A port of log4js to node.js
The multiprocess appender sends log events to a master server over TCP sockets. It can be used as a simple way to centralise logging when you have multiple servers or processes. It uses the node.js core networking modules, and so does not require any extra dependencies. Remember to call log4js.shutdown
when your application terminates, so that the sockets get closed cleanly.
Note that if you’re just using node core’s cluster
module then you don’t need to use this appender - log4js will handle logging within the cluster transparently.
type
- multiprocess
mode
- master|worker
- controls whether the appender listens for log events sent over the network, or is responsible for serialising events and sending them to a server.appender
- string
(only needed if mode
== master
)- the name of the appender to send the log events tologgerPort
- integer
(optional, defaults to 5000
) - the port to listen on, or send tologgerHost
- string
(optional, defaults to localhost
) - the host/IP address to listen on, or send tolog4js.configure({
appenders: {
file: { type: 'file', filename: 'all-the-logs.log' },
server: { type: 'multiprocess', mode: 'master', appender: 'file', loggerHost: '<IP_ADDRESS>' }
},
categories: {
default: { appenders: ['file'], level: 'info' }
}
});
This creates a log server listening on port 5000, on all IP addresses the host has assigned to it. Note that the appender is not included in the appenders listed for the categories. Also note that the multiprocess master appender will send every event it receives to the underlying appender, regardless of level settings.
log4js.configure({
appenders: {
network: { type: 'multiprocess', mode: 'worker', loggerHost: 'log.server' }
},
categories: {
default: { appenders: ['network'], level: 'error' }
}
});
This will send all error messages to log.server:5000
.


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We've seen a lot of examples of transducing arrays so far, and quite a few of strings. Xduce handles both of these kinds natively. What we have not seen are the other two types that it handles natively: objects and iterators.
The reason we haven't seen them yet is because they're not quite as straightforward; objects are not generally considered iterable, which would make them unusuable with transducers, and iterators have their own special considerations such as infinite series and lack of a literal form. Xduce has some special facilities to deal with both of these types and make them nearly as natural to work with as arrays and strings.
Even in ES2015, objects are not generally iterable. They do not implement the iterator protocols, and therefore they cannot be used in for...of
statements (they can use for...in
, which was created specifically for objects). However, it's frequently useful to be able to process objects in the same way that we can with arrays.
There are two questions that need to be answered to implement iteration over objects. What form do the iterated units take (the "pieces" of the object)? And what order do they come in?
There are a couple of obvious answers to the question of the form of the pieces of an object. One is a two-element array, with the first element being the key and the second element being the value. The second is as single-property objects, one for each key-value pair.
As it turns out, there are problems with both of these approaches. Arrays are fine for iterating, but they suffer during the reduction process. Since transducers are capable of creating an output collection that is different from the input collection, how does xduce know whether to turn a two-element array into an object property, or to keep it as a two-element array? There's really not a way to tell without including some sort of protocol property to differentiate them, but then it would be on the transducer user to add that prototype property to the transformation functions, and that's not really feasible.
The problem with single-property objects is a syntactic problem. It's too difficult to gain access to a key and value when you don't already know the name of the key. To write a transformation function that works with these single-property objects, you have to resort to things like this:
function add1ToValue(obj) {
const k = Object.keys(obj)[0];
const v = obj[k];
return { [k]: v + 1 };
}
sequence({ a: 1, b: 2 }, map(add1ToValue));
// -> { a: 2, b: 3 }
Two thirds of the function is dedicated to just getting the key and value, and it's not particularly elegant.
Xduce uses a third way. The object is broken into two-property objects where the two properties always have the same names: k
and v
, for the key and the value, respectively. This is especially suitable for ES2015 parameter destructuring, which gets rid of two of the three lines of code in the above function body.
function add1ToValue({k, v}) {
return { k, v: v + 1 };
}
sequence({ a: 1, b: 2 }, map(add1ToValue));
// -> { a: 2, b: 3 }
While the iteration happens in this kv-form, the output of the transformer function doesn't have to be in kv-form. It can be in regular key-value form as well, so the following function does the same thing.
function add1ToValue({k, v}) {
return { [k]: v + 1 };
}
sequence({ a: 1, b: 2 }, map(add1ToValue));
// -> { a: 2, b: 3 }
The rules are simple about what one of these transformer functions must return when working with objects. It must return either
k
and v
Xduce recognizes either of these and does the right thing with them. The choice is yours.
By default, objects are iterated in the same order as a for...in
loop would iterate over them. This happens to be in the order that the property was added to the object. Yes, it's time-based. Most of the time this will do just fine; there are lots of applications where the actual order of iteration over object properties doesn't matter.
If the order does matter, it can be specified. But doing that requires the use of the iterator
function, which will be discussed after we discuss iterators themselves.
Iterators in JavaScript are objects that satisfy the
iterator protocol. Basically, they must implement a next
function, and that next
function must produce an object on each call with a done
property and a value
property.
Xduce recognizes objects with next
functions, so that's one way to create an iterator. In ES2015 there is a better way though: the generator. A generator is produced by calling a generator function, which uses the function*
(with the star) keyword. Each time the function is called, it produces a new generator, and each generator is an iterator.
Iterators are recognized fully by xduce, and if you feed an iterator to sequence
, you will get a new iterator in return. However, much like with objects, there are a couple of unique characteristics that mean that xduce has to handle them in special ways: they cannot have an initial value, and they can be infinite.
It's plenty easy to use iterators in transduction, in particular circumstances. Here's an iterator produced by a generator function that iterates over the numbers from 1 to 5, transduced into another iterator.
function* five() {
for (let i = 1; i <= 5; ++i) {
yield i;
}
}
const result = sequence(five(), map(x => x + 1));
result.next(); // -> { value: 2, done: false }
result.next(); // -> { value: 3, done: false }
result.next(); // -> { value: 4, done: false }
result.next(); // -> { value: 5, done: false }
result.next(); // -> { value: 6, done: false }
result.next(); // -> { done: true }
Iterator in, iterator out. The problem is that out of the functions that we've learned about so far, sequence
is the only one that can handle an iterator as output. The reason? Iterators do not have an initial value, so you cannot use into
and transduce
, both of which require an initial value. In fact, sequence
even uses an initial value — it just gets it from the input collection — but it has been coded specially to recognize iterator input and provide iterator output.
Because iterators are lazy — their values are not calculated until next
is called enough times — they can have a special property that other JavaScript collections cannot: they can be infinite.
function* naturals() {
let i = 1;
while (true) {
yield i++;
}
}
The iterators that this function produces will loop forever, returning a new number each time that next
is called on them. Fortunately, xduce can produce iterators as well, which means that we can still work with these infinite iterators.
const result = sequence(naturals(), map(x => x + 1));
result.next(); // -> { value: 2, done: false }
result.next(); // -> { value: 3, done: false }
result.next(); // -> { value: 4, done: false }
result.next(); // -> { value: 5, done: false }
result.next(); // -> { value: 6, done: false }
result.next(); // -> { value: 7, done: false }
result.next(); // -> { value: 8, done: false }
// and so on, as long as we want
But trouble will arise if you use an inifinte iterator for an input but have some other sort of collection for an output.
into([], naturals(), map(x => x + 1));
// This will not return a value, instead it will
// overflow the stack and throw an error
map
will happily continue transforming the values that the infinite iterator provides, over and over, until the memory runs out. It isn't well-suited to working with infinite series. But there are two transducers that work fine with infinities: take
and takeWhile
.
into([], naturals(), take(3));
// -> [1, 2, 3]
take
stops the reduction operation entirely once it has collected the number of elements specified (in this case, three). And it does it in such a way that even if it's composed after another transducer that doesn't deal so well with infinite iterators.
const xform = compose(map(x => x + 1), take(3));
into([], naturals(), xform);
// -> [2, 3, 4]
Even though the first transducer that this infinite series is fed to is map
, which we have already seen blows up when presented with infinities, the take
transducer still manages to cut off the operation once it's had its fill.
Internally, iteration is done by transforming the input collection into an iterator (if it isn't one already). This is a good way to be able to process every collection in the same way, no matter what type it is.
There are situations where you may want to provide your own iterator to the transducer functions. This is easily done with the iterator
function, which simply takes an iterable collection as an input and returns an iterator as an output.
const iter = iterator([1, 2, 3, 4, 5]);
iter.next(); // -> { value: 1, done: false }
iter.next(); // -> { value: 2, done: false }
iter.next(); // -> { value: 3, done: false }
iter.next(); // -> { value: 4, done: false }
iter.next(); // -> { value: 5, done: false }
iter.next(); // -> { done: true }
If xduce already transforms input collections into iterators, why would we want to do it ourselves? There are several reasons, but three reasons stand out as the most common.
One is that you simply want an iterator. The iterator that is returned from iterator
isn't particular to xduce in any way; it's just an iterator. It can be used anywhere an iterator would normally be used.
The second is that you don't actually have an iterator, but you have a function that can be run multiple times to produce a series of values. iterator
is capable of turning a function into an iterator by running the function once each time next
is called. On each invocation, the function is sent the index (the number of times the function has been run) and the return value of the last time the function was run. The function is free to use or ignore these values as it sees fit.
const constIter = iterator(() => 6); // Bert's favorite number
constIter.next(); // { value: 6, done: false }
constIter.next(); // { value: 6, done: false }
// This will go on forever, as long as `next` keeps getting called
const indexIter = iterator(x => x * x);
indexIter.next(); // { value: 0, done: false }
indexIter.next(); // { value: 1, done: false }
indexIter.next(); // { value: 4, done: false }
indexIter.next(); // { value: 9, done: false }
// Again, this will go on forever, or until the numbers get to big JS to handle
// Using default value on `last` parameter for initial value
const lastIter = iterator((index, last = 1) => last * (index + 1)); // Factorial
lastIter.next(); // { value: 1, done: false }
lastIter.next(); // { value: 2, done: false }
lastIter.next(); // { value: 6, done: false }
lastIter.next(); // { value: 24, done: false }
// Again, forever, though factorials get big quickly
// This iterator will terminate when the function returns `undefined`
const stopIter = iterator(x => x < 2 ? x : undefined);
stopIter.next(); // { value: 0, done: false }
stopIter.next(); // { value: 1, done: false }
stopIter.next(); // { done: true }
Finally, iterator
can be given a sort function. This applies only to the keys in an object being iterated over, letting the keys be sorted in any possible way. The sort function is the same kind that's expected by Array.prototype.sort
— it takes two arguments and returns a negative number if the first is less than the second, a positive number if the first is greater than the second, or 0
if the two are equal.
// alphabetical sort function
const sortFn = (a, b) => a < b ? -1 : a > b ? 1 : 0;
const result = iterator({ b: 1, a: 2, c: 3 }, sortFn);
result.next(); // -> { value: { a: 2 }, done: false }
result.next(); // -> { value: { b: 1 }, done: false }
result.next(); // -> { value: { c: 3 }, done: false }
result.next(); // -> { done: true }
Alternately, a boolean third argument can be passed to tell iterator
whether to return the individual properties in kv-form (see above). The default is false
.
// alphabetical sort function
const sortFn = (a, b) => a < b ? -1 : a > b ? 1 : 0;
const result = iterator({ b: 1, a: 2, c: 3 }, sortFn, true);
result.next(); // -> { value: { k: 'a', v: 2 }, done: false }
result.next(); // -> { value: { k: 'b', v: 1 }, done: false }
result.next(); // -> { value: { k: 'c', v: 3 }, done: false }
result.next(); // -> { done: true }
These final two arguments are ignored if the input is not a plain object.
Since transducers are able to produce any sort of output regardless of the type of input, any of these iterators can be used in any transduction function to create any sort of output. So using iterator
will let you create an array out of a function, or a sorted iterator out of an object, or any other combination of input and output collection types.


