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| I l@ve RuBoard |
As a fitting finale to this section of the book, we will discuss how you can incorporate Active Scripting in your Python application. If you are working with Python, you already have a very cool extension language built right-in, but there may be good reasons for wanting to extend this to include other languages, marketing being just one!
If there is any end of the Active Scripting specification to work with, creating an application that supports Active Scripting is the one to choose over building a language engine. The COM specifications for applications using Active Scripting are not difficult to understand, and Python has additional helpers that reduce this to a small amount of code.
The sample application exposes an Active Scripting object model. It loads script code from a text file and executes it using any Active Scripting-supported language: two more examples will demonstrate VBScript and Python. The object model the application exposes is simple; there's a single Application object supporting a single method Echo, which displays a message box.
These are the steps:
Creates a PyIActiveScriptSite object. The win32com.axscript.server.axsite module provides an Active Scripting Site base-class that is suitable for our purposes. All you need to do is add an error handler; it's simple and prints the message to the console.
Defines the object model. The win32com.axscript.server.axsite module allows you to specify a dictionary of string-object pairs, where string is the name for the object model, and object is any PyIDispatch object. The example provides a simple Python COM object. For more information on implementing COM objects using Python, see Chapter 12.
Loads the code and passes it to the required language engine. This sample accepts two command-line parameters, the name of the language to use, and the name of a text file containing the code:
# ActiveApp.py - Demonstration of a Python Active Scripting Application. import string, sys from win32com.axscript import axscript from win32com.axscript.server import axsite import pythoncom import win32com.server.util class MySite(axsite.AXSite): # Our error handler will print to the console. def OnScriptError(self, activeScriptError): exc = activeScriptError.GetExceptionInfo() print "Exception:", exc[1] try: sourceText = activeScriptError.GetSourceLineText() except pythoncom.com_error: sourceText = None if sourceText is not None: context, lineNo, charNo = activeScriptError.GetSourcePosition() print sourceText indent = " " * (charNo-1) print indent + "^" return winerror.S_OK # A named object for our namespace # A normal Python COM object (minus registration info) class Application: _public_methods_ = [ 'Echo' ] def Echo(self, *args): print string.join(map(str, args)) # Our function that creates the site, creates the engine # and runs the code. def RunCode(engineName, code): app = win32com.server.util.wrap( Application() ) # Create a dictionary holding our object model. model = { 'Application' : app, } # Create the scripting site. site = MySite(model) # Create the engine and add the code. engine = site.AddEngine(engineName) engine.AddCode(code) # Run the code. engine.Start() if __name__ == '__main__': if len(sys.argv) < 3: print "Usage: ActiveApp.py Language ScriptFile" else: code = open(sys.argv[2]).read() RunCode( sys.argv[1], code )
The error-handling function takes up the bulk of the code as it attempts to accurately indicate the exact location of the error. The code that runs the engine is surprisingly small. You create the script site and the engine, and add the code. When you start the engine, all previously loaded code is executed.
To test this Active Scripting engine, let's use two text files: the first is for VBScript:
rem Sample VBScript code to be used with ActiveApp.py sub JustForTheSakeOfIt Application.Echo("Hello from VBScript") end sub rem Now call the Sub JustForTheSakeOfIt
The second is for Python:
# Sample Python code to be used with ActiveApp.py def JustForTheSakeOfIt(): Application.Echo("Hello from Python") JustForTheSakeOfIt()
Testing the application is straightforward. Assuming that the Python program and both sample text files are in the same directory, use the following commands:
C:\Scripts>ActiveApp.py VBScript ActiveApp_VBScript.txt Hello from VBScript C:\Scripts>
And testing Python:
C:\Scripts>ActiveApp.py Python ActiveApp_Python.txt Hello from Python C:\Scripts>
Finally, to test the error handler, mix the filename and the language. Let's ask VBScript to execute the Python code:
C:\Scripts>ActiveApp.py VBScript ActiveApp_Python.txt Exception: Microsoft VBScript compilation error # Same Python code to be used with ActiveApp.py ^ Traceback (innermost last): File "C:\Scripts\ActiveApp.py", line 49, in ? RunCode( sys.argv[1], code ) File "C:\Scripts\ActiveApp.py", line 40, in RunCode engine.AddCode(code) File "C:\Program Files\Python\win32comext\axscript\server\axsite.py", line 31, in AddCode self.eParse.ParseScriptText(code, None, None, None, 0, 0, 0) pywintypes.com_error: (-2146827264, 'OLE error 0x800a0400', (0, 'Microsoft VBScript compilation error', 'Expected statement', None, 0, -2146827264), None) C:\Scripts>
The error handler worked fine, but the error information was propagated back to the calling function; in this case, the engine.AddCode() line in the sample. Obviously you'd want to add an exception handler for this case.
Although this has not been a thorough discussion of adding Active Scripting to your application, it should whet your appetite and give you enough information to get started. To really take advantage of Active Scripting, you should consult the Active Scripting documentation, available on MSDN.
| I l@ve RuBoard |


Google will have 10 more games ready to support the Stadia launch
by Chris SmithWe found out only a few days ago that Google’s game streaming service will only support 12 games at launch, which isn’t necessarily the great news early buyers expected. However, the first games expansion is already here, as 10 more titles were added to the list of Stadia-ready list of games. That means early Stadia subscribers will have 22 games at their disposal at launch.
Google’s own Phil Harrison, who leads the Stadia division posted the update on Twitter over the weekend in anticipation of the Tuesday launch for the service.
Again, this is the initial list of games that Google announced for Stadia:
- Assassin’s Creed Odyssey
- Destiny 2: The Collection (free with Stadia Pro subscription)
- Gylt
- Just Dance 2020
- Kine
- Mortal Kombat 11
- Rise of the Tomb Raider
- Red Dead Redemption 2
- Samurai Shodown (free with Stadia Pro subscription)
- Shadow of the Tomb Raider
- Thumper
- Tomb Raider 2013
And here are the games that Google added to the service with just a few days to go until launch:
- Attack on Titan: Final Battle 2
- Farming Simulator 2019
- Final Fantasy XV
- Football Manager 2020
- Grid 2019
- Metro Exodus
- NBA 2K20
- Rage 2
- Trials Rising
- Wolfenstein: Youngblood
Google said a few days ago that Stadia will support 26 games by the end of 2019, including the initial batch of 12 titles. That means the service will get four more titles in the coming weeks.
While Google Stadia will let you stream games to a variety of supported devices, including smartphones and tablets, you’ll still need to purchase the games you want to play on top of paying for a monthly subscription that gets you access to the service, aside from the ones that Google is offering for free with Stadia Pro accounts.


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Before continuing to add custom webpack configuration to your application make sure Next.js doesn’t already support your use-case:
Some commonly asked for features are available as plugins:
In order to extend our usage of webpack
, you can define a function that extends its config inside next.config.js
, like so:
module.exports = {
webpack: (config, { buildId, dev, isServer, defaultLoaders, webpack }) => {
// Important: return the modified config
return config;
},
};
The
webpack
function is executed twice, once for the server and once for the client. This allows you to distinguish between client and server configuration using theisServer
property.
The second argument to the webpack
function is an object with the following properties:
buildId
: String
- The build id, used as a unique identifier between buildsdev
: Boolean
- Indicates if the compilation will be done in developmentisServer
: Boolean
- It’s true
for server-side compilation, and false
for client-side compilationdefaultLoaders
: Object
- Default loaders used internally by Next.js:
babel
: Object
- Default babel-loader
configurationExample usage of defaultLoaders.babel
:
// Example config for adding a loader that depends on babel-loader
// This source was taken from the @next/mdx plugin source:
// https://github.com/vercel/next.js/tree/canary/packages/next-mdx
module.exports = {
webpack: (config, options) => {
config.module.rules.push({
test: /\.mdx/,
use: [
options.defaultLoaders.babel,
{
loader: "@mdx-js/loader",
options: pluginOptions.options,
},
],
});
return config;
},
};


Duterte defends cost of ‘kaldero’
The President has come to the defense of the people behind the purchase of the cauldron to be used during the 30th Southeast Asian Games which come off the wraps in less than two weeks at the Philippine Arena in Bocaue, Bulacan.
In a press briefing at Malacañang.yesterday, President Duterte said there’s nothing wrong with spending P50 million for the construction of the cauldron because it is a work of art, adding there was no corruption involved in the purchase.
“There can never be corruption in that situation because you commissioned a national artist (architect Bobby Manosa),” the President told reporters.
“Si Mañosa was commissioned by the government to create ‘yung nakita mo ‘yung kaldero ngayon. It is the product of the mind. You cannot estimate nalugi ka because it is the rendition of the mind of the creator,” Duterte added.
He also said the government cannot do anything about the price if it was what the artist asked for.
“Kung ‘yan ang singil niya, eh ’di sabihin niya, eh di ‘wag mong bilhin kung ayaw mo. ‘Yan ang presyo ko,” Duterte said.
House Speaker Alan Peter Cayetano earlier justified the price of the cauldron, after Senate Minority Leader Franklin Drilon described it as an “unnecessary extravagance”, calling it a ‘kaldero’.
The Philippines’ SEA Games cauldron is “cheaper” than Singapore’s P62-million piece, said Cayetano, who also chairs the Philippine Southeast Asian Games Organizing Committee (PHISGOC).
“Ang cauldron ay isang monumento. Isa itong simbolo. Isa itong work of art. Ito ay isang requirement sa lahat ng games because it symbolizes the games’ competition, spirit,” he told reporters on the sidelines of the Senate budget hearings.


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LDAP Browser
This page provides a simple way of exporing the data in the currently
configured LDAP server. It is useful for fining where in the hierarchy
users and groups are stored, so that they can be correctly entered on
the LDAP Search Bases page.


