The Java platform supports three Standard Streams: Standard
Input, accessed through System.in
; Standard
Output, accessed through System.out
; and
Standard Error, accessed through System.err
.
These objects are defined automatically and do not need to be opened.
Standard Output and Standard Error are both for output; having error
output separately allows the user to divert regular output to a file
and still be able to read error messages. For more information, refer
to the documentation for your command line interpreter.
You might expect the Standard Streams to be character streams,
but, for historical reasons, they are byte streams.
System.out
and System.err
are defined as
PrintStream
objects. Although it is technically a byte stream,
PrintStream
utilizes an internal character stream object
to emulate many of the features of character streams.
By contrast, System.in
is a byte stream with no character
stream features. To use Standard Input as a character stream, wrap
System.in
in InputStreamReader
.
InputStreamReader cin = new InputStreamReader(System.in);
Console
that has most of the features provided
by the Standard Streams, and others besides. The Console is
particularly useful for secure password entry. The Console object also provides
input and output streams that are true character streams, through its
reader
and writer
methods.
Before a program can use the Console, it must attempt to retrieve the Console
object by invoking System.console()
. If the Console
object is available, this method returns it. If
System.console
returns NULL
, then Console
operations are not permitted, either because the OS doesn't support
them or because the program was launched in a noninteractive
environment.
The Console object supports secure password entry through its
readPassword
method. This method helps secure password
entry in two ways. First, it suppresses echoing, so the password is
not visible on the user's screen. Second, readPassword
returns a character array, not a String
, so the
password can be overwritten, removing it from memory as soon as it is
no longer needed.
The
Password
example is a prototype program for changing a user's password. It
demonstrates several Console
methods.
import java.io.Console; import java.util.Arrays; import java.io.IOException; public class Password { public static void main (String args[]) throws IOException { Console c = System.console(); if (c == null) { System.err.println("No console."); System.exit(1); } String login = c.readLine("Enter your login: "); char [] oldPassword = c.readPassword("Enter your old password: "); if (verify(login, oldPassword)) { boolean noMatch; do { char [] newPassword1 = c.readPassword("Enter your new password: "); char [] newPassword2 = c.readPassword("Enter new password again: "); noMatch = ! Arrays.equals(newPassword1, newPassword2); if (noMatch) { c.format("Passwords don't match. Try again.%n"); } else { change(login, newPassword1); c.format("Password for %s changed.%n", login); } Arrays.fill(newPassword1, ' '); Arrays.fill(newPassword2, ' '); } while (noMatch); } Arrays.fill(oldPassword, ' '); } //Dummy change method. static boolean verify(String login, char[] password) { // this method always returns true in this example. // modify this method to verify password according to your rules. return true; } //Dummy change method. static void change(String login, char[] password) { // modify this method to change password according to your rules. } }
Password
class follows these steps:
Console.readLine
to prompt for and read
the user's login name.
Console.readPassword
to prompt for and
read the user's existing password.
verify
to confirm that the user is
authorized to change the password. (In this example,
verify
is a dummy method that always returns
true
.)
Console.readPassword
twice to prompt
for and read a new password.
change
to change it. (Again, change
is a dummy method.)


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Files exist as Tracings(*.JB1).
Select a Tracing from the list.:
Execute enabled file commands on the target.
The following radio buttons are enabled:
OOpenOpen the target for Read-Write
OMapOpen the target for Read
OViewDisplays target in monotone
OCloakErases target from the screen
The following commands are enabled:
Nameto reName a target
Newto Add a new target
Deleteto delete a target
Save Asto continue on a copy
Saveto continue on original
Getto copy target into workfile
Includeto add a Tracing to the Sheet
Cancel to close without saving
OK to save and Close


Testing is an important part of developing software. In this lesson we’ll look at how to test our Elixir code with ExUnit and some best practices for doing so.
Table of Contents
ExUnit
Elixir’s built-in test framework is ExUnit and it includes everything we need to thoroughly test our code.
Before moving on it is important to note that tests are implemented as Elixir scripts so we need to use the .exs
file extension.
Before we can run our tests we need to start ExUnit with ExUnit.start()
, this is most commonly done in test/test_helper.exs
.
When we generated our example project in the previous lesson, mix was helpful enough to create a simple test for us, we can find it at test/example_test.exs
:
defmodule ExampleTest do
use ExUnit.Case
doctest Example
test "greets the world" do
assert Example.hello() == :world
end
end
We can run our project’s tests with mix test
.
If we do that now we should see an output similar to:
..
Finished in 0.03 seconds
2 tests, 0 failures
Why are there two dots in the test output? Besides the test in test/example_test.exs
, Mix also generated a doctest in lib/example.ex
.
defmodule Example do
@moduledoc """
Documentation for Example.
"""
@doc """
Hello world.
## Examples
iex> Example.hello
:world
"""
def hello do
:world
end
end
assert
If you’ve written tests before then you’re familiar with assert
; in some frameworks should
or expect
fill the role of assert
.
We use the assert
macro to test that the expression is true.
In the event that it is not, an error will be raised and our tests will fail.
To test a failure let’s change our sample and then run mix test
:
defmodule ExampleTest do
use ExUnit.Case
doctest Example
test "greets the world" do
assert Example.hello() == :word
end
end
Now we should see a different kind of output:
1) test greets the world (ExampleTest)
test/example_test.exs:5
Assertion with == failed
code: assert Example.hello() == :word
left: :world
right: :word
stacktrace:
test/example_test.exs:6 (test)
.
Finished in 0.03 seconds
2 tests, 1 failures
ExUnit will tell us exactly where our failed assertions are, what the expected value was, and what the actual value was.
refute
refute
is to assert
as unless
is to if
.
Use refute
when you want to ensure a statement is always false.
assert_raise
Sometimes it may be necessary to assert that an error has been raised.
We can do this with assert_raise
.
We’ll see an example of assert_raise
in the next lesson on Plug.
assert_receive
In Elixir, applications consist of actors/processes that send messages to each other, therefore you will want to test the messages being sent.
Since ExUnit runs in its own process it can receive messages just like any other process and you can assert on it with the assert_received
macro:
defmodule SendingProcess do
def run(pid) do
send(pid, :ping)
end
end
defmodule TestReceive do
use ExUnit.Case
test "receives ping" do
SendingProcess.run(self())
assert_received :ping
end
end
assert_received
does not wait for messages, with assert_receive
you can specify a timeout.
capture_io and capture_log
Capturing an application’s output is possible with ExUnit.CaptureIO
without changing the original application.
Simply pass the function generating the output in:
defmodule OutputTest do
use ExUnit.Case
import ExUnit.CaptureIO
test "outputs Hello World" do
assert capture_io(fn -> IO.puts("Hello World") end) == "Hello World\n"
end
end
ExUnit.CaptureLog
is the equivalent for capturing output to Logger
.
Test Setup
In some instances it may be necessary to perform setup before our tests.
To accomplish this we can use the setup
and setup_all
macros.
setup
will be run before each test and setup_all
once before the suite.
It is expected that they will return a tuple of {:ok, state}
, the state will be available to our tests.
For the sake of example, we’ll change our code to use setup_all
:
defmodule ExampleTest do
use ExUnit.Case
doctest Example
setup_all do
{:ok, recipient: :world}
end
test "greets", state do
assert Example.hello() == state[:recipient]
end
end
Test Mocks
We want to be careful of how we think about “mocking”. When we mock certain interactions by creating unique function stubs in a given test example, we establish a dangerous pattern. We couple the run of our tests to the behavior of a particular dependency, like an API client. We avoid defining shared behavior among our stubbed functions. We make it harder to iterate on our tests.
Instead, the Elixir community encourages us to change the way we think about test mocks; that we think about a mock as a noun, instead of a verb.
For a longer discussion on this topic, see this excellent article.
The gist is, that instead of mocking away dependencies for testing (mock as a verb), it has many advantages to explicitly define interfaces (behaviors) for code outside your application and use mock (as a noun) implementations in your code for testing.
To leverage this “mocks-as-a-noun” pattern you can:
- Define a behaviour that is implemented both by the entity for which you’d like to define a mock and the module that will act as the mock.
- Define the mock module
- Configure your application code to use the mock in the given test or test environment, for example by passing the mock module into a function call as an argument or by configuring your application to use the mock module in the test environment.
For a deeper dive into test mocks in Elixir, and a look at the Mox library that allows you to define concurrent mock, check out our lesson on Mox here
Caught a mistake or want to contribute to the lesson? Edit this page on GitHub!


Environment Setup¶
On this page, you will find not only the list of dependencies to install for the tutorial, but a description of how to install them. This tutorial assumes you have a laptop with OSX or Linux. If you use Windows, you might have to install a virtual machine to get a UNIX-like environment to continue with the rest of this instruction. A lot of this instruction is more verbose than needed to accomodate participants of different skill levels.
Please note that these are only optional. On the first day of this training, you will be provided with a link to a JupyterHub instance where the environment will be pre-made and ready to go!
0. Get Anaconda¶
Anaconda is a Python (and R) distribution that aims to provide everything needed for common scientific and machine learning situations out-of-the-box. We chose Anaconda for this tutorial as it significantly simplifies Python dependency management.
In practice, Anaconda can be used to manage different environment and packages. This setup document will assume that you have Anaconda installed as your default Python distribution.
You can download Anaconda here: https://www.continuum.io/downloads
After installing Anaconda, you can access its command-line interface
with the conda
command.
1. Create a new environment¶
Environments are a tool for sanitary software development. By this, we mean that you can install specific versions of packages without worrying that it breaks a dependency elsewhere.
Here is how you can create an environment with Anaconda
conda create -n dl4nlp python=3.6
2. Install Dependencies¶
2a. Activate the environment¶
After creating the environment, you need to activate the environment:
source activate dl4nlp
After an environment is activated, it might prepend/append itself to your console prompt to let you know it is active.
With the environment activated, any installation commands
(whether it is pip install X
, python setup.py install
or using
Anaconda’s install command conda install X
) will only install inside
the environment.
2b. Install IPython and Jupyter¶
Two core dependencies are IPython and Jupyter. Let’s install them first:
conda install ipython
conda install jupyter
To allow a jupyter notebooks to use this environment as their kernel, it needs to be linked:
python -m ipykernel install --user --name dl4nlp
2c. Installing CUDA (optional)¶
NOTE: CUDA is currently not supported out of the conda package control manager. Please refer to pytorch’s github repository for compilation instructions.
If you have a CUDA compatible GPU, it is worthwhile to take advantage of it as it can significantly speedup training and make your PyTorch experimentation more enjoyable.
To install CUDA:
- Download CUDA appropriate to your OS/Arch from here.
- Follow installation steps for your architecture/OS. For Ubuntu/x86_64, see here.
- Download and install CUDNN from here.
Make sure you have the latest CUDA (8.0) and CUDNN (7.0).
2d. Install PyTorch¶
There are instructions on http://pytorch.org which detail how to install it. If you have been following along so far and have Anaconda installed with CUDA enabled, you can simply do:
conda install pytorch torchvision cuda80 -c soumith
The widget on PyTorch.org will let you select the right command line for your specific OS/Arch.
PLEASE NOTE. Make sure you have PyTorch 0.3.0. PyTorch has recently released version 0.4.0, but it has many code changes that we will not be incorporating at this time. The Anaconda installation method for this is:
conda install pytorch=0.3.1 torchvision -c pytorch
If you would like to install using pips and wheels:
pip install http://download.pytorch.org/whl/cpu/torch-0.3.1-cp36-cp36m-linux_x86_64.whl
pip install torchvision
2e. Clone (or Download) Repository¶
At this point, you may have already cloned the tutorial repository. But if you have not, you will need it for the next step.
git clone https://github.com/joosthub/pytorch-nlp-tutorial-ny2018.git
If you do not have git or do not want to use it, you can also download the repository as a zip file
2f. Install Dependencies from Repository¶
Assuming the you have cloned (or downloaded and unzipped) the repository, please navigate to the directory in your terminal. Then, you can do the following:
pip install -r requirements.txt