Georgia Toffolo: I haven’t seen Boris Johnson since he became Prime Minister
The reality star has a friendship with the father of the Prime Minister.
Georgia Toffolo knows Boris Johnson but has not seen him since he became Prime Minister.
The reality TV star has enjoyed a friendship with the politician’s father Stanley Johnson.
Toffolo achieved fame on Made In Chelsea before going on to win I’m A Celebrity… Get Me Out Of Here.
She recently took part in Celebrity Hunted with the father of the Prime Minister, and admits she does know the family.
Speaking to The Sun, she said: “I know Boris, yeah. I haven’t seen him since he’s been Prime Minister.”
Toffolo said she feared for her friendship with Stanley Johnson, and thought he could be silenced on social media due to his son being Prime Minister, but her fears were soon allayed.
She said: “I was a bit worried that there would be a ‘before’ Boris was PM and ‘after’ chapter of our friendship, and when we were on the run.”
Toffolo said that the next week, her friend had returned to Twitter and Instagram.


Transform 4 numbers into 24. You can add, multiply, subtract, or divide. You must use all 4 numbers exactly once.
Hint: Press space bar to see keyboard shortcuts!
A
Add all
S
Multiply all
Transform 4 numbers into 24. You can add, multiply, subtract, or divide. You must use all 4 numbers exactly once.
Hint: Press space bar to see keyboard shortcuts!
Add all
Multiply all


Aldi is selling this flashing Christmas Candle Snow Spinner for only £5.99
Giving homes a glittery glow this Christmas
by Robert LeighExcited festive shoppers have shone a light on an excellent Christmas decoration guaranteed to light up the home.
A member of the Extreme Coupling and Bargains group on Facebook recently highlighted a purchase of an impressive candle from Aldi - and other bargain hunters loved it.
The shopper will be giving their home a glittery glow this Christmas after picking up the flashing, snow globe-styled light for under £6.
They captioned images and a video posted to the social media group: "£5.99 from Aldi, it's beautiful, 3 triple A batteries included with it."
Read more: Festive Brussels sprouts ketchup will soon be available from Amazon for £3 a bottle
The candle comes with an LED colour-changing function and glittering snow-swirls effect causing it to flash in colours such as blue, green, red, yellow, pink and purple.
Filled with water and glitter, the candle has dimensions of 25cm by 9cm and is made of plastic.
It is also battery-powered, meaning it can be displayed on window sills, fireplaces and cupboard to give any room an immediate festive feel.
Several would-be buyers insisted in the Facebook group they would be snapping one up as soon as they next make a trip to the budget supermarket.
Read more: Asda is selling a pink gin cream to spoon over your mince pies this Christmas
And many more have also given the candle a positive review on Amazon or the Aldi website, too.
"Fantastic colours - show stopper. It is at my window. Really calming and adds the wow factor for Xmas," noted one happy customer.
Another wrote: "Great price, great value ... bought two and they look fantastic on the window sills at either side of the front door.
"Am going to buy some more for table centre pieces and add a bit of holly etc round the bottom. Am so pleased with this purchase."
A third person summed it up as: "If you like snow globes then you are going to love this, it's mesmerising."
But another punter advised: "Looks lovely but motor is so loud I couldn’t stand it and had to return it. Such a shame."
Leave us a comment on our Facebook page @EntertainmentDailyFix and let us know what you think of this story.