You are viewing an historical archive of past issues. Please
report new issues to the appropriate project issue tracker on
GitHub.
Comments
-
Greg Hurrell
Ok, in part we're talking about a mis-deployment. Forgot to
git push
before deploying, and strangely, my "pre-update" check didn't warn me... Probably because I was on themaster
(features) branch rather thanmaint
(stable production branch, the one used in deployment). Looks like I might need to add a check for being on the right branch too... -
Greg Hurrell
Ok, fixed.
Add a comment
Comments are now closed for this issue.


pymatgen.io.abinit.nodes module¶
This module defines the Node class that is inherited by Task, Work and Flow objects.
-
class
Dependency
(node, exts=None)[source]¶ Bases:
object
This object describes the dependencies among the nodes of a calculation.
A Dependency consists of a Node that produces a list of products (files) that are used by the other nodes (Task or Work) to start the calculation. One usually creates the object by calling work.register
Example
# Register the SCF task in work. scf_task = work.register(scf_strategy)
# Register the NSCF calculation and its dependency on the SCF run via deps. nscf_task = work.register(nscf_strategy, deps={scf_task: “DEN”})
- Parameters
node – The task or the worfklow associated to the dependency or string with a filepath.
exts – Extensions of the output files that are needed for running the other tasks.
-
apply_getters
(task)[source]¶ This function is called when we specify the task dependencies with the syntax:
deps={node: “@property”}
In this case the task has to the get property from node before starting the calculation.
At present, the following properties are supported:
@structure
-
connecting_vars
()[source]¶ Returns a dictionary with the variables that must be added to the input file in order to connect this
Node
to its dependencies.
-
get_filepaths_and_exts
()[source]¶ Returns the paths of the output files produced by self and its extensions
-
property
info
¶
-
class
FileNode
(filename)[source]¶ Bases:
pymatgen.io.abinit.nodes.Node
A Node that consists of a file. May be not yet existing
Mainly used to connect
Task
objects to external files produced in previous runs.-
color_rgb
= array([0.4, 0.2, 1. ])¶
-
property
filechildren
¶ List with the children (nodes) of this FileNode.
-
property
products
¶
-
property
status
¶ The status of the Node.
-
-
class
GridFsFile
(path, fs_id=None, mode='b')[source]¶ Bases:
monty.collections.AttrDict
Information on a file that will stored in the MongoDb gridfs collection.
-
class
HistoryRecord
(level, pathname, lineno, msg, args, exc_info, func=None)[source]¶ Bases:
object
A HistoryRecord instance represents an entry in the
NodeHistory
.HistoryRecord instances are created every time something is logged. They contain all the information pertinent to the event being logged. The main information passed in is in msg and args, which are combined using str(msg) % args to create the message field of the record. The record also includes information such as when the record was created, the source line where the logging call was made
-
levelno
¶ Numeric logging level for the message (DEBUG, INFO, WARNING, ERROR, CRITICAL)
-
levelname
¶ Text logging level for the message (“DEBUG”, “INFO”, “WARNING”, “ERROR”, “CRITICAL”)
-
pathname
¶ Full pathname of the source file where the logging call was issued (if available)
-
filename
¶ Filename portion of pathname
-
module
¶ Module (name portion of filename)
-
lineno
¶ Source line number where the logging call was issued (if available)
-
func_name
¶ Function name
-
created
¶ Time when the HistoryRecord was created (time.time() return value)
-
asctime
¶ Textual time when the HistoryRecord was created
-
message
¶ -
The result of record.getMessage(), computed just as the record is emitted
Initialize a logging record with interesting information.
-
-
class
Node
[source]¶ Bases:
object
Abstract base class defining the interface that must be implemented by the nodes of the calculation.
Nodes are hashable and can be tested for equality
-
ALL_STATUS
= [<Status: Initialized, at<PHONE_NUMBER>76808>, <Status: Locked, at<PHONE_NUMBER>70504>, <Status: Ready, at<PHONE_NUMBER>40616>, <Status: Submitted, at<PHONE_NUMBER>39976>, <Status: Running, at<PHONE_NUMBER>40872>, <Status: Done, at<PHONE_NUMBER>70696>, <Status: AbiCritical, at<PHONE_NUMBER>67496>, <Status: QCritical, at<PHONE_NUMBER>69352>, <Status: Unconverged, at<PHONE_NUMBER>70440>, <Status: Error, at<PHONE_NUMBER>69992>, <Status: Completed, at<PHONE_NUMBER>70248>]¶
-
Results
¶ alias of
NodeResults
-
S_ABICRITICAL
= <Status: AbiCritical, at<PHONE_NUMBER>67496>¶
-
S_DONE
= <Status: Done, at<PHONE_NUMBER>70696>¶
-
S_ERROR
= <Status: Error, at<PHONE_NUMBER>69992>¶
-
S_INIT
= <Status: Initialized, at<PHONE_NUMBER>76808>¶
-
S_LOCKED
= <Status: Locked, at<PHONE_NUMBER>70504>¶
-
S_OK
= <Status: Completed, at<PHONE_NUMBER>70248>¶
-
S_QCRITICAL
= <Status: QCritical, at<PHONE_NUMBER>69352>¶
-
S_READY
= <Status: Ready, at<PHONE_NUMBER>40616>¶
-
S_RUN
= <Status: Running, at<PHONE_NUMBER>40872>¶
-
S_SUB
= <Status: Submitted, at<PHONE_NUMBER>39976>¶
-
S_UNCONVERGED
= <Status: Unconverged, at<PHONE_NUMBER>70440>¶
-
SpectatorError
¶ alias of
SpectatorNodeError
-
add_deps
(deps)[source]¶ Add a list of dependencies to the
Node
.- Parameters
deps – List of
Dependency
objects specifying the dependencies of the node. or dictionary mapping nodes to file extensions e.g. {task: “DEN”}
-
classmethod
as_node
(obj)[source]¶ Convert obj into a Node instance.
- Returns
obj if obj is a Node instance, cast obj to
FileNode
instance of obj is a string. None if obj is None
-
color_hex
[source]¶ //en.wikipedia.org/wiki/Web_colors#Hex_triplet
- Type
Node color as Hex Triplet https
-
color_rgb
= array([0.41176471, 0.41176471, 0.41176471])¶
-
property
corrections
¶ List of dictionaries with infornation on the actions performed to solve AbiCritical Events. Each dictionary contains the AbinitEvent who triggered the correction and a human-readable message with the description of the operation performed.
-
property
deps
¶ List of
Dependency
objects defining the dependencies of this Node. Empty list if thisNode
does not have dependencies.
-
property
deps_status
¶ Returns a list with the status of the dependencies.
-
property
event_handlers
¶ The list of handlers registered for this node. If the node is not a Flow and does not have its own list of handlers the handlers registered at the level of the flow are returned.
This trick allows one to registered different handlers at the level of the Task for testing purposes. By default, we have a common list of handlers for all the nodes in the flow. This choice facilitates the automatic installation of the handlers when we use callbacks to generate new Works and Tasks!
-
property
finalized
¶ True if the Node has been finalized.
-
property
gc
¶ Garbage collector. None if garbage collection is deactivated. Use flow.set_garbage_collector to initialize the object.
-
get_children
()[source]¶ Return the list of nodes in the
Flow
that depends on thisNode
Note
This routine assumes the entire flow has been allocated.
-
get_graphviz_dirtree
(engine='automatic', **kwargs)[source]¶ Generate directory graph in the DOT language. The graph show the files and directories in the node workdir.
Returns: graphviz.Digraph <https://graphviz.readthedocs.io/en/stable/api.html#digraph>
-
get_vars_dataframe
(*varnames)[source]¶ Return pandas DataFrame with the value of the variables specified in varnames. Can be used for task/works/flow. It’s recursive!
-
property
in_spectator_mode
¶
-
install_event_handlers
(categories=None, handlers=None)[source]¶ Install the EventHandlers for this `Node. If no argument is provided the default list of handlers is installed.
- Parameters
categories – List of categories to install e.g. base + can_change_physics
handlers – explicit list of
EventHandler
instances. This is the most flexible way to install handlers.
Note
categories and handlers are mutually exclusive.
-
property
is_file
¶ True if this node is a file
-
property
is_flow
¶ True if this node is a Flow
-
property
is_task
¶ True if this node is a Task
-
property
is_work
¶ True if this node is a Work
-
isinstance
(class_or_string)[source]¶ Check whether the node is a instance of class_or_string. Unlinke the standard isinstance builtin, the method accepts either a class or a string. In the later case, the string is compared with self.__class__.__name__ (case insensitive).
-
log_correction
(event, action)[source]¶ This method should be called once we have fixed the problem associated to this event. It adds a new entry in the correction history of the node.
- Parameters
event –
AbinitEvent
that triggered the correction.action (str) – Human-readable string with info on the action perfomed to solve the problem.
-
property
name
¶ The name of the node (only used for facilitating its identification in the user interface).
-
property
node_id
¶ Node identifier.
-
property
num_corrections
¶
-
property
relworkdir
¶ Return a relative version of the workdir
-
remove_deps
(deps)[source]¶ Remove a list of dependencies from the
Node
.- Parameters
deps – List of
Dependency
objects specifying the dependencies of the node.
-
send_signal
(signal)[source]¶ Send signal from this node to all connected receivers unless the node is in spectator mode.
signal – (hashable) signal value, see dispatcher connect for details
Return a list of tuple pairs [(receiver, response), … ] or None if the node is in spectator mode.
if any receiver raises an error, the error propagates back through send, terminating the dispatch loop, so it is quite possible to not have all receivers called if a raises an error.
-
show_event_handlers
(stream=<_io.TextIOWrapper name='<stdout>' mode='w' encoding='UTF-8'>, verbose=0)[source]¶ Print to stream the event handlers installed for this flow.
-
abstract property
status
¶ The status of the Node.
-
-
class
NodeCorrections
[source]¶ Bases:
list
Iterable storing the correctios performed by the
EventHandler
-
class
NodeHistory
[source]¶ Bases:
collections.deque
Logger-like object
-
class
NodeResults
(node, **kwargs)[source]¶ Bases:
dict
,monty.json.MSONable
Dictionary used to store the most important results produced by a
Node
.-
JSON_SCHEMA
= {'properties': {'exceptions': {'required': True, 'type': 'array'}, 'files': {'required': True, 'type': 'object'}, 'in': {'description': 'dictionary with input parameters', 'required': True, 'type': 'object'}, 'node_class': {'required': True, 'type': 'string'}, 'node_finalized': {'required': True, 'type': 'boolean'}, 'node_history': {'required': True, 'type': 'array'}, 'node_id': {'required': True, 'type': 'integer'}, 'node_name': {'required': True, 'type': 'string'}, 'node_status': {'required': True, 'type': 'string'}, 'out': {'description': 'dictionary with the output results', 'required': True, 'type': 'object'}}, 'type': 'object'}¶
-
property
exceptions
¶
-
property
gridfs_files
¶ List with the absolute paths of the files to be put in GridFs.
-
register_gridfs_files
(**kwargs)[source]¶ This function registers the files that will be saved in GridFS. kwargs is a dictionary mapping the key associated to the file (usually the extension) to the absolute path. By default, files are assumed to be in binary form, for formatted files one should pass a tuple (“filepath”, “t”).
Example:
results.register_gridfs(GSR="path/to/GSR.nc", text_file=("/path/to/txt_file", "t"))
The GSR file is a binary file, whereas text_file is a text file.
-
-
class
Product
(ext, path)[source]¶ Bases:
object
A product represents an output file produced by ABINIT instance. This file is needed to start another Task or another Work.
- Parameters
ext – ABINIT file extension
path – (asbolute) filepath
-
connecting_vars
()[source]¶ Returns a dictionary with the ABINIT variables that must be used to make the code use this file.
-
property
filepath
¶ Absolute path of the file.
-
exception
SpectatorNodeError
[source]¶ Bases:
pymatgen.io.abinit.nodes.NodeError
Exception raised by
Node
methods when the node is in spectator mode and we are calling a method with side effects.
-
class
Status
[source]¶ Bases:
int
This object is an integer representing the status of the Node.
-
property
color_opts
¶
-
property
colored
¶ Return colorized text used to print the status if the stream supports it.
-
property
is_critical
¶ True if status is critical.
-
property
-
logger
= <Logger pymatgen.io.abinit.nodes (INFO)>¶


This globe includes the dataset of 147 satellites that are currently in orbit under the Earth Resource category. Here you are able to see the plotted points on a 3-D image with a clearer view of the positions of the satellites.


