A Lens Library for Javascript
Installation is easy:
$ npm install nanoscope
What is a Lens?
A Lens
is a construct that allow you to peer into data structures and modify their contents. At base level, a Lens
consists of a getter and a mapping function over a specific sub-part of your data. Lens
es allow you to modify data
in interesting ways with minimal code, and nanoscope
contains many useful Lens
es that you can plug into your existing
code and use right out of the box, that provide things like:
- Safe traversal of deeply nested data structures
- Easy access and modification of single array elements
- Access and modification of complete array slices, including modifications of size
- A wrapper for safe access and modification of data through any
Lens
The Lens
Interface
Lens
es support the following operations:
get
, which gets the value at the focus of theLens
set
, which sets the value at the focus of theLens
map
, which maps a function over the focus of theLens
view
, which sets the view of theLens
to a new valuecompose
, which composes theLens
with another lens, allowing sequencing of actions.add
, which adds anotherLens
focus to the lens, allowing multiple focal points.
Assuming headLens
is a Lens
that focuses on the first element of an array, they can be used like this:
headLens.get([1, 2, 3]); // => 1
// or
headLens.view([1, 2, 3]).get(); // => 1
headLens.set([1, 2, 3], 99); // => [99, 2, 3]
// or
headLens.view([1, 2, 3]).set(99); // => [99, 2, 3]
headLens.map([1, 2, 3], function (elem) { return elem * 10; }); // => [10, 2, 3]
// or
headLens.view([1, 2, 3]).map(function (elem) { return elem * 10; }); // => [10, 2, 3]
headLens.compose(headLens).view([['what'], 2, 3]).get(); // => 'what'
// Assume lastLens focuses on the last element
headLens.compose(lastLens).view([1, 2, 3]).get(); // => [1, 3]
Of particular interest is compose
, which allows us to compose a headLens
with a headLens
to focus on an array's first
element of it's first element, and add
, which allows us to focus on both the first and last elements of the array
in parallel.
IndexedLens
IndexedLenses
focus on a single element of an array, specified by its index. headLens
as shown above can be built using an
IndexedLens
like so:
var headLens = new nanoscope.IndexedLens(0);
This means that we are focusing on the 0
-th element of an array. IndexedLenses
are safe by default, which means
that they will not throw errors when you try to access elements out of range. For example, headLens.view([]).get()
will not throw an error. To make an unsafe IndexedLens
, just use the Unsafe
constructor:
var unsafeHeadLens = new nanoscope.IndexedLens.Unsafe(0);
In an unsafe IndexedLens
, the following operations will throw an error:
get()
, if the index is greater than or equal to the length of the array, andset()
, if the index is strictly greater than the length of the array (you may tack on items to the end of an array)
SliceLens
SliceLenses
focus on a subarray within an array. They can be constructed in two ways:
- By specifying
start
(inclusive) andend
(exclusive) indices in the constructor, like so:
var firstTwo = new nanoscope.SliceLens(0, 2);
- By specifying a python-style slice as a string as a single argument:
var firstTwo = new nanoscope.SliceLens('0:2');
By using the second syntax, you can use any of the python type variants using :
. For example:
// a `Lens` that focuses on everything but the first element
var tailLens = new nanoscope.SliceLens('1:');
// a `Lens` that focuses on everything but the last element
var initLens = new nanoscope.SliceLens(':-1');
Negative indices are accepted, which count backwards from the end of the list.
SliceLenses
can be used not only to modify the elements in each slice, but it can also modify the length of the slice.
For example:
initLens.view([1, 2, 3, 4]).map(
function (arr) {
return _.map(
arr,
function (elem) {
return elem * 2;
}
)
});
// => [1, 4, 6, 4]
// Assume `sum` sums the elements in a list
initLens.view([1, 2, 3, 4]).map(sum);
// => [6, 4]
PathLens
PathLenses
are used to access nested data inside dynamic objects. They are constructed by passing a string representation
of the path followed to get to the element to focus on, separated by .
. They are safe by default; this is best illustrated
by an example.
var testObject = {
a : {
b: {
c : 100
}
}
};
new nanoscope.PathLens('a.b.c').view(testObject).get();
// => 100
new nanoscope.PathLens('a.b.c.d.e.f').view(testObject).get();
// => null
new nanoscope.PathLens('a.b.c').view(testObject).set('foo');
// => testObject.a.b.c == 'foo'
new nanoscope.PathLens('a.b.c.d.e.f').view(testObject).set('foo');
// => testObject.a.b.c.d.e.f == 'foo'
Note that in the last call we're overwriting testObject.a.b.c
; this is by design, but something to be aware of.
If you prefer that your PathLens
throw errors when keys in the path don't exist, you can use the PathLens.Unsafe
constructor instead; these are constructed in the same way:
new nanoscope.PathLens.Unsafe('a.b.c.d.e.f').view(testObject).get();
// => TypeError: Cannot read property 'e' of undefined
One other thing to note is that when using over
in any PathLens
, if:
- You are accessing a field that didn't originally exist, and
- Your function returns
undefined
ornull
,
your structure will be unmodified. This prevents things like:
new nanoscope.PathLens('a.b.c.e.f.g').view({}).over(function (elem) { return elem * 2; });
... from producing this:
{ a: { b: { c: { d: { e: { f: { g: undefined } } } } } } }
Instead, it will not modify the object and, in this case, simply return {}
.
Optional
Optional
Lenses
wrap any Lens
in a function that catches any errors that may happen along the way. They are
constructed with the Optional
constructor, which takes any Lens
as an argument, along with an optional errorHandler
function, This function will be called on any errors that may occur during the execution of any Lens
operations,
and if omitted, these errors will cause get
to silently return null
, and set
/map
to silently
return the object passed in. errorHandler
may also be a default value that you would prefer
to return upon any errors.
For example, we can take an Unsafe IndexedLens
and wrap it in Optional
in order to handle incoming errors as they
are thrown:
var Optional = nanoscope.Optional,
IndexedLens = nanoscope.IndexedLens,
lens;
lens = new Optional( new IndexedLens.Unsafe(10) );
lens.view([]).get(); // => null
lens.view([]).set(0); // => []
lens = new Optional( new IndexedLens.Unsafe(10), 'FAIL!' );
lens.view([]).get(); // => 'FAIL!'
lens.view([]).set(0); // => 'FAIL!'
lens = new Optional( new IndexedLens.Unsafe(10), console.log);
lens.view([]).get(); // => logs 'Error: Array index 10 out of range', returns undefined
lens.view([]).set(0); // => logs 'Error: Array index 10 out of range', returns undefined
One major thing to note is that Optional Lenses
do not catch errors from calls to unimplemented functions in
Getters
and Setters
. That is, calling setter.get
and getter.set
will still fail. This is by design, as these types
of errors are logical in nature and should be caught by the programmer in all cases.
Compose
Compose
is a wrapper (like Optional
) that takes two Lenses
and returns a new Lens
that first focuses on the
focus of the first Lens
, and then on the second, in sequence. The compose()
method constructs a Compose
Lens
under
the hood, so the behavior is exactly the same. For a short example, consider an object with an array for one of the keys:
var obj = {
a: {
anArray: [99, 2, 3, 4]
}
}
And say that we want a Lens
that focuses on the second object in anArray
. We can easily accomplish this with
composite lenses:
var lensA = new nanoscope.PathLens('a.anArray'),
lensB = new nanoscope.IndexedLens(1),
composite = new nanoscope.Compose(lensA, lensB)
// or composite = lensA.compose(lensB);
composite.view(obj).get(); // => 2
composite.view(obj).set(1); // => { a: { anArray: [99, 1, 3, 4] } }
composite
first looks at the focus of lensA
, then at the focus of lensB
starting at the focus of lensA
and uses
this as its own focus.
MultiLens
MultiLenses
allow you to focus on many different things at once and return them all at once. MultiLens
is a sort of
concurrent version of Compose
. It takes either an Array of Lenses
or an object with Lenses
as values, and produces
a Lens
whose focus is all of the focuses in this argument. If the argument is an object, get
will name each of the outputs
in an object; if not, it will return an array of unnamed results. set
and map
will set every focus of the lens.
MultiLenses
can also be constructed using the add
method in any Lens
, just like compose
above.
Here is a simple example of a MultiLens
in action:
var arrayLenses = [
new nanoscope.IndexedLens(0),
new nanoscope.IndexedLens(1)
],
objectLenses = {
head: new nanoscope.IndexedLens(0),
last: new nanoscope.IndexedLens(-1)
},
// A MultiLens built from an Array
arrayMultiLens = new nanoscope.MultiLens(arrayLenses),
// or arrayMultiLens = new nanoscope.IndexedLens(0).add(new nanoscope.IndexedLens(1));
// A MultiLens built from an Object
objectMultiLens = new nanoscope.MultiLens(objectLenses);
arrayMultiLens.view([1, 2]).get(); // => [1, 2]
arrayMultiLens.view([1, 2]).set('g'); // => ['g', 'g']
objectMultiLens.view([1, 2, 3]).get(); // => { head: 1, last: 3 }
objectMultiLens.view([1, 2, 3]).set('g'); // => ['g', 2, 'g']
Getters and Setters
Getters
are Lenses
that only support get()
, and Setters
are Lenses
that only support over
and set
.
Getters
and Setters
are constructed with get
functions and over
functions only, respectively. They can also be
constructed by using the fromLens
static function in Getter
and Setter
, which simply replaces the old over
/get
operations in the original Lens
. Constructing your own Lenses
, Getters
and Setters
is described below, but here is
an example of how fromLens
works:
var Getter = nanoscope.Getter,
Setter = nanoscope.Setter,
IndexedLens = nanoscope.IndexedLens;
Getter.fromLens(new IndexedLens(0)).view([1]).get(); // => 1
Getter.fromLens(new IndexedLens(0)).view([1]).set(10); // => Error: map not permitted in a Getter
Setter.fromLens(new IndexedLens(0)).view([1]).set(10); // => [10]
Setter.fromLens(new IndexedLens(0)).view([1]).get(); // => Error: get not permitted in a Setter
These are useful when you want to restrict access to certain parts of your structures, but still use any Lenses
to access data in one or more ways.
Making your own Lens
es
Consider a Lens
that views an array and focuses on its first element.
The get
function for this Lens
might look like this:
var get = function (arr) {
return arr[0];
};
...and map
might be defined like so:
var map = function (arr, func) {
var newArr = _.cloneDeep(arr);
newArr[0] = func(newArr[0]);
return newArr;
};
There are a couple of things to note here:
- We use
_.cloneDeep
fromlodash
(orunderscore
) to clone the object, becauseLens
es should provide immutable access to data. func
is a function that operates on the focus of theLens
, which in this case isarr[0]
.- We return the full, modified structure at the end.
We can construct a Lens
from these bindings like so:
var nanoscope = require('nanoscope'),
headLens = new nanoscope.Lens(get, map);
All valid Lens
es must also satisfy the so-called "Lens Laws":
- set-get (you get what you put in):
lens.get(lens.set(a, b)) = b
- get-set (putting what is there doesn't change anything):
lens.set(a, lens.get(a)) = a
- set-set (setting twice is the same as setting once):
lens.set(c, lens.set(b, a)) = lens.set(c, a)
These laws ensure that map
, set
and get
behave in the manner you'd expect. If you can convince yourself
that these laws are satisfied, you can rest easy knowing your Lens
is well-behaved.