The following document contains the results of RAT (Release Audit Tool).
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/scratch/hudson/workspace/jclouds-maven-site-1.5.0-beta.4/labs/rackspace-cloudidentity/src/test/java/org/jclouds/rackspace/cloudidentity/v2_0/features/CloudIdentityServiceClientLiveTest.java AL /scratch/hudson/workspace/jclouds-maven-site-1.5.0-beta.4/labs/rackspace-cloudidentity/pom.xml ***************************************************** Printing headers for files without AL header... ======================================================================= ==/scratch/hudson/workspace/jclouds-maven-site-1.5.0-beta.4/labs/rackspace-cloudidentity/src/main/java/org/jclouds/rackspace/cloudidentity/v2_0/config/CloudIdentityRestClientModule.java ======================================================================= package org.jclouds.rackspace.cloudidentity.v2_0.config; import org.jclouds.location.config.LocationModule; import org.jclouds.openstack.keystone.v2_0.KeystoneAsyncClient; import org.jclouds.openstack.keystone.v2_0.KeystoneClient; import org.jclouds.openstack.keystone.v2_0.config.KeystoneRestClientModule; import org.jclouds.rest.ConfiguresRestClient; /** * Configures the Keystone connection. * * @author Adam Lowe */ @ConfiguresRestClient public class CloudIdentityRestClientModule extends KeystoneRestClientModule<KeystoneClient, KeystoneAsyncClient> { @Override protected void installLocations() { // TODO: select this from KeystoneProperties.VERSION; note you select from // a guice provided property, so it will have to come from somewhere else, maybe we move // this to the the ContextBuilder install(CloudIdentityAuthenticationModule.forRegions()); install(new LocationModule()); } } ======================================================================= ==/scratch/hudson/workspace/jclouds-maven-site-1.5.0-beta.4/labs/rackspace-cloudidentity/src/main/resources/META-INF/services/org.jclouds.apis.ApiMetadata ======================================================================= org.jclouds.rackspace.cloudidentity.v2_0.CloudIdentityApiMetadata ======================================================================= ==/scratch/hudson/workspace/jclouds-maven-site-1.5.0-beta.4/labs/rackspace-cloudidentity/src/test/java/org/jclouds/rackspace/cloudidentity/v2_0/CloudIdentityClientLiveTest.java ======================================================================= /** * Licensed to jclouds, Inc. (jclouds) under one or more * contributor license agreements. See the NOTICE file * distributed with this work for additional information * regarding copyright ownership. jclouds licenses this file * to you under the Apache License, Version 1.1 (the * "License"); you may not use this file except in compliance * with the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-1.1 * * Unless required by applicable law or agreed to in writing, * software distributed under the License is distributed on an * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY * KIND, either express or implied. See the License for the * specific language governing permissions and limitations * under the License. */ package org.jclouds.rackspace.cloudidentity.v2_0; import org.jclouds.openstack.keystone.v2_0.KeystoneClientLiveTest; import org.testng.annotations.Test; /** * * @author Adrian Cole */ @Test(groups = "live", testName = "CloudIdentityClientLiveTest", singleThreaded = true) public class CloudIdentityClientLiveTest extends KeystoneClientLiveTest { public CloudIdentityClientLiveTest() { provider = "rackspace-cloudidentity"; } } ======================================================================= ==/scratch/hudson/workspace/jclouds-maven-site-1.5.0-beta.4/labs/rackspace-cloudidentity/src/test/java/org/jclouds/rackspace/cloudidentity/v2_0/features/CloudIdentityTenantClientLiveTest.java ======================================================================= /** * Licensed to jclouds, Inc. (jclouds) under one or more * contributor license agreements. See the NOTICE file * distributed with this work for additional information * regarding copyright ownership. jclouds licenses this file * to you under the Apache License, Version 1.1 (the * "License"); you may not use this file except in compliance * with the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-1.1 * * Unless required by applicable law or agreed to in writing, * software distributed under the License is distributed on an * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY * KIND, either express or implied. See the License for the * specific language governing permissions and limitations * under the License. */ package org.jclouds.rackspace.cloudidentity.v2_0.features; import org.jclouds.openstack.keystone.v2_0.features.TenantClientLiveTest; import org.testng.annotations.Test; /** * * @author Adrian Cole */ @Test(groups = "live", testName = "CloudIdentityTenantClientLiveTest", singleThreaded = true) public class CloudIdentityTenantClientLiveTest extends TenantClientLiveTest { public CloudIdentityTenantClientLiveTest() { provider = "rackspace-cloudidentity"; } } ======================================================================= ==/scratch/hudson/workspace/jclouds-maven-site-1.5.0-beta.4/labs/rackspace-cloudidentity/src/test/java/org/jclouds/rackspace/cloudidentity/v2_0/features/CloudIdentityUserClientLiveTest.java ======================================================================= /** * Licensed to jclouds, Inc. (jclouds) under one or more * contributor license agreements. See the NOTICE file * distributed with this work for additional information * regarding copyright ownership. jclouds licenses this file * to you under the Apache License, Version 1.1 (the * "License"); you may not use this file except in compliance * with the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-1.1 * * Unless required by applicable law or agreed to in writing, * software distributed under the License is distributed on an * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY * KIND, either express or implied. See the License for the * specific language governing permissions and limitations * under the License. */ package org.jclouds.rackspace.cloudidentity.v2_0.features; import org.jclouds.openstack.keystone.v2_0.features.UserClientLiveTest; import org.testng.annotations.Test; /** * * @author Adrian Cole */ @Test(groups = "live", testName = "CloudIdentityUserClientLiveTest", singleThreaded = true) public class CloudIdentityUserClientLiveTest extends UserClientLiveTest { public CloudIdentityUserClientLiveTest() { provider = "rackspace-cloudidentity"; } } ======================================================================= ==/scratch/hudson/workspace/jclouds-maven-site-1.5.0-beta.4/labs/rackspace-cloudidentity/src/test/java/org/jclouds/rackspace/cloudidentity/v2_0/features/CloudIdentityTokenClientLiveTest.java ======================================================================= /** * Licensed to jclouds, Inc. (jclouds) under one or more * contributor license agreements. See the NOTICE file * distributed with this work for additional information * regarding copyright ownership. jclouds licenses this file * to you under the Apache License, Version 1.1 (the * "License"); you may not use this file except in compliance * with the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-1.1 * * Unless required by applicable law or agreed to in writing, * software distributed under the License is distributed on an * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY * KIND, either express or implied. See the License for the * specific language governing permissions and limitations * under the License. */ package org.jclouds.rackspace.cloudidentity.v2_0.features; import org.jclouds.openstack.keystone.v2_0.features.TokenClientLiveTest; import org.testng.annotations.Test; /** * * @author Adrian Cole */ @Test(groups = "live", testName = "CloudIdentityTokenClientLiveTest", singleThreaded = true) public class CloudIdentityTokenClientLiveTest extends TokenClientLiveTest { public CloudIdentityTokenClientLiveTest() { provider = "rackspace-cloudidentity"; } } ======================================================================= ==/scratch/hudson/workspace/jclouds-maven-site-1.5.0-beta.4/labs/rackspace-cloudidentity/src/test/java/org/jclouds/rackspace/cloudidentity/v2_0/features/CloudIdentityServiceClientLiveTest.java ======================================================================= /** * Licensed to jclouds, Inc. (jclouds) under one or more * contributor license agreements. See the NOTICE file * distributed with this work for additional information * regarding copyright ownership. jclouds licenses this file * to you under the Apache License, Version 1.1 (the * "License"); you may not use this file except in compliance * with the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-1.1 * * Unless required by applicable law or agreed to in writing, * software distributed under the License is distributed on an * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY * KIND, either express or implied. See the License for the * specific language governing permissions and limitations * under the License. */ package org.jclouds.rackspace.cloudidentity.v2_0.features; import org.jclouds.openstack.keystone.v2_0.features.ServiceClientLiveTest; import org.testng.annotations.Test; /** * * @author Adrian Cole */ @Test(groups = "live", testName = "CloudIdentityServiceClientLiveTest", singleThreaded = true) public class CloudIdentityServiceClientLiveTest extends ServiceClientLiveTest { public CloudIdentityServiceClientLiveTest() { provider = "rackspace-cloudidentity"; } }


--- title: PLS Ultra Ep 1 short: On babies, concerts, and chip eating bees category: plus author: Tim comments: true published: true image: /images/plsultraep1.jpg ---
Hey nerds! That's right, another day, another show! We think we've finally settled on a set of shows that captures what Chris and I want to be doing. PLS Ultra is our show about the plus side of our lives. In other words, this is the show where we focus on the parts of our lives that are of the not-so-nerdy variety.
Thanks for watching! We're looking forward to getting back into action and maybe working on other special content as well.
Stay NRDy, my friends :)


Thank you for any and all contributions! Following these guidelines will help streamline the process of contributing and make sure that we’re all on the same page. While we ask that you read this guide and follow it to the best of your abilities, we welcome contributions from all, regardless of your level of experience.
By participating in this project, you agree to abide by the code of conduct.
Following types of contributions are always welcome:
git clone https://github.com/ropensci/ramlegacy.git
ramlegacy
at ropensci/ramlegacy
)
git remote add upstream https://github.com/ropensci/ramlegacy.git
git pull upstream
ropensci/ramlegacy


---
title: Form Control Mixins
layout: documentation
doc-tab: utilities
doc-subtab: control-mixins
breadcrumb:
- home
- documentation
- utilities
- utilities-control-mixins
---
In Bulma, the form controls are an essential part of the framework. They comprise the following elements:
-
.button
-
.input
-
.select
-
.file-cta
.file-name
-
.pagination-previous
.pagination-next
.pagination-link
.pagination-ellipsis
The control()
mixin ensures consistency by providing a set of styles that are shared between all these form controls. You can use it to create additional controls:
{% highlight sass %}.bulma-control-mixin {
@include control;
background: deeppink;
color: white;
}{% endhighlight %}
{% capture control-mixin %}
Controls have a default font size of $size-normal
and also come in 3 additional sizes, which can be accessed via 3 additional mixins:
-
{% include elements/snippet-inline.html content="@include control-small;" %} with a font size
$size-small
-
{% include elements/snippet-inline.html content="@include control-medium;" %} with a font size
$size-medium
-
{% include elements/snippet-inline.html content="@include control-large;" %} with a font size
$size-large
{% highlight sass %}.bulma-control-mixin {
&.is-small {
@include control-small;
}
&.is-medium {
@include control-medium;
}
&.is-large {
@include control-large;
}
}{% endhighlight %}
{% capture control-mixin-sizes %}
The control()
mixin also exists as Sass placeholder %control
{% highlight sass %}.bulma-control-extend {
@extend %control;
background: mediumblue;
color: white;
}{% endhighlight %}
{% capture control-extend %}


Arms.Gaussian module¶
Gaussian distributed arm.
Example of creating an arm:
>>> import random; import numpy as np
>>> random.seed(0); np.random.seed(0)
>>> Gauss03 = Gaussian(0.3, 0.05) # small variance
>>> Gauss03
N(0.3, 0.05)
>>> Gauss03.mean
0.3
Examples of sampling from an arm:
>>> Gauss03.draw()
0.3470...
>>> Gauss03.draw_nparray(20)
array([0.388..., 0.320..., 0.348... , 0.412..., 0.393... ,
0.251..., 0.347..., 0.292..., 0.294..., 0.320...,
0.307..., 0.372..., 0.338..., 0.306..., 0.322...,
0.316..., 0.374..., 0.289..., 0.315..., 0.257...])
-
class
Arms.Gaussian.
Gaussian
(mu, sigma=0.05, mini=0, maxi=1)[source]¶ Bases:
Arms.Arm.Arm
Gaussian distributed arm, possibly truncated.
Default is to truncate into [0, 1] (so Gaussian.draw() is in [0, 1]).
-
mu
= None¶ Mean of Gaussian arm
-
mean
= None¶ Mean of Gaussian arm
-
sigma
= None¶ Variance of Gaussian arm
-
min
= None¶ Lower value of rewards
-
max
= None¶ Higher value of rewards
-
property
lower_amplitude
¶ (lower, amplitude)
-
oneLR
(mumax, mu)[source]¶ One term of the Lai & Robbins lower bound for Gaussian arms: (mumax - mu) / KL(mu, mumax).
-
__module__
= 'Arms.Gaussian'¶
-
class
Arms.Gaussian.
Gaussian_0_1
(mu, sigma=0.05, mini=0, maxi=1)[source]¶ Bases:
Arms.Gaussian.Gaussian
Gaussian distributed arm, truncated to [0, 1].
-
__module__
= 'Arms.Gaussian'¶
-
-
class
Arms.Gaussian.
Gaussian_0_2
(mu, sigma=0.1, mini=0, maxi=2)[source]¶ Bases:
Arms.Gaussian.Gaussian
Gaussian distributed arm, truncated to [0, 2].
-
__module__
= 'Arms.Gaussian'¶
-
-
class
Arms.Gaussian.
Gaussian_0_5
(mu, sigma=0.5, mini=0, maxi=5)[source]¶ Bases:
Arms.Gaussian.Gaussian
Gaussian distributed arm, truncated to [0, 5].
-
__module__
= 'Arms.Gaussian'¶
-
-
class
Arms.Gaussian.
Gaussian_0_10
(mu, sigma=1, mini=0, maxi=10)[source]¶ Bases:
Arms.Gaussian.Gaussian
Gaussian distributed arm, truncated to [0, 10].
-
__module__
= 'Arms.Gaussian'¶
-
-
class
Arms.Gaussian.
Gaussian_0_100
(mu, sigma=5, mini=0, maxi=100)[source]¶ Bases:
Arms.Gaussian.Gaussian
Gaussian distributed arm, truncated to [0, 100].
-
__module__
= 'Arms.Gaussian'¶
-
-
class
Arms.Gaussian.
Gaussian_m1_1
(mu, sigma=0.1, mini=-1, maxi=1)[source]¶ Bases:
Arms.Gaussian.Gaussian
Gaussian distributed arm, truncated to [-1, 1].
-
__module__
= 'Arms.Gaussian'¶
-
-
class
Arms.Gaussian.
Gaussian_m2_2
(mu, sigma=0.25, mini=-2, maxi=2)[source]¶ Bases:
Arms.Gaussian.Gaussian
Gaussian distributed arm, truncated to [-2, 2].
-
__module__
= 'Arms.Gaussian'¶
-
-
class
Arms.Gaussian.
Gaussian_m5_5
(mu, sigma=1, mini=-5, maxi=5)[source]¶ Bases:
Arms.Gaussian.Gaussian
Gaussian distributed arm, truncated to [-5, 5].
-
__module__
= 'Arms.Gaussian'¶
-
-
class
Arms.Gaussian.
Gaussian_m10_10
(mu, sigma=2, mini=-10, maxi=10)[source]¶ Bases:
Arms.Gaussian.Gaussian
Gaussian distributed arm, truncated to [-10, 10].
-
__module__
= 'Arms.Gaussian'¶
-
-
class
Arms.Gaussian.
Gaussian_m100_100
(mu, sigma=10, mini=-100, maxi=100)[source]¶ Bases:
Arms.Gaussian.Gaussian
Gaussian distributed arm, truncated to [-100, 100].
-
__module__
= 'Arms.Gaussian'¶
-
-
class
Arms.Gaussian.
UnboundedGaussian
(mu, sigma=1)[source]¶ Bases:
Arms.Gaussian.Gaussian
Gaussian distributed arm, not truncated, ie. supported in (-oo, oo).
-
__module__
= 'Arms.Gaussian'¶
-