Work experience
University
Tak
University
Tak
University
Tak
Tyle sie nauczylam robic w css i html. Oto efekt!
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Tak
Tak
Tak
I'm trying to create a cool webpage so that I can attach it to my CV to prove my skills. I'm trying to create a cool webpage so that I can attach it to my CV to prove my skills. I'm trying to create a cool webpage so that I can attach it to my CV to prove my skills. I'm trying to create a cool webpage so that I can attach it to my CV to prove my skills. I'm trying to create a cool webpage so that I can attach it to my CV to prove my skills. I'm trying to create a cool webpage so that I can attach it to my CV to prove my skills. I'm trying to create a cool webpage so that I can attach it to my CV to prove my skills. I'm trying to create a cool webpage so that I can attach it to my CV to prove my skills. I'm trying to create a cool webpage so that I can attach it to my CV to prove my skills. I'm trying to create a cool webpage so that I can attach it to my CV to prove my skills. I'm trying to create a cool webpage so that I can attach it to my CV to prove my skills.


Place: London, United Kingdom
Teams: Task Force 141 vs. Spetsnaz
Terrain: Warehouse
Storm is a new map included in the Stimulus Package for Call of Duty: Modern Warfare 2. It is described as "an open industrial park littered with heavy machinery." Like its name says, outside of the warehouse is a heavy storm. Storm looks slightly like the maps Killhouse and Vacant from Call of Duty 4: Modern Warfare.
Storm is a very unpredictable map, having many choke points where it is easy to be flanked. Weapons like the UMP45, ACR, SCAR-H, M4A1, Intervention, P90, and MP5K are common and effective on this map.
When on the warehouse floor there are little overhangs which the player can hide under that will provide cover from any fire coming from the catwalks.
In the construction yard, there are deep holes in which the player can hide in when prone.
The roof of the mannequin store provides a great view of the map.
Maintaining a presence in the multi-story buildings across the map can prove to be invaluable as it provides long sight lines covering large portions of the map, whereas the ground level is littered with cover, thus obscuring a player's view.
In Search and Destroy, Ninja Pro is a very useful perk since most of the surfaces in the warehouse and near the bomb sites are metal and makes the players footsteps very loud.
Conversely, SitRep Pro will make enemy footsteps impossible to ignore.
Grenade launchers can fly over some obstructions, killing the enemy without exposing the position of one using the grenade launcher.
In every building, there is more than one way to the top floor. Plant claymores at one and occasionally check the other entry to ensure of no flankers.
It is actually very easy to go from the Spetsnaz spawn point to point A in Domination before the Task Force 141 troops can get there if the player has Marathon, Lightweight, and any third perk. This can easily kill most of the enemies there, and actually enable the player to gain an edge in the map.
There are many piles of wood which can be seen and shot through, thus giving slight cover and the element of surprise when an enemy comes into sight.
When playing domination, it is a good idea to take control of the building overlooking the A flag because it gives you long sight lines in two directions that are common for enemies to go by.


Programming Test #courework
Please code for the following problems.
1. Open the links
2. write code in your own IDE
3. Paste the code to the online judge to pass the test
4. save your pass screenshots into a word document.
5. Submit your word document onto your project page with link name: JavaProgTest20161128_YourName
Problems:
http://codingbat.com/prob/p146974 [5 marks]
http://codingbat.com/prob/p139150 [10 marks]
http://codingbat.com/prob/p120015 [5 marks]
https://www3.ntu.edu.sg/home/ehchua/programming/java/J3f_OOPExercises.html#zz-4.5 [20 marks]


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--- layout: post title: Laminar flow around a cylinder thumb: karman ---
Solution of the incompressible Navier-Stokes in different flow regimes, showing Kármán vortices developing in the wake of the cylinder. Solved using the isogeometric finite element method using compatible velocity/pressure spaces for pointwise divergence free flow fields, and weak imposition of (tangential) no-slip. See the nutils example "cylinderflow" for full implementational details.


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Go Nitpicks
Oct 28, 2014I saw this tweet last night:
A code interview I like to ask:
"What would you change about <your favourite language>?"
Having nothing to say to that is a big strike.
— karlseguin (@karlseguin) October 27, 2014
I figured I’d answer it here about Go. Luckily, Go is a very small language, so there’s not a lot of surface area to dislike. However, there’s definitely some things I wish were different. Most of these are nitpicks, thus the title.
#1 Bare Returns
func foo() (i int, err error) {
i, err = strconv.ParseInt("5")
return // wha??
 The way it works is that if you don’t declare what the function is returning, it’ll return the values stored in the named return variables. Which seems logical and handy, until you see a 100 line function with multiple branches and a single bare return at the bottom, with no idea what is actually getting returned.
To all gophers out there: don’t use bare returns. Ever.
#2 New
a := new(MyStruct)
New means “Create a zero value of the given type and return a pointer to it”. It’s sorta like the C++ new
, which is probably why it exists. The problem is that it’s nearly useless. It’s mostly redundant with simply returning the address of a value thusly:
a := &MyStruct{}
The above is a lot easier to read, it also gives you the ability to populate the value you’re constructing (if you wish). The only time new is “useful” is if you want to initialize a pointer to a builtin (like a string or an int), because you can’t do this:
a := &int
but you can do this:
a := new(int)
Of course, you could always just do it in (gasp) two lines:
a := 0
b := &a
To all the gophers out there: don’t use new. Always use &Foo{} with structs, maps, and slices. Use the two line version for numbers and strings.
#3 Close
The close built-in function closes a channel. If the channel is already closed, close will panic.  I just want to ensure that it’s closed. I’d much prefer if close returned a boolean that said whether or not it did anything, and then if I choose to panic, I can. Or, you know, not.
#4 There is no 4
That’s basically it. There’s some things I think are necessary evils, like goto
and panic
. There’s some things that are necessary ugliness, like the built-in functions append
, make
, delete
, etc. I sorta wish x := range foo
returned the value in x and not the index, but I get that it’s to be consistent between maps and slices, and returning the value in maps would be odd, I think.
All these are even below the level of nitpicks, though. They don’t bug me, really. I understand that everything in programming is a tradeoff, and I think the decisions made for Go were the right ones in these cases. Sometimes you need goto. Sometimes you need to panic. Making those functions built-ins rather than methods on the types means you don’t need any methods on the types, which keeps them simpler, and means they’re “just data”. It also means you don’t lose any functionality if you make new named types based on them.
So that’s my list for Go.
Postscript
Someone on the twitter discussion mentioned he couldn’t think of anything he disliked about C#, which just about made me spit my coffee across the room. I programmed in C# for ~9 years, starting out porting some 1.1 code to 2.0, and leaving as 5.0 came out. The list of features in C# as of 5.0 is gigantic. Even being a developer writing in it 40+ hours a week for 9 years, there was still stuff I had to look up to remember how it worked.
I feel like my mastery of Go after a year of side projects was about equivalent to my mastery of C# after 9 years of full time development. If we assume 1:1 correlation between time to master and size of the language, an order of magnitude sounds about right.


@import fr.gospeak.core.domain.{Group, User} @import fr.gospeak.web.pages.orga.routes.GroupCtrl @import fr.gospeak.web.utils.SecuredReq @(group: Group, orga: User)(implicit req: SecuredReq[AnyContent])
Hi @orga.name.value,
Just to let you know that @req.user.name.value removed you from the @group.name.value group.
You can still apply to existing group or create your own.
The Gospeak team


| I have yet to bother to make a program with a real GUI. I don't care for it |
I don't blame you. It's a pain. I'm not fond of GUI programming myself.
| What's wrong with the CLI? |
When used properly, nothing.
I'm not saying people shouldn't use the console. I'm saying people shouldn't
misuse the console.
Most (if not all) people asking the kinds of questions this topic addresses are misusing the console.
Here's the most severe case I've seen so far:
http://cplusplus.com/forum/beginner/27978/
That thread killed me. Seriously... look at what he was doing.
The pain and hardship that guy was putting himself through was so severe. And because he started with the console and thought it would be easier, he got too stuck in his ways and I wasn't able to convince him to leave, even though he
really should not have used the console for that project.
It's like that point on the "smart questions" essay:
http://www.catb.org/esr/faqs/smart-questions.html#goal
The people asking "how do I clear the screen", "how do I change the text color" are asking about the next step, but they're really going about the overall process all wrong. Answering their quesiton is almost a disservice, as it pushes them further down the wrong path instead of putting them on the right one.


Members
Zeguro Software Solutions
H.V.L.C.Gamage -120162P
Database management
P.Nadeeshani -120410C
Designing and Coding
D.M.A.Nilakshi -120423T
GUI Designer and Coordinator
P.D. Pathirana -120452F
Team Leader and Presentations
P.H.Samarasekara -120561M
Documentation and Presentations


| selectSuperClasses {methods} | R Documentation |
Return superclasses of ClassDef
, possibly only non-virtual or
direct or simple ones.
These functions are designed to be fast, and consequently only work
with the contains
slot of the corresponding class definitions.
selectSuperClasses(Class, dropVirtual = FALSE, namesOnly = TRUE, directOnly = TRUE, simpleOnly = directOnly, where = topenv(parent.frame())) .selectSuperClasses(ext, dropVirtual = FALSE, namesOnly = TRUE, directOnly = TRUE, simpleOnly = directOnly)
Class |
name of the class or (more efficiently) the class
definition object (see |
dropVirtual |
logical indicating if only non-virtual superclasses should be returned. |
namesOnly |
logical indicating if only a vector names instead of a named list class-extensions should be returned. |
directOnly |
logical indicating if only a direct super classes should be returned. |
simpleOnly |
logical indicating if only simple class extensions should be returned. |
where |
(only used when |
ext |
for |
a character
vector (if namesOnly
is true, as per
default) or a list of class extensions (as the contains
slot in
the result of getClass
).
The typical user level function is selectSuperClasses()
which calls .selectSuperClasses()
; i.e., the latter should only
be used for efficiency reasons by experienced useRs.
is
, getClass
; further, the more technical
class classRepresentation
documentation.
setClass("Root") setClass("Base", contains = "Root", slots = c(length = "integer")) setClass("A", contains = "Base", slots = c(x = "numeric")) setClass("B", contains = "Base", slots = c(y = "character")) setClass("C", contains = c("A", "B")) extends("C") #--> "C" "A" "B" "Base" "Root" selectSuperClasses("C") # "A" "B" selectSuperClasses("C", direct=FALSE) # "A" "B" "Base" "Root" selectSuperClasses("C", dropVirt = TRUE, direct=FALSE)# ditto w/o "Root"


CryptoBird
This is CryptoBird Home
Start Game
Current Pool:
Current Balance:
Leaderboard
Loading ...


