4.4 Analysis Example: Insertion
Sort
This section presents an analysis of the
worst-case running time of insertion sort, a simple
sorting algorithm that works by inserting elements into a
sorted set by scanning the set to determine where each new
element belongs. A complete description of insertion sort
appears in Chapter
12. The code for the sort is shown in Example
4.1.
We begin by identifying which lines of code
are affected by the size of the data to be sorted. These are the statements that
constitute the nested loop, whose outer part iterates from 1
to size - 1 and whose inner part iterates from
j - 1 to wherever the correct position for the
element being inserted is found. All other lines run in a
constant amount of time, independent of the number of elements
to be sorted. Typically, the generic variable n is used to refer to the parameter
on which an algorithm's performance depends. With this in
mind, the outer loop has a running time of T (n)
= n - 1, times some constant
amount of time. Examining the inner loop and considering the
worst case, we assume that we will have to go all the way to
the other end of the array before inserting each element into
the sorted set. Therefore, the inner loop iterates once for
the first element, twice for the second, and so forth until
the outer loop terminates. Effectively, this becomes a
summation from 1 to n - 1,
which results in a running time of T
(n) = (n (n +
1)/2) - n, times some constant
amount of time. (This equation is from the well-known formula
for summing a series from 1 to n.) Consequently:
Example 4.1.
Implementation of Insertion Sort from Chapter
12 /*****************************************************************************
* *
* ------------------------------- issort.c ------------------------------- *
* *
*****************************************************************************/
#include <stdlib.h>
#include <string.h>
#include "sort.h"
/*****************************************************************************
* *
* -------------------------------- issort -------------------------------- *
* *
*****************************************************************************/
int issort(void *data, int size, int esize, int (*compare)(const void *key1,
const void *key2)) {
char *a = data;
void *key;
int i,
j;
/*****************************************************************************
* *
* Allocate storage for the key element. *
* *
*****************************************************************************/
if ((key = (char *)malloc(esize)) == NULL)
return -1;
/*****************************************************************************
* *
* Repeatedly insert a key element among the sorted elements. *
* *
*****************************************************************************/
for (j = 1; j < size; j++) {
memcpy(key, &a[j * esize], esize);
i = j - 1;
/**************************************************************************
* *
* Determine the position at which to insert the key element. *
* *
**************************************************************************/
while (i >= 0 && compare(&a[i * esize], key) > 0) {
memcpy(&a[(i + 1) * esize], &a[i * esize], esize);
i--;
}
memcpy(&a[(i + 1) * esize], key, esize);
}
/*****************************************************************************
* *
* Free the storage allocated for sorting. *
* *
*****************************************************************************/
free(key);
return 0;
}
|


| Home | Trees | Index | Help |
|---|
| Package svnmailer :: Package settings :: Module _base :: Class BaseConfig |
|
object
--+
|
BaseConfig
FileConfig
| Method Summary | |
|---|---|
Initialization | |
Removes a section to prevent further processing | |
| iter |
Iterator over the section names |
| generator |
Returns the options of the specified section |
| Inherited from object | |
x.__delattr__('name') <==> del x.name... | |
x.__getattribute__('name') <==> x.name... | |
x.__hash__() <==> hash(x)... | |
helper for pickle... | |
helper for pickle... | |
x.__repr__() <==> repr(x)... | |
x.__setattr__('name', value) <==> x.name = value... | |
x.__str__() <==> str(x)... | |
| Inherited from type | |
T.__new__(S, ...) -> a new object with type S, a subtype of T... |
| Instance Variable Summary | |
|---|---|
| str | charset : Charset of the config file |
| Method Details |
|---|
__init__(self,
settingsobj)
Initialization |
__delitem__(self,
section)
Removes a section to prevent further processing |
__iter__(self)Iterator over the section names
|
extractSection(self, section, xform=True, keep=False, check=True)Returns the options of the specified section The section is also removed. (except
|
| Instance Variable Details |
|---|
charsetCharset of the config file
|
| Home | Trees | Index | Help |
|---|
| Generated by Epydoc 2.0 on Sun Sep 25 20:49:04 2005 | http://epydoc.sf.net |


There’s been a lot of discussion about what kinds of mental activities are actually capable of changing the brain. Some promises of bolstered IQ and enhanced brain function via specially-designed "brain games" have fizzled out. Meanwhile, meditation
and mindfulness training have accumulated some impressive evidence, suggesting that the practices can change not only the structure and function of the brain, but also our behavior and moment-to-moment experience.
Now, a new study from
the Max Planck Institute finds that three different types of meditation training are linked to changes in corresponding brain regions. The results, published in Science Advances, have a lot of relevance to schools, businesses and, of course,
the general public.
Participants, who were between 20 and 55 years of age, engaged in three different types of training for three months each, totaling a nine-month study period. The first training was dubbed the “Presence” module, and
was very similar to focused awareness meditation, an ancient practice that's been studied a lot in recent years. In this study, participants learned to focus their attention, bringing it back when it wandered, and to attend to the breath and
to their internal body sensations.
The second training was called “Affect,” which sought to enhance empathy and compassion for others—participants learned “loving-kindness” (metta) meditation, and did work with partners, the goal of which
was to enhance one’s compassion and empathy.
The last was the "Perspective" module, akin to mindfulness or open-monitoring meditation. Here, the focus was on observing one’s own thoughts non-judgmentally and enhancing understanding of
the perspectives of others.
The researchers wagered that training in each of these methods would lead to volume increases in corresponding brain areas. And this was largely what they found, as they scanned the participants’ brains at
the end of each module and compared groups against one another. Training in Presence was linked to enhanced thickness in the anterior prefrontal cortex (PFC) and the anterior cingulate cortex (ACC), which are known to be strongly involved
in attention. Affect training was linked to increased thickness in regions known to be involved in socially driven emotions like empathy; and Perspective training associated with changes in areas involved in understanding the mental states
of others, and, interestingly, inhibiting the perspective of oneself.
The results are exciting in that they offer an even more nuanced look at how meditation can change the brain, and in a relatively short amount of time. Lots of research
has found that experienced meditators have significantly altered brain structure and function, but a growing number of studies has also found that relatively brief meditation training in novices (for instance, the well-known eight-week MBSR
program) can also shift brain function, improve well-being, and reduce symptoms of depression and anxiety.
And, the authors say, the results may be applicable in a number of settings, for kids and adults alike. “Our findings suggest a
potential biological basis for how mindfulness and different aspects of social intelligence could be nurtured.
" They add that this kind of sensitivity is especially important nowadays, as our community becomes more global, and understanding
of others' experiences more essential.
“With growing globalization, interconnectedness, and complexity of our societies, ‘soft skills’ have become increasingly important," they say. "Social competences, such as empathy, compassion, and
taking the perspective of another person, allow for a better understanding of others’ feelings and different beliefs and are crucial for successful cooperation.”
Meditation, in its different forms, may be a powerful way to boost the types
of intelligence that matter most.


A lambda expressions can have parameters and results. Lamda expressions can be used to create functions. Lamda expressions do not have a local scope.
# declaration of Lambda expressns
new name := λ(p1 ∈ Type,...) => (expression) ∈ ResultType;
** define lambda expression
new exp := λ(x,y ∈ Z) => x^y ∈ Z;
** use introspection
print type(exp); -- L
** use the lambda expression
new z := 2 * exp(2,3);
** verify the result
expect z = 16; -- will pass
print z;
Lambda Expressions...
restrictions:
result:
Lambda expressions have a special type: "L", that is a reference. This type can be used to define variables, collection elements or parameters that require a lambda expression;
In next example we create a dictionary of expressions then we call every expression in the dictionary by string ID. This is a trick useful to parse a specific formula that comes as a string. You can use this trick for example to implement custom domain specific expressions.
** instantiate 3 Lambda expressions
new gt := λ(x, y ∈ Z) => (x > y) ∈ L;
new lt := λ(x, y ∈ Z) => (x < y) ∈ L;
new eq := λ(x, y ∈ Z) => (x = y) ∈ L;
** define a sub-type, dictionary of rules
type Dic: {[A]:L} <: Map;
** define a hash map of expressions
new dic := {'gt':gt,'lt':lt,'eq':eq} ∈ Dic;
** call 3 rules in very unusual way
print dic['gt'](3,1); -- 1
print dic['lt'](1,2); -- 1
print dic['eq'](2,2); -- 1
Lambda expressions become call-back functions when used as arguments for specific rules that require lambda expressions. The function is executed later in the rule. Lambda function signature is required to define the parameter.
rule foo(a1, a2 ∈ N, xp: λ(x,y ∈ N) => R) => (r ∈ Type):
** prepare the result
let r := xp(a1,a2);
return;
rule main:
** call foo using anonymous expression
print foo(2,3,(x,y)=> x^y); -- 8.0
print foo(2,3,(x,y)=> x*y); -- 6.0
print foo(2,3,(x,y)=> x/y); -- 1.5
return
Read next: Objects


STUDENT LOGIN POTAL
Matric number
Error Messages
Email
Error Messages
password
Error Messages
login
If you don't have an account before register here


{% extends "_layouts/base.html" %} {% block content %}
Hi ! Thanks you for your interest in joining Fweddit. We are a Reddit corporation and so we need to verify your Reddit profile. Please click on the following link and allow us access to your history and your reddit identity (we will not share it with anyone else). You will not be able to process if you do not allow us access.


Click on the map to see the difference in elevation before and after the landslide.
Legend:
Surface point before landslide
Surface point after landslide
Show surface after landslide


Defining words with multiple spellings
bogeyman, n.
boogeyman, n.
A mythical creature that lurks under the beds of small children.
aluminium, n.
aluminum, n.
. . .