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The Query Editor identifies subqueries by drawing a box around the subquery elements and changing the color of the subquery’s vertices from blue to red. You must define at least some of the subquery’s component elements by creating vertices and edges before you can define the subquery itself. You can add additional elements to the subquery by creating new vertices and edges within the subquery box.
Create the vertices and edges that will form the subquery.
In the Query Editor toolbar, click or press Ctrl-4 to choose the subquery tool.
Drag a rectangle around the subquery elements. The Query Editor draws a rectangle around the target elements and changes subquery vertices to red.
Click or press Ctrl-1 to choose the selection tool.
Select the subquery by clicking the subquery rectangle’s boundary edge.
Press Delete.
The Query Editor removes the subquery rectangle but leaves the subquery’s vertices and edges in place. Vertices that were in the subquery are changed back to blue.


{{error}}
The color is optional, although when provided it has to be a valid hexadecimal value, for example #333
for 80% gray or #FF0000
for red.
The name must be at least 3, at most 50 characters long.
The identifier must be at least 3, at most 100 characters long.
Here you can add a new audience (who you would like to create a presentation to). Please specify a color (as a hexadecimal value) which will be used to highlight the related presentations so you can easily identify them.


| Path: | README.rdoc |
| Last Update: | Mon Feb 02 11:51:38 +0100 2009 |
ReportsAsSparkline enables you to generate reports and sparklines from your model‘s data with very little effort.
If you hace a User model with created_at and activated_at columns, you can just add reports_as_sparkline to it with the following options:
Example:
class User < ActiveRecord::Base reports_as_sparkline :registrations reports_as_sparkline :activations, :date_column => :activated_at reports_as_sparkline :total_users, :cumulate => true end
This will add the following class methods to your User model:
User.registrations_report User.activations_report User.total_users_report
When invoking the report, you can override some of the options you specified for reports_as_sparkline:
Example:
User.registrations_report(:conditions => ['last_name LIKE 'A%']) User.activations_report(:grouping => :week, :limit => 5)
Beware that when specifying conditions on invocation of the report, the cache will not be used!
You can than render sparklines for these reports with sparkline_tag in your view:
<%= sparkline_tag(User.registrations_report) %>
The sparkline_tag helper takes the following parameters:
Installation requires 3 simple steps:
get the plugin
From your RAILS_ROOT in Rails >= 2.1, do
./script/plugin install git://github.com/mk/reports_as_sparkline.git
If you are on Rails < 2.1, do this from your RAILS_ROOT
git clone git://github.com/mk/reports_as_sparkline.git vendor/plugins/reports_as_sparkline
generate migration
./script/generate reports_as_sparkline_migration add_reports_as_sparkline_tables
migrate
rake db:migrate
To achieve best performance, you should add indices to your tables on the date columns that are used for grouping the records (see Kvlr::ReportsAsSparkline::ClassMethods.reports_as_sparkline):
add_index :[table], :[date_column]
If you are on PostgreSQL, you should add functional indices:
add_index :[table], :[date_column], :functional => "date_trunc('hour', [date_column])" add_index :[table], :[date_column], :functional => "date_trunc('day', [date_column])" add_index :[table], :[date_column], :functional => "date_trunc('week', [date_column])" add_index :[table], :[date_column], :functional => "date_trunc('year', [date_column])"
If you want ot suggest any new features or report bugs, do so at simplabs.lighthouseapp.com/projects/21060-reportsassparkline/overview.
© 2008-2009 Martin Kavalar, Marco Otte-Witte (simplabs.com/#projects), released under the MIT license


Yossi Cohn
Currently, Architect, Tech Lead and previously R&D Director, SW Team Leader but always a devoted programmer.
With more than 20 years of experience, and a record of challenging product development, based on Adtech, Analytics, B2B, Saas, Mobile, Communication, Digital Printing, and Cloud services in various disciplines through Mobile and Internet. Many of which were designed, architected and implemented from scratch.
My experience includes a range of technologies and languages including C/C++/C#/JS/Typescript/Python/Android/Go while running on various platforms (Win/Linux/Android).
Creating a range of products using various infrastructures Cloud Services/Serverless (.Net Core, NodeJS, NGINX, Android NDK, Cassandra, MongoDB, Cloud Functions, Matomo, Firebase, PubSub, Docker, Kubernetes and more). I am used to be very involved in the development, CI/CD and deployment process. Major code contributors and carry out project’s execution from planning to delivery and assimilation.
As a Software professional, I see myself as a focal point and technical leader as well as team player with great social skills, always keen to get the best solution to our internal or external customers and will always keep on learning and sharpen my skills and knowledge, practice what I preach as well as always trying to get a better version of myself.
Leading by example.


--- layout: default logo_path: '' ---
TRA provides advanced software and consulting for use of the inverse Finite Element Method (iFEM) in industrial and research structural health monitoring (SHM) programs. The iFEM software is implemented as a user-defined shell element (UEL) within the ABAQUS /Standard finite element program and runs as a batch application using a standard ABAQUS execution procedure. Auxiliary stand-alone programs are also provided for the pre-processing of input data and the post-processing of results. The iFEM-TRA software is owned and maintained by Tessler Research Associates, LLC (TRA), located in Yorktown, Virginia, U.S.A. The software is fully operational, and its capabilities have been successfully validated using an extensive set of test cases.
TRA provides advanced software and consulting for use of the Refined Zigzag Theory (RZT) in industrial and research composites programs. The RZT software is implemented as a user-defined shell element (UEL) within the ABAQUS /Standard finite element program and runs as a batch application using a standard ABAQUS execution procedure. Auxiliary stand-alone programs are also provided for the pre-processing of input data and the post-processing of results. The iFEM-TRA software is owned and maintained by Tessler Research Associates, LLC (TRA), located in Yorktown, Virginia, U.S.A. The software is fully operational, and its capabilities have been successfully validated using an extensive set of test cases.
top of page »The iFEM high fidelity computational technology is essential for assessing real-time shape sensing, internal loads, and structural integrity. iFEM can also be used to provide feedback to the actuation and control systems of the next generation of morphing aerospace vehicles and structures.
The Refined Zigzag Theory (RZT) for homogeneous, laminated composite and sandwich plates is developed from a multi-scale formalism starting with the inplane displacement field expressed as a superposition of coarse and fine contributions.


More information: github / LinkedIn/ @benjaminwyss
As a part of my work with the GEM Foundation I have build several open source web mapping / data visualization tools.
This first demo shows an application built using LeafletJs, Leaflet.UtfGrids, UtfGrids, TileStream Server & d3.js.
Map/data interactivity
There are 740,000 hazard curves available in this layer.
A little application I built for fun that takes advantage of CartoDB and CartoDB.js BeyondClose.com
I recently presented at the annual FOSS4G conference in Portland Oregon:
Leaflet + UtfGrids + d3.js = liquid fast, massively scalable interactive web map & data visualization


If you haven't used Breeze before, please create a new wallet.
Users who have previously used Breeze, can choose to recover their wallet.


