public class VectorF
extends java.lang.Object
VectorF
represents a single-dimensional vector of floats. It is not a matrix,
but can easily be converted into either a RowMatrixF
or a ColumnMatrixF
should
that be desired. That said, vectors can be multiplied by matrices to their left (or right); this
is commonly used to transform a set of coordinates (in the vector) by a transformation matrix.MatrixF
,
RowMatrixF
,
ColumnMatrixF
| Modifier and Type | Field and Description |
|---|---|
protected float[] |
data |
| Constructor and Description |
|---|
VectorF(float x) |
VectorF(float[] data) |
VectorF(float x,
float y) |
VectorF(float x,
float y,
float z) |
VectorF(float x,
float y,
float z,
float w) |
| Modifier and Type | Method and Description |
|---|---|
void |
add(VectorF addend) |
MatrixF |
added(MatrixF addend)
Adds this vector, taken as a row vector against, to the indicated matrix.
|
VectorF |
added(VectorF addend) |
protected java.lang.RuntimeException |
dimensionsError() |
protected static java.lang.RuntimeException |
dimensionsError(int length) |
float |
dotProduct(VectorF him)
Returns the dot product of this vector and another.
|
float |
get(int index) |
float[] |
getData() |
int |
length() |
static VectorF |
length(int length)
Creates a new vector of the indicated length.
|
float |
magnitude() |
VectorF |
multiplied(float scale)
Returns a new vector containing the elements of this vector scaled by the indicated factor.
|
MatrixF |
multiplied(MatrixF him)
Multiplies this vector, taken as a row vector, against the indicated matrix.
|
void |
multiply(float scale) |
VectorF |
normalized3D()
Consider this vector as a 3D coordinate or 3D homogeneous coordinate, and, if the
latter, return its normalized form.
|
void |
put(int index,
float value) |
void |
subtract(VectorF subtrahend) |
MatrixF |
subtracted(MatrixF subtrahend)
Subtracts the indicated matrix from this vector, taken as a row vector.
|
VectorF |
subtracted(VectorF subtrahend) |
java.lang.String |
toString() |
public VectorF(float[] data)
public VectorF(float x)
public VectorF(float x, float y)
public VectorF(float x, float y, float z)
public VectorF(float x, float y, float z, float w)
public static VectorF length(int length)
length
- the length of the new vector to return@Const public float[] getData()
@Const public int length()
@Const public float get(int index)
@NonConst public void put(int index, float value)
public java.lang.String toString()
toString
in class java.lang.Object
@Const public VectorF normalized3D()
@Const public float magnitude()
@Const public float dotProduct(VectorF him)
him
- the other vector with whom the dot product is to be formed@Const public MatrixF multiplied(MatrixF him)
@Const public MatrixF added(MatrixF addend)
@Const public MatrixF subtracted(MatrixF subtrahend)
@Const public VectorF multiplied(float scale)
@NonConst public void multiply(float scale)
protected java.lang.RuntimeException dimensionsError()
protected static java.lang.RuntimeException dimensionsError(int length)


Sainsbury's Avocado Ripe & Ready XL Loose 300g
£1.50
/
unit
£1.50
/
ea
Quantity
Sainsbury's Avocado, Ripe & Ready x2
£1.80
/
unit
£1.80
/
ea
Quantity


%# Note that this file is not a valid *.html file! %# It is intended to be a bottlepy - style template %# used for the scripting part of TheOnionBox! {{!header_row('Tor', 'Monitoring', 'monitor')}}
Total: 0 Bytes | Current: 0 Bytes/s
Total: 0 Bytes | Current: 0 Bytes/s
Live Chart monitoring Tor node


Transfers
${{Transfers.scheduled() | number}} within the next month
{{Transfers.totalIsUpdating}}
You have no transfers scheduled.
Make a transfer
{{transfer.created_at | date:'M/dd'}}
{{transfer.recipient}}
from Family Checking #1234
{{transfer.amount | currency}}
{{transfer.description}}
Weekly on {{transfer.created_at | date:'EEEE'}}s
Cancel


{% import '@apostrophecms/pager:macros.html' as pager with context %} {% import 'fragments.html' as fragments with context %} {% extends "layout.html" %} {% block pageTitle %}


This small port lies about 10nm south west of Le Port. It is a popular seaside resort.
Position 21° 03'16"S, 55° 13'19"E (harbour entrance)
Almost all spaces in the part are taken up by local sport fishing boats and visiting yachts may not find a berth.
Last updated August 2016.


Tutorial Tabs:
should show tutorial infomation. info tab show feature user story. test tab show test coverage and
examples of tests.
click on a tab should select the tab. Click the tab again, should de-select the tab
When a tab is selected, corresponding information is shown in pane below.
When a tab is selected, its font should be in bold and click icon should be expanded.
When a tab is de-selected, its font should not be in bold and click icon should not be expanded.
At any given time, only one tab can be selected.
click to see directive unit tests.
Login:
should allow to enter username and password to login.
verify if username is not set, login button
should be disabled. If username is set, login button should be enabled.
click to see unit test.
verify if button is clicked, login controller's login function is called.
click to see unit test.


User Greeting
Parking Meteor
It is the year<PHONE_NUMBER>20 and Mickey Mouse is the king of the Universe! He needs your help... Pluto has gone missing! It is your task to search the stars and find him! Pay your parking ticket at the parking meteor for 2 starbux and hop in your ship to find Pluto!
Freddy Mercury
WOW an ALIEN! I bet he has a clue...Greet the alien...choose wisely...
Oh no!! you have made the alien very angry, you told him his mom's feet are smelly! To advance you must make the alien your friend. Luckily aliens LOVE marsbars...click on your marsbar item to give the alien a marsbar
Alien: NOMNOMNOM...to advance to find pluto you must next find the movie star...good luck!
Which captain said... "Things are only impossible until they're not."
What is the official party song of saturn?
Saturn-down for WHAT
How do you organize a space party? Click on the answer...
Where do aliens go for a drink? Press the correct key to advance.
✩✩✩✩✩ WINNER ✩✩✩✩✩
CONGRATULATIONS SPACE KNIGHT! You found Pluto...treat yourself to a Pan Galactic Gargle Blaster!


Note: To access the Content Attachments API during the preview period, you must provide a custom media type in the Accept
header:
application/vnd.github.corsair-preview+json
Warning: The API may change without advance notice during the preview period. Preview features are not supported for production use. If you experience any issues, contact your GitHub Enterprise site administrator.
Creates an attachment under a content reference URL in the body or comment of an issue or pull request. Use the id
of the content reference from the content_reference
event to create an attachment.
The app must create a content attachment within six hours of the content reference URL being posted. See "Using content attachments" for details about content attachments.
You must use an installation access token to access this endpoint.
POST /content_references/:content_reference_id/attachments
| Name | Type | Description |
|---|---|---|
title |
string |
Required. The title of the content attachment displayed in the body or comment of an issue or pull request. |
body |
string |
Required. The body text of the content attachment displayed in the body or comment of an issue or pull request. This parameter supports markdown. |
This example creates a content attachment for the domain https://errors.ai/
.
{
"title": "[A-1234] Error found in core/models.py file",
"body": "You have used an email that already exists for the user_email_uniq field.\n ## DETAILS:\n\nThe<EMAIL_ADDRESS>already exists.\n\n The error was found in core/models.py in get_or_create_user at line 62.\n\nself.save()"
}
Status: 200 OK
{
"id": 101,
"title": "[A-1234] Error found in core/models.py file'",
"body": "You have used an email that already exists for the user_email_uniq field.\n ## DETAILS:\n\nThe<EMAIL_ADDRESS>already exists.\n\n The error was found in core/models.py in get_or_create_user at line 62.\n\n self.save()"
}