| ifsogui.scrollbar: | Types | Modinfo | Source |
| ifsoGUI_ScrollBar | Scrollbar Type. |
| Type ifsoGUI_ScrollBar Extends ifsoGUI_Base | |
| Description | Scrollbar Type. |
| Methods Summary | |
|---|---|
| CalcBarPos | Calculates the position of the progressbar. |
| CanActive | Can this gadget be active. |
| Draw | Draws the gadget. |
| GetBarInterval | Returns the change in value when the bar area is clicked. |
| GetInterval | Returns the interval value. |
| GetMax | Returns the maximum value of the gadget. |
| GetMin | Returns the minimum value of the gadget. |
| GetMinLength | Returns the minimum length of the gadget to be drawn correctly. |
| GetValue | Returns the value of the gadget. |
| GetVertical | Returns whether the gadget is vertical or not. |
| gMouseDown | Called when the mouse button is pressed on the gadget. |
| gMouseUp | Called when the mouse button is released on the gadget. |
| IsMouseOver | Returns whether or not the mouse is over the gadget. |
| KeyPress | Called when a key is pressed on the active gadget. |
| LoadSkin | Load a skin for one instance of the gadget. |
| MouseOut | Called when the mouse leaves the gadget. |
| MouseStatus | Called to determine the mouse status from the gadget. |
| Refresh | Refreshes the gadget. |
| SetBarInterval | Sets the amount the value changes when the bar area is clicked. |
| SetInterval | Sets the interval the value changes when the arrow buttons are pressed. |
| SetMax | Sets the maximum value of the gadget.. |
| SetMin | Sets the minimum value of the gadget. |
| SetMinMax | Sets the minimum and maximum values of the gadget in one call. |
| SetTabOrder | Sets the gadgets TabOrder. 0=Do not tab to this gadget -1=Last in the Tab Order. |
| SetValue | Sets the value of the gadget. |
| Functions Summary | |
|---|---|
| Create | Create and returns a scrollbar gadget. |
| LoadTheme | Called to load the graphics when a new theme is loaded. |
| SystemEvent | GUI system event occured. |
| Method CalcBarPos() | |
| Description | Calculates the position of the progressbar. |
| Information | Internal function should not be called by the user. |
| Method CanActive:Int() | |
| Description | Can this gadget be active. |
| Information | Internal function should not be called by the user. |
| Method Draw(parX:Int, parY:Int, parW:Int, parH:Int) | |
| Description | Draws the gadget. |
| Information | Internal function should not be called by the user. |
| Method GetBarInterval:Int() | |
| Description | Returns the change in value when the bar area is clicked. |
| Method GetInterval:Int() | |
| Description | Returns the interval value. |
| Method GetMax:Int() | |
| Description | Returns the maximum value of the gadget. |
| Method GetMin:Int() | |
| Description | Returns the minimum value of the gadget. |
| Method GetMinLength:Int() | |
| Description | Returns the minimum length of the gadget to be drawn correctly. |
| Method GetValue:Int() | |
| Description | Returns the value of the gadget. |
| Method GetVertical:Int() | |
| Description | Returns whether the gadget is vertical or not. |
| Method gMouseDown(iButton:Int, iMouseX:Int, iMouseY:Int) | |
| Description | Called when the mouse button is pressed on the gadget. |
| Information | Internal function should not be called by the user. |
| Method gMouseUp(iButton:Int, iMouseX:Int, iMouseY:Int) | |
| Description | Called when the mouse button is released on the gadget. |
| Information | Internal function should not be called by the user. |
| Method IsMouseOver:Int(parX:Int, parY:Int, parW:Int, parH:Int, iMouseX:Int, iMouseY:Int) | |
| Description | Returns whether or not the mouse is over the gadget. |
| Information | Internal function should not be called by the user. |
| Method KeyPress(key:Int) | |
| Description | Called when a key is pressed on the active gadget. |
| Information | Internal function should not be called by the user. |
| Method LoadSkin(strSkin:String) | |
| Description | Load a skin for one instance of the gadget. |
| Method MouseOut(iMouseX:Int, iMouseY:Int, gOverGadget:ifsoGUI_Base) 'Called when mouse no longer over gadget | |
| Description | Called when the mouse leaves the gadget. |
| Information | Internal function should not be called by the user. |
| Method MouseStatus:Int(iMouseX:Int, iMouseY:Int) | |
| Description | Called to determine the mouse status from the gadget. |
| Information | Called to the active gadget only. Internal function should not be called by the user. |
| Method Refresh() 'Refresh the size/pos/value of the bar | |
| Description | Refreshes the gadget. |
| Information | Recalculates any geometry/font changes, etc. Internal function should not be called by the user. |
| Method SetBarInterval(iBarInterval:Int) | |
| Description | Sets the amount the value changes when the bar area is clicked. |
| Method SetInterval(iInterval:Int) | |
| Description | Sets the interval the value changes when the arrow buttons are pressed. |
| Method SetMax(iMax:Int) | |
| Description | Sets the maximum value of the gadget.. |
| Method SetMin(iMin:Int) | |
| Description | Sets the minimum value of the gadget. |
| Method SetMinMax(intMin:Int, intMax:Int) | |
| Description | Sets the minimum and maximum values of the gadget in one call. |
| Method SetTabOrder(iTabOrder:Int) | |
| Description | Sets the gadgets TabOrder. 0=Do not tab to this gadget -1=Last in the Tab Order. |
| Method SetValue(iNewValue:Int) | |
| Description | Sets the value of the gadget. |
| Function Create:ifsoGUI_ScrollBar(iX:Int, iY:Int, iW:Int, iH:Int, strName:String, bVertical:Int = True) | |
| Description | Create and returns a scrollbar gadget. |
| Function LoadTheme() | |
| Description | Called to load the graphics when a new theme is loaded. |
| Information | A GadgetSystemEvent is then sent out to all gadgets. Internal function should not be called by the user. |
| Function SystemEvent(id:Int, data:Int) | |
| Description | GUI system event occured. |
| Information | Internal function should not be called by the user. |
| Version | 1.00 |
|---|---|
| Author | Marcus Trisdale |
| Copyright | (c) 2009 Marcus Trisdale |


or
Girl Develop It is here to provide affordable and accessible programs to learn software through mentorship and hands-on instruction.
Some “rules”
Tell us about yourself.
A typical web site will live or is hosted on a web server. Web servers are computers connected to a network.
IP Address: Internet Protocol Address - A unique address for a computer or a server.
Some IP Addresses are only unique to the network they are on while others are completely unique.
These look like random numbers, e.g. http://<IP_ADDRESS>
DNS: Domain Name Service - A directory that associates domain names with host IPs to allow users to connect to web sites via URLs. This separation is important because memorizing numbers is hard, but also because in most professional applications, IP addresses change regularly.
Clients make requests, servers fulfill them (usually).
For our web discussions, client = browser, but search engine crawlers, command line interfaces, and other applications can also behave as clients.
While any type of computer can be used as a server, they are generally larger and more powerful than others.
You may hear large/powerful servers called beefy.
HTML: Hyper Text Markup Language - The coding format used to convey the structure and content of a web site
CSS: Cascading Style Sheets - A language used to describe the presentation of the content
WYSIWYG: What You See Is What You Get - A type of editing software meant to be used by those who don’t know how to code
IDE: Integrated Development Environment - Software meant to support the entire development process, often including compilation for a server-side language. A developer’s main productivity tool.
CMS: Content Management System - A program that allows publishing, editing, and modifying content as well as maintenance from a central interface
Open source: A program in which the source code is available to the general public for use and/or modification from its original design
API: Application Programming Interface - A contract between an application and the world. The interface defines how other applications can interact with the underlying system the API represents.
REST: REpresentational State Transfer - A particular kind of API commonly used by web applications. It uses HTTP verbs and has a defined W3 specification.
RPC: Remote Procedure Call - Another kind of API. Less common than REST.
SEO: Search Engine Optimization - The process of increasing your web site’s perceived value to search engine algorithms, raising its rank in search results
Web 2.0: Buzzword generally describing a trend towards interactivity, rich media, and social engagement in web design
The Cloud: Services and technology that offer remote storage, processing, or other functionality by way of the internet
Programming language: A set of special commands and instructions (usually relatively readable by humans) that tell the computer what to do. These usually have to be compiled.
Compile: Converting a human-readable (high-level) programming language into a lower-level language that the computer understands.
Transpile: A portmaneau of compile and translate. To convert a programming langauge to another language that has a similar level of abstraction. A common example is transpiling ES6+ Javascript to ES5 syntax so browsers can understand it.
Library: A package of related code. For example, moment.js is a cross-broswer compatible JavaScript library for date manipulation and formatting. Other examples: jQuery, React, Backbone, Prototype, Mootools
Framework: In general, a framework is a way of structuring application code. Frameworks often include a set of libraries, and the line between frameworks and libraries can sometimes be blurred. Frameworks tend to be more opinionated than libraries. Examples: Angular, Flask, Django, Rails, Cake
Specification: A set of currently acceptable rules for a given language. For example, HTML5 expands on the HTML4 spec and deprecates some older HTML syntax.
The Stack: (development stack) - The set of languages, libraries, frameworks, and other technologies that an application or development team uses.
Microservice: A way of breaking up an application into small, focused parts that can make development and maintenance faster and easier, but increases dependencies.
Client-side:
Sever-side:
Java:
JavaScript (JS):
Databases:
DevOps:
All these languages, libraries, frameworks, and technologies are tools. Which one you need depends on what problem you’re trying to solve and the constraints that you are under.
Programming technologies are commonly compared to a tool set: A hammer is a great choice if you are trying to get nails into a piece of wood, but probably not the best choice if you are trying to loosen a screw.
PHP
echo "Hello, world!";
Java
class HelloWorld {
static public void main( String args[] ) {
System.out.println( "Hello World!" );
}
}
Python
'Hello, world!'
Ruby
puts 'Hello, world!'
JavaScript
Not server-side, but just for example
document.writeln('Hello, World!');
To build your web site, you will probably need:
You will also need:
A developer’s main job is to solve problems.


Ruby Classes
This week I wanted to explore more into Ruby Classes as they were a big part of this past week's curriculum. To understand classes or when and how to use them, one needs to understand what objects are in Ruby. If someone came up to you and asked you what an object was, you would probably respond by saying, "A visible or tangible thing", right? Yet I cannot physically pick up a Ruby object like I would a ball or box. So what is a Ruby object? An object is an instance of a class and objects have both state and behaviors. States are properties or attributes and behavior is what the object can do through the use of methods. Imagine you are a CEO of a company. Objects are your employees. You can assign objects task for them to perform. They can compute calculations and report back. You can also assign objects to work together with other objects. Classes are essentially the blue print for a set of objects, endowing them with a common structure and common behavior.
I proudly drive a Prius now but I can't help miss the days I use to drive around in my M3! So I created a Car Class where all the objects created in the Car Class are given a set of properties through the use of instance variables. Instance variables always start with "@" symbol. I created 3 instance variables : @model, @top_speed and @drive_train. Each object created in the Car class can hold their individual values for those instance variables. I create a method #drive. The #drive method tells you more about an object in the car class.
def initialize (model, top_speed, drive_train)
@model = model
@top_speed = top_speed
@drive_train = drive_train
end
def drive
puts "The #{@model} is a #{@drive_train} vehicle and can drive up to a top speed of #{@top_speed} mph "
end
end
Now we create 2 Car objects bmw and audi and enter in their model, top speed and drive train. All three are properties set my the Car Class to endow to each of its objects but each object may have different attributes. After creating the objects I invoke the # drive method to tell you more about itself.
audi = Car.new("S4", 155, "four wheel")
bmw.drive
audi.drive
Output:
==> "The S4 is a four wheel vehicle and can drive up to a top speed of 155 mph"


{% extends '../layouts/layout-email.html' %} {% block pageTitle %} {{ data.firstName or 'Bob' }} {{ data.lastName or 'Smith' }} has accepted your invite {% endblock %} {% block content %}
{{ data.firstName or 'Bob' }} has been added to your NHS login as your {{data.relationship or 'carer'}} and can enter {{ data.service or 'stepWell' }} on your behalf.
You can control what {{ data.firstName or 'Bob' }} can see and do on your behalf by contacting {{ data.service or 'stepWell' }}.
You can cancel and remove {{ data.firstName or 'Bob' }}’s access to {{ data.service or 'stepWell' }}, or remove them from your NHS login completely, by visiting your NHS login account management area.