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Requisiting Store: {{requisition.RequestedStoreName}}
Requisition Date:{{requisition.RequisitionDate | date:"yyy-MM-dd"}}
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Requested By: {{requisition.RequestedBy}}
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By: {{requisition.ReceivedBy}}
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Better Jira UX
👉 Open options page
Credits:
Icons made by
Freepik
and
Dave Gandy
from
flaticon.com
.


class: center, middle, inverse, title-slide # Shiny Apps in Genomics and Trials ## R/Pharma 2018
### Jessica Minnier, PhD
Oregon Health & Science University
@datapointier
### August 16, 2018
Slides available at
http://bit.ly/rpharma-minnier
--- # Our Team ## Biostatistics Shared Resoure
   --- class: inverse, center, middle # Why Shiny? --- background-image: url(figs/spreadsheetcombo.png) background-position: center background-size: 120% # Motivation: Too many spreadsheets! --- # An example: START Shiny Transcriptome Analysis Resource Tool
 BSR: Jessica Minnier, PhD; OHSU KCVI: J Sklenar, PhD, A.P. Barnes, PhD, J. Nelson, PhD
 Github: https://github.com/jminnier/STARTapp/
 Shinyapps.io:  https://kcvi.shinyapps.io/START/
  DATA = RNA-seq gene expression   ---  # Very quick tour   --- # Data Input - Input data ~ multiple formats: Special input formats - Interface with other software? Export special formats   --- # Data Exploration: Interactive ![](figs/start_scatterplot.png) --- # Drug Development ## Combination Therapy `\(\rightarrow\)` Visualize drug synergy *BSR*: Andy Kaempf, MS & Tomi Mori, PhD
 *Knight Cancer Leukemia Team*: Steve Kurtz, PhD & Chris Eide, B.A. ![](figs/combo1.png)    --- class: clear ![](figs/combo4.png) --- # Clinical Trials Methods ## Bayesian Adaptive Design `\(\rightarrow\)` An Adaptive Bayesian Sequential Design for Determining the Subject-Specific Optimal Treatment Length (manuscript in progress) https://bayesiantrial.shinyapps.io/Bayesian12/ *BSR*: Yiyi Chen, PhD; Lina Gao, PhD
 *OHSU*: Zunqiu Chen, MS; Matthew F Halsey, PhD; Jodi Lapidus, PhD - Select directions and weights of various outcomes - Determine potential length of treatment to be evaluated - Upload data - Potential actions: Escalate; De-escalate; Stay ![](figs/bayes0.png) --- # General App & Trial Specific ![](figs/bayes1.png) --- class: inverse, middle, center # Tips/Lessons Learned --- # Present QA plots up front  --- # Provide Instructions!  --- # Old fasioned debugging/logging works ![](figs/start_error.png) --- # Conclusions - R Shiny can be a tool to creatively interact with data - Improve collaboration and promote your methods - Avoid repetitive analyses and visualizations - Instructions, data checks/QA are vital ## START - working on extensions to single-cell and proteomics specific analyses and visualizations - (one day) switch to use modules - we welcome collaboration! --- # Thank you!
 Contact me:  minnier-[at]-ohsu.edu,  [datapointier](https://twitter.com/datapointier),  [jminnier](https://github.com/jminnier/) START: http://jessicaminnier.com/STARTapp/ RELATED SLIDES ON SHINY (Challenges/Responsibilities): - Data Day Texas <http://bit.ly/shiny-ddtx> - CSP: <http://bit.ly/shiny-csp18> Slides available at <http://bit.ly/rpharma-minnier>
 Code for slides available at <https://github.com/jminnier/talks_etc> Slides created via the R package [xaringan](https://github.com/yihui/xaringan) by [Yihui Xie](https://twitter.com/xieyihui?lang=en) with the metropolis theme


2 references to ReduceAssignment
System.Management.Automation (2)
engine\parser\Compiler.cs (2)
3529
ReduceAssignment
(
6888
exprs.Add(compiler.
ReduceAssignment
((ISupportsAssignment)lhsElement, TokenKind.Equals, indexedRHS));


Hey There!
I am an allround web developer. I am a programmer with good knowledge of front-end techniques. I love structure and order and I also stand for quality. I love spending time on fixing little details and optimizing web apps. Also I like working in a team, you'll learn faster and much more. As the saying goes: 'two heads are better than one'. Apart from these I also like travelling to new places.
Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur.


VIDEOLIST FETCH ERROR! PLEASE GO INTO DASHBOARD/VIDEOS.HTML TO CONTINUE
how do i get rid of this error?


This page shows the contents of the selected container. Samples can be added and edited by clicking the pencil icon, and removed by clicking the x
This container is currently assigned and in use on a beamline sample changer. Unassign it to make it editable