Glossary¶
- agent
- The Agent would be a standalone service that acts as a sort of mirror to mdns. It would receive AXFR/IXFR, NOTIFYs, and other notifications and perform changes to a DNS server through a plugin-style backend. The agent is intended for deployments that may not be able to use mdns as a true DNS Master.
- api
- HTTP REST API service for Designate
- central
- Software service running on a central management node that stores information persistently in a backend storage using a configurable driver like SQLAlchemy or other.
- mdns
- Also known as mini dns. This is a dns server with limited capabilities like NOTIFY’s, AXFR’s and record queries. The pool manager uses mdns to transfer data to/from the pool servers.
- mq
- A message queue, typically something like RabbitMQ or ZeroMQ
- name server
- A FQDN (or IP, but usually a FQDN) that is used to populate the NS Records of a Designate Managed Zone. Each Pool will have a set of Name Servers, which users then delegate to from their registrar.
- node
- A server, physical or virtual, running some aspect of the designate system.
- pool
- A collection of pool servers sharing similar attributes. Different pools could have different capabilities - such as GeoIP / Round Robin DNS / Anycast.
- pool manager
- This is a service that is responsible for notifying pool servers of the changes that have occurred. It also updates central once the changes are live on the pool servers.
- pool manager backend
- A backend is used by the pool manager to transfer the data from storage to name servers. There are backends that support PowerDNS, BIND, & NSD.
- pool server
- The DNS servers that are updated by the pool manager. These need not be the same as the name servers. When they are different a mechanism outside of designate is needed to ensure the data on pool servers is consistent with that on the name servers.
- private pool
A pool of ‘private’ DNS servers. These servers would typically allow non standard TLDs (.dev , .local etc), and may not have the same level of blacklist restrictions. They would be aimed at people with Neutron Networking, and VPC style set ups, where access to the DNS server would come from trusted networks (E.G. in-cloud - owned instances, and onsite resources connect by VPN)
This would allow customers to set DNS entries for internal servers, on domains that would not be available on the public pools, and have them accessible by internal users
- secondary zone
- A zone within Designate that has external Masters.
- sink
- Optional Software Service that is configured to listen to events from the Nova or Neutron event queue and use the central service to generate simple A records for instances as they are created, and delete A records as they are deleted.
- storage
- A backend for storing data/information persistently. Typically MongoDB or a SQL based server software.


Our Recipies
Here are some recipies we have developed over the years.
Biscuits
Brandy Chicken
Cauliflower Tabbouleh
Chai Spice Mix
Cookies
Cornbread
Coconut Macaroons
Creme Brûlée
Caramel-Glazed Flan
Granola
Injera
Noodle Kugel
Mojito
Pancakes
goldy's Pizza
Pumpkin Pie
QuinonaAppleCake
Simple Syrup
Spicy Fish Cakes
Copyright ©, 2003 - 2023, Steve Goldhaber


mkmamedb —
create database for use by ckmame
| mkmamedb |
[-huV]
[-C
hashtypes]
[-F
outputformat]
[-o
dbfile]
[-x
pat]
[--detector
file]
[--exclude
pat]
[--hash-types
types]
[--help]
[--no-directory-cache]
[--only-files
pattern]
[--output
dbfile]
[--prog-description
description]
[--prog-name
name]
[--prog-version
version]
[--roms-unzipped]
[--skip-files
pattern]
[--version]
[rominfo-file
...] |
mkmamedb converts ROM set descriptions from one
format to another.
The ROM set description is read from the specified files (or directories) or the
standard input if no files are specified. The default output file is
mame.db. You can override it with the
-o option or the
MAMEDB
environment variable.
Supported input formats are:
- CMPro dat file
- MAME XML file
- MESS Softlist XML file
- Romcenter dat file
- ckmame(1)
database format
- directory of zip archives
- directory with subdirectories (with
-u); each sub-directory is taken as a
game
Supported output formats are:
The CMPro file format is described at
http://www.logiqx.com/FAQs/CMPro.shtml, the DTD
for MAME xml can be found in
PREFIX/share/doc/ckmame/.
mkmamedb supports the following options:
-
-
- -C
types,
--hash-types
types
- A comma separated list of hash types to compute when
creating a ROM set description from a directory of zip archives. Supported
hash types are: crc, md5, sha1. Default are all.
-
-
- -F
outputformat,
- -format
outputformat
- Specify output format. Supported formats are
cm (clrmamepro dat file),
dat (XML datfile),
db
(ckmame(1) database), and
mtree
(mtree(8) file). The
default is cm.
-
-
- --detector
file
- Use CMPro XML header skip detector description from
file. This overrides any detectors given
in the file itself. mkmamedb looks for the
detector in the input file (if it is a zip file) or the directory of the
input file.
-
-
- -h,
--help
- Display a short help message.
-
-
- -o
dbfile,
--output
dbfile
- Write to database dbfile
instead of the default
“mame.db”.
-
-
- --no-directory-cache
- When mkmamedb is used to
create a database from an input directory, it will by default write a
.ckmame.db database file to it, caching the
directory contents' hashes in it so that consecutive re-runs are faster.
When mkmamedb finds such a database, it only
computes the hashes for the files that have changed since the last
run.
-
-
- --only-files
pattern
- When reading files from the file system as input, only
accept files matching the shell glob
pattern.
-
-
- --prog-description
description
- Set description for the program the ROM info is from.
-
-
- --prog-name
name
- Set name of the program the ROM info is from.
-
-
- --prog-version
version
- Set version of the program the ROM info is from.
-
-
- --skip-files
pattern
- When reading files from the file system as input, skip
files matching the shell glob
-
-
- -u,
--roms-unzipped
- ROMs are files on the disk. Each game is represented by a
directory instead of a ZIP archive. Only relevant when creating a database
based on file system contents.
-
-
- -V,
--version
- Display program name and version number.
-
-
- -x
pat,
--exclude
pat
- Exclude games with names matching
pat from the created database.
-
-
MAMEDB
- Location for the database file. Can be overridden with the
-o option. Defaults to
“mame.db”.
Get an input file for
mkmamedb(1) from MAME and
convert it to the internal database format:
# mame -listxml | mkmamedb
ckmame(1),
dumpgame(1)
mkmamedb was written by
Dieter Baron<EMAIL_ADDRESS>and
Thomas Klausner
<
tk@giga.or.at>.


Tweets by CTC Athletics


On this page:
Note: To complete these procedures, you must be assigned a role having the necessary permissions. To determine your role, follow the directions in Participant roles. For a basic understanding of roles and permissions, see Permissions and roles: Overview.
Sections may or may not be populated with official course data, depending on implementation. If they are not automatically created, then you may create them if you have the appropriate role. Participants (e.g., students) cannot create or modify sections.
Note: If your implementation has an automatic feed, you will have the option to automatically or manually manage section membership from the Options page in the Section Info tool. Membership information can be based on official registration information, or you can discontinue section and membership updates from the registration system and manually control everything. However, when you select manual mode and then return to automatic mode, you will lose all the changes you made while in manual mode.
To create a section:
Section Info
. This will
open the Section Info tool.
Note: If you do not see "Section Info" on your menubar, you may need to add the tool. For more information, see Adding, editing, removing, hiding, or reordering tools.
Add Sections
.
Note: The name of a category is the only thing that differentiates it from other categories; the categories are otherwise the same. For instance, a Lab section will function exactly as a Discussion section in the Section Info tool.
Unlimited number
of students in section
or Limit number of students in section
to
. For the second choice, enter the maximum number of members
allowed in the section.
8:00
. Check next to
AM
or PM
to indicate time of day.
Add Sections
. If
you have changed your mind and do not wish to add the section(s),
click Cancel
.
To edit a section you have already created:
Section
Info
. Overview
. Edit
. Update
to accept
these changes, or Cancel
to cancel them.
To delete a section you have created:
Section
Info
. Overview
. Remove Sections
to remove the section(s), and then
click Remove
to confirm. Click Cancel
to cancel.


--- template: example.html title: Custom styles for polygons shortdesc: Showing the vertices of a polygon with a custom style geometry. docs: > In this example two different styles are created for the polygons: * The first style is for the polygons themselves. * The second style is to draw the vertices of the polygons. tags: "polygon, vector, style, GeometryFunction" resources: - polygon-styles.css ---


Mike Roberts / @michaelaroberts
Product Engineer @card
We'll need to install a few things first. I'll assume we have the basics like an editor or IDE.
We need a few endoints that return JSON. Depending on what you want to return you can use the services module or build a custom page callback that does exactly what you need and returns JSON and skips most of the Drupal layers that could cause some performance hiccups.
The easiest way to get set up is using the services module. Services integrates well with views so it's pretty easy to get that all set up and running.
/**
* Implements hook_menu().
*/
function droopycamp_menu() {
$items = array();
$items['api/sessions'] = array(
'title' => 'Sessions',
'page callback' => 'droopycamp_api_sessions',
'access callback' => TRUE,
);
return $items;
}
/**
* Gets sessions, prints JSON then exits.
*
* @param string $type
* The type of session to look up.
*
*/
function droopycamp_api_sessions($type) {
$data = array();
$data = db_select('node', 'node')
->condition('type', 'session')
->execute()->fetchAll();
print drupal_json_encode($data);
drupal_exit();
}
$ ionic start appName sidemenu
This gives you an app skeleton with a few pages, a login popup and full hamburger menu functionality.
http://ionicframework.com/getting-started/
Angular structure - there are three main files, app.js, controllers.js, and services.js.
Add templates in the templates folder
$ cordova build ios && cordova build android
Gulp and Grunt aren't just for mobile development and they essentially allow you to chain a bunch of functionality together to make your life a lot easier. You can watch your sass files, run a server, and have live reload all from running one command from terminal. If you're a frontend developer and you're not already using one of these or a similar tool, you should probably look into it.
var gulp = require('gulp'), gutil = require('gulp-util'), concat = require('gulp-concat'), sass = require('gulp-sass'), minifyCss = require('gulp-minify-css'), rename = require('gulp-rename'), sh = require('shelljs'); var paths = { sass: ['./scss/**/*.scss'] }; gulp.task('default', ['sass']); gulp.task('sass', function(done) { gulp.src('./scss/ionic.app.scss').pipe(sass()).pipe(gulp.dest('./www/css/')).pipe(minifyCss({keepSpecialComments: 0})).pipe(rename({ extname: '.min.css' })).pipe(gulp.dest('./www/css/')).on('end', done); }); gulp.task('watch', function() { livereload.listen(); gulp.watch(paths.sass, ['sass']).on('change', livereload.changed); }); gulp.task('prepare', function() { sh.exec('cordova prepare ios'); sh.exec('cordova prepare android'); }); gulp.task('serve', ['prepare'], function() { sh.exec('ionic serve'); });
An easy way to run a local server
$ python -m SimpleHTTPServer
Cordova has hooks similar to git hooks that you can run after certain actions happen.
http://devgirl.org/2013/11/12/three-hooks-your-cordovaphonegap-project-needs/
The cordova hooks are just javascript files that can do pretty much anything gulp/grunt/node can do.
My favorite hook is the after_prepare hook that copies you app icons to all the correct places when you run `cordova prepare` or `cordova build`


multiple time use and error solving troubleshooting through various methods thatn are practised many number of times
multiple time use and error solving troubleshooting through various methods thatn are practised many number of times and many more
we czan do things a lot of things really like a llt a lot
YOU DIDN'T NOTICED THE NUMBERS COUNT DID YOU?
random numbers
BEST
transparency insideout
hellohello