trace_airmass_source: trajectory analysis tool¶
Airmass transport simulations are combined with a land cover classification for a temporally and vertically resolved airmass source attribution. The air parcel locations can be taken form HYSPLIT ensemble trajectories (Stein et al., 2015) or particle positions from FLEXPART (PISSO et al., 2019).
Whenever a airparcel is below a defined reception height, the land cover is categorized using custom defined polygons encompassing areas of interest or a simplified version (number of categories reduced to 7) of the MODIS land cover classification (Friedl et al., 2002, Broxton et al., 2014). An airparcel is assumed to be influenced by the land surface if the trajectory is below the reception. The residence time for each category is then the total time an airparcel fulfilled this criterion by land cover category. This calculation is repeated in steps of 3h in time and 500m in height to provide a continuous estimate on the airmass source and as a first hint on potential aerosol load. From the results a time-height plot of airmass source can be generated for a certain location, which is comparable to active remote sensing time-height plots.
Comprehensive documentation is available at trace-doc and in ACP Discussion paper
Examples¶
Installation¶
trace_airmass_source is written in python3 and requires an extensive of additional packages. There are two options to acquire these packages.
local python installataion¶
Install all the packages listed in requirements.txt
docker container¶
Deployment may be simplified using a docker image which includes all the dependencies.
When using docker under windows, the pwd
has to be replaced by the path to the local trace directory.
Quick-Setup¶
Please put your credentials (name, institution, contact) in the output_meta.toml
file.
If FLEXPART shall be used with GFS grib data, the login credential for the GFS data from rda.ucar.edu
has to be stored in server_logins.toml
.
[flexpart]
login = ''
password = ''
Each station requires a config file. An example for Limassol is provided config_limassol.toml
.
A subfolder named after the respective station should exisit the folders trajectories
, flexpart_partposit
and output
.
Usage¶
Running trace consists of several steps, that are (partly) automated in the autorun.sh
script.
Preparing the transport simulations¶
As input for an airmass source estimate, either HYSPLIT backward trajectories or FLEXPART particle positions are required. Simulations with FLEXPART can be done within the docker container. The HYSPLIT backward trajectories have to be calculated separately.
HYSPLIT¶
HYSPLIT backward trajectories are required, a 10-day 27-member ensemble setup is recommended. Please note that HYSPLIT itself is not provided within this package (The binary to run is hyts_ens
with the respective CONTROL
file).
Meteorological input data for HYSPLIT are taken from the GDAS1 dataset (https://www.ready.noaa.gov/gdas1.php) provided by the Air Resources Laboratory (ARL) of the U.S. National Weather Service’s National Centers for Environmental Prediction (NCEP).
An trajectory is calculated every 3h in steps of 500m. Conveniently the input trajectories are placed in the trajectories
directory.
A list of required trajectories can be generated with:
python3 gen_hysplit_input.py --station STATIONNAME
The filename of each trajectory should be
hysplit_trajectory-[YYYYMMDD-HH]-[lat]-[lon]-[height]-[length].tdump
See the documenation for more information on configuring the HYSPLIT simulations. After the HYSPLIT output is on hand, it can be checked if all required files are available:
python3 test_data_avail.py --station [stationname] --daterange [YYYYMMDD_begin-YYYYMMDD_end]
FLEXPART¶
Download the GFS grib files (using the credentials defined in server_logins.toml
)
python3 download_gfs.py --daterange YYYYMMDD-YYYYMMDD
Start the FLEXPART run
python3 run_flexpart_trace.py --station STATIONNAME --date YYYYMMDD
Optionally, plot and animate the particle positions
python3 animate_flex.py --station STATIONNAME --datetime YYYYMMDD-HH --levels I,J --dynamics true|false
Running the airmass source estimate¶
The actual processing is started with:
python3 run_assemble.py --model FLEX¦HYSPLIT --station STATIONNAME --daterange YYYYMMDD-YYYYMMDD
From the netcdf files in the output
directory the plots are generated by:
python3 plot2d.py --model FLEX|HYSPLIT --station STATIONNAME --daterange YYYYMMDD-YYYYMMDD
Afterwards the files with the raw trajectires (currently only HYSPLIT) can be compressed to day-wise zip files:
python3 compress_data.py --station STATIONNAME --daterange YYYYMMDD-YYYYMMDD
Surface classification¶
Currently two sources for the surface classification are available. The raster-based MODIS land cover classification and the polygon-based geography names.
MODIS land cover¶
The MODIS land cover classification (Friedl et al., 2002, Broxton et al., 2014) with its 17 categories and 0.5km resolution is simplified to 7 categories (barren, snow, urban, grass, savanna/shrublands, forrest, water) and regridded to a 0.1º (~11km).
“named geography”¶
The extend and the name of a geography feature - usually a (sub-)continent - is defend within a .kml
file. Examples for are available in the data
directory for Europe and the shorelines of the Atlantic Ocean.
config files¶
Trace can by adjusted by two types of config files. One for the site or campaign named config_[site_name].toml
. Examples are given for the site of Limassol and the Polarstern cruise PS113.
The second one - geonames_config.toml
- is used to wire togehter the named geographies.
Used in¶
Haarig, M., Ansmann, A., Gasteiger, J., Kandler, K., Althausen, D., Baars, H., Radenz, M., and Farrell, D. A.: Dry versus wet marine particle optical properties: RH dependence of depolarization ratio, backscatter, and extinction from multiwavelength lidar measurements during SALTRACE, Atmos. Chem. Phys., 17, 14199-14217, https://doi.org/10.5194/acp-17-14199-2017, 2017.
Foth, A., Kanitz, T., Engelmann, R., Baars, H., Radenz, M., Seifert, P., Barja, B., Fromm, M., Kalesse, H., and Ansmann, A.: Vertical aerosol distribution in the southern hemispheric midlatitudes as observed with lidar in Punta Arenas, Chile (53.2° S and 70.9° W), during ALPACA, Atmos. Chem. Phys., 19, 6217–6233, https://doi.org/10.5194/acp-19-6217-2019, 2019.
References¶
Stein, A.F., R.R. Draxler, G.D. Rolph, B.J. Stunder, M.D. Cohen, and F. Ngan: NOAA’s HYSPLIT Atmospheric Transport and Dispersion Modeling System. Bull. Amer. Meteor. Soc., 96, 2059–2077, https://doi.org/10.1175/BAMS-D-14-00110.1, 2015
Friedl, M. A., McIver, D. K., Hodges, J. C., Zhang, X. Y., Muchoney, D., Strahler, A. H., Woodcock, C.E., Gopal, S., Schneider, A., Cooper, A., Baccini, A., Gao, F., Schaaf, C.: Global land cover mapping from MODIS: algorithms and early results. Remote Sens. Environ., 83(1-2), 287-302, https://doi.org/10.1016/S0034-4257(02)00078-0, 2002
Broxton, P.D., Zeng, X., Sulla-Menashe, D., Troch, P.A.: A Global Land Cover Climatology Using MODIS Data. J. Appl. Meteor. Climatol., 53, 1593-1605. http://dx.doi.org/10.1175/JAMC-D-13-0270.1, 2014
Radenz, M., Seifert, P., Baars, H., Floutsi, A. A., Yin, Z., and Bühl, J.: Automated time-height-resolved airmass source attribution for profiling remote sensing applications, Atmos. Chem. Phys. Discuss. [preprint], https://doi.org/10.5194/acp-2020-955, in review, 2020.
License¶
See the LICENSE file for more information Copyright 2020, Martin Radenz MIT License


Help
News
Topics
Contact
Home
Contact Us Now
Enter You Name :
Enter Your Email :
Send
Contact Us
Address: Kigali,Kacyiru Kimironko Road
phone:0726281137
<EMAIL_ADDRESS>Quick links
Home
Contact us
News
REMA
Help
Main Topics
Meaning of Green Rwanda
Causes of climatic Change in Rwanda
Effect Of Climatic Change in Rwanda
Ways of Making Our Rwanda Green
Importance of Making Rwanda Green
©DOne by Muhodari Sage


--- layout: post title: Why operators love SMS date: 2004-01-05 00:00:00 category: mobile ---
Tom Coady just sent me a link to this article, which sums up why operators love SMS in one simple table on page 4:


Match Play. Red trails 2-4 to 5 (post-Crawford). How should Red play 44?
pips Red=139 White=133
(CorrectAnswer= 0/0, ErrorScore= 0)
The first obvious play to look at is 22/14(2) but the race is relatively close and an ace from White could even things up.
Red needs to take advantage of the two blots in White’s home board. The point he really wants to make is his 9-pt and so he should slot it with 13/9. After that either 22/10 or 22/18(2), 11/7 are both OK.
These two plays win slightly fewer games than 22/14(2) but they more than make up for that with many more gammon wins. 22/18, 22/14, 13/9 is also OK. The key is that you must slot the 9-pt in this position.
Remember to look at all four quadrants when deciding upon your game plan and then your candidate moves.
Red needs to take advantage of the two blots in White’s home board. The point he really wants to make is his 9-pt and so he should slot it with 13/9. After that either 22/10 or 22/18(2), 11/7 are both OK.
These two plays win slightly fewer games than 22/14(2) but they more than make up for that with many more gammon wins. 22/18, 22/14, 13/9 is also OK. The key is that you must slot the 9-pt in this position.
Remember to look at all four quadrants when deciding upon your game plan and then your candidate moves.
1. Cubeful 2-ply 22/10 13/9 Eq.: +0.667 0.718 0.115 0.004 - 0.282 0.058 0.002 2. Cubeful 2-ply 22/18(2) 13/9 11/7 Eq.: +0.661 (-0.005) 0.723 0.108 0.003 - 0.277 0.046 0.001 3. Cubeful 2-ply 22/14(2) Eq.: +0.626 (-0.040) 0.749 0.064 0.001 - 0.251 0.028 0.000 4. Cubeful 2-ply 22/10 22/18 Eq.: +0.600 (-0.067) 0.725 0.075 0.002 - 0.275 0.042 0.001 5. Cubeful 2-ply 22/10 11/7 Eq.: +0.598 (-0.069) 0.686 0.113 0.004 - 0.314 0.069 0.002


Rules
- •   The registrants up to the age of 26 years are eligible for participation and prizes. A valid government photo-identification proof is required.
- •   You can apply as a team of 1-5 members.
- •   Once a team has submitted their idea, no new members can be added/removed from the team.
- •   Only one idea can be submitted per team. Multiple entries will be disqualified.
- •   Usage of English is mandatory during product pitching sessions.
- •   There are 3 themes of the TechNo-Fest, you must submit a idea that is pertaining to one of these themes.
- •   The participants should have a good Internet connection during the event.
- •   Ideas should be original and unique.
- •   We welcome attendees from all backgrounds, genders and geographies. This event is about increasing the overall amount of innovation, partnership, and engagement in the developer community.
Disqualifications
- •   TechNo-Fest organizers have the right at their sole discretion to determine whether an entrant is eligible for the Contest. They may disqualify TechNo-Fest entries (including, without limitation, content submitted in connection therewith) that (a) are in violation of third party rights or law or regulation, (b) use inappropriate or explicit language or images, or display content that TechNo-Fest or Sponsors otherwise find objectionable.
- •   Copyright violations, cheating, recklessness and endangering others, disrespectful behaviour, immoral acts, illegal acts etc. are strictly not allowed and will lead to immediate disqualification.


