The Raspberry Pi (read R-pi) is a series of low-cost, credit card-sized single-board computers. It is just like any other computer and features built in Wi-Fi, Bluetooth. You can connect a keyboard, mouse through USB or Bluetooth and a display monitor through HDMI cable and start using it just like a normal computer.
But the real power of Rpi is realized in embedded systems. The Raspberry Pi has the ability to interact with the outside world, and has been used in a wide array of digital maker projects, from music machines and parent detectors to weather stations and tweeting birdhouses with infra-red cameras.
Contents:
First Look
What does Raspberry Pi board look like?
The image given below is a top-view of Raspberry Pi 3 model B.
-
The 40 pins shown at the top contain the Ground pins, I2C, SPI, GPIO pins, supply voltage pins.
-
On the right, the top two structures are the USB ports and bottom one is the ethernet port.
-
Comming down, we have the USB charging port on the left and the and the HDMI port next to it.
-
On the left hand side we have a micro SD slot which acts as the hard drive of Raspberry Pi.
Now lets have a closer look at those 40 pins. Here is a pin diagram of those 40 pins. We can see that out of the 40 pins
- 27 pins are GPIO pins
- 8 pins are Ground
- 2 pins are 5V supply
- 2 pins are 3.3V supply
- The other 2 pins are ID_SD and ID_SC used in I2C communication
The GPIO pins are used to connect to electronic devices and can be used as input or output. GPIO 2 and 3 can be used for I2C communication as they are the SDA and SCL pins respectively.
The 5V pins can be used to give 5V supply to any of the electronic devices. Same goes for 3.3V pins.
Installation
Depending on whether your laptop/pc has Linux or Windows, follow this steps to set your Raspberry Pi.
For Linux
- First download the image file of the operating system you want to install on your R-pi.
- Open a linux terminal of your choice.
- Connect your R-pi to laptop using the connector and insert the memory card in its slot.
-
Now unmount the memory card using command:
sudo umount /dev/PORT_NAME
To see which port your sdcard belongs to, type:
lsblk
-
To copy the contents of img file to sdcard, type:
sudo dd if=PATH_TO_IMG_FILE of=PATH_TO_SD_CARD_MOUNT_POINT
- It may take some time to copy the contents.
For Windows
- First download the image file of the operating system you want to install on your R-pi.
- Download Win32DiskImager and unzip the application (.exe file) inside.
- Insert your SD card into your Windows PC using a card reader.
- Open Win32DiskImager.exe with Administrator privileges ( That is, right click on it and choose “Run as Administrator” ).
- If your SD card isn’t automatically detected by the application, click on the drop-down menu at the top right (labeled “De
- Click the Write button and wait for Win32DiskImager to do its thing. When it finishes, you can safely eject your SD card and insert it into your Raspberry Pi.
For OSX
- First download the image file of the operating system you want to install on your R-pi.
- Download RPi-sd card builder (be sure to pick the appropriate version for your installed version of OS X) and unzip the application.
- Insert your SD card into your Mac using a card reader.
- Open RPi-sd card builder. You’ll immediately be asked to choose a Raspbian image. Choose the .img file you downloaded earlier.
- You’ll be asked if your SD card is connected. Since we inserted it earlier, it is, so go ahead and click Continue. You’ll be presented with SD card options. If you only have one inserted, you won’t see anything else in the list and it’ll be checked. If not, just check only the card you want to use and click OK.
- Enter your administrator password and click OK. You’ll be asked if the SD card was ejected. This is supposed to happen, as the application needs to unmount it so it can perform a direct copy. Double-check that your SD card is no longer available in the Finder. DO NOT remove it from your USB port. When you’re sure, click Continue.
- RPi-sd card builder finishes prepping your SD card, safely eject it and insert it into your Raspberry Pi unit.
Time to configure your R-pi!
Configuration
We use SSH to control R-pi through our laptop for SSH, we need r-pi to be connected to some network.
We can configure R-pi’s SSH, without ever requiring to boot R-pi.
Once the OS image has been burned on the SD-Card, remount the SD-card. You will see a lot of folders required by the OS to boot. We will change some configuration files before we insert the SD-card into R-Pi so that our R-Pi can directly connect to WiFi networks and you can SSH into it.
WiFi password setting
Open /etc/wpa_supplicant/wpa_supplicant.conf
in the SD-card
and write following piece of code in it at the end:
Enable SSH
Edit file /etc/rc.local
and add the following line at the end
Now remove the SD-card, put it in the R-Pi and power it up. You should see a red power light and a green light flashing up, if the OS boots correctly.
After some time, connect to the R-Pi using SSH. On linux, you can run the
command ssh<EMAIL_ADDRESS>, or use PuTTY on Windows/OSX.
Note: raspberrypi.local
is an identifier for R-Pi’s connected to your local network,
hence you don’t need to specify the exact IP address. Though, if you know the IP
address, you can specify that too instead.
Enter the default password raspberry
, and the RPi terminal will be accessible
looking something like this
Change the password of the RPi by running passwd
.
And that’s it!
Static IP configuration
Note: Static IP configuration is no longer required because recent versions of the RPi OS have a discovery protocol enabled which lets you SSH into the RPi without knowing the IP address.
This can be done by editing the file on your PC too.
We will assign a static IP to the R-Pi so that every time it connects to WiFi, it uses the same IP, hence we know what IP the R-Pi has.
You will need to know the IP address format, netmask and gateway of your network. For Tinkerers’ Lab, it is
For setting static ip, open /etc/network/interfaces.d
(again by mounting the
SD-card)
You will see a line reading iface wlan0 inet manual
Change manual
to static
and add the following lines
Once configured, type ssh pi@<ip-address>
in terminal to connect to your R-pi.
GPIO Pins
Configuring GPIO
For programming the GPIO pins we have to install the python 2 library RPi.GPIO. This module makes it simple to use the GPIO pins. To install RPi.GPIO on your Raspberry Pi follow the following instructions.
In the LXTerminal of your R-Pi type the commands
sudo apt-get update
To install RPi.GPIO, you first need to install the Python Development toolkit that RPi.GPIO requires.
To do this enter the following command:
sudo apt-get install python-dev
Then to install Rpi.GPIO itself type:
sudo apt-get install python-rpi.gpio
Thats it! Now you are ready to program GPIO pins.
Basics of GPIO programming
To program GPIO pins you have to import RPi.GPIO library in your python program. To do this type the following line at the top of your program:
import RPi.GPIO as GPIO
But before we start programming we have to set the numbering system of the pins. There are two types of numbering systems:
- BOARD
- BCM
The GPIO.BOARD option specifies that you are referring to the pins by the number of the pin the the plug - i.e the numbers printed on the board (e.g. P1) and in the middle of the diagrams below.
The GPIO.BCM option means that you are referring to the pins by the “Broadcom SOC channel” number, these are the numbers after “GPIO” in the green rectangles around the outside of the below diagrams:
In the image below the numbers in the middle correspond to BOARD numbering and those written outside refer to BCM numbering.
Based on which numbering system is comfortable to you, which RPi shield your are using, what program you are using you can choose the numbering sytem which is most convinient to you.
To specify in your code which number-system is being used, use the GPIO.setmode() function. For example…
GPIO.setmode(GPIO.BCM)
or
GPIO.setmode(GPIO.BOARD)
After specifying the numbering system we have to decide whether the pins that we are using will be input or output (just like in Arduino).
To do this we use GPIO.setup() function. So if you want to setup pin 4 as output you would enter:
GPIO.setup(4, GPIO.OUT)
If you want to set pin 17 as input you would enter:
GPIO.setup(17, GPIO.IN)
So if you have set a particular pin as input you would like to read the value of that pin. To do this you would use the GPIO.input() function.
For example if you would like to read the value of pin 17 you would enter:
GPIO.input(17)
If you have setup a pin as output you would like to write a value to it. You would use the function GPIO.output() for it.
For example if you would like to set the value of pin 4 as HIGH you would enter:
GPIO.output(4, GPIO.HIGH)
If you want to set it as low:
GPIO.output(4, GPIO.LOW)
Now that you know how to set input and output of pins you are set to use any electronic devices along with the entire convinience of python.
One important thing to note that after the program is terminated either on its own or by a Keyboard Interrupt some of the pins which were high remain high after execution of the program. So in order to set everything to low we use the GPIO.cleanup() function.
Here is an example of simple LED blink program in which the usage of each and every function will become clear
When we execute this program with a led at pin 4 we would see the LED blinking at a rate of 1 second. This program would go on for ever unless we terminate it by CTRL-C which is a KeyBoardInterrupt which then initiates the GPIO.cleanup function.
With this much knowledge you should be able to interface any electronic equipment with R-Pi with one last precation :P.
All the GPIO pins on R-pi are 3.3 volt logic level. So it is not safe to connect any device that gives or takes more than 3.3v as it might damage the GPIO pins. If you have to use any device that has a 5V supply such as HCSR04 ultrasonic sensors you should use a potential divider.
Time to try some good projects with your R-pi. Happy tinkering!


Creating Curved Corner Edge Flows 19/07/2015 #3d modelling #b3d #topology Creating curved corner edge flows.