Utilities¶
Helper Functions¶
Miscellaneous Helpers for NetworkX.
These are not imported into the base networkx namespace but can be accessed, for example, as
>>> import networkx
>>> networkx.utils.is_string_like('spam')
True
is_string_like (obj) |
Check if obj is string. |
flatten (obj[, result]) |
Return flattened version of (possibly nested) iterable object. |
iterable (obj) |
Return True if obj is iterable with a well-defined len(). |
is_list_of_ints (intlist) |
Return True if list is a list of ints. |
make_str (x) |
Return the string representation of t. |
generate_unique_node () |
Generate a unique node label. |
default_opener (filename) |
Opens filename using system’s default program. |
pairwise (iterable[, cyclic]) |
s -> (s0, s1), (s1, s2), (s2, s3), … |
groups (many_to_one) |
Converts a many-to-one mapping into a one-to-many mapping. |
create_random_state ([random_state]) |
Returns a numpy.random.RandomState instance depending on input. |
Data Structures and Algorithms¶
Union-find data structure.
UnionFind.union (*objects) |
Find the sets containing the objects and merge them all. |
Random Sequence Generators¶
Utilities for generating random numbers, random sequences, and random selections.
powerlaw_sequence (n[, exponent, seed]) |
Return sample sequence of length n from a power law distribution. |
cumulative_distribution (distribution) |
Return normalized cumulative distribution from discrete distribution. |
discrete_sequence (n[, distribution, …]) |
Return sample sequence of length n from a given discrete distribution or discrete cumulative distribution. |
zipf_rv (alpha[, xmin, seed]) |
Return a random value chosen from the Zipf distribution. |
random_weighted_sample (mapping, k[, seed]) |
Return k items without replacement from a weighted sample. |
weighted_choice (mapping[, seed]) |
Return a single element from a weighted sample. |
Decorators¶
open_file (path_arg[, mode]) |
Decorator to ensure clean opening and closing of files. |
not_implemented_for (*graph_types) |
Decorator to mark algorithms as not implemented |
nodes_or_number (which_args) |
Decorator to allow number of nodes or container of nodes. |
preserve_random_state (func) |
Decorator to preserve the numpy.random state during a function. |
random_state (random_state_index) |
Decorator to generate a numpy.random.RandomState instance. |
Cuthill-Mckee Ordering¶
Cuthill-McKee ordering of graph nodes to produce sparse matrices
cuthill_mckee_ordering (G[, heuristic]) |
Generate an ordering (permutation) of the graph nodes to make a sparse matrix. |
reverse_cuthill_mckee_ordering (G[, heuristic]) |
Generate an ordering (permutation) of the graph nodes to make a sparse matrix. |


Predict Football Player's Annual Salary
Predict Salary
player's annual salary should be
{{ prediction_text }}


I am originally from Los Angeles, CA and currently studying Business Administration and Industrial Engineering at UC Berkeley class of 2020.
I have experience with launching startups, management consulting, marketing strategy, financial markets, financial modeling and investment management.
I am passionate about learning new skills and gaining new experiences. I am interested in the finance industry and pursuing a career in investment banking.
Will spearhead strategies for client sales initiatives and creation of client facing slide decks to streamline client meetings. Responsible for leading prospect outreach and assisting in end-to-end client acquisition and experience optimization
Produced weekly fintech industry update articles to share with clients and internal company usage. Developed a new company international expense policy and managed the tracking and verification of all expenses. Produced slide-deck presentations for high-net worth client pitches and facilitated preparation of meeting logistics.
Launched a social media and brand ambassador marketing campaign leading to 900+ app downloads within 3 months Selectively recruited 35 student interns while developing and leading a marketing internship program with 4 divisions. Collaborated with 7 UC Berkeley organizations and 3 local businesses to orchestrate over 15 Schmooze sponsored events
Formulated 10 company recommendations based on industry trends (micro-chip manufacturing) and key fundamentals. Produced asset allocation spreadsheets for 40+ high net worth clients to display performance, diversification and income. Managed the creation of 30+ client facing portfolio summaries to display holdings, risk levels and retirement planning
Planned and launched an email and door-to-door marketing campaign to onboard the first 10 restaurant delivery partners. Actively managed restaurant relationships to negotiate mutually beneficial pricing and optimize customer discounts
Conducted 40+ hours of on-site research and 200+ consumer surveys to understand customer preferences and pain points. Minimized queue wait times through location specific recommendations and techniques for customer flow optimization.
Co-managed a $45,000 budget allocating among 10+ committees, property maintenance costs and alumni events. Ensured consistent revenue flow by communication with 110+ members to facilitate prompt collection of all payments. Spearheaded a $9,000+ fundraising campaign raising and a volleyball tournament with 200+ participants and $1,000+ profit.
Developed and launched a Haas Business School application mentorship program with a 70% acceptance rate in 2018. Ensured the academic excellence of the brotherhood by organizing study aids and implementing a weekly study program.
Lead a team of 5 to create a business and finance curriculum to teach middle age students within Oakland School District. Launching this weekly in-class teaching program led with hands on learning experiences via a mobile food cart business.
Collaborated with 10 other investment partners to choose select value investments and manage a fund of over $30,000. Contributed via 10K analysis and investment pitches to this fund which has seen 32% growth throughout 2017.
GPA: 3.51
GPA: 4.35
Outside of school, I enjoy woodworking in which I have built canoes, skateboards and skiis from scratch. I have been a competitive runner for the past 6 years and have now shifted towards marathon training.
I love spending time outdoor and enjoy backpacking/camping. I was introduced to camping as a Boy Scout in my teenage years and since then my favorite backpacking trips have been to the Grand Canyon, Arizona and Juneau, Alaska. I have been skydiving and participated in multiple competitive eating challanges.


| # | Name | Status | Edit | Delete |
|---|---|---|---|---|
| 1 | Swimming Pool | Active |
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| 2 | Bar | Inactive |
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| 3 | Restaurant | Active |
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| 4 | Spa | Active |
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@* Shopping Cart *@ @(cart: List[Item], user: User, total: Double) @usercomponent("My shopping Cart", user) {


Enter frequencies (cycles/sec aka Hz) and see their time values, or vice-versa
- Frequency input:
1 0 2:45
is 0Hz (size 1) + 1Hz (size 0) + 2Hz (size 2, phase-shifted 45-degrees)
- Time input:
1 2 3
generates a wave that hits 1 2 3
Click Mr. Fourier for night mode. Have fun!


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Every good work of software starts by scratching a developer's personal itch!!
Cove.tool, Atlanta
Experienced in all stages of Software Development Life Cycle.
Developed new features for, cove.tool a web-based SaaS application, which aided in a more useful and accurate
optimization of results using Python(Django)
Customized the Interface to make it consistent and reduce cognitive load based on direct user feedback and
insights from consultants.
I also took up the task to integrate React into the software as cove involves high user interaction and view updates. React made it easy with dynamic data display and Fast render with Virtual DOM.
Implemented an npm package for react API calls and react cove components to be reused internally.
Managed every stage of application development with git version control, virtual servers using AWS EC2 instance
and storage and backup using AWS S3
Worked on reducing the number of hits to Postgres database resulting in faster simulations.
At CoveTool my personal mission is to create a simple, easy to access, consistent, clear, purposeful user Interface by using the most fast, scalable, and simple technology. Yes, I am a big fan of React.js.
Illinois Institute of Technology,Chicago
Customized the application to make it suitable and efficient for back-end users as well as front-end staff and faculty
users.
Used ES6 and HTML5 to make the user interface clear, concise, consistent, and responsive
Illinois Institute of Technology,Chiacgo
Assisted students, faculty, and staff with various technology issues. Provided technical
support via FootPrints, phone calls, emails, and face-to-face walk-ins.
Remotely
troubleshoot and install software.
I believe in writing clean, elegant and efficient code!!
Master's in Computer Science
Chicago,IL
Bachelor of Engineering, Information Science & Engineering
Bangalore,India
Designer, developer, and an overall thinker!!


I am a final year student pursuing my bachelors in Electrical Engineering at Jadavpur University. I am currently doing my undergraduate research under the guidance of Prof. Ram Sarkar at the CMATER lab. My research interests lie at the intersection of Computer Vision and Geometric Deep Learning with a particular focus on their applications in Virtual reality and Augmented reality systems.
I love doing research in challenging fields, I have worked on various image classification models using fuzzy integral methods, optimizers and Graph Neural Networks.
I am looking to pursue Master of Science in Computer Science Engineering specializing in Computer Vision and Computer graphics in the future.
 Here, we use the pre-trained DenseNet121 model as a feature extractor to build a classifier for the said purpose. Before extracting features, we work on the original thermal breast images to get outputs using two edge detectors - Prewitt and Roberts. These two edge-maps along with the original image make the input to the DenseNet121 model as a 3-channel image. The thermal breast image dataset namely, Database for Mastology Research (DMR-IR) is used to evaluate performance of our model.
In this work, a classifier ensemble technique is proposed, utilizing Choquet fuzzy integral, wherein convolutional neural network (CNN) based models are used as base classifiers. We use the transfer learning scheme to train the base classifiers, which are InceptionV3, DenseNet121, and VGG19. We utilize the pre-trained CNN models to extract features and classify the chest X-ray images using two dense layers and one softmax layer. After that, we combine the prediction scores of the data from individual models using Choquet fuzzy integral to get the final predicted labels, which is more accurate than the prediction by the individual models. To determine the fuzzy-membership values of each classifier for the application of Choquet fuzzy integral, we use the validation accuracy of each classifier.
We propose an ensemble learning model which uses the output of three image denoising models namely, ADNet, DnCNN, and IRCNN in the ratio of 2:3:6 respectively. The first model (ADNet) consists of Convolutional Neural Networks with attention along with median filter layers after every convolutional layer and a dilation rate of 8. In case of the second model, it is a feed forward denoising CNN or DnCNN with median filter layers after half of the Convolutional layers. For the third model which is Deep CNN Denoiser Prior or IRCNN, the model contains dilated convolutional layers and median filter layers up to the dilated convolutional layers with a dilation rate of 6. By quantitative analysis, we note that our model performs significantly well when tested on the BSD500 and Set12 datasets
In this work we use the attention-guided CNN model as the base model. Attention-guided CNN model consists of 4 sections the SB or Sparse Block, the FEB or Feature Enhancement Block, the AB or Attention Block and the RB or Reconstruction Block. In the Sparse Block section we add median filter layers after every convolutional or dilated convolutional block. We also increase the dilation rate of the dilated convolutional layers from 2 as proposed in the original paper to 8.