19:00- Pre-conference social event @ Bruuveri (map)
8:30 Registration Opens
9:00 - 9:30 Welcome and quick introduction of all talks
9:30 - 10:00 Lightning talks
10:00 - 10:30 Coffee / mingling
10:30 - 11:30 [Track 1] FP in Python: it's simpler than you thought [Track 2] Modern day serialization in Python
11:30 - 12:30 [Track 1] Representation Learning and Deep Sequential Modeling for Predicting Topics of Sentences in Job Advertisements [Track 2] Data scraping for beginners (25 min) [Track 2] Visualizing twitter discussions with networkx (25 min)
12:30 - 13:30 Lunch (om nom)
13:30 - 14:30 [Track 1] Attack of Pythons : Gotchas and Landmines in Python [Track 2] Testing webapps without ids or xpaths (25 min) [Track 2] ZODB – the Python database (25 min)
14:30 - 15:30 [Track 1] Unit testing in the Scientific Python stack [Track 2] Closing the gap with TLS adoption
15:30 - 16:00 Coffee / mingling
16:00 - 17:00 Machine Learning with Python - from Model to Web-Service
17:00 - 17:30 Wrap-up and final words
18:00 - 21:00 (approximately) Dinner at Huone (map)
21:00 (approximately) - late After-party and sauna at a to-be-disclosed location


| Trees | Indices | Toggle frames |
|---|
Display positioned, scaled and rotated images.
A sprite is an instance of an image displayed on-screen. Multiple sprites can display the same image at different positions on the screen. Sprites can also be scaled larger or smaller, rotated at any angle and drawn at a fractional opacity.
The following complete example loads a "ball.png" image and creates a sprite for that image. The sprite is then drawn in the window's draw event handler:
import pyglet ball_image = pyglet.image.load('ball.png') ball = pyglet.sprite.Sprite(ball_image, x=50, y=50) window = pyglet.window.Window() @window.event def on_draw(): ball.draw() pyglet.app.run()
The sprite can be moved by modifying the x and y properties. Other properties determine the sprite's rotation, scale and opacity.
The sprite's positioning, rotation and scaling all honor the original image's anchor (anchor_x, anchor_y).
Sprites can be "batched" together and drawn at once more quickly than if each of their draw methods were called individually. The following example creates one hundred ball sprites and adds each of them to a Batch. The entire batch of sprites is then drawn in one call:
batch = pyglet.graphics.Batch() ball_sprites = [] for i in range(100): x, y = i * 10, 50 ball_sprites.append(pyglet.sprite.Sprite(ball_image, x, y, batch=batch) @window.event def on_draw(): batch.draw()
Sprites can be freely modified in any way even after being added to a batch, however a sprite can belong to at most one batch. See the documentation for pyglet.graphics for more details on batched rendering, and grouping of sprites within batches.
Since: pyglet 1.1
|
SpriteGroup
Shared sprite rendering group.
|
|
|
Sprite
Instance of an on-screen image.
|
| Trees | Indices | Toggle frames |
|---|
| Generated by Epydoc 3.0beta1 on Sun Mar 22 20:15:38 2009 | http://epydoc.sourceforge.net |


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SOLDIER Review by Victory A. Marasigan http://www.gl.umbc.edu/~vmaras1/reviewsidx.html
_Soldier_ is hands down one of the worst movies a person could ever have to sit through that doesn't have Jean Claude Van Damme in it. I could liken it to the sci-fi cheese that was the Hollywood product-of-choice back in the early 80s, but that would be too much of a compliment. If there is a movie theater in hell, this film is playing there 24 hours a day.
The story, such that there is, revolves around Todd (Kurt Russell), an automaton of a man who has been raised from birth to be a merciless soldier in a not-too-distant ultra-conservative future (is there any other kind?)  Who the enemies in these wars are is never revealed, but the few glimpses of Todd in battle show that it doesn't matter, because innocent hostages are wiped out as indifferently as the bad guys.
After ten minutes of this nihilistic trash -- yes folks, there's more -- we see Todd as a buff, scarred adult, now so accustomed to the carnage that no confrontation at all causes him to break a sweat. There's a new wrinkle, though. Todd and his brethren are declared obsolete, and a new batch of soldiers takes their place. After losing a sanctioned battle with _Dragon_'s Jason Scott Lee, the seemingly dead Todd is dumped by a flying ice-cube tray (well, that's what is looked like) on a remote garbage planet.

It's surprising that _Soldier_ is the brain-child of _Blade Runner_ co-writer David Webb Peoples. Unlike that mind-twisting classic, this film contains just barely enough dialogue to fill about three double-spaced pages. Add into the mix the _Mortal Kombat_'s Paul Anderson inept direction, and it's easy to see how _Soldier_ turned out so bad. And the special effects! Remember the flying steam irons in Hardware Wars?
Gary Busey is in this movie. 'Nuff said.
_Soldier_ is proof that Hollywood still has plenty of bad ideas sitting in its script vaults. That this sad film made it to the silver screen should encourage plenty of aspiring screenwriters out there that there is hope after all. Now if you'll excuse me, I have to go weep for the future.
GRADE: F
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rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
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Related links: index of all rec.arts.movies.reviews reviews


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Check out what you can do with this software!
Manage projects visually through an interactive timeline
Chat with your entire team. Send models, blueprints with ease.
Assign tasks to each team member, and follow their progress
Automates your work schedule with notifications