Class JXG.Turtle
↳ JXG.Turtle
This is the Turtle class.
It is derived from JXG.GeometryElement.
It stores all properties required
to move a turtle.
Defined in: turtle.js.
| Constructor Attributes | Constructor Name and Description |
|---|---|
|
JXG.Turtle(board, parents, attributes)
Constructs a new Turtle object.
|
| Method Attributes | Method Name and Description |
|---|---|
|
back(len)
Move the turtle backwards.
|
|
|
bk(len)
Alias for #back
|
|
|
clean()
Removes the turtle curve from the board.
|
|
|
Removes the turtle completely and resets it to its initial position and direction.
|
|
| <private> |
copyAttr(key, val)
Set a future attribute of the turtle.
|
|
cs()
Alias for #clearScreen
|
|
|
evalAt(t)
the "co"-coordinate of the turtle curve at position t is returned.
|
|
|
fd(len)
Alias for #forward
|
|
|
forward(len)
Move the turtle forward.
|
|
|
hasPoint(x, y)
Checks whether (x,y) is near the curve.
|
|
|
Sets the visibility of the turtle head to false,
|
|
|
home()
Moves the turtle to position [0,0].
|
|
|
ht()
Alias for #hideTurtle
|
|
| <private> |
init(x, y, dir)
Initialize a new turtle or reinitialize a turtle after JXG.Turtle#clearScreen.
|
|
left(angle)
Rotate the turtle direction to the right.
|
|
|
lookTo(target)
Rotates the turtle into a new direction.
|
|
|
lt(angle)
Alias for #left
|
|
|
maxX()
Gives the upper bound of the parameter if the the turtle is treated as parametric curve.
|
|
|
minX()
Gives the lower bound of the parameter if the the turtle is treated as parametric curve.
|
|
|
moveTo(target)
Moves the turtle to a given coordinate pair.
|
|
|
pd()
Alias for #penDown
|
|
|
penDown()
Pen down, continues visible drawing
|
|
|
penUp()
Pen up, stops visible drawing
|
|
|
pop()
Alias for #popTurtle
|
|
|
Gets the last position of the turtle on the stack, sets the turtle to this position and removes this
position from the stack.
|
|
|
pu()
Alias for #penUp
|
|
|
push()
Alias for #pushTurtle
|
|
|
Pushes the position of the turtle on the stack.
|
|
|
right(angle)
Rotate the turtle direction to the right
|
|
|
rt(angle)
Alias for #right
|
|
|
setAttribute(attributes)
Sets properties of the turtle, see also JXG.GeometryElement#setAttribute.
|
|
|
setHighlightPenColor(color)
Sets the highlight pen color.
|
|
|
setPenColor(color)
Sets the pen color.
|
|
|
setPenSize(size)
Sets the pen size.
|
|
|
setPos(x, y)
Moves the turtle without drawing to a new position
|
|
|
Sets the visibility of the turtle head to true,
|
|
|
st()
Alias for #showTurtle
|
|
|
X(t)
if t is not supplied the x-coordinate of the turtle is returned.
|
|
|
Y(t)
if t is not supplied the y-coordinate of the turtle is returned.
|
|
|
Z(t)
|
Class Detail
JXG.Turtle(board, parents, attributes)
Constructs a new Turtle object.
- Parameters:
- {JXG.Board} board
- The board the new turtle is drawn on.
- {Array} parents
- Start position and start direction of the turtle. Possible values are [x, y, angle] [[x, y], angle] [x, y] [[x, y]]
- {Object} attributes
- Attributes to change the visual properties of the turtle object All angles are in degrees.
Method Detail
{JXG.Turtle}
back(len)
Move the turtle backwards.
- Parameters:
- {Number} len
- of backwards move in user coordinates
- Returns:
- {JXG.Turtle} pointer to the turtle object
bk(len)
Alias for #back
- Parameters:
- len
{JXG.Turtle}
clean()
Removes the turtle curve from the board. The turtle stays in its position.
- Returns:
- {JXG.Turtle} pointer to the turtle object
{JXG.Turtle}
clearScreen()
Removes the turtle completely and resets it to its initial position and direction.
- Returns:
- {JXG.Turtle} pointer to the turtle object
<private>
{Object}
copyAttr(key, val)
Set a future attribute of the turtle.
- Parameters:
- {String} key
- {Number|String} val
- Returns:
- {Object} pointer to the attributes object
cs()
Alias for #clearScreen
{Number}
evalAt(t)
the "co"-coordinate of the turtle curve at position t is returned.
- Parameters:
- {Number} t
- parameter
- {String} co.
- Either 'X' or 'Y'.
- Returns:
- {Number} x-coordinate of the turtle position or x-coordinate of turtle at position t
fd(len)
Alias for #forward
- Parameters:
- len
{JXG.Turtle}
forward(len)
Move the turtle forward.
- Parameters:
- {Number} len
- of forward move in user coordinates
- Returns:
- {JXG.Turtle} pointer to the turtle object
{Boolean}
hasPoint(x, y)
Checks whether (x,y) is near the curve.
- Parameters:
- {Number} x
- Coordinate in x direction, screen coordinates.
- {Number} y
- Coordinate in y direction, screen coordinates.
- Returns:
- {Boolean} True if (x,y) is near the curve, False otherwise.
{JXG.Turtle}
hideTurtle()
Sets the visibility of the turtle head to false,
- Returns:
- {JXG.Turtle} pointer to the turtle object
{JXG.Turtle}
home()
Moves the turtle to position [0,0].
- Returns:
- {JXG.Turtle} pointer to the turtle object
ht()
Alias for #hideTurtle
<private>
init(x, y, dir)
Initialize a new turtle or reinitialize a turtle after JXG.Turtle#clearScreen.
- Parameters:
- x
- y
- dir
{JXG.Turtle}
left(angle)
Rotate the turtle direction to the right.
- Parameters:
- {Number} angle
- of the rotation in degrees
- Returns:
- {JXG.Turtle} pointer to the turtle object
{JXG.Turtle}
lookTo(target)
Rotates the turtle into a new direction.
There are two possibilities:
- Parameters:
- {Number|Array} target
- If a number is given, it is interpreted as the new direction to look to; If an array consisting of two Numbers is given targeted is used as a pair coordinates.
- Returns:
- {JXG.Turtle} pointer to the turtle object
lt(angle)
Alias for #left
- Parameters:
- angle
maxX()
Gives the upper bound of the parameter if the the turtle is treated as parametric curve.
May be overwritten in @see generateTerm.
minX()
Gives the lower bound of the parameter if the the turtle is treated as parametric curve.
{JXG.Turtle}
moveTo(target)
Moves the turtle to a given coordinate pair.
The direction is not changed.
- Parameters:
- {Array} target
- Coordinates of the point where the turtle looks to.
- Returns:
- {JXG.Turtle} pointer to the turtle object
pd()
Alias for #penDown
{JXG.Turtle}
penDown()
Pen down, continues visible drawing
- Returns:
- {JXG.Turtle} pointer to the turtle object
{JXG.Turtle}
penUp()
Pen up, stops visible drawing
- Returns:
- {JXG.Turtle} pointer to the turtle object
pop()
Alias for #popTurtle
{JXG.Turtle}
popTurtle()
Gets the last position of the turtle on the stack, sets the turtle to this position and removes this
position from the stack.
- Returns:
- {JXG.Turtle} pointer to the turtle object
pu()
Alias for #penUp
push()
Alias for #pushTurtle
{JXG.Turtle}
pushTurtle()
Pushes the position of the turtle on the stack.
- Returns:
- {JXG.Turtle} pointer to the turtle object
{JXG.Turtle}
right(angle)
Rotate the turtle direction to the right
- Parameters:
- {Number} angle
- of the rotation in degrees
- Returns:
- {JXG.Turtle} pointer to the turtle object
rt(angle)
Alias for #right
- Parameters:
- angle
{JXG.Turtle}
setAttribute(attributes)
Sets properties of the turtle, see also JXG.GeometryElement#setAttribute.
Sets the property for all curves of the turtle in the past and in the future.
- Parameters:
- {Object} attributes
- key:value pairs
- Returns:
- {JXG.Turtle} pointer to the turtle object
{JXG.Turtle}
setHighlightPenColor(color)
Sets the highlight pen color. Equivalent to setAttribute({highlightStrokeColor:color})
but affects only the future turtle.
- Parameters:
- {String} color
- Returns:
- {JXG.Turtle} pointer to the turtle object
{JXG.Turtle}
setPenColor(color)
Sets the pen color. Equivalent to setAttribute({strokeColor:color})
but affects only the future turtle.
- Parameters:
- {String} color
- Returns:
- {JXG.Turtle} pointer to the turtle object
{JXG.Turtle}
setPenSize(size)
Sets the pen size. Equivalent to setAttribute({strokeWidth:size})
but affects only the future turtle.
- Parameters:
- {Number} size
- Returns:
- {JXG.Turtle} pointer to the turtle object
{JXG.Turtle}
setPos(x, y)
Moves the turtle without drawing to a new position
- Parameters:
- {Number} x
- new x- coordinate
- {Number} y
- new y- coordinate
- Returns:
- {JXG.Turtle} pointer to the turtle object
{JXG.Turtle}
showTurtle()
Sets the visibility of the turtle head to true,
- Returns:
- {JXG.Turtle} pointer to the turtle object
st()
Alias for #showTurtle
{Number}
X(t)
if t is not supplied the x-coordinate of the turtle is returned. Otherwise
the x-coordinate of the turtle curve at position t is returned.
- Parameters:
- {Number} t
- parameter
- Returns:
- {Number} x-coordinate of the turtle position or x-coordinate of turtle at position t
{Number}
Y(t)
if t is not supplied the y-coordinate of the turtle is returned. Otherwise
the y-coordinate of the turtle curve at position t is returned.
- Parameters:
- {Number} t
- parameter
- Returns:
- {Number} x-coordinate of the turtle position or x-coordinate of turtle at position t
{Number}
Z(t)
- Parameters:
- t
- Returns:
- {Number} z-coordinate of the turtle position


Well it all started with a trip to Matamoros, Mexico. A little border town of Texas near Brownsville and Padre Island. I went down there to party and party is what I did. I came back with a shitload of xanax and valiums, and a bottle of Oxycontin. All week long I was taking more than the reccomended dosage of pills. Usually around 3 or 4 valiums and 2 xanax at night time before bed. Man did I sleep well!!! I usually woke up feeling better than the night before looking forward to the night time when I could dose up again. During the day I would usually take about 2 to 3 Oxycontin's.
I would be feeling pretty good, and then it would be night time once more and then I could take my usual dose of valiums and xanax along with my prescribed dose of 20 mg daily paxil.  It was saturday night and I was staying at my friends house cuz I was going to go to church with her the next day, well I didnt make it to church the next morning as planned. I overdosed on valiums and Xanax.
I had taken 9 valiums with 3 xanax, two oxycontins, and my paxil. Well that night my dad had said somthing to me that I didnt believe. He had told me that all week he had noticed that I was on something, but that he didn't know what. I had felt 'normal' all week and for him to say something like that, well I didn't believe him so I continued on using until that night. All I remember was that I was kneeling down trying to say a prayer before bed and I kept nodding off. Until my friend just told me to go to bed. The next time I was able to talk was 3 days later after I awoke from my coma.
My friend says that the next morning when she tried to wake me up that I was just unresponsive. She then saw that I had puked pink stuff all over myself and that I was making some kind of garggling noise like I was choking. She then called 911 and had me picked up at her house. I awoke from my coma about 3 days later to see all my family and friends gathered around me like it was my funeral. Seeing my mom crying was probably the hardest thing to see. The side effects were horrible as well, I noticed that I had trouble thinking of anything for long periods of time and I just seemed kind of spaced out.
I couldn't even remember parts of my trip to Mexico or other events that have happened in my life.  I used to be a very outgoing person able to liven any party and able to talk my way into or out of anything. Like jobs.  Definitely better than I used to be but still not 100% better. I have trouble taking to anybody. Even my friends and family. It's like I can think of many things to say but they just don't come out of my mouth. So my friend who saved me always tells me that I am just not the same which makes me feel so great! And Another thing is that I used to be pretty heavy into raving and dancing, and its like I have forgotten how to dance at all. I can hardly move my legs at all which sucks.

Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


Data
struct Data : ReferenceConvertible, Equatable, Hashable, RandomAccessCollection, MutableCollection, RangeReplaceableCollection, MutableDataProtocol, ContiguousBytes
-
Auxiliar method to split a data into smaller packets with a maximum defined size.
Declaration
Swift
func dataPacketsWithMaximumSize(_ size: Int) -> [Data]
Parameters
size
Maximum size for a packet
Return Value
NSData array with data splitted into packets
-
The CRC16 calculated using CRC-CCITT (0xFFFF) method with 0x1021 polynomial.
Declaration
Swift
var CRC16: UInt16 { get }
-
Calculates the CRC16 for the data and appends it to the end.
The CRC16 is calculated using the CRC-CCITT (
0xFFFF
) method with0x1021
polynomial.Declaration
Swift
public func dataWithCRC16() -> Data
Return Value
A new NSData object with the CRC16 appended to the end.
-
Verifies the data with CRC16 check. The CRC16 must be at the end of this object.
Declaration
Swift
public func checkCRC16() -> Bool
Return Value
true
if the check is successful andfalse
otherwise. -
Gets Base32 Encoded String
Declaration
Swift
public func base32EncodedString() -> String
Return Value
Base3D Encoded String


| package xdc.runtime |
|
Basic runtime support for RTSC programs
The modules and interfaces in the
xdc.runtime package form the "core"
RTSC target runtime support library which provides basic system services
required by virtually all applications.
[
more ... ]
package xdc.runtime [2, 1, 0] {
// Interface for supporting filtering of Log events by detail level
// Interface implemented by all gate providers
// Interface to heap functions
// Common instance params
// Interface to service Log events
// Base interface for all modules
// Interface to core system functions
// Timestamp Client Interface
// Timestamp provider interface
// Runtime assertion manager
// Default attributes inherited by all target modules
// Diagnostics manager
// Runtime error manager
// Critical section support
// Growth-only based heap implementation
// Malloc/free based heap implementation
// Event logging manager
// A logger which stores Log events in a buffer
// A logger that passes events to a user supplied callback function
// A logger which routes events to the System_printf function
// Configuration "stand-in" for application code
// Static and run-time memory manager
// Register modules that are not statically configured
// Startup reset function manager
// The Rta module contains target and configuration code for providing RTA
support
// The xdc.runtime startup bootstrap
// ISystemSupport implementation for user callback functions
// Basic system services
// Runtime text handling services
// Timestamp services
// Basic constants and types
}
DETAILS
The modules and interfaces in the xdc.runtime package form the "core"
RTSC target runtime support library which provides basic system services
required by virtually all applications.
Since this package's services are intended to be available to any C/C++
client, this package does not contain any pre-compiled libraries. Instead,
this package provides complete sources which are built and supplied by a
target-specific package named by the
rts
parameter of the target used to build the client sources. This "indirection"
makes it possible for new targets to be added by interested parties whithout
ever having to update this package.
The functionality provided by this package can be roughly partitioned
into four categories:
- Diagnostics and Logs
- Memory Management
- Concurrency Support
- Startup and Shutdown
DIAGNOSTICS AND LOGS
This package provides for diagnostics with a set of modules that operate
together to configure and implement diagnostics.
The modules can be partitioned into three groups: modules that generate
events, a module that allows precise control over when (or if) various
events are generated, and modules that manage the output or display of the
events.
Assert,
Error, and
Log provide methods that
are added to source code and generate events. The
Diags module
provides both configuration and runtime methods to selectively enable or
disable different types of events on a per module basis. Finally,
LoggerBuf,
LoggerSys and
LoggerCallback are
simple alternative implementations of the
ILogger event "handler"
interface. You can provide more sophisticated or platform-specific
implementations of
ILogger without making any changes to code that
uses
Assert,
Log,
Error, or
Diags.
The diagnostics and logger modules include the following:
- Assert - Add integrity checks to the code.
- Diags - Manage a module's diagnostics mask.
- Error - Raise error events.
- Log - Generate log events in realtime.
- LoggerBuf - A logger using a buffer for log events.
- LoggerCallback - A logger using user defined callback function
for log events.
- LoggerSys - A logger using printf for log events.
- Types - Define diagnostics configuration parameters.
- Timestamp - Simple timestamp service
MEMORY MANAGEMENT
The memory management modules include the following:
- Memory - module used by clients to allocate and free memory
- HeapMin - Deterministic implementation that minimizes code
size footprint by not supporting reuse of allocated
memory.
- HeapStd - Implementation that builds atop ANSI C malloc()
and free()
CONCURRENCY SUPPORT
The concurency support modules include the following:
- Gate - module used by clients to serialize access to
shared data structures
- GateNull - "null" implementation for applications that
don't need serialization; e.g., single threaded
applications
STARTUP AND SHUTDOWN
The system startup and shutdown support modules include:
- Reset - Manages platform-specific startup initialization
before main() is called
- Startup - Manages "portable" startup initialization before
main() is called
- System - In addition to other basic services (such as
printf), this module provides an atexit
capability that allows modules to cleanly exit
during normal application terminiation.
- SysCallback - Implementation of ISystemSupport
that calls back user defined functions.
- SysMin - Minimal implementation of ISystemSupport
required by the System module, suitable for
deeply embedded applications.
- SysStd - Implementation of ISystemSupport
that relies on ANSI C Standard I/O Library
functions.
generated on Wed, 28 Aug 2019 17:00:50 GMT


(You
can search any file or page on this web site by following the steps found by
clicking on Search.)
Descendants of William Steele
[ Click on the red arrow for a shortcut to
the list of family trees on this site
s Click on the
blue question mark for assistance navigating among family trees
1 William Steele
b: 1825 d: 1893
... + Deborah Bracy
.. 2 George Washington Steele b: 1859
d: 1950 Pleasant Grove Cem, Ozark
..... + Anna Bigger b: 1861
d: 1937 Woodsfield, OH
....... 3 Arthur Steele
....... 3 Alfred (Fred) I. Steele b: Sept 23, 1886 d: Aug 2, 1981 Arizona
.......... + Ruth (unknown)
............
4 Raymond Steele
....... 3 Maude Nolie Steele b: Jan 7,
1889 d: 1921
.......... + Andrew Fulton b: Aug
4, 1886 d: Sept 12, 1934 Chicago,
Illinois
............
4 Glenn
(nmi) Steele b: Sept 15, 1908 Altitude, OH near
Woodsfield, OH d: Nov 27, 2000 St. Clairsville, OH at the Forrest Hill Retirement Community at
2:10 p.m.
...............
+ Mary Mabel Young b: June 30, 1911
Monroe Co., OH d: Feb 2, 1998 Wheeling,
WV at the Wheeling Hospital
.................
5 Norma Jean
Steele b: June 21, 1931
....................
+ David Mead Eells
b: Nov 15, 1932 d: April 25, 1996
......................
6 Tamara Lynn Eells b: Sept 21, 1955 England
.........................
+ Raymond Lee (Jr.) Tyler b: Nov 30, 1955 OH
...........................
7 Jessica Liegh
Tyler b: March 31, 1987
...........................
7 Richard Ian Tyler b: July 3, 1992
......................
6 Mark Eells b: March 17, 1958
.................
5 Glenna Joy Steele b: Nov 4, 1936 Woodsfield, OH
....................
+ Gary Ronald Graham b: Aug 12, 1936
Bloomfield, OH
......................
6 Gina Michelle Graham b: Oct 22, 1956
.........................
+ John Most b: May 14, 1957
...........................
7 Michelle Ren'ee
Most b: Dec 12, 1993
......................
6 Julie Ren'ee
Graham b: Nov 22, 1961
.........................
+ Jim Bacon
...........................
7 Adam James Bacon
......................
6 Gary Glen Graham b: June 30, 1967
.........................
+ Dawn Halton
...........................
7 Mackenzie Steele Graham b: Feb 20, 1995
......................
6 Jodi Leigh Graham b: April 10, 1971
.........................
+ Paul Pacek
b: May 28, 1972
.................
5 Janet Sue Steele b: Feb 14, 1944 Woodsfield, OH (at home)
....................
+ John Charles Pember b: Oct 2, 1944
Washington, D.C.
......................
6 John Craig Pember b: Dec 6, 1969 Circleville, OH
.........................
+ Leslie Suzanne Cobble b: April 6, 1967
...........................
7 Lauren Grace Pember b: Sept 9, 2002
.................
5 Rita Ann Steele b: July 29, 1945 d: May 14, 2005 Alpharetta, GA obit
....................
+ Bernard Braverman b: Jan 25, 1931
....... 3 Cecil Brace Steele b: July 16, 1892
....... 3 Mary Audrey Steele b: Nov 9, 1893 d: July 18, 1979 In Barnesville, OH
.......... + Frank Hamilton
....... 3 Raymond Steele b: Feb 27, 1896
....... 3 George Roy Steele b: May 3, 1900 d: 1992
.......... + Mary Starkey
....... 3 Oliver Russell Steele b: Dec 3, 1905
Provided by: e-mail:
Richard
Harrington
Last Modified on February 26, 2011 by reh
Click here for the Short-Cut Table of Contents


Step 3: Run Your Application
Before running your application, make it sure you have copied the
assembly containing compact types (if it is using Read-Through/Write-Through) in the 'Service' folder of NCache installation
directory (%INSTALL_DIR%/NCache/bin/service).
Also, make sure compact types are registered with
the cache and cache is running if it is
configured as OutProc cache. You may see the statistics of the cache
through statistics window.
See Also
Register Compact Types with NCache


TypeHandlerSpace provides a JAX-RS Root Resource Class that delegates requests in its URI space (i.e. URIs starting with the prefix the bundle is installed with) to a TypeHandler for the RDF-Type(s) of the resource named by the requested URI. TypeHandlerSpace works on the clerezza.org platform it interacts with Triaxrs and with SCB and expects content and system graph to be located as per the platform conventions.
While JAX-RS allows to bind Root Resources Classes to a specific
URI-Path TypeHandlerSpace allows to bind such resources to an rdf:type
.
Root Resources are POJO providing methods handling different types of
requests, with TypeHandlerSpace such POJOs can be bound to an RDF type
in this function the class is called TypeHandler
. When a
request is processed by TypeHandlerSpace the rdf:type
s of
the requested resource are determined from the content graph.
TypeHandlerSpace provides a root resource org.apache.clerezza.platform.typehandlerspace.TypeHandlerSpace
which determines the type(s) of requested resource and calls a service
of org.apache.clerezza.platform.typehandlerspace.TypeHandlerDiscovery
to get a Typehandler
, the request is the forwarded to this
TypeHandler
The provided implementation of TypeHandlerDiscovery
returns the available TypeHandler
for the rdf:type
with the highest priority. The Priority of rdf:type
s is
determined by an rdf:List
named
<urn:x-localinstance:/typePriorityList> in the system graph. The
actual TypeHandler
s are OSGi services exposing java.lang.Object
as service interface and with the property org.apache.clerezza.platform.typehandler=true
.
TypeHandler
s are annotated with the org.apache.clerezza.platform.typehandlerspace.SupportedTypes
annotation defining the rdf:type
s supported by the class.
The following defines a class that is both a regular JAX-RS Root
Resource Class as well as a TypeHandler
for
<http://example.org/ontology#MyType>.
Sub-resource methods in TypeHandler
s are never invoked by TypeHandlerSpace, so they are only
useful if a typeHandler is also used as regular JAX-RS Root Resource.


