Class PartialShapeMatcher2
- java.lang.Object
-
- algorithms.imageProcessing.matching.PartialShapeMatcher2
-
public class PartialShapeMatcher2 extends java.lang.Object
based upon algorithm in paper "Efficient Partial Shape Matching of Outer Contours: by Donoser - called IS-Match, integral shape match - a silhouette of ordered points are sampled making it an "order preserved assignment problem". - a chord angle descriptor is local and global and is invariant to similarity transformations. - the method returns partial sub matches so works with articulated data and occluded shapes - uses an efficient integral image based matching algorithm - the multi-objective optimization uses principles of Paretto efficiency, defined with the fraction of the total matched and the summed differences of angles. - the final result returned is the sequences and the total fraction matched and summed absolute differences, instead of the Salukwadze distance of a Paretto frontier. point sampling: (a) same number of points over each contour - can handle similarity transforms. disadvantage is that it is less able to handle occlusion or extraneous shapes in the shape. using the euclidean option works around this. - to use in this mode: setToUseSameNumberOfPoints() and the number of points can be set using dp, with nSample = min(p.n, q.n)/dp and overrideSamplingDistance(dp) and optionally: setToUseEuclidean() (b) OR, equidistant points (default) - can handle occlusion. disadvantage in matching when there are scale differences between the shapes is handled in part by an internal euclidean projection. - the default sampling of pixels is 3. this can be changed using overrideSamplingDistance(dp) unit test using dp of 1 and 2 work well This version of the code follows the paper algorithm in that it uses summed area table instead of summed column table as PartialShapeMatcher.java does. This very has a faster runtime, but is less precise. The runtime complexity for building the integral image is O(n*m*n) where m and n are the number of sampled points on the input shapes.
NOTE: You may need to pre-process the shape points for example, smooth the boundary. NOTE: You may want to use the Euclidean setting to avoid some of the ambiguities of the articulated search using this faster but less precise search.The runtime complexity for the search of the integral image of summed differences and analysis, is n2 * (O(n1 * lg2(n1)) where n1 and n2 are the number of points in the 2 shapes after the spacing has been considered. The algorithm runtime complexity could be reduced more, but with more loss in accuracy by selecting a discrete number of diagonal read block sizes. For instance, if wanted to read only a single block size of n1/10, the total runtime complexity would be approx n2 * n1/10. (and in this case, could build the summed difference chord matrix smaller and more quickly than O(n2 * n1 * n1) before that. Essentially, would use summed column table and the rows would only be offsets of n1/10 so the total runtime complexity for building would be O(n1*(n1/10)) and reads would be smaller...it's effectively the result of comparing the 2 curves at offets of n1/10 intervals which would give fast but very rough results that would not handle articultion well if at all.)This method: PairIntArray p = imageProcessor .extractSmoothedOrderedBoundary() uses a Gaussian smoothing of 1 sigma,
- Author:
- nichole
-
-
Nested Class Summary
Nested Classes Modifier and Type Class Description static class
PartialShapeMatcher2.Result
static class
PartialShapeMatcher2.SRComparator
-
Field Summary
Fields Modifier and Type Field Description protected int
dp
in sampling the boundaries of the shapes, one can choose to use the same number for each (which can result in very different spacings for different sized curves) or one can choose a set distance between sampling points.protected java.util.logging.Logger
log
-
Constructor Summary
Constructors Constructor Description PartialShapeMatcher2()
-
Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description void
_overrideToThreshhold(float t)
override the threshold for using a chord differernce value for the average value.protected void
applySummedAreaTableConversion(float[][] mdI)
protected void
applySummedAreaTableConversion(float[][][] md)
float
calculateAChordDifference(int pXRef1, int pYRef1, int pXRef2, int pYRef2, int pX, int pY, int qXRef1, int qYRef1, int qXRef2, int qYRef2, int qX, int qY)
calculate the chord difference between point (pX, pY) and point (qX, qY) with respect to the corresponding reference points from their reference frames (where the reference points are matched to one another, respectively in the other frames).gnu.trove.list.TDoubleList
calculateChordDiffs(algorithms.util.PairIntArray p, algorithms.util.PairIntArray q, algorithms.util.PairIntArray matchedIndexes)
as an alternative to finding the best correspondence between two shapes, instead, given the correspondence, sum the chord differences.double
calculateChordDiffSums(algorithms.util.PairIntArray p, algorithms.util.PairIntArray q, algorithms.util.PairIntArray matchedIndexes)
as an alternative to finding the best correspondence between two shapes, instead, given the correspondence, sum the chord differences.protected float[][]
createDescriptorMatrix(algorithms.util.PairIntArray p, int n)
given the shape points for p and q, create a matrix of descriptors, describing the difference in chord angles.protected float[][][]
createDifferenceMatrices(algorithms.util.PairIntArray p, algorithms.util.PairIntArray q)
create the matrices of differences between p and q.protected int
distanceSqEucl(int x1, int y1, int x2, int y2)
EpipolarTransformationFit
getStoredEpipolarFit()
PartialShapeMatcher2.Result
match(algorithms.util.PairIntArray p, algorithms.util.PairIntArray q)
A shape is defined as the clockwise ordered sequence of points P_1...P_N and the shape to match has points Q_1...Q_N.void
overrideMinimumLength(int length)
override the default minimum length of 7.void
overrideSamplingDistance(int d)
the default sampling distance is 3.void
overrideToStoreMatrix()
set this to store the difference matrix and scale information in order to read more from the matrix later.protected void
populatePointArrays(SR sr, algorithms.util.PairIntArray p, algorithms.util.PairIntArray q, algorithms.util.PairIntArray pOut, algorithms.util.PairIntArray qOut, algorithms.util.PairIntArray pUnmatchedOut, algorithms.util.PairIntArray qUnmatchedOut)
float
readStoredMatrix(int pIdx, int qIdx)
void
setToDebug()
use this to enable the debug log comments and plotsvoid
setToRemoveOutliers()
void
setToUseEuclidean()
turn on the euclidean transformation to evaluate the best initial answers.void
setToUseSameNumberOfPoints()
if this is set, the same number of points are used to sample both shapes.
-
-
-
Field Detail
-
dp
protected int dp
in sampling the boundaries of the shapes, one can choose to use the same number for each (which can result in very different spacings for different sized curves) or one can choose a set distance between sampling points. dp is the set distance between sampling points. The authors of the paper use 3 as an example.
-
log
protected java.util.logging.Logger log
-
-
Method Detail
-
overrideToStoreMatrix
public void overrideToStoreMatrix()
set this to store the difference matrix and scale information in order to read more from the matrix later.
-
setToUseEuclidean
public void setToUseEuclidean()
turn on the euclidean transformation to evaluate the best initial answers. NOTE: this needs to be improved. might need to be combined with a lower threshold.
-
setToRemoveOutliers
public void setToRemoveOutliers()
-
_overrideToThreshhold
public void _overrideToThreshhold(float t)
override the threshold for using a chord differernce value for the average value. By default it is set to 1.- Parameters:
t
-
-
overrideMinimumLength
public void overrideMinimumLength(int length)
override the default minimum length of 7.- Parameters:
length
-
-
setToUseSameNumberOfPoints
public void setToUseSameNumberOfPoints()
if this is set, the same number of points are used to sample both shapes. The number of points is min(p.n, q.n)/dp. You can change dp from the default of 3 by using the method overrideSamplingDistance(dp).
-
overrideSamplingDistance
public void overrideSamplingDistance(int d)
the default sampling distance is 3. use this method to override it.- Parameters:
d
-
-
setToDebug
public void setToDebug()
use this to enable the debug log comments and plots
-
match
public PartialShapeMatcher2.Result match(algorithms.util.PairIntArray p, algorithms.util.PairIntArray q)
A shape is defined as the clockwise ordered sequence of points P_1...P_N and the shape to match has points Q_1...Q_N. The spacings used within this method are equidistant unless changed using method setToUseSameNumberOfPoints(). The default spacing is 3, so override that if a different number is needed. NOTE: You may need to pre-process the shape points for example, smooth the boundary.This method: PairIntArray p = imageProcessor .extractSmoothedOrderedBoundary() uses a Gaussian smoothing of 2 sigma, but a smaller sigma can be specified.
- Parameters:
p
-q
-- Returns:
-
calculateChordDiffSums
public double calculateChordDiffSums(algorithms.util.PairIntArray p, algorithms.util.PairIntArray q, algorithms.util.PairIntArray matchedIndexes)
as an alternative to finding the best correspondence between two shapes, instead, given the correspondence, sum the chord differences. The same instance variables such as the point spacing are used here too.- Parameters:
p
-q
-matchedIndexes
-- Returns:
-
calculateChordDiffs
public gnu.trove.list.TDoubleList calculateChordDiffs(algorithms.util.PairIntArray p, algorithms.util.PairIntArray q, algorithms.util.PairIntArray matchedIndexes)
as an alternative to finding the best correspondence between two shapes, instead, given the correspondence, sum the chord differences. The same instance variables such as the point spacing are used here too.- Parameters:
p
-q
-matchedIndexes
-- Returns:
-
createDifferenceMatrices
protected float[][][] createDifferenceMatrices(algorithms.util.PairIntArray p, algorithms.util.PairIntArray q)
create the matrices of differences between p and q. Note that the matrix differences are absolute differences. index0 is rotations of q, index1 is p.n, index2 is q.n returns a[0:q.n-1][0:p.n-1][0:p.n-1]
-
createDescriptorMatrix
protected float[][] createDescriptorMatrix(algorithms.util.PairIntArray p, int n)
given the shape points for p and q, create a matrix of descriptors, describing the difference in chord angles. The chord descriptor is invariant to translation, rotation, and scale: - a chord is a line joining 2 region points - uses the relative orientation between 2 chords angle a_i_j is from chord P_i_P_j to reference point P_i to another sampled point and chord P_j_P_(j-d) and P_j d is the number of points before j in the sequence of points P. a_i_j is the angle between the 2 chords P_i_P_j and P_j_P_(j-d)
-
distanceSqEucl
protected int distanceSqEucl(int x1, int y1, int x2, int y2)
-
applySummedAreaTableConversion
protected void applySummedAreaTableConversion(float[][][] md)
-
applySummedAreaTableConversion
protected void applySummedAreaTableConversion(float[][] mdI)
-
populatePointArrays
protected void populatePointArrays(SR sr, algorithms.util.PairIntArray p, algorithms.util.PairIntArray q, algorithms.util.PairIntArray pOut, algorithms.util.PairIntArray qOut, algorithms.util.PairIntArray pUnmatchedOut, algorithms.util.PairIntArray qUnmatchedOut)
-
readStoredMatrix
public float readStoredMatrix(int pIdx, int qIdx)
-
calculateAChordDifference
public float calculateAChordDifference(int pXRef1, int pYRef1, int pXRef2, int pYRef2, int pX, int pY, int qXRef1, int qYRef1, int qXRef2, int qYRef2, int qX, int qY)
calculate the chord difference between point (pX, pY) and point (qX, qY) with respect to the corresponding reference points from their reference frames (where the reference points are matched to one another, respectively in the other frames). NOTE: for more accurate results, should pass in a list of correspondences in p and q and then calc chord diff of (pX, pY) and point (qX, qY) with avg or lin regr and outlier removal.- Parameters:
pXRef1
-pYRef1
-pXRef2
-pYRef2
-pX
-pY
-qXRef1
-qYRef1
-qXRef2
-qYRef2
-qX
-qY
-- Returns:
-
getStoredEpipolarFit
public EpipolarTransformationFit getStoredEpipolarFit()
-
-