The aim of the project is teaching basic molecular biology concepts and techniques. Gene expression and protein purification are visualized using green fluorescent protein (GFP) from jellyfish Aequoria victoria, which has become an invaluable tool in contemporary biological research, because its bright intrinsic fluorescence. The relationship between the genome and proteome is further extended in individual theoretical and bioinformatics projects. State-of-the-art experimental methodology is accompanied with lectures and discussions and scientific communication skills are introduced through designing posters and presentations.
Martina Mijuskovic
Swiss Federal Institute of Technology (ETH), Zurich, Switzerland
Danijel Dojcinovic
The Scripps Research Institute, La Jolla, USA
Danijel holds an MS in molecular and cellular biology from Arizona State University, USA. His field of research is interorganellar communication in Arabidopsis thaliana.
Martina is a doctoral student at the Institute for Molecular Biology and Biophysics, ETH Zurich, Switzerland. Her research field is crystallography of general transcription factor protein-DNA complexes. She is a teaching assistant in several molecular biology courses at the Instutute.
The principal goal of the project is familiarizing students with the basic concepts and models of complex networks. Special emphasis is put on the description of complex networks appearing in nature and society, such as Internet. Theoretical models which successfully explain some of the features of real complex networks are introduced. The model of preferential attachment of Barabási and Albert, along with some of its elaborations, is studied in particular. The main results of theoretical models are verified in numerical simulations of the network growth.
Students are guided in developing the understanding of models of network growth and in adopting skills required in performing numerical simulations. In a brainstorming session, possibilities of more advanced and realistic simulation models are considered.
Hrvoje Stefancic
Rudjer Boskovic Institute, Zagreb, Croatia
Hrvoje is a postdoctoral research assistant at the Theoretical Physics Division, Rudjer Boskovic Institute. He holds a Ph. D. in high energy theoretical physics. His other fields of research comprise cosmology and astroparticle physics and recently, modelling of complex networks. His permanent area of interest is the application of tools and methods of theoretical physics in quantitative description of complex phenomena in economics, social sciences and biology.
Of all directional intermolecular interactions, the hydrogen bond is the most important. Its importance in many systems, from simple chemical to the most complex biochemical multienzime complexes, arouses vital scientific interest for more than 50 years. In recent years in particular, hydrogen-bond research has strongly expanded in depth as well as in breadth, new concepts have been established, and the complexity of the phenomena considered has increased dramatically.
The goal of this project is to introduce students to the basic concepts of the formation and vibrational properties of the intermolecular complexes with weak hydrogen bonds. The systems which will be considered include 1,1'-bi-2-naphthol as an example of proton-donor, and, as a proton-accepting compounds, N,N-dimethylformamide and m-dinitrobenzene in several solvents from polar to nonpolar. From the previously acquired infrared spectra, the formation constants and basic thermodynamic properties will be determined. Also, analysis of the spectra will give a look into the structural details of the complexes. Last but not the least, complexes will be crystalised to obtain monocrystals good enough to carry out x-ray difractional structural analysis.
In such a way, students will be introduced to molecular vibrational spectroscopy, to «mechanical» properties of the molecules and weak intermolecular forces, and also to basic properties of solutions. Methodology of the spectral analysis and experimental techniques will be accompanied with lectures and discussions.
Nikola Biliskov
Rudjer Boskovic Insitute, Zagreb, Croatia
Nikola is a PhD student of chemistry at the Laboratory of Molecular Spectroscopy, Division of Organic Chemistry and Biochemistry, Ruðer Boškoviæ Institute in Zagreb, Croatia. His other interests comprise chemistry of the atmosphere, geochemistry and, particularly, meteor astronomy. He was leader of the meteor groups of the Višnjan School of Astronomy. He participated in expedition that observed Leonid meteor storm in Mongolia in 1998.
The Scanning Tunneling Microscope (STM) has become one of the most useful tools for surface imaging at the atomic level and atomic manipulation.
The goal of the group is to build a simple, fully functional scanning tunneling microscope and image a number of surfaces with it. Through this proces the participants will learn the theoretical background of the STM functioning, the specifics of the mechanical design, the why and the how of the electric circuits and the operational techniques.
The participants will learn skills connected with the building of a scientific instrument like metal craftwork, electronic circuit assembly and function testing. Beside these skills the participants will also learn how to present their work to the scientific community and how to create an Internet webpage.
Ivica Crljenica
Faculty of Science, University of Zagreb, Croatia
Ivica is a second year physics student at the Faculty of Science, University of Zagreb. His fields of interest encompases light pollution, education, instrument building . . .
Light pollution was considered as astronomical issue for many years. There is much evidence that artificial night lights have some influence on night animals. The aim of the project is to compare impact the different types of street lamps have on animals, particularly insects. Impact of street lamps will be measured also through pray-predator relationships.
Even the little children know that the moths are attracted to lamps, but the top leptidopterologists (scientists who are studying butterflies and moths) cannot find universal answer to question WHY? Can we do it?
Zrinka Mesic
Zumberak-Samoborsko gorje Nature Park, Croatia
Zrinka is a guide and environmental educator in Žumberak-Samoborsko gorje Nature Park. She is postgraduate student at the Faculty of Science, University of Zagreb. Her main interest is implementation of GIS technologies in conservation biology.
One of the top challenges in astrophysics today is direct imaging of extra-solar planets. Direct imaging of extra-solar planets is highly desirable because one could separate the light from the star and the planet. However, such imaging is difficult. The most prominent is very wide dynamic range of the light intensities from the stars. To achieve that range participants of this group will try some of new techinics of data reduction on original VLT (Very Large Telescope-ESO) images. With the indirect method (Radial velocity) planet's wobbling around the parent star is measured. This has led to the discovery of about 110 planets in our galaxy. Another goal of this project will be to determine which of those known planets are in or close to place around the star where life could develop - in so-called Habitable zone.
Participants will be expected to learn how to search scientific databases, form the goal of their research, do basic data reduction of astronomical images, make conclusions and present their work to public. The planet hunting season will yield exciting results soon.
Ana Bedalov
Astrophysical Institute and University Observatory, Friedrich-Schiller-University Jena, Germany
Ana is PhD student in astrophysics at Observatory of University of Jena in Germany. She works on extra-solar planet and brown dwarfs search. Her other interests are education and popularization of science. She organised S3 2002 and S3 2003 and now she is leader of educational project Nebo na poklon. Her hobbies are photography, cooking and traveling.
Lectures covered topics from current frontiers of science.
Marko Kralj (Institute for Physical and Theoretical Chemistry, University of Bonn, Germany): Imaging and manipulation on the atomic level with scanning probe techniques
Goran Zgrablic (Swiss Federal Institute of Technology, Lausanne, Switzerland): Taking movies of molecules in action using ultrafast laser spectroscopy
Danijel Dojcinovic (Arizona State University, Tempe, USA): GM food: please don't panic
Dejan Vinkovic (Institute for Advanced Study, Princeton, USA): A prelude to planet formation: what do we know about the environments where planets are born
Ana Bedalov (Astrophysical Institute and University Observatory, Friedrich-Schiller-University Jena, Germany): Planets Hunting Season
Jasminka Cindric (Pliva Research Institute, Zagreb, Croatia): Sciences in drug development (from a molecule to a drug
Workshops covered other topics:
Branimir Lukic (Swiss Federal Institute of Technology, Lausanne, Switzerland): Imaging and manipulation on the atomic level with scanning probe techniques
Marija Lukic (Economics High School, Pozega, Croatia): Team-cooperative learning in the class: Croatian kingdom in the tenth century


Stalin urges Prime Minister Modi to protect Tamils
The DMK president, in a statement, said that the world knew that newly-elected President of Sri Lanka, Gotabaya Rajapaksa, had historically been against Tamils
by Special CorrespondentDMK president M.K. Stalin said Prime Minister Narendra Modi, who had greeted Gotabaya Rajapaksa on his election as the President of Sri Lanka, should take steps to protect the interest of Tamils in the country.
In a statement, he said the world and the United Nations knew that historically Mr. Rajapaksa had been totally against Tamils and a solution had not been found for the consequences of his actions.
“His election with over 50 % of votes has come as a shock to Tamils across the world. He should come out of his enmity and authoritarian attitude and should treat Tamils as citizens with constitutional rights. He should be humane in his approach and only such an attitude will become meaningful in his political life,” Mr. Stalin’s statement said.


--- layout: post title: ACF Nationals 2017- A-Values announced date: 2017-02-22 14:04:35.000000000 -06:00 type: post parent_id: '0' published: true password: '' status: publish categories: [] tags: [] meta: _rest_api_published: '1' _rest_api_client_id: "-1" _publicize_job_id: '2145370891' author: login: acfquizbowl email<EMAIL_ADDRESS>display_name: acfquizbowl first_name: '' last_name: '' permalink: "/2017/02/22/acf-nationals-2017-a-values-announced/" ---
The A-values from 2017 ACF Regionals have been announced. These values will be used to invite teams to the 2017 ACF Nationals Tournament in April 2017. Please refer to the linked page for more details.
Congratulations to all teams who earned a qualification bid!


The Btree data structure is a sorted, balanced tree structure storing associated key/data pairs.
The sort order for the Btree can be specified as part of the db_open call to open the database, specifically by setting the bt_compare element of the DB_INFO structure. If no comparison routine is specified, the sort order is lexical, with shorter keys collating before longer keys.
Sort routines are passed pointers to keys as arguments. The keys are represented as DBT structures. The routine must return an integer less than, equal to, or greater than zero if the first argument is considered to be respectively less than, equal to, or greater than the second argument. The only fields that the routines may examine in the DBT structures are data and size fields.
An example routine that might be used to sort integer keys in the database is as follows:
compare_int(a, b) const DBT *a, *b; { int ai, bi;/* * Returns: * < 0 if a < b * = 0 if a = b * > 0 if a > b */ memcpy(&ai, a->data, sizeof(int)); memcpy(&bi, b->data, sizeof(int)); return (ai - bi); }
Note that the data must first be copied into memory that is appropriately aligned, as Berkeley DB does not guarantee any kind of alignment of the underlying data, including for comparison routines.
When doing integer comparison routines, it is important to remember that databases created on machines of different architectures may have different integer byte orders, for which your code may need to compensate.
An example routine that might be used to sort keys based on the first five bytes of the key (ignoring any subsequent keys) is as follows:
compare_dbt(a, b) const DBT *a, *b; { u_char *p1, *p2;/* * Returns: * < 0 if a < b * = 0 if a = b * > 0 if a > b */ for (p1 = a->data, p2 = b->data, len = 5; len--; ++p1, ++p2) if (*p1 != *p2) return ((long)*p1 - (long)*p2); return (0); }


Topics
Poaching
Africa is home to the world's most iconic wildlife, but illegal poaching might destroy it forever.
Endangered animals are slaughtered so that a single body part - like tusks, pelt, or bones - can be illegally sold for huge sums of money.
The vast majority of poaching is caused by organized crime syndicates that use high-powered technology and weaponry to track and kill many animals at once without being detected.
At current poaching rates, elephants, rhinos, and other iconic African wildlife may be gone within our lifetime.
Our goal is to protect wildlife, conserve land, and educate the public.
For more information go tohttps://campaign.awf.org/poaching-infographic/