Package org.drip.spaces.functionclass
Class NormedRxToNormedRdFinite
java.lang.Object
org.drip.spaces.functionclass.NormedRxToNormedRxFinite
org.drip.spaces.functionclass.NormedRxToNormedRdFinite
- Direct Known Subclasses:
HilbertRxToSupremumRdFinite
public class NormedRxToNormedRdFinite extends NormedRxToNormedRxFinite
NormedRxToNormedRdFinite implements the Class F with f E f : Normed Rx To Normed
Rd Space of Finite Functions. The References are:
- Carl, B. (1985): Inequalities of the Bernstein-Jackson type and the Degree of Compactness of Operators in Banach Spaces Annals of the Fourier Institute 35 (3) 79-118
- Carl, B., and I. Stephani (1990): Entropy, Compactness, and the Approximation of Operators Cambridge University Press Cambridge UK
- Williamson, R. C., A. J. Smola, and B. Scholkopf (2000): Entropy Numbers of Linear Function Classes, in: Proceedings of the 13th Annual Conference on Computational Learning Theory ACM New York
- Module = Computational Core Module
- Library = Statistical Learning Library
- Project = R1 and Rd Vector/Tensor Spaces (Validated and/or Normed), and Function Classes
- Package = Normed Finite Spaces Function Class
- Author:
- Lakshmi Krishnamurthy
-
Constructor Summary
Constructors Constructor Description NormedRxToNormedRdFinite(double dblMaureyConstant, NormedRxToNormedRd[] aNormedRxToNormedRd)
NormedRxToNormedRdFinite Constructor -
Method Summary
Modifier and Type Method Description FunctionClassCoveringBounds
agnosticCoveringNumberBounds()
Retrieve the Agnostic Covering Number Upper/Lower Bounds for the Function ClassNormedRxToNormedRd[]
functionSpaces()
Retrieve the Array of Function Spaces in the ClassGeneralizedMetricVectorSpace
inputMetricVectorSpace()
Retrieve the Input Vector Spacedouble
operatorPopulationMetricNorm()
Compute the Operator Population Metric Normdouble
operatorPopulationSupremumNorm()
Compute the Operator Population Supremum Normdouble
operatorSampleMetricNorm(GeneralizedValidatedVector gvvi)
Compute the Operator Sample Metric Normdouble
operatorSampleSupremumNorm(GeneralizedValidatedVector gvvi)
Compute the Operator Sample Supremum NormRdNormed
outputMetricVectorSpace()
Retrieve the Output Vector Spacedouble[]
populationCoveringNumber(double dblCover)
Estimate for the Function Class Population Covering Number Array, one for each dimensiondouble[]
populationCoveringNumber(double[] adblCover)
Estimate for the Function Class Population Covering Number Array, one for each dimensiondouble[]
populationRdMetricNorm()
Compute the Population R^d Metric Normdouble[]
populationRdSupremumNorm()
Compute the Population R^d Supremum Normdouble[]
populationSupremumCoveringNumber(double dblCover)
Estimate for the Function Class Population Supremum Covering Number Array, one for each dimensiondouble[]
populationSupremumCoveringNumber(double[] adblCover)
Estimate for the Function Class Population Supremum Covering Number Array, one for each dimensiondouble[]
sampleCoveringNumber(GeneralizedValidatedVector gvvi, double dblCover)
Estimate for the Scale-Sensitive Sample Covering Number Array for the specified Cover Sizedouble[]
sampleCoveringNumber(GeneralizedValidatedVector gvvi, double[] adblCover)
Estimate for the Scale-Sensitive Sample Covering Number Array for the specified Cover Sizedouble[]
sampleRdMetricNorm(GeneralizedValidatedVector gvvi)
Compute the Sample R^d Metric Normdouble[]
sampleRdSupremumNorm(GeneralizedValidatedVector gvvi)
Compute the Sample R^d Supremum Normdouble[]
sampleSupremumCoveringNumber(GeneralizedValidatedVector gvvi, double dblCover)
Estimate for the Scale-Sensitive Sample Supremum Covering Number for the specified Cover Sizedouble[]
sampleSupremumCoveringNumber(GeneralizedValidatedVector gvvi, double[] adblCover)
Estimate for the Scale-Sensitive Sample Supremum Covering Number for the specified Cover SizeMethods inherited from class org.drip.spaces.functionclass.NormedRxToNormedRxFinite
maureyConstant, outputDimension, populationMetricCoveringBounds, populationSupremumCoveringBounds, sampleMetricCoveringBounds, sampleSupremumCoveringBounds, scaleSensitiveCoveringBounds
Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
-
Constructor Details
-
NormedRxToNormedRdFinite
public NormedRxToNormedRdFinite(double dblMaureyConstant, NormedRxToNormedRd[] aNormedRxToNormedRd) throws java.lang.ExceptionNormedRxToNormedRdFinite Constructor- Parameters:
dblMaureyConstant
- Maurey ConstantaNormedRxToNormedRd
- Array of the Normed R^x To Normed R^d Spaces- Throws:
java.lang.Exception
- Thrown if the Inputs are Invalid
-
-
Method Details
-
agnosticCoveringNumberBounds
Description copied from class:NormedRxToNormedRxFinite
Retrieve the Agnostic Covering Number Upper/Lower Bounds for the Function Class- Specified by:
agnosticCoveringNumberBounds
in classNormedRxToNormedRxFinite
- Returns:
- The Agnostic Covering Number Upper/Lower Bounds for the Function Class
-
inputMetricVectorSpace
Description copied from class:NormedRxToNormedRxFinite
Retrieve the Input Vector Space- Specified by:
inputMetricVectorSpace
in classNormedRxToNormedRxFinite
- Returns:
- The Input Vector Space
-
outputMetricVectorSpace
Description copied from class:NormedRxToNormedRxFinite
Retrieve the Output Vector Space- Specified by:
outputMetricVectorSpace
in classNormedRxToNormedRxFinite
- Returns:
- The Output Vector Space
-
functionSpaces
Retrieve the Array of Function Spaces in the Class- Returns:
- The Array of Function Spaces in the Class
-
populationCoveringNumber
public double[] populationCoveringNumber(double[] adblCover)Estimate for the Function Class Population Covering Number Array, one for each dimension- Parameters:
adblCover
- The Size of the Cover Array- Returns:
- Function Class Population Covering Number Estimate Array, one for each dimension
-
populationCoveringNumber
public double[] populationCoveringNumber(double dblCover)Estimate for the Function Class Population Covering Number Array, one for each dimension- Parameters:
dblCover
- The Cover- Returns:
- Function Class Population Covering Number Estimate Array, one for each dimension
-
populationSupremumCoveringNumber
public double[] populationSupremumCoveringNumber(double[] adblCover)Estimate for the Function Class Population Supremum Covering Number Array, one for each dimension- Parameters:
adblCover
- The Size of the Cover Array- Returns:
- Function Class Population Supremum Covering Number Estimate Array, one for each dimension
-
populationSupremumCoveringNumber
public double[] populationSupremumCoveringNumber(double dblCover)Estimate for the Function Class Population Supremum Covering Number Array, one for each dimension- Parameters:
dblCover
- The Cover- Returns:
- Function Class Population Covering Supremum Number Estimate Array, one for each dimension
-
sampleCoveringNumber
Estimate for the Scale-Sensitive Sample Covering Number Array for the specified Cover Size- Parameters:
gvvi
- The Validated Instance Vector SequenceadblCover
- The Size of the Cover Array- Returns:
- The Scale-Sensitive Sample Covering Number Array for the specified Cover Size
-
sampleCoveringNumber
Estimate for the Scale-Sensitive Sample Covering Number Array for the specified Cover Size- Parameters:
gvvi
- The Validated Instance Vector SequencedblCover
- The Size of the Cover Array- Returns:
- The Scale-Sensitive Sample Covering Number Array for the specified Cover Size
-
sampleSupremumCoveringNumber
Estimate for the Scale-Sensitive Sample Supremum Covering Number for the specified Cover Size- Parameters:
gvvi
- The Validated Instance Vector SequenceadblCover
- The Size of the Cover Array- Returns:
- The Scale-Sensitive Sample Supremum Covering Number for the specified Cover Size
-
sampleSupremumCoveringNumber
Estimate for the Scale-Sensitive Sample Supremum Covering Number for the specified Cover Size- Parameters:
gvvi
- The Validated Instance Vector SequencedblCover
- The Cover- Returns:
- The Scale-Sensitive Sample Supremum Covering Number for the specified Cover Size
-
populationRdMetricNorm
public double[] populationRdMetricNorm()Compute the Population R^d Metric Norm- Returns:
- The Population R^d Metric Norm
-
populationRdSupremumNorm
public double[] populationRdSupremumNorm()Compute the Population R^d Supremum Norm- Returns:
- The Population R^d Supremum Norm
-
sampleRdMetricNorm
Compute the Sample R^d Metric Norm- Parameters:
gvvi
- The Validated Vector Space Instance- Returns:
- The Sample R^d Metric Norm
-
sampleRdSupremumNorm
Compute the Sample R^d Supremum Norm- Parameters:
gvvi
- The Validated Vector Space Instance- Returns:
- The Sample R^d Supremum Norm
-
operatorPopulationMetricNorm
public double operatorPopulationMetricNorm() throws java.lang.ExceptionDescription copied from class:NormedRxToNormedRxFinite
Compute the Operator Population Metric Norm- Specified by:
operatorPopulationMetricNorm
in classNormedRxToNormedRxFinite
- Returns:
- The Operator Population Metric Norm
- Throws:
java.lang.Exception
- Thrown if the Operator Norm cannot be computed
-
operatorPopulationSupremumNorm
public double operatorPopulationSupremumNorm() throws java.lang.ExceptionDescription copied from class:NormedRxToNormedRxFinite
Compute the Operator Population Supremum Norm- Specified by:
operatorPopulationSupremumNorm
in classNormedRxToNormedRxFinite
- Returns:
- The Operator Population Supremum Norm
- Throws:
java.lang.Exception
- Thrown if the Operator Population Supremum Norm cannot be computed
-
operatorSampleMetricNorm
Description copied from class:NormedRxToNormedRxFinite
Compute the Operator Sample Metric Norm- Specified by:
operatorSampleMetricNorm
in classNormedRxToNormedRxFinite
- Parameters:
gvvi
- The Validated Vector Space Instance- Returns:
- The Operator Sample Metric Norm
- Throws:
java.lang.Exception
- Thrown if the Operator Norm cannot be computed
-
operatorSampleSupremumNorm
public double operatorSampleSupremumNorm(GeneralizedValidatedVector gvvi) throws java.lang.ExceptionDescription copied from class:NormedRxToNormedRxFinite
Compute the Operator Sample Supremum Norm- Specified by:
operatorSampleSupremumNorm
in classNormedRxToNormedRxFinite
- Parameters:
gvvi
- The Validated Vector Space Instance- Returns:
- The Operator Sample Supremum Norm
- Throws:
java.lang.Exception
- Thrown if the Operator Sample Supremum Norm cannot be computed
-