Stock Search
LookupResult -> count() > 0) {
global $companyName, $companySymbol, $companyExchange;
echo "";
echo "";
echo "| Name | ";
echo "Symbol | ";
echo "Exchange | ";
echo "Details | ";
echo "
";
// read elements from xmlFile
foreach ($xmlFile -> LookupResult as $LookupResult) {
$companyName = $LookupResult -> Name;
echo "| " . $companyName . " | ";
$companySymbol = $LookupResult -> Symbol;
echo "" . $companySymbol . " | ";
$companyExchange = $LookupResult -> Exchange;
echo "" . $companyExchange . " | ";
echo "More Info |
";
echo "
";
}
echo "
";
}
else {
echo "";
echo "
No Records has been found.
";
echo "";
}
// the URL to JSON
$infoURL = 'http://dev.markitondemand.com/MODApis/Api/v2/Quote/json?symbol=' . $companySymbol;
echo $infoURL;
}
?>


The Lightmap Parameters Asset is used to store a set of values for the parameters which control Unity’s Global Illumination (GI) features. They allow you to define and save different sets of values for lighting, for use in different situations. Upon creation, they are stored in your Project folder, and can be accessed via the Project window.
Lightmap Parameters Assets allow you to quickly create presets optimized for different types of GameObjects, or for different platforms and different Scene types (for example, indoor or outdoor Scenes).
When you click on a Lightmap Parameters Asset in the Project window, the Inspector window displays the values defined in that Asset. The parameters and their descriptions are listed in the table below.
| Property | Function |
|---|---|
| Precomputed Realtime GI | |
| Resolution | This value scales the Realtime Resolution value in the Scene tab of the Lighting Window (menu: Window > Lighting > Scene) to give the final resolution of the lightmap in texels per unit of distance. |
| Cluster Resolution | The ratio of the cluster resolution (the resolution at which the light bounces are calculated internally) to the final lightmap resolution. See documentation on GI Visualizations in the Scene view for more information. |
| Irradiance Budget | This value determines the precision of the incoming light data used to light each texel in the lightmap. Each texel’s lighting is obtained by sampling a “view” of the Scene from the texel’s position. Lower values of irradiance budget result in a more blurred sample. Higher values increase the sharpness of the sample. A higher irradiance budget improves the lighting, but this increases run-time memory usage and might increase CPU usage. |
| Irradiance Quality | Use the slider to define the number of rays that are cast and used to compute which clusters affect a given output lightmap texel. Higher values offer visual improvements in the lightmap, but increase precomputing time in the Unity Editor. The value does not affect runtime performance. |
| Backface Tolerance | The structure of a Mesh sometimes causes some texels to have a “view” that includes back-facing geometry. Incoming light from a backface is meaningless in any Scene. Because of this, this property lets you select a percentage threshold of light that must come from front-facing geometry in order for a texel to be considered valid. Invalid texels have their lighting approximated from their neighbors’ values. Lowering this value can solve lighting problems caused by incoming light from backfaces. |
| Modelling Tolerance | This value controls the minimum size of gaps in Mesh geometry that allows light to pass through. Make this value lower to allow light to pass through smaller gaps in your environment. |
| Edge Stitching | If enabled, this property indicates that UV charts in the lightmap should be joined together seamlessly, to avoid unwanted visual artifacts. |
| Is Transparent | If enabled, the object appears transparent during the Global Illumination calculations. Back-faces do not contribute to these calculations, and light travels through the surface. This is useful for invisible emissive surfaces. |
| System Tag | A group of objects whose lightmap Textures are combined in the same lightmap atlas is known as a “system”. The Unity Editor automatically defines additional systems and their accompanying atlases if all the objects can’t be fitted into a single atlas. However, it is sometimes useful to define separate systems yourself (for example, to ensure that objects inside different rooms are grouped into one system per room). Change the System Tag number to force new system and lightmap creation. The exact numeric sequence values of the tag are not significant. |
| Baked GI | |
| Blur Radius | The radius of the blur filter that is applied to direct lighting during post-processing in texels. The radius is essentially the distance over which neighboring texels are averaged out. A larger radius gives a more blurred effect. Higher levels of blur tend to reduce visual artifacts but also soften the edges of shadows. |
| Antialiasing Samples | The degree of anti-aliasing (the reduction of “blocky” artifacts) that is applied. Higher numbers increase quality and bake time. |
| Direct Light Quality | The number of rays used to evaluate direct lighting. A higher number of rays tends to produce more accurate soft shadows but increases bake time. |
| Baked Tag | Similar to the System Tag property above, this number lets you group specific sets of objects together in separate baked lightmaps. As with the System Tag, the exact numeric value is not significant. Objects with different Baked Tag values are never put in the same atlas; however, there is no guarantee that objects with the same tag end up in the same atlas, because those objects might not necessarily fit into one lightmap (see image A, below, for an example of this). You don’t have to set this when using the multi-scene bake API, because grouping is done automatically (use the Baked Tag to replicate some of the behavior of the Lock Atlas option). |
| Pushoff | The distance to push away from the surface geometry before starting to trace rays in modelling units. It is applied to all baked lightmaps, so it affects direct light, indirect light, and AO. Pushoff is useful for getting rid of unwanted AO or shadowing. Use this setting to solve problems where the surface of an object is shadowing itself, causing speckled shadow patterns to appear on the surface with no apparent source. You can also use this setting to remove unwanted artifacts on huge objects, where floating point precision isn’t high enough to accurately ray-trace fine detail. |
| Baked AO | |
| Quality | The number of rays cast when evaluating ambient occlusion (AO). A higher numbers of rays increases AO quality but also increases bake time. |
| Antialiasing Samples | The number of samples to take when doing anti-aliasing of AO. A higher number of samples increases the AO quality but also increases the bake time. |
Image A shows two views of the same Scene:
Left: Everything is in one atlas because all the objects have the same Baked Tag.
Right: One object is forced into a second lightmap by assigning a different Baked Tag.
To assign a Lightmap Parameters Asset to the whole Scene, go to Window > Lighting to open the Lighting window. Here, click the Scene tab and navigate to the General GI settings.
Use the Default Parameters drop-down to assign a default Lightmap Parameters Asset. This drop-down lists all available Lightmap Parameters Assets.
To assign a Lightmap Parameters Asset to a single GameObject, ensure the GameObject has a Mesh Renderer or Terrain component attached. Select the GameObject then open the Lighting window (menu: Window > Lighting) and select the Object tab.
To assign a Lightmap Parameters Asset to a Mesh Renderer, tick the Lightmap Static checkbox and select an option from Advanced Parameters. Choose Default scene parameter if you want to use the same Lightmap Parameters Asset that is assigned to the whole Scene.
To assign a Lightmap Parameters Asset to a Terrain, tick the Lightmap Static checkbox and select an option from Advanced Parameters. Choose Default scene parameter if you want to use the same Lightmap Parameters Asset that is assigned to the whole Scene.
To create a new Lightmap Parameters Asset, click Create New… from the list of available Lightmap Parameters Assets. When you do this, the Lighting window changes to display a list of properties for you to create a custom Lightmap Parameters Asset. This window has the same properties as the ones you see in the Inspector window when you select the Lightmap Parameters Asset in the Project window.


JOYCE TANG
Joyce Tang is the Founder and Chief Customer Happiness Officer of AgilisIT. She has over 20 years of from-the-ground-up IT experience in different industries, from life sciences, healthcare, investment banking, academia to non-profits. She has been a consultant to Fortune 1000’s, and was one of the youngest IT managers to be in charge of multiple departments at UCLA School of Medicine. Her unique experience has given her a n invaluable perspective into both the enterprise and small/mid-sized business segments. It also enabled her to develop her highly-appraised Lean IT methodologies and customer-focused IT service model.
Joyce received her B.S. in Electrical Engineering Computer Engineering from the University of California, Los Angeles (UCLA) and her M.B.A from Indiana University (IU). She is also a Microsoft Certified Systems Engineer (MCSE), a VMware certified and CompTIA Security+ certified specialist and has been trained in Project Risk Management.
You can find Joyce being quoted by prominent IT publications such as Inc., The New York Times, CIO Update, Processor.com, SmallBusinessComputing.com, SearchSMBStorage.com, Redmond Magazine, etc. She writes a technical column on Microsoft email technology at OutlookExchange.com. She has also been interviewed by local TV and radio shows as an award-winning small business owner.
As a dog lover, she co-founded Woof’s Life, an organization that raises money and brings awareness to animal adoptions while offering job opportunities to workers with developmental disabilities. She believes in the “ Work Hard, Play Hard ” mantra. She loves to dive in the summer, snowboard in the winter, look for good eats and autocross her car all year round. For the rest of the time? You’ll likely find her looking for the next IT process to improve.


