Data scientists and AI developers use the Azure Machine Learning SDK for R to build and run machine learning workflows with Azure Machine Learning.
Azure Machine Learning SDK for R uses the reticulate package to bind to Azure Machine Learning’s Python SDK. By binding directly to Python, the Azure Machine Learning SDK for R allows you access to core objects and methods implemented in the Python SDK from any R environment you choose.
Main capabilities of the SDK include:
Please take a look at the package website https://azure.github.io/azureml-sdk-for-r for complete documentation.
✔ feature available 🔄 in progress 📋 planned
| Features | Description | Status |
|---|---|---|
| Workspace | The Workspace class is a foundational resource in the cloud that you use to experiment, train, and deploy machine learning models |
✔ |
| Compute | Cloud resources where you can train your machine learning models. | ✔ |
| Data Plane Resources |
Datastore , which stores connection information to an Azure storage service, and DataReference , which describes how and where data should be made available in a run. |
✔ |
| Experiment | A foundational cloud resource that represents a collection of trials (individual model runs). | ✔ |
| Run | A Run object represents a single trial of an experiment, and is the object that you use to monitor the asynchronous execution of a trial, store the output of the trial, analyze results, and access generated artifacts. You use Run inside your experimentation code to log metrics and artifacts to the Run History service. |
✔ |
| Estimator | A generic estimator to train data using any supplied training script. | ✔ |
| HyperDrive | HyperDrive automates the process of running hyperparameter sweeps for an Experiment . |
✔ |
| Model | Cloud representations of machine learning models that help you transfer models between local development environments and the Workspace object in the cloud. |
✔ |
| Webservice | Models can be packaged into container images that include the runtime environment and dependencies. Models must be built into an image before you deploy them as a web service. Webservice is the abstract parent class for creating and deploying web services for your models. |
✔ |
| Dataset | An Azure Machine Learning Dataset allows you to explore, transform, and manage your data for various scenarios such as model training and pipeline creation. When you are ready to use the data for training, you can save the Dataset to your Azure ML workspace to get versioning and reproducibility capabilities. TabularDataset support is experimental.
|
✔ |
Install Conda if not already installed. Choose Python 3.5 or later.
# Install Azure ML SDK from CRAN
install.packages("azuremlsdk")
# Or the development version from GitHub
install.packages("remotes")
remotes::install_github('https://github.com/Azure/azureml-sdk-for-r', build_vignettes = TRUE)
# Then, use `install_azureml()` to install the compiled code from the AzureML Python SDK.
azuremlsdk::install_azureml()
Now, you’re ready to get started!
For a more detailed walk-through of the installation process, advanced options, and troubleshooting, see our Installation Guide.
To begin running experiments with Azure Machine Learning, you must establish a connection to your Azure Machine Learning workspace.
If you don’t already have a workspace created, you can create one by doing:
# If you haven't already set up a resource group, set `create_resource_group = TRUE`
# and set `resource_group` to your desired resource group name in order to create the resource group
# in the same step.
new_ws <- create_workspace(name = <workspace_name>,
subscription_id = <subscription_id>,
resource_group = <resource_group_name>,
location = location,
create_resource_group = FALSE)
After the workspace is created, you can save it to a configuration file to the local machine.
write_workspace_config(new_ws)
If you have an existing workspace associated with your subscription, you can retrieve it from the server by doing:
existing_ws <- get_workspace(name = <workspace_name>,
subscription_id = <subscription_id>,
resource_group = <resource_group_name>)
Or, if you have the workspace config.json file on your local machine, you can load the workspace by doing:
loaded_ws <- load_workspace_from_config()
Once you’ve accessed your workspace, you can begin running and tracking your own experiments with Azure Machine Learning SDK for R.
Take a look at our code samples and end-to-end vignettes for examples of what’s possible with the SDK!
We welcome contributions from the community. If you would like to contribute to the repository, please refer to the contribution guide.
This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact<EMAIL_ADDRESS>with any additional questions or comments.