Spectrum Example
Spectrum demonstrates how the Qt Multimedia module can be used to analyze an audio stream while recording it, and also play the recorded stream.
Because Qt Multimedia allows the application to access the raw audio stream, the data can either be inspected or modified by the application. The Spectrum Analyzer example displays three pieces of information while audio is being either captured or played back:
- Information about the raw audio stream, shown in the uppermost widget:
- The amount of data currently in the buffer, shown in blue
- The segment of data which was most recently analysed to compute the frequency spectrum, shown in green
- The raw audio waveform, shown in white and scrolling from right to left
- A representation of the frequency spectrum, shown at the lower left
- The current RMS level of the audio stream, and the recent 'high watermark' level, shown at the lower right
Spectrum analysis is performed by calculating the Fast Fourier Transform (FFT) of a segment of audio data. An open-source library, FFTReal, against which the application is dynamically linked, is used to compute the transform.
Running the Example
To run the example from Qt Creator, open the Welcome mode and select the example from Examples. For more information, visit Building and Running an Example.
Files:
- multimedia/spectrum/3rdparty/fftreal/Array.h
- multimedia/spectrum/3rdparty/fftreal/DynArray.h
- multimedia/spectrum/3rdparty/fftreal/FFTReal.h
- multimedia/spectrum/3rdparty/fftreal/FFTRealFixLen.h
- multimedia/spectrum/3rdparty/fftreal/FFTRealFixLenParam.h
- multimedia/spectrum/3rdparty/fftreal/FFTRealPassDirect.h
- multimedia/spectrum/3rdparty/fftreal/FFTRealPassInverse.h
- multimedia/spectrum/3rdparty/fftreal/FFTRealSelect.h
- multimedia/spectrum/3rdparty/fftreal/FFTRealUseTrigo.h
- multimedia/spectrum/3rdparty/fftreal/OscSinCos.h
- multimedia/spectrum/3rdparty/fftreal/TestAccuracy.h
- multimedia/spectrum/3rdparty/fftreal/TestHelperFixLen.h
- multimedia/spectrum/3rdparty/fftreal/TestHelperNormal.h
- multimedia/spectrum/3rdparty/fftreal/TestSpeed.h
- multimedia/spectrum/3rdparty/fftreal/TestWhiteNoiseGen.h
- multimedia/spectrum/3rdparty/fftreal/def.h
- multimedia/spectrum/3rdparty/fftreal/fftreal_wrapper.cpp
- multimedia/spectrum/3rdparty/fftreal/fftreal_wrapper.h
- multimedia/spectrum/3rdparty/fftreal/test.cpp
- multimedia/spectrum/3rdparty/fftreal/test_fnc.h
- multimedia/spectrum/3rdparty/fftreal/test_settings.h
- multimedia/spectrum/3rdparty/fftreal/stopwatch/ClockCycleCounter.cpp
- multimedia/spectrum/3rdparty/fftreal/stopwatch/ClockCycleCounter.h
- multimedia/spectrum/3rdparty/fftreal/stopwatch/Int64.h
- multimedia/spectrum/3rdparty/fftreal/stopwatch/StopWatch.cpp
- multimedia/spectrum/3rdparty/fftreal/stopwatch/StopWatch.h
- multimedia/spectrum/3rdparty/fftreal/stopwatch/def.h
- multimedia/spectrum/3rdparty/fftreal/stopwatch/fnc.h
- multimedia/spectrum/app/engine.cpp
- multimedia/spectrum/app/engine.h
- multimedia/spectrum/app/frequencyspectrum.cpp
- multimedia/spectrum/app/frequencyspectrum.h
- multimedia/spectrum/app/levelmeter.cpp
- multimedia/spectrum/app/levelmeter.h
- multimedia/spectrum/app/mainwidget.cpp
- multimedia/spectrum/app/mainwidget.h
- multimedia/spectrum/app/progressbar.cpp
- multimedia/spectrum/app/progressbar.h
- multimedia/spectrum/app/settingsdialog.cpp
- multimedia/spectrum/app/settingsdialog.h
- multimedia/spectrum/app/spectrograph.cpp
- multimedia/spectrum/app/spectrograph.h
- multimedia/spectrum/app/spectrum.h
- multimedia/spectrum/app/spectrumanalyser.cpp
- multimedia/spectrum/app/spectrumanalyser.h
- multimedia/spectrum/app/tonegenerator.cpp
- multimedia/spectrum/app/tonegenerator.h
- multimedia/spectrum/app/tonegeneratordialog.cpp
- multimedia/spectrum/app/tonegeneratordialog.h
- multimedia/spectrum/app/utils.cpp
- multimedia/spectrum/app/utils.h
- multimedia/spectrum/app/waveform.cpp
- multimedia/spectrum/app/waveform.h
- multimedia/spectrum/app/wavfile.cpp
- multimedia/spectrum/app/wavfile.h
- multimedia/spectrum/app/main.cpp
- multimedia/spectrum/spectrum.pro
- multimedia/spectrum/3rdparty/fftreal/fftreal.pro
- multimedia/spectrum/app/app.pro
- multimedia/spectrum/app/spectrum.qrc


Try out our Premium Member services: Virtual Legal Assistant, Query Alert Service and an ad-free experience. Free for one month and pay only if you like it.
IN THE HIGH COURT OF JUDICATURE AT PATNA CRIMINAL MISCELLANEOUS No.39556 of 2019 Arising Out of PS. Case No.-6 Year-2019 Thana- BARUN District- Aurangabad ====================================================== 1. VINOD SINGH @ VINOD KUMAR SINGH Son of Late Jagganath Singh Resident of Village-Suara, P.S.-Dehri, District-Rohtas. 2. Ram Lakhan Saw S/o Gaura Saw Resident of Dehri, P.S.-Dehri, District- Rotas. ... ... Petitioner/s Versus 1. The State of Bihar 2. The Principal Secretary, Mines Dept. Government of Bihar, Patna. ... ... Opposite Party/s ====================================================== Appearance : For the Petitioner/s : Mr.Uma Shankar Singh For the Opposite Party/s : Mr. Satya Nand Shukla, APP Mr. Naresh Dikshit, P.P. Ms. Kalpana. ====================================================== CORAM: HONOURABLE MR. JUSTICE ANIL KUMAR SINHA ORAL ORDER
3 28-06-2019 Heard learned counsel for the parties.
The petitioners apprehend their arrest in connection with Barun P.S.Case No. 6 of 2019 registered under Sections 379, 411 and 420/34 of the Indian Penal Code, 4 and 40 of the Bihar Minor Mineral Concession Rules and 15 of the Pollution Control Act.
Allegation, as per the FIR, is that the Mining Officer, on getting secret information, raided that place and found that sand was being loaded on a truck bearing No. UP 65BT 2171. On inspection, 200 CFT sand was found loaded on that truck. It is alleged that said truck belongs to petitioner no. 1 and petitioner no. 2 is driver.
Submission of learned counsel for the petitioners is that Patna High Court CR. MISC. No.39556 of 2019(3) dt.28-06-2019 2/2 petitioners have valid licence for loading 500 CFT of sand and accordingly under that licence, 200 CFT of sand was being loaded for the purpose of transportation.
After having heard learned counsel for the petitioner and learned counsel for the State as well as learned counsel appearing on behalf of the Mining Department and from perusal of the materials available on record, it appears that petitioners have valid licence for transporting sand as such I am inclined to grant privilege of anticipatory bail to petitioners.
Accordingly, let the petitioners, abovenamed, in the event of arrest or surrender before the court below within a period of four weeks from the date of receipt of a copy of this order, be released on bail upon furnishing bail bond of Rs. 10,000/- each with two sureties of the like amount each to the satisfaction of the learned CJM, Aurangabad in connection with Barun P.S. Case No. 06 of 2019; subject to condition as laid down under Section 438(2) of the Code of Criminal Procedure.
(Anil Kumar Sinha, J) sujit/-
U T


Choose A Specific Job Type Below
Construction
Warehouse
Health
Driving
Office
Government
Cashier
Restaurant
Support


Instructions
This visualization framework aims to address current bottlenecks in the analysis of large sequence datasets (rRNA amplicons, metagenomes), helping researchers analyze high-throughput datasets more efficiently. Phich takes advantage of standard outputs from computational pipelines in order to bridge the gap between biological software (e.g. QIIME) and existing data visualization capabilities (harnessing the scalability of WebGL and HTML5 in a browser-based tool).
Phinch currently supports downstream analyses of .biom files ( Biological Observation Matrix, a JSON-formatted file type typically used to represent marker gene OTUs or metagenomic data). All sample metadata and taxonomy/ontology information MUST be embedded in the .biom file before being uploaded into Phinch.
In QIIME (version 1.7 or later), users can prepare the .biom file by executing the following commands:
First, construct an OTU table:
make_otu_table.py -i final_otu_map_mc2.txt -o otu_table_mc2_w_tax.biom -t rep_set_tax_assignments.txt
Where your input file (-i) is your OTU Map (defining clusters of raw sequences reads), and taxonomy file (-t) contains the taxonomy or gene ontology strings that correspond to each OTU.
Second, add your sample metadata to your .biom file. In QIIME version 1.8 this can be done using the following command:
biom add-metadata -i otu_table_mc2_w_tax.biom -o otu_table_mc2_w_tax_and_metadata.biom -m sample_metadata_mapping_file.txt
In QIIME version 1.7 or below, you can add metadata with the following command:
add_metadata.py -i otu_table_mc2_w_tax.biom -o otu_table_mc2_w_tax_and_metadata.biom -m sample_metadata_mapping_file.txt
Where your input file (-i) is your .biom file from the previous step, and your mapping file (-m) is a tab-delimited file containing sample metadata (formatted according to these QIIME instructions).
After these two steps, you're ready to upload.
If you want to visualize biological data currently formatted as a tab-delimited text file (e.g. the style of OTU tables produced by older versions of QIIME, the style of OTU tables produced by older versions of QIIME, or any other type of genomic data that can be reprsented in matrix format), please refer to this documentation for conversion instructions. Phinch supports both "sparse" and "dense" BIOM formats (although sparse .biom files are highly recommended, since the file size is much smaller).
Some important notes on metadata
In order to be properly detected, all date/time metadata must be standardized according to MIxS standardized format (more information at the Genomic Standards Consortium wiki), and entered into one column in your original sample metadata mapping file, as follows:
[YYYY]-[MM]-[DD]T[hh]:[mm]:[ss]-[Z]
This date format lists the year, month, and day, followed by a 24hr timestamp with a UTC offset (Z). Inclusion of timestamp and UTC offset are both optional; metadata columns can include date only. For example, metadata for a sample collected at 2:30pm EST on May 4, 2007 would be entered as: 2007-04-05T14:30:00-05:00
Similarly, any geographic coordinates or GPS data must be entered as decimal degrees (the format used by GoogleMaps, e.g. -90.017926). We recommend using separate columns labeled “Latitude” and “Longitude” in your original sample metadata mapping file, to ensure that GPS metadata is correctly detected.
To label your samples in Phinch and export graphics with human-readable IDs, include a column in your metadata mapping file with the header labelled as “phinchID” (these entries can be the same or different as the first SampleID column). The phinchID values will be pulled through into the visualizations to populate graph axes. If this column is not included, an arbitrary numerical ID will be assigned to each sample.
Chrome Browser Recommended! Your browser does not support the Phinch framework!
Please cite the Phinch framework as follows: Phinch: An interactive, exploratory data visualization framework for –Omic datasets Holly M Bik, Pitch Interactive. bioRxiv 009944; https://doi.org/10.1101/009944
Phinch is an open-source framework for visualizing biological data, funded by a grant from the Alfred P. Sloan foundation. This project represents an interdisciplinary collaboration between Pitch Interactive, a data visualization studio in Oakland, CA, and biological researchers at UC Davis. Whether it's genes, proteins, or microbial species, Phinch provides an interactive visualization tool that allows users to explore and manipulate large biological datasets. Computer algorithms face significant difficulty in identifying simple data patterns; writing algorithms to tease out complex, subtle relationships (the type that exist in biological systems) is almost impossible. However, the human eye is adept at spotting visual patterns, able to quickly notice trends and outliers. It is this philosophy especially when presented with intuitive, well-designed software tools and user interfaces. The sheer volume of data produced from high-throughput sequencing technologies will require fundamentally different approaches and new paradigms for effective data analysis. Scientific visualization represents an innovative method towards tackling the current bottleneck in bioinformatics; in addition to giving researchers a unique approach for exploring large datasets, it stands to empower biologists with the ability to conduct powerful analyses without requiring a deep level of computational knowledge.


Ride details
Trip to Yankari Games Reserve Bauchi state, Nigeria
...let's get you closer to nature
| Destination | Bauchi state, Nigeria |
|---|---|
| Departure terminal | Iyana-Ipaja, Lagos state |
| Date of ride | 27-07-2018 |
| Travel info | Just something to fill up this space (bvhjncunccfyevbevbuw cubevvqdbv cnec9ubevcj nvc bjkascbhcjeiujevbvhjce) |


This page demonstrates how to set up a Select Form Validation widget that works with Spry Data.
As with all widgets that use Spry Data, the data refreshing wipes out the widget functionality. Therefore, after the data updates in the region, the widget constructor needs to be rerun. There are 2 ways to do that.
One is to include the widget constructor script is put INSIDE the spry:region. Spry recognizes scripts within regions and automatically runs them after the data is loaded.
The other way it to set an observer on the region and run the constructor onPostLoad.
Observer Version
This form uses an observer to recreate the widget.