The short version
I have it all working. It's kind of magic. But there are issues, and I'm not sure it should even exist, and am looking for input.
The long version
In Auto caching tables I presented with a hack which allows getting cached or fresh results via a simple SELECT queries.
The drive for the above hack was INFORMATION_SCHEMA tables. There are two major problems with INFORMATION_SCHEMA:
- Queries on schema-oriented tables such as TABLES, COLUMNS, STATISTICS, etc. are heavyweight. How heavyweight? Enough to make a lockdown of your database. Enough to crash down your database in some cases.
- The data is always generated on-the-fly, as you request it. Query the COLUMNS table twice, and risk two lockdowns of your database.
The auto-cache mechanism solves issue #2. I have it working, time based. I have an auto-cache table for each of the INFORMATION_SCHEMA heavyweight tables. Say, every 30 minutes the cache is invalidated. Throughout those 30 minutes, you get a free pass!
The auto-cache mechanism also paves the road to solving issue #1: since it works by invoking a stored routine, I have better control of the way I read INFORMATION_SCHEMA. This, I can take advantage of INFORMATION_SCHEMA optimization. It's tedious, but not complicated.
For example, if I wanted to cache the TABLES table, I don't necessarily read the entire TABLES data in one read. Instead, I can iterate the schemata, get a list of table names per schema, then read full row data for these, table by table. The result? Many many more SELECTs, but more optimized, and no one-big-lock-it-all query.
And the problem is...
I have two burning problems.
- INFORMATION_SCHEMA optimization only works that much. It sometimes does not work. In particular, I've noticed that if you have a view which relies on another view (possibly relying on yet another view), things get out of hand. I author a monitoring tool for MySQL called mycheckpoint. It uses some fancy techniques for generating aggregated data, HTML and charts, by means of nested views. There are a few views there I can never query for in COLUMNS. It just crashes down my server. Repeatedly. And it's a good machine with good configuration. Make that 5 machines. They all crash, repeatedly. I just can't trust INFORMATION_SCHEMA!
- Replication: any caching table is bound to replicate. Does it make any sense to replicate cache for internal metadata? Does it make sense to query for the cached table on slave, to have it answer for master's data? With plain old INFORMATION_SCHEMA, every server is on its own. Caching kinda works against this. Or is it fair enough, since we would usually expect master/slaves to reflect same schema structure?
I would feel much better if I could read SHOW statements with a SELECT query. Though I've found this nice hack, it can't work from a stored function, only via stored procedure. So it can't be used from within a SELECT query. I've been banging my head for months now, I think I gave up on this one.
Any insights are welcome!
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We've been using Finagle quite a lot on our current project, so I decided to dig into the Client implementation in order to check if we are properly using it and understand what else it could offer us.
Finagle currently ships with client implementation for protocols such as HTTP, MySql, Redis, Memcached, and is extensible for any protocol implementation. Initializing a HTTP client for example, would be as simple as:
val client = Http.client.newService("example.com:80")
This creates a new client for the host and port specified, and from that it's fairly simple to send requests out and work with responses as follows:
val req = Request("/foo", ("my-query-string", "bar"))
req.host = "example.com"
val resp: Future[Response] = client(req)
There's also another handy method for retrieving page content based on a HTTP url, which currently doesn't support HTTPS.
val resp: Future[Response] = Http.fetchUrl("http://example.com")
But as we all know, the only certainty we have when integrating with external services is that it will fail at some point in time. That will happen for lots of different reasons such as network problems, bugs on the service, unavailability, etc.
It's really important to understand these types of failures and take them into account when defining clients that will act as integration points with external services.
Currently Finagle client implementation comes with support to Timeouts, Retries, Circuit Breakers, Tracing, Rate Limiting, among other features, and it can also be customized by composing with custom Filter
and Service
implementations.
Timeouts
Nowadays pretty much every application needs to integrate with other services through the network. In case of any problem with the service or the network, timeouts are used to tell the client when it's time to give up and keep going, instead of waiting for a response that might never come.
The TimeoutFilter are used to configure global timeouts, that will be applied to every request performed by the client.
def timeoutFilter[Req, Rep](duration: Duration) = {
val timer = DefaultTimer.twitter
new TimeoutFilter[Req, Rep](duration, timer)
}
val clientWithTimeout = timeoutFilter(1.second) andThen client
But it's also possible to specify the timeout criteria on request level, which will take precedence over the global timeout configuration.
client(req) within 1.second
Retries
When a call to a service results on failure, timeout or is successful but returned an undesired result, there's the chance of retrying the request on a hope for a successful and desired result.
The RetryFilter, when hooked into the client stack, acts coordinating the retries of service executions. By default clients will retry any request that doesn't write anything to the output or throws any kind of WriteException
. But the retry behavior can be easily customized and applied to pretty much any situation.
The conditions for whether a retry will happen or not, as well as the total number of retries and the time interval between them are defined on the RetryPolicy class.
val retryCondition: PartialFunction[Try[Nothing], Boolean] = {
case Throw(error) => error match {
case e: TooManyRequestsException => true
case _ => false
}
case _ => false
}
val retryPolicy = RetryPolicy.tries(3, retryCondition)
val retryFilter = new RetryExceptionsFilter[Request, Response](
retryPolicy, timer, statsReceiver)
The code above defines a retry filter, which will retry every request that fails with TooManyrequestsException
, and will do it for at most 3 times, including the first attempt. The .tries
factory method uses jittered back-offs between retries.
Finagle also allows you to specify your own back-off strategy, in case you need more control over the time interval between executions.
val backoffs = Stream(1.second, 4.seconds, 8.seconds)
val retryPolicy = RetryPolicy.backoff(backoffs)(retryCondition)
a note on service retries
As I mentioned earlier, most common causes of service failures involves problems in the network or on the remote system, which won't be resolved right away. So be careful when defining back-off strategies and try not to use immediate retries, as they are likely to fail again for the exactly same reason.
On the other hand, using longer intervals might as well bring undesired results, specially from clients perspective. They will have to wait longer for service responses, risking pushing response time past timeout configuration.
Michael Nygard has an excellent book on the subject where he recommends the queue-and-retry strategy for a slow retry, responding something to the user right away. The goal is to ensure that once the remote service is healthy again the overall system will be able to recover.
Rate Limited Services
Another important aspect to take into account is rate limiting. It has been widely adopted by most API vendors on the market, and is indeed a good practice to place them in front of services, specially those that will be exposed to the outside world. Rate limiting prevents brute force attacks and is also used to control access quotas for different client profiles.
Recently I was working integrating with a service that only allowed my client key to perform 10 requests within a second. So I wanted to find a way to make the Finagle client coordinate the calls to this API, and avoid as much as I could the propagation of any HTTP 429 Too Many Requests
errors to end users.
Looking at Finagle codebase I came across the RequestSemaphoreFilter implementation which uses Twitter's AsyncSemaphore to grant permits and enqueue waiters when no more permits are available. That was roughly what I was looking for, except for the fact that it doesn't take time into account.
Moses Nakamura introduced me to the recently implemented AsyncMeter, which has a similar behavior to the semaphore implementation, but adding time into the game. I could easily configure a new meter which releases 1 new permit every 100 milliseconds (10 per second), and allows at most 1000 waiters to be enqueued, as demonstrated on the snippet below.
val meter = AsyncMeter.newMeter(1, 100.milliseconds, 1000)
There's also the handy .perSecond
method, which simplifies this configuration and makes the code more readable.
val meter = AsyncMeter.perSecond(10, 1000)
From that I decided to make my first contribution to the project and implemented the RequestMeterFilter using the AsyncMeter
. And as the docs states:
A
Filter
that rate limits requests to a fixed rate over time by using theAsyncMeter
implementation. It can be used for slowing down access to throttled resources. Requests that cannot be enqueued to await a permit are failed immediately with aFailure
that signals that the work was never done, so it's safe to re-enqueue.
Hooking the filter to the client definition is just a matter of instantiating it and adding to the stack, as follows.
val requestMeter = new RequestMeterFilter(meter)
val limitedClient = requestMeter andThen client
This filter will execute a new request every 100 milliseconds and will allow 1000 requests to enqueue, waiting for their time to execute. Once the waiting queue reaches the max size, new requests will be dropped immediately.
On the next post I will continue exploring Finagle client features in greater detail, more specifically Circuit Breakers (Failure Accrual and Fail Fast), Monitoring and client Statistics. But the material presented here is enough to start building fault tolerant clients. Have fun!


Comparison of performance: Python NumPy and Numba, MATLAB, and Fortran
September 27, 2017
TL;DR; Python Numba acceleration is really fast.
Like faster than Fortan fast.
Edit September 28, 2017: I’ve updated the benchmark to include runs with gfortran -O2.
Preface
So this post was inspired by a HN comment by CS207 about NumPy performance. The post demonstrates a trick that you can use to increase NumPy’s peformance with integer arrays. Unfortunately the performance gain greatly diminishes when working with double precision floats (though it is still always faster on average). The demo and conversation that follows was interesting, and I got my first taste of Numba (high performance Python acceleration libarary – which has a seamless integration with NumPy).
Introudction
I’m going to benchmark adding big arrays together in NumPy, Numba, MATLAB, and Fortran. It’ll be interesting to see what Numba’s acceleration has to offer since the majoriy of my numerical work is done with NumPy. Many of my colleges still use MATLAB (hopefully my class on Python and this post may convince them to seriously consider Python as an alternative.) Now everyone already knows that Python and MATLAB are slow languages, but NumPy and MATLAB are optimized for array calculations which is what Fortran is all about. And Fortran is fast, so a fair comparison of array operations in Numpy and MATALAB should also consider Fortran.
The Benchmark
The benchmark is going to solve the following equation
where \( X, Y \) are double precision floating point arrays with a lot of elements. I’m going to benchmark this problem for arrays between 1,000,000 and and 1,000,000,000 elements (the most I can fit into my RAM). So essentially I’m going to run functionally equivalent code in Python (either NumPy or NumPy + Numba), MATLAB, and Fortran on two different machines. Machine 1: AMD FX-8370 Eight-Core @ 4.0 GHz with 32 GB DDR3 RAM. Machine 2: ThinkPad 13 i5-6300U with 32 GB DDR4 RAM. I’m not going to touch GPU acceleration in this benchmark, but I think it will be worthwhile to do so sometime.
The benchmark will run \( X = X + 2.0 Y \) 10 times, and return the average run time for 1 dimensional array sizes of 1,000,000, 10,000,000, 100,000,000, and 1,000,000,000 elements. The sample code for one run in each language is provided below.
NumPy code:
NumPy + Numba single threaded code (inspired by jzwinck):
NumPy + Numba parallel code:
MATLAB Code:
Fortran code:
Application versions:
| Program | Version |
|---|---|
| Python | 2.7.13 |
| NumPy | 1.13.1 |
| Numba | 0.35.0 |
| MATLAB | R2015a |
| GNU Fortran | 4.8.5 |
Python folder and execution:
MATLAB folder and execution:
Fortran folder and execution:
Results
On both of my machines a single threaded Numba run was on average faster than compiled Fortran code (without the -O2 optimization level). With the -O2 optimization level it appears the that Fortan is faster than numba single threaded, but by a very narrow margin. Below you’ll see the mean run times in seconds between gfortran -O2 and the single threaded Python Numba.
| CPU | array elements | gfortran -O2 (s) | Python Numba single (s) |
|---|---|---|---|
| AMD FX-8370 | 1,000,000 | 0.00225 | 0.00202 |
| AMD FX-8370 | 10,000,000 | 0.01952 | 0.01946 |
| AMD FX-8370 | 100,000,000 | 0.19258 | 0.18895 |
| AMD FX-8370 | 1,000,000,000 | 1.90781 | 1.91261 |
| i5-6300u | 1,000,000 | 0.00128 | 0.00098 |
| i5-6300u | 10,000,000 | 0.00996 | 0.01041 |
| i5-6300u | 100,000,000 | 0.10023 | 0.10142 |
| i5-6300u | 1,000,000,000 | 0.94956 | 1.03110 |
I wasn’t expecting this – and I’m not sure how this black magic called Numba works… I need to do some more research into what Numba is actually doing with the JIT compilation. The speed ranks from Slowest to Fastest on the AMD-FX870: MATLAB, NumPy, gfortran, Numba single thread, gfortran -O2, Numba parallel. With the i5-6300U there is less discrepancy between MATLAB times and NumPy times (they are basically the same).
I was also surprised to see with the i5-6300u that NumPy and Fortran ran at nearlly the same speed. For the 1,000,000,000 element arrays, the Fortran code (without the O2 flag) was only 3.7% faster than the NumPy code.
The parallel Numba code really shines with the 8-cores of the AMD-FX870, which was about 4 times faster than MATLAB, and 3 times faster than Numpy. However the parallel Numba code was only about two times faster than Numpy with the i5-6300u, but this makes sences since this is only a two core (4 threads) processor.
The figures bellow show the benchmarks results of the average run times on a log-log scale. Another figure shows how much slower the implementation was when compared to the Numba parallel run average.
Discusion about memory usage
You can’t perform this benchmark without mentioning that this Python example is a Memory HOG wen compared to Fortran and MATLAB. Python will peak at 24 GB of RAM to do the math with the 1,000,000,000 element arrays, regardless of if you use Numba or pure NumPy. This is horribly inefficient – since Python is only storing 16 GB of data in RAM after and before the operation. MATLAB and Fortran solve this problem with a peak memory usage of 16 GB of RAM. This is 33% more RAM required to perform the array operation with Python than MATLAB or Fortran. (Peak RAM usage was estimated using GNU time /usr/bin/time -v)
Conclusion
Wow Numba is Fast. I would have never expected to see a Python NumPy Numba array combination as fast as compiled Fortran code. The cost is obviously that it takes time to port your already existing Python NumPy code to Numba. Numba’s parallel acceleration worked really well on this problem, and with the 8 core AMD-FX870 Numba parallel ran 4 times faster than MATLAB code.
Is there anything I missed? I’m looking forward to playing with Numba GPU acceleration in the future. You can take a look at the code I used to run the benchmark here.
It’s worthwhile to note that I did not do this benchmark with ATLAS, and that using ATLAS may seriously speed up the Fortran execution of this problem (and likely speed up the Numpy and Numba execution as well).