In Jupyter notebook you can execute only one cell at a time. So, you have to mind code dependencies when executing cells. For your convenience, you can use smart shortcuts to execute the current cell and select the below one: Shift+Enter for Windows or for macOS .


| MemTotal | 1550676 | The total amount of memory available for the android system. This does not count memory used by kernel code or the modem side. |
| MemFree | 270560 | This is the amount of yet completely not used memory. |
| Buffers | 13364 | Memory in buffer cache. This memory can be freed by the kernel when needed. |
| Cached | 739432 | Memory in disk cache (memory copy of disk content in order to speed disk IO). This memory can be freed by the kernel when needed. |
| SwapCached | 0 | Memory that once was swapped out, is swapped back in but still also is in the swapfile (if memory is needed it doesn't need to be swapped out AGAIN because it is already in the swapfile. This saves I/O). Not used in android (since officially android doesn't use a swap partition). |
| Active | 791448 | Memory that has been used more recently and usually not reclaimed unless absolutely necessary. |
| Inactive | 392184 | Memory which has been less recently used. It is more eligible to be reclaimed for other purposes. |
| SwapTotal | 0 | Total amount of physical swap memory. Not used in android (since officially android doesn't use a swap partition). |
| SwapFree | 0 | Total amount of swap memory free. Not used in android (since officially android doesn't use a swap partition). |
| Dirty | 264 | Memory which is waiting to get written back to the disk. |
| Writeback | 0 | Memory which is actively being written back to the disk. |
| AnonPages | 435256 | Non-file backed pages mapped into userspace page tables. |
| Mapped | 363832 | Files which have been mmaped, such as libraries. |
| Shmem | 27680 | Used shared memory (usually used by IPC) |
| Slab | 34652 | In-kernel data structures cache. |
| SReclaimable | 14244 | Part of Slab, that might be reclaimed, such as caches. |
| SUnreclaim | 20408 | Part of Slab, that cannot be reclaimed on memory pressure. |
| PageTables | 12880 | Amount of memory dedicated to the lowest level of page tables. |
| VmallocTotal | 122880 | Total size of vmalloc memory area. |
| VmallocUsed | 46556 | Amount of vmalloc area which is used. |
| VmallocChunk | 14244 | Largest contiguous block of vmalloc area which is free. |


This is the Moon also known as Luna, the only moon and the only permanent natural satellite of earth. It is currently the fifth largest natural satellite in our Solar System, and the largest satellite among other planetary satellites relative to the size of the planet that it orbits. Talking about size, it is about a quarter or one fourth of the size of Earth, the planet it orbits. It is about 238,855 miles away from Earth and has a twenty seven day orbit around our planet.
Thhe moon does not have it's own source of light. Instead, it uses the light from the sun by simply reflecting it which causes it to glow during the night. The moon takes on different stages during its orbit due to the sun reflecting different parts of the moon as it goes through its monthly cycle. There is a far side of the moon due to the moon rotating on its own axis at the same rate as it orbits Earth making us see the same side of the moon. The cycle goes from a new moon, waxing crescent, first quarter, waxing gibbous, full moon, waning gibbous, third quarter, waning crescent, and back to a new moon in its full twenty seven day cycle.
Scientists predict that the Moon formed early on in the solar system’s history just after Earth and an object relative to the size of Mars smashed into each other. The collision sent chunks of Earth and the impactor flying into space that were then pulled back together by the gravity which then formed the moon.


#include <math.h>
#include "superlu_ddefs.h"
Functions/Subroutines | |
| static void | pdgstrf2 (superlu_options_t *options, int_t k, double thresh, Glu_persist_t *Glu_persist, gridinfo_t *grid, LocalLU_t *Llu, SuperLUStat_t *stat, int *info) |
| static void | pdgstrs2 (int_t, int_t, Glu_persist_t *, gridinfo_t *, LocalLU_t *, SuperLUStat_t *) |
| int_t | pdgstrf (superlu_options_t *options, int m, int n, double anorm, LUstruct_t *LUstruct, gridinfo_t *grid, SuperLUStat_t *stat, int *info) |
| static int | probe_recv (int iam, int source, int tag, MPI_Datatype datatype, MPI_Comm comm, int buf_size) |
-- Distributed SuperLU routine (version 1.0) -- Lawrence Berkeley National Lab, Univ. of California Berkeley.  * Factor diagonal and subdiagonal blocks and test for exact singularity. ( pdgstrf2(0), one column at a time ) * Compute block row of U * Update trailing matrix
Loop over the remaining blocks of columns. mycol = MYCOL( iam, grid ); myrow = MYROW( iam, grid ); N = nsupers; For (k = 1; k < N; ++k) { krow = PROW( k, grid ); kcol = PCOL( k, grid ); Pkk = PNUM( krow, kcol, grid );
* Factor diagonal and subdiagonal blocks and test for exact singularity. if ( mycol == kcol ) { pdgstrf2(k), one column at a time }
* Parallel triangular solve if ( iam == Pkk ) multicast L_k,k to this process row; if ( myrow == krow && mycol != kcol ) { Recv L_k,k from process Pkk; for (j = k+1; j < N; ++j) if ( PCOL( j, grid ) == mycol && A_k,j != 0 ) U_k,j = L_k,k \ A_k,j; }
* Parallel rank-k update if ( myrow == krow ) multicast U_k,k+1:N to this process column; if ( mycol == kcol ) multicast L_k+1:N,k to this process row; if ( myrow != krow ) { Pkj = PNUM( krow, mycol, grid ); Recv U_k,k+1:N from process Pkj; } if ( mycol != kcol ) { Pik = PNUM( myrow, kcol, grid ); Recv L_k+1:N,k from process Pik; } for (j = k+1; k < N; ++k) { for (i = k+1; i < N; ++i) if ( myrow == PROW( i, grid ) && mycol == PCOL( j, grid ) && L_i,k != 0 && U_k,j != 0 ) A_i,j = A_i,j - L_i,k * U_k,j; } }
Remaining issues (1) Use local indices for L subscripts and SPA. [DONE]
| int_t pdgstrf | ( | superlu_options_t * | options, | |
| int | m, | |||
| int | n, | |||
| double | anorm, | |||
| LUstruct_t * | LUstruct, | |||
| gridinfo_t * | grid, | |||
| SuperLUStat_t * | stat, | |||
| int * | info | |||
| ) |
Purpose =======
PDGSTRF performs the LU factorization in parallel.
Arguments =========
options (input) superlu_options_t* The structure defines the input parameters to control how the LU decomposition will be performed. The following field should be defined: o ReplaceTinyPivot (yes_no_t) Specifies whether to replace the tiny diagonals by sqrt(epsilon)*norm(A) during LU factorization.
m (input) int Number of rows in the matrix.
n (input) int Number of columns in the matrix.
anorm (input) double The norm of the original matrix A, or the scaled A if equilibration was done.
LUstruct (input/output) LUstruct_t* The data structures to store the distributed L and U factors. The following fields should be defined:
o Glu_persist (input) Glu_persist_t* Global data structure (xsup, supno) replicated on all processes, describing the supernode partition in the factored matrices L and U: xsup[s] is the leading column of the s-th supernode, supno[i] is the supernode number to which column i belongs.
o Llu (input/output) LocalLU_t* The distributed data structures to store L and U factors. See superlu_ddefs.h for the definition of 'LocalLU_t'.
grid (input) gridinfo_t* The 2D process mesh. It contains the MPI communicator, the number of process rows (NPROW), the number of process columns (NPCOL), and my process rank. It is an input argument to all the parallel routines. Grid can be initialized by subroutine SUPERLU_GRIDINIT. See superlu_ddefs.h for the definition of 'gridinfo_t'.
stat (output) SuperLUStat_t* Record the statistics on runtime and floating-point operation count. See util.h for the definition of 'SuperLUStat_t'.
info (output) int* = 0: successful exit < 0: if info = -i, the i-th argument had an illegal value > 0: if info = i, U(i,i) is exactly zero. The factorization has been completed, but the factor U is exactly singular, and division by zero will occur if it is used to solve a system of equations.
| static void pdgstrf2 | ( | superlu_options_t * | options, | |
| int_t | k, | |||
| double | thresh, | |||
| Glu_persist_t * | Glu_persist, | |||
| gridinfo_t * | grid, | |||
| LocalLU_t * | Llu, | |||
| SuperLUStat_t * | stat, | |||
| int * | info | |||
| ) | [static] |
Purpose ======= Factor diagonal and subdiagonal blocks and test for exact singularity. Only the process column that owns block column *k* participates in the work.
Arguments =========
k (input) int (global) The column number of the block column to be factorized.
thresh (input) double (global) The threshold value = s_eps * anorm.
Glu_persist (input) Glu_persist_t* Global data structures (xsup, supno) replicated on all processes.
grid (input) gridinfo_t* The 2D process mesh.
Llu (input/output) LocalLU_t* Local data structures to store distributed L and U matrices.
stat (output) SuperLUStat_t* Record the statistics about the factorization. See SuperLUStat_t structure defined in util.h.
info (output) int* = 0: successful exit < 0: if info = -i, the i-th argument had an illegal value > 0: if info = i, U(i,i) is exactly zero. The factorization has been completed, but the factor U is exactly singular, and division by zero will occur if it is used to solve a system of equations.
| static void pdgstrs2 | ( | int_t | m, | |
| int_t | k, | |||
| Glu_persist_t * | Glu_persist, | |||
| gridinfo_t * | grid, | |||
| LocalLU_t * | Llu, | |||
| SuperLUStat_t * | stat | |||
| ) | [static] |
| static int probe_recv | ( | int | iam, | |
| int | source, | |||
| int | tag, | |||
| MPI_Datatype | datatype, | |||
| MPI_Comm | comm, | |||
| int | buf_size | |||
| ) | [static] |


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I play on a server that is technically "epic", but once you hit low-20's for level its boring and tedious (same areas/stuff over and over) to go much further and most players stop about mid 20's in level.
There's a lot of very nice builds designed for epic play, but where do you all play them?
Let me know!
It depends on your play style, persistant worlds usualy have slow level progress, which is fine if you got alot of time or like roleplaying. When I play on a PW I always try to find a server with extremly low xp and good roleplayers, but that doesn't seem to be an option for you. I Dunno about any PW with high xp, but I know there are a few out there. If you like PVP then my suggestion would be to try Bastions of War. That is a PVP arena where you begin in the mid twenties and play up to level 40, but beware, if your build isn't good enough you will get slaughtered.
IMO the best PvP arena is Antiworld (CTF), if that's what interests you.
EDIT: linkified AW _________________ Fanget av begravelsen pines vi av guds godhet ingen flammer, intet hat de hadde rett vi kom til Helvete...
Try The Heartlands Project PW. It is relatively fast leveling up to 20 then gets progressively harder, but still fast. The epic areas are challenging and give decent xp up till level 35 or so. All builds are welcome, but be warned there are some modifications to various feats and a custom Dev Crit in place that does not require you to take the feat. Be sure to visit the forum for more info or PM me. They have a thread over in Ye Olde Tavern.
Right now you won't find hardly anyone on due to most folks helping with getting ready for the transition over to NwN2.
Athas Reborn is based on the 2'nd edition pnp world of Darksun. Gear and nerfs are balanced for pvp. If you like a challenge click:


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Simbody
3.6
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This is a bidirectional iterator suitable for moving forward or backward within a list of Nodes, for writable access. More...
Public Member Functions | |
| node_iterator (NodeType allowed=AnyNodes) | |
| node_iterator (Node &node, NodeType allowed=AnyNodes) | |
| node_iterator (const node_iterator &src) | |
| Copy constructor takes a node_iterator that can be const, but that still allows writing to the Node. More... | |
| ~node_iterator () | |
| An iterator destructor never deletes the object to which it refers. More... | |
| node_iterator & | operator= (const node_iterator &src) |
| Copy assignment takes an node_iterator that can be const, but that still allows writing to the Node. More... | |
| node_iterator & | operator++ () |
| node_iterator | operator++ (int) |
| node_iterator & | operator-- () |
| node_iterator | operator-- (int) |
| Node & | operator* () |
| Node * | operator-> () |
| Node & | operator* () const |
| Node * | operator-> () const |
| bool | operator== (const node_iterator &other) const |
| bool | operator!= (const node_iterator &other) const |
Protected Member Functions | |
| node_iterator (TiXmlNode *tiNode, NodeType allowed=AnyNodes) | |
| void | reassign (TiXmlNode *tiNode) |
Friends | |
| class | Document |
| class | Node |
| class | Element |
| class | element_iterator |
This is a bidirectional iterator suitable for moving forward or backward within a list of Nodes, for writable access.
By default we will iterate over all nodes but you can restrict the types at construction.
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inlineexplicit |
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inline |
Copy constructor takes a node_iterator that can be const, but that still allows writing to the Node.
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inline |
An iterator destructor never deletes the object to which it refers.
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inlineexplicitprotected |
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inline |
Copy assignment takes an node_iterator that can be const, but that still allows writing to the Node.
| node_iterator& SimTK::Xml::node_iterator::operator++ | ( | ) |
| node_iterator SimTK::Xml::node_iterator::operator++ | ( | int | ) |
| node_iterator& SimTK::Xml::node_iterator::operator-- | ( | ) |
| node_iterator SimTK::Xml::node_iterator::operator-- | ( | int | ) |
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friend |