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- randomValue(XmlAction, int, int) - Method in class com.datamelt.rules.core.action.MathAction
-
- ReferenceField - Class in com.datamelt.rules.core
-
Defines a reference field as it is used and output by the BusinessRulesMaintenance Tool.
- ReferenceField() - Constructor for class com.datamelt.rules.core.ReferenceField
-
- reInit(String) - Method in class com.datamelt.util.VelocityDataWriter
-
re-initializes the datawriter with a new template. this is useful
to re-use an existing datawriter object
- reloadRuleFile(String) - Method in class com.datamelt.rules.engine.BusinessRulesEngine
-
reloads the rule xml file for a running BusinessRulesEngine instance
- reloadRuleFile(File[]) - Method in class com.datamelt.rules.engine.BusinessRulesEngine
-
reloads the rule xml file for a running BusinessRulesEngine instance
- reloadRuleFileFolder(String) - Method in class com.datamelt.rules.engine.BusinessRulesEngine
-
reloads all rule xml files from a folder for a running BusinessRulesEngine instance
- reloadZipFile(ZipFile) - Method in class com.datamelt.rules.engine.BusinessRulesEngine
-
reloads the rule project zip file for a running BusinessRulesEngine instance.
- remainderValue(XmlAction, long, long) - Method in class com.datamelt.rules.core.action.MathAction
-
- remainderValue(XmlAction, long, int) - Method in class com.datamelt.rules.core.action.MathAction
-
- remainderValue(XmlAction, int, int) - Method in class com.datamelt.rules.core.action.MathAction
-
- remove(int) - Method in class com.datamelt.rules.core.RuleMessageCollection
-
- remove(int) - Method in class com.datamelt.rules.core.RuleObjectCollection
-
remove the rule object from the collection
- remove(int) - Method in class com.datamelt.rules.core.util.XmlActionCollection
-
Remove an action from the collection
- removeActionGetterObject(int) - Method in class com.datamelt.rules.core.XmlAction
-
removes an object from the list of action objects
- removeField(String) - Method in class com.datamelt.util.RowFieldCollection
-
Remove a field from the array of fields.
- removeField(int) - Method in class com.datamelt.util.RowFieldCollection
-
Remove a field from the array of fields.
- removeFields() - Method in class com.datamelt.util.RowFieldCollection
-
Remove all fields from the array of fields.
- replaceValue(XmlAction, String, String, String) - Method in class com.datamelt.rules.core.action.StringAction
-
- replaceValueFromList(XmlAction, int, String) - Method in class com.datamelt.rules.core.action.StringAction
-
- replaceValueFromMap(XmlAction, String, String) - Method in class com.datamelt.rules.core.action.StringAction
-
- RESPONSE_EXIT - Static variable in class com.datamelt.server.ClientHandler
-
- RESPONSE_HELLO - Static variable in class com.datamelt.server.ClientHandler
-
- RESPONSE_NUMBER_OF_GROUPS - Static variable in class com.datamelt.server.ClientHandler
-
- RESPONSE_PROCESSID - Static variable in class com.datamelt.server.ClientHandler
-
- RESPONSE_RELOAD - Static variable in class com.datamelt.server.ClientHandler
-
- RESPONSE_ROWSPROCESSED - Static variable in class com.datamelt.server.ClientHandler
-
- RESPONSE_RULEENGINE_VERSION - Static variable in class com.datamelt.server.ClientHandler
-
- RESPONSE_RULEFILE - Static variable in class com.datamelt.server.ClientHandler
-
- RESPONSE_UPTIME - Static variable in class com.datamelt.server.ClientHandler
-
- reverseValue(XmlAction, String) - Method in class com.datamelt.rules.core.action.StringAction
-
returns the reverse string of the value
- rollback() - Method in class com.datamelt.db.MySqlConnection
-
rolls back a transaction that has been started. this mean
that all changes belonging to this transaction will NOT be
applied to the database.
- roundValue(XmlAction, double) - Method in class com.datamelt.rules.core.action.MathAction
-
- roundValue(XmlAction, float) - Method in class com.datamelt.rules.core.action.MathAction
-
- Row - Class in com.datamelt.util
-
the row class represents a row in an ASCII file.
- Row() - Constructor for class com.datamelt.util.Row
-
- Row(String[]) - Constructor for class com.datamelt.util.Row
-
constructor that takes an array of fields as parameter
- Row(Object[]) - Constructor for class com.datamelt.util.Row
-
constructor that takes an array of objects as parameter.
- RowDefinitionParser - Class in com.datamelt.rules.parser.xml
-
this parser is used to parse row definition files. these describe how
a fixed length ASCII file is constructed in regards to its fields.
- RowDefinitionParser() - Constructor for class com.datamelt.rules.parser.xml.RowDefinitionParser
-
- RowField - Class in com.datamelt.util
-
the RowField class represents a field defined by a name and its value (in form of an object).
- RowField(Object) - Constructor for class com.datamelt.util.RowField
-
constructor that takes the name of the field as argument. because no object/value is
specified, the object/value is set to null
- RowField(Object, Object) - Constructor for class com.datamelt.util.RowField
-
constructor that takes the name and an object/value of the field as arguments.
- RowField(String, Object) - Constructor for class com.datamelt.util.RowField
-
constructor that takes the name and an object/value of the field as arguments.
- RowField(String, String) - Constructor for class com.datamelt.util.RowField
-
constructor that takes the name and an object/value of the field as arguments.
- RowField(String, int) - Constructor for class com.datamelt.util.RowField
-
constructor that takes the name and an object/value of the field as arguments.
- RowField(String, long) - Constructor for class com.datamelt.util.RowField
-
constructor that takes the name and an object/value of the field as arguments.
- RowField(String, double) - Constructor for class com.datamelt.util.RowField
-
constructor that takes the name and an object/value of the field as arguments.
- RowField(String, float) - Constructor for class com.datamelt.util.RowField
-
constructor that takes the name and an object/value of the field as arguments.
- RowField(String, boolean) - Constructor for class com.datamelt.util.RowField
-
constructor that takes the name and an object/value of the field as arguments.
- RowField(String, BigDecimal) - Constructor for class com.datamelt.util.RowField
-
constructor that takes the name and an object/value of the field as arguments.
- RowField(String, BigInteger) - Constructor for class com.datamelt.util.RowField
-
constructor that takes the name and an object/value of the field as arguments.
- RowField(String, Date) - Constructor for class com.datamelt.util.RowField
-
constructor that takes the name and an object/value of the field as arguments.
- ROWFIELD_TYPE_BIGDECIMAL_DEFAULT_VALUE - Static variable in class com.datamelt.util.Constants
-
- ROWFIELD_TYPE_BOOLEAN_DEFAULT_VALUE - Static variable in class com.datamelt.util.Constants
-
- ROWFIELD_TYPE_DATE_DEFAULT_VALUE - Static variable in class com.datamelt.util.Constants
-
- ROWFIELD_TYPE_DOUBLE_DEFAULT_VALUE - Static variable in class com.datamelt.util.Constants
-
- ROWFIELD_TYPE_FLOAT_DEFAULT_VALUE - Static variable in class com.datamelt.util.Constants
-
- ROWFIELD_TYPE_INTEGER_DEFAULT_VALUE - Static variable in class com.datamelt.util.Constants
-
- ROWFIELD_TYPE_LONG_DEFAULT_VALUE - Static variable in class com.datamelt.util.Constants
-
- ROWFIELD_TYPE_STRING_DEFAULT_VALUE - Static variable in class com.datamelt.util.Constants
-
- RowFieldCollection - Class in com.datamelt.util
-
the RowFieldCollection class represents a container with RowField objects.
- RowFieldCollection() - Constructor for class com.datamelt.util.RowFieldCollection
-
empty default constructor
- RowFieldCollection(String[]) - Constructor for class com.datamelt.util.RowFieldCollection
-
constructor that takes an array of field names as parameter
the field names define the names of the fields of the row. make sure that
before running the ruleengine values are assigned to the fields using one of the
setFields() methods
- RowFieldCollection(ArrayList<RowField>) - Constructor for class com.datamelt.util.RowFieldCollection
-
constructor that takes an array of row fields as parameter.
- RowFieldCollection(String[], String[]) - Constructor for class com.datamelt.util.RowFieldCollection
-
constructor that takes an array of field names and an array of values as parameter.
- RowFieldCollection(HeaderRow, String[]) - Constructor for class com.datamelt.util.RowFieldCollection
-
constructor that takes a header row (field names) and an array of values as parameter.
- RowFieldCollection(HeaderRow, Object[]) - Constructor for class com.datamelt.util.RowFieldCollection
-
constructor that takes a HeaderRow and an array of objects/values as parameter.
- RowFieldCollection(String[], Object[]) - Constructor for class com.datamelt.util.RowFieldCollection
-
constructor that takes an array of field names and an array of objects/values as parameter.
- RowFieldCollection(Map<String, Object>) - Constructor for class com.datamelt.util.RowFieldCollection
-
constructor that takes an map of field names and objects/values as parameter.
- RowFieldCollection(ArrayList<String>, Object[]) - Constructor for class com.datamelt.util.RowFieldCollection
-
constructor that takes an array of field names and an array of objects/values as parameter.
- RowFieldCollection(GenericRecord, Schema) - Constructor for class com.datamelt.util.RowFieldCollection
-
constructor that takes an avro generic record and the avro schema as parameter.
- RowFieldCollection(GenericRecord) - Constructor for class com.datamelt.util.RowFieldCollection
-
constructor that takes an avro generic record as parameter.
- RowFieldCollection(Object[]) - Constructor for class com.datamelt.util.RowFieldCollection
-
constructor that takes an array of objects as parameter
- RuleCollection - Class in com.datamelt.rules.core
-
collection of rules in the form of XmlRule objects.
- RuleCollection() - Constructor for class com.datamelt.rules.core.RuleCollection
-
- RuleEngineClient - Class in com.datamelt.server
-
- RuleEngineClient(String, int) - Constructor for class com.datamelt.server.RuleEngineClient
-
- RuleEngineClient(String) - Constructor for class com.datamelt.server.RuleEngineClient
-
- RuleEngineClientMessage - Class in com.datamelt.server
-
utility class which can be used to send messages to a running rule engine server.
- RuleEngineClientMessage() - Constructor for class com.datamelt.server.RuleEngineClientMessage
-
- RuleEngineServer - Class in com.datamelt.server
-
- RuleEngineServerObject - Class in com.datamelt.server
-
- RuleEngineServerObject() - Constructor for class com.datamelt.server.RuleEngineServerObject
-
- RuleEngineServerObject(RowFieldCollection, int) - Constructor for class com.datamelt.server.RuleEngineServerObject
-
- RuleEngineServerObject(String[], String[], int) - Constructor for class com.datamelt.server.RuleEngineServerObject
-
- RuleEngineServerObject(ArrayList<RowField>, int) - Constructor for class com.datamelt.server.RuleEngineServerObject
-
- RuleExecutionCollection - Class in com.datamelt.rules.core
-
is used to collect the results in form of RuleExecutionResult objects.
- RuleExecutionCollection() - Constructor for class com.datamelt.rules.core.RuleExecutionCollection
-
- RuleExecutionResult - Class in com.datamelt.rules.core
-
this class carries the results of the execution of one rule.
- RuleExecutionResult(String) - Constructor for class com.datamelt.rules.core.RuleExecutionResult
-
constructor including the timestamp of when the rule was executed
- RuleExecutionResult(String, XmlRule, String, String) - Constructor for class com.datamelt.rules.core.RuleExecutionResult
-
constructor for this class using the timestamp, the rule and a label
for the rule used during output.
- RuleGroup - Class in com.datamelt.rules.core
-
Rules are organized in groups and subgroups.
- RuleGroup(String, String) - Constructor for class com.datamelt.rules.core.RuleGroup
-
constructor for a rule group using its id and description
- RULEGROUP_STATUS_MODE_ALL_FAILED - Static variable in class com.datamelt.rules.engine.BusinessRulesEngine
-
- RULEGROUP_STATUS_MODE_ALL_PASSED - Static variable in class com.datamelt.rules.engine.BusinessRulesEngine
-
- RULEGROUP_STATUS_MODE_AT_LEAST_ONE_FAILED - Static variable in class com.datamelt.rules.engine.BusinessRulesEngine
-
- RULEGROUP_STATUS_MODE_AT_LEAST_ONE_PASSED - Static variable in class com.datamelt.rules.engine.BusinessRulesEngine
-
- RULEGROUP_STATUS_MODE_MINIMUM_NUMBER - Static variable in class com.datamelt.rules.engine.BusinessRulesEngine
-
- RULEGROUP_STATUS_MODE_NOT_ALL_FAILED - Static variable in class com.datamelt.rules.engine.BusinessRulesEngine
-
- RULEGROUP_STATUS_MODE_NOT_ALL_PASSED - Static variable in class com.datamelt.rules.engine.BusinessRulesEngine
-
- RuleGroupPrioritizer - Class in com.datamelt.util
-
a rulegroup may depend on another rulegroup. this also means, that the dependent rulegroup
needs to be executed first, before the rulegroup depending on the group.
- RuleGroupPrioritizer(ArrayList<RuleGroup>) - Constructor for class com.datamelt.util.RuleGroupPrioritizer
-
- RuleMessage - Class in com.datamelt.rules.core
-
this class is used for the messages that are used for a rule. a rule can have
a message in case it fails and one in case it passes.
- RuleMessage(int, String) - Constructor for class com.datamelt.rules.core.RuleMessage
-
constructor using the type of the message (failed or passed) and the
text of the message
- RuleMessage(int) - Constructor for class com.datamelt.rules.core.RuleMessage
-
constructor using the type of the message (failed or passed)
- RuleMessageCollection - Class in com.datamelt.rules.core
-
collection of messages that belong to a rule in form of
RuleMessage objects.
- RuleMessageCollection() - Constructor for class com.datamelt.rules.core.RuleMessageCollection
-
- RuleObject - Class in com.datamelt.rules.core
-
a RuleObject identifies an object that will be instantiated and one of its methods
will be run.
- RuleObject(String, String, String) - Constructor for class com.datamelt.rules.core.RuleObject
-
constructor using the classname, name of the method to execute and the return
type of the method
- RuleObject(String, String, String, String, String) - Constructor for class com.datamelt.rules.core.RuleObject
-
constructor using the classname, name of the method to execute and the return
type of the method, the parameter that has to be passed to the method and its type
- RuleObjectCollection - Class in com.datamelt.rules.core
-
collection of RuleObject objects that are created from parsing the
rule definition xml file(s).
- RuleObjectCollection() - Constructor for class com.datamelt.rules.core.RuleObjectCollection
-
- RuleSubGroup - Class in com.datamelt.rules.core
-
- RuleSubGroup(String, String, String, String) - Constructor for class com.datamelt.rules.core.RuleSubGroup
-
- RuleSubGroupCollection - Class in com.datamelt.rules.core
-
collection of RuleSubGroups which belong to a certain RuleGroup
- RuleSubGroupCollection() - Constructor for class com.datamelt.rules.core.RuleSubGroupCollection
-
- run(String, Object) - Method in class com.datamelt.rules.engine.BusinessRulesEngine
-
method runs the rules for all groups and subgroups
against the object with the given label
- run(String, String, Object) - Method in class com.datamelt.rules.engine.BusinessRulesEngine
-
method runs the rules for a given rule group by specifying the group id.
- run(String[], String, Object) - Method in class com.datamelt.rules.engine.BusinessRulesEngine
-
method runs the rules for a given array of rule groups by specifying the group names.
- run(RuleGroup, String, Object) - Method in class com.datamelt.rules.engine.BusinessRulesEngine
-
method runs the rules for a given rule group against the object with the given label.
- run(Collection<Object>) - Method in class com.datamelt.rules.engine.BusinessRulesEngine
-
method runs the rules for all groups and subgroups
for all objects of the collection.
- run(String, String) - Method in class com.datamelt.rules.engine.BusinessRulesEngine
-
method runs the rules for all groups and subgroups.
- run(Object) - Method in class com.datamelt.rules.engine.BusinessRulesEngine
-
method runs the rules for all groups and subgroups
against the object.
- run() - Method in class com.datamelt.server.ClientHandler
-
- run() - Method in class com.datamelt.server.RuleEngineServer
-
- runRules(String, Object) - Method in class com.datamelt.rules.core.RuleGroup
-
this method is used to run all rules in all subgroups.
- runRules(String, Object) - Method in class com.datamelt.rules.core.RuleSubGroup
-
method runs all rules against the object that the rule has to be
checked against.


