G: `$$\begin{gather}\begin{bmatrix} x_0(t+1) \\ x_1(t+1) \end{bmatrix} = \begin{bmatrix} 0 & f_1 \\ p_{10} & 0 \end{bmatrix}\begin{bmatrix} x_0(t) \\ x_1(t) \end{bmatrix}\end{gather}$$` --- # Structured populations models ## With 3 age classes `$$\begin{gather}\begin{bmatrix} x_0(t+1) \\ x_1(t+1) \\ x_2(t+1) \end{bmatrix} = \begin{bmatrix} 0 & f_1 & f_2 \\ p_{10} & 0 & 0 \\ 0 & p_{21} & 0 \end{bmatrix}\begin{bmatrix} x_0(t) \\ x_1(t) \\ x_2(t) \end{bmatrix}\end{gather}$$` --- # Structured populations models ## With 4 age classes `$$\begin{gather}\begin{bmatrix} x_0(t+1) \\ x_1(t+1) \\ x_2(t+1) \\ x_3(t+1) \end{bmatrix} = \begin{bmatrix} 0 & f_1 & f_2 & f_3 \\ p_{10} & 0 & 0 & 0 \\ 0 & p_{21} & 0 & 0 \\ 0 & 0 & p_{32} & 0 \end{bmatrix}\begin{bmatrix} x_0(t) \\ x_1(t) \\ x_2(t) \\ x_3(t) \end{bmatrix}\end{gather}$$` --- # Structured populations models ## With arbitrary `\((n)\)` numers of age classes `$$\begin{gather}\begin{bmatrix} x_0(t+1) \\ x_1(t+1) \\ x_2(t+1) \\ x_3(t+1) \\ \vdots \\ x_n(t+1) \end{bmatrix} = \begin{bmatrix} 0 & f_1 & f_2 & f_3 & \dots & f_{m-1} \\ p_{10} & 0 & 0 & 0 & & 0 \\ 0 & p_{21} & 0 & 0 & & 0 \\ 0 & 0 & p_{32} & 0 & & 0 \\ \vdots & & & \ddots & & \vdots \\ 0 & \dots & & & p_{n, m-1} & 0 \end{bmatrix}\begin{bmatrix} x_0(t) \\ x_1(t) \\ x_2(t) \\ x_3(t) \\ \vdots \\ x_n(t) \end{bmatrix}\end{gather}$$` --- # Some matrix math: notation Annotation in **bold** signifies that we are working with matrices. -- For instance, the first, 2-age-class model `$$\begin{gather}\begin{bmatrix} x_0(t+1) \\ x_1(t+1) \end{bmatrix} = \begin{bmatrix} 0 & f_1 \\ p_{10} & 0 \end{bmatrix}\begin{bmatrix} x_0(t) \\ x_2(t) \end{bmatrix}\end{gather}$$` can be written more concisely as `$$\mathbf{X(t+1) = PX(t)}$$` --- # Some matrix math: multiplication It's important to note that a vector is a matrix with one column; e.g., as the depicted `\(\mathbf{x}\)` above. -- Second, let's multiply a matrix times a vector by hand. Let's say you have a matrix that looks like this: `$$\begin{gather} ? = \begin{bmatrix} 0 & 4 & 8 \\ 0.1 & 0 & 0 \\ 0 & 0.9 & 0 \end{bmatrix}\begin{bmatrix} 6 \\ 4 \\ 2 \end{bmatrix}\end{gather}$$` (Think about how you did this in the biennial-plant problem.) -- `$$\begin{gather}\begin{bmatrix} 6(0) + 4(4) + 2(8) \\ 6(0.1) + 4(0) + 2(0) \\ 6(0) + 4(0.9) + 2(0) \end{bmatrix} = \begin{bmatrix} 0 & 4 & 8 \\ 0.1 & 0 & 0 \\ 0 & 0.9 & 0 \end{bmatrix}\begin{bmatrix} 6 \\ 4 \\ 2 \end{bmatrix}\end{gather}$$` --- # Some matrix math: multiplication It's important to note that a vector is a matrix with one column; e.g., as the depicted `\(\mathbf{x}\)` above. Second, let's multiply a matrix times a vector by hand. Let's say you have a matrix that looks like this: `$$\begin{gather} ? = \begin{bmatrix} 0 & 4 & 8 \\ 0.1 & 0 & 0 \\ 0 & 0.9 & 0 \end{bmatrix}\begin{bmatrix} 6 \\ 4 \\ 2 \end{bmatrix}\end{gather}$$` (Think about how you did this in the biennial-plant problem.) `$$\begin{gather}\begin{bmatrix} 32 \\ 0.6 \\ 3.6 \end{bmatrix} = \begin{bmatrix} 6(0) + 4(4) + 2(8) \\ 6(0.1) + 4(0) + 2(0) \\ 6(0) + 4(0.9) + 2(0) \end{bmatrix} = \begin{bmatrix} 0 & 4 & 8 \\ 0.1 & 0 & 0 \\ 0 & 0.9 & 0 \end{bmatrix}\begin{bmatrix} 6 \\ 4 \\ 2 \end{bmatrix}\end{gather}$$` --- # Some matrix math: using R 😌 :relieved: First, build the projection matrix and population vector `$$\begin{gather} ? = \begin{bmatrix} 0 & 4 & 8 \\ 0.1 & 0 & 0 \\ 0 & 0.9 & 0 \end{bmatrix}\begin{bmatrix} 6 \\ 4 \\ 2 \end{bmatrix}\end{gather}$$` -- ```r proj.mat <- matrix(data = c(0, 