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{% extends 'bridge/base.html' %}
{% comment "License" %}
% Copyright (c) 2019 ISP RAS (http://www.ispras.ru)
% Ivannikov Institute for System Programming of the Russian Academy of Sciences
%
% Licensed under the Apache License, Version 2.0 (the "License");
% you may not use this file except in compliance with the License.
% You may obtain a copy of the License at
%
% http://www.apache.org/licenses/LICENSE-2.0
%
% Unless required by applicable law or agreed to in writing, software
% distributed under the License is distributed on an "AS IS" BASIS,
% WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
% See the License for the specific language governing permissions and
% limitations under the License.
{% endcomment %}
{% load i18n %}
{% load static %}
{% load compress %}
{% block title %}{% trans 'Job version creating' %}{% endblock %}
{% block head_block %}
{% compress js file restart-decision %}
{% endcompress %}
{% compress css file create-decision %}
{% endcompress %}
{% endblock %}
{% block body_block %}
{% include 'jobs/startDecision.html' with data=start_data decisions=other_decisions base_decision=object %}
{% trans 'Cancel' %}{% trans 'VerifierCloud credentials were successfully saved (you can change them in your settings)' %}


| 1 | /* =========================================================== | |
| 2 | * JFreeChart : a free chart library for the Java(tm) platform | |
| 3 | * =========================================================== | |
| 4 | * | |
| 5 | * (C) Copyright 2000-2008, by Object Refinery Limited and Contributors. | |
| 6 | * | |
| 7 | * Project Info: http://www.jfree.org/jfreechart/index.html | |
| 8 | * | |
| 9 | * This library is free software; you can redistribute it and/or modify it | |
| 10 | * under the terms of the GNU Lesser General Public License as published by | |
| 11 | * the Free Software Foundation; either version 2.1 of the License, or | |
| 12 | * (at your option) any later version. | |
| 13 | * | |
| 14 | * This library is distributed in the hope that it will be useful, but | |
| 15 | * WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY | |
| 16 | * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public | |
| 17 | * License for more details. | |
| 18 | * | |
| 19 | * You should have received a copy of the GNU Lesser General Public | |
| 20 | * License along with this library; if not, write to the Free Software | |
| 21 | * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, | |
| 22 | * USA. | |
| 23 | * | |
| 24 | * [Java is a trademark or registered trademark of Sun Microsystems, Inc. | |
| 25 | * in the United States and other countries.] | |
| 26 | * | |
| 27 | * ---------------------------------------- | |
| 28 | * StandardToolTipTagFragmentGenerator.java | |
| 29 | * ---------------------------------------- | |
| 30 | * (C) Copyright 2003-2008, by Richard Atkinson and Contributors. | |
| 31 | * | |
| 32 | * Original Author: Richard Atkinson; | |
| 33 | * Contributors: David Gilbert (for Object Refinery Limited); | |
| 34 | * | |
| 35 | * Changes | |
| 36 | * ------- | |
| 37 | * 12-Aug-2003 : Version 1 (RA); | |
| 38 | * 04-Dec-2007 : Escape tool tip text to fix bug 1400917 (DG); | |
| 39 | * | |
| 40 | */ | |
| 41 | ||
| 42 | package org.jfree.chart.imagemap; | |
| 43 | ||
| 44 | /** | |
| 45 | * Generates tooltips using the HTML title attribute for image map area tags. | |
| 46 | */ | |
| 47 | public class StandardToolTipTagFragmentGenerator | |
| 48 | implements ToolTipTagFragmentGenerator { | |
| 49 | ||
| 50 | /** | |
| 51 | * Creates a new instance. | |
| 52 | */ | |
| 53 | public StandardToolTipTagFragmentGenerator() { | |
| 54 | super(); | |
| 55 | } | |
| 56 | ||
| 57 | /** | |
| 58 | * Generates a tooltip string to go in an HTML image map. | |
| 59 | * | |
| 60 | * @param toolTipText the tooltip. | |
| 61 | * | |
| 62 | * @return The formatted HTML area tag attribute(s). | |
| 63 | */ | |
| 64 | public String generateToolTipFragment(String toolTipText) { | |
| 65 |
1
1. generateToolTipFragment : mutated return of Object value for org/jfree/chart/imagemap/StandardToolTipTagFragmentGenerator::generateToolTipFragment to ( if (x != null) null else throw new RuntimeException ) → KILLED |
return " title=\"" + ImageMapUtilities.htmlEscape(toolTipText) |
| 66 | + "\" alt=\"\""; | |
| 67 | } | |
| 68 | ||
| 69 | } | |
Mutations | ||
| 65 |
1.1 |


I started working as a front-end developer in the beginning of 2013. I have worked as a front-end developer and a designer, as well as a back-end developer.Now, i am traviling the world while working as a freelencer.


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:: com :: sun :: star :: chart2 ::
|
| unpublished |
struct Symbol |
|
|
|
- Usage Restrictions
- not published
- Description
- properties that are used for DataSeries that display symbols.
|
| Elements' Summary |
| Style |
determines which of the following members determines the
appearance of the symbol.
|
| PolygonCoords |
The given polygon is used as symbol.
|
| StandardSymbol |
Use the nth standard symbol, if Style is set
to ::SymbolStlye::STANDARD.
|
| Graphic |
use this graphic as symbol
|
| Size |
The size of the symbol in 100th of a mm.
@todo use a structure using doubles insted of longs
|
| BorderColor |
The color used for drawing the border of symbols.
|
| FillColor |
The color used for filling symbols that contain closed polygons.
|
| Elements' Details |
Style
SymbolStyle Style;
- Description
- determines which of the following members determines the
appearance of the symbol.
|
|
| PolygonCoords
|
StandardSymbol
long StandardSymbol;
- Description
- Use the nth standard symbol, if Style is set
to ::SymbolStlye::STANDARD.
If n is the number of standard symbols available in an
implementation, the symbol number is
StandardSymbol modulo n.
The default implementation for example currently uses 8 different
standard symbols that are matched to the numbers 0 to 7.
| value StandardSymbol | visible Symbol |
0 | square |
1 | diamond |
2 | down arrow |
3 | up arrow |
4 | right arrow |
5 | left arrow |
6 | bowtie |
7 | sandglass |
|
|
Graphic
::com::sun::star::graphic::XGraphic Graphic;
- Description
- use this graphic as symbol
|
|
Size
::com::sun::star::awt::Size Size;
- Description
- The size of the symbol in 100th of a mm.
@todo use a structure using doubles insted of longs
|
|
| BorderColor
|
| FillColor
|
Top of Page
Copyright © 2013, The Apache Software Foundation, Licensed under the Apache License, Version 2.0. Apache, the Apache feather logo, Apache OpenOffice and OpenOffice.org are trademarks of The Apache Software Foundation. Other names may be trademarks of their respective owners.


lib
/
com.github.thibaultbee.srtdroid.enums
/
Boundary
/
SUBSEQUENT
SUBSEQUENT
SUBSEQUENT
Middle packet of a message


Iterative algorithms occur in many domains of data analysis, such as machine learning or graph analysis. Such algorithms are crucial in order to realize the promise of Big Data to extract meaningful information out of your data. With increasing interest to run these kinds of algorithms on very large data sets, there is a need to execute iterations in a massively parallel fashion.
Stratosphere programs implement iterative algorithms by defining a step function and embedding it into a special iteration operator. There are two variants of this operator: Iterate and Delta Iterate. Both operators repeatedly invoke the step function on the current iteration state until a certain termination condition is reached.
Here, we provide background on both operator variants and outline their usage. The programming guides explain how to implement the operators in both Scala and Java. We also provide a vertex-centric graph processing API called Spargel.
The following table provides an overview of both operators:
| Iterate | Delta Iterate | |
|---|---|---|
| Iteration Input | Partial Solution | Workset and Solution Set |
| Step Function | Arbitrary Data Flows | |
| State Update | Next partial solution |
|
| Iteration Result | Last partial solution | Solution set state after last iteration |
| Termination |
|
|
The iterate operator covers the simple form of iterations: in each iteration, the step function consumes the entire input (the result of the previous iteration, or the initial data set), and computes the next version of the partial solution (e.g. map
, reduce
, join
, etc.).
map
, reduce
, join
, etc. (see programming model for details) and depends on your specific task at hand.There are multiple options to specify termination conditions for an iteration:
You can also think about the iterate operator in pseudo-code:
IterationState state = getInitialState();
while (!terminationCriterion()) {
state = step(state);
}
setFinalState(state);
In the following example, we iteratively incremenet a set numbers:
1
to 5
).map
operator, which increments the integer field from i
to i+1
. It will be applied to every record of the input.11
to 15
.// 1st 2nd 10th
map(1) -> 2 map(2) -> 3 ... map(10) -> 11
map(2) -> 3 map(3) -> 4 ... map(11) -> 12
map(3) -> 4 map(4) -> 5 ... map(12) -> 13
map(4) -> 5 map(5) -> 6 ... map(13) -> 14
map(5) -> 6 map(6) -> 7 ... map(14) -> 15
Note that 1, 2, and 4 can be arbitrary data flows.
The delta iterate operator covers the case of incremental iterations. Incremental iterations selectively modify elements of their solution solution and evolve the solution rather than fully recompute it.
Where applicable, this leads to more efficient algorithms, because not every element in the solution set changes in each iteration. This allows to focus on the hot parts of the solution and leave the cold parts untouched. Frequently, the majority of the solution cools down comparatively fast and the later iterations operate only on a small subset of the data.
map
, reduce
, join
, etc. (see programming model for details) and depends on your specific task at hand.The default termination condition for delta iterations is specified by the empty workset convergence criterion and a maximum number of iterations. The iteration will terminate when a produced next workset is empty or when the maximum number of iterations is reached. It is also possible to specify a custom aggregator and convergence criterion.
You can also think about the iterate operator in pseudo-code:
IterationState workset = getInitialState();
IterationState solution = getInitialSolution();
while (!terminationCriterion()) {
(delta, workset) = step(workset, solution);
solution.update(delta)
}
setFinalState(solution);
In the following example, every vertex has an ID and a coloring. Each vertex will propagete its vertex ID to neighboring vertices. The goal is to assign the minimum ID to every vertex in a subgraph. If a received ID is smaller then the current one, it changes to the color of the vertex with the received ID. One application of this can be found in community analysis or connected components computation.
The intial input is set as both workset and solution set. In the above figure, the colors visualize the evolution of the solution set. With each iteration, the color of the minimum ID is spreading in the respective subgraph. At the same time, the amount of work (exchanged and compared vertex IDs) decreases with each iteration. This corresponds to the decreasing size of the workset, which goes from all seven vertices to zero after three iterations, at which time the iteration terminates. The important observation is that the lower subgraph converges before the upper half does and the delta iteration is able to capture this with the workset abstraction.
In the upper subgraph ID 1 (orange) is the minimum ID. In the first iteration, it will get propagated to vertex 2, which will subsequently change its color to orange. Vertices 3 and 4 will receive ID 2 (in yellow) as their current minimum ID and change to yellow. Because the color of vertex 1 didn't change in the first iteration, it can be skipped it in the next workset.
In the lower subgraph ID 5 (cyan) is the minimum ID. All vertices of the lower subgraph will receive it in the first iteration. Again, we can skip the unchanged vertices (vertex 5) for the next workset.
In the 2nd iteration, the workset size has already decreased from seven to five elements (vertices 2, 3, 4, 6, and 7). These are part of the iteration and further propagate their current minimum IDs. After this iteration, the lower subgraph has already converged (cold part of the graph), as it has no elements in the workset, whereas the upper half needs a further iteration (hot part of the graph) for the two remaining workset elements (vertices 3 and 4).
The iteration terminates, when the workset is empty after the 3rd iteration.
We referred to each execution of the step function of an iteration operator as a single iteration. In parallel setups, multiple instances of the step function are evaluated in parallel on different partitions of the iteration state. In many settings, one evaluation of the step function on all parallel instances forms a so called superstep, which is also the granularity of synchronization. Therefore, all parallel tasks of an iteration need to complete the superstep, before a next superstep will be initialized. Termination criteria will also be evaluated at superstep barriers.