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Movies have been based on novels for a while. Even old TV-shows and comic books. But only recently have movies been based on video games. The following are short reviews of some recent movies based on video games. Enjoy. Send any comments/critiques/flames to<EMAIL_ADDRESS>(me). Enjoy!!
SUPER MARIO BROS.: THE MOVIE (1994) Starring: Dennis Hopper and John Leguizamo
This movie is based off the wildly popular video-game series of the same name. Before this film, the game had a few spin-off cartoons- which were OK. But the idea of doing a movie is insane. It should have been animated, if it should have been done at all. Instead the people do the best they can with a talented cast. Yet it still fails.
The plot is completely different from the game's plot- I'm not complaining about that. The story involves the Mario Bros. having a plumbing business in Brooklyn and having to compete with a rival company. Eventually they find a construction site by their nemesis, which happens to be enviromentally un-safe. So, due to Luigi's (John Leguizamo) girlfriend - Princess Daisy - they go and investigate. They get transported to a Blade Runner-esque world lead by King Koopa (Dennis Hopper). Somehow a plot dealing with all the dinosaurs being mutated and transported to an alternate futuristic mega-city jumbles in. The plot is fine- better than the movie deserves.
The acting is OK. This seems to be more of a visual film. The special effects are good, especially on the robotic Yoshi. However the film drags and is no fun. And it leaves itself open to a sequel, which probably won't ever be made. This movie begins sort of promising, but ends up leaving a weird taste in your mouth. So if you want to watch a sort of odd movie starring the excellent Dennis Hopper, then watch SUPER MARIO BROS.: THE MOVIE. You could do worse. But you could definitely do better... *1/2 out of ****.
STREET FIGHTER: THE MOVIE (1995) Starring: Raul Julia and Jean Claude Van-Damme
This movie was based off of a series of never ending sequels to a game called Street Fighter 2. It has all the characters from the game in a reasonable plot. It is more like a "movie" than it should be. Yes, it's watchable. Raul Julia does a good job, considering this was his final film. While the game had non-stop fighting sequences, this movie is a hodge-podge of action scenes and flashy sets and costumes while trying to show off a plot at the same time. Does it work? Sort of...
The plot involves the evil Shadowloo Organization run by M. Bison (Raul Julia). Guile (Jean Claude Van-Damme) takes his troops to attack Bison's main base in an attempt to liberate the innocent villages he has taken over. In a short amount of time, the movie introduces several characters well. It catches your attention. But it ultimately seems like a showcase for fans of the game so you can point out things like "There's Chun Li!!" or "Look at that Fire-Ball Ryu did at Vega". It hits the bases by presenting the characters in a plot with good sets, but goes no further.
This movie needed more action in the first place. The action scenes that are here are short and not very exciting. If you like light-hearted action flicks, or if you liked the game, watch this one. It is even worth watching if you want to see Raul Julia's last performance, or if you can't get enough of Van Damme. Other than that, you could find better action flicks. ** out of ****.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


Targeting elements without classes or ids
Target Current node
unordered list inside of a div
This is the parent
The radio button itsel here is the current element
This is the paernt of the parent
his input is inside a div wrapped in a list item
current li element
current div element
Target Parent node
unordered list inside of a div
This is the parent of the input
red
This is the paernt of the parent of the input
This input is inside a div wrapped in a list item
purple
current li element
current Div element
Adding an element
this button will add a paragraph to the an already existing div
Create Element
Adding an element to current parent element
this button will add a paragraph to the parent div pf the current element. This div is the parent node of the button
Create to current parent Element
Adding an element to current element
this button will add a paragraph to the current element. Thie button is the current element
Create to current button Element


Priest Greymore:
Hm... now that I think about it, might I tempt you with a mission from Dominic? It is not that I am incapable of doing it, but my face is too well known. Not like yours, at least not around here.
Besides, you're already here, and if Dominic saw fit to trust you with this parcel, I see no reason not to trust you myself.
Accept the mission.


React Maybe Matchers for Jasmine
Tests using the React test utilities directly are both difficult to read
and inconvenient to type. These matchers are intended to to make it
easier to write tests and to understand what they are doing later.
Please see the
project page
or browse the
annotated source code
for more information of how to use the matchers.
Tests
You can run the tests.
License
react-maybe-matchers is covered by the
MIT License.


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Wow!  Ready for some more? You have received an invitation of battle. Get yourself ready!
Energy Enchanted Sword The Book of Curse Traditional Healing Talisman


Le Marin lies at the head of a deep bay, Le Cul-de-Sac du Marin, on the southern end of Martinique. It has one of the largest marinas in the Caribbean.
Position 14° 25'38"N, 60° 55'04"W (entrance to the channel)
Position 14° 26'N, 60° 53'W (St Anne anchorage)
See the main Noonsite/Martinique/Formalities page for full details.
Clearance is possible at the marina office at one of the 4 computers and is as relaxed as elsewhere in the French islands. Fast and efficient. This office is open in the mornings. Unless intending to use the marina, arriving boats usually anchor and take their dinghy to one of the marina pontoons.
Alternatively yachts can anchor at St Anne where there is a clearance computer terminal at the "Snack Boubou" next to the church (see recommendation below in comments). Be careful at the dinghy pontoon here and be sure to use a stern anchor or lift the front out to prevent it from sliding under.
Last updated December 2015.
Take care when navigating the channel into the lagoon as it has many twists and turns. Note: Buoyage is IALA-B (red to sta'bd).
There is a great anchorage just round the Pointe Marin, in the mangroves. A bit tricky to enter, with a short but winding channel surrounded by shallows (and a small yacht wreck to show in the middle), but well worth it. Very good holding, totally protected from all sides, and calm. There is room for no more than 2 or 3 yachts.
The yacht harbour here is one of the largest in the Caribbean with 650 berths. Staff are bilingual. Whilst 220vt electricity is included in the berthing fee, water is reported to be expensive. WiFi is charged as extra. Pontoon gates are controlled by key card, however they are seldom closed, so security is not ideal. Be sure to secure anything left on deck and your dinghy and associated gear at all times.
Stocking up on provisions is very easy here, with some good supermarkets and a great range of produce.
A less-crowded anchorage can be found off nearby St. Anne (where clearance is also possible). St. Anne is a pretty little town, and it's easy to catch a bus into Marin for provisioning.
Last updated December 2015.


Reinforcement Learning(RL) is a type of machine learning technique that enables an agent to learn in an interactive environment by trial and error using feedback from its own actions and experiences.
Though both supervised and reinforcement learning use mapping between input and output, unlike supervised learning where feedback provided to the agent is correct set of actions for performing a task, reinforcement learning uses rewards and punishment as signals for positive and negative behavior.
As compared to unsupervised learning, reinforcement learning is different in terms of goals. While the goal in unsupervised learning is to find similarities and differences between data points, in reinforcement learning the goal is to find a suitable action model that would maximize the total cumulative reward of the agent. The figure below represents the basic idea and elements involved in a reinforcement learning model.


I am a eager learner and currently pursuing my batchelor degree in computer science . i have experience in few languages and current working on other language. I am event lead in one of my university club and had quiet professional experience in organising it .
VIT Bhopal University | 2020 - 2024
currently studing in computer science branch in VIT bhopal university
| 2018 - 2019
completed my secondary schooling from central academy school
| 2006-2018
completed my primary schooling from st pauls
College clubs | Excellent
currently working as Event head cyber warrior club in vit bhopal and worked in ai club as event manager and in 2018 organised a national level hackethon in delhi and also own my own organisation named as parivartan
College clubs | Good
worked in code academy as social media marketor , and for my own organisation i have done quiet good marketing for its growth .
self practise | good
learned web dev and currently practising web dev


§560:2-111 Alienage. No individual is disqualified to take as an heir because the individual or an individual through whom the individual claims is or has been an alien. [L 1996, c 288, pt of §1]


Welcome to Iris Flower Prediction ML App
Simple, yet useful app which allows to analyze Iris flower species!
Thank You. Here is the Information You Gave:
Sepal Length: {{session['sepal_length']}}
Sepal Width: {{session['sepal_width']}}
Petal Length: {{session['petal_length']}}
Petal Width: {{session['petal_width']}}
Predicted Flower Class is:
{{results}}


-> If you are an individual looking to dispose of E-Waste, create an account by providing details and log in.
-> You will see a ‘Home’ tab by default with the option of specifying your personal details and your E-Waste specifications.
-> Enter your details and go to the ‘Bins’ section to view the bins in your vicinity. You will find the bin details such as the unique bin number, bin location and the access code to open the hatch of the bin.
-> Head to the nearest empty bin as shown by the portal and drop off your E-Waste, and that’s it! Being sustainable does not take too much effort!
-> If you are a mid-level E-Waste Collector, you have the option to specify the details of the E-Waste you possess (category, quantity, etc.) as part of the request to bulk recyclers of E-Waste, in the ‘Requests’ section and specify the shipment details for the requests that have been accepted by the recycler, in the ‘Shipments’ section.
-> You may use the ‘view Bin Info’ section to view the information about the bin numbers, bin locations and bin status along with your access code to open the top hatch of the bin when you go to the bin location to collect the E-Waste from a bin that is full.
-> Clicking on ‘Track Bin capacity’ will take you to a special dashboard that lets you view the status of the bins at a glance. The bin capacity will be updated in the dashboard automatically. Use the ‘view bin info’ section to correlate the bin numbers with the bin location.
-> If you are a recycler, you have the option to track requests to deposit E-waste, from collectors. You may choose to accept or ignore the request.
-> For the requests which you do accept, you may view the shipment details specified by the corresponding collectors, under the ‘Shipments’ tab.
-> You may monitor multiple shipments from multiple collectors simultaneously.