Drag a column header and drop it here to group by that column |
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ProductID |
Product name |
Unit price |
Quantity per unit |
Units in stock |
Discontinued |
| 1 2 3 4 5 6 7 8 9 10 ... | 335104 items in 33511 pages |
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1 |
Chai |
$18.00 |
10 boxes x 20 bags |
39 |
|
2 |
Chang |
$19.00 |
24 - 12 oz bottles |
17 |
|
3 |
Aniseed Syrup |
$10.00 |
12 - 550 ml bottles |
13 |
|
4 |
Chef Anton's Cajun Seasoning |
$22.00 |
48 - 6 oz jars |
53 |
|
5 |
Chef Anton's Gumbo Mix |
$21.35 |
36 boxes |
0 |
|
6 |
Grandma's Boysenberry Spread |
$25.00 |
12 - 8 oz chars |
120 |
|
7 |
uncle Bob's Organic Dried Pears |
$30.00 |
12 - 1 lb pkgs. |
15 |
|
8 |
Northwoods Cranberry Sauce |
$40.00 |
12 - 12 oz jars |
6 |
|
9 |
Mishi Kobe Niku |
$97.00 |
18 - 500 g pkgs. |
29 |
|
10 |
Ikura |
$31.00 |
12 - 200 ml jars |
31 |


Last Updated: 12th February 2020
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Sheila Kauffman
Unafffiliated
I have two part time jobs currently. Contractor for Blue Tree Network ( Healthcare Project Management) Sales and Sewing machine repair at The Presserfoot (Bernina Sewing Machine store). My background is primarily IT and I have managed multiple teams that specialized in Data Analytics.
Bachelor of Science in Computer Science/Mathematics Master in Secondary Education / Mathematics
80513
Father served on a Planning Commission, City Council, and eventually served as Mayor in town I grew up in.
None
I have worked as a Manager at both IBM and UCHealth. In both positions I had large teams in multiple locations that had to work together toward common goals. My management style was often described as democratic, since bringing consensus across the team members would insure their buy-in and ultimately achieve success for the team and our projects. I started a Dog Agility Club in Colorado in the late 1990's since there was not a club in Northern Colorado, this in turn created opportunities for dog owners in this part of the state. Later I became an AKC Agility Judge in Colorado and also judged across the country. As an agility judge part of my challenge was to create a fun successful experience for ALL breeds of dogs, which obviously vary widely. Through this experience I became very familiar with most of the fairgrounds across our state and elsewhere. I was the Quilt Show Chair for the Longmont Quilt Guild in 2019. This was our largest event and involved over 100 guild members quilts and experienced our largest attendance over the two days. I have a small flock of sheep and while it is small, I have some understanding of the agricultural community and believe I could represent this minority, at least to some degree.
I believe that more Americans should take an active role in serving our communities. This is often hard for folks working 40 hour/week jobs and taking care of their families. I am currently in a position where I have the time to serve our community and would like to give something back to the state of Colorado which has been a fantastic place to call home for over 20 years. This is an amazing place to live and I would like to help make sure that it is in the future. I believe this opportunity will open my eyes too many things about our government processes and state constitution that I would like to further understand. The bottom line is I want to do something positive to make a difference.
Throughout my lifetime I have displayed impartiality which lead to a career as a successful manager and even judging dog shows. Both of these roles required one to look at all the information presented to come to a consensus or decision. I strongly promote that every voice should be heard and considered. I also understand that all voices may not speak out but still deserve the right to be heard.
My formal education in Computer Science and Mathematics laid a great foundation for ability to apply logic and analyze data and situations. Throughout my career I have exercised these skills to find solutions for teams and organizations. I have created and lead data analytics teams to solve problems with reduced costs continually. For instance, optimizing use of Operating Rooms to save over $1 Billion annually for a healthcare system. Data used properly can definitely be utilized to make improvements. I also understand that not all data is of quality and should not be utilized when making important decisions. Knowing how to check data for accuracy is a asset I believe I would able to bring to this committee should I be chosen.
Female


|
ARDP
2.1.3
Another RDF Document Parser
|
Go to the source code of this file.
Functions | |
| def | DirectoryOfThisScript () |
| def | MakeRelativePathsInFlagsAbsolute (flags, working_directory) |
| def | IsHeaderFile (filename) |
| def | GetCompilationInfoForFile (filename) |
| def | FlagsForFile (filename, kwargs) |
Variables | |
| list | flags |
| string | compilation_database_folder = '' |
| tuple | database = ycm_core.CompilationDatabase( compilation_database_folder ) |
| list | SOURCE_EXTENSIONS = [ '.cpp', '.cxx', '.cc', '.c', '.m', '.mm' ] |
| def DirectoryOfThisScript | ( | ) |
Definition at line 65 of file .ycm_extra_conf.py.
Referenced by FlagsForFile().
| def FlagsForFile | ( | filename, | |
| kwargs | |||
| ) |
Definition at line 121 of file .ycm_extra_conf.py.
References DirectoryOfThisScript(), GetCompilationInfoForFile(), and MakeRelativePathsInFlagsAbsolute().
| def GetCompilationInfoForFile | ( | filename | ) |
Definition at line 103 of file .ycm_extra_conf.py.
References IsHeaderFile().
Referenced by FlagsForFile().
| def IsHeaderFile | ( | filename | ) |
Definition at line 98 of file .ycm_extra_conf.py.
Referenced by GetCompilationInfoForFile().
| def MakeRelativePathsInFlagsAbsolute | ( | flags, | |
| working_directory | |||
| ) |
Definition at line 69 of file .ycm_extra_conf.py.
Referenced by FlagsForFile().
| string compilation_database_folder = '' |
Definition at line 56 of file .ycm_extra_conf.py.
| database = ycm_core.CompilationDatabase( compilation_database_folder ) |
Definition at line 59 of file .ycm_extra_conf.py.
| list flags |
Definition at line 36 of file .ycm_extra_conf.py.
| list SOURCE_EXTENSIONS = [ '.cpp', '.cxx', '.cc', '.c', '.m', '.mm' ] |
Definition at line 63 of file .ycm_extra_conf.py.


SasView Development Workshop 2013
April 3-7, 2013
The SasView development workshop will be held at the NIST Center for Neutron Research from April 3 to 7, 2013. Representative from the institutions currently active on the SasView project will discuss the technical aspect of the SasView Small-angle Scattering Data Analysis program to set the direction of the project. New developers will have the opportunity to be trained by implementing new features during the workshop.
Organizers: Paul Butler (NIST), Andrew Jackson (ESS), Mathieu Doucet (ORNL)
Tentative agenda:
- Tuesday April 2nd
- Workshop preparation by the organizers
- Wednesday April 3rd
- Technical design overview
- Development guideline
- Build servers and code repository
- Thursday April 4th to Friday April 5th
- Coding projects TBD
- Saturday April 6th
- Morning: coding projects (continued)
- Afternoon: long term vision discussion
- Sunday April 7th
- Coding project wrap up
Useful links:
- NCNR site
- Lodging near the NCNR
- Directions to NIST
Brief Report
The workshop brought together 13 developers from around the world and began the process of moving the development responsibilities from the original developers to a broader community while providing outputs which will form a significant fraction of the upgrades to the next release. The participants agreed that such a forum is highly useful not only to bring the development community together but to provide a framework for making significant progress on advancing the project.
Wednesday focused mostly on presentations giving an overview of the project and current design and on a discussion of potential projects. The rest of the meeting evolved into a “code camp” beginning with ensuring complete working installations of development systems on participant laptops. The participants agreed that the next code camp should occur within a year and hosted either in Australia or Europe. Meanwhile the project continues to host biweekly conference call meetings.
Added to the support for polarized beam and magnetic scattering, the upgrades coming out of this code camp will provide a very significant upgrade which will be released as version 3.0. These project include:
- Changed GUI interface from AUI to MDI: complete
- Allow for reading of GRASP .dat data: complete
- provide a log q spacing option when choosing number of points to compute:complete
- addition of a “pringle” shape model: complete except documentation
- Added sum of pixel intensities in a box besides the average intensity: complete
- Provide for a C model plugin interface: on-going
- Complete rewrite of canSAS reader to better take advantage of format and include support for vers. 1.1: on-going
- Fix of category management code: on-going


Electronics Store Manager
Products
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Sale Records
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My Profile
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Logout
My Profile
12
Sale Records
50
Products Sold
200,500
Worth of Goods


The input formmethod Attribute
The formmethod attribute defines the HTTP method for sending form-data to the action URL.
First name:
Last name:


Want to change the fill color and get the code(s)? Click on an SVG below!
Add your color here
SVG ID: (SVG only)
Color:
ViewBox Value: (Defaults to original viewBox as seen above)
Width: (Defaults to 24, only adds to base64)
Height: (Defaults to 24, only adds to base64)
Here's the the updated SVG and it's associated Base64 encode! Enjoy!