RESTful API
GET:
Lesson ID
Get Lessons
POST:
Lesson Title
Lesson Author
Post Lesson
DELETE:
Lesson ID:
Delete Lesson
UPDATE:
Lesson ID to update:
Lesson Title:
Lesson Author
PATCH
Lessons:


You wish to start learning basics of SQL
RDBMS Concepts and types
Structure of a Table
Entity Relationship Diagram (ERD)
Index
Database Normalization
Denormalization
Primary Key And Foreign Key
Read through pages 4-10 in this material
Latentview internal content
Select Statement
Where
Like
Creating Tables
Inserting Into A Table
Update Statement
Delete/Truncate
Unions, Intersections, Exceptions
Refer W3schools - SQL Tutorial Sections for the listed topics
Complete stage 0 to 5 on SQLZOO to complete this step
SQLZOO
Complete Database management essentials to understand how RDMS works. This course is part of a 5-week specialization.
Practice Database management essentials to understand how RDMS works.
Coursera
You have successfully completed all the beginner level courses.
You wish to start learning basics of Python
Variables Expressions and Statements
Read through this material
Openbookproject
Global Variables and Local Variables
Refer Stack Overflow for the listed topics
Korylprince
Refer the following LINK to complete this step
Loyola University Chicago - Andrew Harrington
Refer the LINK to understand Conditionals.
Refer LINK to understand how Loops works.
Refer LINK to understand how Tuples works.
Refer LINK to understand how Lists works.
Refer LINK to understand how Sets works.
Dotnetpearls
Refer LINK to understand how Dictionaries works.
Refer LINK to complete section.
Trey Hunner
You wish to start learning basics of Tableau
Connecting to data sources - Excel, Teradata and SQL
Understanding the data - Dimensions and Measures
Rows and Columns
Data types - Date, String and Number
Creating cross-tab of data
Refer this material to complete the step
Tableau
Refer Link to complete this step
Creating a basic trend chart Using Colors, Size, Label, Tooltip and Pages
Understanding the chart types - 'Show me' button
Creating different types of basic charts like bar, Line, Pie and Area
Sorting
Filters
Formatting of measures
Refer Link to complete this step.
Latentview Internal Content
Creating a calculated field
Logical functions
Case-if functions
ZN function
Else-if function
Ad-Hoc Calculations
Manipulating text-left and right functions
Creating dashboard with multiple worksheet
Dashboard Layouts - Floating and Tiled
Publishing the dashboard in a tableau server
You wish to start learning basics of Visualization
Create speaker notes
Design motion paths
Working with watermarks
Create a flow chart
Create an org chart
Create a template from a presentation
Read through this link Essentials of PowerPoint
Webinar- Creating a Culture of Data Visualization
Refer this Webinar for improvised approach to visualization
You will learn- how to turn complex data sets into beautiful, simple diagrams that tease out unseen patterns and connections Click here for more
TED
Complete Aggregated tutorials and articles from different sources to ace PPT
Skilledup
You wish to start learning basics of Excel
Getting Started with Excel
Creating and Opening Worksheets
Saving and sharing worksheets
Cell Basics
Numbers Formats
Creating your first Worksheets
Entering and Editing worsheet data
Working with cells and ranges
Refer ExcelPro Bible for the listed topics
You will learn- Creating and formatting Worksheets,Cells and Ranges,Numbers and functions Click here for more
chandoo.org
Complete Udemy Excel Training Course to complete this step
Udemy
You wish to learn advanced concepts
Data types
Number Functions
String Functions
Date Functions
Using Logical Operators
Case When Statements
SQL Aggregate Functions
The Having Clause
The Order By Clause
Statistical Functions
Read through pages 18-41 in this SQL Manual-FundamentalsTraining
Inner Join
Left Join
Right Join
Full Join
Cross Join
Aliases
Self Join
Refer W3schools - SQL Tutorial Sections for the listed topics Sections: SQL Aliases, SQL joins, SQL Inner join, SQL left join, SQL right join, SQL full join
W3schools
Correlated Sub Queries
Exists Operator
Nested Sub Queries
Analytical Functions
Set Operators
Hierarchical Queries
Regular Expressions
Read through pages 48-70 in this SQL Manual-FundamentalsTraining
Internal
Complete stage 6 to 10 on SQLZOO to complete this step
Stanford Course: DB5 SQL Self paced, free course
Stanford University
File Handling
Refer this Link
Python for beginners
Regular expressions
Refer Link for the listed topics
Google Develeopers
Exception Handling
Refer this Material
Doug Hellman
Refer Link to complete the step
Bogotobogo
Python wiki
Using parameter as a filter in the sheet
Using parameter to display multiple metrics in same sheet
Groups and hierarchy in dimensions
Dual Axis for Multiple Measures
Measure Values in Axis
Anne Stevens
Stories in Tableau
Actions to control dashboards
replacing a data source
Bookmarks
Google Book
Animation
Animation Speed
Smart Arts
Adding Images and Videos
More on Shapes
Text Formatting
Everything you need to make professional Powerpoint Presentations. From Creating slides to complex animations and transitions.Read through the link to know more PowerPoint Training
Skillshare
More on Presentations, text, images,Design, audio, video, Animation, tables, and sharing
Refer PowerPoint training for the listed topics
Microsoft Office Support
Article on attracting people using effective business storytelling
Complete the tasks here Art of storytellingto advance to next section
HBR
You have successfully completed all the intermediate level courses.
Modifying Columns and cells
Checking Spellings
Page Layout and printing
Read through the link to know more Excel Manual-Fundamental Training
Find and replace
Working with multiple sheets
Filtering and sorting data
Refer TutorialsPoint for the listed topics
TutorialsPoint
Practice Excercises
Complete the tasks here to advance to next section Free Excel Test
Introductions to formulas and functions
Creating complex formula
Relative and absolute cell reference
Freezing panes and view Options
Charts and graphs
Conditional Formatting
Complete this coursera course Analysis using Excel to advance to next section
You wish to learn intense querying concepts
Stored procedures
User Defined Functions
Triggers
Macros in SQL
Pivoting
Utilities
SQL Hosting
Transactions
Refer Udacity Intro to Relational Databases Self paced, free course
Udacity
Coursera: Relational Database Support for Data Warehouses This course is part of Specialization, $ 49 USD p.m for the entire specialization Also available for free
Learn SQL the Hard Way Cost: $19.99 Course : Ebook
Learn SQL the Hard Way
Joe Celko's SQL Puzzles and Answers Cost: $16.67 on Kindle, $31.43 for Paperback .
Amazon
You have successfully completed all the Advanced level courses.
Object oriented Programming
Jeff Knupp
Searching and Sorting
python-course.eu
Refer the LINK complete the step.
Scipy
Refer LINK to complete the step.
Pandas Tutorials
Pythonprogramming.net
Kevin Markham
Christine Doig
Refer LINK to completet the step.
Dataquest.io
Selenium-Python docs
Scrapy docs
Waterfall charts
Funnel Charts
Bump charts
Donut Charts
Creating Bubble Charts
Scatter plots
Box plots
Read through the Tableau Charts to know more
Tutorialspoint
Using Maps
Custom Geocoding
Refer Video-Mapping and Custom Geocoding to complete this step
Forecasting time series data in Tableau
Click here to know more on Video-Visual Analytics
Forecasting in Tableau Quiz
Click here to take the Quiz
Blending two different data sources in a single chart
Click here to know more on data binding
Quiz on Blending and Joins
Adding images
Using images as links
Different ways of using images in Tableau
Click Using Images in Tableau to know more
The Information Lab
Recap of concepts
Presenting the story of the data, using PowerPoint. You'll learn how to structure a presentation, to include insights and supporting data
Read through the Coursera-Powerpoint presentation to know more
Micrsoft Videos and tutorials
Refer PowerPoint 2013 videos and tutorials to advance to next step
Microsoft Excel
In this talk, presentation expert Nancy Duarte shares practical lessons on how to make a powerful call-to-action.
Click here to know more on powerful calls to action presented by TED Talks
Webinar on how making a persuasive online presentation demands much more than a set of static rules for creating visualizations
Click here for a webinar on how making a persuasive online presentation demands much more than a set of static rules for creating visualizations
Pivot Table
VBA
Data Analysis
Data from other resource
Read through the link to know more Analyzing and Visualizing Data with Excel
Edx
What if Analysis
Using advanced graphs and presentation techniques to maximise impact
Refer Advanced Excel to demystify some of the most complex business relevant areas of Microsoft Excel.
wiziq


Hey, I am the headless html!
Some paragraphs
Some of the parts of my head are in my body! What, again?!


Fresh Perspective Blog Archive
Posted May 21, 2018
When Worlds Collide
This isn't my first blog. But it's my first as a nascent developer. Can I successfully balance my writer and developer sides? And more importantly, will anyone bother to look at either?
Dipping my toe in the blogging pool
I started blogging in 2009 on the Blogger platform. I don't know whether anyone even uses it anymore, but my blog is still up there. For some reason, my post about a dying mosquito resonated with a lot of people, so I'll link to it here once more for old time's sake.
While I started this blog intending to talk about social media, you can tell by the mosquito post I strayed from my original mission — so much so that the original titled morphed to Miscellaneous Online Musings. I didn't think I had anything unique to say, and I was already more interested in how digital content worked as opposed to its substance. Foreshadowing indeed.
Posting with a purpose
Fast forward a few years to 2013. I became my Grandmother's caregiver in 2005 when my dear Grandfather passed away, and we lived together in relative harmony for eight years. In 2012 she started showing signs of dementia, and even though her doctor never actually diagnosed her with the disease, it slowly took her memory.
By 2013 I was working at home because I worried about Granny wandering off with her Kleenex ear flaps (she said they protected her ears) and her elastic-less pants (if they weren't sagging, they were too tight). I read everything I could about caring for a loved one with dementia, but everything I found was either unhelpful, woefully outdated or titled something like Signs Your Loved One Needs Assisted Living. In my frustration I started blogging, and Grandma Drives Me Crazy was born.
Writing this blog was an amazing experience. It was somewhere to vent. Someplace to educate. And a wonderful laboratory for building an audience through organic content optimization. I built a small following — mostly comprising other caregivers who welcomed some honest conversations about helping someone who's living with dementia. It takes more than checklists and platitudes to maintain your sanity when you're balancing raising children, working and taking care of someone who forgets something new every day. In a very real sense, blogging helped me help her.
Merging passions through words
One thing my second blog reinforced for me was the importance of maintaining a consistent theme. It's easy to attract readers with a singular subject, and I plan to adhere to that with blog number three. I've thought many times as I struggle with learning a new development technology or celebrate the occasional epiphany that it would be great to have a place to share my thoughts and get feedback from others on their own coding journey. And now I do.
Unlike my previous blogs, this one isn't hosted on an existing platform or created through a CMS. So functionality is up to me lol. I hope to work with a mentor at Kansas City Women in Technology (KCWiT) to merge my development and content portfolios along with this blog into one all-encompassing showcase of my content and development work. I don't know where my skills will lead me career-wise, but I'll be back here often to log my thoughts along the way.


addEventListener("load", function() { setTimeout(hideURLbar, 0); }, false); function hideURLbar(){ window.scrollTo(0,1); }
Our school motto is " Forward Ever Backward Never":", the capacity that we normally admit especially in Form1 is 200 students annually.
Our school admission policy is to admit a student with minimum 300 marks scored in KCPE, Our rules and regulations policies are friendly and easy to adhere to,The environment is conducive for learning
Our school motto is " Forward Ever Backward Never":", the capacity that we normally admit especially in Form1 is 200 students annually.
Our school admission policy is to admit a student with minimum 300 marks scored in KCPE, Our rules and regulations policies are friendly and easy to adhere to,The environment is conducive for learning
school principal since 2012.
school deputy principal
sciences are chem, bio, phy,.
heads the sporting department in the school.