The all? method iterates over each element in the array, comparing them all based on the data entered into the code block. The return value is true if all of the elements meet the criteria, or false if at least one element does not. If no block is given, the return value is true because Ruby uses an implicitly-true code block design: { |elem| elem }.
array_num = [1, 2, 3, 5, 10]
array_num.all? { |elem| p elem > 3 }
false
The all? method iterates over each element of the hash, comparing them all based on the data entered into the code block. The return value is true if all of the elements meet the criteria, or false if at least one element does not. If no block is given, the return value is true because Ruby uses an implicitly-true code block design: { |elem| elem }.
The block takes two arguments – the key & the value.
meal = { "App" => "cheesebread", "Entree" => "steak", "Dessert" => "bread" }
puts meal.all? { |key, value| value.match('bread') }
false
The any? method iterates over each element in the array, looking to see if any of them contain the data entered into the code block. The return value is true if an element meets the criteria, or false if an element does not. If no block is given, the return value is true because Ruby uses an implicitly-true code block design: { |elem| elem }.
array_num = [1, 2, 3, 5, 10]
array_num.any? { |elem| p elem > 7 }
false
false
false
false
true
The any? method iterates over each element of the hash, looking to see if any of them contain the data entered into the code block. The return value is true if an element meets the criteria, or false if an element does not. If no block is given, the return value is true because Ruby uses an implicitly-true code block design: { |elem| elem }.
The block takes two arguments – the key & the value.
meal = { "App" => "cheesebread", "Entree" => "steak", "Dessert" => "bread" }
puts meal.any? { |key, value| value.match('bread') }
true
The chunk method iterates over each element of the array, grouping the elements together in arrays based on the return value of the code block.
Consecutive elements with equivalent code block return values are "chunked" together.
array_of_stuff = [1, 10, 713, "I", "can't", 3, "drive", 55, "fifty", "five"]
array_of_stuff.chunk { |elem|
elem.is_a? String
}.each { |result, items| puts "#{result}: #{items}" }
false: [1, 10, 713]
true: ["I", "can't"]
false: [3]
true: ["drive"]
false: [55]
true: ["fifty", "five"]
The chunk method iterates over each element of the hash, grouping the elements together in arrays based on the return value of the code block.
Consecutive elements with equivalent code block return values are "chunked" together.
XXXXX
XXXXXXXXXX
XXXXXXX
YYYYYY
YYYYY
YYYYYYYY
The collect method iterates over each element in the array, runs the code block on each element, and returns a new array.
The collect method will yield each member of an array to the block. But unlike the each method (which just returns the original array), the collect method will collect the results in a new array and return that instead.
The collect! method modifies the original array (NOT an Enumerable method).
make_em_grow = [2, 4, 6, 8]
p make_em_grow.collect { |elem| elem ** 2 }
p make_em_grow
make_em_grow.collect! { |elem| elem ** elem }
p make_em_grow
[4, 16, 36, 64]
[2, 4, 6, 8]
[4, 256, 46656, 16777216]
The collect method iterates over each key:value pair of the hash, runs the code block on each key:value pair, and returns a new array.
The collect method will yield each key:value pair of a hash to the block. But unlike the each method (which just returns the original array), collect will collect the results in a new array and return that instead.
The block takes two arguments – the key & the value.
meals = { "breakfast" => "apple", "lunch" => "rice", "dinner" => "salad" }
nom = meals.map do |course, food|
food = "cookie"
"ME WANT #{food.upcase} FOR #{course.upcase}!!!"
end
p nom
["ME WANT COOKIE FOR BREAKFAST!!!",
"ME WANT COOKIE FOR LUNCH!!!",
"ME WANT COOKIE FOR DINNER!!!"]
The collect_concat method iterates over each element in the array, runs the code block on each element, and returns a new concatenated array.
Unlike the collect method, the collect_concat method concatenates the resulting array.
original_array = [3, 15, 75, 375]
print "collect method results: "
p original_array.collect { |elem| [elem, -elem] }
print "collect_concat method results: "
p original_array.collect_concat { |elem| [elem, -elem] }
collect method results: [[3, -3], [15, -15], [75, -75], [375, -375]]
collect_concat method results: [3, -3, 15, -15, 75, -75, 375, -375]
The collect_concat method iterates over each key:value pair of the hash, runs the code block on each key:value pair, and returns a new concatenated array.
Unlike the collect method, the collect_concat method concatenates the resulting array.
mega_nest = { a: { b: { c: 9, d: { e: { f: 7 } } } }, g: 2, h: { i: { } } }
puts "map method results: "
p mega_nest.map { |the_hash| the_hash + [99, 100] }
puts "flat_map method results: "
p mega_nest.flat_map { |the_hash| the_hash + [99, 100] }
map method results:
[[:a, {:b=>{:c=>9, :d=>{:e=>{:f=>7}}}}, 99, 100], [:g, 2, 99, 100], [:h, {:i=>{}}, 99, 100]]
flat_map method results:
[:a, {:b=>{:c=>9, :d=>{:e=>{:f=>7}}}}, 99, 100, :g, 2, 99, 100, :h, {:i=>{}}, 99, 100]
The count method returns the number of elements contained in the array it is called upon.
If the optional argument is passed, then the return value will be the number of elements found in the array that are equal to that argument.
If a block is given, then the return will be the number of elements for which the code block returns a true value.
number_fest = [73, 73, 37, 49, 94, 21, 73, 12, 73]
puts number_fest.count
puts number_fest.count(73)
puts number_fest.count { |num| num % 2 == 0 }
9
4
2
The count method returns the number of key:value pairs contained in the hash it is called upon.
If the optional argument is passed on a values-count method chain, then the return value will be the number of values found in the hash that are equal to that argument. This can be done with keys using a keys-count chain, but this isn't too useful because every key in a hash must be unique.
If a block is given, then the return will be the number of elements for which the code block returns a true value.
rating = { low: 5, medium: 10, mid: 10, middle: 10, high: 15, extreme: 20 }
puts rating.count
puts rating.values.count(10)
puts rating.count { |num| num[1] % 2 == 0 }
puts rating.keys.count(:low)
6
3
4
1
The cycle method iterates over each element in the array and runs the code block on each element.
If the optional argument n is passed, then the code block will be run on each element n times. If no argument or nil is passed, then the code block will be run on each element an infinite number of times.
exponential_growth = [0, 6, 12]
exponential_growth.cycle(5) do |repeat|
print repeat ** 3
print " – "
end
#
hut_sut_raw = ["And ", "so ", "on ", "so_on ", "so-on, "]
hut_sut_raw.cycle { |lyric| print lyric }
0 – 216 – 1728 – 0 – 216 – 1728 – 0 – 216 – 1728 – 0 – 216 – 1728 – 0 – 216 – 1728 –
#
And so on so_on so-on, And so on so_on so-on, And so on so_on so-on,... FOREVER
The cycle method iterates over each key:value pair in the hash and runs the code block on each key:value pair.
If the optional argument n is passed, then the code block will be run on each element n times. If no argument or nil is passed, then the code block will be run on each element an infinite number of times.
crew = { "Captain" => "Picard", "First Officer" => "Riker", "Science Officer" => "Data", "Tactical Officer" => "Worf" }
food = %w{Bacon Jahamaron Pizza Meatloaf Salad Gumbo}.cycle
crew.cycle { |rank, name| puts "I am #{rank} #{name} of USS Enterprise. I shall prepare #{food.next}." }
I am Captain Picard of the USS Enterprise. I shall prepare Bacon.
I am First Officer Riker of the USS Enterprise. I shall prepare Jahamaron.
I am Science Officer Data of the USS Enterprise. I shall prepare Pizza.
I am Tactical Officer Worf of the USS Enterprise. I shall prepare Meatloaf.
I am Captain Picard of the USS Enterprise. I shall prepare Salad.
I am First Officer Riker of the USS Enterprise. I shall prepare Gumbo.
I am Science Officer Data of the USS Enterprise. I shall prepare Bacon.
I am Tactical Officer Worf of the USS Enterprise. I shall prepare Jahamaron.... FOREVER
The detect method iterates over each element in the array, searching for a certain element based on the return value of the code block.
The first element that returns true from the code block, will be the method return. If no match is found, the return of the method will be nil.
eighteen = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18]
puts eighteen.detect { |num| num % 2 == 0 and num % 7 == 0 }
seven = [1, 2, 3, 4, 5, 6, 7]
p seven.detect { |num| num % 2 == 0 and num % 7 == 0 }
14
nil
The find method iterates over each element in the array, searching for a certain key:value pair based on the return value of the code block.
The first item that returns true from the code block, will be the method return. If no match is found, the return of the method will be nil. The method's return value will be an array with two elements – key & value.