Setting up an EC2 Instance was actually much easier than I anticipated. To begin with you need to creat an AWS account that will house all of your AWS services. These services include, but are not limited to, EC2, S3 and Lightsail.
Once an AWS account is created you are granted what's called the "Free Tier" of services. Within this "Free Tier" the EC2 service is available. You simply click on EC2, and it will take you to a new Dashboard for all of your EC2 needs.
Once in this Dashboard there is an option that says "Create Instance." You press that button and it will redirect you to a Wizard, similar to a Windows set-up wizard, that will direct you on the options for creating your EC2 instance.
The main thing to focus on is the "AMI" that is chosen. This AMI is the operating system that gets booted onto the EC2 server. Amazon offers their propietary AMI, which is a perfectly fine OS to test this EC2 instance with.
Once you finish the Set-Up Wizard, choosing storage requirements and setting tags, you have completed the first set up of an EC2 instance. This instsance, depending on which protocols and services you included, is now SSH ready, able to host a Web service or even able to be setup as a database.


"Work hard play hard"
nav 1
nav 2
nav 3
Main Title
To-do list
Fix page
new item
Click!
Points:
0
Get Location!
Show my location
Refresh!


Class RTPChannel
A communications channel for transmitting and receiving Real-time Protocol (RTP) and
Real-time Control Protocol (RTCP) packets. This class performs the socket management
functions.
Inheritance
System.Object
RTPChannel
Implements
System.IDisposable
Inherited Members
System.Object.Equals(System.Object)
System.Object.Equals(System.Object, System.Object)
System.Object.GetHashCode()
System.Object.GetType()
System.Object.MemberwiseClone()
System.Object.ReferenceEquals(System.Object, System.Object)
System.Object.ToString()
Assembly: SIPSorcery.dll
Syntax
public class RTPChannel : IDisposable
Constructors
|
Improve this Doc
View Source
RTPChannel(IPAddress, Boolean, IPEndPoint, IPEndPoint, Int32, Int32)
Creates a new RTP channel. The RTP and optionally RTCP sockets will be bound in the constructor.
They do not start receiving until the Start method is called.
Declaration
public RTPChannel(IPAddress localAddress, bool createControlSocket, IPEndPoint rtpRemoteEndPoint = null, IPEndPoint controlEndPoint = null, int mediaStartPort = 10000, int mediaEndPort = 20000)
Parameters
| Type |
Name |
Description |
| System.Net.IPAddress |
localAddress |
|
| System.Boolean |
createControlSocket |
Set to true if a separate RTCP control socket should be created. If RTP and
RTCP are being multiplexed (as they are for WebRTC) there's no need to a separate control socket.
|
| System.Net.IPEndPoint |
rtpRemoteEndPoint |
The remote end point that the RTP socket is sending to.
|
| System.Net.IPEndPoint |
controlEndPoint |
The remote end point that the RTCP control socket is sending to.
|
| System.Int32 |
mediaStartPort |
The media start port.
|
| System.Int32 |
mediaEndPort |
The media end port.
|
Properties
|
Improve this Doc
View Source
ControlLocalEndPoint
The local end point the control socket is listening on.
Declaration
public IPEndPoint ControlLocalEndPoint { get; }
Property Value
| Type |
Description |
| System.Net.IPEndPoint |
|
|
Improve this Doc
View Source
ControlPort
The local port we are listening for RTCP packets on.
Declaration
public int ControlPort { get; }
Property Value
| Type |
Description |
| System.Int32 |
|
|
Improve this Doc
View Source
IsClosed
Declaration
public bool IsClosed { get; }
Property Value
| Type |
Description |
| System.Boolean |
|
|
Improve this Doc
View Source
RTPLocalEndPoint
The local end point the RTP socket is listening on.
Declaration
public IPEndPoint RTPLocalEndPoint { get; }
Property Value
| Type |
Description |
| System.Net.IPEndPoint |
|
|
Improve this Doc
View Source
RTPPort
The local port we are listening for RTP (and whatever else is multiplexed) packets on.
Declaration
public int RTPPort { get; }
Property Value
| Type |
Description |
| System.Int32 |
|
|
Improve this Doc
View Source
RtpSocket
Declaration
public Socket RtpSocket { get; }
Property Value
| Type |
Description |
| System.Net.Sockets.Socket |
|
Methods
|
Improve this Doc
View Source
Close(String)
Closes the session's RTP and control ports.
Declaration
public void Close(string reason)
Parameters
| Type |
Name |
Description |
| System.String |
reason |
|
|
Improve this Doc
View Source
Dispose()
Declaration
|
Improve this Doc
View Source
Dispose(Boolean)
Declaration
protected virtual void Dispose(bool disposing)
Parameters
| Type |
Name |
Description |
| System.Boolean |
disposing |
|
|
Improve this Doc
View Source
SendAsync(RTPChannelSocketsEnum, IPEndPoint, Byte[])
Declaration
public SocketError SendAsync(RTPChannelSocketsEnum sendOn, IPEndPoint dstEndPoint, byte[] buffer)
Parameters
| Type |
Name |
Description |
| RTPChannelSocketsEnum |
sendOn |
|
| System.Net.IPEndPoint |
dstEndPoint |
|
| System.Byte[] |
buffer |
|
Returns
| Type |
Description |
| System.Net.Sockets.SocketError |
|
|
Improve this Doc
View Source
Start()
Starts listening on the RTP and control ports.
Declaration
Events
|
Improve this Doc
View Source
OnClosed
Declaration
public event Action<string> OnClosed
Event Type
| Type |
Description |
| System.Action<System.String> |
|
|
Improve this Doc
View Source
OnControlDataReceived
Declaration
public event Action<IPEndPoint, IPEndPoint, byte[]> OnControlDataReceived
Event Type
| Type |
Description |
| System.Action<System.Net.IPEndPoint, System.Net.IPEndPoint, System.Byte[]> |
|
|
Improve this Doc
View Source
OnRTPDataReceived
Declaration
public event Action<IPEndPoint, IPEndPoint, byte[]> OnRTPDataReceived
Event Type
| Type |
Description |
| System.Action<System.Net.IPEndPoint, System.Net.IPEndPoint, System.Byte[]> |
|
Implements
System.IDisposable


--- layout: post title: no title date: '2015-12-04T18:30:39+01:00' categories: - Sketchbooks - Sketches picture_url: https://film-Storyboards.tumblr.com/post/134556442352 ---


Maize as our main cash crop is grown to increase sales and also to promote the economy. Cost:ksh1200 per sack.
Cabbages are grown in large numbers. Cost:ksh100 per sack.
Carrots are grown in large farm. Cost:ksh 50 per Kg.
Brocoli are grown in large farm. Cost:ksh 50 per Kg.
Ginger are grown in large farm. Cost:ksh 80 per Kg.
Peas are grown in large farm. Cost:ksh 120 per Kg.
hoho are grown in large farm. Cost:ksh 60 per Kg.
Kales are grown in large farm. Cost:ksh 35 per Kg.
Apples are grown in large farm. Cost:ksh 99 per Kg.
Oranges are grown in large farm. Cost:ksh 69 per Kg.
Mangoes are grown in large farm. Cost:ksh 55 per Kg.
Strawberries are grown in large farm. Cost:ksh 102 per Kg.
Pineapple are grown in large farm. Cost:ksh 89 @each.
Banana are grown in large farm. Cost:ksh 89 per kg.
Watermelon are grown in large farm. Cost:ksh 224 @ each.
Papaya are grown in large farm. Cost:ksh 58 per Kg.
The bull cost ksh 45,000.
The chicken cost ksh 900.
The freshian Cow cost ksh 55,000.
The sheep cost ksh 5,000.
The horses cost ksh 65,000.
The Goat cost ksh 5,000.
The pig cost ksh 10,000 @ each.
The Rabbit cost ksh 2,500 @ each.
The Sulphate does well in farm planting, it cost Ksh 5000 per sack.
The Manure does well in farm planting, it cost Ksh 5000 per sack.
The Bioxa does well in farm planting, it cost Ksh 3500 per sack.
The Ammonium does well in farm planting, it cost Ksh 4200 per sack.
The Plant Tractor does well in farm planting, it cost Ksh 820,000.
The Harvest Tractor does well in farm planting, it cost Ksh 420000 .
The Plough does well in farm planting, it cost Ksh 200000 .