High-technology exports are products with high R&D intensity, such as in aerospace, computers, pharmaceuticals, scientific instruments, and electrical machinery. Data are in current U.S. dollars.
Source: Worldbank/United Nations, Comtrade database.


| Class | Description |
|---|---|
| ErrorsKt | |
| ExpandableFab |
The design and behavior of a Floating Action Button which can animate and expand to show
optional
class FabOption s when clicked. It's the focal point for the ExpandableFab widget's
functionality, from an end-user's perspective. |
| ExpandableFabLayout |
The container and controller for all children views of the ExpandableFab widget (Overlay,
ExpandableFab, FabOption, Label). The ExpandableFabLayout handles the bulk of the functionality
for the ExpandableFab widget as a whole (from coordinating opening and closing animations to
screen orientation changes, etc). See below for an example on how to easily set up the
ExpandableFab widget using the ExpandableFabLayout as the containing ViewGroup.
|
| FabOption |
The design and behavior of a single option within an
class ExpandableFab . |
| Label |
A label of text attached to a view of the ExpandableFab widget.
|
| OrientationConfiguration |
Holder for all the views of an ExpandableFab widget in a specific
enum Orientation .
Not meant to be instantiated by clients, as an instance can be retrieved via
ExpandableFabLayout.portraitConfiguration or ExpandableFabLayout.landscapeConfiguration .
Values for the views will only be populated after they are added through calls to
ExpandableFabLayout's addView methods (or after they're defined via XML). |
| Overlay |
An overlay that will show when an
class ExpandableFab is clicked in order to partially or fully
obscure the screen's content, allowing the class ExpandableFab and class FabOption s to become more
apparent. |
| Enum | Description |
|---|---|
| FabOptionPosition |
The legal positions of FabOptions, in relation to the previous FabOption in an orientation.
By default, FabOptions are positioned ABOVE the previous FabOption in an orientation.
|
| FabSize |
The legal sizes of ExpandableFabs and FabOptions.
|
| LabelPosition |
The legal positions of Labels, in relation to the view they're attached to.
By default, labels are positioned to the LEFT of the view they're attached to.
|
| Orientation |
The screen orientations that the views of this widget can be in. If you only set a single
ExpandableFab widget, it will automatically be used for both portrait and landscape orientations.
|


Create New Organization Profile
Business Contact Information
Name of organization:
Charitable Registration Number:
Email:
Definitely not an email address
Contact Name:
Address:
Phone Number:
e.g.<PHONE_NUMBER>
Phone number not formatted correctly
e.g.<PHONE_NUMBER>
Organization Website:
Password:
Verify Password:
Passwords do not match
Organization Description:
Mission Statement:
History of Organization:
Provide a brief (200 words, maximum) history of your organization
Programs and Services:
Briefly describe your organization's main programs and services
Target Populations:
i.e. people, neighbourhoods and communities served by the program
Computer Program Description:
Briefly describe the computer mentoring/tutoring program, objectives, and outcomes, providing any relevant statistics.
(Optional) Accolades and accomplishments:
Provide information on any awards and successes


Methods
end(hash)
Signal that the task `hash` has finished.
Frees its slot in the queue
Frees its slot in the queue
Parameters:
| Name | Type | Description |
|---|---|---|
hash |
any | Unique hash identifying the task, Symbol() works very well |
flush() → {Promise.<void>}
Returns a promise that resolves when the queue is empty
Returns:
- Type
- Promise.<void>
run(job, priorityopt) → {Promise.<any>}
Run a job (equivalent to calling Queue.wait(), fn() and then Queue.end())
fn can be both synchronous or asynchronous function
fn can be both synchronous or asynchronous function
Parameters:
| Name | Type | Attributes | Default | Description |
|---|---|---|---|---|
job |
function | The job | ||
priority |
number |
<optional> |
0 | Optional priority, -1 is higher priority than 1 |
Returns:
Resolved when the task has finished with the return value of fn
- Type
- Promise.<any>
stat() → {QueueStats}
Return the number of running and waiting jobs
Returns:
running, waiting, last
- Type
- QueueStats
wait(hash, priorityopt) → {Promise.<void>}
Wait for a slot in the queue
Parameters:
| Name | Type | Attributes | Default | Description |
|---|---|---|---|---|
hash |
any | Unique hash identifying the task | ||
priority |
number |
<optional> |
0 | Optional priority, -1 is higher priority than 1 |
Returns:
Resolved when the task is ready to run
- Type
- Promise.<void>


{% include "Home/includes/CAF.html" %}
The central axiom of freedom is our primary principle of operation. We are committed to making each of the basic needs available to each person in Afrika and the rest of the world.
{% include "Home/proverb/p13.html" %} {% endblock %}