The concept of backup is straightforward: create a copy of your data so that you have a backup in case the original goes down! But when it comes to setting up a backup technology, you'll quickly realize that in order to understand which backup technology to use, you'll need to understand the nature of yourself and of your system. As it turns out, there many backup technologies that are simply not right for you. Some technologies, designed for backup on older systems, no longer make sense on the popular, widespread, and economic systems available today. Others are designed for modern systems, but only for the biggest of the big. Thus, you'll need to understand the full spectrum of users and uses, both past and present, in order to make an informed decision.
Looking at snapshots of computers throughout history is very telling about where we are with computers today. For each specific computer we analyze here, we look at where its data comes from, what it stores, and how its data (or the data, for that matter) is backed up.
Computer: Abacus/Pocket calculator
External data: Manual input by human operator
Internal data: Only temporary working set data
Backup style: None, you just copy out the result of
the computation to the sheet of paper you are using to solve your
problem
Computer: Punched card tabulator
External data: Programs are hand-wired, data read
from punched cards
Internal data: Only temporary working set data
Backup style: None, you just pick up the printed
results of the computation
Computer: Minicomputer with 2 MB hard disk
drive
External data: Read from any of a variety of sources:
teletype terminal, serial cable, electronic sensors, paper tape,
magnetic tape, even another computer
Internal data: Programs, text files, large arrays of
numbers ("binary data")
Backup style: Copy the entire hard disk drive's
contents to a magnetic tape. Multiple different tapes are
maintained in a library to save different images from different
backup runs. This made sense because 1) the entire hard disk
drive's contents could be read in a very short amount of time, 2)
the disk stored so little data that most of it would have ended up
being changed under normal use, and 3) files would be regularly
deleted from disk when they are no longer relevant to the current
project at hand.
Computer: Early PC microcomputer
External data: Same as minicomputer
Internal data: Only temporary working set data
Backup style: Create a copy of an existing paper
tape, magnetic tape, or floppy disk
Computer: Television with video cassette
recorder
External data: Broadcast, video input source, or
video cassette tape
Internal data: Only temporary working set data
Backup style: None, the entire procedure was
forbidden on the grounds of potential copyright infringement. Only
highly authorized users possessed devices that featured copying the
contents from one tape to another.
Computer: Desktop computer of 2000-2010s
External data: Same as minicompter
Internal data: Programs, text files, graphics, sound,
movies, physically accurate models of objects, databases, archives
of old files that might be potentially useful, and more
Backup style: For most users, copy to an external
hard drive or to another computer. Backups must always be
incremental, because it now takes an unwieldly amount of time to
copy off an entire disk's contents. For the biggest of the big,
data is eventually copied to expensive enterprise-class magnetic
tapes.
There are two important trends to observe from these snapshots of history.
Modern computers, with their abundant storage space, are very useful for storing archival data. If you are not an absolute minimalist, you probably take advantage of the large storage space that modern computers offer so that you can store old files that could possibly be of use to you. If this is the case, then you can roughly cut your data into two classes: working set data and archival data.
Asman was originally created to manage archival data rather than working set data. Most other backup systems take the opposite route, being designed to first manage working set data and second archival data. The Unix `tar', `cpio', and `dump' commands are excellent examples.
A key difference between the use patterns of working set data and archival data is that working set data tends to change much more frequently in its entirety than archival data. The most common and important changes that happen in working set data are file creations, modifications, and deletions. Archival data, in comparison, tends to experience a lot of additions and rearranging of files but not many modifications and deletions. Thus, for example, re-copying all files to create a backup is reasonably efficient for working set data, but for archival data, only the changes should be applied to existing backup copies. Due to the sheer volume of archival data, re-copying all of the data would take a prohibitive amount of time.
Here are some tips you should consider if you store archival data:
The space used to store your working set data is your workspace, naturally. The working set always has priority over the archival set, so the working set must always be sufficiently sized first.  Should you need a larger working set, you can manually increase the quota later. If the working set is not at full quota, archival may take up the unused space.
Remember, the archival space is always on an abundance basis, when storage is abundant and you have extra to spare, you should utilize all the space you can. But when you're out, you're out. No time for nonsense. Archival no longer makes sense. Now if archival truly is mandatory, then under these definitions, it's part of your working set!
Consider this hypothetical on backing up your working set. You're working on a free time project, then you must be suddenly interrupted to work on something more important. What should you do? You need to keep backing up your data. "But," you say, "I should wait until I'm finished before backing up, because then my dataset will be much more compact. If I backup now, I'll be wasting space, and I don't need to backup right now, right?"
Wrong.
You need to always make sure you have sufficient space to backup your WORKING SET. It's like at a moment's notice, your progress so far is frozen in place by an unexpected blast of dry ice, permanantly preserved, because, at a moment's notice, catastrophic failure could also destroy all your working set data. If it's been taking THIS long for you to finish the project, all the more better for you to save your working set where you are currently at! And you should always allocate sufficient space to backup your working set, because this is traditionally the ONLY data that was backed up, NOT archival data.
Naturally, this brings up the point. You may be working on serveral different "projects" concurrently, and for each one, you need a separate working set domain with a separate quota. One big giant workspace probably doesn't do it for most people. Of course, perhaps a problem with contemporary operating systems is that disk quotas may be provided on only a per-user basis, and users might not be able to use the operating system to help them with nested disk quotas, instead having to rely on user applications to perform the task sub-optimally.
Yet the previous point brings up another point. How many concurrent projects are you working on? How many are you willing to let sit idle for how much time? If a project is not done, you still need a workspace for the project in progress. For lots of concurrent projects, the total workspace size will be very large. The only ways to eliminate the workspace for the project in progress are to either finish the project or cancel it.
"But I feel bad to declare it canceled." Sure, but how bad do you feel to have an enormous workspace? Too many concurrent projects, in unwieldly proportions? So, figure out your concurrency limit and do not exceed it. Of course, you can always change it, but make sure you are fully aware of the implications of greater concurrency: Each task gets less average attention from you and takes overall longer to complete.
Although you can archive all data should you feel so inclined, as a practical matter, it is not strictly necessary to archive all data. The first question to ask is "Do you really care about the data?" If you could care less about saving it, then you don't need to backup a copy in your personal archives. Additionally, some data may already have sufficient redundancy outside of your personal archives, so it may not make sense to provide additional redundancy in your personal archives. Here are some tips in regard to these considerations:
Data in modern computers can be separated into different "storage classes," roughly corresponding to how traditional the data is. Under my definitions, measure of traditionality hinges on the amount of storage space that the data takes up, so naturally, your data is keyed into magnitude storage classes. Data from a smaller magnitude class corresponds to much more data value than the same amount of data in a larger magnitude class. For example, thousands of typed stories could be stored in the digital space needed to store just one movie! I'm pretty sure that most people would consider it more important to save 1000 typed stories than to save only one movie.
Here is a non-comprehensive listing of storage classes, from largest to smallest, along with recommendations on how to decimate the data:
One thing to keep in mind is that your collection of data is a system. Oragnisms are systems too, and systems, just like organisms, can grow, shrink, or die. Presumably your data system has been already created; otherwise, you wouldn't be here. Can your system really shrink and die? Maybe. Shrinking and end of life has been observed with many systems, but not all, so it could happen. This is not to think of the worst, but to remember it is still a possibility.
Data system growth is easy to manage at an abstract level. When there's more data in the system, just add larger and more sophisticated indexing and organization schemes to deal with it. In other words, add more data to deal with more data. Shrinking, on the other hand, is more difficult: You can't add more data to get by with less data, that would defeat the purpose!
So, the answer to dealing with less data is archive system pruning. Shrinking working space is as easy as cleaning up a project when you are done working on it, so the difficult part rests on managing the archive space. The first thing to remember is that none of the archive system is strictly necessary, so you can just prune the data at random. Of course, a strategy to perform this process will produce better results.
The solution is simple. You want to prune the data the takes up the greatest amount of space but contributes the least useful information to your system. Take a look at my previously-given storage classes definitions. What data is this likely to be? Yep, that's right: big, modern media files. Start by deleting those first. Ideally, you would down-convert the media to a more compact format, but failing that, delete. Also, you want to delete the oldest files, as that is farest away from your "working set", and the most archival-style data you can chuck.
So, in default pruning mode, you first scan the data, break it up into storage classes, select the largest storage class, and delete files in order from oldest (preferably least recently used, with reads included as "use") to newest until you've freed up enough space. Then you keep doing this with progressively smaller storage classes. Note that you can consider deleting files from large subdirectories before considering small subdirectories.
Wait, we have an argument between old versus big. How do you decide between the two? What if you have a big new file? Default rule: Assume all archival data within a large storage class is strictly less necessary than that of a smaller storage class, so you delete the big new file before the small old files.
Wait, a problem with this system is that eventually when storage space runs out, all large scale data will be wiped out, and only small scale data will remain. Is that what you really want? Yes, just one large scale data file corresponds to an immeasurable amount of small scale data, so unless you think you know better, this is probably what you want, since it corresponds to the least amount of actual data loss. The whole idea of deleting the big files first is a bit of a systems deconstruction theory. If you are a traditionalist computer user, you would strip down to text files at last, then start deleting the text files when nothing else works to free up space.
Another pruning method is for the user to put together a data importance priority list. Files and subdirectories near the top of the list are considered most important, and those near the bottom of the list are considered as first candidates for deletion.
Now, there is more than one way to delete a file or directory when it is time. One way is total decimation, where all contents of the file or directory are completely deleted before moving on to deleting the next up the list. Another way is partial decimation, where only the big stuff out of one directory is deleted (or only part of a file is deleted) before moving on to deleting the next up the list. Last, there is atomic deletion, which is total decimation that occurs atomically. A traditional file delete is an example of total decimation. Here, the assumption is the software and user are not capable of handling a partially deleted file at a later date.
A general idea that is likely to be useful for shrinking your data system is deevolution, winding backwards to how things were like at the beginning. On a holistic level, you can't turn back the clock and make today how it was yesterday, even though you can do so with archive data in the computer, so don't try to do this. So, whatever you have now that you didn't have at the beginning, get rid of it. Say in the beginning, you had only what you've collected the week before that day. To deevolve your current data system to be like the original data system, you would delete everything outside the time range of one week before today.
Ultimately, when all else fails, systems just suffer catastrophic and total destruction. All data are lost. If it can't be regenerated, then things can never go back to how they were in the past. If there must be a system, only a new beginning can be started, from the ground up. If you had to start all over, what would you do?
Think about software development lifecycles, for example. It's actually really easy to write programs from scratch. In the initial stages, most of your time (and money) is spend on technical work, adding new code. Nothing in the way of management, so work, as in technical work, tends to get done really, really quickly. Overall, the system seems complete and working in the initial stages. Then as things scale up, the amount of work that one person can do is exceeded, so you cannot maintain your personal data anymore. Here's a lesson from business. Companies can decimate and go out of business. So can the viability of your personal collection of data. And someone else who comes in your place will be able to rebuild something similar to what you've built in basically no time and money at all. So you have to ask yourself, are you realistically going to build a company over your data? If not, then the future is that things will start all over, building up from the bottom.
If you ever wonder about open-source software projects out there, starting from scratch, isn't that a waste when there are existing projects to build off of? Well, now that you know the way software is developed, incomplete isn't all that bad, what matters is that there are people willing to work on it, and the genesis technical work isn't all that hard. Really, but is this even so when most other people in the workforce don't do software development technical work? Business matters, remember that.
Start by identifying your working set data. Everything else not identified is your archival data. Next, you need to partition your data by storage class. It's likely that projects correlate to storage classes. For example, on one hand, you might be working on a multimedia video (large working set space), while on the other hand, you might be typing a book (small working set space).
How should size the storage classes in relation to each other? For this, you first ask the question in isolation. Looking at text alone, how much characters of text do you need to store? 2 million? 4 million? Verify that limit can be satisfied. Then move on to the next storage class, say raster images. How many raster images of 6 megapixel resolution do you need to store? 10,000? 20,000? Verify that limit can be satisfied. Oops! Out of disk space! Well if you can't even satisfy the requirements for your current project at hand, you better expand your storage capacity!
Project-oriented organization works well for archival data, and the projects are naturally chronologically ordered. For non-functional computer data, at least. For functional software tools, there is likely to be reusability, so they should be ordered by a different manner.
Once you've got the data classification done, you need to select the proper backup technology to use. For the working set data, you can use any of a large variety of classical and modern backup technologies. For your personal archival data, there is only one true solution: Asman! So, why don't you get started learning how to use the technologies?


Chris Mills, Manchester, The Grim North, UK
Page written by abbreviations.
当你使用日期、化学方程式、和数学方程式时会偶尔使用上标和下标。和元素可以解决这样的问题。
My birthday is on the 25th of May 2001.
Caffeine's chemical formula is C8H10N4O2.
If x2 is 9, x must equal 3 or -3.


| HTML5 SYNTAX |
| Basic |
<tagname attribute="value" attribute="value">CONTENT</tagname> |
| WELL-FORMED AND VALID HTML5 |
| Basic Rules |
-
All elements are properly closed.

 content

-
Empty elements are never closed. [exception]

-
All elements are properly nested.

 content

-
All attributes have a quoted value assigned.

-
Single-valued attributes are minimized. [exception]
<input autofocus selected>
|
| Semantic correctness all elements are chosen well. |
| OVERVIEW |
| Basic |
|
| ROOT AND CHILDREN OF HEAD |
 |
Defines the root of an HTML document |
lang |
<meta> |
Defines metadata about an HTML document |
charset |
<link> |
Defines the relationship between a document and an external resource (most used to link to style sheets) |
type|rel|href |
<title> |
Defines a title for the document |
|