It is a well-known fact that behind every good comet is a UFO. These UFOs often come to collect loyal supporters from here on Earth. Unfortunately, they only have room to pick up one group of followers on each trip. They do, however, let the groups know ahead of time which will be picked up for each comet by a clever scheme: they pick a name for the comet which, along with the name of the group, can be used to determine if it is a particular group's turn to go (who do you think names the comets?). The details of the matching scheme are given below; your job is to write a program which takes the names of a group and a comet and then determines whether the group should go with the UFO behind that comet.
Both the name of the group and the name of the comet are converted into a number in the following manner: the final number is just the product of all the letters in the name, where "A" is 1 and "Z" is 26. For instance, the group "USACO" would be 21 * 19 * 1 * 3 * 15 = 17955. If the group's number mod 47 is the same as the comet's number mod 47, then you need to tell the group to get ready! (Remember that "a mod b" is the remainder left over after dividing a by b; 34 mod 10 is 4.)
Write a program which reads in the name of the comet and the name of the group and figures out whether according to the above scheme the names are a match, printing "GO" if they match and "STAY" if not. The names of the groups and the comets will be a string of capital letters with no spaces or punctuation, up to 6 characters long.
Examples:
| Input | Output |
COMETQ HVNGAT | GO |
ABSTAR USACO | STAY |
| Line 1: | An upper case character string of length 1..6 that is the name of the comet. |
| Line 2: | An upper case character string of length 1..6 that is the name of the group. |
NOTE: The input file has a newline at the end of each line but does not have a "return". Sometimes, programmers code for the Windows paradigm of "return" followed by "newline"; don't do that! Use simple input routines like "readln" (for Pascal) and, for C/C++, "fscanf" and "fid>>string".
NOTE 2: Because of the extra characters, be sure to leave enough room for a 'newline' (also notated as '\n') and an end of string character ('\0') if your language uses it (as C and C++ do). This means you need eight characters of room instead of six.
COMETQ HVNGAT
GO
| C | O | M| E | T | Q | | |
| 3 | 15 | 13| 5 | 20 | 17 | | |
| H | V | N| G | A | T | | |
| 8 | 22 | 14| 7 | 1 | 20 | |
3 * 15 * 13 * 5 * 20 * 17 = 994500 mod 47 = 27 8 * 22 * 14 * 7 * 1 * 20 = 344960 mod 47 = 27
Because both products evaluate to 27 (when modded by 47), the mission is 'GO'.


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Spaghetti Sauce
Yields: 6
Preparation time: 15
Cooking time: 300
Ingredients
-
5-6 cans tomato sauce (14-15 oz)2 cans stewed tomatoes (14-15 oz)2 small cans tomato paste (~6 oz)1 large onion, chopped5-6 large cloves of garlic, minced1 Tbsp. (heaping) Basil4 Tbsp. oregano1 Tsp. Rosemary1/2 Tsp. Marjoram1 Tsp. Fennel Seed3 Bay leaves2 Tbsp. Salt3 Tbsp. Sugar1 lb. of ground beefMore salt and pepper to tasteParmesan cheese (optional)Pasta
Directions
-
Put everything in the slow cooker except for the onions, garlic, and meat.Add just enough water to each can to rinse it out and add to the crockpot.Saute onions and garlic in olive oil until clear and add to crockpot.


This is a sample html file representing a larger web site in a real life system.
This page's html file is served from a folder that is shared with the server.


Tissue-specific regulation of the rabbit 15-lipoxygenase gene in erythroid cells by a transcriptional silencer.
Abstract
The 15-lipoxygenase (lox) gene is expressed in a tissue-specific manner, predominantly in erythroid cells but also in airway epithelial cells and eosinophils. We demonstrate in this report that the 5 ' flanking DNA of the 15-lox gene contains sequences which down-regulate its activity in a variety of non-erythroid cell lines but not in two erythroid cell lines. The element has characteristics of a transcriptional 'silencer ' since it functions in both orientations. The main activity of the silencer has been mapped to the first 900 bp of 5 ' flanking DNA, which contains nine binding sites for a nuclear factor present in non- erythroid cells but not in erythroid cells. These binding sites have similar sequences and multiple copies of the binding sites confer tissue-specific down-regulation when attached to a minimal lox promoter fragment. The 5 ' flanking DNA also contains a cluster of three binding sites for the GATA family of transcription factors.


{% extends 'base.html' %} {% load static %} {% block content %}
Use custom button styles for actions in forms, dialogs, and more with support for multiple sizes, states, and more.


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Rong Zhuang
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You can contact me via following ways:
Email<EMAIL_ADDRESS>Cell Phone: (+1)<PHONE_NUMBER>
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Talk to your peers in a perfect secure channel, only people you want can understand your message
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Recall your keywords and date please!


We've put together an amazing lineup of speakers this year. See below for some information about each speaker and the talks they will deliver.
Microservices have become the defecto architecture pattern for building services. However separating business logic into small services that operate with a single logical data set has introduced consistency challenges. Previous attempts to solve this problem like two phase commit have not been widely adopted due to availability and liveness issues.
The defect standard today is developers implementing feral concurrency control mechanism. This technique can be error prone, and often results in “Death Star” architectures which rely on chained calls to enforce application invariants. These architectures become more complicated over time, and are difficult to modify and extend.
In this talk I propose a new solution for this problem, Distributed Sagas, a protocol for coordinating requests among multiple micro services, while ensuring application invariants.
Reality operates on a set of rules. Through replication, Life has evolved to exist inside of these rules. By utilizing mutations, it is possible to evolve a neural network that is capable of operating inside of an artificial environment.
C# is very popular with game developers, and the ways it is used in game development can be very different from "regular" development. On this tour of game development tools, techniques and practices, we'll look at various scripting techniques and approaches used by the industry, from component based programming to data driven design, dynamic programming tools and functional programming approaches to enforce a hard separation between the game engine and the game designers that are making the games.
Well look at how the Unity Editor uses C# to create a dynamic programming environment where you make your game by extending the editor that you're using to build the game, how Naughty Dog made the Uncharted series, and the interesting lessons that can be drawn from how game developers approach programming and how the constraints of games encourage different ways of doing things.
By the end of this talk you should have a better understanding of how games are built, a broader perspective of development techniques and approaches, and a few tricks under your belt in case you're looking to make games.

Coming soon...
Parallel and asynchronous programming has an important place in solving real world problems of efficient processing of constantly growing data and need for lower latencies. Sometimes, regular means of dealing with concurrency are not enough and in this talk we will look at Hopac. Hopac is F# library that makes it easy to write correct, modular and efficient parallel, asynchronous, concurrent and reactive programs. We will see in which cases Hopac is faster and more useful than existing F# solutions for dealing with parallel and asynchronous computations. Looking at the examples, audience will also see why F# is a great choice for parallel programming.
Does your unit, integration, and manual testing scale? Did that nasty bug that you thought you fixed reappear? Do you lack manual testers? UI automation can assist with these challenges as a supplement to your quality process.
Let's look into the reasons why you might want to consider adding UI automation testing with a case study of how the GitHub for Visual Studio Extension does this with Coded UI Tests.
It has never been easier to get a new person writing their first few lines of C#. DotNetCoreKoans is intended to be used as a teaching tool for beginners. The overall goal is to get someone having fun learning and writing C# in just a few minutes. It can be used solo, in a class setting or a coding dojo.
In this session, I will introduce the project along with the confluence of people and events that inspired it. Then I'll cover holes in the existing code base and how to contribute to the project. Finally, after the talk I will facilitate a hacking session to add new koans and features focused on first time OSS contributors.
Stay connected with the community!
Follow us on Twitter at @dotnetfringe
Chat with us in Slack
Join the mailing list!


Editing rasters¶
Setting ‘no data’ values¶
The xarray.DataArray.where()
function masks data by setting nans, as demonstrated by the example below.
import geowombat as gw
from geowombat.data import l8_224078_20200518
# Zeros are replaced with nans
with gw.open(l8_224078_20200518) as src:
data = src.where(src != 0)
Setting ‘no data’ values with scaling¶
In GeoWombat, we use xarray.where()
and xarray.DataArray.where()
along with optional scaling in the set_nodata()
function. In this example, we set zeros as 65535 and scale all other values from a [0,10000] range to [0,1].
import geowombat as gw
from geowombat.data import l8_224078_20200518
# Set the 'no data' value and scale all other values
with gw.open(l8_224078_20200518) as src:
data = src.gw.set_nodata(0, 65535, (0, 1), 'float64', scale_factor=0.0001)
Replace values¶
The GeoWombat replace()
function mimics pandas.DataFrame.replace()
.
import geowombat as gw
from geowombat.data import l8_224078_20200518
# Replace 1 with 10
with gw.open(l8_224078_20200518) as src:
data = src.gw.replace({1: 10})
Note
The replace()
function is typically used with thematic data.