BY EDWIN JAHIEL
TOPSY-TURVY (U.K., 1999) **** Written and directed by Mike Leigh. Photography, Dick Pope. Editing, Robin Sales. Music,Carl Davis (from Arthur Sullivan's). Production design , Eve Stewart. Produced by Simon Channing-Williams. Cast: Dorothy Atkinson (Jessie Bond), Jim Broadbent (W. S. Gilbert), Ron Cook (Richard D'Oyly Carte), Allan Corduner (Arthur Sullivan), Eleanor David (Fanny Ronalds), Shirley Henderson (Leonora Braham), Lesley Manville (Lucy Gilbert), Kevin McKidd (Durward Lely), Wendy Nottingham (Helen Lenoir), Martin Savage (George Grossmith), Timothy Spall (Richard Temple), Alison Steadman (Madame Leon) and many others. A USA Films release. 160 minutes. PG
Delicious is the word for this labor of love and love for the theater. Delicious like a long, leisurely gourmet meal of "haute cuisine" which lasts for hours, has an unhurried pace, makes time pass most pleasurably, brings in course after course, and progresses with interesting conversations.
Writer-director Mike Leigh has carved a special film-niche for himself with very British movies that reveal extraordinary things about ordinary working-class people: High Hopes, Life Is Sweet, Naked, Secrets and Lies, et al. He (and his actors) have been awarded a host of major prizes. And that's not counting Leigh's activities in the theater, and with TV films which also get theatrical releases.
In Topsy-Turvy Leigh deals with the team of librettist W.S. Gilbert (1836-1911) and composer Arthur Sullivan (1842-1900) or Sir Arthur after he was knighted in 1883. There's also a third man, impresario-manager D'Oyly Carte (1844-1901).
Even though one my cats is called Yum-Yum, I am no G & S aficionado. Yet I appreciate how distinctive and novel their works were and how they brought out another side of staid Victorianism.
Compared to the familiar hoi polloi characters in the other Leigh movies, the "showbiz" people of Topsy-Turvy are downright patrician. They appear not in the old genre of artists' biopic but within a limited time-frame which allows depth and details.
It begins in 1884, when the latest G & S production, Princess Ida, was not well received. By G & S standards, it's a flop. The team's first collaboration, Trial by Jury, had been followed by several hits: The Sorcerer, H.M.S. Pinafore, The Pirates of Penzance, Patience , and Iolanthe. Princess Ida may have not deserved its unsuccess, but certainly Ida is no Aida. Not that one can compare hefty Grand Operas and their Bel Canto to the comic operettas that G & S invented.
Sir Arthur, bedridden with painful kidney trouble, still finds the strength to get to the Savoy Theater and conduct the orchestra. (His expressive face as he mouths the score is a marvel). But he also suffers from the musical ambition to compose, as he had in his early career, serious music. Princess Ida is the last straw. " I can't waste any more time on these trivial soufflés" he tells Carte.
Sir Arthur takes a break by going to the Continent. He is a bon vivant whose appreciation of French food and, in a Paris bordello, of a topless singing duo of ladies, bring out his "joie de vivre" and wit. It's charming.. But by the time Gilbert reads him his latest libretto, Sullivan has had it with topsy-turvy, formulaic plots.
The film's 160 minutes never drag or fatigue. And I say this as the founder of the BBNMM movement -- Bring Back the Ninety Minute Movie. We are treated (and it is a treat) to wonderfully calibrated Victoriana: interiors, artifacts, people; character and personality-revealing talk; thoughts on creativity and art; the business side of productions; insights into private lives. Every minute brings something of interest, and many skillfully brief moments stand for full situations.
Topsy-Turvy revels in contrasts especially between lively man-about-town Sullivan and. serious, often dour Gilbert. The choice of words and images has the effortless feeling that comes from intelligent preparations. "Echt" British humor and educated wit are both a contrast to and a supplement of the funny singing patter of the G & S productions.
The partners are on the verge of breaking up permanently when smart Mrs. Gilbert (who like all the supporting characters is painted with forceful economy) drags her husband to a novelty, an Exposition of Japanese culture. Kabuki, dances, music and other Japanese exotica suddenly set Gilbert on his operetta road to Damascus. Thus is The Mikado born in 1885.
All this is dealt with a succession of cleverly edited scenes. Gilbert, who has bought a Japanese sword, plays with it. Cut to G & S together again, reading a new script. Cut to February 12, 1885, when dire, Empire-shaking news reaches England: General "Chinese" Gordon and his men in besieged Khartoum were massacred on January 26 by the Mahdi's rebel Sudanese. Cut to performers-to-be in The Mikado gorging themselves with oysters --and soon becoming sick. Life does go on.
The acting, from tiny to main roles, is flawless. Smart, telling, enjoyable moments, scenes or sequences abound. The funniest have Gilbert rehearsing his cast and thus becoming like a modern stage director. He has Japanese ladies show his performers how to stand, walk, and deploy fans. He instructs others on delivering lines. (Was Leigh partly inspired by Truffaut's film-within-film mishaps in Day for Night?). It is high comedy, doubly impressive when one thinks of the movie's cast rehearsing how to handle The Mikado's rehearsals. Especially since Mike Leigh and his people, in plays and movies, do not work in kosher ways. There are no standard scripts; everything derives from interaction, invention and improvisation. Assuming that process was also used in Topsy-Turvy, the approach results in wonderful smoothness and dovetailing.
There is even suspense .Gilbert cuts out the song of a performer (who recalls Robert Morley). Will he reinstate it? Will the key actor who shoots drugs, the actress wih a bad leg, or the actress who drinks, affect the performance?
One gets here many films for the price of one. G & S's life and works; how "An Operetta Is Born"; authentic shoptalk; backstage life of total verisimilitude --the best I know of-- and more. Technical aspects are brilliant. But the press seems to neglect the contribution of a major collaborator. Composer Carl Davis, born in Brooklyn but a longtime resident in England, though well-known in inner circles is not a name familiar to the public. Yet his output is huge and magnificent. Davis's scores include theatrical films (he won the British music award for The French Lieutenant's Woman); many TV films (Channel 4, BBC, etc.) that have often been released as "regular" movies or appeared on PBS; TV series from the UK; documentary series such as The World at War, The Unknown Chaplin, Cinema Europe: The Other Hollywood. His new scores for silent classics (Intolerance, Ben-Hur, The Eagle, Greed, etc.) are the best ever. Prodigious Davis is the top film composer of our day, yet no one of my acquaintance knows him, except for maestro-pianist Ian Hobson who has recorded with him in England and admires him.
A final thought. Other operettas, e.g. by Vienna's Johann Strauss, by the Hungarian-born Franz Lehar, or by France's Offenbach, have traveled very well. But the untranslatable texts of W.S. Gilbert have limited the G & S repertory to English-speaking countries. Topsy-Turvy, in spite of getting two New York Film Critics Award (Best Film, Best Director) may also meet with this fate.
"Le mauvais gout mene au crime"(Stendhal)
Edwin Jahiel's film reviews are at: http://www.prairienet.org/ejahiel/
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