NHL teams facing the scariest salary-cap recapture situations
by Lyle RichardsonAfter retiring over the summer after 19 NHL seasons — including 11 years with the Florida Panthers and eight years with the Vancouver Canucks — goaltender Roberto Luongorejoined the club as a special advisor to general manager Dale Tallon this month.
And for Vancouver general manager Jim Benning, the situation is less than ideal.Luongo's retirement last summer meant the Canucks areon the hook for over $3 million in annual salary-cap recapture penalties over the next three years. Meanwhile, Luongo's back to drawing paychecks from the Panthers.
“I wanted to voice our displeasure with the whole thing,” Benning told the Vancouver Sun's Ben Kuzma.
MORE: Panthers to retire Luongo's No. 1 jersey
Hisconcern isLuongo is recouping money he left on the table by retiring in June. Benning said the Panthers are allowed to hire Luongo as long as it's a market-level position at an entry-level salary comparable to a similar position in the league.
“I don't know what he's getting paid,” Benning added.
A source told The Athletic's Pierre LeBrun it's nowhere close to Luongo's former salary, guessingit's around $200,000.
Benning also acknowledged there's little his club can do under the salary-cap recapture rules in the current collective bargaining agreement; he and his club are paying the price for his predecessor, employing a form of salary-cap circumvention allowable under the former CBA when Luongo signed his 12-year contract a decade ago.
Back then, several teams signed a handful of players to exceedingly long, heavily front-loaded contracts as a mean of garnering a more favorable annual salary-cap hit. The league shut down that loophole under the present CBA, limiting contracts to eight years for re-signings andseven for unrestricted free agents, as well as placing limits on how much contracts can be front-loaded.
The salary-cap recapture penalty was also implemented, whichgoes into effect when a player carrying one of those lengthy contracts retires. It affects the club that signed him to the deal, as well as any club that acquires him via trade or waivers.
In Luongo's case, Vancouvergot tagged the hardest because the team signed him to that long-term contract. The Panthers are also penalized, though they pay a moreaffordable $1.09 million annually.
Currently, 13 players carry those lengthy, front-loaded contracts, as perCapFriendly.
| PLAYER | TEAM | YEARS SIGNED | EXPIRES | AAV (million) |
|---|---|---|---|---|
| Shea Weber | MTL* | 14 | 2026 | $7.857 |
| Duncan Keith | CHI | 13 | 2023 | $5.538 |
| Alex Ovechkin | WSH | 13 | 2021 | $9.538 |
| Zach Parise/Ryan Suter | MIN | 13 (each) | 2025 | $7.538 (apiece) |
| Marian Hossa | ARI^ | 12 | 2021 | $5.275 |
| Sidney Crosby | PIT | 12 | 2025 | $8.7 |
| Henrik Zetterberg | DET | 12 | 2021 | $6.083 |
| Jeff Carter | LAK" | 11 | 2022 | $5.272 |
| Johan Franzen | DET | 11 | 2020 | $3.954 |
| Jonathan Quick | LAK | 10 | 2023 | $5.8 |
| Nicklas Backstrom | WSH | 10 | 2020 | $6.7 |
| Jordan Staal | CAR | 10 | 2023 | $6 |
*Contract originally signed with Nashville; ^Contract originally signed with Chicago; "Contract originally signed with Philadelphia
Three of them —Hossa, Zetterbergand Franzen —are all but retired due to injuries or chronic ailments, leading theirrespective teams to place them on long-term injury reserve. That provides those clubs with salary-cap relief if needed while assuring they won't be tagged with recapture penalties.
Backstrom's contract expires next July and Ovechkin's in 2021 so the Capitals have no fear of cap recapture there.
That leaves eight —Weber, Keith, Parise, Suter, Crosby, Carter, Quick and Staal —with the potential to create cap-recapture headaches down the road.Most could play out the remaining term of their respective deals. Injuries could force some with long injury histories, such as Parise and Quick, onto the permanent LTIR.
The one to watch is Weber. Nashvillematched a hefty offer sheet from the Philadelphia Flyers in 2012 before the last NHL lockout and the current CBA. In 2016, they traded Weber to the Canadiens for P.K. Subban. Both clubs could see cap recapture penalties but the Predators will bear the heaviest burden.
MORE: Winter Olympics potential roadblock in CBA talks
LeBrun recently posted a breakdownof the potential recapture penalties facing the Predators. Their portion, if he retires next year or in 2021 would be over $4 million annually, or over $6 million per season if he pulls the chute in 2022.
Those numbers are bad enough, but it's the penalties in the final three seasons that's concerning.
If Weber retires in 2023, the Predators will be tagged with over $8.1 million in annual recapture penalties. If he goes in 2024, it jumps to over $12 million annually. Should he retire before the final season of his contract, the Preds get walloped with over $24 million.
LeBrun reports the league has no intention of doing away with the cap recapture penalty. However, he said there have been discussions about amending the formula under the next CBA to soften those penalties by spreading them out over a longer period.
In the meantime, Predators fans — as well as the organization — should hope that the Habs captaindoesn't retire before his contract expires.


Wikipedia mentions DevOps as a portmanteau of "development" and "operations", describing a software development method that stresses communication, collaboration, integration, automation, and measurement of cooperation between software developers and other information-technology professionals. .
Though many would try to use this as a buzzword (like 'agile' or 'cloud'!?), it is much more than a mere buzzword. It is a culture. But is that it? Tools and some processes? Definitely not!
"Devops means caring about your job enough to not pass the buck. Devops means caring about your job enough to want to learn all the parts and not just your little world. Developers need to understand infrastructure. Operations people need to understand code. People need to work with each other and not just occupy space next to each other."
- as this post so succintly puts it.
 We are willing to help organizations and teams adopt the DevOps culture in their daily workflow by identifying possible areas of improvement and suggesting relevant tools and techniques.
Follow our blog for interesting insights on this topic.
We provide consulting to teams/organizations for tools and techniques for DevOps practices.
We provide training for developers/sysadmins on tools and techniques to level up their DevOps practices.
We provide support for various open source tools used for development/build/deployment/maintenance.
We are DevOps culture evangelists! We love to talk about the DevOps culture. TechTalks mostly!


Offcanvas Side Panels
Codebase offcanvas panels are a activator components using data-content-id="{identifier}"
for specificity.
On this page:
The Simplest Offcanvas
Example 1 – click this button:
This is an Offcanvas Side Panel
In this simple example, no width has been specified. Therefore it will expand to the width required for its content (i.e. the text you are currently reading), up to max-width: 1000px
.
Click the icon above-right to dismiss. Alternatively, if there is any of your device screen not covered by this panel, then you can "click outside to dismiss".

You will need to specify whether the content of the offcanvas side panel is to slide in from the left or right – and you must also position its respective controller on the same side as what the content will slide in from).
You will also need to add an offcanvas control (e.g. navicon) for toggling the side panel. Be sure to set the offcanvas control code data-control_id=""
to point to its respective offcanvas content id=""
.
It is possible to have more than one offcanvas side panel component. But only one can be activated at any one time.
Controlling the Offcanvas Content Width
The offcanvas content block will "stretch to fit" the width of whatever content you put inside it (up to 100% width).
You can also control the offcanvas content block width in your own stylesheet.
Note: The .offcanvas-content
slides offcanvas to a width of 110% of the content width. The extra 10% ensures that a box-shadow on the content will also be hidden offcanvas.
The following demos operate as offcanvas sidebars at all viewport widths:
Example 2 – this offcanvas side panel is only as wide as its content requires:
Example 3 – this offcanvas side panel has style="width:200px"
:
Example 4 – this offcanvas side panel has style="width:75%"
:
Deactivating an Offcanvas Component Above a Media Query Viewport Width
Sometimes you may require some content to be displayed using an offcanvas side panel for smaller viewports but that switches to being an ordinary on-canvas panel for wider viewports. This is done by adding modifier classes (and by hiding the controls on wider viewports), as in the following table:
| Offcanvas content | Offcanvas control | Offcanvas close |
|---|---|---|
.offcanvas-content |
(Offcanvas side panel operates at all viewport widths – so you won’t want to hide the controls.) | |
.offcanvas-content-sm |
.hide-md-up |
.hide-md-up |
.offcanvas-content-md |
.hide-lg-up |
.hide-lg-up |
Example 5 – Click the icon below (if you can see this on browser widths medium-down).
Example 5
This colored panel operates as an offcanvas side panel at small viewport widths, but it is on-canvas (as a simple DIV within this article) for medium viewports up.
You will also need to add the appropriate class to hide the controller and the closer above the same viewport width.
Offcanvas Classes
| Class | Notes | Modifiers |
|---|---|---|
.offcanvas-ctrl |
The offcanvas controller element. | Controller alignment: .offcanvas-ctrl-left , .offcanvas-ctrl-right |
.offcanvas-content |
The offcanvas content panel element. | Content panel alignment: .offcanvas-content-left , .offcanvas-content-right Responsive ’switches': .offcanvas-content-sm – operates as an offcanvas side panel only on narrow viewports (below the md viewport width)1 .offcanvas-content-md – operates as an offcanvas side panel only on narrow-medium viewports (below the lg viewport width)2
|
.offcanvas-close |
The offcanvas close-controller element (place this within the content panel). | Close-controller alignment: .offcanvas-close-left , .offcanvas-close-right |
1 Use .hide-md-up
for hiding the controllers.
2 Use .hide-lg-up
for hiding the controllers.


| fkSession reference pages |
event=LOAD_EVENT(rootdir,event_name)
event=LOAD_EVENT(rootdir,event_name) load a previously saved event file with the name event_name from rootdir. The function returns a structure with 'timestamp' and 'description' fields.
| load_segment | Toolbox page | import_clusters |


Dictate is a tool to aid in dictation. A teacher creates a group of sentences and reads the sentences out to a class of students. Each student enters the sentences as the student believes they should be spelled. Dictate keeps scores and at the end of the dictation the student gets a chance to view the correct answers. Furthermore, the score can be saved and printed out using Diploma (see below).
Dictate was created as a response to the wishlist found at: http://www.mpsomaha.org/willow/technology/wishlist.html.
Dictate is released under the GNU General Public License v2 and requires Palm OS 3.0 or better.
You can support this project by donating any amount to my Pay Pal account.
A special Thank You! must go to Tony Vincent for the lovely icons and just as lovely User Guide.
v1.5 (2005-10-17) Changed versioning from 1rX to 1.X. Fixed a bug in the Category system. Changes to the existing categories and adding new categories are no longer reverted to the defaults when launching Dictate (thanks Elaine Waters!) v1r4 (2005-08-30) Added the 'All' button to the "Available Sentences" form. Removed the "double-redraw" syndrome on tables. v1r3 (2005-05-19) When viewing answers a correct sentence is only shown once (as in the export score to Memo Pad option) (Tony Vincent). v1r2 (2005-05-19) Fixed a bug where the some of the controls on the export sentences form didn't respond as intended. v1r1 (2005-05-18) First public release.
Diploma is used to print out the score file generated by Dictate. Diploma currently only runs on Microsoft Windows.