PLEASE CHOOSE A DIFFERENT OBJECT, THIS ONE
IS NOT QUITE READY YET :)
STORY
origins
About
Origins
Objects
Living Rooms


I read some calamus experiences and was taken in by stories of seeing feries and easter island statues, and I passed off all the sickly trip reports as people with weak stomachs.
So just to be safe I started off with only 2 1/2 grams. I capsulised the root powder into five size 00 capsules (this comes out to be almost exactly 1/2 a gram per capsule).
I swallowed all 5 capsules on a somewhat empty stomach and waited for awhile. About half an hour later I notice that I feel weak, a bit shaky and slightly strange, nothing fun at all. So I told myself that I'll try a larger dose tomorrow. A couple hours later I went and ate chinese food. I came home feeling absolutely horrible. I wasn't just nausious, I felt shaky and weak and even had a slight headache all at the same time. It was absolutely horrible. Normally, I don't mind blowing my groceries when i'm on something, cause I usualy feel so much better after I puke. But this wasn't like that at all, I didn't feel any desired effects, it's like I had just taken some pills that gave me the stomach flu. I threw up all the chinese food that I had just barely eaten. Which was absolutely horrible cause it was all chunks, and I hadn't drunk much liquid with it so I thought somthing was going to get stuck in my thoat and I was going to choke.
 Then I started feeling horrible again, so I would have to go right back to the bathroom and puke up all the water I had just drunk. I would do that again and again throughout the whole night, until eventually I was puking yellowish-green bile.  I puked a total of 23 times that night! It was making me cold too cause I would drink cold water, and it would cool off my stomach, then before my stomach could warm the water up, I would puke up the cold water and drink more cold water.
I still have a respect for this plant, but it is definately somthing that I will NEVER try again, it was absolute misery.
Peace
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


{% extends "base.html" %} {% block title %}Reset your password{% endblock %} {% block content %}
Enter your e-mail address to obtain a new password.


HOME
TEAMS
GALLERY
CONTACT
APPLY
LOGIN
Apply
Home
Teams
Gallery
Contact
Apply
Login
MAKERS
Apply
Applications Closed for Fall 2017
Applications will open again in Spring 2018
Meanwhile, like our
Facebook page
to get the latest updates from Makers!


Mount Sion is a place where our children can develop and mature physically, emotionally, intellectually and spiritually in a safe and caring environment
Mount Sion, established by Blessed Edmund Rice in 1802, is a Catholic School for boys only and is committed to the Christian Ethic in education.


Welcome to our Virtual Campout
{{ site.description }}
To join our virtual campout, follow these simple steps:
First, put up a tent or pillowfort
Second, complete four of the suggested activities of your choice:
1. _________________________
2. _________________________
3. _________________________
4. _________________________
Finally, join your troop or service unit for a virtual dance party and s'mores!
(Check your email or ask your troop leader for a video conference link.)


A basic search consists of three parts: The metadata category to search over, the operator to use, and the value to use in the search. For example, to retrieve all soil samples in the database, the query would be:
env_matter includes soil
Valid operators for searches are:
| Operator | Function |
| < | Less than (for integer and float values) |
| > | Greater than (for integer and float values) |
| <= | Less than or equal (for integer and float values) |
| >= | Greater than or equal (for integer and float values) |
| = | Equals (matches exact number or string) |
| != | Not equals (matches opposite of exact number or string) |
| includes | Partial string matching |
Complex queries can also be created by using AND, OR, and NOT operators. As an example, if we want all soil samples that are low or extremely high pH, we can use the following search:
env_matter includes soil AND (ph < 4 OR ph > 8)
You can search for multi-word phrases using quotes. For example, to search for any study with "chicken pox" in the title, the query would be:
study_title includes "chicken pox"
Note that you can not use wild cards in any string searches. Only alphanumeric characters and colons are supported.


PropertyPro-Lite
Signout
Post Ad
×
Post Ad
View all properties
Signout
Post a Property for Rent or Sale
Name of Property
State
Property Type
One Bedroom
2 Bedroom flat
3 Bedroom flat
4 Bedroom flat
Bungalow
Duplex
City
Address
Price in Naira
Upload Picture of Property


{% extends 'base.html'%} {% import 'macros.html' as macro%} {% block content %}
Thoughts on "{{blog.title}}" by {{blog.user.username}}
{{blog.message}}


Enzo Documentation
|
|
Enzo User Guide
This is the most up-to-date version of the Enzo user guide, and has instructions on how to compile
the code, run the initial conditions generator, and has a list of Enzo parameters and other useful things.
|
|
Enzo Tutorial & Cookbook
The Enzo tutorial has information on the algorithms used in the Enzo code and general information on how
to generate initial conditions and put together parameter files for Enzo simulations. The Cookbook has
more specific information on tips and tricks for running Enzo on various platforms and for doing data
analysis and visualization, and also a list of step-by-step instructions for compiling Enzo and executing a
test problem.
|
|
Code Developer's Guide
The Enzo developer's guide has information useful to those who are interested in making changes, both
major and minor, to the Enzo source code.
|
|
Change Log
This log keeps track of web page changes. Code changes are recorded in the Enzo code bundle.
|
|
Notes
A Developer Guide is currently in the works. If you have questions or comments about that,
or any other aspect of the Enzo documentation, please email
the Enzo development group.
|


Example of an LvS activity
First, read the instructions on the first tab at right upper corner of the screen.
e.g. Click on the word "here" to start this LvS subtitling activity.
Read and follow the suggestions
e.g. Click on the button "Play" to watch the clip.


| [1] |
Pascal Cotret, Muhammad Abdul Wahab.
TrustZone is not enough – Hijacking debug components for embedded security
In 34th Chaos Communication Congress (CCC 2017), September.
[ Recorded Talk ]
Keywords: ARM Coresight components ; Information Flow Tracking ; DIFT ; Heterogeneous SoC
|
| [2] |
Muhammad Abdul Wahab, Pascal Cotret, Mounir Nasr Allah, Guillaume Hiet, Vianney
Lapotre, and Guy Gogniat.
ARMHEx: A hardware extenstion for DIFT on ARM-based SoCs.
In 27th International Conference on Field-Programmable Logic
and Applications (FPL 2017), September.
[ http |
.pdf ]
Keywords: ARM Coresight components ; Information Flow Tracking ; DIFT ; Heterogeneous SoC
|
| [3] |
Muhammad Abdul Wahab, Pascal Cotret, Mounir Nasr Allah, Guillaume Hiet, Vianney
Lapotre, and Guy Gogniat.
ARMHEx: A framework for efficient DIFT in real-world SoCs.
In 27th International Conference on Field-Programmable Logic
and Applications (FPL 2017), Demo Session, September.
[ http |
.pdf ]
Keywords: ARM Coresight components ; Information Flow Tracking ; DIFT ; Heterogeneous SoC
|
| [4] |
Muhammad Abdul Wahab and Pascal Cotret.
Pwning ARM Debug Components for Sec-Related Stuff.
In HITBSecConf CommSec track 2017 (Hack In The Box Security
Conference), 2017.
[ http ]
|
| [5] |
Muhammad Abdul Wahab, Pascal Cotret, Mounir Nasr Allah, Guillaume Hiet, Vianney
Lapotre, and Guy Gogniat.
Towards a hardware-assisted information flow tracking ecosystem for
ARM processors.
In 26th International Conference on Field-Programmable Logic
and Applications (FPL 2016), Lausanne, Switzerland, August 2016.
[ http |
.pdf ]
Keywords: ARM Coresight components ; Information Flow Tracking ; DIFT ; Heterogeneous SoC
|
| [6] |
Muhammad Abdul Wahab, Christophe Moy, and Pascal Cotret.
A hardware coprocessor for Zynq-based Dynamic Information Flow
Tracking.
In 14th International Workshop on Cryptographic architectures
embedded in logic devices (CryptArchi), La Grande Motte, France, June 2016.
[ http |
.pdf ]
|


The menu "Diagram" contains the following options::
copy,
save,
save under,
load from clipboard,
load from file,
plot with a printer,
plot into a HPGL-file,
plot into a DXF-file,
colour of the periphery,
colour of the diagram,
colour of the frame,
colour of the background,
printer.