simulateCyclopsData
generates a simulated large, sparse data set for use by fitCyclopsSimulation
.
simulateCyclopsData( nstrata = 200, nrows = 10000, ncovars = 20, effectSizeSd = 1, zeroEffectSizeProp = 0.9, eCovarsPerRow = ncovars/100, model = "survival" )
| nstrata | Numeric: Number of strata |
|---|---|
| nrows | Numeric: Number of observation rows |
| ncovars | Numeric: Number of covariates |
| effectSizeSd | Numeric: Standard derivation of the non-zero simulated regression coefficients |
| zeroEffectSizeProp | Numeric: Expected proportion of zero effect size |
| eCovarsPerRow | Number: Effective number of non-zero covariates per data row |
| model | String: Simulation model. Choices are: |
A simulated data set
#Generate some simulated data: sim <- simulateCyclopsData(nstrata = 1, nrows = 1000, ncovars = 2, eCovarsPerRow = 0.5, model = "poisson")#> Sparseness = 77.4 %cyclopsData <- convertToCyclopsData(sim$outcomes, sim$covariates, modelType = "pr", addIntercept = TRUE)#> Sorting covariates by covariateId and rowId#Define the prior and control objects to use cross-validation for finding the #optimal hyperparameter: prior <- createPrior("laplace", exclude = 0, useCrossValidation = TRUE) control <- createControl(cvType = "auto", noiseLevel = "quiet") #Fit the model fit <- fitCyclopsModel(cyclopsData,prior = prior, control = control)#> Using cross-validation selector type byRow #> Performing 10-fold cross-validation [seed =<PHONE_NUMBER>] with data partitions of sizes 100 100 100 100 100 100 100 100 100 100 #> Using 1 thread(s) #> Starting var = 0.226 (default) #> Running at Laplace(2.97482) None Grid-point #1 at 0.226 Fold #1 Rep #1 pred log like = 792.844 #> Running at Laplace(2.97482) None Grid-point #1 at 0.226 Fold #2 Rep #1 pred log like = 617.557 #> Running at Laplace(2.97482) None Grid-point #1 at 0.226 Fold #3 Rep #1 pred log like = 616.862 #> Running at Laplace(2.97482) None Grid-point #1 at 0.226 Fold #4 Rep #1 pred log like = 590.672 #> Running at Laplace(2.97482) None Grid-point #1 at 0.226 Fold #5 Rep #1 pred log like = 677.662 #> Running at Laplace(2.97482) None Grid-point #1 at 0.226 Fold #6 Rep #1 pred log like = 553.036 #> Running at Laplace(2.97482) None Grid-point #1 at 0.226 Fold #7 Rep #1 pred log like = 698.08 #> Running at Laplace(2.97482) None Grid-point #1 at 0.226 Fold #8 Rep #1 pred log like = 737.317 #> Running at Laplace(2.97482) None Grid-point #1 at 0.226 Fold #9 Rep #1 pred log like = 807.911 #> Running at Laplace(2.97482) None Grid-point #1 at 0.226 Fold #10 Rep #1 pred log like = 576.817 #> AvgPred = 666.876 with stdev = 85.803 #> Completed at 0.226 #> Next point at 2.26 with value 0 and continue = 1 #> search[ 0.226 ] = 666.876(85.803) #> #> Running at Laplace(0.940721) None Grid-point #2 at 2.26 Fold #1 Rep #1 pred log like = 792.826 #> Running at Laplace(0.940721) None Grid-point #2 at 2.26 Fold #2 Rep #1 pred log like = 617.55 #> Running at Laplace(0.940721) None Grid-point #2 at 2.26 Fold #3 Rep #1 pred log like = 616.879 #> Running at Laplace(0.940721) None Grid-point #2 at 2.26 Fold #4 Rep #1 pred log like = 590.679 #> Running at Laplace(0.940721) None Grid-point #2 at 2.26 Fold #5 Rep #1 pred log like = 677.644 #> Running at Laplace(0.940721) None Grid-point #2 at 2.26 Fold #6 Rep #1 pred log like = 553.048 #> Running at Laplace(0.940721) None Grid-point #2 at 2.26 Fold #7 Rep #1 pred log like = 698.06 #> Running at Laplace(0.940721) None Grid-point #2 at 2.26 Fold #8 Rep #1 pred log like = 737.304 #> Running at Laplace(0.940721) None Grid-point #2 at 2.26 Fold #9 Rep #1 pred log like = 807.94 #> Running at Laplace(0.940721) None Grid-point #2 at 2.26 Fold #10 Rep #1 pred log like = 576.831 #> AvgPred = 666.876 with stdev = 85.7988 #> Completed at 2.26 #> Next point at 22.6 with value 0 and continue = 1 #> search[ 0.226 ] = 666.876(85.803) #> search[ 2.26 ] = 666.876(85.7988) #> #> Running at Laplace(0.297482) None Grid-point #3 at 22.6 Fold #1 Rep #1 pred log like = 792.82 #> Running at Laplace(0.297482) None Grid-point #3 at 22.6 Fold #2 Rep #1 pred log like = 617.548 #> Running at Laplace(0.297482) None Grid-point #3 at 22.6 Fold #3 Rep #1 pred log like = 616.885 #> Running at Laplace(0.297482) None Grid-point #3 at 22.6 Fold #4 Rep #1 pred log like = 590.682 #> Running at Laplace(0.297482) None Grid-point #3 at 22.6 Fold #5 Rep #1 pred log like = 677.639 #> Running at Laplace(0.297482) None Grid-point #3 at 22.6 Fold #6 Rep #1 pred log like = 553.052 #> Running at Laplace(0.297482) None Grid-point #3 at 22.6 Fold #7 Rep #1 pred log like = 698.054 #> Running at Laplace(0.297482) None Grid-point #3 at 22.6 Fold #8 Rep #1 pred log like = 737.299 #> Running at Laplace(0.297482) None Grid-point #3 at 22.6 Fold #9 Rep #1 pred log like = 807.949 #> Running at Laplace(0.297482) None Grid-point #3 at 22.6 Fold #10 Rep #1 pred log like = 576.835 #> AvgPred = 666.876 with stdev = 85.7974 #> Completed at 22.6 #> Next point at 6.20929 with value 666.876 and continue = 0 #> search[ 0.226 ] = 666.876(85.803) #> search[ 2.26 ] = 666.876(85.7988) #> search[ 22.6 ] = 666.876(85.7974) #> #> #> Maximum predicted log likelihood (666.876) estimated at: #> 6.20929 (variance) #> 0.567537 (lambda) #> #> Fitting model at optimal hyperparameter #> Using prior: Laplace(0.567537) None#> [1] 6.209294#> 'log Lik.' -2175.875 (df=3)#> (Intercept) 1 2 #> -3.65827000 -0.02978819 -0.01326344#> Using 1 thread(s)#> covariate 2.5 % 97.5 % evaluations #> [1,] 0 -3.688468 -3.628274 22


{% extends "base.html" %} {% load static %} {% block content %}
Are you sure you want to delete "{{ object }}"?


Results-driven change agent seeking for data engineering and software development opportunities.
Proven talent for aligning business strategy and objectives with established software development and operations management paradigms to achieve maximum operational impacts with minimum resource expenditures. Growth-focused thought leader with expertise spanning machine learning, artificial intelligence, Python, AWS, data analysis, software development life cycle, team leadership, operations optimization, cross-functional team collaboration, web development, technology solutions, and project management. Exceptionally dedicated professional with keen interpersonal, communication, and organizational skills.
GPA: 4.00
GPA: 4.00
• Served as key contributor in complete software development life cycle from requirements gathering and analysis, design, development to testing.
• Participated in code reviews to resolve technical issues and ensure adherence to business requirements.
• Directed the team tasked with creating and optimizing Gherkins for user stories, designed and implemented automation architecture and suite using Selenium, Jenkins and Object-Oriented Programming concepts as part of ATDD methodology.
• Responsible for designing and implementing SQL queries using MySQL in over 5 applications.
• Executed comprehensive root cause analysis and business impact analysis through testing and fixing bugs on 20+ time and business critical hotfixes for fare management system client on both Windows and Linux systems.
• Conceptualized, created, and maintained more than 100 test scripts for a financial firm’s legal application utilizing HP Quick Test Professional automation tool to facilitate automated regression, decreasing all manual work by 70%.
• Defined and deployed 3000+ test scripts and maintained the Requirements Traceability Matrix. Spearheaded triage calls to enable defect closure.
• Determined and outlined test estimation, designed, and implemented the test plan for both financial and digital clients and headed testing teams with team size varying from 5 to 12 members.
• Served as a full-stack developer as part of a collaborative team charged with building a care coordination application for Anthem, to enable healthcare providers to deliver quality care and simultaneously reduce spending costs.
• Developed the application in Python using Django framework and Docker with Bootstrap and JavaScript for frontend development, later deployed in HDAP (Health Data Analytics Platform) environment.
• Enabled the application to use FHIR integration for real time updates to synchronize patient data using RESTful APIs and Postgres database to effectively capture session notes and Zoom video chat integration for care coordination among healthcare providers.
• Created and developed a chatbot in Python with TextBlob and Word libraries using Natural Language Processing (NLP) to classify the input in JSON files utilizing a probabilistic approach that responded with 90% accuracy.
• Designed the chatbot to learn from user feedback in real time and update the intent and entity details.
• Engineered to be integrated with APIs of chat platforms such as Slack or Hangouts.
• Recognized among the top 10 chatbots in the class.
• Completed implementation and analysis of Supervised Learning algorithms, including Decision trees with minimum-error pruning, Artificial Neural Networks, Adaptive Boosting, Support Vector Machines with Linear and Radial Basis Function (RBF) kernels, and k-Nearest Neighbors using sklearn library.
• Incorporated investigation of learning curves, confusion matrices, time complexities, and tuning of hyperparameters that affect the performance of the algorithms into the analysis.
• Formulated and developed a Strategy Learner, that encompassed a Bag Learner and a Random Tree Learner.
• Planned the algorithm to assess the value of the portfolio and allocate funds to the equities in the portfolio, maximizing the investment performance, based on four years of historical stock data, using Python’s NumPy, Pandas, and SciPy libraries and visualized optimized output using matplotlib libraries.
• Feature engineering techniques of Numerical Imputation and Scaling are used for data preprocessing.
• Established an agent that solves Raven’s Progressive Matrices, a standardized intelligence test, using Python with NumPy and Python Imaging Library (PIL).
• Devised the agent to learn about the images in the problem matrix using Semantic Networks and determined the appropriate answers for 25 of 30 out-of-sample problems using Generate and Test method.
• Employed principles of Human-Computer Interaction (HCI) to design an enhanced prototype for a mobile trading app E*TRADE qualitatively evaluated by users.
• Navigated the design life cycle with needfinding via user surveys, interviews, market research of apps, and deciding on design alternatives and wireframe prototyping.
• Moribus is a game for children where they can read moral stories and answer a morally challenging question with respect to that story.
• Developed a multi-level graphical Android game for children in GameSalad Creator IDE supported by GameSalad game engine which uses the concept of Game-Based Learning and graphics were engaged through Adobe Illustrator and Graphical Template Packs; this was accompanied by a submission ready CHI paper.
• Designed and developed an Android game that allows user to create and solve cryptograms.
• Involved in complete SDLC of the game- gathering high level requirements, analysing problem domain and refining requirements, identifying and detailing architectural (UML) and low-level design components of the game, authoring detailed design document, development in Java complete with user authentication, data persistence using SharedPreferences and automated testing with Espresso.
Member of AnitaB.org and Systers group
Planned and organized International Women’s Day event for women engagement at Accenture.
Started an environment-friendly project as an entrepreneur under LEAD, a youth-leadership program at Deshpande Foundations.