Class: Aws::MediaConvert::Types::Av1Settings
| Relationships & Source Files | |
| Super Chains via Extension / Inclusion / Inheritance | |
|
Class Chain:
self,
Struct
|
|
|
Instance Chain:
self,
::Aws::Structure ,
Struct
|
|
| Inherits: |
Struct
|
| Defined in: | gems/aws-sdk-mediaconvert/lib/aws-sdk-mediaconvert/types.rb |
Overview
Required when you set Codec, under VideoDescription>CodecSettings to the value AV1.
Constant Summary
Instance Attribute Summary
-
#adaptive_quantization ⇒ String
rw
Specify the strength of any adaptive quantization filters that you enable.
-
#bit_depth ⇒ String
rw
Specify the Bit depth.
-
#framerate_control ⇒ String
rw
Use the Framerate setting to specify the frame rate for this output.
-
#framerate_conversion_algorithm ⇒ String
rw
Choose the method that you want
::Aws::MediaConvert
to use when increasing or decreasing the frame rate. -
#framerate_denominator ⇒ Integer
rw
When you use the API for transcode jobs that use frame rate conversion, specify the frame rate as a fraction.
-
#framerate_numerator ⇒ Integer
rw
When you use the API for transcode jobs that use frame rate conversion, specify the frame rate as a fraction.
-
#gop_size ⇒ Float
rw
Specify the GOP length (keyframe interval) in frames.
-
#max_bitrate ⇒ Integer
rw
Maximum bitrate in bits/second.
-
#number_b_frames_between_reference_frames ⇒ Integer
rw
Specify from the number of B-frames, in the range of 0-15.
-
#qvbr_settings ⇒ Types::Av1QvbrSettings
rw
Settings for quality-defined variable bitrate encoding with the H.265 codec.
-
#rate_control_mode ⇒ String
rw
'With AV1 outputs, for rate control mode,
::Aws::MediaConvert
supports only quality-defined variable bitrate (QVBR). -
#slices ⇒ Integer
rw
Specify the number of slices per picture.
-
#spatial_adaptive_quantization ⇒ String
rw
Keep the default value, Enabled, to adjust quantization within each frame based on spatial variation of content complexity.
Instance Method Summary
::Aws::Structure
- Included
| #to_hash | Alias for Structure#to_h. |
Instance Attribute Details
#adaptive_quantization ⇒ String
(rw)
Specify the strength of any adaptive quantization filters that you enable. The value that you choose here applies to Spatial adaptive quantization.
# File 'gems/aws-sdk-mediaconvert/lib/aws-sdk-mediaconvert/types.rb', line 1115
class Av1Settings < Struct.new( :adaptive_quantization, :bit_depth, :framerate_control, :framerate_conversion_algorithm, :framerate_denominator, :framerate_numerator, :gop_size, :max_bitrate, :number_b_frames_between_reference_frames, :qvbr_settings, :rate_control_mode, :slices, :spatial_adaptive_quantization) SENSITIVE = [] include Aws::Structure end
#bit_depth ⇒ String
(rw)
Specify the Bit depth. You can choose 8-bit or 10-bit.
# File 'gems/aws-sdk-mediaconvert/lib/aws-sdk-mediaconvert/types.rb', line 1115
class Av1Settings < Struct.new( :adaptive_quantization, :bit_depth, :framerate_control, :framerate_conversion_algorithm, :framerate_denominator, :framerate_numerator, :gop_size, :max_bitrate, :number_b_frames_between_reference_frames, :qvbr_settings, :rate_control_mode, :slices, :spatial_adaptive_quantization) SENSITIVE = [] include Aws::Structure end
#framerate_control ⇒ String
(rw)
Use the Framerate setting to specify the frame rate for this output. If you want to keep the same frame rate as the input video, choose Follow source. If you want to do frame rate conversion, choose a frame rate from the dropdown list or choose Custom. The framerates shown in the dropdown list are decimal approximations of fractions. If you choose Custom, specify your frame rate as a fraction.
# File 'gems/aws-sdk-mediaconvert/lib/aws-sdk-mediaconvert/types.rb', line 1115
class Av1Settings < Struct.new( :adaptive_quantization, :bit_depth, :framerate_control, :framerate_conversion_algorithm, :framerate_denominator, :framerate_numerator, :gop_size, :max_bitrate, :number_b_frames_between_reference_frames, :qvbr_settings, :rate_control_mode, :slices, :spatial_adaptive_quantization) SENSITIVE = [] include Aws::Structure end
#framerate_conversion_algorithm ⇒ String
(rw)
Choose the method that you want ::Aws::MediaConvert
to use when increasing
or decreasing the frame rate. For numerically simple conversions,
such as 60 fps to 30 fps: We recommend that you keep the default
value, Drop duplicate. For numerically complex conversions, to avoid
stutter: Choose Interpolate. This results in a smooth picture, but
might introduce undesirable video artifacts. For complex frame rate
conversions, especially if your source video has already been
converted from its original cadence: Choose FrameFormer to do
motion-compensated interpolation. FrameFormer uses the best
conversion method frame by frame. Note that using FrameFormer
increases the transcoding time and incurs a significant add-on cost.
When you choose FrameFormer, your input video resolution must be at
least 128x96.
# File 'gems/aws-sdk-mediaconvert/lib/aws-sdk-mediaconvert/types.rb', line 1115
class Av1Settings < Struct.new( :adaptive_quantization, :bit_depth, :framerate_control, :framerate_conversion_algorithm, :framerate_denominator, :framerate_numerator, :gop_size, :max_bitrate, :number_b_frames_between_reference_frames, :qvbr_settings, :rate_control_mode, :slices, :spatial_adaptive_quantization) SENSITIVE = [] include Aws::Structure end
#framerate_denominator ⇒ Integer
(rw)
When you use the API for transcode jobs that use frame rate conversion, specify the frame rate as a fraction. For example, 24000 / 1001 = 23.976 fps. Use FramerateDenominator to specify the denominator of this fraction. In this example, use 1001 for the value of FramerateDenominator. When you use the console for transcode jobs that use frame rate conversion, provide the value as a decimal number for Framerate. In this example, specify 23.976.
# File 'gems/aws-sdk-mediaconvert/lib/aws-sdk-mediaconvert/types.rb', line 1115
class Av1Settings < Struct.new( :adaptive_quantization, :bit_depth, :framerate_control, :framerate_conversion_algorithm, :framerate_denominator, :framerate_numerator, :gop_size, :max_bitrate, :number_b_frames_between_reference_frames, :qvbr_settings, :rate_control_mode, :slices, :spatial_adaptive_quantization) SENSITIVE = [] include Aws::Structure end
#framerate_numerator ⇒ Integer
(rw)
When you use the API for transcode jobs that use frame rate conversion, specify the frame rate as a fraction. For example, 24000 / 1001 = 23.976 fps. Use FramerateNumerator to specify the numerator of this fraction. In this example, use 24000 for the value of FramerateNumerator. When you use the console for transcode jobs that use frame rate conversion, provide the value as a decimal number for Framerate. In this example, specify 23.976.
# File 'gems/aws-sdk-mediaconvert/lib/aws-sdk-mediaconvert/types.rb', line 1115
class Av1Settings < Struct.new( :adaptive_quantization, :bit_depth, :framerate_control, :framerate_conversion_algorithm, :framerate_denominator, :framerate_numerator, :gop_size, :max_bitrate, :number_b_frames_between_reference_frames, :qvbr_settings, :rate_control_mode, :slices, :spatial_adaptive_quantization) SENSITIVE = [] include Aws::Structure end
#gop_size ⇒ Float
(rw)
Specify the GOP length (keyframe interval) in frames. With AV1,
::Aws::MediaConvert
doesn't support GOP length in seconds. This value must
be greater than zero and preferably equal to 1 + ((numberBFrames +
1) * x), where x is an integer value.
# File 'gems/aws-sdk-mediaconvert/lib/aws-sdk-mediaconvert/types.rb', line 1115
class Av1Settings < Struct.new( :adaptive_quantization, :bit_depth, :framerate_control, :framerate_conversion_algorithm, :framerate_denominator, :framerate_numerator, :gop_size, :max_bitrate, :number_b_frames_between_reference_frames, :qvbr_settings, :rate_control_mode, :slices, :spatial_adaptive_quantization) SENSITIVE = [] include Aws::Structure end
#max_bitrate ⇒ Integer
(rw)
Maximum bitrate in bits/second. For example, enter five megabits per second as 5000000. Required when Rate control mode is QVBR.
# File 'gems/aws-sdk-mediaconvert/lib/aws-sdk-mediaconvert/types.rb', line 1115
class Av1Settings < Struct.new( :adaptive_quantization, :bit_depth, :framerate_control, :framerate_conversion_algorithm, :framerate_denominator, :framerate_numerator, :gop_size, :max_bitrate, :number_b_frames_between_reference_frames, :qvbr_settings, :rate_control_mode, :slices, :spatial_adaptive_quantization) SENSITIVE = [] include Aws::Structure end
#number_b_frames_between_reference_frames ⇒ Integer
(rw)
Specify from the number of B-frames, in the range of 0-15. For AV1 encoding, we recommend using 7 or 15. Choose a larger number for a lower bitrate and smaller file size; choose a smaller number for better video quality.
# File 'gems/aws-sdk-mediaconvert/lib/aws-sdk-mediaconvert/types.rb', line 1115
class Av1Settings < Struct.new( :adaptive_quantization, :bit_depth, :framerate_control, :framerate_conversion_algorithm, :framerate_denominator, :framerate_numerator, :gop_size, :max_bitrate, :number_b_frames_between_reference_frames, :qvbr_settings, :rate_control_mode, :slices, :spatial_adaptive_quantization) SENSITIVE = [] include Aws::Structure end
#qvbr_settings ⇒ Types::Av1QvbrSettings (rw)
Settings for quality-defined variable bitrate encoding with the H.265 codec. Use these settings only when you set QVBR for Rate control mode.
# File 'gems/aws-sdk-mediaconvert/lib/aws-sdk-mediaconvert/types.rb', line 1115
class Av1Settings < Struct.new( :adaptive_quantization, :bit_depth, :framerate_control, :framerate_conversion_algorithm, :framerate_denominator, :framerate_numerator, :gop_size, :max_bitrate, :number_b_frames_between_reference_frames, :qvbr_settings, :rate_control_mode, :slices, :spatial_adaptive_quantization) SENSITIVE = [] include Aws::Structure end
#rate_control_mode ⇒ String
(rw)
'With AV1 outputs, for rate control mode, ::Aws::MediaConvert
supports
only quality-defined variable bitrate (QVBR). You can''t use CBR
or VBR.'
# File 'gems/aws-sdk-mediaconvert/lib/aws-sdk-mediaconvert/types.rb', line 1115
class Av1Settings < Struct.new( :adaptive_quantization, :bit_depth, :framerate_control, :framerate_conversion_algorithm, :framerate_denominator, :framerate_numerator, :gop_size, :max_bitrate, :number_b_frames_between_reference_frames, :qvbr_settings, :rate_control_mode, :slices, :spatial_adaptive_quantization) SENSITIVE = [] include Aws::Structure end
#slices ⇒ Integer
(rw)
Specify the number of slices per picture. This value must be 1, 2, 4, 8, 16, or 32. For progressive pictures, this value must be less than or equal to the number of macroblock rows. For interlaced pictures, this value must be less than or equal to half the number of macroblock rows.
# File 'gems/aws-sdk-mediaconvert/lib/aws-sdk-mediaconvert/types.rb', line 1115
class Av1Settings < Struct.new( :adaptive_quantization, :bit_depth, :framerate_control, :framerate_conversion_algorithm, :framerate_denominator, :framerate_numerator, :gop_size, :max_bitrate, :number_b_frames_between_reference_frames, :qvbr_settings, :rate_control_mode, :slices, :spatial_adaptive_quantization) SENSITIVE = [] include Aws::Structure end
#spatial_adaptive_quantization ⇒ String
(rw)
Keep the default value, Enabled, to adjust quantization within each frame based on spatial variation of content complexity. When you enable this feature, the encoder uses fewer bits on areas that can sustain more distortion with no noticeable visual degradation and uses more bits on areas where any small distortion will be noticeable. For example, complex textured blocks are encoded with fewer bits and smooth textured blocks are encoded with more bits. Enabling this feature will almost always improve your video quality. Note, though, that this feature doesn't take into account where the viewer's attention is likely to be. If viewers are likely to be focusing their attention on a part of the screen with a lot of complex texture, you might choose to disable this feature. Related setting: When you enable spatial adaptive quantization, set the value for Adaptive quantization depending on your content. For homogeneous content, such as cartoons and video games, set it to Low. For content with a wider variety of textures, set it to High or Higher.
# File 'gems/aws-sdk-mediaconvert/lib/aws-sdk-mediaconvert/types.rb', line 1115
class Av1Settings < Struct.new( :adaptive_quantization, :bit_depth, :framerate_control, :framerate_conversion_algorithm, :framerate_denominator, :framerate_numerator, :gop_size, :max_bitrate, :number_b_frames_between_reference_frames, :qvbr_settings, :rate_control_mode, :slices, :spatial_adaptive_quantization) SENSITIVE = [] include Aws::Structure end


{% extends 'core/index.html' %} {% load static from staticfiles %} {% block styles %} {% endblock %} {% block body %}
Tweet Retrieval
All historic tweets within the site's dataset have been gathered using GetOldTweets-python tweet scraping api.
Find out more on GitHub
Data Rights
All tweets are sourced directly from the public Twitter timeline feed in accordance with Twitter's terms of service.
What is Sentiment Analysis?
To extrapolate opinion from a piece of text or corpora of texts is said to be the extraction of "Sentiment".
Sentiment can be around an emotion or regarding an entity, within Senticle50's analysis of the brexit debate both aspects are analysed.
Tweet Classification
All tweets within the dataset have undergone classification against:
- Sentiment
- Stance on Brexit
- Stance on Brexit (Inclusive of Sentiment)
Neural Network Analysis
The Neural Networks used in this project utilised Keras API
Real Time
Tweets are collected, tokenized, analysed and visualised within real time


Meet the Team
Cedric Ith
Front-end
As a sophomore at UW, Cedric is an aspiring web developer. His work on the team involved conceptializing and building the website from scratch.
Akshat Shrivastava
Back-end
Akshat is a very motivated and academic Computer Science student at the University of Washington. Starting his sophomore year now he has been eager to work at various companies and make his contribution to the tech world.
Robby Mitchell
Android Dev
Focused on the Android UI and node server communication with mobile services. Also helped with hardware integration on the bike chassis.
Joseph Zhong
Full Stack
Joseph learned his first line of code in 10th grade, and now an aspiring Computer Scientist and Business Major, Joseph has an ecstatic passion towards learning and applying new technologies from the ground up.
Trevor Hedges
Hardware Dev
Trevor is a sophomore in the Department of Aerospace at UW. He developed tech to measure RPM of a bicycle wheel and a system to send information to an Android device using Bluetooth.