The C++ runtime and generated grammars look very much the same as the java ones. There are some subtle differences though, but more on this later.
The following is a bit unix centric. For Windows some contributed project files can be found in lib/cpp/contrib. These may be slightly outdated.
The runtime files are located in the lib/cpp subdirectory of the ANTLR distribution. Building it is in general done via the toplevel configure script and the Makefile generated by the configure script. Before configuring please read the lib/cpp/README file for additional info on specific target machines.
./configure --prefix=/usr/local make
Installing ANTLR and the runtime is then done by typing
make installThis installs the runtime library libantlr.a in /usr/local/lib and the header files in /usr/local/include/antlr. Two convenience scripts antlr and antlr-config are also installed into /usr/local/bin. The first script takes care of invoking antlr and the other can be used to query the right options for your compiler to build files with antlr.
c++ -c MyParser.cpp -I/usr/local/includeLinking is done with something similar to:
c++ -o MyExec <your .o files> -L/usr/local/lib -lantlr
To get ANTLR to generate C++ code you have to add
language="Cpp";to the global options section. After that things are pretty much the same as in java mode except that a all token and AST classes are wrapped by a reference counting class (this to make live easier (in some ways and much harder in others)). The reference counting class uses
operator->to reference the object it is wrapping. As a result of this you use -> in C++ mode in stead of the '.' of java. See the examples in examples/cpp for some illustrations.
New in ANTLR 2.7.2 is that if you supply the
buildAST=trueoption to a parser then you have to set and initialize an ASTFactory for the parser and treewalkers that use the resulting AST.
ASTFactory my_factory; // generates CommonAST per default.. MyParser parser( some-lexer ); // Do setup from the AST factory repeat this for all parsers using the AST parser.initializeASTFactory( my_factory ); parser.setASTFactory( &my_factory );
In C++ mode it is also possible to override the AST type used by the code generated by ANTLR. To do this you have to do the following:
#include <antlr/CommonAST.hpp> typedef antlr::ASTRefCount<My_AST> RefMyAST; class MyAST : public antlr::CommonAST { public: MyAST( void ) { } ~MyAST( void ) { } void initialize( antlr::RefToken t ) { antlr::CommonAST::initialize(t); // more stuff.... // ... } void initialize(int t,const std::string& txt) { setType(t); setText(txt); } /// Initialize the AST from a stream (need to document this!) void initialize( std::istream& infile ); /// Clone this instance (used by several support lib algorithms) antlr::RefAST clone( void ) { MyAST *ast = new MyAST(*this); return antlr::RefAST(ast); } void addChild( RefMy_AST c ) { antlr::BaseAST::addChild( static_cast<antlr::RefAST>(c) ); } static antlr::RefAST factory( void ) { antlr::RefAST ret = static_cast<antlr::RefAST>(RefMyAST(new MyAST)); return ret; } };
ASTLabelType = "RefMyAST";After that you only need to tell the parser before every invocation of a new instance that it should use the AST factory defined in your class. This is done like this:
// make factory with default type of MyAST ASTFactory my_factory( "MyAST", MyAST::factory ); My_Parser parser(lexer); // make sure the factory knows about all AST types in the parser.. parser.initializeASTFactory(my_factory); // and tell the parser about the factory.. parser.setASTFactory( &my_factory );
After these steps you can access methods/attributes of (Ref)MyAST directly (without typecasting) in parser/treewalker productions.
Forgetting to do a setASTFactory results in a nice SIGSEGV or you OS's equivalent. The default constructor of ASTFactory initializes itself to generate CommonAST objects.
If you use a 'chain' of parsers/treewalkers then you have to make sure they all share the same AST factory. Also if you add new definitions of ASTnodes/tokens in downstream parsers/treewalkers you have to apply the respective initializeASTFactory methods to this factory
This should now (as of 2.7.2) work in C++ mode. With probably some caveats.
The heteroAST example show how to set things up. A short excerpt:
ASTFactory ast_factory; parser.initializeASTFactory(ast_factory); parser.setASTFactory(&ast_factory);
A small excerpt from the generated initializeASTFactory method:
void CalcParser::initializeASTFactory( antlr::ASTFactory& factory ) { factory.registerFactory(4, "PLUSNode", PLUSNode::factory); factory.registerFactory(5, "MULTNode", MULTNode::factory); factory.registerFactory(6, "INTNode", INTNode::factory); factory.setMaxNodeType(11); }
After these steps ANTLR should be able to decide what factory to use at what time.
header "<identifier>" { }
| identifier | where |
pre_include_hpp |
Code is inserted before ANTLR generated includes in the header file. |
post_include_hpp |
Code is inserted after ANTLR generated includes in the header file, but outside any generated namespace specifications. |
pre_include_cpp |
Code is inserted before ANTLR generated includes in the cpp file. |
post_include_cpp |
Code is inserted after ANTLR generated includes in the cpp file, but outside any generated namespace specifications. |
Sometimes various tree building constructs with '#' in them clash with the C/C++ preprocessor. ANTLR's preprocessor for actions is slightly extended in C++ mode to alleviate these pains.
NOTE: At some point I plan to replace the '#' by something different that gives less trouble in C++.
The following preprocessor constructs are not touched. (And as a result you cannot use these as labels for AST nodes.
if
define
ifdef
ifndef
else
elif
endif
warning
error
ident
pragma
include
As another extra it's possible to escape '#'-signs with a backslash e.g. "\#". As the action lexer sees these they get translated to simple '#' characters.
header "pre_include_hpp" {
// gets inserted before antlr generated includes in the header file
}
header "post_include_hpp" {
// gets inserted after antlr generated includes in the header file
// outside any generated namespace specifications
}
header "pre_include_cpp" {
// gets inserted before the antlr generated includes in the cpp file
}
header "post_include_cpp" {
// gets inserted after the antlr generated includes in the cpp file
}
header {
// gets inserted after generated namespace specifications in the header
// file. But outside the generated class.
}
options {
language="Cpp";
namespace="something"; // encapsulate code in this namespace
// namespaceStd="std"; // cosmetic option to get rid of long defines
// in generated code
// namespaceAntlr="antlr"; // cosmetic option to get rid of long defines
// in generated code
genHashLines = true; // generated #line's or turn it off.
}
{
// global stuff in the cpp file
...
}
class MyParser extends Parser;
options {
exportVocab=My;
}
{
// additional methods and members
...
}
... rules ...
{
// global stuff in the cpp file
...
}
class MyLexer extends Lexer;
options {
exportVocab=My;
}
{
// additional methods and members
...
}
... rules ...
{
// global stuff in the cpp file
...
}
class MyTreeParser extends TreeParser;
options {
exportVocab=My;
}
{
// additional methods and members
...
}
... rules ...
Version: $Id: //depot/code/org.antlr/test/antlr-2.7.0a11/doc/runtime.html#3 $


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TQ3CameraTransformData |
typedef struct TQ3CameraTransformData { TQ3Matrix4x4 localToWorld; TQ3Matrix4x4 worldToCamera; TQ3Matrix4x4 cameraToFrustum; } TQ3CameraTransformData;
State data for a transform object that manipulates the camera matrix state.
Vertices are passed through three transforms to convert them from local
coordinates to the canonical viewing frustum.
The localToWorld transform converts local coordinates to the world coordinate
system.
The worldToCamera transform converts world coordinates to the camera's
coordinate system, which places the camera at the origin and establishes
the camera's view of the world.
The cameraToFrustum converts the camera's coordinate system to the canonical
viewing frustum. This frustum is a box centered on the origin, ranging from
-1 to +1 in x and y. In z the frustum ranges from 0 at the near clipping plane
to -1 at the far clipping plane.
Once vertices have been transformed to the canonical frustum, a portion of
the frustum is then selected using the current camera's viewPort and that
portion mapped to the draw context's pane. These two steps are controlled by
the current camera and draw context, and are not affected by a camera transform
object.
- localToWorld
- The local-to-world matrix.
- worldToCamera
- The world-to-camera matrix.
- cameraToFrustum
- The camera-to-frustum matrix.
TQ3RotateAboutAxisTransformData |
typedef struct TQ3RotateAboutAxisTransformData { TQ3Point3D origin; TQ3Vector3D orientation; TQ3Float32 radians; } TQ3RotateAboutAxisTransformData;
State data for a transform object that rotates about an arbitrary axis.
Note that the orientation vector must be normalized.
- origin
- A point on the axis of rotation.
- orientation
- A normal vector determining the direction of the axis.
- radians
- Number of radians to rotate about the axis.
TQ3RotateAboutPointTransformData |
typedef struct TQ3RotateAboutPointTransformData { TQ3Axis axis; TQ3Float32 radians; TQ3Point3D about; } TQ3RotateAboutPointTransformData;
State data for a rotate-about-point transform.
- axis
- Enumerated value specifying the x, y, or z axis.
- radians
- Number of radians to rotate about the axis.
- about
- A point on the desired axis of rotation.
TQ3RotateTransformData |
typedef struct TQ3RotateTransformData { TQ3Axis axis; TQ3Float32 radians; } TQ3RotateTransformData;
State data for a rotate transform.
- axis
- Enumerated value specifying the x, y, or z axis.
- radians
- Number of radians to rotate about the axis.
© 1999-2023 Quesa Developers (Last Updated 1/27/2023)


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