bypass is a 2-factor-authentication solution for purchases through voice controlled devices such as Alexa or Google Home. Thanks to our solution we provide you with an easy to implement solution that provides a dynamically generated code that is sent to your phone via sms each time you have a request that needs protection and security.
It is easy to implement. we have abstracted all of the difficult work using flowroute and providing an easy to use python module. Its as easy as this flask tutorial
place the source code into your alexa skills directory
1. set up a virtualenvironment for your project
2. migrate to the bypass-auth folder
3. install the requirements
$ pip install -r requirements.txt
4. retrieve your users phone number from your database (amazon linked accounts tutorial below)https://developer.amazon.com/blogs/post/Tx3CX1ETRZZ2NPC/Alexa-Account-Linking-5-Steps-to-Seamlessly-Link-Your-Alexa-Skill-with-Login-wit
receiving linked accounts requires your skill to be accepted first, for development, you can hard code in a test number or use a dummy account. the xample below uses Flask-sqlalchemy
user = User.query.filter_by(userid='#######').first()
phone_number = user.phone_number
5. Add the code into your main routing file and save what the method returns
pass_code = bypass_sms.send_auth(phone_number)
6. Configure your auth service to receive your variables in the config file
This includes your:
#configuration.py
USERNAME = '##########'
PASSWORD = '18###88ec#####d#########f7cab5'
from_number = '15104050151'
$ python main.py * Running on http://localhost:5000/


PiCard
This page shows a demonstration of
PiCard
with some dummy data and mostly default options.
Single Chart
Loading …
Multiple Charts
Loading …


The first year we went to a festival it was magical, and we've never seen anything like it. Watching all the people dress up and get into it gave a whole new meaning.
Among all the things you encounter at a festival, there's nothing as fun as totems. Totems are a beacon of energy and excitement, each bringing their own flavor to the crowd.
After spending time working on our own totems, we learned they can be a constant headache. Most totems fall apart or are smashed and usually require a good amount of time and money to upkeep.
We decided it's time to create a solution that can be easily attained and withstand the harshest of climates. All the while giving you a totem that Lights up and keeps the place energized.


Kindergarten First Grade Second Grade Third Grade Fourth Grade Fifth Grade Flashcards and Vocabulary Lists Go to Students' Site Back to Home Page


When? Every Wednesday
Where? Ifgi
Where (more precise)? GEO1, 3rd floor, Room 323
Course Language: English
First Name:
Password:
Target degree: Bachelor Master PhD None of these
Why I've decided to study Geoinformatics: I'm interested in everything that is related to geography I'm interested in everything that is related to inpatics I must study I like to study
Here is my CV: Durchsuchen... Keine Datei ausgewählt.


{% extends "base.html" %} {% load i18n %} {% load staticfiles %} {% load crispy_forms_tags %} {% block title %}{{ block.super }}Home{% endblock %} {% block navbar-left %} {% include "_navbar.html" with active_link="home" %} {% endblock %} {% block splash %} {% get_current_language as LANGUAGE_CODE %}
{% endblock splash %} {% block extrahead %} {% endblock extrahead %} {% block container %}{% trans "This open-source and open-hardware project is the result of a continuous necessity to learn and explore new horizonts." %}
{% trans "As knowledge is power, this project will empower its user since it will allow him/her to gather tons of information about anything " %} {% trans "that can be measured around him/her. " %}
{% trans "By the way, do never forget that everything concerning Django and Python " %} {% trans "may be implemented in some other (much more efficient) way since this is my baptismal project." %}
{% trans "In a general way, it pretends to implement a simple and affordable, yet powerful, data acquisition environment based on " %} {% trans " open-hardware platforms such as "%} Arduino {% trans " and " %} Raspberry.
{% trans "The project consist of a Master unit (usually a Raspberry) that is in charge of controlling everything. Around it, several Slave devices (usually Arduinos)" %} {% trans " will be waiting for an HTTP query from the Master unit. When a proper query reaches an Slave device, it responds with an XML datagram " %} {% trans " containing the requested information. The Master unit stores the information in a database and this is all, simple isn't it??" %} {% trans "Somebody at this point will be probably asking: Why shouldn't you use the trendy "%} MQTT {% trans " infrastructure??" %}
{% trans "My first answer will be just because I wanted... Because I wanted to keep it extremely simple!!" %}
{% trans "Using MQTT protocol will require to configure it on every single piece of equipment living in the environment, thus making it more" %} {% trans " difficult to setup. On the contrary, with the XML exchange architecture, only the Master unit needs to be configured in certain way, and" %} {% trans " the Slave devices are just it, slaves.
{% trans "The communication between the Master and the Slaves will be defined in the main XML file resident in the Master unit. The information sent by the Slaves is contained " %} {% trans "within a so called datagram. Each Slave may have more than one datagram with different information, sampling times, etc. " %} {% trans "In the main XML file, the communications between the Master and the Slaves are defined by means of the following parameters:" %}
{% trans "The data in the datagrams can be of three types basically:" %}
{% trans "Moreover, in the initial release there will be a feature that will generate automatic Arduino code templates " %} {% trans " based on the information placed in the main XML file. " %}
{% trans "Eventhough it may seem that the main objective of this project is to gather information about habits, daily patterns, etc, actually it is" %} {% trans " not. The main and initial objective of the project was diving into " %} Python. {% trans " One thing took to another and finally this project was raised. If one decides to accept the challenge of getting involved in this project (as a developer or a power-user)," %} {% trans " he/she will gain expertise and knowledge in the follwoing fields: " %}
{% trans "Seems interesting humm??" %}
{% trans "This project started in May 2017 and it never expects to be finished since a continuous development phylosophy is laying behind it." %} {% trans "Eventhough it is an open-source and open-hardware project, it is being carefully developed and tested following industrial procedures " %} {% trans "that hopefully will end up in a robust and stable first release." %}
{% trans "The minimum features required for the very first release are:" %}
{% trans "and its target deadline is set by end September 2017. By this date, an operating environment consisting of a Master unit and at " %} {% trans "least one Slave device should be up and running." %}


Sorting an array means to arrange its elements in increasing order. Write a script to sort an array.
Use the "selection sort" algorithm: Find the smallest element, move it at the first position, find the smallest from
the rest, move it at the second position, etc.Hint: Use a second array


---
layout: post
authors: ["Karen Cranston"]
title: "Our First Data Carpentry Workshop"
date: 2014-05-14
time: "07:30:00"
tags: ["Bootcamps", "Data Carpentry"]
---
Update: for more information on Data Carpentry, please see their web site.
On May 8 and 9, 2014, 4 instructors, 4 assistants, and 27 learners filed into
the largest meeting space at the National Evolutionary Synthesis Center
(NESCent) for the inaugural Data Carpentry bootcamp. Data Carpentry is modeled
on Software Carpentry, but focuses on tools and practices for more
productively managing and manipulating data. The inaugural group of learners
for this bootcamp was very diverse. They included graduate students, postdocs,
faculty and staff, from three of the largest local research universities (Duke
University, University of North Carolina, and North Carolina State
University). Over 55% of the attendees were women and research areas ranged
from evolutionary biology and ecology to microbial ecology, fungal
phylogenomics, marine biology, and environmental engineering. One participant
was even a library scientist from Duke Library.
Acquiring data has become easier and less costly, including in many fields of
biology. Hence, we expected that many researchers would be interested in Data
Carpentry to help manage and analyze their increasing amounts of data. To get
a better idea of the breadth of perspectives that learners brought to the
course, we started by asking learners why they were attending. The responses
reflected a broad spectrum of the daily data wrangling challenges researchers
face:
- I'm tired of feeling out of my depth on computation and want to increase my confidence.
- I usually manage data in Excel and it's terrible and I want to do it better.
- I'm organizing GIS data and it's becoming a nightmare.
- This workshop sounds like a good way to dive in head first.
- My advisor insists that we store 50,000 barcodes in a spreadsheet, and something must be done about that.
- I want to teach a reproducible research class.
- I'm having a hard time analyzing microarray, SNP or multivariate data with Excel and Access.
- I want to use public data.
- I work with faculty at undergrad institutions and want to teach data practices, but I need to learn it myself first.
- I'm interested in going in to industry and companies are asking for data analysis experience.
- I'm trying to reboot my lab's workflow to manage data and analysis in a more sustainable way.
- I'm re-entering data over and over again by hand and know there's a better way.
- I have overwhelming amounts of NGS data.
The instructors discussed many of these kinds of scenarios during the months
of planning that preceded the event. Therefore we were hopeful that the
curriculum elements we chose from the many potentially useful subjects would
qaddress what many of the learners were hoping to get out of the course. Here
is what we finally decided to teach, and the lessons we learned from that as
well as from the feedback we received from the learners.
We taught four different sections:
-
Wrangling data in the shell (bash):
Differences between Excel documents and plain text;
getting plain text out of Excel;
navigating the bash shell;
exploring, finding and subsetting data using cat, head, tail, cut, grep,
find, sort, uniq
(Karen Cranston)
-
Managing and analyzing data in R: navigating R studio;
importing tabular data into dataframes;
subsetting dataframes;
basic statistics and plotting
(Tracy Teal)
-
Managing, combining and subsetting data in SQL: database structure;
importing CSV files into SQLite;
querying the database;
creating views;
building complex queries
(Ethan White)
-
Creating repeatable workflows using shell scripts: putting shell commands in
a script;
looping over blocks of commands;
chaining together data synthesis in SQL with data analysis in R
(Hilmar Lapp)
This was the first-ever bootcamp of this kind,
so after it was all done, we had a lot of ideas for future improvements:
-
The SQL section should come before the R section! It makes more sense in
terms of workflow (extract subset of data; export to CSV for analyses) but
is also an easier entry for learners (easier syntax, can see data in
Firefox plugin). The learners seemed to get SQL: there were fewer red
sticky notes and questions were more about transfer ("how would I structure
this other query") than comprehension ("how do I correct bash / R
syntax").
-
Each section should include discussion about how to structure data and files to make one's life easier.
Ethan did this for the SQL section, and it was very effective.
-
Students were already motivated when they came to the bootcamp; they didn't
need to be convinced that what we were teaching was important. Many people
are already struggling with data, and are hungry for better tools and
practices. Our bootcamp filled up in less than 24 hours after opening
registration, and there was virtually no attrition despite zero tuition
costs—everyone showed up, and every learner stayed until the end of day 2.
 When
would I use bash vs R vs SQL? Learners brought this up repeatedly, and we
didn't always have good answers that didn't involve hand waving, perhaps in
part because the answer depends so much on context and the problem at hand.
-
+1 for using a real (published!) data set that was relevant to at least some
of the participants; for using this same data set throughout the course; and
for having an instructor with intimate knowledge of the data (could explain
some of the quirks of the data).
#squirrelcannon
-
For the shell scripting section, an outline and/or concept map would have
been useful to give learners a good idea upfront of what we were trying to
accomplish. Without this, some learners (and helpers!) were confused about
which endpoint we were working towards.
-
People who fall behind need a good way to catch up. Ways to do this include
providing a printed cheat sheet of commands at the start of the session;
providing material online (unlike the well polished Software Carpentry
material, the material for Data Carpentry is still in the early stages of
online documentation); and having one helper dedicated to entering commands
in the Etherpad.
-
There is great demand for this type of course. Even without charging a fee, we
didn't have any empty seats the first day, and 100% of attendees returned for
the second day. Also, there were 62 people on the wait list! And we know that
many people didn't even sign up for the wait list, even though they were
interested.
There were also various things we wanted to teach but that came under the
chopping block due to lack of time and other reasons. One of these, and one
that learners asked about repeatedly, was the subject of "getting data off the
web". It will take more thought to pin down what that should actually
mean as part of Data Carpentry bootcamp aimed at zero-barrier to entry. It
might mean using APIs to access data from NCBI or GBIF, but it's far from
clear whether that would be meeting learners' needs or not. For most
general-purpose data repositories, such as Dryad, most of their data are too
messy to use without extensive cleanup.
All of the helpers including Darren Boss (iPlant), Matt Collins (iDigBio),
Deb Paul (iDigBio), and Mike Smorul (SESYNC) did a great job of helping the
students pick up new data skills.
Finally, we'd like to thank our sponsors for their support, including NESCent
for hosting the event and keeping us nourished, and the Data Observation
Network for Earth (DataONE), without whom this event wouldn't have taken
place.
For more on this workshop, please see this Storify.