public interface AuthenticationHandler
AuthenticationHandler
interface defines the service API used
by the authentication implementation to support plugin various ways of
extracting credentials from the request.| Modifier and Type | Interface and Description |
|---|---|
static class |
AuthenticationHandler.FAILURE_REASON_CODES
This enum indicates the supported detailed login failure reason codes:
invalid_login : indicates username/password mismatch. |
| Modifier and Type | Field and Description |
|---|---|
static String |
FAILURE_REASON
Name of the request attribute which may be set by the
extractCredentials(HttpServletRequest, HttpServletResponse)
method if AuthenticationInfo.FAIL_AUTH is returned. |
static String |
FAILURE_REASON_CODE
Name of the request attribute which may be set by the
extractCredentials(HttpServletRequest, HttpServletResponse)
method if AuthenticationInfo.FAIL_AUTH is returned. |
static String |
PATH_PROPERTY
The name of the service registration property listing one or more URL
paths for which the authentication handler is to be used.
|
static String |
REQUEST_LOGIN_PARAMETER
The request parameter which may be used to explicitly select an
authentication handler by its
type if
authentication will be requested through
requestCredentials(HttpServletRequest, HttpServletResponse) . |
static String |
SERVICE_NAME
The name under which an implementation of this interface must be
registered to be used as an authentication handler.
|
static String |
TYPE_PROPERTY
The name of the service registration property (single string) providing
the authentication type of authentication handler.
|
| Modifier and Type | Method and Description |
|---|---|
void |
dropCredentials(javax.servlet.http.HttpServletRequest request,
javax.servlet.http.HttpServletResponse response)
Drops any credential and authentication details from the request and asks
the client to do the same.
|
AuthenticationInfo |
extractCredentials(javax.servlet.http.HttpServletRequest request,
javax.servlet.http.HttpServletResponse response)
Extracts credential data from the request if at all contained.
|
boolean |
requestCredentials(javax.servlet.http.HttpServletRequest request,
javax.servlet.http.HttpServletResponse response)
Requests authentication information from the client.
|
static final String SERVICE_NAME
static final String PATH_PROPERTY
Each string value may either be an absolute path (e.g. /content) or an absolute URL (e.g. http://thehost/content) to assign the authentication handler to authenticate request for a select virtual host.
Authentication handlers without a path
service registration
property are ignored.
static final String TYPE_PROPERTY
authentication type
returned by the
extractCredentials(HttpServletRequest, HttpServletResponse)
method.
This property is optional but allows the client to optionally select the
authentication handler which will actually request credentials upon the
requestCredentials(HttpServletRequest, HttpServletResponse)
method.
REQUEST_LOGIN_PARAMETER
,
Constant Field Valuesstatic final String REQUEST_LOGIN_PARAMETER
type
if
authentication will be requested through
requestCredentials(HttpServletRequest, HttpServletResponse)
.static final String FAILURE_REASON
extractCredentials(HttpServletRequest, HttpServletResponse)
method if AuthenticationInfo.FAIL_AUTH
is returned.
This result may be used by authentication handlers to inform the user of any failures.
extractCredentials(HttpServletRequest, HttpServletResponse)
,
Constant Field Valuesstatic final String FAILURE_REASON_CODE
extractCredentials(HttpServletRequest, HttpServletResponse)
method if AuthenticationInfo.FAIL_AUTH
is returned.
This result may be used by authentication handlers to inform the user of more detailed failure reasons, e.g. "password_expired".
extractCredentials(HttpServletRequest, HttpServletResponse)
,
Constant Field ValuesAuthenticationInfo extractCredentials(javax.servlet.http.HttpServletRequest request, javax.servlet.http.HttpServletResponse response)
The method returns any of the following values :
| value | description |
|---|---|
null
| no user details were contained in the request or the handler is not capable or willing to extract credentials from the request |
AuthenticationInfo.DOING_AUTH
| the handler is in an ongoing authentication transaction with the client. Request processing should be aborted at this stage. |
AuthenticationInfo.FAIL_AUTH
| the handler failed extracting the credentials from the request for
any reason. An example of this result is that credentials are present in
the request but they could not be validated and thus not be used for
request processing. When returning this value, the authentication handler
may also set the FAILURE_REASON request attribute to inform
interested parties (including its own
requestCredentials(HttpServletRequest, HttpServletResponse)
method for the reasons of failure to extract the credentials.
|
AuthenticationInfo object
| The user sent credentials. The returned object contains the credentials as well as the type of authentication transmission employed. |
The method must not request credential information from the client, if they are not found in the request.
The value of PATH_PROPERTY
service registration property value
triggering this call is available as the path
request
attribute. If the service is registered with multiple path values, the
value of the path
request attribute may be used to implement
specific handling.
request
- The request object containing the information for the
authentication.response
- The response object which may be used to send the
information on the request failure to the user.AuthenticationInfo
instance identifying the
request user, AuthenticationInfo.DOING_AUTH
if the
handler is in an authentication transaction with the client or
null if the request does not contain authentication information.
In case of AuthenticationInfo.DOING_AUTH
, the method must
have sent a response indicating that fact to the client.boolean requestCredentials(javax.servlet.http.HttpServletRequest request, javax.servlet.http.HttpServletResponse response) throws IOException
true
if the information has been requested and request
processing can be terminated normally. Otherwise the authorization
information could not be requested.
The HttpServletResponse.sendError
methods should not be used
by the implementation because these responses might be post-processed by
the servlet container's error handling infrastructure thus preventing the
correct operation of the authentication handler. To convey a HTTP
response status the HttpServletResponse.setStatus
method
should be used.
The value of PATH_PROPERTY
service registration property value
triggering this call is available as the path
request
attribute. If the service is registered with multiple path values, the
value of the path
request attribute may be used to implement
specific handling.
If the REQUEST_LOGIN_PARAMETER
request parameter is set only
those authentication handlers registered with an authentication type
matching the parameter will be considered for
requesting credentials through this method.
A handler not registered with an authentication
type
will, for backwards compatibility reasons, always be called
ignoring the actual value of the REQUEST_LOGIN_PARAMETER
parameter.
request
- The request object.response
- The response object to which to send the request.true
if the handler is able to send an authentication
inquiry for the given request. false
otherwise.IOException
- If an error occurs sending the authentication
inquiry to the client.void dropCredentials(javax.servlet.http.HttpServletRequest request, javax.servlet.http.HttpServletResponse response) throws IOException
request
- The request object.response
- The response object to which to send the request.IOException
- If an error occurs asking the client to drop any
authentication traces.Copyright © 2014 The Apache Software Foundation. All rights reserved.


--- layout: article article: true permalink: /blog/article/enumeration title: "Enumeration" cover: "enumeration.jpg" description: "Enumeration?" time_reading_minutes: "30" categories: ["Software"] ---


sudo npm install -g @vue/cli
vue create hello-world
Select, "Manually select features" (using the arrow keys and enter)
Select, "2.x" - 3.x is in beta and doesn't work with the best design library!
Press Enter (default)
Arrow down to "ESLint + Prettier" and press enter, or if you dont like prettier (think black for JS), then pick "ESLint with error prevention only"
Both work, I usually only select, "Lint on save"
Any are good, "Cypress (Chrome only)" is the best feature wise, Nightwatch is best for compatability testing
Press Enter (select default)
I usually select N (no), but feel free to!
Give it about 2 min, vue will install
cd into your app!
This is optional, but HIGHLY recommended, vuetify is the material lib I used with Checkmarks and its bomb
Make sure you are on the root directory of the project (cd into your project), then type:
vue add vuetify
Select default!
80% of my time coding in vue, I am on vuetify's website. All the docs and examples you need are there
Dont build large pages! Think about your pages in terms of reusable components! Can you abstract that barchart? Make it a component. Does that api


|
CellularHelper
|
Used to hold the results for one cell (service or neighbor) from the AT+CGED command. More...
#include <CellularHelper.h>
Public Member Functions | |
| bool | isValid (bool ignoreCI=false) const |
| Returns true if this object looks valid. More... | |
| void | parse (const char *str) |
| Parses the output from the modem (used internally) More... | |
| void | addKeyValue (const char *key, const char *value) |
| Add a key-value pair (used internally) More... | |
| String | toString () const |
| Returns a readable representation of this object as a String. More... | |
| int | getBand () const |
| Calculated field to determine the cellular frequency band. More... | |
| String | getBandString () const |
| Returns a readable string that identifies the cellular frequency band. More... | |
| int | getRSSI () const |
| Get the RSSI (received signal strength indication) More... | |
| int | getBars () const |
| Get the RSSI as "bars" of signal strength (0-5) More... | |
Data Fields | |
| int | mcc = 65535 |
| Mobile Country Code. More... | |
| int | mnc = 255 |
| Mobile Network Code. More... | |
| int | lac |
| Location Area Code. More... | |
| int | ci |
| Cell Identity. More... | |
| int | bsic |
| Base Station Identify Code. More... | |
| int | arfcn |
| Absolute Radio Frequency Channel Number. More... | |
| int | rxlev |
| Received signal level on the cell. More... | |
| bool | isUMTS = false |
| RAT is GSM (false) or UMTS (true) | |
| int | dlf |
| Downlink frequency. More... | |
| int | ulf |
| Uplink frequency. Range 0 - 16383 [3G only]. | |
| int | rscpLev = 255 |
| Received signal level [3G]. More... | |
Used to hold the results for one cell (service or neighbor) from the AT+CGED command.
You will normally use CellularHelperEnvironmentResponseStatic<> or CellularHelperEnvironmentResponse which includes this as a member.
| void CellularHelperEnvironmentCellData::addKeyValue | ( | const char * | key, |
| const char * | value | ||
| ) |
Add a key-value pair (used internally)
The AT+CGED response contains key-value pairs. This parses out the ones we care about and stores them in the specific fields of this structure.
| int CellularHelperEnvironmentCellData::getBand | ( | ) | const |
Calculated field to determine the cellular frequency band.
Values are frequency in MHz, such as: 700, 800, 850, 900, 1700, 1800, 1900, 2100
Not all bands are used by existing hardware.
Note that for 2G, 1800 is returned for the 1900 MHz band. This is because they use the same arfcn values. So 1800 really means 1800 or 1900 MHz for 2G.
| String CellularHelperEnvironmentCellData::getBandString | ( | ) | const |
Returns a readable string that identifies the cellular frequency band.
Example 3G: rat=UMTS mcc=310, mnc=410, lac=1af7 ci=817b57f band=UMTS 850 rssi=0 dlf=4384 ulf=4159
Example 2G: rat=GSM mcc=310, mnc=260, lac=ab22 ci=a78a band=DCS 1800 or 1900 rssi=-97 bsic=23 arfcn=596 rxlev=24
| int CellularHelperEnvironmentCellData::getBars | ( | ) | const |
Get the RSSI as "bars" of signal strength (0-5)
| RSSI | Bars |
|---|---|
| >= -57 | 5 |
| > -68 | 4 |
| > -80 | 3 |
| > -92 | 2 |
| > -104 | 1 |
| <= -104 | 0 |
This is simlar to the bar graph display on phones.
| int CellularHelperEnvironmentCellData::getRSSI | ( | ) | const |
Get the RSSI (received signal strength indication)
This only available on 3G devices, and even then is not always returned. It may be 0 or 255 if not known.
| bool CellularHelperEnvironmentCellData::isValid | ( | bool | ignoreCI = false | ) | const |
Returns true if this object looks valid.
| ignoreCI | (bool, default false) Sometimes the cell identifier (CI) valid is not returned by the towers but other fields are set. Passing true in this parameter causes the CI to be ignored. |
| void CellularHelperEnvironmentCellData::parse | ( | const char * | str | ) |
Parses the output from the modem (used internally)
Some classes use postprocess() to process the + response, but the AT+CGED response is sufficiently complicated that we parse each response as it comes in using the parse() method rather than waiting until all responses have come in.
| str | The comma separated response from the modem to parse |
| String CellularHelperEnvironmentCellData::toString | ( | ) | const |
Returns a readable representation of this object as a String.
| int CellularHelperEnvironmentCellData::arfcn |
Absolute Radio Frequency Channel Number.
arfcn
is 0x2CD (717) and belongs to 1900 band). | int CellularHelperEnvironmentCellData::bsic |
Base Station Identify Code.
| int CellularHelperEnvironmentCellData::ci |
Cell Identity.
| int CellularHelperEnvironmentCellData::dlf |
Downlink frequency.
| int CellularHelperEnvironmentCellData::lac |
Location Area Code.
| int CellularHelperEnvironmentCellData::mcc = 65535 |
Mobile Country Code.
| int CellularHelperEnvironmentCellData::mnc = 255 |
Mobile Network Code.
| int CellularHelperEnvironmentCellData::rscpLev = 255 |
Received signal level [3G].
Received Signal Code Power expressed in dBm levels. Range 0 - 91.
| Value | RSCP | Note |
|---|---|---|
| 0 | RSCP < -115 dBm | Weak |
| 1 | -115 <= RSCP < -114 dBm | |
| 90 | -26 <= RSCP < -25 dBm | |
| 91 | RSCP == -25 dBm | Strong |
| int CellularHelperEnvironmentCellData::rxlev |
Received signal level on the cell.