ggplot()
sandwichdata frame
c("item 1", "item 2", "item 3")
data frames
read_csv()
ggplot()
function to make our first plotHere’s an example air monitoring project from start to finish.
Imagine we just received 3 years worth of ozone monitoring data to summarize. Fun! Below is an example workflow we might follow using R.
Let’s be creative and name our project: "2019_Ozone"
library(readr)
# Read a file from the web
air_data <- read_csv("https://itep-r.netlify.com/data/OZONE_samples_demo.csv")
| SITE | Date | OZONE | TEMP_F |
|---|---|---|---|
| 27-137-7554 | 2018-05-06 | 6 | 45.8 |
| 27-137-7001 | 2016-08-24 | 13 | 70.4 |
| 27-137-7001 | 2016-08-05 | 11 | 77.0 |
| 27-137-7554 | 2018-07-14 | 17 | 58.4 |
| 27-137-7554 | 2017-09-05 | 11 | 59.6 |
library(janitor)
# Capital letters and spaces make things more difficult
# Let's clean them out
air_data <- clean_names(air_data)
library(ggplot2)
ggplot(air_data, aes(x = temp_f, y = ozone)) +
geom_point(alpha = 0.2) +
geom_smooth(method = "lm")
library(dplyr)
# Drop values out of range
air_data <- air_data %>% filter(ozone > 0, temp_f < 199)
# Convert all samples to PPB
air_data <- air_data %>%
mutate(OZONE = ifelse(units == "PPM", ozone * 1000,
ozone))
ggplot(air_data, aes(x = temp_f, y = ozone)) +
geom_point(alpha = 0.2, size = 3) +
geom_smooth(method = "lm") +
facet_wrap(~site) +
labs(title = "Ozone increases with temperature",
subtitle = "Observations from 2015-2017")
air_data <- air_data %>%
group_by(site, year) %>%
summarize(avg_ozone = mean(ozone) %>% round(2),
avg_temp = mean(temp_f) %>% round(2))
| site | year | avg_ozone | avg_temp |
|---|---|---|---|
| 27-137-7001 | 2016 | 11.01 | 60.74 |
| 27-137-7001 | 2017 | 11.26 | 60.66 |
| 27-137-7001 | 2018 | 11.54 | 60.59 |
| 27-137-7554 | 2016 | 12.23 | 61.23 |
| 27-137-7554 | 2017 | 11.81 | 60.98 |
| 27-137-7554 | 2018 | 12.87 | 61.02 |
Save the final data table
air_data %>% write_csv("results/2015-17_ozone_summary.csv")
Save the site plot to PDF
ggsave("results/2015-2017 - Ozone vs Temp.pdf")
Having an exact record of what you did can be great documentation for yourself and others. It’s also handy when you want to repeat the same analysis on new data. Then you only need to copy the script, update the read data line, and push run to get a whole new set of fancy charts.
Let’s start fresh with a new R script.
OPEN a new R script
day2.R
will work wellLoad the readr
package from our library
library(readr)
Read the scrap data from the web
# Read in scrap data and set name to "scrap"
scrap <- read_csv("https://itep-r.netlify.com/data/starwars_scrap_jakku.csv")
Last time we made a column plot showing the amount of scrap coming from each origin city.
library(ggplot2)
ggplot(scrap, aes(y = amount, x = origin)) +
geom_col() +
labs(title = "Which origin sold the most scrap?")
Let’s break this down into its main ingredients and get to know ggplot()
.
ggplot()
sandwichggplot
has 3 ingredients.
library(ggplot2)
ggplot(scrap)
we load the package
library (ggplot2)
, but the function to make a plot isggplot(scrap)
.
The aesthetics assign the components from the data that you want to use in the chart. These also determine the dimensions of the plot.
ggplot(scrap, aes(x = origin, y = amount))
ggplot(scrap, aes(x = origin, y = amount)) + geom_col()
Now let’s change the fill color to match the origin.
ggplot(scrap, aes(x = origin, y = amount, fill = origin)) +
geom_col()
Try making a column plot showing the total amount of scrap for each destination
or for each item
.
ggplot(scrap, aes(x = destination, y = amount )) + geom_col()
It’s officially time to solve our “All” city issue.
The dplyr package is our go-to tool for exploring, re-arranging, and summarizing data. Use install.packages("dplyr")
to add dplyr to your library.
| Function | Information |
|---|---|
names(scrap) |
column names |
nrow(...) |
number of rows |
ncol(...) |
number of columns |
summary(...) |
summary of all column values (ex. max, mean, median) |
glimpse(...) |
column names + a glimpse of first values (requires dplyr package) |
glimpse()
the columnsUse the glimpse()
function to find out what type and how much data you have.
Use the summary()
function to get a quick report on your numeric data.
library(dplyr)
# View the first few values & the type of data each column contains
glimpse(scrap)
## Observations: 1,132
## Variables: 7
## $ receipt_date <chr> "4/1/2013", "4/2/2013", "4/3/2013", "4/4/2013"...
## $ item <chr> "Flight recorder", "Proximity sensor", "Vitus-...
## $ origin <chr> "Outskirts", "Outskirts", "Reestki", "Tuanul",...
## $ destination <chr> "Niima Outpost", "Raiders", "Raiders", "Raider...
## $ amount <dbl> 887, 7081, 4901, 707, 107, 32109, 862, 13944, ...
## $ units <chr> "Tons", "Tons", "Tons", "Tons", "Tons", "Tons"...
## $ price_per_pound <dbl> 590.93, 1229.03, 225.54, 145.27, 188.28, 1229....
# Use the summary function to get a quick of idea of means and maxima for your numeric data
summary(scrap)
## receipt_date item origin
## Length:1132 Length:1132 Length:1132
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## destination amount units
## Length:1132 Min. : 65 Length:1132
## Class :character 1st Qu.: 1544 Class :character
## Mode :character Median : 4099 Mode :character
## Mean : 18751
## 3rd Qu.: 7475
## Max. :2971601
## NA's :910
## price_per_pound
## Min. : 145.3
## 1st Qu.: 259.6
## Median : 790.7
## Mean : 3811.7
## 3rd Qu.: 1496.7
## Max. :579215.3
## NA's :910
# Try the rest on your own - be BRAVE!
nrow()
ncol()
names()
dplyr
dplyr
is our go-to package for most analysis tasks. With the six functions below you can accomplish just about anything you’d want to do with data.
Your new analysis toolbox
Function Job select()
Select individual columns to drop or keep arrange()
Sort a table top-to-bottom based on the values of a column filter()
Keep only a subset of rows depending on the values of a column mutate()
Add new columns or update existing columns summarize()
Calculate a single summary for an entire table group_by()
Sort data into groups based on the values of a column
A poggle of porgs has volunteered to help us demo the dplyr
functions.
select()
Use the select()
function to:
-column_name
library(dplyr)
library(readr)
scrap <- read_csv("https://itep-r.netlify.com/data/starwars_scrap_jakku.csv")
# Drop the destination column
select(scrap, -destination)
## # A tibble: 1,132 x 6
## receipt_date item origin amount units price_per_pound
## <chr> <chr> <chr> <dbl> <chr> <dbl>
## 1 4/1/2013 Flight recorder Outskir~ 887 Tons 591.
## 2 4/2/2013 Proximity sensor Outskir~ 7081 Tons 1229.
## 3 4/3/2013 Vitus-Series Attitud~ Reestki 4901 Tons 226.
## 4 4/4/2013 Aural sensor Tuanul 707 Tons 145.
## 5 4/5/2013 Electromagnetic disc~ Tuanul 107 Tons 188.
## 6 4/6/2013 Proximity sensor Tuanul 32109 Tons 1229.
## 7 4/7/2013 Hyperdrive motivator Tuanul 862 Tons 1485.
## 8 4/8/2013 Landing jet Reestki 13944 Tons 1497.
## 9 4/9/2013 Electromagnetic disc~ Cratert~ 7788 Tons 188.
## 10 4/10/2013 Sublight engine Outskir~ 10642 Tons 7211.
## # ... with 1,122 more rows
# Keep the item, amount and price_per_pound columns
select(scrap, c(item, amount, price_per_pound))
## # A tibble: 1,132 x 3
## item amount price_per_pound
## <chr> <dbl> <dbl>
## 1 Flight recorder 887 591.
## 2 Proximity sensor 7081 1229.
## 3 Vitus-Series Attitude Thrusters 4901 226.
## 4 Aural sensor 707 145.
## 5 Electromagnetic discharge filter 107 188.
## 6 Proximity sensor 32109 1229.
## 7 Hyperdrive motivator 862 1485.
## 8 Landing jet 13944 1497.
## 9 Electromagnetic discharge filter 7788 188.
## 10 Sublight engine 10642 7211.
## # ... with 1,122 more rows
everything()
select()
also works to change the order of columns. The code below puts the item
column first and then moves the units
and amount
columns directly after item
. We then keep everything()
else the same.
# Make the `item`, `units`, and `amount` columns the first three columns
# Leave `everything()` else in the same order
select(scrap, item, units, amount, everything())
## # A tibble: 1,132 x 7
## item units amount receipt_date origin destination price_per_pound
## <chr> <chr> <dbl> <chr> <chr> <chr> <dbl>
## 1 Flight re~ Tons 887 4/1/2013 Outski~ Niima Outp~ 591.
## 2 Proximity~ Tons 7081 4/2/2013 Outski~ Raiders 1229.
## 3 Vitus-Ser~ Tons 4901 4/3/2013 Reestki Raiders 226.
## 4 Aural sen~ Tons 707 4/4/2013 Tuanul Raiders 145.
## 5 Electroma~ Tons 107 4/5/2013 Tuanul Niima Outp~ 188.
## 6 Proximity~ Tons 32109 4/6/2013 Tuanul Trade cara~ 1229.
## 7 Hyperdriv~ Tons 862 4/7/2013 Tuanul Trade cara~ 1485.
## 8 Landing j~ Tons 13944 4/8/2013 Reestki Niima Outp~ 1497.
## 9 Electroma~ Tons 7788 4/9/2013 Crater~ Raiders 188.
## 10 Sublight ~ Tons 10642 4/10/2013 Outski~ Niima Outp~ 7211.
## # ... with 1,122 more rows
arrange()
Rey wants to know what the highest priced items are. Use arrange()
to find the highest priced scrap item and see which origins might have a lot of them.
# Arrange scrap items by price
scrap <- arrange(scrap, price_per_pound)
# View the top 6 rows
head(scrap)
## # A tibble: 6 x 7
## receipt_date item origin destination amount units price_per_pound
## <chr> <chr> <chr> <chr> <dbl> <chr> <dbl>
## 1 4/4/2013 Aural se~ Tuanul Raiders 707 Tons 145.
## 2 5/22/2013 Aural se~ Outskirts Niima Outp~ 3005 Tons 145.
## 3 5/23/2013 Aural se~ Tuanul Raiders 6204 Tons 145.
## 4 6/4/2013 Aural se~ Tuanul Raiders 3120 Tons 145.
## 5 6/10/2013 Aural se~ Blowback~ Niima Outp~ 2312 Tons 145.
## 6 6/20/2013 Aural se~ Outskirts Trade cara~ 6272 Tons 145.
145 credits
! That’s not very much at all, oh wait…desc()
To arrange a column in descending order with the biggest numbers on top, we use: desc(price_per_pound)
# Put most expensive items on top
scrap <- arrange(scrap, desc(price_per_pound))
# View the top 8 rows
head(scrap, 8)
## # A tibble: 8 x 7
## receipt_date item origin destination amount units price_per_pound
## <chr> <chr> <chr> <chr> <dbl> <chr> <dbl>
## 1 12/31/2016 Total All All 2.97e6 Tons 579215.
## 2 4/10/2013 Sublight~ Outskirts Niima Outp~ 1.06e4 Tons 7211.
## 3 4/14/2013 Sublight~ Outskirts Raiders 2.38e3 Tons 7211.
## 4 4/15/2013 Sublight~ Craterto~ Raiders 6.31e3 Tons 7211.
## 5 4/16/2013 Sublight~ Tuanul Trade cara~ 3.98e3 Tons 7211.
## 6 5/14/2013 Sublight~ Craterto~ Raiders 2.99e2 Tons 7211.
## 7 6/14/2013 Sublight~ Blowback~ Raiders 8.58e3 Tons 7211.
## 8 8/6/2013 Sublight~ Craterto~ Raiders 1.77e3 Tons 7211.
Try arranging by more than one column, such as price_per_pound
and amount
. What happens?
HINT: You can view the entire table by clicking on it in the upper-right Environment tab.
When you save an arranged data table it maintains its order. This is perfect for sending people a quick Top 10 list of pollutants or sites.
filter()
The filter()
function creates a subset of the data based on the value of one or more columns. Let’s take a look at the records with the origin "All"
.
filter(scrap, origin == "All")
## # A tibble: 1 x 7
## receipt_date item origin destination amount units price_per_pound
## <chr> <chr> <chr> <chr> <dbl> <chr> <dbl>
## 1 12/31/2016 Total All All 2971601 Tons 579215.
Use a ==
(double equals sign) for comparing values. A ==
makes the comparison “is it equal to?” and returns a True or False answer. So the code above returns all the rows where the condition origin == "All"
is TRUE.
A single equals sign =
is used within functions to set options, for example read_csv(file = "starwars_scrap_jakku.csv")
. Don’t worry too much. If you use the wrong symbol R is often helpful and will let you know which one is needed.
Processing data requires many types of filtering. You’ll want to know how to select observations in your table by making various comparisons.
Key comparison operators
| Symbol | Comparison |
|---|---|
> |
greater than |
>= |
greater than or equal to |
< |
less than |
<= |
less than or equal to |
== |
equal to |
!= |
NOT equal to |
%in% |
is value in a list: X %in% c(1,3,5) |
is.na(...) |
Is the value missing? |
Try comparing some things in the console and see if you get what you’d expect. R doesn’t always think like we do.
4 != 5
4 == 4
4 < 3
4 > c(1, 3, 5)
5 == c(1, 3, 5)
5 %in% c(1, 3, 5)
2 %in% c(1, 3, 5)
2 == NA
Let’s look at the data without that pesky All category. Look in the comparison table above to find the NOT
operator. We’re going to filter the data to keep only the origins that are NOT equal to
“All”.
scrap <- filter(scrap, origin != "All")
We can arrange the data in ascending order by item
to confirm that the “All” category is gone.
# Arrange data
scrap <- arrange(scrap, item)
head(scrap)
## # A tibble: 6 x 7
## receipt_date item origin destination amount units price_per_pound
## <chr> <chr> <chr> <chr> <dbl> <chr> <dbl>
## 1 4/4/2013 Aural se~ Tuanul Raiders 707 Tons 145.
## 2 5/22/2013 Aural se~ Outskirts Niima Outp~ 3005 Tons 145.
## 3 5/23/2013 Aural se~ Tuanul Raiders 6204 Tons 145.
## 4 6/4/2013 Aural se~ Tuanul Raiders 3120 Tons 145.
## 5 6/10/2013 Aural se~ Blowback~ Niima Outp~ 2312 Tons 145.
## 6 6/20/2013 Aural se~ Outskirts Trade cara~ 6272 Tons 145.
Now let’s take another look at that bar chart. Is there anything else that is less than perfect with our data?
library(ggplot2)
ggplot(scrap, aes(x = origin, y = amount)) + geom_col()
We can add multiple comparisons to filter()
to further restrict the data we pull from a larger data set. Only the records that pass the conditions of all the comparisons will be pulled into the new data frame.
The code below filters the data to only scrap records with an origin of Outskirts
AND a destination of Niima Outpost
.
outskirts_to_niima <- filter(scrap,
origin == "Outskirts",
destination == "Niima Outpost")
Are you the best Jedi detective out there? Let’s play a game and find out.
Guess what else comes with the dplyr
package? A Star Wars data set.
You can open the data set with the following steps:
dplyr
package from your library()
library(dplyr)
starwars_data <- starwars
sample_n(starwars_data, 1)
to choose your character at random.)filter()
function and narrow down the potential characters your neighbor may have picked.For example: Here’s a filter()
statement that filters the data to the character Plo Koon.
mr_koon <- filter(starwars_data,
mass < 100,
eye_color != "blue",
gender == "male",
homeworld == "Dorin",
birth_year > 20)
Elusive answers are allowed. For example, if someone asks: What is your character’s mass?
Sometimes a character will not have a specific attribute. We learned earlier how R stores nulls as NA
. If your character has a missing value for hair color, one of your filter statements could be is.na(hair_color)
.
WINNER!
The winner is the first to guess their neighbor’s character.
WINNERS Click here!
How about make it best of 3 games?
Let’s calculate some new columns to help focus Rey’s scavenging work.
mutate()
mutate()
can edit existing columns in a data frame or add new values that are calculated from existing columns.
First, let’s add a column with our names. That way Rey can thank us personally when her ship is finally up and running.
# Add your name as a column
scrap <- mutate(scrap, scrap_finder = "BB8")
Let’s also add a new column to document the data measurement method.
# Add your name as a column and
# some information about the method
scrap <- mutate(scrap,
scrap_finder = "BB8",
measure_method = "REM-24")
## REM = Republic Equivalent Method
Remember how the units of Tons was written two ways: “TONS” and “Tons”? We can use mutate()
together with tolower()
to make sure all of the scrap units are written in lower case. This will help prevent them from getting grouped separately in our plots and summaries.
# Set units to all lower-case
scrap <- mutate(scrap, units = tolower(units))
# toupper() changes all of the letters to upper-case.
In our work we often use mutate
to convert units for measurements. In this case, let’s estimate the total pounds for the scrap items that are reported in tons.
to
Pounds conversionWe can use mutate()
to convert the amount
column to pounds. Multiply the amount
column by 2000 to get new values for a column named amount_lbs
.
scrap_pounds <- mutate(scrap, amount_lbs = amount * 2000)
We now have all the tools we need. To get her ship working, Rey is trying to track down more of the scrap item: Ion engine
.
Step 1:
Ion engine
Show code
# Grab only the items named "Ion engine"
scrap_pounds <- filter(scrap_pounds, item == "Ion engine")
Now, arrange the data in descending order of pounds so Rey knows where the highest amount of Ion engine
scrap comes from.
Step 2:
amount_lbs
# Arrange data
scrap_pounds <- arrange(scrap_pounds, desc(amount_lbs))
# Return the origin of the highest amount_lbs of scrap
head(scrap_pounds, 1)
# Plot the total amount_lbs by origin
ggplot(scrap_pounds, aes(x = origin, y = amount_lbs)) +
geom_col()
For the item Ion engine
, which origin has the highest amount_lbs
?
Tuanul
Cratertown
Outskirts
Reestki
Show solution
Cratertown
Yes!! You receive the ship parts to repair Rey’s Millennium Falcon. Onward!
Nice work!
Rey got a great deal on her engines and even traded in some scrap for spending cash.
Time to get off this dusty planet, we’re flying to Endor!
You can’t break your original dataset if you always name it something else. Let’s use the readr
package to save our new CSV with the tons converted to pounds.
# Save data as a CSV file
write_csv(scrap_pounds, "scrap_in_pounds.csv")
Where did R save the file?
Let’s create a new results/
folder to keep our processed data separate from any raw data we receive.
# Save data as a CSV file to results folder
write_csv(scrap_pounds, "results/scrap_in_pounds.csv")
BB8 received new data from the wookies suggesting there was a large magnetic storm just before Site 1
burned down on Endor. Sounds like we’re going to be STORM CHASERS tomorrow. Mission accepted.