Table of content
User guide
- Setup
- Import gradle projects
- New gradle projects by wizard
- Virtual root project
- Junit-Integration
- Launch gradle
- Editor
- Actions
- Refresh complete workspace
- Show project dependencies
- Quick launch
- Reimport project(s)
- Add new sub project
- Other
- Validation
- File handling
- Project decoration


class: center, middle, inverse, title-slide # Density dependent change ### Christopher Moore ### Week 2 --- # Creating a density-dependent model, au Français ![VerhulstImage](Wk02_DensDep_files/Verhulst.png) --- # Creating a density-dependent model, translated *If `\(p\)` is the population, then `\(dp\)` is an infinitesimally small increase that is received in a very short period of time `\(dt\)`. If the population increase by geometric progression, we would have the equations `\(\frac{dp}{dt} = mp\)`. However, as the rate of population growth is slowed by the very increase in the number of inhabitants, we must subtract from `\(mp\)` an unknown function of `\(p\)`, so that the formula to be integrated can be written as* `$$\frac{dp}{dt} = mp - \varphi (p)$$` *The simplest hypothesis that can be made on the form of the function `\(\varphi\)` is to suppose that `\(\varphi (p) = np^2\)`.* --- # The logistic model: a balance of forces Most generally, we wish model population growth with two functions that capture two biological phenomena, growth and crowding. -- `$$\frac{\Delta N}{\Delta t} = f(N),$$` with `\(f(N)\)` describing growth and crowding: -- `$$f(N) = \text{growth} - \text{crowding}.$$` -- Let growth be `\(rN\)` and crowding be `\(\alpha N^2\)`, to give us `$$\frac{\Delta N}{\Delta t} = rN - \alpha N^2$$` -- In continuous and discrete time the logistic equations are respectively: `$$\begin{align} \frac{dN}{dt} &= rN - \alpha N^2 \\ N_{t+1} &= \lambda N_t - \alpha N_t^2 \end{align}$$` --- # Births and deaths in the logistic model (I'm only describing continous time, but it's analagous in discrete time) A generalized way of writing a more mechanistic model of births and deaths into the logisitc model is respectively by the use of functions of `\(N\)`, `\(B(N)\)` and `\(D(N)\)`: -- `$$\frac{dN}{dt} = B(N) - D(N)$$` -- Let's say that both per-capita births and death rates linearly decrease as a function of density, `\(N\)`. So, we can write: -- `$$\frac{dN}{dt} = (bN - \mu N^2) - (dN - \nu N^2)$$` -- Linearity becomes clear when we write this as *per-capita* by dividing both sides by `\(N\)`: `$$\frac{1}{N}\frac{\mathrm{d}N}{\mathrm{d}t} = (b - \mu N) - (d - \nu N)$$` --- class: inverse, center, middle  --- # We have (a) model(s)—let's do all of the things! * Analyze it! * Simulate it * Solve it * Find equilibria (long-term behavior) * Determine stability (behavior if perturbed) * Visualize it! * Plot a time series * Plot population size `\((N)\)` and population growth `\(\left(\frac{dN}{dt}\right)\)` * Plot population size `\((N)\)` and per-capita growth `\(\left(\frac{1}{N}\frac{dN}{dt}\right)\)` --- # Analyze it!: simulation .pull-left[ Exactly what you did yesterday: ![](Wk02_DensDep_files/figure-html/unnamed-chunk-1-1.png) ] -- .pull-right[ But also vary parameters (here, `\(r\)`): ![](Wk02_DensDep_files/figure-html/many.log-1.png) ] --- #Analyze it!: solve it For the `\(r\text{-}\alpha\)` logistic equation: `$$N(t) = \frac{rN(0)e^{rt}}{r + \alpha N(0)\left(e^{rt} - 1\right)}$$` -- For the `\(K\)` logistic equation: `$$N(t) = \frac{KN(0)e^{rt}}{K + N(0)\left(e^{rt} - 1\right)}$$` -- ** This will be the final analytical solution in this class 😥 ** --- #Analyze it!: finding equlibria The continuous logistic `$$\begin{align}\frac{\mathrm{d}N}{\mathrm{d}t} &= rN - \alpha N^2 \\ 0 &= rN - \alpha N^2 \\ 0 &= N\left(r - \alpha N\right) \\ N^* &= 0 \\ 0 &= r - \alpha N\\ \alpha N &= r \\ N^* &= \frac{r}{\alpha} \end{align}$$` --- #Analyze it!: finding equlibria The discrete logistic `$$\begin{align} N_{t+1} &= \lambda N_t - \alpha N_t^2 \\ N_t &= \lambda N_t - \alpha N_t^2 \\ 0 &= \lambda N_t - \alpha N_t^2 - N_t \\ 0 &= N_t \left(\lambda - \alpha N_t - 1 \right) \\ N^* &= 0 \\ 0 &= N_t \left(\lambda - \alpha N_t - 1 \right) \\ 0 &= \lambda - \alpha N_t - 1 \\ \alpha N_t &= \lambda - 1 \\ N^* &= \frac{\lambda - 1}{\alpha} \end{align}$$` --- # Analyze it!: perturbation Perturb the equilibira! Actually, we'll cover more of this in Ch. 4, *Dynamics.* --- # Visualize it!: time series ```r logistic <- function(t, y, p) { N <- 1.5*y - 0.15*y^2 return(list(N)) } out <- ode(y = 0.01, times = seq(0, 10, 0.01), parms = NA, func = logistic) par(mar = c(4, 4, 0.1, 0.1), oma = c(0, 0, 0, 0)) plot(x = out[,1], y = out[,2], las = 1, xlab = "Time", ylab = "Density (N)", type = "l", lwd = 2) ``` ![](Wk02_DensDep_files/figure-html/unnamed-chunk-2-1.png) --- # Visualize it!: population growth and density ```r logistic <- function(t, y, p) { N <- 1.5*y - 0.15*y^2 return(list(N)) } out <- ode(y = 0.01, times = seq(0, 10, 0.01), parms = NA, func = logistic) par(mar = c(4, 4, 0.1, 0.1), oma = c(0, 0, 0, 0)) len.out <- nrow(out) plot(x = out[1:(len.out-1),2], y = (out[2:len.out,2] - out[1:(len.out-1),2]), las = 1, xlab = "Density (N)", ylab = "Population growth (dN/dt)", type = "l", lwd = 2) ``` ![](Wk02_DensDep_files/figure-html/unnamed-chunk-3-1.png) --- # Visualize it!: per-capita growth and density ```r logistic <- function(t, y, p) { N <- 1.5*y - 0.15*y^2 return(list(N)) } out <- ode(y = 0.01, times = seq(0, 10, 0.01), parms = NA, func = logistic) par(mar = c(4, 4, 0.1, 0.1), oma = c(0, 0, 0, 0)) len.out <- nrow(out) plot(x = out[1:(len.out-1),2], y = (out[2:len.out,2] - out[1:(len.out-1),2])/out[1:(len.out-1),2], las = 1, xlab = "Density (N)", ylab = "Per calita growth (dN/dt/N)", type = "l", lwd = 2) ``` ![](Wk02_DensDep_files/figure-html/unnamed-chunk-4-1.png) --- # Discrete-time density dependence -- Hassel (also Bleasdale and Nedler) model: `$$N_{t+1} = \frac{\lambda N_t}{\left(1 + \alpha N_t\right)^b}$$` -- Beverton and Holt (same as Hassel when `\(b = 1\)`): `$$N_{t+1} = \frac{\lambda N_t}{\left(1 + \alpha N_t\right)}$$` -- The Ricker equation: `$$N_{t+1} = N_t \exp\left(r\left(1 - bN_t\right)\right)$$` --- # Analyze it!: simulation .pull-left[ Choosing the Hassell model: ![](Wk02_DensDep_files/figure-html/unnamed-chunk-5-1.png) ] -- .pull-right[ But also vary parameters (here, `\(b\)`): ![](Wk02_DensDep_files/figure-html/many.disc.log-1.png) ] --- # Analyze it!: solve it and find equilibria 1. No analytical solutions 2. We can find equilibira for some! - For discrete-time equations, set `\(N_{t + 1} = N^*\)` and `\(N_t = N^*\)`, and solve for `\(N^*\)` - E.g., `$$\begin{align} N_{t+1} &= \frac{\lambda N_t}{1 + \alpha N_t} = \\ N^* &=\frac{\lambda N^*}{1 + \alpha N^*} \\ N^* &= 0,~\text{Equilibrium 1} \\ 1 &= \frac{\lambda}{1 + \alpha N^*} \\ 1 + \alpha N^* &= \lambda \\ \alpha N^* &= \lambda - 1 \\ N^* &= \frac{\lambda - 1}{\alpha},~\text{Equilibrium 2}\\ \end{align}$$` --- # Analyze it!: perturb equilibira Again, more on this in a few weeks. --- # Visualize it!: time series ```r Hassell <- function(t, y, p) { Nt <- y lambda <- p["lambda"] alpha <- p["alpha"] b <- p["b"] Nt1 <- lambda*Nt/((1 + alpha*Nt)^b) return(list(Nt1)) } Hassell.parms <- c(lambda = 1.5, alpha = 2, b = 0.5) out <- ode(y = 0.01, times = seq(0, 25, 1), parms = Hassell.parms, func = Hassell, method = "iteration") par(mar = c(4, 4, 0.1, 0.1), oma = c(0, 0, 0, 0)) plot(x = out[,1], y = out[,2], las = 1, xlab = "Time", ylab = "Density (N)", type = "p", lwd = 2, pch = 16) segments(x0 = out[,1][-nrow(out)], y0 = out[,2][-nrow(out)], x1 = out[,1][-1], y1 = out[,2][-nrow(out)], lwd = 2) ``` --- # Visualize it!: time series ![](Wk02_DensDep_files/figure-html/unnamed-chunk-7-1.png) --- # Visualize it!: population growth and density ```r Hassell <- function(t, y, p) { Nt <- y lambda <- p["lambda"] alpha <- p["alpha"] b <- p["b"] Nt1 <- lambda*Nt/((1 + alpha*Nt)^b) return(list(Nt1)) } Hassell.parms <- c(lambda = 1.5, alpha = 2, b = 0.5) out <- ode(y = 0.001, times = seq(0, 40, 1), parms = Hassell.parms, func = Hassell, method = "iteration") Hassell.out <- out[-1,2] - out[-nrow(out),2] plot(x = out[1:(nrow(out)-1),2], y = Hassell.out, las = 1, xlab = "Density (N)", ylab = bquote("Population growth N"[t+1]-"N"[t]), type = "l", lwd = 2) ``` --- # Visualize it!: population growth and density ![](Wk02_DensDep_files/figure-html/unnamed-chunk-9-1.png) --- # Visualize it!: per-capita growth and density ```r Hassell <- function(t, y, p) { Nt <- y lambda <- p["lambda"] alpha <- p["alpha"] b <- p["b"] Nt1 <- lambda*Nt/((1 + alpha*Nt)^b) return(list(Nt1)) } Hassell.parms <- c(lambda = 1.5, alpha = 2, b = 0.5) out <- ode(y = 0.001, times = seq(0, 40, 1), parms = Hassell.parms, func = Hassell, method = "iteration") Hassell.out <- (out[-1,2] - out[-nrow(out),2])/out[-1,2] plot(x = out[1:(nrow(out)-1),2], y = Hassell.out, las = 1, xlab = "Density (N)", ylab = bquote("Population growth N"[t+1]-"N"[t]/"N"[t]), type = "l", lwd = 2) ``` --- # Visualize it!: per-capita growth and density ![](Wk02_DensDep_files/figure-html/unnamed-chunk-11-1.png)