Classic Alert Styled
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All of the methods return the Legend object to enable the chaining of configuration options
Alternatively, you can build an associative array, using the method names as keys, and pass the array into the Legend's constructor


[Erowid Note: Driving while intoxicated or tripping is dangerous and irresponsible because it endangers other people. Don't do it!]
12:00n: I chew up a 20mg oxycontin for a 100mile drive to visit friends and family in my hometown. Being used to and slightly tolerant of the drug, nothing unusual occured, just the warm cozy feeling it offers, almost a sensation like receiving a backrub.  My previous dose had tapered off but was at approximately 2/3 intensity. The insufflation boosted me to a level a little above the oral dose (as it was complementing it) and a friend called to offer to tell me his wife would soon have dinner ready and he had a joint, so I happily headed over there.
5:00pm: I arrived at my friend's and told him I had a few oxycontin, and gave him one, which he ate and we smoked a nice sized joint, my first one in 3 or 4 weeks. Then we painted the nursery for his pending baby, to be born in a month or so, and had a fine chicken & dumplings meal with his family.
7:30pm: After dinner we touched up on the painting job, and it should be noted that as he has no opiate tolerance, or maybe just a coincedental reaction, he was feeling very sick, nauseus and hot, undoubtebly from the oxycodone. Naturally I felt horrible for this, but as it wasn't a very high dose, advised him to get some air, and allow himself to vomit if needed. So he got ready for bed and I headed back to my cousin's. When I got there, my cousin told me he had some Duragesic patched but was unsure of their worth/usefulness. I was very shocked as I've never had any fentanyl though I was aware of what it is and does.
8:00pm: With a little research, we decided that smoking it would be the best route of administration, as injection seemed very, very dangerous, and that by smoking it we could share a patch easily and be able to divide it into very small doses. So we took one of the 5mg (50mcg/h) patched and squeezed a dab of the gel onto a small piece of foil, and smoked it in normal dragon-chasing fashion. Immediately we noticed a somewhat intense buzz, though we toyed with the idea of it being placebo from the hype I raised when I was told we had fentanyl. So anyway, we smoked a couple more hits each and 10-15minutes later we decided we were definitely high, and were very comfortable so we stopped for a while.
8:45pm: Having measured our buzzes for almost an hour, we decided it would be safe to take a few more hits and this time soaked a cigarette in the gel. At this time about 1/3 to 1/2 of the gel was spent from the patch, and we were not disappointed nor overwhelmed by the effects. At this time another friend called and invited us both to eat at Waffle House. It is of note that during the 45 minutes from the first smoked hits to the laced cigarette, me and my cousin had been eating like crazy, hot dogs, cheetos, frozen pizza, and coffee. I would've attributed it to the pot but my cousin had not smoked any. So anyway we went to meet my friend at Waffle House, and I had some pie and coffee. We returned to the house a while later.
11:00pm: At this time I measured a few drops of fentanyl-gel onto a couple tylenol pills, to experiment with on the next day, and cut the patch open to lick some gel out.  My cousin reported feeling very high but also unable to sleep, not really uncomfortable, more or less unfortunate as he had to work the next day. I could not sleep either but did not attempt to and instead spent a few hours playing a video game and browsing the web.
1:00am: I took a couple more licks of the patch (no more smoking) and for the rest of the night I had the most comfortable, carefree buzz of my life rivaling IV'd heroin or hydromorphone, A slight itch creeped over my body but not nearly as intense as say dilaudid, and the sense of wellbeing heightened for the rest of the night well into the morning.
4:00am: I sucked the patch for 10-15 seconds, getting a very nice taste of the somewhat bitter drug all over my tongue, and that taste is persisting even now, an hour later. The euphoric trance that I am writing this in is certainly the highest level of intoxication I've been at all through the experience, and I am absently listening to the Shawshank Redemption being played. I plan to fall asleep in a few hours tops, although that may not happen. Fentanyl was never a drug I expected to try but always wanted to sample. The experience was very fulfilling and I definitely look forward to repeating it, as I have a few patches my cousin gave me and the tylenol that I dripped the remaining ~1mg from tonight's shared patch onto.
5:06am: I am completing this article, and plan to smoke one last cigarette and play a video game if sleep proves difficult. I am in complete recognition of my sleep deprivation by the bags under my eyes and clammy feeling on my skin, but the itching and euphoria are every bit as strong as they've been all night. The experience could not have been more satisfying, although I dare say it could *easily* have gotten out of hand had I for example tried to chew up the whole patch or do any large quantities at one time. 1mg would probably be a safe dose, probably accompanied with nods, more intense itching, and possibly nausea, and I will probably try to shoot for that next time. I have about that much on the tylenol caps, so I will take them one at a time over the period of an hour to further my experimenting with this fascinating new drug.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


DSC-RIT Recruitment Test 2020 Question Paper
Topic: Machine Learning
Q1: What is PCA used for?
Reducing the number of features
Reducing the number of dimensions of the data
Increasing the number of features
Increasing the dimensions of the data
Q2:What is a kernel used for?
Reducing the number of features
Reducing the number of dimensions of the data
Increasing the number of features
Increasing the dimensions of the data
Q3: What is the equation of a Logistic Regression line?
y = log(ax + b)
y = 1 / (1 + exp (-(ax + b)))
y = 1 + exp (-(ax + b))
y = 1 / exp (-(ax + b))
Q4: What does High Bias and Low Variance indicate?
Underfit
Overfit
Perfect fit
None of the above
Q5: Dropout in a Neural network refers to:
Penalizing the weights to remove overfit
Stop the training when optimum accuracy is achieved
Stop the training when the specified number of epochs are reached
Turn off a few neurons randomly to remove overfit
Q6: For a healthcare job-critical scenario,
Precision is of highest priority
F1 score is of highest priority
Recall is of highest priority
Accuracy is of highest priority
Q7: When the algorithm reaches close to global minima
Statement X: Its learning rate decreases in Adam
Statement Y: Its learning decreases in Stochastic Gradient Descent
X is true, Y is false
X is false, Y is false
X is false, Y is true
X is true, Y is true
Q8: What is a good test size: train size ratio?
0.5
0.7
0.05
0.25
Q9: What is an Eigenvector?
A vector which is not transformed by a Linear Matrix transformation
A vector which is scaled by a scalar but not rotated by a Linear Matrix Transformation
A vector which is not scaled but only rotated by a Linear matrix transformation
None of the above
Q10: How is ML different from DL?
Deep learning only includes neural networks
Deep learning models choose their features to learn from while ML models need to be fed the features
ML models use simple linear functions while DL models leverage non-linearity
None of the above
Submit


Sudheer Kumar D
Web Developer
I am a Web developer with a Bachelor of Technology (B.Tech) in Computer Science from Jawaharlal Nehru Technological University and 3.5 years of software development experience.
I am experienced in web development with frontend technologies using Angular 2/4 with Typescript, Bootstrap and HTML5. Good exposure to consuming data through different interfaces (Web API’s REST/ RESTFUL/JSON). Expertise in analyzing the DOM Layout, JavaScript functions, Cascading Styles across cross-browser using Fire Bug, Developer Tool Bar. Experience with POSTman for API testing to verify the CRUD operations.


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This is a repository made just for beginners who want to explore github and its features like pull request. When your pull request is merged you will be able to see your card in 'The Contributors' section (if done properly).
In this repository, you can request 1 or 2 pull request, since there is nothing more that can be done here. If you have signed up for Hacktober Fest , then you will only need 3 more pull requests to get a chance to win a t-shirt. This event is conducted so as to invite you to contribute to Open-Source Projects.
Go to this repository.
Open the index.html file.
Click on the edit icon on the top right (this will fork this repo into your account)
Check for the part where the comment says "Add your card above this and leave a line after it"
Paste the code found in the readme.md file, above this comment and make changes for your card.
After making suitable changes, make a pull request (Also do keep in mind the instructions in the readme file)
Sit back and wait for your card to appear below 😇


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GET /[collection]?q=type:urlquery+url:[url]Queries all available snapshots for the given URL.
GET /[collection]?q=type:prefixquery+url:[urlPrefix]Queries all records with the given URL prefix.
POST /[collection]Adds records to the collection. Post body should be in 9 or 11 field CDX format. Creates the collection if it doesn't already exist.
GET /[collection]?url=[url]Plain text URL query.


{% extends "layout.html" %} {% block body %}
Check the last time the device watered:
Check last time watered
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Installation of your custom RobotWare plugins is very straighforward. Simply place
your compiled dynamic link library (DLL) in the same directory as the main
RobotWare product. On startup, RobotWare will load your DLL and look for its
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these will be seamlessly integrated with all the other RobotWare functions.


My name is Ihab Basri. I love soccer.


| Doctor Name | City | Location | Specialization | Education | Profile | Remove |
|---|---|---|---|---|---|---|
| {{record.doctorname}} | {{record.city_c}} | {{record.location_c}} | {{record.specialization_c}} | {{record.education_c}} | View Profile | Remove |
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| Doctor Name | City | Location | Specialization | Education | Profile | Add to Panel |
|---|---|---|---|---|---|---|
| {{record.doctorname}} | {{record.city_c}} | {{record.location_c}} | {{record.specialization_c}} | {{record.education_c}} | View Profile | Add |
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