public class ExemptionMechanism extends Object
Applications or applets that use an exemption mechanism may be granted stronger encryption capabilities than those which don't.
| Modifier | Constructor and Description |
|---|---|
protected |
ExemptionMechanism(ExemptionMechanismSpi exmechSpi,
Provider provider,
String mechanism)
Creates a ExemptionMechanism object.
|
| Modifier and Type | Method and Description |
|---|---|
protected void |
finalize()
Ensures that the key stored away by this ExemptionMechanism
object will be wiped out when there are no more references to it.
|
byte[] |
genExemptionBlob()
Generates the exemption mechanism key blob.
|
int |
genExemptionBlob(byte[] output)
Generates the exemption mechanism key blob, and stores the result in
the
output buffer. |
int |
genExemptionBlob(byte[] output,
int outputOffset)
Generates the exemption mechanism key blob, and stores the result in
the
output buffer, starting at outputOffset
inclusive. |
static ExemptionMechanism |
getInstance(String algorithm)
Returns an
ExemptionMechanism object that implements the
specified exemption mechanism algorithm. |
static ExemptionMechanism |
getInstance(String algorithm,
Provider provider)
Returns an
ExemptionMechanism object that implements the
specified exemption mechanism algorithm. |
static ExemptionMechanism |
getInstance(String algorithm,
String provider)
Returns an
ExemptionMechanism object that implements the
specified exemption mechanism algorithm. |
String |
getName()
Returns the exemption mechanism name of this
ExemptionMechanism object. |
int |
getOutputSize(int inputLen)
Returns the length in bytes that an output buffer would need to be in
order to hold the result of the next
genExemptionBlob
operation, given the input length inputLen (in bytes). |
Provider |
getProvider()
Returns the provider of this
ExemptionMechanism object. |
void |
init(Key key)
Initializes this exemption mechanism with a key.
|
void |
init(Key key,
AlgorithmParameters params)
Initializes this exemption mechanism with a key and a set of algorithm
parameters.
|
void |
init(Key key,
AlgorithmParameterSpec params)
Initializes this exemption mechanism with a key and a set of algorithm
parameters.
|
boolean |
isCryptoAllowed(Key key)
Returns whether the result blob has been generated successfully by this
exemption mechanism.
|
protected ExemptionMechanism(ExemptionMechanismSpi exmechSpi, Provider provider, String mechanism)
exmechSpi
- the delegateprovider
- the providermechanism
- the exemption mechanismpublic final String getName()
ExemptionMechanism
object.
This is the same name that was specified in one of the
getInstance
calls that created this
ExemptionMechanism
object.
ExemptionMechanism
object.public static final ExemptionMechanism getInstance(String algorithm) throws NoSuchAlgorithmException
ExemptionMechanism
object that implements the
specified exemption mechanism algorithm.
This method traverses the list of registered security Providers, starting with the most preferred Provider. A new ExemptionMechanism object encapsulating the ExemptionMechanismSpi implementation from the first Provider that supports the specified algorithm is returned.
Note that the list of registered providers may be retrieved via
the Security.getProviders()
method.
algorithm
- the standard name of the requested exemption
mechanism.
See the ExemptionMechanism section in the
Java Cryptography Architecture Standard Algorithm Name Documentation
for information about standard exemption mechanism names.ExemptionMechanism
object.NullPointerException
- if algorithm
is null.NoSuchAlgorithmException
- if no Provider supports an
ExemptionMechanismSpi implementation for the
specified algorithm.Provider
public static final ExemptionMechanism getInstance(String algorithm, String provider) throws NoSuchAlgorithmException, NoSuchProviderException
ExemptionMechanism
object that implements the
specified exemption mechanism algorithm.
A new ExemptionMechanism object encapsulating the ExemptionMechanismSpi implementation from the specified provider is returned. The specified provider must be registered in the security provider list.
Note that the list of registered providers may be retrieved via
the Security.getProviders()
method.
algorithm
- the standard name of the requested exemption mechanism.
See the ExemptionMechanism section in the
Java Cryptography Architecture Standard Algorithm Name Documentation
for information about standard exemption mechanism names.provider
- the name of the provider.ExemptionMechanism
object.NullPointerException
- if algorithm
is null.NoSuchAlgorithmException
- if an ExemptionMechanismSpi
implementation for the specified algorithm is not
available from the specified provider.NoSuchProviderException
- if the specified provider is not
registered in the security provider list.IllegalArgumentException
- if the provider
is null or empty.Provider
public static final ExemptionMechanism getInstance(String algorithm, Provider provider) throws NoSuchAlgorithmException
ExemptionMechanism
object that implements the
specified exemption mechanism algorithm.
A new ExemptionMechanism object encapsulating the ExemptionMechanismSpi implementation from the specified Provider object is returned. Note that the specified Provider object does not have to be registered in the provider list.
algorithm
- the standard name of the requested exemption mechanism.
See the ExemptionMechanism section in the
Java Cryptography Architecture Standard Algorithm Name Documentation
for information about standard exemption mechanism names.provider
- the provider.ExemptionMechanism
object.NullPointerException
- if algorithm
is null.NoSuchAlgorithmException
- if an ExemptionMechanismSpi
implementation for the specified algorithm is not available
from the specified Provider object.IllegalArgumentException
- if the provider
is null.Provider
public final Provider getProvider()
ExemptionMechanism
object.ExemptionMechanism
object.public final boolean isCryptoAllowed(Key key) throws ExemptionMechanismException
The method also makes sure that the key passed in is the same as the one this exemption mechanism used in initializing and generating phases.
key
- the key the crypto is going to use.key
is null.ExemptionMechanismException
- if problem(s) encountered
while determining whether the result blob has been generated successfully
by this exemption mechanism object.public final int getOutputSize(int inputLen) throws IllegalStateException
genExemptionBlob
operation, given the input length inputLen
(in bytes).
The actual output length of the next
genExemptionBlob
call may be smaller than the length returned by this method.
inputLen
- the input length (in bytes)IllegalStateException
- if this exemption mechanism is in a
wrong state (e.g., has not yet been initialized)public final void init(Key key) throws InvalidKeyException, ExemptionMechanismException
If this exemption mechanism requires any algorithm parameters
that cannot be derived from the given key
, the
underlying exemption mechanism implementation is supposed to
generate the required parameters itself (using provider-specific
default values); in the case that algorithm parameters must be
specified by the caller, an InvalidKeyException
is raised.
key
- the key for this exemption mechanismInvalidKeyException
- if the given key is inappropriate for
this exemption mechanism.ExemptionMechanismException
- if problem(s) encountered in the
process of initializing.public final void init(Key key, AlgorithmParameterSpec params) throws InvalidKeyException, InvalidAlgorithmParameterException, ExemptionMechanismException
If this exemption mechanism requires any algorithm parameters
and params
is null, the underlying exemption
mechanism implementation is supposed to generate the required
parameters itself (using provider-specific default values); in the case
that algorithm parameters must be specified by the caller, an
InvalidAlgorithmParameterException
is raised.
key
- the key for this exemption mechanismparams
- the algorithm parametersInvalidKeyException
- if the given key is inappropriate for
this exemption mechanism.InvalidAlgorithmParameterException
- if the given algorithm
parameters are inappropriate for this exemption mechanism.ExemptionMechanismException
- if problem(s) encountered in the
process of initializing.public final void init(Key key, AlgorithmParameters params) throws InvalidKeyException, InvalidAlgorithmParameterException, ExemptionMechanismException
If this exemption mechanism requires any algorithm parameters
and params
is null, the underlying exemption mechanism
implementation is supposed to generate the required parameters itself
(using provider-specific default values); in the case that algorithm
parameters must be specified by the caller, an
InvalidAlgorithmParameterException
is raised.
key
- the key for this exemption mechanismparams
- the algorithm parametersInvalidKeyException
- if the given key is inappropriate for
this exemption mechanism.InvalidAlgorithmParameterException
- if the given algorithm
parameters are inappropriate for this exemption mechanism.ExemptionMechanismException
- if problem(s) encountered in the
process of initializing.public final byte[] genExemptionBlob() throws IllegalStateException, ExemptionMechanismException
IllegalStateException
- if this exemption mechanism is in
a wrong state (e.g., has not been initialized).ExemptionMechanismException
- if problem(s) encountered in the
process of generating.public final int genExemptionBlob(byte[] output) throws IllegalStateException, ShortBufferException, ExemptionMechanismException
output
buffer.
If the output
buffer is too small to hold the result,
a ShortBufferException
is thrown. In this case, repeat this
call with a larger output buffer. Use
getOutputSize
to determine how big
the output buffer should be.
output
- the buffer for the resultoutput
IllegalStateException
- if this exemption mechanism is in
a wrong state (e.g., has not been initialized).ShortBufferException
- if the given output buffer is too small
to hold the result.ExemptionMechanismException
- if problem(s) encountered in the
process of generating.public final int genExemptionBlob(byte[] output, int outputOffset) throws IllegalStateException, ShortBufferException, ExemptionMechanismException
output
buffer, starting at outputOffset
inclusive.
If the output
buffer is too small to hold the result,
a ShortBufferException
is thrown. In this case, repeat this
call with a larger output buffer. Use
getOutputSize
to determine how big
the output buffer should be.
output
- the buffer for the resultoutputOffset
- the offset in output
where the result
is storedoutput
IllegalStateException
- if this exemption mechanism is in
a wrong state (e.g., has not been initialized).ShortBufferException
- if the given output buffer is too small
to hold the result.ExemptionMechanismException
- if problem(s) encountered in the
process of generating.protected void finalize()
finalize
in class Object
WeakReference
,
PhantomReference
Submit a bug or feature
For further API reference and developer documentation, see Java SE Documentation. That documentation contains more detailed, developer-targeted descriptions, with conceptual overviews, definitions of terms, workarounds, and working code examples.
Copyright © 1993, 2015, Oracle and/or its affiliates. All rights reserved.


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Service is available 24*7 as per the customer requirements. All types of insurances are available with premium process. Claim process is very easy. You can get your money back within 48 hours.
Service is available 24*7 as per the customer requirements. All types of insurances are available with premium process. Claim process is very easy. You can get your money back within 48 hours.
Service is available 24*7 as per the customer requirements. All types of insurances are available with premium process. Claim process is very easy. You can get your money back within 48 hours.
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This is a game that will test your memory.
An image will be shown to the right for 5 seconds. Pay close attention. Read and answer a question related to the image within 10 seconds. Got it?
Press play to start.