Welcome to your RESTful Web Service
Data-Centric Service Examples (OData)
When you create a new Harmony Core project we provide a sample repository and
data set, and we pre-configure the environment with sample endpoints that provide
examples of how those endpoints can be used. The entities in the sample data set
are as follows:
Each customer can have zero or more orders, each order has one or more order items,
each order item is associated with an item (inventory) and each item is supplied by
a vendor.
The links below can be used to explore various capabilities of the sample API.
Once you are ready to remove the sample content and add your own, follow the
instructions here.
Customer Data
Primary Key Endpoint
Alternate Key Endpoints
OData Queries
| $select | constrains returned properties |
| $filter | constrains returned entities |
| $orderby | alters entity sequence |
| $top | determines how many entities are returned |
| $expand | joins to related entities |
| Complex Queries | combine $select, $filter, $orderby and $expand |
Item Data
Primary Key Endpoint
Alternate Key Endpoints
OData Queries
$select | constrains returned properties |
| $filter | constrains returned entities |
| $orderby | alters entity sequence |
| $top | determines how many entities are returned |
| $expand | joins to related entities |
| Complex Queries | combine $select, $filter, $orderby and $expand |
Order Data
Primary Key Endpoint
Alternate Key Endpoints
OData Queries
$select | constrains returned properties |
| $filter | constrains returned entities |
| $orderby | alters entity sequence |
| $top | determines how many entities are returned |
| $expand | joins to related entities |
| Complex Queries | combine $select, $filter, $orderby and $expand |
Order Item Data
Primary Key Endpoint
Alternate Key Endpoints
OData Queries
$select | constrains returned properties |
| $filter | constrains returned entities |
| $orderby | alters entity sequence |
| $top | determines how many entities are returned |
| $expand | joins to related entities |
| Complex Queries | combine $select, $filter, $orderby and $expand |
Vendor Data
Primary Key Endpoint
Alternate Key Endpoints
OData Queries
| $select | constrains returned properties |
| $filter | constrains returned entities |
| $orderby | alters entity sequence |
| $top | determines how many entities are returned |
| $expand | joins to related entities |
| Complex Queries | combine $select, $filter, $orderby and $expand |
Code-Centric Service Examples (Traditional Bridge)
We also provide a simple pre-configured example of how to use Traditional Bridge to incorporate traditional Synergy subroutines and functions in a Harmony Core service.
Customizing the Services
When you are ready to get started with your own data files and structures, the basic
procedure that you will need to follow is:
- In the Repository project, replace the content of the schema file (repository.scm) with your own repository schema.
- In the Services.Controllers project, delete the source files related to the sample data (CustomersController.dbl, ItemsController.dbl, OrderItemsController.dbl, OrdersController.dbl and VendorsController.dbl).
- In the Services.Models project, delete the source files related to the sample data (Customer.dbl, CustomerMetaData.dbl, Item.dbl, ItemMetaData.dbl, Order.dbl, OrderItem.dbl, OrderItemMetaData.dbl, OrderMetaData.dbl, Vendor.dbl and VendorMetaData.dbl).
-
Edit regen.bat and
- Change the content of the DATA_STRUCTURES environment variable so that it lists the structures you wish to expose.
- Remove the value SYSPARAMS from the value of the environment variable PARAMSTR.
- Review which of the ENABLE_ options are commented in and out to define the options that you wish to use.
- Execute the regen.bat file to generate code for your environment.
- Add the newly generated source files into the Services.Controllers and Services.Models projects as necessary.
- If you wish to maintain the use of a static home page (this page) then edit the content of index.html which you will find in the wwwroot folder of the Services project.


Click and Drag circular controlpoints of transfer function widget to adjust position and transparency.
Double-click circular controlpoints of transfer function widget to pick or adjust a color value. The color value can be specified using either the hue slider and the saturation-/value picker or by entering RGB values in the input fields.
Click and Drag rectangular anchor of transfer function widget to move transfer function widget. Hold the Shift key while dragging to lock dragging direction to either horizontal or vertical dragging.
To add a controlpoint, either double-click or hold the Shift key and click on the line connecting the controlpoints.
Hold the Shift key and click on the handle to
delete a controlpoint, or bring up the context menu with a right click.
Click and Drag the vertical edges of transfer function widget to horizontally scale the widget.
Right-click the rectangular anchor of a transfer function widget to bring up the context menu. You can delete the widget from this context menu, or change the layer ordering of the widgets.
Right-click any place in the transfer function editor to add a new transfer function widget and choose from a number of presets.
Play around with the parameters of the volume rendering by adjusting the transfer function in the transfer function editor, picking a volume from the upper-right menu and modifying sampling rate and alpha correction.[ view fullscreen ]
Resulting transfer function
tf_panel.getTF()
returns an array of [ value, { r, g, b, a } ] items.
The transfer function generated from these values looks like this:
Options
The Transfer Function Editor's look and feel is customizable using multiple options passed when the editor is instantiated. All options are substituted by default values if not specified.
The options are passed as a JSON object and can be queried from the editor using tf_panel.getOptions()
panel {
options for the appearance of the main transfer function editor
width
[ number ] total width of transfer function editor (default: 650)
height
[ number ] total height of transfer function editor (default: 170)
[ boolean ] creates vertical button on left of panel to collapse/expand panel (default: false)
showTFResult
[ boolean ] specifies whether a bottom bar should show the result of the alpha blended transfer function widgets (default: false)
resultHeight
[ number ] height of result bar (default: 20)
resultBackground
[ css ] specifies css background attribute for result bar (default: #000000)
colorScheme
[ 'dark', 'light' or 'blue' ] specifies the color scheme for the context menus, tooltips and color picker (default: 'dark')
}
histogram {
options for the histogram displayed in the back of the editor (optional)
fillColor
[ color ] fill color for the histogram SVG (default: #333333)
lineColor
[ color ] line color for the histogram SVG (default: #666666)
style
[ 'polygon' or 'bars' ] specifies whether the histogram should be plotted as a polyline or vertical rectangular bars (default: 'polygon')
scale
[ function ] (mathematical) function by which the histogram values should be scaled (e.g. logarithmic, ...) (default: Math.log)
overlayUnscaled
[ boolean ] whether the histogram (scaled by the 'scale' function) should be overlayed with an unscaled version (default: true)
}
gradientPresets {
options for the gradient presets available when adding a new widget (right click context menu)
defaultPresets
[ boolean ] specifies whether the default presets should be loaded and appended to the custom presets. If presets array is empty, default presets will be loaded anyway. (default: true)


KBD
Section: Devices and Network Interfaces (4)Updated: xf86-input-keyboard 1.6.0
Index Return to Main Contents
NAME
kbd - Keyboard input driverSYNOPSIS
Section N'34'InputDeviceN'34' Identifier N'34'idevnameN'34' Driver N'34'kbdN'34' ... EndSection
DESCRIPTION
kbd is an Xorg input driver for keyboards. The driver supports the standard OS-provided keyboard interface, but these are currently only available to this driver module for Linux, BSD, and Solaris. This driver is the replacement for the built-in keyboard driver formerly included in Xorg.The kbd driver functions as a keyboard input device.
CONFIGURATION DETAILS
Depending on the X server version in use, input device options may be set in either a xorg.conf file, an xorg.conf.d snippet, or in the configuration files read by the Hardware Abstraction Layer (HAL) daemon, hald(1).
Please refer to xorg.conf(5) for general configuration details and for options that can be used with all input drivers. This section only covers configuration details specific to this driver.
The following driver Options are supported:
- Option N'34'DeviceN'34' N'34'stringN'34'
- Specify the keyboard device. Default: the OS's default console keyboard input source.
- Option N'34'ProtocolN'34' N'34'stringN'34'
- Specify the keyboard protocol. Valid protocol types include:
- Standard, Xqueue.
- Not all protocols are supported on all platforms. Default: "Standard".
- Option N'34'XLedsN'34' N'34'ledlistN'34'
- makes the keyboard LEDs specified in ledlist available for client use instead of their traditional function (Scroll Lock, Caps Lock and Num Lock). The numbers in the list are in the range 1 to 3. Default: empty list.
- Option N'34'XkbRulesN'34' N'34'rulesN'34'
- specifies which XKB rules file to use for interpreting the XkbModel, XkbLayout, XkbVariant, and XkbOptions settings. Default: "xorg" for most platforms, but "xfree98" for the Japanese PC-98 platforms. If you use the "xorg" value then you can find listing of all valid values for these four options in the /usr/share/X11/xkb/rules/xorg.lst file.
- Option N'34'XkbModelN'34' N'34'modelnameN'34'
- specifies the XKB keyboard model name. Default: "pc105" for most platforms, but "pc98" for the Japanese PC-98 platforms.
- Option N'34'XkbLayoutN'34' N'34'layoutnameN'34'
- specifies the XKB keyboard layout name. This is usually the country or language type of the keyboard. Default: "us" for most platforms, but "jp" for the Japanese PC-98 platforms.
- Option N'34'XkbVariantN'34' N'34'variantsN'34'
- specifies the XKB keyboard variant components. These can be used to enhance the keyboard layout details. Default: not set.
- Option N'34'XkbOptionsN'34' N'34'optionsN'34'
- specifies the XKB keyboard option components. These can be used to enhance the keyboard behaviour. Default: not set.
EXAMPLE
The following xorg.conf fragment ensures that user will be able to switch between us and sk layouts by pressing the "menu" key. The scroll lock LED shows which layout is currently active.The XkbVariant option defines which variants of the two layouts should be used. In case of the us layout its default variant is used. In case of the sk layout its qwerty variant is used.
- Section N'34'InputDeviceN'34'
- Identifier "Generic Keyboard" Driver "kbd" Option "CoreKeyboard" Option "XkbRules" "xorg" Option "XkbModel" "pc105" Option "XkbLayout" "us,sk" Option "XkbVariant" ",qwerty" Option "XkbOptions" "grp:menu_toggle,grp_led:scroll"
SEE ALSO
Xorg(1), xorg.conf(5), Xserver(1), X(7).
Index
This document was created by man2html, using the manual pages.
Time: 05:33:53 GMT, December 24, 2015


DIW 2019-Objects365 Full Track Leaderboard
| Rank |
Team Name |
Institution |
AP |
| 1 |
One-Anchor Detector |
Baidu VIS |
0.323 |
| 2 |
DLBird |
ByteDance |
0.311 |
| 3 |
shunlou |
USTC & iFlytek |
0.309 |
| 4 |
vitju |
Tianjin University |
0.224 |
| 5 |
dereyly |
NtechLab |
0.185 |
| 6 |
xj1128 |
JD.com |
0.169 |
| 7 |
JiexiangWang |
Xiamen University |
0.131 |
| 8 |
wxzs5 |
Zhejiang University |
0.085 |
| 9 |
liningxiao |
Qingdao University |
0.031 |
| 10 |
rider |
Beijing University of Posts and Telecommunications |
0.023 |
| 11 |
zhihaocao |
South China University of Technology |
0.014 |
| 12 |
loveisp |
CASIA |
0.005 |
| 13 |
crazyhe |
Beijing University of Posts and Telecommunications |
0.0 |