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We're holding another two-day CukeUp! conference in New York City on Tuesday 30th Sept - Wednesday 1st October.
I missed last year's conference, and I love New York, so I'm delighted we're running it again. In fact, this year CukeUp! NYC has grown to two days. It's a fun and informal conference for everyone involed in BDD: product owners, business analysts, testers and programmers.
The first day will be a fast-paced firehose of 30-minute talks from people like Aslak Hellesøy, George Dinwiddie, Richard Lawerence, and Eric Evans.
The second day we'll dive deeper, with two half-day tutorials.
True to the spirit of BDD, you'll find that CukeUp! is a very friendly, collaborative conference. It's a chance for you to mix with the people who write the code and books you use every day, and to make new friends from the community. Don't be surprised if someone puts a whiteboard pen in your hand, especially on day 2!
Still reading? Why haven't you booked your ticket yet?


The quality is in the detail
LOOKBOOK 2016
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| PREV NEXT | FRAMES NO FRAMES |
| Packages that use MathException | |
|---|---|
| org.apache.commons.math | Common classes used throughout the commons-math library. |
| org.apache.commons.math.analysis.interpolation | Univariate real functions interpolation algorithms. |
| org.apache.commons.math.distribution | Implementations of common discrete and continuous distributions. |
| org.apache.commons.math.estimation | This package provided classes to solve estimation problems, it is deprecated since 2.0. |
| org.apache.commons.math.fraction | Fraction number type and fraction number formatting. |
| org.apache.commons.math.geometry | This package provides basic 3D geometry components. |
| org.apache.commons.math.linear | Linear algebra support. |
| org.apache.commons.math.ode | This package provides classes to solve Ordinary Differential Equations problems. |
| org.apache.commons.math.ode.events | This package provides classes to handle discrete events occurring during Ordinary Differential Equations integration. |
| org.apache.commons.math.optimization | This package provides common interfaces for the optimization algorithms provided in sub-packages. |
| org.apache.commons.math.optimization.linear | This package provides optimization algorithms for linear constrained problems. |
| org.apache.commons.math.random | Random number and random data generators. |
| org.apache.commons.math.special | Implementations of special functions such as Beta and Gamma. |
| org.apache.commons.math.stat.correlation | Correlations/Covariance computations. |
| org.apache.commons.math.stat.inference | Classes providing hypothesis testing and confidence interval construction. |
| org.apache.commons.math.stat.regression | Statistical routines involving multivariate data. |
| org.apache.commons.math.util | Convenience routines and common data structures used throughout the commons-math library. |
| Uses of MathException in org.apache.commons.math |
|---|
| Subclasses of MathException in org.apache.commons.math | |
|---|---|
class |
ArgumentOutsideDomainException
Error thrown when a method is called with an out of bounds argument. |
class |
ConvergenceException
Error thrown when a numerical computation can not be performed because the numerical result failed to converge to a finite value. |
class |
DimensionMismatchException
Deprecated. in 2.2 (to be removed in 3.0). Please use its equivalent from package org.apache.commons.math.exception . |
class |
DuplicateSampleAbscissaException
Exception thrown when a sample contains several entries at the same abscissa. |
class |
FunctionEvaluationException
Exception thrown when an error occurs evaluating a function. |
class |
MathConfigurationException
Signals a configuration problem with any of the factory methods. |
class |
MaxEvaluationsExceededException
Error thrown when a numerical computation exceeds its allowed number of functions evaluations. |
class |
MaxIterationsExceededException
Error thrown when a numerical computation exceeds its allowed number of iterations. |
| Uses of MathException in org.apache.commons.math.analysis.interpolation |
|---|
| Methods in org.apache.commons.math.analysis.interpolation that throw MathException | |
|---|---|
MultivariateRealFunction |
MicrosphereInterpolator.interpolate(double[][] xval,
double[] yval)
Computes an interpolating function for the data set. |
MultivariateRealFunction |
MultivariateRealInterpolator.interpolate(double[][] xval,
double[] yval)
Computes an interpolating function for the data set. |
UnivariateRealFunction |
UnivariateRealInterpolator.interpolate(double[] xval,
double[] yval)
Computes an interpolating function for the data set. |
PolynomialSplineFunction |
LoessInterpolator.interpolate(double[] xval,
double[] yval)
Compute an interpolating function by performing a loess fit on the data at the original abscissae and then building a cubic spline with a SplineInterpolator
on the resulting fit. |
PolynomialFunctionLagrangeForm |
NevilleInterpolator.interpolate(double[] x,
double[] y)
Computes an interpolating function for the data set. |
BivariateRealFunction |
SmoothingBicubicSplineInterpolator.interpolate(double[] xval,
double[] yval,
double[][] zval)
Deprecated. Computes an interpolating function for the data set. |
BivariateRealFunction |
BivariateRealGridInterpolator.interpolate(double[] xval,
double[] yval,
double[][] fval)
Computes an interpolating function for the data set. |
BicubicSplineInterpolatingFunction |
BicubicSplineInterpolator.interpolate(double[] xval,
double[] yval,
double[][] fval)
Computes an interpolating function for the data set. |
BicubicSplineInterpolatingFunction |
SmoothingPolynomialBicubicSplineInterpolator.interpolate(double[] xval,
double[] yval,
double[][] fval)
Computes an interpolating function for the data set. |
TricubicSplineInterpolatingFunction |
TricubicSplineInterpolator.interpolate(double[] xval,
double[] yval,
double[] zval,
double[][][] fval)
Computes an interpolating function for the data set. |
TrivariateRealFunction |
TrivariateRealGridInterpolator.interpolate(double[] xval,
double[] yval,
double[] zval,
double[][][] fval)
Computes an interpolating function for the data set. |
double[] |
LoessInterpolator.smooth(double[] xval,
double[] yval)
Compute a loess fit on the data at the original abscissae. |
double[] |
LoessInterpolator.smooth(double[] xval,
double[] yval,
double[] weights)
Compute a weighted loess fit on the data at the original abscissae. |
| Constructors in org.apache.commons.math.analysis.interpolation that throw MathException | |
|---|---|
LoessInterpolator(double bandwidth,
int robustnessIters)
Constructs a new LoessInterpolator
with given bandwidth and number of robustness iterations. |
|
LoessInterpolator(double bandwidth,
int robustnessIters,
double accuracy)
Constructs a new LoessInterpolator
with given bandwidth, number of robustness iterations and accuracy. |
| Uses of MathException in org.apache.commons.math.distribution |
|---|
| Methods in org.apache.commons.math.distribution that throw MathException | |
|---|---|
double |
GammaDistributionImpl.cumulativeProbability(double x)
For this distribution, X, this method returns P(X < x). |
double |
ChiSquaredDistributionImpl.cumulativeProbability(double x)
For this distribution, X, this method returns P(X < x). |
double |
TDistributionImpl.cumulativeProbability(double x)
For this distribution, X, this method returns P(X < x ). |
double |
FDistributionImpl.cumulativeProbability(double x)
For this distribution, X, this method returns P(X < x). |
double |
Distribution.cumulativeProbability(double x)
For a random variable X whose values are distributed according to this distribution, this method returns P(X ≤ x). |
double |
AbstractIntegerDistribution.cumulativeProbability(double x)
For a random variable X whose values are distributed according to this distribution, this method returns P(X ≤ x). |
double |
ExponentialDistributionImpl.cumulativeProbability(double x)
For this distribution, X, this method returns P(X < x). |
double |
BetaDistributionImpl.cumulativeProbability(double x)
For a random variable X whose values are distributed according to this distribution, this method returns P(X ≤ x). |
double |
NormalDistributionImpl.cumulativeProbability(double x)
For this distribution, X, this method returns P(X < x ). |
double |
Distribution.cumulativeProbability(double x0,
double x1)
For a random variable X whose values are distributed according to this distribution, this method returns P(x0 ≤ X ≤ x1). |
double |
AbstractIntegerDistribution.cumulativeProbability(double x0,
double x1)
For a random variable X whose values are distributed according to this distribution, this method returns P(x0 ≤ X ≤ x1). |
double |
BetaDistributionImpl.cumulativeProbability(double x0,
double x1)
For a random variable X whose values are distributed according to this distribution, this method returns P(x0 ≤ X ≤ x1). |
double |
AbstractDistribution.cumulativeProbability(double x0,
double x1)
For a random variable X whose values are distributed according to this distribution, this method returns P(x0 ≤ X ≤ x1). |
abstract double |
AbstractIntegerDistribution.cumulativeProbability(int x)
For a random variable X whose values are distributed according to this distribution, this method returns P(X ≤ x). |
double |
BinomialDistributionImpl.cumulativeProbability(int x)
For this distribution, X, this method returns P(X ≤ x). |
double |
PoissonDistributionImpl.cumulativeProbability(int x)
The probability distribution function P(X <= x) for a Poisson distribution. |
double |
PascalDistributionImpl.cumulativeProbability(int x)
For this distribution, X, this method returns P(X ≤ x). |
double |
IntegerDistribution.cumulativeProbability(int x)
For a random variable X whose values are distributed according to this distribution, this method returns P(X ≤ x). |
double |
AbstractIntegerDistribution.cumulativeProbability(int x0,
int x1)
For a random variable X whose values are distributed according to this distribution, this method returns P(x0 ≤ X ≤ x1). |
double |
IntegerDistribution.cumulativeProbability(int x0,
int x1)
For this distribution, X, this method returns P(x0 ≤ X ≤ x1). |
double |
BetaDistribution.density(Double x)
Return the probability density for a particular point. |
double |
HasDensity.density(P x)
Deprecated. Compute the probability density function. |
double |
GammaDistributionImpl.inverseCumulativeProbability(double p)
For this distribution, X, this method returns the critical point x, such that P(X < x) = p . |
double |
ChiSquaredDistributionImpl.inverseCumulativeProbability(double p)
For this distribution, X, this method returns the critical point x, such that P(X < x) = p . |
double |
TDistributionImpl.inverseCumulativeProbability(double p)
For this distribution, X, this method returns the critical point x, such that P(X < x) = p . |
double |
FDistributionImpl.inverseCumulativeProbability(double p)
For this distribution, X, this method returns the critical point x, such that P(X < x) = p . |
double |
AbstractContinuousDistribution.inverseCumulativeProbability(double p)
For this distribution, X, this method returns the critical point x, such that P(X < x) = p . |
int |
AbstractIntegerDistribution.inverseCumulativeProbability(double p)
For a random variable X whose values are distributed according to this distribution, this method returns the largest x, such that P(X ≤ x) ≤ p . |
int |
BinomialDistributionImpl.inverseCumulativeProbability(double p)
For this distribution, X, this method returns the largest x, such that P(X ≤ x) ≤ p . |
int |
PascalDistributionImpl.inverseCumulativeProbability(double p)