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any()
on a list?any()
function will randomly return any item from the list.any()
function returns True if any item in the list evaluates to True. Otherwise, it returns False.any()
function takes as arguments the list to check inside, and the item to check for. If "any" of the items in the list match the item to check for, the function returns True.any()
function returns a Boolean value that answers the question "Are there any items in this list?"linked list
queue
set
OrderedDict
Static methods are called static because they always return "None".
Static methods can be bound to either a class or an instance of a class.
They serve mostly as utility methods or helper methods, since they can't access or modify a class's state.
Static methods can access and modify the state of a class or an instance of a class.
if/else
statement, used when testing for equality between objects.tuple assignment
tuple unpacking
tuple matching
tuple duplication
".delete()" method
pop(my_list)
del(my_list)
".pop()" method
to capture command-line arguments given at a file's runtime
to connect varios systems, such as connecting a web front end, an API service, a database, and a mobile app
to take a snapshot of all the packages and libraries in your virtual environment
to scan the health of your Python ecosystem while inside a virtual environment
"O(n)", also called linear time
"O(log n)", also called logarithmic time
"O(n^2)", also called quadratic time
"O(1)", also called constant time
class Game: pass
def Game(): pass
def Game: pass
class Game(): pass
-
def sum(a, b):
"""
sum(4, 3)
7
sum(-4, 5)
1
"""
return a + b
-
def sum(a, b):
"""
>>> sum(4, 3)
7
>>> sum(-4, 5)
1
"""
return a + b
-
def sum(a, b):
"""
# >>> sum(4, 3)
# 7
# >>> sum(-4, 5)
# 1
"""
return a + b
-
def sum(a, b):
###
>>> sum(4, 3)
7
>>> sum(-4, 5)
1
###
return a + b
set
list
None. You can only build a stack from scratch.
dictionary
college_years = ['Freshman', 'Sophomore', 'Junior', 'Senior']
return list(enumerate(college_years, 2019)
[('Freshman', 2019), ('Sophomore', 2020), ('Junior', 2021), ('Senior', 2022)]
[(2019, 2020, 2021, 2022), ('Freshman', 'Sophomore', 'Junior', 'Senior')]
[('Freshman', 'Sophomore', 'Junior', 'Senior'), (2019, 2020, 2021, 2022)]
[(2019, 'Freshman'), (2020, 'Sophomore'), (2021, 'Junior'), (2022, 'Senior')]
defaultdict
work?defaultdict
will automatically create a dictionary for you that has keys which are the integers 0-10.defaultdict
forces a dictionary to only accept keys that are of the types specified when you created the defaultdict
(such as string or integers).defaultdict
will create a new key for you instead of throwing a KeyError
.defaultdict
stores a copy of a dictionary in memory that you can default to if the original gets unintentionally modified.class Game.LogicGame(): pass
def Game(LogicGame): pass
class Game(LogicGame): pass
def Game.LogicGame(): pass
self means that no other arguments are required to be passed into the method
There is no real purpose for the self method; it"s just historic computer science jargona that Python keeps to stay consistent with other programming languages
self refers to the instance whose method was called
self refers to the class that was inherited from to create the object using self
You can assign a name to each of the namedtuple members and refer to them that way, similarly to how you would access keys in dictionary
Each member of a namedtuple object can be indexed to directly, just like in a regular tuple
namedtuples are just as memory efficient as regular tuples
No import is needed to use namedtuples because they are available in the standard library
Instance methods can modify the state of an instance or the state of its parent class
Instance methods hold data related to the instance
An instance method is any class method that doesn"t take any arguments
An instance method is a regular function that belongs to a class, but it must return None
-
num_people = 5
if num_people > 10;
print("There is a lot of people in the pool.")
elif num_people > 4;
print("There are some people in the pool.")
elif num_people > 0;
print("There are a few people in the pool.")
else:
print("There is no one in the pool.")
-
num_people = 5
if num_people > 10;
print("There is a lot of people in the pool.")
if num_people > 4;
print("There are some people in the pool.")
if num_people > 0;
print("There are a few people in the pool.")
else:
print("There is no one in the pool.")
-
num_people = 5
if num_people > 10:
print("There is a lot of people in the pool.")
elif num_people > 4:
print("There are some people in the pool.")
elif num_people > 0:
print("There are a few people in the pool.")
else:
print("There is no one in the pool.")
-
if num_people > 10;
print("There is a lot of people in the pool.")
if num_people > 4;
print("There are some people in the pool.")
if num_people > 0;
print("There are a few people in the pool.")
else:
print("There is no one in the pool.")
It protects the data from outside interference
A parent class is encapuslated and no data from the parent class passes on to the child class
It keeps data and the methods that can manipulate that data in one place
It only allows the data to be changed by methods
An if/else statement tells the computer which chunk of code to run if the instructions you coded are incorrect
An if/else statement runs one chunk of code if all the imports were succesful, and another chunk of code if the imports were not succesful
An if/else statement executes one chunk of code if a condition it true, but a different chunk of code if the condition is false
An if/else statement tells the computer which chunk of code to run if the is enough memory to handle it. and which chunk of code to run if there is not enough memory to handle it
dictionary
set
None. You can only build a stack from scratch.
list
my_game = class.Game()
my_game = class(Game)
my_game = Game()
my_game = Game.create()
The function will return a RuntimeError if you don't return a value.
If the return keyword is absent, the function will return None.
If the return keyword is absent, the function will return True.
The function will enter an infinite loop because it won't know when to stop executing its code.
pass
statement in Python?yield
statement of a generator and return a value of None.while
or for loop
and return to the start of the loop.arguments
paradigms
attributes
decorators
slot
dictionary
queue
sorted list
when it encounters an infinite loop
when it encounters an if/else statement that contains a break keyword
when it has assessed each item in the iterable it is working on or a break keyword is encountered
when the runtime for the loop exceeds O(n^2)
fruits = ['Apples', 'Oranges', 'Bananas']
quantities = [5, 3, 4]
prices = [1.50, 2.25, 0.89]
# Desired output
[('Apples', 5, 1.50),
('Oranges', 3, 2.25),
('Bananas', 4, 0.89)]
-
output = []
fruit_tuple_0 = (first[0], quantities[0], price[0])
output.append(fruit_tuple)
fruit_tuple_1 = (first[1], quantities[1], price[1])
output.append(fruit_tuple)
fruit_tuple_2 = (first[2], quantities[2], price[2])
output.append(fruit_tuple)
return output
-
i = 0
output = []
for fruit in fruits:
temp_qty = quantities[i]
temp_price = prices[i]
output.append((fruit, temp_qty, temp_price))
i += 1
return output
-
groceries = zip(fruits, quantities, prices)
return groceries
>>> [
('Apples', 5, 1.50),
('Oranges', 3, 2.25),
('Bananas', 4, 0.89)
]
-
i = 0
output = []
for fruit in fruits:
for qty in quantities:
for price in prices:
output.append((fruit, qty, price))
i += 1
return output
The all() function returns a Boolean value that answers the question "Are all the items in this list the same?"
The all() function returns True if all the items in the list can be converted to strings. Otherwise, it returns False.
The all() function will return all the values in the list.
The all() function returns True if all items in the list evaluate to True. Otherwise, it returns False.
-
>>> dice = Game()
>>> dice.roll()
-
>>> dice = Game(self)
>>> dice.roll(self)
-
>>> dice = Game()
>>> dice.roll(self)
-
>>> dice = Game(self)
>>> dice.roll()
backtracking
dynamic programming
decrease and conquer
divide and conquer
O(1), also called constant time
O(log n), also called logarithmic time
O(n^2), also called quardratic time
O(n), also called linear time
Abstraction means that a different style of code can be used, since many details are already known to the program behind the scenes.
Abstraction means the implementation is hidden from the user, and only the relevant data or information is shown.
Abstraction means that the data and the functionality of a class are combined into one entity.
Abstraction means that a class can inherit from more than one parent class.
def print_alpha_nums(abc_list, num_list):
for char in abc_list:
for num in num_list:
print(char, num)
return
print_alpha_nums(['a', 'b', 'c'], [1, 2, 3])
-
a 1
a 2
a 3
b 1
b 2
b 3
c 1
c 2
c 3
-
['a', 'b', 'c'], [1, 2, 3]
-
aaa
bbb
ccc
111
222
333
-
a 1 2 3
b 1 2 3
c 1 2 3
Game
?-
my_game = Game()
my_game.roll_dice()
-
my_game = Game()
self.my_game.roll_dice()
-
my_game = Game(self)
self.my_game.roll_dice()
-
my_game = Game(self)
my_game.roll_dice(self)
-
def sum(a, b):
# a = 1
# b = 2
# sum(a, b) = 3
return a + b
-
def sum(a, b):
"""
a = 1
b = 2
sum(a, b) = 3
"""
return a + b
-
def sum(a, b):
"""
>>> a = 1
>>> b = 2
>>> sum(a, b)
3
"""
return a + b
-
def sum(a, b):
'''
a = 1
b = 2
sum(a, b) = 3
'''
return a + b
When instantiating an object, the object doesn't inherit any of the parent class's methods.
When instantiating an object, the object will inherit the methods of whichever parent class has more methods.
When instantiating an object, the programmer must specify which parent class to inherit methods from.
An instance of the Game class will inherit whatever methods the BoardGame and LogicGame classes have.
a generic object class with iterable parameter fields
a generic object class with non-iterable named fields
a tuple subclass with non-iterable parameter fields
a tuple subclass with iterable named fields
&&
=
==
||
fruit_info = { 'fruit’: 'apple’, 'count’: 2, 'price’: 3.5 }
fruit_info ['price'] = 1.5
my_list [3.5] = 1.5
1.5 = fruit_info ['price]
my_list['price'] == 1.5
5!=6
yes
False
True
None
The __init_method makes classes aware of each other if more than one class is defined in a single code file.
The _init_method is included to preserve backwards compatibility from Python 3 to Python 2, but no longer needs to be used in Python 3.
The __init__() method is a constructor method that is called automatically whenever a new object is created from a class. It sets the initial state of a new object.
The __init__ method initializes any imports you may have included at the top of your file.
How many microprocessors it would take to run your code in less than one second
How many lines of code are in your code file
The amount of space taken up in memory as a function of the input size
How many copies of the code file could fit in 1 GB of memory
fruit_info = {'fruit': 'apple', 'count': 2, 'price': 3.5}
fruit_info =('fruit': 'apple', 'count': 2,'price': 3.5 ).dict()
fruit_info = ['fruit': 'apple', 'count': 2,'price': 3.5 ].dict()
fruit_info = to_dict('fruit': 'apple', 'count': 2, 'price': 3.5)
fruits = {'Apples’: 5, 'Oranges’: 3, 'Bananas’: 4}
fruit_names = [x in fruits.keys() for x]
fruit_names = for x in fruits.keys() *
fruit_names = [x for x in fruits.keys()]
fruit_names = x for x in fruits.keys()
backtracking
divide and conquer
dynamic programming
decrease and conquer
self
keyword when defining or calling methods on an instance of an object?self
refers to the class that was inherited from to create the object using self
.self
method. It’s just legacy computer science jargon that Python keeps to stay consistent with other programming languages.self
means that no other arguments are required to be passed into the method.self
refers to the instance whose method was called.A class method is a regular function that belongs to a class, but it must return None.
Class methods can modify the state of the class, but they can't directly modify the state of an instance that inherits from that class.
A class method is similar to a regular function, but a class method doesn't take any arguments.
Class methods hold all of the data for a particular class.
def getMaxNum(list_of_nums): # body of function goes here
func get_max_num(list_of_nums): # body of function goes here
func getMaxNum(list_of_nums): # body of function goes here
def get_max_num(list_of_nums): # body of function goes here
explanationmaxValue = 255
max_value = 255
MAX_VALUE = 255
MaxValue = 255
myset = {0, 'apple', 3.5}
myset = to_set(0, 'apple', 3.5)
myset = (0, 'apple', 3.5).to_set()
myset = (0, 'apple', 3.5).set()
__init__()
method that takes no parameters?-
class __init__(self):
pass
-
def __init__():
pass
-
class __init__():
pass
-
def __init__(self):
pass
None
For any given Node in a binary Search Tree, the child node to the left is less than the value of the given node and the child node to its right is greater than the given node.
(Not Sure)Binary Search Tree cannot be used to organize and search through numeric data, given the complication that arise with very deep trees
The top node of the binary search tree would be an arbitray number. All the nodes to the left of the top node need to be less than the top node's number, but they don't need to ordered in any particular way
The smallest numeric value would go in the top most node. The next highest number would go in its left child node, the the next highest number after that would go in its right child node. This pattern would continue until all numeric values were in their own node
A decorator is similar to a class and should be used if you are doing functional programming instead of object oriented programming.
A decoratore is a visual indicator to someone reading your code that a portion of your code is critical and should not be changed
You use the decorator to alter the functionality of a function without the without having to modify the functions code
An import statement is preceded by a decorator, pyhton knows to import the most recent version of whatever package or library is being imported
Only in some situations, as loops are used ony for certaing type of programming
When you need to check every element in an iterable of known length
When you want to minimize the use of strings in your code
When you want to run code in one file for a function in another file
def tax(my_float): '''Calculates the sales tax of a purchase. Takes in a float representing the subtotal ...???
def tx(amt): '''Gets the tax on an amount.'''
def sales_tax(amount): '''Calculates the sales tax of a purchase. Takes in a float representing the subtotal ...???
-[x] def calculate_sales_tax(subtotal): pass