Plugins are the most efficient way to customize or change the default behavior of a chart. They have been introduced at version 2.1.0 (global plugins only) and extended at version 2.5.0 (per chart plugins and options).
Plugins can be shared between chart instances:
var plugin = {
/* plugin implementation */
};
// chart1 and chart2 use "plugin"
var chart1 = new Chart(ctx, {
plugins: [plugin],
});
var chart2 = new Chart(ctx, {
plugins: [plugin],
});
// chart3 doesn't use "plugin"
var chart3 = new Chart(ctx, {});
Plugins can also be defined directly in the chart plugins
config (a.k.a. inline plugins):
inline plugins are not registered. Some plugins require registering, i.e. can’t be used inline.
var chart = new Chart(ctx, {
plugins: [
{
beforeInit: function (chart, args, options) {
//..
},
},
],
});
However, this approach is not ideal when the customization needs to apply to many charts.
Plugins can be registered globally to be applied on all charts (a.k.a. global plugins):
inline plugins can’t be registered globally.
Plugins must define a unique id in order to be configurable.
This id should follow the npm package name convention:
If a plugin is intended to be released publicly, you may want to check the registry to see if there’s something by that name already. Note that in this case, the package name should be prefixed by chartjs-plugin-
to appear in Chart.js plugin registry.
Plugin options are located under the options.plugins
config and are scoped by the plugin ID: options.plugins.{plugin-id}
.
var chart = new Chart(ctx, {
options: {
foo: { ... }, // chart 'foo' option
plugins: {
p1: {
foo: { ... }, // p1 plugin 'foo' option
bar: { ... }
},
p2: {
foo: { ... }, // p2 plugin 'foo' option
bla: { ... }
}
}
}
});
To disable a global plugin for a specific chart instance, the plugin options must be set to false
:
Chart.register({
id: "p1",
// ...
});
var chart = new Chart(ctx, {
options: {
plugins: {
p1: false, // disable plugin 'p1' for this instance
},
},
});
To disable all plugins for a specific chart instance, set options.plugins
to false
:
var chart = new Chart(ctx, {
options: {
plugins: false, // all plugins are disabled for this instance
},
});
Read more about the existing plugin extension hooks.
Plugins are notified during the initialization process. These hooks can be used to setup data needed for the plugin to operate.
Plugins are notified during throughout the update process.
Plugins can interact with the chart throughout the render process. The rendering process is documented in the flowchart below. Each of the green processes is a plugin notification. The red lines indicate how cancelling part of the render process can occur when a plugin returns false
from a hook. Not all hooks are cancelable, however, in general most before*
hooks can be cancelled.
Plugins can interact with the chart during the event handling process. The event handling flow is documented in the flowchart below. Each of the green processes is a plugin notification. If a plugin makes changes that require a re-render, the plugin can set args.changed
to true
to indicate that a render is needed. The built-in tooltip plugin uses this method to indicate when the tooltip has changed.


#include <db_cxx.h>DBTYPE Db::get_type(void) const;
The Db::get_type method returns the type of the underlying access method (and file format). It returns one of DB_BTREE, DB_HASH or DB_RECNO. This value may be used to determine the type of the database after a return from Db::open with the type argument set to DB_UNKNOWN.


--- title: resizing layout: component ---
A critical feature of GUI based operating systems is the ability to resize a window.
Resizing is typically indicated by a change in the size of the affected window. When resizing with the mouse, the mousce icon will usually change from a pointer to multiple arrows, similar to the image below.
Windows are typically resized by clicking one of the edges and dragging the mouse to the desired shape. They may alternatively be resized by accessing the window menu. For minimizing and maximizing windows, users may use the buttons at the top of the window to minimize or maximize the window size.
The most relevent resize event is the resize
event. A resize
event is triggered when the size of the window has been changed. While maximizing or minimizing a window, a minimize
or maximize
event may also be triggered.
A window is typically in a standby
phase before being resized. Once the mouse starts dragging the edge or corner, the window enters the resizing
state. Once finished, the window reaches the resized
state.
An example of window resizing can be seen here.
Window resizing has remained relatively the same since the introduction of windows in GUI baed operating systems. The basic characteristics of dragging edges and corners, minimizing, and maximizing have remained the primary method of window resizing.
Since it is a critical aspect of any GUI based operating system, most of the priority metrics are vital in this component's design analysis. Users who intend to resize a window must have no confusion as to how to accomplish the task. In the physical world, the natural way of unfolding or unrolling a piece of paper is to pull from either the sides or the corners. Resizing follows this natural way of thinking by allowing the user to increase or decrease the size from the corners and sides of the window, making the process simple to learn. Also, since resizing follows the natural mental model, the way in which the user resizes windows is easily memorable.
Since window resizing corresponds to either mouse input or window menu input, the response is immediate. Since window resizing is easily learnable and highly memorable, it is unlikely that users commit errors when attempting the task.
Due to its simplicity and utilitarian nature, resizing does very little in the way of providing satisfaction to the user. However, this does not detract from the overall good design of window resizing.
Key characteristics of resizing include the changing of the mouse icon from a pointer to arrows along with the visible change in window size.
For resizing, the window visibly grows larger or shrinks according to user input. In older operating systems, a rectangle is shown to represent the size the window will change to when the user stops dragging the mouse.
When resizing windows with a mouse in older operating systems, a rectangle would be drawn to indicate the resulting shape of the resize once finished dragging, as shown in the picture below. The computer is running on Windows 8.1, but is set to the style of older operating systems, such as Windows 98.
For modern operating systems, the window dynamically changes size and content within conforms to the shape as the window is resized, as demonstrated in the components in action video.
Component in Action video is by Youtube user FreeWebTeacher.


Select a Player
Dark
Light
Phil's Players
HLS Manifest:
Play HLS!
Load Demo HLS Manifest
HLS.js Latest
This player sends analytics to
Mux Data


 What kind of entertainment can top that? While you stumble about for a response, let me unleash the powerful story of Paulie.
Mind you, my friend Misha, a Russian immigrant janitor at the university, passed on this tale to me. He found Paulie locked up in the dingy dark basement of the school and was amazed when he heard the bird talk and sing like a human.  But, my friend Misha is a little bit naïve when it comes to exploitation, so I digress.
 He started out as a gift to a little girl named Marie. They were the best of friends, until her overbearing father came home from the war and got all nutso when he found out that Marie had a stuttering problem.
He finds his next home in a pawnshop run by Artie (Buddy Hackett…isn't he dead?) and frequented by a two-bit hoodlum named Benny (Jay Mohr, Jerry Maguire and the voice of Paulie). Apparently, this is where he picks up his tough Jersey accent and insulting demeanor.
Paulie is bought by a lonely widow named Ivy (Gena Rowlands, Unhook the Stars) and the two decide to make their way across the country to find Marie. But, in a strange twist, Ivy is suddenly rendered blind and Paulie is forced to continue on his own. This is an important message to all the kids out there – help a bird find his owner and lose the power of sight.
His next stop is in East Los Angeles, where Paulie finds work at a taco stand run by Igancio (Cheech Marin). He falls in love with another parrot named Lupe, but is again forced to move on.
A bit too heady, Paulie may turn kids off with little action and a lot of talking. But screw them, I liked it.
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


September 2019 Challenges
Fitness/Healthy Eating Challenge
Work out every day, for 30 days straight.
Avoid carbs, sugars, and processed foods.
Details
Workouts: even if its only 15 or 20 minutes, get a workout in. Its important to not overdue, so still only aim for 3–5 serious strength workouts per week.
Food: the goal is to eat as much natural fruit, veggies, and meats as possible. Cutting out processed foods while maintaining calorie intake will force you to eat a lot more veggies and fruit.
Progress
updated 2019–09–07
workouts are going good. i did have to do a few light ones because i’ve been so exhausted this week. but i’ve been getting them all in.
food… forgive me body, for i have sinned. i am eating better than previously, but i still lack in the self control department. but life is about getting back on the horse.
Mental Challenge
Make something every day for 30 days.
Minimize inputs, especially fast burn, low value things.
Details
Make something, even if it only takes 5 minutes. acceptable media for making things includes writing, drawing, cooking/baking (beyond necessary), or making actual, physical, real-world things.
Inputs to be avoided include things like news, social media, online ‘communities’, youtube, etc. Weirdly, I have found myself shying away from music as well, unless it to keep me focused while at work. Some things I have decided will continue to be allowed:
- podcasts on the drive home (but no tech news)
- Do By Friday while in the car with Kayla
- one episode of a DND podcast (The Adventure Zone or Total Party Kill) per day
- books
- movies with family/friends
- predetermined, dedicated research onine
Progress
updated Saturday the 7th
Making has been going well. Inputs, not so great. But tomorrow is another day!
Financial Challenge
Not so much a challenge, as just being more aware/cautious of what we are spending. Its been on our mind with our interest in FIRE.


Correct parameter errors
You must enter the agreed name for the chemical or substance you’re monitoring - exactly as given in the EA controlled list for parameter.
Download the EA controlled list of parameters.
CORY sample file_1 DW Data Returns.xls : Hill Valley
| Row number(s) | Error | Your data |
|---|---|---|
| 2-72 | Incorrect | Dip to leachate |
| 73-143 | Incorrect | Leachate Head above surveyed base |
| 152-155 | Incorrect | Redox |
| 160-163 | Incorrect | Ammoniacal-N as N |
| 168-171 | Incorrect | Chem Oxygen Demand |
| 172-175 | Incorrect | Tot Organic Carbon |
| 176-179 | Incorrect | Alkalinity tot as CACO3 |
| 180-183 | Incorrect | Bio Oxygen Demand |
| 216-219 | Incorrect | Tot Oxidised Nitrogen |
| 220-224 | Incorrect | Data Comments |
| 225-228 | Incorrect | Calcium, Dissolved |


×
HARDWARE ASSEMBLY
DESCRIPTION
We all know how to use a pc. Not all can assemble one.bring to life all the pieces of a dismantled pc.
RULES
- This event is for individual participation.
- Participants must have the following minimum skills:
- A good understanding of computer system hardware components.
- Skills in assembling a computer system and performing basic configuration.
- The participants must proceed to their individual work space allotted to them to start the actual assembly and performing the required basic configuration.