For this distribution, X, this method returns the largest x, such that P(X ≤ x) ≤ p . |
double |
ExponentialDistributionImpl.inverseCumulativeProbability(double p)
For this distribution, X, this method returns the critical point x, such that P(X < x) = p . |
int |
IntegerDistribution.inverseCumulativeProbability(double p)
For this distribution, X, this method returns the largest x such that P(X ≤ x) <= p. |
double |
ContinuousDistribution.inverseCumulativeProbability(double p)
For this distribution, X, this method returns x such that P(X < x) = p. |
double |
BetaDistributionImpl.inverseCumulativeProbability(double p)
For this distribution, X, this method returns the critical point x, such that P(X < x) = p . |
double |
NormalDistributionImpl.inverseCumulativeProbability(double p)
For this distribution, X, this method returns the critical point x, such that P(X < x) = p . |
double |
PoissonDistribution.normalApproximateProbability(int x)
Calculates the Poisson distribution function using a normal approximation. |
double |
PoissonDistributionImpl.normalApproximateProbability(int x)
Calculates the Poisson distribution function using a normal approximation. |
double |
AbstractContinuousDistribution.sample()
Generates a random value sampled from this distribution. |
int |
AbstractIntegerDistribution.sample()
Generates a random value sampled from this distribution. |
int |
PoissonDistributionImpl.sample()
Generates a random value sampled from this distribution. |
double |
ExponentialDistributionImpl.sample()
Generates a random value sampled from this distribution. |
double |
NormalDistributionImpl.sample()
Generates a random value sampled from this distribution. |
double[] |
AbstractContinuousDistribution.sample(int sampleSize)
Generates a random sample from the distribution. |
int[] |
AbstractIntegerDistribution.sample(int sampleSize)
Generates a random sample from the distribution. |
| Uses of MathException in org.apache.commons.math.estimation |
|---|
| Subclasses of MathException in org.apache.commons.math.estimation | |
|---|---|
class |
EstimationException
Deprecated. as of 2.0, everything in package org.apache.commons.math.estimation has been deprecated and replaced by package org.apache.commons.math.optimization.general |
| Uses of MathException in org.apache.commons.math.fraction |
|---|
| Subclasses of MathException in org.apache.commons.math.fraction | |
|---|---|
class |
FractionConversionException
Error thrown when a double value cannot be converted to a fraction in the allowed number of iterations. |
| Uses of MathException in org.apache.commons.math.geometry |
|---|
| Subclasses of MathException in org.apache.commons.math.geometry | |
|---|---|
class |
CardanEulerSingularityException
This class represents exceptions thrown while extractiong Cardan or Euler angles from a rotation. |
class |
NotARotationMatrixException
This class represents exceptions thrown while building rotations from matrices. |
| Uses of MathException in org.apache.commons.math.linear |
|---|
| Subclasses of MathException in org.apache.commons.math.linear | |
|---|---|
class |
NotPositiveDefiniteMatrixException
This class represents exceptions thrown when a matrix expected to be positive definite is not. |
class |
NotSymmetricMatrixException
This class represents exceptions thrown when a matrix expected to be symmetric is not |
| Uses of MathException in org.apache.commons.math.ode |
|---|
| Subclasses of MathException in org.apache.commons.math.ode | |
|---|---|
class |
DerivativeException
This exception is made available to users to report the error conditions that are triggered while computing the differential equations. |
class |
IntegratorException
This exception is made available to users to report the error conditions that are triggered during integration |
| Uses of MathException in org.apache.commons.math.ode.events |
|---|
| Subclasses of MathException in org.apache.commons.math.ode.events | |
|---|---|
class |
EventException
This exception is made available to users to report the error conditions that are triggered by EventHandler |
| Uses of MathException in org.apache.commons.math.optimization |
|---|
| Subclasses of MathException in org.apache.commons.math.optimization | |
|---|---|
class |
OptimizationException
Deprecated. in 2.2 (to be removed in 3.0). |
| Uses of MathException in org.apache.commons.math.optimization.linear |
|---|
| Subclasses of MathException in org.apache.commons.math.optimization.linear | |
|---|---|
class |
NoFeasibleSolutionException
This class represents exceptions thrown by optimizers when no solution fulfills the constraints. |
class |
UnboundedSolutionException
This class represents exceptions thrown by optimizers when a solution escapes to infinity. |
| Uses of MathException in org.apache.commons.math.random |
|---|
| Methods in org.apache.commons.math.random that throw MathException | |
|---|---|
double |
RandomDataImpl.nextBeta(double alpha,
double beta)
Generates a random value from the Beta Distribution . |
int |
RandomDataImpl.nextBinomial(int numberOfTrials,
double probabilityOfSuccess)
Generates a random value from the Binomial Distribution . |
double |
RandomDataImpl.nextCauchy(double median,
double scale)
Generates a random value from the Cauchy Distribution . |
double |
RandomDataImpl.nextChiSquare(double df)
Generates a random value from the ChiSquare Distribution . |
double |
RandomDataImpl.nextF(double numeratorDf,
double denominatorDf)
Generates a random value from the F Distribution . |
double |
RandomDataImpl.nextGamma(double shape,
double scale)
Generates a random value from the Gamma Distribution . |
int |
RandomDataImpl.nextHypergeometric(int populationSize,
int numberOfSuccesses,
int sampleSize)
Generates a random value from the Hypergeometric Distribution . |
double |
RandomDataImpl.nextInversionDeviate(ContinuousDistribution distribution)
Generate a random deviate from the given distribution using the inversion method. |
int |
RandomDataImpl.nextInversionDeviate(IntegerDistribution distribution)
Generate a random deviate from the given distribution using the inversion method. |
int |
RandomDataImpl.nextPascal(int r,
double p)
Generates a random value from the Pascal Distribution . |
double |
RandomDataImpl.nextT(double df)
Generates a random value from the T Distribution . |
double |
RandomDataImpl.nextWeibull(double shape,
double scale)
Generates a random value from the Weibull Distribution . |
int |
RandomDataImpl.nextZipf(int numberOfElements,
double exponent)
Generates a random value from the Zipf Distribution . |
| Uses of MathException in org.apache.commons.math.special |
|---|
| Methods in org.apache.commons.math.special that throw MathException | |
|---|---|
static double |
Erf.erf(double x)
Returns the error function |
static double |
Erf.erfc(double x)
Returns the complementary error function |
static double |
Beta.regularizedBeta(double x,
double a,
double b)
Returns the regularized beta function I(x, a, b). |
static double |
Beta.regularizedBeta(double x,
double a,
double b,
double epsilon)
Returns the regularized beta function I(x, a, b). |
static double |
Beta.regularizedBeta(double x,
double a,
double b,
double epsilon,
int maxIterations)
Returns the regularized beta function I(x, a, b). |
static double |
Beta.regularizedBeta(double x,
double a,
double b,
int maxIterations)
Returns the regularized beta function I(x, a, b). |
static double |
Gamma.regularizedGammaP(double a,
double x)
Returns the regularized gamma function P(a, x). |
static double |
Gamma.regularizedGammaP(double a,
double x,
double epsilon,
int maxIterations)
Returns the regularized gamma function P(a, x). |
static double |
Gamma.regularizedGammaQ(double a,
double x)
Returns the regularized gamma function Q(a, x) = 1 - P(a, x). |
static double |
Gamma.regularizedGammaQ(double a,
double x,
double epsilon,
int maxIterations)
Returns the regularized gamma function Q(a, x) = 1 - P(a, x). |
| Uses of MathException in org.apache.commons.math.stat.correlation |
|---|
| Methods in org.apache.commons.math.stat.correlation that throw MathException | |
|---|---|
RealMatrix |
PearsonsCorrelation.getCorrelationPValues()
Returns a matrix of p-values associated with the (two-sided) null hypothesis that the corresponding correlation coefficient is zero. |
| Uses of MathException in org.apache.commons.math.stat.inference |
|---|
| Methods in org.apache.commons.math.stat.inference that throw MathException | |
|---|---|
double |
OneWayAnova.anovaFValue(Collection<double[]> categoryData)
Computes the ANOVA F-value for a collection of double[]
arrays. |
double |
OneWayAnovaImpl.anovaFValue(Collection<double[]> categoryData)
Computes the ANOVA F-value for a collection of double[]
arrays. |
double |
OneWayAnova.anovaPValue(Collection<double[]> categoryData)
Computes the ANOVA P-value for a collection of double[]
arrays. |
double |
OneWayAnovaImpl.anovaPValue(Collection<double[]> categoryData)
Computes the ANOVA P-value for a collection of double[]
arrays. |
boolean |
OneWayAnova.anovaTest(Collection<double[]> categoryData,
double alpha)
Performs an ANOVA test, evaluating the null hypothesis that there is no difference among the means of the data categories. |
boolean |
OneWayAnovaImpl.anovaTest(Collection<double[]> categoryData,
double alpha)
Performs an ANOVA test, evaluating the null hypothesis that there is no difference among the means of the data categories. |
static double |
TestUtils.chiSquareTest(double[] expected,
long[] observed)
|
double |
ChiSquareTest.chiSquareTest(double[] expected,
long[] observed)
Returns the observed significance level, or p-value, associated with a Chi-square goodness of fit test comparing the observed
frequency counts to those in the expected array. |
double |
ChiSquareTestImpl.chiSquareTest(double[] expected,
long[] observed)
Returns the observed significance level, or p-value, associated with a Chi-square goodness of fit test comparing the observed
frequency counts to those in the expected array. |
static boolean |
TestUtils.chiSquareTest(double[] expected,
long[] observed,
double alpha)
|
boolean |
ChiSquareTest.chiSquareTest(double[] expected,
long[] observed,
double alpha)
Performs a Chi-square goodness of fit test evaluating the null hypothesis that the observed counts conform to the frequency distribution described by the expected counts, with significance level alpha . |
boolean |
ChiSquareTestImpl.chiSquareTest(double[] expected,
long[] observed,
double alpha)
Performs a Chi-square goodness of fit test evaluating the null hypothesis that the observed counts conform to the frequency distribution described by the expected counts, with significance level alpha . |
static double |
TestUtils.chiSquareTest(long[][] counts)
|
double |
ChiSquareTest.chiSquareTest(long[][] counts)
Returns the observed significance level, or p-value, associated with a chi-square test of independence based on the input counts
array, viewed as a two-way table. |
double |
ChiSquareTestImpl.chiSquareTest(long[][] counts)
|
static boolean |
TestUtils.chiSquareTest(long[][] counts,
double alpha)
|
boolean |
ChiSquareTest.chiSquareTest(long[][] counts,
double alpha)
Performs a chi-square test of independence evaluating the null hypothesis that the classifications represented by the counts in the columns of the input 2-way table are independent of the rows, with significance level alpha . |
boolean |
ChiSquareTestImpl.chiSquareTest(long[][] counts,
double alpha)
|
static double |
TestUtils.chiSquareTestDataSetsComparison(long[] observed1,
long[] observed2)
|
double |
UnknownDistributionChiSquareTest.chiSquareTestDataSetsComparison(long[] observed1,
long[] observed2)
Returns the observed significance level, or p-value, associated with a Chi-Square two sample test comparing bin frequency counts in observed1 and