Before Change
builder=self,
description=_DESCRIPTION,
// tfds.features.FeatureConnectors
features=tfds.features.FeaturesDict({
"text": tfds.features.Text(),
"toxicity": tf.float32,
"severe_toxicity": tf.float32,
"obscene": tf.float32,
"threat": tf.float32,
"insult": tf.float32,
"identity_attack": tf.float32,
"sexual_explicit": tf.float32
}),
// The supervised_keys version is very impoverished.
supervised_keys=("text", "toxicity"),
homepage="https://www.kaggle.com/c/jigsaw-unintended-bias-in-toxicity-classification/data",
After Change
]
def _info(self):
features = {"text": tfds.features.Text()}
labels = [
"toxicity", "severe_toxicity", "obscene", "threat", "insult",
"identity_attack", "sexual_explicit"


{% extends "base.html" %} {% set title = 'File drop' %} {% block content_classes %}drop-window{% endblock %} {% block content %}
File drop lets you upload a single file which can then be retrieved from the same page. This allows you to quickly share a file between two devices without having to copy over the download link.


Sensors package¶
Overview¶
Sensors act as an interface between the environment and the vehicles’ intelligence modules. This module acts as a simulation of real world sensors by taking in information from the vehicle and the maps module about the vehicle’s surrounding environment. The sensors currently implemented include BasicVisual, GPS and Speed. BasicVisual provides information about the objects present in the vehicle’s field of view. This can be thought of as LIDAR or RADAR readings or simply as the surroundings as seen by a vehicle driver through the windshield or the rear view mirrors. GPS provides the coordinates of the vehicle and Speed provides the speedometer reading of the vehicle. These sensor readings are used by the vehicle’s internal modules to localize the vehicle and to take a decision based on the inferences. To understand the effect of sensor failures/malfunctions, these sensors can be configured to provide noisy readings to the vehicle.
sensors.sensor module¶
-
class
core.lib.sensors.sensor.
BasicVisual
¶ Bases:
object
Simulates the capability of a human visual system.
-
static
get_intersection_traffic
(car, tg)¶ Used to ‘peep and look’ at turnings. Essentially used only in a right way rules to see if there is a car coming to the intersection from an another road. Refer to implementation docs for details on how this function works, and what the dict keys mean.
Note
Currently this seems to be used all the time instants and it often returns to the dictionary with keys from [1,8] or [0,7]. It occurs when it is called on turning roads. Don’t be panic!!
Parameters: - car (object) – vehicle object
- tg (object) – traffic Graph object
Returns: with keys as [1,3,5,7] and values as a list of vehicle objects
Return type: dict
-
static
get_traffic_signal_state
(car)¶ Shows traffic signals that are visible to a human driver.
Currently included in Basic Visual as a driver can ‘see’ a traffic signal. It should be included in communication module later.
Parameters: car (object) – vehicle object Returns: [color, time remaining] , if there is no signal, returns [None, None] Return type: list
-
static
get_visible_cars
(car, tg)¶ Shows cars that are visible to a human driver. Similar to what a driver can see (directly, via mirrors, sides or rears).
Note
Instead of passing a car, pass an only attribute as a message or via a bus in the future.
Parameters: - car (object) – vehicle object
- tg (object) – traffic Graph object
Returns: with keys as [‘front’, ‘back’, ‘left’, ‘right’] and values as a list of vehicle objects
Return type: dict
-
static
-
class
core.lib.sensors.sensor.
GPS
¶ Bases:
object
Simulates a GPS device.
-
static
get_position
(x, y)¶ Shows GPS coordinates of a vehicle.
Parameters: - x (float) – x coordinate of vehicle
- y (float) – y coordinate of vehicle
Returns: [x, y] of the vehicle
Return type: list
-
static
-
class
core.lib.sensors.sensor.
LaneCenterSensor
¶ Bases:
object
Simulates a sensor that gives offset from the lane center.
Note
Implementation might have to change for curved roads/roadstring ds in the future.
-
static
get_lane_center_dtheta
(car)¶ Takes in a car object and returns the difference between the heading of the road/lane and the heading of the vehicle.
Parameters: car (object) – vehicle object Returns: angle in radians Return type: float
-
static
get_lane_center_dy
(car)¶ Takes in a car object and returns the displacement from the lane center.
Note
Calculates the distance from left edge of road and subtracts the lane number * lane width.
Parameters: car (object) – vehicle object Returns: distance from the center of lane Return type: float
-
static
offset_direction
(car)¶ Deprecated. When lane center is calculated using distance from center of road, this method is used to check if the car is to the left of the road center or to the right.
Note
Not using this currently.
Parameters: car (object) – car Returns: 0 or 1 or -1 Return type: int
-
static
-
class
core.lib.sensors.sensor.
PositionBasedVelocityEstimator
¶ Bases:
object
Estimates vehicle speed based on its position.
Note
Not implemented currently. It returns to the speed directly. It will be implemented as a fusion of speed sensor and a position based on velocity estimator.
-
static
calc_speed
(car)¶
-
static
read_speed
(speed)¶
-
static
-
class
core.lib.sensors.sensor.
VehicleSpeedSensor
(car=None)¶ Bases:
object
Simulates a speed sensor.
Note
Will be implemented with noisy version of speed and sensor fusion using GPS data.
-
car
¶ Vehicle object
Type: object
-
read_speed
()¶ Shows the speed of vehicle.
Returns: speed Return type: float
-
-
core.lib.sensors.sensor.
get_adj_polygon_from_point
(x, y, theta, width, distance, direction, lane_width)¶ Returns to a polygon with lane_width away from (x, y) along with theta angle in a given direction with the sizes distance x width.
Parameters: - x (float) – x coordinate
- y (float) – y coordinate
- theta (float) – angle in radians
- width (float) – width of the bounding box
- distance (float) – length of the bounding box
- direction (str) – ‘left’ or ‘right’
- lane_width (float) – to check lane_width distance away = finding in the adjacent lane
Returns: shapely polygon object
Return type: object
-
core.lib.sensors.sensor.
get_car_bounding_box
(car)¶ Returns to a bounding box (not axis aligned; generic one) of the vehicle.
Parameters: car (object) – vehicle object Returns: shapely Polygon object Return type: object
-
core.lib.sensors.sensor.
get_car_bounding_box_adj
(car, lane_width, direction)¶ Returns to a bounding box of the area in the adjacent lane of the vehicle determined by the input args.
Parameters: - car (object) – vehicle object
- lane_width (float) –
- direction (str) – ‘left’ or ‘right’
Returns: shapely Polygon object
Return type: object
-
core.lib.sensors.sensor.
get_car_bounding_box_back
(car)¶ Returns the bounding box (not axis aligned; generic one) of the area in the back vehicle (determined by safe dist).
Parameters: car (object) – vehicle object Returns: shapely Polygon object Return type: object
-
core.lib.sensors.sensor.
get_car_bounding_box_front
(car)¶ Returns to a bounding box (not axis aligned; generic one) of the area in the front vehicle (determined by safe distance).
Parameters: car (object) – vehicle object Returns: shapely Polygon object Return type: object
-
core.lib.sensors.sensor.
get_polygon_from_point
(x, y, theta, width, front_distance, back_distance)¶ Returns to a polygon around a point in a given heading angle with given dimensions. Front_distance and back_distance are determined by the heading angle to figure out which one is front or back.
Parameters: - x (float) – x coordinate
- y (float) – y coordinate
- theta (float) – heading angle in radians
- width (float) – width of the bounding box
- front_distance (float) – distance from the point to the end of the front of the box (ahead of the point)
- back_distance (float) – distance from the point to the end of the back of the box (behind the point)
Returns: shapely Polygon object
Return type: object
sensors.sensor_factory module¶
-
class
core.lib.sensors.sensor_factory.
SensorFactory
¶ Bases:
object
Factory class to build sensors of various types.
-
static
build_sensor
(type)¶ Parameters: type (str) – should be a valid sensor type among the following implemented Returns: returns to an instantiation of a mentioned sensor Return type: object Note
Currently only includes the following sensors.
- ‘gps’
- ‘lane_center’
- ‘speed’
- ‘basic_visual’
-
static