Rocket Elevator, your Expert in commercial and corporate installations
We helped over the years many corporations around the world to get the right elevators..
A quick call to our sales department and engineering department as soon as you have your building plans will ensure you are setup right.
We also specialize in retrofitting if your building as require.


if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install(version = "3.16")
Resources
Career Topics
General
A collection of resources on (scientific) career planning from the Nature Publishing Group.
A resource from the NIH toward Broadening Experiences in Scientific Training
A good list of books on ‘learning how to learn’
Individual Development Plan (IDP)
- myIDP from AAAS. Free IDP focused on scientific career planning.
Data Science Internships
- Insight Data Science arranges short internships with some of the big names.
Academic Job Search/Hiring
- This blog post provides a nice description how applications for faculty positions are reviewed. From my own experience having been on and chaired several faculty searches, I think it’s a fairly accurate description.
Academic Career
Teaching Tools
Software
- learnr - R package that allows development of interactive web-based R tutorials.
-
Feedback at scale - tutorial for using
learnr
andgradethis
as teaching tools.
Books
- rstudio4edu - A Handbook for Teaching and Learning with R and RStudio - still very much a draft.
Online Resources
- Teaching Statistics and Data Science Online - materials for several teacher workshops taught by Mine Çetinkaya-Rundel.
Other
- Bioicons - a collection of free drawings and diagrams on biological topics, which can be used in teaching (or research) presentations.
Programming
R Programming
Lists by others
- [A list of the best R tools] (https://github.com/qinwf/awesome-R)
Online Courses for R
Swirl - An R package that teaches R interactively inside R. Not as polished as DataCamp, but good interactivity, great motivating feedback/messages, beginner and intermediate levels. Completely free.
R books and Tutorials
YaRrr! The Pirate’s Guide to R: A nice R introduction with a piratey bend
Springer has a series of books called ‘Use R’ - A long and growing series of books on a lot of different R topics. From beginner to advanced. Many university libraries have a subscription to Springer Online, which allows you to get the books for free.
Roger Peng’s “R programming for data science” book on Leanpub. Name your own price.
General R Online Resources
Quick R - a great resource for many ‘how do I’ questions of common data analysis and graphics tasks.
Cookbook for R - another useful collection of ‘how do I do X’ information.
R bloggers an aggregation of blogs about all things R
Convenient reference/cheat sheets for some important R tasks
Resource collection to do useful data analysis related tasks in R
R Documentation: - a webpage and R package that tries to enhance the help/documentation files for R and its packages.
The Task View sorting R packages into categories is often useful
R and Shiny
- Official shiny webpage
- Collection of Shiny tips and tricks, see also here and here
- Engineering Production-Grade Shiny Apps
- Outstanding User Interfaces with Shiny - a book covering advanced Shiny material, covering advanced styling, mobile development, integration with other web technologies, etc.
R package development
- “R packages” by Hadley Wickham. This (free online) book alone is enough to get a package done. Should definitely be the first (and maybe even only) source to read/use.
- How to quickly write an R package
- A series of online videos talking about package development
-
devtools
,roxygen2
, etc. - almost required for development. See Hadley’s book. -
available
- tests if a specific name is still available -
usethis
- helps with a lot of setup tasks for packages (and other R coding tasks)
Data Analysis and Statistics
Other lists
Awesome data science - Someone else’s list of resources related to data science.
Machine learning book list - A list of free online books concerning all things machine learning and data analysis.
Online Courses for Data Analysis
Stat 545 at UBC - Data wrangling, exploration, and analysis with R
Check out online providers such as Coursera, edX, Udacity, etc. for more such courses
Hadley taught a [Readings in applied data science] at Stanford and the material is online
A very well done set of online materials teaching some basic stats concepts.
Data Analysis Books
Data Science in Education - all R, nice walk-through case-studies of different datasets and topics one might encounter in education.
Stat 545 - Jenny Bryan’s book based on her previous teaching of a course by that name (see above)
The Effect: An Introduction to Research Design and Causality - focus on causal inference.
Specific Topics
Data cleaning and checking
Check out the R packages tidyr, plyr, dplyr, validate, vtreat (you can find good documentation for all of them)
A nice series of blog posts describing common data manipulations for dplyr
Visualization
- R Graph Gallery: Has lots of examples of graphs and plots in R, including the underlying code that produced the graph. Great place to find a graph similar to one you’d like to make, take the code and adjust it.
Missing Data/Imputation
Check out R packages mi, mice, Amelia, missforest, imputation
Little & Rubin “Statistical Analysis with Missing Data, 2nd Edition”
p-values
Epidemiology specific topics
tableone - A package that allows for convenient creation of a descriptive table based on a data frame.
compareGroups - A package that allows for convenient creation of result tables from linear and logistic (and related) models.
The R survival package - Lots of functionality for survival analysis.
Time-series analysis
The R survival package - Lots of functionality for survival analysis.
Data Sources
Some data Sources
(listed in no particular order)
Kaggle Data - A growing number of datasets used in Kaggle data analysis contests and available for any other use.
Nasdaq Data Link - mainly finance related data
NHANES - longstanding and thorough survey done by CDC
SEER - Cancer data
CDC WONDER - list of mainly CDC online databases
Healthy People Website - contains among other things links to various data sources
HCUP - collection of health related databases, focusing on US wide and state-specific samples of ER and hospital visits. Not free, but not too expensive.
Clinical Study Data Request - a way to get (tedious) access to clinical trial data
EMA Clinical Data Portal - looks like a way to get access to some clinical trial data for EMA registered studies.
MIMIC - a free and open database of critical care patient visits to a Boston hospital.
Data.gov - federak government data platform.
Analyze Survey Data for Free - Step by Step Instructions to Explore Public Microdata from an Easy to Type Website
Inter-university Consortium for Political and Social Research (ICPSR) - access to various social and behavioral sciences data.
A list hosted by Microsoft with links to various data sources
Infectious Disease Specific
General
- Project Tycho - infectious disease data
- http://www.viprbrc.org
- http://eupathdb.org
- ClinEpiDB - a database of (a few) clinical epidemiology studies, focusing on infectious diseases.
- ImmPort
Influenza
- http://www.fludb.org
- WHO Flunet
- gisaid.org
- http://www.cdc.gov/flu/index.htm
- http://www.ncbi.nlm.nih.gov/genomes/FLU/FLU.html
- SystemsInfluenza.org
TB
- OTIS on CDC WONDER: http://wonder.cdc.gov/tb.html
Data and Tools for Cancer Genomics
Data
The Cancer Genome Atlas (TCGA): TCGA is a comprehensive collection of multi-dimensional cancer genomics data covering multiple cancer types.
International Cancer Genome Consortium (ICGC): Description: ICGC provides high-quality genomic and clinical data from various cancer projects worldwide.
Gene Expression Omnibus (GEO): GEO is a public repository hosted by the National Center for Biotechnology Information (NCBI) containing a vast collection of gene expression data, including cancer datasets.
European Genome-phenome Archive (EGA): Description: EGA is a repository for secure storage and sharing of human genetic and phenotypic data, including cancer datasets.
National Cancer Institute (NCI) Genomic Data Commons (GDC): Description: GDC is an open-access data portal providing access to a wide range of cancer genomics datasets.
OncoLnc: Description: OncoLnc is a web resource that provides survival analysis and expression correlation for genes of interest across multiple cancer datasets.
UCSC Cancer Genomics Browser: The UCSC Cancer Genomics Browser offers a comprehensive collection of cancer genomics data integrated with genomic annotations.
GREIN : GEO RNA-seq Experiments Interactive Navigator: GREIN is an interactive web platform that provides user-friendly options to explore and analyze GEO RNA-seq data. GREIN is powered by the back-end computational pipeline for uniform processing of RNA-seq data and the large number (>6,000) of already processed datasets. These datasets were retrieved from GEO and reprocessed consistently by the back-end GEO RNA-seq experiments processing pipeline (GREP2).
Tools
GEPIA2: GEPIA2 is a web-based tool for analyzing gene expression data in cancer. It stands for Gene Expression Profiling Interactive Analysis 2 and is an updated version of the original GEPIA tool.
UALCAN: UALCAN is a web-based platform that provides interactive and comprehensive analysis of cancer transcriptome data. It enables users to explore gene expression patterns, perform survival analyses, and compare gene expression between tumor and normal samples across different cancer types. UALCAN utilizes data from The Cancer Genome Atlas (TCGA) to facilitate cancer research and provide insights into tumor biology.
cBioPortal for Cancer Genomics:: cBioPortal hosts a large collection of cancer genomics datasets, allowing users to explore and visualize the data.
ONCOMINE: ONCOMINE is a powerful web-based platform for the analysis and visualization of cancer transcriptomic data. It provides researchers with access to a vast collection of publicly available gene expression datasets derived from cancer studies. ONCOMINE allows users to explore gene expression patterns, identify potential biomarkers, and compare gene expression between different cancer types or subtypes.
Guideline for Bioconductor Users
Bioconductor is an open-source and open-development software project that provides a comprehensive collection of bioinformatics and computational biology tools in the R programming language. It focuses on the analysis and comprehension of high-throughput genomic data, including DNA sequencing, RNA sequencing, microarray analysis, proteomics, and more.
Required software
- R: http://www.r-project.org/ (FREE)
- RStudio (additional libraries required): http://www.rstudio.com/ (FREE)
Prework
Before attending the any workshop please have the following installed and configured on your machine. - Recent version of R - Recent version of RStudio - Most recent release of the Bioconductor and other packages used in courses
Install the latest release of R, then get the latest version of Bioconductor by starting R and entering the commands.
-
Ensure you can knit R markdown documents
- Open RStudio and create a new Rmarkdown document
- Save the document and check you are able to knit it.
Install Bioconductor Packages
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install()
Install specific packages, e.g., “GenomicFeatures” and “AnnotationDbi”, with
The install()
function (in the BiocManager package) has arguments that change its default behavior; type ?install for further help.
R Packages RNASeq and Single-cell RNA-seq Analysis
-
DESeq2
: DESeq2 is a widely used package for differential gene expression analysis in RNA-seq data. -
edgeR
: edgeR is another popular package for differential gene expression analysis in RNA-seq data. -
limma
: limma is a package commonly used for the analysis of microarray and RNA-seq data, particularly for differential expression analysis. -
Ballgown
: Ballgown is a package for differential expression analysis and visualization of transcriptome assembly data. -
DEXSeq
: DEXSeq is specifically designed for the detection of differential exon usage in RNA-seq data. -
NOISeq
: NOISeq is a package for non-parametric analysis of differential expression in RNA-seq data. -
clusterProfiler
: clusterProfiler is a package for functional enrichment analysis of gene clusters derived from RNA-seq data. -
GenomicFeatures
: GenomicFeatures provides tools for working with genomic features, such as gene models, and is useful for annotating RNA-seq data. -
Seurat
: Seurat is a package for single-cell RNA-seq data analysis, allowing exploration and visualization of cellular heterogeneity.
Blogs for R Programming, Statistics, and Data Analyis
- Programiz - https://www.datamentor.io/r-programming/
- PennState STAT 484 - https://online.stat.psu.edu/stat484/
- PennState Topics in R Statistical Language - https://online.stat.psu.edu/stat484/
- Simply Statistics - https://simplystatistics.org/
- TutorialPoint - https://www.tutorialspoint.com/r/index.htm
- R for Biologists - https://www.rforbiologists.org/
- Computational Genomics with R - https://compgenomr.github.io/book/
- Stat and R - https://statsandr.com/
- Rafa Lab - https://rafalab.github.io/pages/harvardx.html
- University of Florida - https://bolt.mph.ufl.edu/software/r-phc-6055/
Videos
-
July 9, 2023: I’m thrilled to announce that the highly anticipated videos from our workshop on “R for Research: Fundamentals of R - Part 1” are now available for viewing. Whether you missed the live event or want to revisit the valuable insights shared during the session, these videos are your gateway to mastering the basics of R programming language for data analysis and research. Join us as we explore the foundations of R and learn essential skills to enhance your data analysis capabilities. Don’t wait any longer; dive into the videos today and take your research to new heights! Check it out:
-
April 12, 2023: Watch this informative 2-hour workshop on how NASA Earth Observing Data can help improve public health. Discover how we can use these data to monitor our environment and identify potential health risks. Learn about the different ways NASA Earth Observing Data can benefit our communities and keep us safe. Check it out:


Serves as the main interface to Agave for a webapp developer, with the {@link agave.AgaveFilter AgaveFilter} serving as the Front Controller in a Model-View-Controller architecture, and several annotations to describe how handler methods will field HTTP requests. The {@link agave.HandlesRequestsTo HandlesRequestsTo} annotation specifies the URI pattern that the handler method will field.
An example of a handler method:
public class FunHandler { @HandlesRequestsTo("/haveFun") public void haveSomeFun(FunForm funForm) throws ServletException, IOException { // wheeee! } }


{% comment %} # Copyright 2009-2010 by Ka-Ping Yee # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. {% endcomment %}
| Date | Topic URL |
|---|


CrimPapers
Articles published on 14 June 2020
On 14 June 2020, 6 new articles were published in 4 journals.
Staying Home, Staying Safe? A Short-Term Analysis of Covid-19 on Dallas Domestic Violence
Child Victim Services in the Time of Covid-19: New Challenges and Innovative Solutions
Endocrine Markers of Puberty Timing and Antisocial Behaviour in Girls and Boys by Philip Jules Simon Michielsen,
sabine Judith Roza,
hjalmar Johan Carel Marle
The Role of Sex on Officer Perpetrated Intimate Partner Violence: An Empirical Analysis of Mechanisms of Intimate Partner Violence by Matthew Williamson
Ingroup Biases of Forensic Experts: Perceptions of Wrongful Convictions Versus Exonerations by Kyle C. Scherr, Itiel E. Dror
The Potential Effect of Neurobiological Evidence on the Adjudication of Criminal Responsibility of Psychopathic Defendants in Involuntary Manslaughter Cases by Colleen M. Berryessa, Federica Coppola, Gerardo Salvato


{% extends "base.html" %}
{% load staticfiles %}
{% block extra_styles %}
{% endblock %}
{% block title %}Why I build Thanks Open Source{% endblock %}
{% block content %}
Why I build Thank You Open Source
I taught myself programming in my early 20s, when I suck at English and didn’t have any friend with programming skills since I majored in civil engineering. So most of the time I just learned from outdated and poorly translated docs and low-quality blogs. I was also in debt since my programming skills weren’t good enough to get me a great job, so I felt quite helpless at that time.
One day I ran into a problem that didn’t know how to solve even after searching online for a whole day and felt quite frustrated. I asked the maintainers on the GitHub Issues page for help (I later realized that I should be using StackOverflow instead in such case). However, the maintainers there were so kind, so nice to answer my silly questions. See
I am especially grateful to cnoon, the maintainer of Alamofire, and desandro,the maintainer of masonry, the first maintainer I meet, They just so nice and always willing to help others. Also, they're definitely some guys you wanna have a beer together. Thank you so much for helping me, a newbie, to be a better programmer. I wanted to give something back to the community,so I later started to make contribution on Django and taught newbies in some NGO programming camps. I learned a lot from my students, and enjoyed the happiness teaching gave me that salary never could. Maybe this happiness is something we share and what we pass onto others through our passion and devotion.
Most of the maintainers on the internet are such excellent programmers who could live an easier life without spending their spare time to build projects and help people they don't know and will probably never know, but they do, and year after years they continue to do so. Most of them don't want to add any ad to their projects to make profit, so I build this project to say thank you and provide them a place to promote their side-projects or websites.
In the end, I would like to quote the great physicist Richard Feynman's words but changing "physics" into "programming" for my case here:
"[Programming] isn't the most important thing. Love is."


| PostgreSQL 9.0.10 Documentation | ||||
|---|---|---|---|---|
| Prev | Up | Appendix B. Date/Time Support | Next |
The Julian calendar was introduced by Julius Caesar in 45 BC. It was in common use in the Western world until the year 1582, when countries started changing to the Gregorian calendar. In the Julian calendar, the tropical year is approximated as 365 1/4 days = 365.25 days. This gives an error of about 1 day in 128 years.
The accumulating calendar error prompted Pope Gregory XIII to reform the calendar in accordance with instructions from the Council of Trent. In the Gregorian calendar, the tropical year is approximated as 365 + 97 / 400 days = 365.2425 days. Thus it takes approximately 3300 years for the tropical year to shift one day with respect to the Gregorian calendar.
The approximation 365+97/400 is achieved by having 97 leap years every 400 years, using the following rules:
| Every year divisible by 4 is a leap year. |
| However, every year divisible by 100 is not a leap year. |
| However, every year divisible by 400 is a leap year after all. |
The papal bull of February 1582 decreed that 10 days should be dropped from October 1582 so that 15 October should follow immediately after 4 October. This was observed in Italy, Poland, Portugal, and Spain. Other Catholic countries followed shortly after, but Protestant countries were reluctant to change, and the Greek Orthodox countries didn't change until the start of the 20th century. The reform was observed by Great Britain and Dominions (including what is now the USA) in 1752. Thus 2 September 1752 was followed by 14 September 1752. This is why Unix systems have the cal program produce the following:
$ cal 9 1752 September 1752 S M Tu W Th F S 1 2 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
The SQL standard states that "Within the definition of a 'datetime literal', the 'datetime value's are constrained by the natural rules for dates and times according to the Gregorian calendar". Dates between 1582-10-05 and 1582-10-14, although eliminated in some countries by Papal fiat, conform to "natural rules" and are hence valid dates. PostgreSQL follows the SQL standard's lead by counting dates exclusively in the Gregorian calendar, even for years before that calendar was in use.
Different calendars have been developed in various parts of the world, many predating the Gregorian system. For example, the beginnings of the Chinese calendar can be traced back to the 14th century BC. Legend has it that the Emperor Huangdi invented that calendar in 2637 BC. The People's Republic of China uses the Gregorian calendar for civil purposes. The Chinese calendar is used for determining festivals.
The "Julian Date" is unrelated to the "Julian calendar". The Julian Date system was invented by the French scholar Joseph Justus Scaliger (1540-1609) and probably takes its name from Scaliger's father, the Italian scholar Julius Caesar Scaliger (1484-1558). In the Julian Date system, each day has a sequential number, starting from JD 0 (which is sometimes called the Julian Date). JD 0 corresponds to 1 January 4713 BC in the Julian calendar, or 24 November 4714 BC in the Gregorian calendar. Julian Date counting is most often used by astronomers for labeling their nightly observations, and therefore a date runs from noon UTC to the next noon UTC, rather than from midnight to midnight: JD 0 designates the 24 hours from noon UTC on 1 January 4713 BC to noon UTC on 2 January 4713 BC.
Although PostgreSQL supports Julian Date notation for input and output of dates (and also uses them for some internal datetime calculations), it does not observe the nicety of having dates run from noon to noon. PostgreSQL treats a Julian Date as running from midnight to midnight.


Quick Start¶
What is WD.py?¶
WD.py is a Python WebDriver client implemented most of the APIs in the WebDriver Protocol. It was originally designed for Macaca (A Node.js powered WebDriver server), but also available for any other implementation of WebDriver server such as Selenium, Appium and etc.
Installation¶
To install WD.py, simply:
pip install wd
To get latest code from source via GitHub.
git clone https://github.com/macacajs/wd.py.git
Prerequisite¶
WD.py does not start the WebDriver server automaticalliy, you may use Macaca to start a WebDriver server and run the tests after.
Usage¶
Configure the WebDriver
Firstly, you need to configure the WebDriver with desired capabilities and server url.
from macaca import WebDriver
desired_caps = {
'browserName': 'Chrome', # Electon, Safari(iOS).
'platformName': 'desktop', # iOS, Android.
'platformVersion': '*',
'autoAcceptAlerts': True # Accept the Alerts in page automaticalliy.
}
server_url = 'http://<IP_ADDRESS>:3456/wd/hub/'
# You can omit the server_url if you use the default url above.
driver = WebDriver(desired_caps, server_url)
# You can also use a dict to represent the url.
driver = WebDriver(desired_caps, {
'protocol': 'https',
'hostname': '<IP_ADDRESS>',
'port': 5678,
'username': 'macaca',
'password': '123456',
'path': '/hub'
})
# Defaults
{
'protocol': 'http',
'hostname': '<IP_ADDRESS>',
'port': 3456,
'path': '/wd/hub'
}
# Which equals to
driver = WebDriver(desired_caps, 'https://macaca:123456@<IP_ADDRESS>:5678/hub')
Init the WebDriver
# Create a new session towards WebDriver server.
driver.init()
Stop the WebDriver
# Delete current session.
driver.quit()
Attach to an existing session
# Attach to a given session.
driver.attach('012-345-678-9')
WebDriver methods
The instance methods of WebDriver mostly related to the global action of driver. For example, switch to a new url, refresh and get title.
# Navigate to a url.
driver.get('https://www.google.com')
# Refresh current page.
driver.refresh()
# Get title of current page
title = driver.title
Find element(s)
The Find Element and Find Elements commands allow look up of individual elements and collections of elements, respectively. Locator strategies are listed below:
- “id”
- “xpath”
- “link text”
- “partial link text”
- “tag name”
- “class name”
- “css selector”
The basic method of finding element(s) is element:
# Finding the element which its `id` matches `login`
driver.element('id', 'login')
But in most cases, you don’t need to use this basic method, there are a lot of extension methods for convenience.
# Finding the element which its `id` matches `login`
driver.element_by_id('login')
# Similarly, all the strategies can be append after `element` using snake case.
driver.element_by_id('login')
driver.element_by_xpath('//*[@id="finding-elements-to-interact"]/table[4]')
driver.element_by_link_text('macaca')
driver.element_by_partial_link_text('maca')
driver.element_by_tag_name('input')
driver.element_by_class_name('btn')
driver.element_by_css_selector('.btn')
# And we have element_if_exists and element_or_none to avoid
# raise WebDriverException of ` no such element` when element not found.
# Return True if the element does exists and return False otherwise.
driver.element_by_id_if_exists('login')
# Return Element if the element does exists and return None otherwise.
driver.element_by_id_or_none('login')
# More over, there are `wait for` method to wait for element
# till satisfy the given condition
# Default to wait 10s, each interval 1s.
# The asserter function defaults to asserters.is_displayed.
# See more at API section.
driver.wait_for_element_by_id('login')
WebElement methods
The instance methods of WebElement mostly related to the action element such as click the element, get the tag name or get the innerText of the element.
The WebElement instance is returned by finding element command.
from macaca import WebElement
# Retrieve the element by id
web_element = driver.element_by_id('login')
print(type(web_element) == WebElement) # True
# Click the element
web_element.click()
# Get the tag name of the element
tag_name = web_element.tag_name
# Get the innerText of the element
text = web_element.text
Futhermore, all the element methods on WebDriver can be used on WebElement, it means to find element from the current Web Element.
web_element.element_by_id('ss')
Keys
We can send a sequence of key strokes to an element when need to fulfill a input field.
web_element.send_keys('123456')
# or
driver.send_keys(web_element, '123456')
# `send_keys` also accept an array, it's very useful when sending special keys.
driver.send_keys(web_element, [1, 2, 3, 4, 5, 6])
Special keys means the pressable keys that aren’t text, learn more at Character Types.
For easily use, the keys defined in above protocol can import from Keys module directly.
>>> from macaca import keys
>>> print(keys.ENTER)
\uE007
>>> print(keys.DELETE)
\uE017
It is convenient to send special keys using array.
from macaca.keys import ENTER, DELETE
web_element.keys([1, DELETE, 1, 2, 3, 4, 5, 6])
Screenshot
There are two methods to use when taking screenshot.
# Return the base64 encoded string of the screenshot.
base64_str = driver.take_screenshot()
# Save screenshot to the given path.
driver.save_screenshot('./screen.png')
# `save_screenshot` has the optional second parameter
# to decide whether to ignore the IOError when failed to
# save to file system for some reason.
# For example, no permission to write.
>>> driver.save_screenshot('/etc/screen.png')
IOError: [Errno 13] Permission denied: '/etc/screen.png'
# Nothing happened.
>>> driver.save_screenshot('/etc/screen.png', True)
Switch context
For mobile testing, we will need to switch context between Native and Webview.
# Get existing contexts
ctxs = driver.contexts
print(ctxs) # ['NATIVE', 'WEBVIEW_1', 'WEBVIEW_2']
# Switch to `WEBVIEW_1`
driver.context = 'WEBVIEW_1'
print(driver.context) # WEBVIEW_1
Execute JavaScript Snippets
In some complex situation, we may need to inject a snippet of JavaScript into the page and get whatever we want.
# You can use `arguments` in the script to represent the
# indexed parameter after the `script`.
script = 'return document.querySelector(".btn").tagName === arguments[0]'
args = ['div']
result = driver.execute_script(script, *args)
# The script above equals to a IIFE in JavaScript.
# function () {
# return document.querySelector(".btn").tagName === "div"
# }()
Fluent Interface
All the APIs in WebDriver and WebElement support fluent interface, which means we can chain the method if the method returns None.
>>> driver.get('https://www.google.com').element_by_id('login').click()
# For method that returns something, it's not working.
>>> driver.element_by_id('login').get_attribute('class').click()
AttributeError: 'str' object has no attribute 'click'
Due to the nature of Python, it is illegal to write method chaining like JavaScript below:
driver
.get('https://www.google.com')
.element_by_id('login')
.click()
For Pythoner, we recommend two coding style for you to choose.
# Use additional parenthesis
(
driver
.get('https://www.google.com')
.element_by_id('login')
.click()
)
# Use backslashes
driver \
.get('https://www.google.com') \
.element_by_id('login') \
.click()
Next Step¶
TODO