0.1, 0, 4, 0, 0.9, 8, 0, 0), nrow = 3, ncol = 3) proj.mat ## [,1] [,2] [,3] ## [1,] 0.0 4.0 8 ## [2,] 0.1 0.0 0 ## [3,] 0.0 0.9 0 N.vec <- matrix(data = c(6, 4, 2), nrow = 3, ncol = 1) N.vec ## [,1] ## [1,] 6 ## [2,] 4 ## [3,] 2 ``` --- # Some matrix math: using R ```r proj.mat*N.vec ## Error in proj.mat * N.vec: non-conformable arrays ``` -- ```r proj.mat%*%N.vec ## [,1] ## [1,] 32.0 ## [2,] 0.6 ## [3,] 3.6 ``` This is matrix multiplication (AKA, the inner product)! -- Also, it's important to note that matrix multiplication is non-commutative ```r N.vec%*%proj.mat ## Error in N.vec %*% proj.mat: non-conformable arguments ``` --- # Projecting matrix models ## Write a for loop for the matrix you just created -- ```r steps <- 7 N.mat <- matrix(data = NA, ncol = steps, nrow = length(N.vec)) N.mat[,1] <- N.vec for (i in 2:steps){ N.mat[,i] <- proj.mat%*%N.mat[,i-1] } ``` -- To sum across columns, use the `apply()` function ```r sumN <- apply(X = N.mat, MARGIN = 2, FUN = sum) sumN ## [1] 12.0000 36.2000 34.9400 23.1200 40.0400 34.4048 32.6624 ``` (The MARGIN = 2 means apply the function over the columns; to apply a funciton over rows use MARGIN = 1) --- # Visualizing a structured model ```r plot(x = 1:steps, y = sumN, type = "l", xlab = "Time step", ylab = "Density", las = 1) points(x = 1:steps, y = sumN, pch = 16, cex = 1.25) ``` ![](Wk03_StrPops_files/figure-html/unnamed-chunk-10-1.png) --- # Visualizing a structured model ```r plot(x = 1:steps, y = sumN, type = "l", xlab = "Time step", ylab = "Density", las = 1) points(x = 1:steps, y = sumN, pch = 16, cex = 1.25); segments(x0 = 1, x1 = 11, y0 = 50, y1 = 50, lwd = 1.5, lty = 2); text(x = 6, y = 53, labels = "Transience"); segments(x0 = 12.5, x1 = 20, y0 = 40, y1 = 59, lwd = 1.5); text(x = 17.5, y = 40, labels = "Stable(-ish)\nage\ndistribution") ``` ![](Wk03_StrPops_files/figure-html/unnamed-chunk-12-1.png) --- # Visualizing a structured model (each age class) .pull-left[ Same figure from previous slide, with the total population size ![](Wk03_StrPops_files/figure-html/unnamed-chunk-14-1.png) ] -- .pull-right[ Each age class as different colors; grey as the total population) ![](Wk03_StrPops_files/figure-html/unnamed-chunk-15-1.png) ] --- # Visualizing a structured model (each age class) ![](Wk03_StrPops_files/figure-html/unnamed-chunk-17-1.png) --- # Visualizing a structured model (many time steps) ```r plot(x = 1:steps, y = sumN, type = "l", xlab = "Time step", ylab = "Density", las = 1) points(x = 1:steps, y = sumN, pch = 16, cex = 1.25) ``` ![](Wk03_StrPops_files/figure-html/unnamed-chunk-19-1.png) --- # Can we relate stable-age distribution growth with a constant value `\((\lambda)\)`? -- Yes!!! -- .pull-left[ Structured-population growth at a stable-age distribution `$$\begin{align} \mathbf{N}_{t+1} &= \lambda \mathbf{N}_t \\ \mathbf{N}_{t+2} &= \lambda \mathbf{N}_{t+1} = \lambda \lambda \mathbf{N}_t = \lambda ^2\mathbf{N}_t \\ \dots \\ \mathbf{N}_{t+n} &= \lambda ^n\mathbf{N}_t \end{align}$$` ] -- .pull-right[ General structured-population growth `$$\begin{align} \mathbf{N}_{t+1} &= \mathbf{P}\mathbf{N}_t \\ \mathbf{N}_{t+2} &= \mathbf{P}\mathbf{N}_{t+1} = \mathbf{P}\mathbf{P}\mathbf{N}_t = \mathbf{P}^2N_t \\ \dots \\ \mathbf{N}_{t+n} &= \mathbf{P}^n\mathbf{N}_t \end{align}$$` ] -- *Et vualá*: `\(\mathbf{P}^n\mathbf{N}_t = \lambda ^n\mathbf{N}_t\)` --- # A characteristic of matrices: die eigenvalue -- It turns out if we have a projection matrix, *we can solve for the finite rate of increase `\((\lambda)\)`*! -- We just need to solve for `\((\lambda)\)` from the pervious slide, `\(\mathbf{P}^n\mathbf{N}_t = \lambda ^n\mathbf{N}_t\)` -- To do so, we need to conform both sides to one another (LHS is a matrix, RHS is a scalar) (eqn. 10), then solve for `\((\lambda)\)` (equation 10 until the end of the section) -- Read the derivation in the book and know that the dominant eigenvalue (the largest absoute value) is equal to the finite rate of increase. Knowing that relation is important, but for finding it we should let R do it for us. In R, the eigenvalues can be found of a matrix by using the function `eigen()`. Do this over the matrix we've been looking at: `$$\begin{gather} ? = \begin{bmatrix} 0 & 4 & 8 \\ 0.1 & 0 & 0 \\ 0 & 0.9 & 0 \end{bmatrix}\begin{bmatrix} 6 \\ 4 \\ 2 \end{bmatrix}\end{gather}$$` -- An interactive webpage to help usederstand eigenvalues, in general: [http://setosa.io/ev/eigenvectors-and-eigenvalues/](http://setosa.io/ev/eigenvectors-and-eigenvalues/) --- class: inverse, middle, center # Hopefully you feel confident about these age structured models (now)! ![](https://media.giphy.com/media/KBCxijnlSs9jy/giphy.gif) --- class: inverse, center, middle # Stage structured models --- # Stage structured models So far we have learned about age-structured models, where, with the exception to those organisms that transcend time, indiviudals must move from one age class to another. BUT, we can also model populations that are also structured demographically by *stage*. This allows us to reduce the number of effective classes (e.g., if survival and fecundity of a 44- and 45-year-old human is the same, then the classes are redundant) to more easily analyze the population dynamics. -- As an example, imagine a population of holometabolan (complete metamorphosis) insects, say a dung beetle, with 4 age classes: egg, larva, pupa, adult. The adults can live many years, but the other three stages advance each year. --- # Stage structured models: sea turtles ![sea turtle data](Wk03_StrPops_files/SeaTurtleTitle.png) --- # Stage structured models: sea turtles ![sea turtle data](Wk03_StrPops_files/SeaTurtleData.png) -- ![sea turtle data](Wk03_StrPops_files/SeaTurtleMatrix.png)


Question no.1
Create a for loop that iterates upto 100 while outputing "fizz" at multiple of 3,"Buzz" at multiple of 5 and "fizzbuzz" as multiple of 3 and 5.
Question no.2
Destructure the following object.
Question no.3
Create a new array called Shopping Basket,that will be a copy of ShoppingList array,and add some new product in it.
Question no.4
Make a calculator in javascripts which can do operation as Addition,Substaction,Multiplication,Division,Square root,Percentage.
Question no.5
Log the total commission earned by employee as given in question's table
Question no.6
Rewrite the function using '?' or '||'
Write a loops which prompt for a number greater than 100.If the visitor enters another no ask them to enter again.
The loops must ask for a no until either the visitor enter a no greater than 100 or cancle the input/enter empty line
Question no.7
Write a code which outputs prime numbers in the interval from 2 to n.
Question no.8
Replace function expressions with the arrow function in the code given in question.


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from urldecorators.defaults import * urlpatterns = patterns('', url(r'^private/$', include('testproject.private.urls'), decorators=['django.contrib.auth.decorators.login_required']), ... )