Start
2 hour UltraHD Movie (40G)
2 hour High Definition Movie (4G)
2 hour Standard Definition Movie (1.5G)
45 min TV Show (200M)
5 min video (30M)
4 min song (4M)
3 Mbps
10 Mbps
25 Mbps Broadband
100 Mbps Fiber from Wave
1 Gbps Fiber from Wave


|
ViennaCL - The Vienna Computing Library
1.5.2
|
Provides the implementation for tuning the kernels for a particular device. More...
Data Structures | |
| class | tuning_param |
| class for a tuning parameter More... | |
| class | tuning_config |
| Tuning configuration. More... | |
Functions | |
| template<class ProfileT > | |
| double | benchmark_impl (viennacl::scheduler::statement const &statement, code_generator::forced_profile_key_type key, ProfileT const &prof, unsigned int n_runs) |
| Add the timing value for a given profile and an statement. | |
| template<class ConfigType > | |
| void | benchmark (std::map< double, typename ConfigType::profile_type > *timings, scheduler::statement const &op, code_generator::forced_profile_key_type const &key, tuning_config< ConfigType > &config, unsigned int n_runs, std::ofstream *out) |
| Fills a timing map for a given statement and a benchmark configuration. |
Provides the implementation for tuning the kernels for a particular device.
| void viennacl::generator::autotune::benchmark | ( | std::map< double, typename ConfigType::profile_type > * | timings, |
| scheduler::statement const & | op, | ||
| code_generator::forced_profile_key_type const & | key, | ||
| tuning_config< ConfigType > & | config, | ||
| unsigned int | n_runs, | ||
| std::ofstream * | out | ||
| ) |
Fills a timing map for a given statement and a benchmark configuration.
| OpT | type of the statement |
| ConfigType | type of the benchmark configuration |
| timings | the timings to fill |
| op | the given statement |
| key | a key for forcing a particular kernel profile (i.e. to pick profile A for a device which would usually use profile B) |
| config | the given configuration |
| n_runs | Number of runs for the benchmark |
| out | Pointer to output file stream for writing to file (if not NULL) |
| double viennacl::generator::autotune::benchmark_impl | ( | viennacl::scheduler::statement const & | statement, |
| code_generator::forced_profile_key_type | key, | ||
| ProfileT const & | prof, | ||
| unsigned int | n_runs | ||
| ) |
Add the timing value for a given profile and an statement.


Component: Msp430SpiNoDma0P
configuration Msp430SpiNoDma0P
Author:
Jonathan Hui<EMAIL_ADDRESS>Version:
$Revision: 1.6 $ $Date: 2010-06-29 22:07:45 $
Provides
interface
FastSpiByte
interface
Resource
[uint8_t]
interface
ResourceConfigure
[uint8_t]
interface
SpiByte
interface
SpiPacket
[uint8_t]
Uses
interface
Msp430SpiConfigure
[uint8_t]
interface
HplMsp430UsartInterrupts
as
UsartInterrupts
interface
Resource
as
UsartResource
[uint8_t]
Wiring


| Path: | /usr/lib/ruby/gems/1.8/gems/activeresource-3.0.0.beta4/README |
| Last Update: | Sun Jun 20 17:19:16 -0600 2010 |
Active Resource (ARes) connects business objects and Representational State Transfer (REST) web services. It implements object-relational mapping for REST web services to provide transparent proxying capabilities between a client (ActiveResource) and a RESTful service (which is provided by Simply RESTful routing in ActionController::Resources).
Active Resource attempts to provide a coherent wrapper object-relational mapping for REST web services. It follows the same philosophy as Active Record, in that one of its prime aims is to reduce the amount of code needed to map to these resources. This is made possible by relying on a number of code- and protocol-based conventions that make it easy for Active Resource to infer complex relations and structures. These conventions are outlined in detail in the documentation for ActiveResource::Base.
Model classes are mapped to remote REST resources by Active Resource much the same way Active Record maps model classes to database tables. When a request is made to a remote resource, a REST XML request is generated, transmitted, and the result received and serialized into a usable Ruby object.
Putting Active Resource to use is very similar to Active Record. It‘s as simple as creating a model class that inherits from ActiveResource::Base and providing a site class variable to it:
class Person < ActiveResource::Base self.site = "http://api.people.com:3000/" end
Now the Person class is REST enabled and can invoke REST services very similarly to how Active Record invokes lifecycle methods that operate against a persistent store.
# Find a person with id = 1 ryan = Person.find(1) Person.exists?(1) #=> true
As you can see, the methods are quite similar to Active Record‘s methods for dealing with database records. But rather than dealing directly with a database record, you‘re dealing with HTTP resources (which may or may not be database records).
Active Resource is built on a standard XML format for requesting and submitting resources over HTTP. It mirrors the RESTful routing built into Action Controller but will also work with any other REST service that properly implements the protocol. REST uses HTTP, but unlike "typical" web applications, it makes use of all the verbs available in the HTTP specification:
For more information on how this protocol works with Active Resource, see the ActiveResource::Base documentation; for more general information on REST web services, see the article here.
Find requests use the GET method and expect the XML form of whatever resource/resources is/are being requested. So, for a request for a single element, the XML of that item is expected in response:
# Expects a response of # # <person><id type="integer">1</id><attribute1>value1</attribute1><attribute2>..</attribute2></person> # # for GET http://api.people.com:3000/people/1.xml # ryan = Person.find(1)
The XML document that is received is used to build a new object of type Person, with each XML element becoming an attribute on the object.
ryan.is_a? Person #=> true ryan.attribute1 #=> 'value1'
Any complex element (one that contains other elements) becomes its own object:
# With this response: # # <person><id>1</id><attribute1>value1</attribute1><complex><attribute2>value2</attribute2></complex></person> # # for GET http://api.people.com:3000/people/1.xml # ryan = Person.find(1) ryan.complex #=> <Person::Complex::xxxxx> ryan.complex.attribute2 #=> 'value2'
Collections can also be requested in a similar fashion
# Expects a response of # # <people type="array"> # <person><id type="integer">1</id><first>Ryan</first></person> # <person><id type="integer">2</id><first>Jim</first></person> # </people> # # for GET http://api.people.com:3000/people.xml # people = Person.find(:all) people.first #=> <Person::xxx 'first' => 'Ryan' ...> people.last #=> <Person::xxx 'first' => 'Jim' ...>
Creating a new resource submits the XML form of the resource as the body of the request and expects a ‘Location’ header in the response with the RESTful URL location of the newly created resource. The id of the newly created resource is parsed out of the Location response header and automatically set as the id of the ARes object.
# <person><first>Ryan</first></person> # # is submitted as the body on # # POST http://api.people.com:3000/people.xml # # when save is called on a new Person object. An empty response is # is expected with a 'Location' header value: # # Response (201): Location: http://api.people.com:3000/people/2 # ryan = Person.new(:first => 'Ryan') ryan.new? #=> true ryan.save #=> true ryan.new? #=> false ryan.id #=> 2
‘save’ is also used to update an existing resource - and follows the same protocol as creating a resource with the exception that no response headers are needed - just an empty response when the update on the server side was successful.
# <person><first>Ryan</first></person> # # is submitted as the body on # # PUT http://api.people.com:3000/people/1.xml # # when save is called on an existing Person object. An empty response is # is expected with code (204) # ryan = Person.find(1) ryan.first #=> 'Ryan' ryan.first = 'Rizzle' ryan.save #=> true
Destruction of a resource can be invoked as a class and instance method of the resource.
# A request is made to # # DELETE http://api.people.com:3000/people/1.xml # # for both of these forms. An empty response with # is expected with response code (200) # ryan = Person.find(1) ryan.destroy #=> true ryan.exists? #=> false Person.delete(2) #=> true Person.exists?(2) #=> false
You can find more usage information in the ActiveResource::Base documentation.