Interface IHasComponents
Interface for an object that has components that can be added, removed, checked for, and retrieved by type. Typically, you would implement this via a backing field of type ComponentContainer, which implements the logic for these functions. See that class's documentation for details of functionality.
Namespace: GoRogue
Assembly: GoRogue.dll
Syntax
public interface IHasComponents
Methods
| Improve this Doc View SourceAddComponent(Object)
Adds the given object as a component. Throws ArgumentException if the specific instance has already been added.
Declaration
void AddComponent(object component)
Parameters
| Type | Name | Description |
|---|---|---|
| System.Object | component | Component to add. |
GetComponent<T>()
Gets the first component of type T that was added, or default(T) if no component of that type has been added.
Declaration
T GetComponent<T>()
Returns
| Type | Description |
|---|---|
| T | The first component of Type T that was attached, or default(T) if no components of the given type have been attached. |
Type Parameters
| Name | Description |
|---|---|
| T | Type of component to retrieve. |
GetComponents<T>()
Gets all components of type T that are added.
Declaration
IEnumerable<T> GetComponents<T>()
Returns
| Type | Description |
|---|---|
| System.Collections.Generic.IEnumerable<T> | All components of Type T that are attacked. |
Type Parameters
| Name | Description |
|---|---|
| T | Type of components to retrieve. |
HasComponent(Type)
Returns whether or not there is at least one component of the specified type attached. Type may be specified by using typeof(MyComponentType).
Declaration
bool HasComponent(Type componentType)
Parameters
| Type | Name | Description |
|---|---|---|
| System.Type | componentType | The type of component to check for. |
Returns
| Type | Description |
|---|---|
| System.Boolean | True if the implementer has at least one component of the specified type, false otherwise. |
HasComponent<T>()
Returns whether or not there is at least one component of type T attached.
Declaration
bool HasComponent<T>()
Returns
| Type | Description |
|---|---|
| System.Boolean | True if the implemented has at least one component of the specified type attached, false otherwise. |
Type Parameters
| Name | Description |
|---|---|
| T | Type of component to check for. |
HasComponents(Type[])
Returns whether or not the implementer has at least one of all of the given types of components attached. Types may be specified by using typeof(MyComponentType)
Declaration
bool HasComponents(params Type[] componentTypes)
Parameters
| Type | Name | Description |
|---|---|---|
| System.Type[] | componentTypes | One or more component types to check for. |
Returns
| Type | Description |
|---|---|
| System.Boolean | True if the implementer has at least one component of each specified type, false otherwise. |
RemoveComponent(Object)
Removes the given component. Throws an exception if the component isn't attached.
Declaration
void RemoveComponent(object component)
Parameters
| Type | Name | Description |
|---|---|---|
| System.Object | component | Component to remove. |
RemoveComponents(Object[])
Removes the given component(s). Throws an exception if a component given isn't attached.
Declaration
void RemoveComponents(params object[] components)
Parameters
| Type | Name | Description |
|---|---|---|
| System.Object[] | components | One or more component instances to remove. |


Module Drag
Component to handle drag action on node.
Drag have correct handling for multitouch and swap
touched while dragging. Drag will be processed even
the cursor is outside of node, if drag is already started
| style |
Component style params. |
-
init(self, node, on_drag_callback)
-
Drag component constructor
Parameters:
- self
Drag
- node
node
GUI node to detect dragging
- on_drag_callback
function
Callback for on_drag_event(self, dx, dy)
-
set_click_zone(self, node)
-
Strict drag click area. Useful for
restrict events outside stencil node
Parameters:
- self
Drag
- node
node
Gui node
-
style
-
Component style params.
You can override this component styles params in druid styles table
or create your own style
Fields:
- DRAG_DEADZONE
number
Distance in pixels to start dragging
(default 10)
-
on_touch_start
-
Event on touch start callback(self)
- on_touch_start
druid_event
-
on_touch_end
-
Event on touch end callback(self)
-
on_drag_start
-
Event on drag start callback(self)
- on_drag_start
druid_event
-
on_drag
-
on drag progress callback(self, dx, dy)
- on_drag
druid_event
Event
-
on_drag_end
-
Event on drag end callback(self)
-
is_touch
-
Is component now touching
-
is_drag
-
Is component now dragging
-
can_x
-
Is drag component process vertical dragging. Default - true
-
can_y
-
Is drag component process horizontal. Default - true
-
x
-
Current touch x position
-
y
-
Current touch y position
-
touch_start_pos
-
Touch start position


macbook pro mid-2017 make
2.3GHz dual-core 7th-generation Intel Core i5 processor, Turbo Boost up to 3.6GHz, Intel Iris Plus Graphics 640, 8GB 2133MHz LPDDR3 memory, 256GB SSD storage1, Retina display, Two Thunderbolt 3 ports
Available: 4
Allowed minimum: 1
Price: Ksh. 99,999


Pan the two maps below and observe that the blank background underneath the tiles is less likely to be seen when using the EdgeBuffer plugin.
Add the script to your document. E.g.
<script src="./leaflet.edgebuffer.js"></script>
Add the edgeBufferTiles property to your tiled map layers (or any L.GridLayer-based layer). The value is the minimum number of tiles to load outside of the visible area. Fractional values are permitted. E.g.
var openStreetMap = L.tileLayer('http://{s}.tile.osm.org/{z}/{x}/{y}.png', { edgeBufferTiles: 1 })
See https://github.com/TolonUK/Leaflet.EdgeBuffer for the code and to download.


This page describes the different types of tablespaces
Problem Description
With the knowledge of different storage object types, its important to determine the type of space to allocate to store the data.
Operation
Different tablespaces for specific storage requirements are present in DB2. An appropriate tablespace design is chosen for best database performance.
Solution
Table spaces are the logical layer between the database and the tables stored in that database. Table spaces are created within a database and tables are created within table spaces. DB2 supports three kinds of table spaces :
- System Managed Space (SMS): Here, the operating system's file system manager allocates and manages the space. SMS table spaces require very little maintenance. However, SMS table spaces offer
fewer optimization options and may not perform as well as DMS table spaces
- Database Managed Space (DMS): Here, the database manager controls the storage space. This table space is, essentially, an implementation of a special purpose file system designed to best meet the needs of the
database manager
- Automatic Storage With DMS:Automated storage is not really a separate type of table space, but a different way of handling DMS storage. DMS containers require more maintenance and Automatic Storage was introduced as a way of simplifying space management


Team: {{student.classroomName}} Grade Level: {{student.gradeLevel}} Emotion Score: {{student.totalScore}}


---
layout: post
title: Chessboard chamber set
date: '2013-04-07T16:37:00+02:00'
categories:
- Atoleiros Battle
- Set Design
- Storyboards
picture_url: https://film-Storyboards.tumblr.com/post/47400795741/chessboard-chamber-set
---
Chessboard Chamber set.