This user guide explains how to simulate isotropic and fast-motion cw EPR spectra using EasySpin's function garlic. It is assumed that you are familiar with the basics of MATLAB, esp. with structures.
It contains the following topics:Solution cw EPR spectra of radicals are computed by the EasySpin function garlic.
garlic(Sys,Exp)
It is called with two arguments. The first argument Sys
tells garlic
all about the
spin system, and the second argument Exp
gives the experimental
parameters.
If no output argument is given, garlic
plots the computed spectrum. But it can also return one or two outputs. (Don't forget the semicolon at the end of the line to suppress
output to the command window.)
Spec = garlic(Sys,Exp); [Field,Spec] = garlic(Sys,Exp);
The outputs Field
and Spec
are
arrays that contain the values of th magnetic field axis and the spectrum, respectively.
If these are requested, garlic
does not plot the spectrum.
Doing a simulation only requires a few lines of code. A simple example is
Sys = struct('g',2,'Nucs','1H','n',2,'A',15,'lwpp',[0 0.05]); Exp = struct('mwFreq',9.5); garlic(Sys,Exp);
The first two lines define the spin system (a radical with an unpaired electron spin and two equivalent 1H) and the experimental parameters (X band spectrometer frequency). The details will be explained below. The third line calls the simulation function, which plots the result. Copy and paste the code above to your MATLAB command window to see the graph.
Of course, the names of the input and output variables don't have
to be Sys
, Exp
, Field
and Spec
.
You can give them any name you like, as long as it is a valid MATLAB
variable name, e.g., FremySaltSolution
or QbandExperiment
.
For convenience, thoughout this tutorial, we will use the short names Sys
and Exp
.
The first input argument specifies the spin system. It is a MATLAB structure with various fields giving values for the spin system parameters.
Sys.g = 2.006; Sys.Nucs = '1H'; Sys.A = 15; % MHz Sys.n = 2; Sys.lwpp = 0.05; % mT
The first line defines the isotropic g value of the spin system, in this
case 2.006. garlic
always assumes a single unpaired electron spin S=1/2.
The field Sys.Nucs
contains a character array giving all the
magnetic nuclei in the spin system, a proton in the above example.
Use a comma-separated list of isotope labels to give more than one
nucleus. E.g., Sys.Nucs = '1H,1H,14N'
specifies two
different protons and one nitrogen.
Sys.A
gives the hyperfine coupling in MHz (Megahertz),
for each of the nuclei listed in Sys.Nucs
. The following
defines a hydrogen atom with a 10 MHz coupling to the unpaired electron and
a 13C atom with a 12 MHz coupling.
Sys.Nucs = '1H,13C'; Sys.A = [10 12]; % MHz
Remember that garlic
(and other EasySpin functions, too),
take the hyperfine coupling values to be in MHz.
Often, values for hyperfine couplings are given in G (Gauss) or mT
(Milltesla), so you have to convert these values.
For g = 2.00232, 1 G corresponds to 2.8025 MHz, and 1 mT corresponds to 28.025 MHz.
The simplest way to convert coupling constants from magnetic field units to MHz is to use the EasySpin
function mt2mhz:
A_MHz = mt2mhz(A_mT); % mT -> MHz conversion A_MHz = mt2mhz(A_G/10); % G -> MHz conversion (1 G = 0.1 mT)
Sys.n
gives the number of equivalent nuclei. So
Sys.Nucs = '1H'; Sys.n = 1; Sys.A = 5.3;
indicates a single proton, whereas
Sys.Nucs = '1H'; Sys.n = 2; Sys.A = 5.3;
specifies two equivalent protons, i.e. protons with identical hyperfine coupling constants. The statements
Sys.Nucs = '1H,1H'; Sys.n = [4 4]; Sys.A = [-14 -5];
specify two groups of protons with 4 equivalent nuclei in each (as in a naphthalene radical anion or cation).
Sys.lwpp
gives the peak-to-peak line widths. It is described in detail below in the
section about line broadenings.
The second input argument, Exp
, collects all experimental settings. Just as the spin system, Exp
is a structure containing several fields.
Microwave frequency. To simulate an EPR spectrum, Easyspin needs at a minimum the spectrometer frequency. Put it into Exp.mwFreq
, in units of GHz.
Exp.mwFreq = 9.385; % X-band Exp.mwFreq = 34.9; % Q-band
Field range. There are two ways to enter the magnetic field sweep range. Either give the center field and the sweep width (in mT) in Exp.CenterSweep
, or specify the lower and upper limit of the sweep range (again in mT) in Exp.Range
.
Exp.CenterSweep = [340 80]; % in mT Exp.Range = [300 380]; % in mT
On many cw EPR spectrometers, the field range is specified using center field and sweep width, so Exp.CenterSweep
is often the more natural choice.
Exp.CenterSweep
and Exp.Range
are only optional. If both are omitted, EasySpin tries to determine a field range large enough to accomodate the full spectrum. This automatic ranging works for most common systems, but fails in some complicated situations. EasySpin will issue an error when it fails.
Points. By default, pepper
computes a 1024-point spectrum. However, you can change the number of points to a different value using
Exp.nPoints = 5001;
You can set any value, unlike some EPR spectrometers, where often only powers of 2 are available (1024, 2048, 4096, 8192).
Harmonic. By default, EasySpin computes the first-harmonic absorption spectrum, i.e. the first derivative of the absorption spectrum. By changing Exp.Harmonic
, you can request the absorption spectrum directly or the second-harmonic (second derivative) of it.
Exp.Harmonic = 0; % absorption spectrum, direct detection Exp.Harmonic = 1; % first harmonic (default) Exp.Harmonic = 2; % second harmonic
Modulation amplitude. If you want to include effects of field modulation like overmodulation, use Exp.ModAmp
Exp.ModAmp = 0.2; % 0.2 mT (2 G) modulation amplitude, peak-to-peak
Time constant. To include the effect of the time constant, apply the function rcfilt to the simulated spectrum.
For more advanced spectral simulations, EasySpin offers more possibilities in the experimental parameter structure Exp
.
Mode. Most cw EPR resonators operate in perpendicular mode, i.e., the oscillating magnetic field component of the microwave in the resonator is perpendicular to the static field. Some resonators can operate in parallel mode, where the microwave field is parallel to the static one. EasySpin can simulate both types of spectra:
Exp.Mode = 'perpendicular'; % perpendicular mode (default) Exp.Mode = 'parallel'; % parallel mode
Temperature. The polarizing effects of low sample temperatures can also be included in the simulation by specifying the temperature:
Exp.Temperature = 4.2; % temperature in kelvin
With this setting, EasySpin will include the relevant polarization factors resulting from a thermal equilibrium population of the energy levels. For S=1/2 systems, it is not necessary to include the temperature. However, it is important in high-spin systems with large zero-field splittings, and in coupled spin systems with exchange couplings.
Microwave phase. Occasionally, the EPR absorption signal has a small admixture of the dispersion signal. This happens for example when the microwave phase in the reference arm is not absolutely correctly adjusted. EasySpin can mix dispersion with absorption if a Lorentzian broadening is given:
Sys.lwpp = [0.2 0.01]; % Lorentzian broadening (2nd number) required Exp.mwPhase = 0; % pure absorption Exp.mwPhase = pi/2; % pure dispersion Exp.mwPhase = 3*pi/180; % 3 degrees dispersion admixed to absorption
Lines in an isotropic cw EPR spectrum are not infinitely narrow,
the have a certain linewidth. This linewidth
can be supplied to garlic
in the lwpp
or the lw
field of the spin system structure, in mT.
Sys.lw = [0 0.05]; % Gaussian and Lorentzian FWHM (full width at half height), mTThis defines the FWHM of the absorption Gaussian (first number) and Lorentzian (second number) broadening of the lines in the spectrum. Note that these are NOT the peak-to-peak line widths in first-harmonic spectra. To specify the peak-to-peak width, use the field
Sys.lwpp
.
Sys.lwpp = [0 0.03]; % Gaussian and Lorentzian peak-to-peak line width, mT
If you give both a Gaussian and a Lorentzian broadening, both will be used, yielding a so-called Voigtian line shape, e.g.
Sys.lw = [0.05 0.01]; % mT
For ways to model line widths when the anisotropies of the magnetic interactions don't average out completely, see below.
Often, an EPR spectrum shows a mixture of spin species. To simulate these spectra, each of the component spectra has to be simulated and added with the appropriate weight (depending on spin concentration) to the total spectrum.
This can be done all in one go with garlic
. Just provide the component spin systems
with their weights as a cell list (in curly braces) to garlic
. For example, here
is the simulation of a very simple two-component mixture with 2:1 ratio of spin concentrations.
Sys1.g = 2; Sys1.lwpp = 1; Sys1.weight = 2; Sys2.g = 2.1; Sys2.lwpp = 0.8; Sys2.weight = 1; Exp.mwFreq = 9.5; Exp.Range = [300 360]; garlic({Sys1,Sys2},Exp);
You don't have to specify Sys.weight
- if it's absent it is assumed to be 1. These
weights are absolute, i.e. a simulation with Sys.weight=20
yields a spectrum that
is 10 times more intense than the one obtained with Sys.weight=2
. There is no limit
to the number of components in a simulation.
If the tumbling of paramagnetic molecules in solution is fast compared to the EPR time scale, but not orders of magnitude faster, dynamic effects appear in the spectrum: Different lines will have different line widths, all of them broader than in the isotropic spectrum. This is the so-called fast-motional regime.
If the tumbling is assumed isotropic and governed by Brownian movement, the only parameter necessary to characterize the speed of tumbling is the rotational correlation time. It can be given in the spin system structure, directly in units of seconds
Sys.tcorr = 1e-10; % rotational correlation time, in seconds.
or alternatively as the base-10 logarithm of the same value
Sys.logtcorr = -10; % corresponds to 1e-10 seconds
The origin of the line broadenings lies in the anisotropy of the magnetic interactions, so
garlic
has to be supplied with full g and A tensor information. This includes the principal values and the orientation of the tensors.
Sys.g = [2.005 2.003 2.007]; Sys.Nucs = '14N'; Sys.A = [17 17 84];
Sys.g
contains the three principal values of the g tensor. Sys.A
contains the three principal values of the hyperfine tensor. If more than one nucleus is present, one 3-element row per nucleus has to be given. E.g.
Sys.Nucs = '14N,1H'; % two nuclei Sys.A = [17 17 84; 5 5 2]; % 2x3 array
The orientations of the tensors relative to the molecular frame are defined in terms of Euler angles in 3-element array (see the function erot).
Sys.gFrame = [0 0 0]; % Euler angles for g tensor Sys.AFrame = [0 pi/4 0]; % Euler angles for A tensor
All-zero values can of course be omitted.
Remember that for fast-motion simulations of systems with more than one nucleus, Sys.n
cannot be used. Equivalent nuclei have to be specified one at a time.
garlic doesn't compute the fast-motion linewidths: It calls fastmotion. After the spectrum with the fast-motion linewidths is constucted, garlic
convolutes it using the Lorentzian (and possibly Gaussian) FWHM from Sys.lw
. This way, residual broadenings are easily included.
In conclusion, an illustrative example of a nitroxide radical in the fast-motion regime
A = mt2mhz([5.8 5.8 30.8]/10); Sys = struct('g',[2.0088 2.0061 2.0027],'Nucs','14N','A',A); Sys.logtcorr = -9; % corresponds to 1e-9 s = 1 ns Exp = struct('mwFreq',9.5); garlic(Sys,Exp);
garlic
, like the other cw EPR simulation functions pepper
and chili
, does field sweeps by default. However, you can use it to
simulate frequency-swept spectra as well.
For this, all you need to do is the following
Exp.Field
. Make sure you do not set Exp.mwFreq
,
otherwise EasySpin does not know what to do.
Exp.Range
or Exp.CenterSweep
. You can also omit these, in which case pepper
will determine an adequate range automatically.
Sys.lw
or Sys.lwpp
, make sure they are in MHz units. For a frequency sweep, these convolutional linewidth parameters are understood to be in MHz (and not in mT, as they are for field sweeps).
Here is an example of a frequency-swept spectrum of an organic radical, with automatic frequency range determination:
clear Sys.g = 2.005; Sys.Nucs = '1H,1H,1H,14N'; Sys.A = [6 5 2 1.7]; Sys.n = [2 2 2 1]; Sys.lwpp = 0.1; % peak-to-peak linewidth, in MHz Exp.Field = 340; % static field, in mT garlic(Sys,Exp);
By default, garlic
returns the absorption spectrum (Exp.Harmonic=0
) when you simulate a frequency-swept spectrum. To get the first or second derivative, change Exp.Harmonic
to 1 or 2. Note however that Exp.ModAmp
is not supported for frequency sweeps.
All other capabilities of garlic
apply equally to frequency sweep and to field sweeps. For example, you can simulate multi-component spectra, and you can simulate spectra in the fast-motion regime.