[1]
Decent pda device; No phone function
[2]
apps, music, video, internet, pictures, podcasts, games, speaker; no bluetooth support yet.
[3]
Functionality, WiFi-Support, Design, Control; Pricey, No Bluetooth, Miserable sound-quality, iTunes


THE GAME IS LOADING. PLEASE WAIT
IT MAY TAKE UP TO 2 MINUTES
CONTROLS:
ARROWS
- MOVEMENT, JUMP, DUCK
SPACE
- FIRE
HOLD
SPACE
TO FIRE A GRENADE


Stay up to date with the latest happenings on and off the field.
Ok, so you didn't find the answer you were loooking for, maybe this page will help. I will try to address questions and concerns in this document as we move foward.
The club season runs from August 1st, 2015 to June 1st, 2016. We will be part of the Port of Subs Open league in Arizona. Season 1 starts 3rd week in September and season 2 starts the 3rd week in December. There will be a total of 12 games played across both seasons, 6 away and 6 home games. This is a competitive team and we will be playing teams from other cities in Arizona. Be prepared to travel when required. Each team will strive to play atleast 20 games which include league play, tournament play and scheduled friendlys.
topThe cost of the season is based on the number of players per team. This year, the club fee will be between 175 and 200 dollars for the season.
topEach player will receive a home and away jersey, shorts, socks and 1 training shirt. Bags and cold wear are extra.
We will hold at least 2 practice sessions per week with games on Saturday. On the off weeks where there are no games scheduled, a practice session or friendly can be setup, per the coaches schedule and avialability.
topYes, each team registered with Laveen FC will participate in at least 2 tournaments per year.
topNo, tournament fees are in addition to the regular club fee.
topThe cost per player will be determined based on the number of players attending the tournament and the tournament fee. Tournament fees will vary from tournament to tournament but roughly fall in the 500 dollar range.
topLaveen FC currently has openings for U13 and U14 teams. These are '02' and '03' boys and girls. At this time, we do not have older than U14 and younger than U13. Laveen FC will try to grow 2 new teams each year.
topNo, once you pay your club fee, there are no additional monthly fees. Tournaments will be on a case by case basis.
topNo, there are currently no payment option plans available.
topCoach Alek


From the Firehose
Sample blog post
This blog post shows a few different types of content that’s supported and styled with Bootstrap. Basic typography, images, and code are all supported.
Yeah, she dances to her own beat. Oh, no. You could've been the greatest.  Maybe a reason why all the doors are closed. Open up your heart and just let it begin. So très chic, yeah, she's a classic.
Bikinis, zucchinis, Martinis, no weenies. I know there will be sacrifice but that's the price. This is how we do it. I'm not sticking around to watch you go down. You think you're so rock and roll, but you're really just a joke. I know one spark will shock the world, yeah yeah. Can't replace you with a million rings.
Trying to connect the dots, don't know what to tell my boss. Before you met me I was alright but things were kinda heavy. You just gotta ignite the light and let it shine. Glitter all over the room pink flamingos in the pool.
Heading
Suiting up for my crowning battle. If you only knew what the future holds. Bring the beat back. Peach-pink lips, yeah, everybody stares.
 Straight stuntin' yeah we do it like that. Calling out my name. ‘Cause I, I’m capable of anything.
Example code block
Before you met me I was alright but things were kinda heavy. You just gotta ignite the light and let it shine.
Sub-heading
You got the finest architecture. Passport stamps, she's cosmopolitan. Fine, fresh, fierce, we got it on lock. Never planned that one day I'd be losing you. She eats your heart out.
- Got a motel and built a fort out of sheets.
- Your kiss is cosmic, every move is magic.
- Suiting up for my crowning battle.
Takes you miles high, so high, 'cause she’s got that one international smile.
- Scared to rock the boat and make a mess.
- I could have rewrite your addiction.
- I know you get me so I let my walls come down.
After a hurricane comes a rainbow.
Another blog post
I am ready for the road less traveled. Already brushing off the dust. Yeah, you're lucky if you're on her plane. I used to bite my tongue and hold my breath. Uh, She’s a beast. I call her Karma (come back). Black ray-bans, you know she's with the band.
Growing fast into a bolt of lightning. Be careful Try not to lead her on
I'm intrigued, for a peek, heard it's fascinating. Oh oh! Wanna be a victim ready for abduction. She's got that international smile, oh yeah, she's got that one international smile. Do you ever feel, feel so paper thin. I’m gon’ put her in a coma. Sun-kissed skin so hot we'll melt your popsicle.
This is transcendental, on another level, boy, you're my lucky star.
New feature
From Tokyo to Mexico, to Rio. Yeah, you take me to utopia. I'm walking on air. We'd make out in your Mustang to Radiohead. I mean the ones, I mean like she's the one. Sun-kissed skin so hot we'll melt your popsicle. Slow cooking pancakes for my boy, still up, still fresh as a Daisy.
- I hope you got a healthy appetite.
- You're never gonna be unsatisfied.
- Got a motel and built a fort out of sheets.
Don't need apologies.  Talk about our future like we had a clue. I can feel a phoenix inside of me.


A site redesign of the popular Portland restaurant
A look at the process and goals of this redesign
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Before you start
You should only use this service if you are repaying the full amount.
If you not able to pay the full amount you must contact Debt Management on 0345 850 0293 to discuss other payment options and agree a repayment plan.
If you make a part payment using this service Debt Management will continue recovery action which may include contacting your employer to make deductions directly from your wages or sending your case to an independent debt collector.


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--- layout: page title: Projects ---
Here you will find my personal projects per topic. Most of them was done when I was studying some specific topic


This page is about my journey in digital fabrication and engineering. Click on the tabs above to explore our progress. Click below to learn more about me.


Discover the cosmos! Each day a different image or photograph of our fascinating universe is featured, along with a brief explanation written by a professional astronomer.
Explanation: That's no sunspot. It's the International Space Station (ISS) caught passing in front of the Sun. Sunspots, individually, have a dark central umbra, a lighter surrounding penumbra, and no solar panels. By contrast, the ISS is a complex and multi-spired mechanism, one of the largest and most sophisticated machines ever created by humanity. Also, sunspots occur on the Sun, whereas the ISS orbits the Earth. Transiting the Sun is not very unusual for the ISS, which orbits the Earth about every 90 minutes, but getting one's timing and equipment just right for a great image is rare. Strangely, besides that fake spot, in this recent two-image composite, the Sun lacked any real sunspots. The featured picture combines two images -- one capturing the space station transiting the Sun -- and another taken consecutively capturing details of the Sun's surface. Sunspots have been rare on the Sun since the dawn of the current Solar Minimum, a period of low solar activity. For reasons not yet fully understood, the number of sunspots occurring during both the previous and current solar minima have been unusually low.
Authors & editors:
Robert Nemiroff
(MTU) &
Jerry Bonnell (UMCP)
NASA Official: Phillip Newman
Specific rights apply.
NASA Web
Privacy Policy and Important Notices
A service of:
ASD at
NASA /
GSFC
& Michigan Tech. U.


Infant Twisting Riding Car Driving Activity.
Teddy Bear Plus Soft Toy Gifts.
Socks For baby Body Toddler Newborn.
Sport Running.
Checked Happy.
Baby Socks Unisex.
Shoe Girl Footwear Blue.
Lace Up-Leather Shoes
Kids Fashion Shoes, Sneakers.