observed2 . |
double |
ChiSquareTestImpl.chiSquareTestDataSetsComparison(long[] observed1,
long[] observed2)
|
static boolean |
TestUtils.chiSquareTestDataSetsComparison(long[] observed1,
long[] observed2,
double alpha)
|
boolean |
UnknownDistributionChiSquareTest.chiSquareTestDataSetsComparison(long[] observed1,
long[] observed2,
double alpha)
Performs a Chi-Square two sample test comparing two binned data sets. |
boolean |
ChiSquareTestImpl.chiSquareTestDataSetsComparison(long[] observed1,
long[] observed2,
double alpha)
|
static double |
TestUtils.homoscedasticTTest(double[] sample1,
double[] sample2)
|
double |
TTestImpl.homoscedasticTTest(double[] sample1,
double[] sample2)
Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the input arrays, under the assumption that the two samples are drawn from subpopulations with equal variances. |
double |
TTest.homoscedasticTTest(double[] sample1,
double[] sample2)
Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the input arrays, under the assumption that the two samples are drawn from subpopulations with equal variances. |
static boolean |
TestUtils.homoscedasticTTest(double[] sample1,
double[] sample2,
double alpha)
|
boolean |
TTestImpl.homoscedasticTTest(double[] sample1,
double[] sample2,
double alpha)
Performs a two-sided t-test evaluating the null hypothesis that sample1
and sample2 are drawn from populations with the same mean,
with significance level alpha , assuming that the
subpopulation variances are equal. |
boolean |
TTest.homoscedasticTTest(double[] sample1,
double[] sample2,
double alpha)
Performs a two-sided t-test evaluating the null hypothesis that sample1
and sample2 are drawn from populations with the same mean,
with significance level alpha , assuming that the
subpopulation variances are equal. |
protected double |
TTestImpl.homoscedasticTTest(double m1,
double m2,
double v1,
double v2,
double n1,
double n2)
Computes p-value for 2-sided, 2-sample t-test, under the assumption of equal subpopulation variances. |
static double |
TestUtils.homoscedasticTTest(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2)
|
double |
TTestImpl.homoscedasticTTest(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2)
Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the datasets described by two StatisticalSummary instances, under the hypothesis of equal subpopulation variances. |
double |
TTest.homoscedasticTTest(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2)
Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the datasets described by two StatisticalSummary instances, under the hypothesis of equal subpopulation variances. |
static double |
TestUtils.oneWayAnovaFValue(Collection<double[]> categoryData)
|
static double |
TestUtils.oneWayAnovaPValue(Collection<double[]> categoryData)
|
static boolean |
TestUtils.oneWayAnovaTest(Collection<double[]> categoryData,
double alpha)
|
static double |
TestUtils.pairedT(double[] sample1,
double[] sample2)
|
double |
TTestImpl.pairedT(double[] sample1,
double[] sample2)
Computes a paired, 2-sample t-statistic based on the data in the input arrays. |
double |
TTest.pairedT(double[] sample1,
double[] sample2)
Computes a paired, 2-sample t-statistic based on the data in the input arrays. |
static double |
TestUtils.pairedTTest(double[] sample1,
double[] sample2)
|
double |
TTestImpl.pairedTTest(double[] sample1,
double[] sample2)
Returns the observed significance level, or p-value, associated with a paired, two-sample, two-tailed t-test based on the data in the input arrays. |
double |
TTest.pairedTTest(double[] sample1,
double[] sample2)
Returns the observed significance level, or p-value, associated with a paired, two-sample, two-tailed t-test based on the data in the input arrays. |
static boolean |
TestUtils.pairedTTest(double[] sample1,
double[] sample2,
double alpha)
|
boolean |
TTestImpl.pairedTTest(double[] sample1,
double[] sample2,
double alpha)
Performs a paired t-test evaluating the null hypothesis that the mean of the paired differences between sample1 and
sample2 is 0 in favor of the two-sided alternative that the
mean paired difference is not equal to 0, with significance level
alpha . |
boolean |
TTest.pairedTTest(double[] sample1,
double[] sample2,
double alpha)
Performs a paired t-test evaluating the null hypothesis that the mean of the paired differences between sample1 and
sample2 is 0 in favor of the two-sided alternative that the
mean paired difference is not equal to 0, with significance level
alpha . |
static double |
TestUtils.tTest(double[] sample1,
double[] sample2)
|
double |
TTestImpl.tTest(double[] sample1,
double[] sample2)
Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the input arrays. |
double |
TTest.tTest(double[] sample1,
double[] sample2)
Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the input arrays. |
static boolean |
TestUtils.tTest(double[] sample1,
double[] sample2,
double alpha)
|
boolean |
TTestImpl.tTest(double[] sample1,
double[] sample2,
double alpha)
Performs a two-sided t-test evaluating the null hypothesis that sample1
and sample2 are drawn from populations with the same mean,
with significance level alpha . |
boolean |
TTest.tTest(double[] sample1,
double[] sample2,
double alpha)
Performs a two-sided t-test evaluating the null hypothesis that sample1
and sample2 are drawn from populations with the same mean,
with significance level alpha . |
static double |
TestUtils.tTest(double mu,
double[] sample)
|
double |
TTestImpl.tTest(double mu,
double[] sample)
Returns the observed significance level, or p-value, associated with a one-sample, two-tailed t-test comparing the mean of the input array with the constant mu . |
double |
TTest.tTest(double mu,
double[] sample)
Returns the observed significance level, or p-value, associated with a one-sample, two-tailed t-test comparing the mean of the input array with the constant mu . |
static boolean |
TestUtils.tTest(double mu,
double[] sample,
double alpha)
|
boolean |
TTestImpl.tTest(double mu,
double[] sample,
double alpha)
Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from which sample is drawn equals mu . |
boolean |
TTest.tTest(double mu,
double[] sample,
double alpha)
Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from which sample is drawn equals mu . |
protected double |
TTestImpl.tTest(double m,
double mu,
double v,
double n)
Computes p-value for 2-sided, 1-sample t-test. |
protected double |
TTestImpl.tTest(double m1,
double m2,
double v1,
double v2,
double n1,
double n2)
Computes p-value for 2-sided, 2-sample t-test. |
static double |
TestUtils.tTest(double mu,
StatisticalSummary sampleStats)
|
double |
TTestImpl.tTest(double mu,
StatisticalSummary sampleStats)
Returns the observed significance level, or p-value, associated with a one-sample, two-tailed t-test comparing the mean of the dataset described by sampleStats
with the constant mu . |
double |
TTest.tTest(double mu,
StatisticalSummary sampleStats)
Returns the observed significance level, or p-value, associated with a one-sample, two-tailed t-test comparing the mean of the dataset described by sampleStats
with the constant mu . |
static boolean |
TestUtils.tTest(double mu,
StatisticalSummary sampleStats,
double alpha)
|
boolean |
TTestImpl.tTest(double mu,
StatisticalSummary sampleStats,
double alpha)
Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from which the dataset described by stats is
drawn equals mu . |
boolean |
TTest.tTest(double mu,
StatisticalSummary sampleStats,
double alpha)
Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from which the dataset described by stats is
drawn equals mu . |
static double |
TestUtils.tTest(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2)
|
double |
TTestImpl.tTest(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2)
Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the datasets described by two StatisticalSummary instances. |
double |
TTest.tTest(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2)
Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the datasets described by two StatisticalSummary instances. |
static boolean |
TestUtils.tTest(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2,
double alpha)
|
boolean |
TTestImpl.tTest(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2,
double alpha)
Performs a two-sided t-test evaluating the null hypothesis that sampleStats1 and sampleStats2 describe
datasets drawn from populations with the same mean, with significance
level alpha . |
boolean |
TTest.tTest(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2,
double alpha)
Performs a two-sided t-test evaluating the null hypothesis that sampleStats1 and sampleStats2 describe
datasets drawn from populations with the same mean, with significance
level alpha . |
| Uses of MathException in org.apache.commons.math.stat.regression |
|---|
| Methods in org.apache.commons.math.stat.regression that throw MathException | |
|---|---|
double |
SimpleRegression.getSignificance()
Returns the significance level of the slope (equiv) correlation. |
double |
SimpleRegression.getSlopeConfidenceInterval()
Returns the half-width of a 95% confidence interval for the slope estimate. |
double |
SimpleRegression.getSlopeConfidenceInterval(double alpha)
Returns the half-width of a (100-100*alpha)% confidence interval for the slope estimate. |
| Uses of MathException in org.apache.commons.math.util |
|---|
| Methods in org.apache.commons.math.util that throw MathException | |
|---|---|
double |
ContinuedFraction.evaluate(double x)
Evaluates the continued fraction at the value x. |
double |
ContinuedFraction.evaluate(double x,
double epsilon)
Evaluates the continued fraction at the value x. |
double |
ContinuedFraction.evaluate(double x,
double epsilon,
int maxIterations)
Evaluates the continued fraction at the value x. |
double |
ContinuedFraction.evaluate(double x,
int maxIterations)
Evaluates the continued fraction at the value x. |
double |
NumberTransformer.transform(Object o)
Implementing this interface provides a facility to transform from Object to Double. |
double |
TransformerMap.transform(Object o)
Attempts to transform the Object against the map of NumberTransformers. |
double |
DefaultTransformer.transform(Object o)
|
|
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In this week’s challenges, we worked with arrays and hashes—2 concepts that may cause some confusion. This post will help to clarify these concepts and their uses. An array is a systematic arrangement of objects, usually in rows or columns. I first came across arrays in matrix algebra; they were called vectors. It was simply a row or column of number in brackets. Arrays in ruby are not limited to numbers only. What's important about arrays, however, is that the order of the objects matters. Let's give an example: Say you have a list of numbers representing grades on class assignments. You might want to work with that array to identify the lowest grade, highest grade, or even apply weights to grades. Rather than searching through the list, using arrays and methods, you can have what you want returned to you. Hashes are similar to arrays, except they use arbitrary keys, or names, in the index of objects and the keys are assigned values. Hashes are collections of these key/value pairs. For example, you may have a grocery list with vegetable, fruit, meat, drink. These would be the keys and their values would be broccoli, apple, chicken, and lemonade. You could use ruby syntax to return to you the type of drink to purchase, or a list of the types of drinks if there were multiple keys called drink. Hopefully, this have provided some insight into arrays and hashes and how they can be used.


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