| 017:017 Khan | : |
And how many generations have We destroyed after Nuh (Noah)! And Sufficient is your Lord as an All-Knower and All-Beholder of the sins of His slaves. |
| 017:017 Maulana | : |
And how many generations did We destroy after Noah! And thy Lord suffices as being Aware and Seer of his servants' sins. |
| 017:017 Pickthal | : |
How many generations have We destroyed since Noah! And Allah sufficeth as Knower and Beholder of the sins of His slaves. |
| 017:017 Rashad | : |
Many a generation have we annihilated after Noah. Your Lord is most efficient in dealing with the sins of His servants; He is fully Cognizant, Seer. |
| 017:017 Sarwar | : |
We have destroyed many generations after the time of Noah. Your Lord is All knowing and Well Aware of the sins of His servants. |
| 017:017 Shakir | : |
And how many of the generations did We destroy after Nuh! and your Lord is sufficient as Knowing and Seeing with regard to His servants' faults. |
| 017:017 Sherali | : |
How many generations did WE destroy after Noah ! and thy Lord suffices as Knower and Seer of the sins of HIS servants. |
| 017:017 Yusufali | : |
How many generations have We destroyed after Noah? and enough is thy Lord to note and see the sins of His servants. |
Concepts/Themes Covered: أركان الإسلام > التوحيد > توحيد الله تعالي > صفات الله تعالى > بصيراً Pillars of Islam> Islamic> Oneness of Allah> His Glory's Characteristics> All Seer الإيمان > اليوم الآخر > الجزاء بالعمل Faith> The Hereafter> The Award against Action العمل > العمل الطالح > اقتراف الذنوب Action(Work)> Bad Deeds>Committing Sins القصص والتاريخ > العبر التاريخية فى أنباء القرى The Stories and the History> The Historic Examples of Towns' News
This tool uses eight English parallel translations for the Holy Quran imported from Mr. Clay Smith. You can also visit Qurany Concepts for browsing the Quran themes or topics. If you want to search the Holy Quran for keywords, please visit Qurany Keywords.


file_type(path)
file_device(path)
file_inode(path)
file_mode(path)
file_number_of_links(path)
file_owner(path)
file_group(path)
file_size(path)
file_last_access_time(path)
file_last_modification_time(path)
file_last_change_time(path)
file_creation_time(path)
file_attributes(path)
Return the various attributes of the file at path
.
These functions combines a call to file_info
with an accessor
to one of the file-information object's fields.
For file_type(path)
, the returned value is one of the following symbols:
'regular (a regular file), 'directory, 'character_special (character special device), 'block_special (block special device), 'fifo, 'symbolic_link, 'socket, 'unknown (file is of an unknown type).
For file_last_access_time
, file_last_modification_time
, file_last_change_time
and
file_creation_time
, the return value is a UNIX timestamp. (seconds elapsed since the UNIX epoch).


Combining multiple images into a single one
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Click on the above button to combine the two images above together


| WWW Access Statistics for 2001 |
|---|
| Month | Hits | Files | Pageviews | Sessions | KBytes sent |
|---|---|---|---|---|---|
| December 2001 | 15541 | 4067 | 2181 | 1461 | 60798 |
| November 2001 | 16293 | 4248 | 2358 | 1422 | 67494 |
| October 2001 | 21214 | 4382 | 1745 | 1327 | 60002 |
| September 2001 | 44684 | 5429 | 1934 | 1393 | 93329 |
| August 2001 | 15866 | 7139 | 2734 | 1165 | 62434 |
| July 2001 | 13471 | 3650 | 2117 | 1205 | 33734 |
| June 2001 | 0 | 0 | 0 | 0 | 0 |
| May 2001 | 0 | 0 | 0 | 0 | 0 |
| April 2001 | 0 | 0 | 0 | 0 | 0 |
| March 2001 | 0 | 0 | 0 | 0 | 0 |
| February 2001 | 0 | 0 | 0 | 0 | 0 |
| January 2001 | 0 | 0 | 0 | 0 | 0 |
| Total | 127069 | 28915 | 13069 | 7973 | 377789 |
| Average | 10589 | 2409 | 1089 | 664 | 31482 |
|
Frames version (requires JavaScript) |
Back to the Main Page Evaluation version - please register your copy |
3D model (requires VRML) |
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| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
java.lang.Object | +--org.apache.catalina.session.StoreBase
Abstract implementation of the Store interface to support most of the functionality required by a Store.
| Field Summary | |
protected int |
checkInterval
The interval (in seconds) between checks for expired sessions. |
protected int |
debug
The debugging detail level for this component. |
protected static java.lang.String |
info
The descriptive information about this implementation. |
protected LifecycleSupport |
lifecycle
The lifecycle event support for this component. |
protected Manager |
manager
The Manager with which this JDBCStore is associated. |
protected StringManager |
sm
The string manager for this package. |
protected boolean |
started
Has this component been started yet? |
protected static java.lang.String |
storeName
Name to register for this Store, used for logging. |
protected java.beans.PropertyChangeSupport |
support
The property change support for this component. |
protected java.lang.Thread |
thread
The background thread. |
protected boolean |
threadDone
The background thread completion semaphore. |
protected java.lang.String |
threadName
Name to register for the background thread. |
| Fields inherited from interface org.apache.catalina.Lifecycle |
START_EVENT, STOP_EVENT |
| Constructor Summary | |
StoreBase()
|
| Method Summary | |
void |
addLifecycleListener(LifecycleListener listener)
Add a lifecycle event listener to this component. |
void |
addPropertyChangeListener(java.beans.PropertyChangeListener listener)
Add a property change listener to this component. |
int |
getCheckInterval()
Return the check interval (in seconds) for this Store. |
int |
getDebug()
Return the debugging detail level for this Store. |
java.lang.String |
getInfo()
Return the info for this Store. |
Manager |
getManager()
Return the Manager with which the Store is associated. |
java.lang.String |
getStoreName()
Return the name for this Store, used for logging. |
java.lang.String |
getThreadName()
Return the thread name for this Store. |
protected void |
log(java.lang.String message)
Log a message on the Logger associated with our Container (if any). |
protected void |
processExpires()
Called by our background reaper thread to check if Sessions saved in our store are subject of being expired. |
void |
removeLifecycleListener(LifecycleListener listener)
Remove a lifecycle event listener from this component. |
void |
removePropertyChangeListener(java.beans.PropertyChangeListener listener)
Remove a property change listener from this component. |
void |
run()
The background thread that checks for session timeouts and shutdown. |
void |
setCheckInterval(int checkInterval)
Set the check interval (in seconds) for this Store. |
void |
setDebug(int debug)
Set the debugging detail level for this Store. |
void |
setManager(Manager manager)
Set the Manager with which this Store is associated. |
void |
start()
Prepare for the beginning of active use of the public methods of this component. |
void |
stop()
Gracefully terminate the active use of the public methods of this component. |
protected void |
threadSleep()
Sleep for the duration specified by the checkInterval
property. |
protected void |
threadStart()
Start the background thread that will periodically check for session timeouts. |
protected void |
threadStop()
Stop the background thread that is periodically checking for session timeouts. |
| Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Methods inherited from interface org.apache.catalina.Store |
clear, getSize, keys, load, remove, save |
| Field Detail |
protected static java.lang.String info
protected int checkInterval
protected java.lang.String threadName
protected static java.lang.String storeName
protected java.lang.Thread thread
protected boolean threadDone
protected int debug
protected boolean started
protected LifecycleSupport lifecycle
protected java.beans.PropertyChangeSupport support
protected StringManager sm
protected Manager manager
| Constructor Detail |
public StoreBase()
| Method Detail |
public java.lang.String getInfo()
getInfo
in interface Store
public java.lang.String getThreadName()
public java.lang.String getStoreName()
public void setDebug(int debug)
debug
- The new debugging detail levelpublic int getDebug()
public void setCheckInterval(int checkInterval)
checkInterval
- The new check intervalpublic int getCheckInterval()
public void setManager(Manager manager)
setManager
in interface Store
manager
- The newly associated Managerpublic Manager getManager()
getManager
in interface Store
public void addLifecycleListener(LifecycleListener listener)
addLifecycleListener
in interface Lifecycle
listener
- The listener to addpublic void removeLifecycleListener(LifecycleListener listener)
removeLifecycleListener
in interface Lifecycle
listener
- The listener to addpublic void addPropertyChangeListener(java.beans.PropertyChangeListener listener)
addPropertyChangeListener
in interface Store
listener
- a value of type 'PropertyChangeListener'public void removePropertyChangeListener(java.beans.PropertyChangeListener listener)
removePropertyChangeListener
in interface Store
listener
- The listener to removeprotected void processExpires()
protected void log(java.lang.String message)
message
- Message to be loggedpublic void run()
run
in interface java.lang.Runnable
public void start() throws LifecycleException
configure()
,
and before any of the public methods of the component are utilized.
start
in interface Lifecycle
java.lang.IllegalStateException
- if this component has already been
started
LifecycleException
- if this component detects a fatal error
that prevents this component from being usedpublic void stop() throws LifecycleException
stop
in interface Lifecycle
java.lang.IllegalStateException
- if this component has not been started
LifecycleException
- if this component detects a fatal error
that needs to be reportedprotected void threadStart()
protected void threadSleep()
checkInterval
property.
protected void threadStop()
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Tuition is set each year by the board of trustees of Nantucket Lighthouse School. Tuition for the 2013-2014 school year:
$12,400, or $344 a week over the 36 weeks of the school year
$13,700, or $380 a week over the 36 weeks of the school year
We understand that different families may have different financial needs. That's why we offer several payment plans to best fit your budget:
Financial Aid is available to qualifying families who complete an application and submit tax records. Awards are generally 20- 30% of tuition. Learn more about the process of applying for financial aid here.