Contact/Hire Me
1
Your contact information
Name:
Organization:
Email Address:
Phone Number:
2
Your message
Message:
Submit


19703 Hubbard Creek Court, Cypress, Texas – 77433
832-220-3289<PHONE_NUMBER>
<EMAIL_ADDRESS>customerservice@ctservices.com


-
Asynchronous completion handlers with Result type
This week we will talk about Result enum, which had been a part of the standard library since Swift 5. With Result enum, we can easily describe the resulting state of an asynchronous operation. It can be success or failure at one time not both of them. Let's take a look at Result enum definition in the Swift standard library.
-
Inclusive enums with OptionSet
Enums are one of the most powerful features of Swift language. It forms Value-Oriented Programming in conjunction with Structs. Enum is the best way to describe the exclusive state in Swift, but what about the case when you need an inclusive state. Today we will talk about OptionSet protocol and how we can achieve inclusive states with it.
-
Adapting app for iPad with UISplitViewController
Apple promotes iPad as the primary computer for regular users. This trend is visible during the last couple of years. More and more users start to use iPad as the main device. I think it is essential to support iPad screens and efficiently use that space. This week we will talk about adapting apps for iPad with the help of UISplitViewController.
-
Deep dive into Pattern matching with ~= operator


The Apache Software License, Version 1.1
Copyright (c) 1999 The Apache Software Foundation. All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
- Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
- Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
- The end-user documentation included with the redistribution, if any, must include the following acknowledgment:
"This product includes software developed by the Apache Software Foundation (http://www.apache.org/)."
Alternately, this acknowledgment may appear in the software itself, if and
wherever such third-party acknowledgments normally appear.
- The names "Xerces" and "Apache Software Foundation" must not be
used to endorse or promote products derived from this software without prior
written permission. For written permission, please contact<EMAIL_ADDRESS>- Products derived from this software may not be called "Apache",
nor may "Apache" appear in their name, without prior written permission
of the Apache Software Foundation.
 IN NO EVENT SHALL THE
APACHE SOFTWARE FOUNDATION OR ITS CONTRIBUTORS BE LIABLE FOR ANY DIRECT,
INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF
USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE,
EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. ====================================================================
This software consists of voluntary contributions made by many individuals
on behalf of the Apache Software Foundation and was originally based on software
copyright (c) 1999, International Business Machines, Inc. For more information
on the Apache Software Foundation, please see <http://www.apache.org/>.
|


glab release list- Display information about a specific release:
glab release view tag- Create a new release:
glab release create tag- Delete a specific release:
glab release delete tag- Download assets from a specific release:
glab release download tag- Upload assets to a specific release:
glab release upload tag path/to/file1 path/to/file2


In the beginning there was nothing: I was staring at the COSS exchange page, how does one tackle the uncharted space with little knowledge of how these things work? I was lurking around discord and reddit, untill I got lucky enough to find an internall api. And from that point, the history of CELT begins.
Find out more!Our goal is to make COSS usefull for everyone by providing liquidity!
Everyday we are trying to update the bot with new features adn trading strategies. The bot becomes smarter and smarter every week.
Lorem ipsum dolor sit amet, consectetur adipisicing elit. Quod tenetur ex natus at dolorem enim! Nesciunt pariatur voluptatem sunt quam eaque, vel, non in id dolore voluptates quos eligendi labore.
Lorem ipsum dolor sit amet, consectetur adipisicing elit. Rem magni quas ex numquam, maxime minus quam molestias corporis quod, ea minima accusamus.


Communication complexity and information theory
23 Dec 2017I attended the annual meeting of the complexity and algorithms working group of the CNRS (GT CoA) a few weeks ago, and I wanted to review some parts of it. This is the first element of a series of posts. The talks at this meeting were quite technical, and I cannot give a deep overview of each them. So instead I will just write about some details that caught my attention, and that are easy to explain, or, like today, give a very succinct summary of the story. For most of the talks, the post will deal with basic considerations, and not with the new things developed by the speakers. For comments: feuilloley [at] irif [dot] fr.
The first talk was actually a lecture, entitled Information Theory and Communication Protocols by Florent Urrutia from IRIF at Paris Diderot university.
Communication complexity
In a nutshell, communication complexity measures the number of bits that some agents must exchange to complete a task. More precisely, in the basic setting, there are two players, traditionally named Alice and Bob, and each of them is given half of an input bit string. They both have to output the result of a boolean function of the (whole) input. A task is for example to output the parity of the number of 1s in the input string. Before outputting, they can communicate, that is exchange some bits one after the other. Then an easy protocol is to send each other all the (half-)inputs they have, and then to compute the output in parallel. The basic question is: for which tasks you can do better, that is sending less bits than the size of the input?
Information complexity
In another nutshell, information theory measure the amount of information contained in some message given some context. This has been introduced by Shannon in the forties, and is used in many contexts. It requires formulas, with logs, sups, infs etc. to make this precise, and I do not want to dive into this. If you know about Shannon entropy, mutual information etc., you know what I mean. Otherwise, no problem, it is not really necessary for this post. Now, very roughly speaking, information complexity measures the amount of information that one needs to reveal to solve some task under some distribution, and its definition is based on the one of the entropy.
Information as a lower bound on communication
The focus of the course was to look at the relation between these two fields. The main point, that is very powerful, can be stated as a naive sentence: the number of bits communicated in any protocol to solve the task must be larger than the information the players have to reveal, in theory, when communicating. Namely, the communication complexity must be at least the information complexity. As I have not properly defined the two notions, this may sound quite useless, I will try to convince the reader that it is interesting. What is surprizing is that these two notions are quite different in the way they are defined. The first one is defined as a simple worst-case measure and has a quite combinatorial flavour, it really counts bits. Indeed it is possible to prove lower bound on communication complexity by studying some combinatorics of 0-1 matrices.1 The second one is defined as an infimum (over communication protocols) of a supremum over distributions of inputs of an (entropy-like) function that is based on a sum of logs. A pretty non-combinatorial object.
I guess this inequality mainly means that these definitions are the right ones..!
Further
It is not true that communication complexity is equal to information complexity, there can even be an exponential gap between those, but this happens in some very special context. See the paper Exponential Separation of Information and Communication for Boolean Functions (not for the beginners).
Nevertheless, this approach is very powerful, and almost all the lower bounds we have on communication complexity can be phrased as information complexity lower bounds (See this paper).
Multi-party communication (the more the merrier… maybe not)
Multi-party communication is the setting in which the input is split between more than two players. In this new setting, lower bounds are difficult to get. A natural step is to use information complexity. But this is not easy. There are different ways to define the information revealed during a multi-party protocol, and none of ones we know gives very good bounds.
Footnotes
-
See the classic rectangle method, for example in this survey. ↩


FILM TITLE: IKIRU DIRECTOR: AKIRA KUROSAWA COUNTRY: JAPAN 1952 CAST: Takishi Shimura, Nobuo Kaneko, Kyoko Saki SUPER FEATURES: Wonderfull Story....
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
This is one of Akira Kurosawa's earlier films.
And it is a beaut. A real beaut.
An elder gentleman finds out that he is going to die soon, and begins his depression. After his affair with the drink, one day he comes face to face with one thing which saves him. He becomes a bit of a child again, and sees an old run down area, and decides that a park should be built there for children.
And much to the chagrin of anyone who gets in his way, the old man succeeds in bypassing all the red tape, and gets the job done. One good deed which made his life seem totally worthwhile. He was no longer empty.
Simplest of stories, simplest of shoots, and yet, as is customary of Kurosawa, the combination of the two makes for an extraordinary film which few people get a chance to see, and which our local video store probably got by accident.
There are many touches through out this film that differ from the Kurosawa mold. One keeps expecting to find a grandiose film with magnanimous gestures and filming, and instead one finds a rather intimate film that uses the close up, not for acting this time, but to get us to understand what is happening around this man. The directing touch is so sweet, that it is difficult to dislike this film, and it makes it very deserving of its awards.
Worth seeing. Truly, a beautiful little film. Excellent acting. And the old man is addictive.......
5 GIBLOONS
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


FREE DELIVERY | ORDER BEFORE 1PM FOR NEXT DAY DELIVERY | FREE RETURNS
Home & Electricals
Inspiration
Men
Women


New Era with the New UT
Jammu and Kashmir is a region administered by India as a union territory, and constituting the southern portion of the larger Kashmir region, which has been the subject of a dispute between India and Pakistan since 1947, and between India and China since 1962.The region of Jammu and Kashmir is separated by the Line of Control from the Pakistani-administered territories of Azad Kashmir and Gilgit-Baltistan in the west and north respectively. It lies to the north of the Indian states of Himachal Pradesh and Punjab and to the west of Ladakh, which is also subject to the dispute as a part of Kashmir, and administered by India as a union territory.
The order comes two days after the nation's newest union territories were formally created and received their first Lieutenant Governors; Girish Chandra Murmu, the former Union Expenditure Secretary, was sworn in as the first Lieutenant-Governor of Jammu and Kashmir
The new UTs came into existence on Thursday, which was the 144th birth anniversary of Sardar Vallabhbhai Patel, who is credited for the merger of over 560 princely states into the Union of India.With the bifurcation of Jammu and Kashmir, the number of states in India has come down to 28 and the number of Union Territories has gone up to nine.


{% extends "tx_lobbying/base.html" %} {% block page_title %}{{ object }}{% endblock %} {% block main %} {% include "tx_lobbying/includes/coversheet.html" with cover=object data=object.raw_data %} {% endblock %}


Technical Blog: The Basics of Active Record
September 22st, 2014
Active Record: The "M" in MVP
Active Record is the "M" in MVC (Model-View-Controller) which is the layer of the system responsible for representing business data and logic. Before we get into Active Record, we need to dwelve into MVW, Model-View-Controller.
Model-View-Controller (MVP)
- Models
- Models represent knowledge. A model could be a single object, or it could be some structure of objects. There should be a one-to-one correspondence between the model and its parts on the one hand, and the represented world as perceived by the owner of the model on the other hand.
- Views
- A view is a visual representation of its model. It would ordinarily highlight certain attributes of the model and suppress others. It is thus acting as a presentation filter. A view is attached to its model (or model part) and gets the data necessary for the presentation from the model by asking questions. It may also update the model by sending appropriate messages. All these questions and messages have to be in the terminology of the model, the view will therefore have to know the semantics of the attributes of the model it represents.
- Controllers
- A controller is the link between a user and the system. It provides the user with input by arranging for relevant views to present themselves in appropriate places on the screen. It provides means for user output by presenting the user with menus or other means of giving commands and data. The controller receives such user output, translates it into the appropriate messages and pass these messages on to one or more of the views.
- Model = HTML
- View = CSS
- Controller = Browser
- Represents models and their data.
- Represent associations between these models.
- Represent inheritance hierarchies through related models.
- Validate models before they get persisted to the database.
- Perform database operations in an object-oriented fashion.
The MVC Model
A simple example of MVC is this:
Back to Active Record
In Active Record, objects carry both persistent data and behavior which operates on that data. Active Record takes the opinion that ensuring data access logic is part of the object will educate users of that object on how to write to and read from the database.