P.S. I know this Home page is about as interesting as the Japanese flag but trust me, it gets better.


In this chart, each chart label is styled independently. View source to see how it works.
This version of the chart uses the default styles:


Node's http.createServer() on the browser
const server = http.createServer(function(req, res) { ... });
server.listen();
This activates the push states. Then you can add HTML like the following.
A Sample Link
Go to Foo Bar
A Sample Form
That's it!
-
The request is an extended version of the native
window.Request.
-
The response is an extended version of the native
window.Response.
- This means you can fetch a request as in
fetch(req)
to get info from the server.


- Troubleshooting -
The following are possible issues that may occur while playing the game.
If you run across problems not listed here, feel free to contact the author via email or on Studio Pixel's message board.
(Translator's note: Studio Pixel is not responsible for errors and problems related to the AGTP English translation patch.
If you have problems related to the translation, kindly email the AGTP
at<EMAIL_ADDRESS>or post a message on the Pantheon at
http://agtp.romhack.net/.)
* I get an error message saying, "Cannot read generic file."
(Translator's note: Error messages may appear in Japanese.)
- Try redownloading the game.
The files may have been corrupted.
- Try using a different uncompression program.
Some uncompression software may alter the directory structure so that the program is unable to find certain files.
* The game runs extremely slowly.
- Try changing the screen mode in DoConfig.exe.
There shouldn't be any problems if your computer is fast enough,
but the most appropriate screen mode can vary depending on the computer.
(Full-screen is recommended.)
- Try changing the "color quality" in your Display Properties.
Depending on your computer, the number of colors displayed can significantly affect the game speed.
24-bit or 32-bit color is recommended.
- Try adjusting your DirectX settings.
You can adjust DirectX settings using the diagnostic tool "dxdiag.exe".
Select "Run..." from the Start Menu and enter "dxdiag".
For detailed instructions on how to use the tool, consult the program's "Help" function.
- Try adjusting your hardware acceleration.
You can change the settings of your hardware acceleration
by opening Display Properties -> Settings -> Advanced and selecting the "Troubleshoot" or "Performance" tag.
- Try updating your drivers.
Some problems may be resolved if you update your graphics drivers.
* The background music cuts off.
- Try adjusting your audio hardware acceleration.
You may be able to fix this problem by adjusting the hardware acceleration for your sound card.
Open Control Panel -> Sounds and Audio Devices -> Audio -> Advanced -> Performance.
* When I press two keys on the keyboard at once, only one registers.
- Change the keys in DoConfig.exe.
Some keyboards fail to register the down-arrow key if "Z" and the right-arrow key are pressed.
If this is the case, please play using the "< > /" setting.
* When playing with a gamepad, the main character moves in directions that aren't being pressed.
- Please restart the game without any buttons on the gamepad being pressed.
If you start the game while holding a directional button,
the game will have problems recognizing directional input after that.
* Saving doesn't work.
- Save data is stored in the file "Profile.dat", created in the same directory as Doukutsu.exe.
If this file cannot be written to, saving will not be possible.
Check that "Profile.dat" is not set to "Read-only" and that the game is not being run from a read-only drive.
* Running in 256-color mode
- This game was created assuming an operating environment with 16-bit color or higher.
Playing with only 256 colors will result in abrupt color shifts and missing portions of some pictures, among other problems.
I have no plans to correct this.
* The "error" file
If certain errors cause the game to quit, a file labeled "error" will sometimes be created in the same directory
as the executable (Doukutsu.exe). This file can be deleted safely.


1. Go to Settings -> General -> Network Settings -> Advanced Settings -> DNS Settings
2. Choose Manual
3. Change your primary DNS to **<IP_ADDRESS>**. You do not need to change your secondary DNS.
4. Go to servers and join the server titled "CubeCraft Games". Once the Gray table pops up, select "Add Server".
5. Type the following in for the server IP and Port:
IP: capmc.mine.bz
Port: 19132
6. Move the switch to the right and add the server to the list to save yourself from typing in the server IP each time. (Note: This will be added to the server list where you clicked “Add Server,” not the nmain server list)
If you're playing on the Beta, follow these instructions after having done steps 1-3.
4. Download Xbox Insider via Microsoft Store (Its free)
5. Visit the Microsoft Page and log in
6. Change your age to 18 (Xbox won’t let you access the app unless you do this).
For help with steps 4-6, see this video here.
7. Open the Xbox Insider app and go to Insider Content -> Minecraft -> Manage -> Leave
8. Uninstall Minecraft.
9. Reinstall Minecraft.
10. Go to servers and join the server titled "CubeCraft Games". Once the Gray table pops up, select "Add Server".
11. Type the following in for the server IP and Port:
IP: capmc.mine.bz
Port: 19132
12. Move the switch to the right and add the server to the list to save yourself from typing in the server IP each time. (Note: This will be added to the server list where you clicked “Add Server,” not the main server list)


# 32022-10-15T17:19:37+03:00
|
Lower Bound |
Estimate |
Upper Bound |
| Value: |
1.11µs |
1.11µs |
1.11µs |
| Throughput: |
1.12GiB/s |
1.12GiB/s |
1.12GiB/s |
| Change in Value: |
-5.0787% |
-3.9867% |
-2.9745% |
| Change in Throughput: |
+5.3505% |
+4.1523% |
+3.0657% |
No change in performance detected.
# 22022-10-15T16:53:50+03:00
|
Lower Bound |
Estimate |
Upper Bound |
| Value: |
1.14µs |
1.16µs |
1.18µs |
| Throughput: |
1.09GiB/s |
1.08GiB/s |
1.06GiB/s |
| Change in Value: |
+2.3651% |
+3.5322% |
+4.7005% |
| Change in Throughput: |
-2.3105% |
-3.4117% |
-4.4895% |
No change in performance detected.
# 12022-10-08T17:30:36+03:00
|
Lower Bound |
Estimate |
Upper Bound |
| Value: |
1.11µs |
1.11µs |
1.11µs |
| Throughput: |
1.12GiB/s |
1.12GiB/s |
1.12GiB/s |
| Change in Value: |
-4.9783% |
-2.5543% |
-0.6875% |
| Change in Throughput: |
+5.2391% |
+2.6212% |
+0.6922% |
No change in performance detected.
# 02022-10-08T17:11:20+03:00
|
Lower Bound |
Estimate |
Upper Bound |
| Value: |
1.12µs |
1.12µs |
1.14µs |
| Throughput: |
1.12GiB/s |
1.11GiB/s |
1.10GiB/s |


Qualifications
Current qualifications
One Year of Masters Degree Computer Science - Software Engineering Option
To : l'ISTIC - University of Rennes 1
Achieved qualifications :
Bachelors Degree Computer Science - With honors - Rank 23/86
Obtained in : May 2013
To : l'ISTIC - University of Rennes 1
Associate Degree business computing : App developer Option
Obtained in : June 2012
To : High School de la Salle - Rennes
Bachelor level M.R.I.M.
Obtained in : June 2010
To : High School Coëtlogon - Rennes
School-leaving diploma electronic
Obtained in : June 2008
To : High School La Providance - Saint Malo


---
layout: post
title: Italicise your unread firefox tabs and other bits
tags: []
status: publish
type: post
published: true
meta: {}
---
Stumbled across this neat little entry (courtesy of a blog entry on javablogs.com), which allows you to modify the userChrome.css file to have your unread tabs italicised (and/or colour). Simple and effective. The details can be found here. The easiest way is to grab a copy of the ChromEdit extension and edit the userChrome.css file. Scroll to the end of the file and paste in the following code to italicise unread tabs:
[code]
/* Italicise the title of unread tabs */
#content tab {
font-style: italic !important;
}
/* Normalise the title of selected tab */
#content tab[selected="true"] {
font-style: normal !important;
}
/* Normalise the title of read unselected tabs */
#content tab[selected="false"] {
font-style: normal !important;
}[/code]
Note you'll need to re-start FireFox once to load the ChromEdit extension and another time to have the style sheet take effect.
And over at DevNulled there is a good post on how to speed up FireFox. Be warned though: it really does increase the load of the server you are trying to connect to, which strictly speaking isn't very polite.