Contents
Note: Although the whole API is covered in this guide, it is not a substitute for the API documentation. The API documentation can be found in all of the source files, and is formatted to be accessible with pydoc.
The first thing to do is to figure out what functions you can parallelize. Functions that can run independently from other functions are strong candidates for parallelization. Functions that depend on each other’s output (sequential functions) are weak candidates for parallelization.
Functions that tend to be good candidates for parallelization include functions that are repeated often, usually in a loop.
Note that it’s not necessarily the function itself that defines if it can be parallelized or not, but the use of the function.
Here are some examples to help explain what works and what doesn’t.
This is an example of a function that works great with parallelization:
def incr(n):
return n + 1
for x in range(0, 5):
print incr(x)
This is an example of a function that will not work well with parallelization:
def incr(n):
return n + 1
x = 0
while x < 10:
x = incr(x)
print(x)
Notice how the functions are exactly the same, but the usage of those functions determined whether it could be parallelized or not.
The latter example requires the previous result before the next result could be computed. Because of that, you must run the code in order, and therefore you can not split the operation up.
With the former, however, you are simply incrementing each number in the range. There is no dependency on any result, and therefore it’s possible to split the operation up.
If you have trouble visualizing this, try evaluating the statements. Let’s make the function more complicated so that we can’t guess anything.
def setn(n):
n = random.randint(0, n)
return n
For the first example with the for loop, it will evaluate to:
print setn(0)
print setn(1)
print setn(2)
print setn(3)
print setn(4)
For the second one, it’s very different. We have no idea what the output will be, and the input to the function depends on the output after the intial run. Here’s how it will look like:
x = setn(0)
print(x)
x = setn(?)
print(x)
x = setn(?)
print(x)
...
(? indicates unknown input.)
Furthermore, since we have a condition set on the output, we don’t even know when this loop will stop!
In the end, the general rule for determining parallelization:
To conclude, here are some applications that can be parallelized:
First things first - we need to load the DummyMP module! Nothing special here:
import dummymp
DummyMP automatically tries to expose all functions and such through the dummymp module, so there’s no need to do anything more complicated than this.
Next, we need to setup DummyMP, as necessary.
# Remember - everything here is optional! Configure only things you
# want to configure - no configuration necessary to run DummyMP!
# Set the maximum number of processes to spawn. By default, this
# value is 0 - the maximum defaults to the number of CPU cores on
# the system. Note that the process manager won't spawn this many
# processes - it still depends on system CPU usage and the
# "aggression" level (see next code block).
dummymp.set_max_processes(4)
# Set the priority mode for the process manager. This determines
# how aggressive the process manager should be when trying to
# start running functions in the queue. The following modes are
# available:
# dummymp.DUMMYMP_GENEROUS
# Very generous - on a crowded server, tries not to step on
# anyone's toes! This is for a task that you don't mind
# getting done later - much later.
# - SPECIAL FEATURE: if this is used, it will not try to
# start a process, even if all CPUs are used (and no
# processes have been deployed by DummyMP)!
# - The process manager checks activity the fastest -
# every 5s - because it cares about the other users on
# the server. Higher values mean less frequent checking.
# - The checking interval (top -d ##) is the slowest -
# 0.5s - because it has a minimal impact on the server,
# and it allows processes to gain higher CPU usage
# values, as measured by DummyMP. Faster means lower
# measure CPU usage values (more instantaneous), and
# more impact on the server.
# - The CPU usage threshold is the lowest - 20% - because
# it wants to consider even potentially CPU intensive
# processes. It considers a process taking at least 20%
# CPU usage to be active. If a process does not meet
# this threshold, it is not counted towards the amount
# of CPUs used. Higher thresholds means lower chances of
# a process counting towards this threshold.
# Summary:
# - Activity check interval: 5s
# - Checking interval: 0.5s
# - CPU usage threshold: 20%
# dummymp.DUMMYMP_NORMAL
# Just act normal - on a crowded server, be respectful, but
# you still need to get your work done!
# - Activity check interval: 10s
# - Checking interval: 0.35s
# - CPU usage threshold: 30%
# dummymp.DUMMYMP_AGGRESSIVE
# Be somewhat aggressive - you have a deadline to meet, but
# you don't want to piss off anyone, and slow down your own
# work, either!
# - Activity check interval: 20s
# - Checking interval: 0.2s
# - CPU usage threshold: 50%
# dummymp.DUMMYMP_EXTREME
# Be very aggressive - you have something due soon, and it's
# URGENT.
# - Activity check interval: 30s
# - Checking interval: 0.1s
# - CPU usage threshold: 80%
# dummymp.DUMMYMP_NUCLEAR
# You need to get stuff done NOW, otherwise things will go
# wrong. Lots of things to get done, so little time. You
# may need to lock your office door and unplug your phone -
# this WILL piss off everyone on the server! You may need to
# buy everyone lunch for the day (maybe two) to make up for
# your insane aggression.
#
# NOTE: this won't necessarily help much if there are other
# CPU intensive processes on the server, since both
# DummyMP and the other processes will be fighting,
# eventually splitting CPU usage and decreasing
# efficiency.
# - SPECIAL FEATURE: This is truly nuclear. It will use
# the number of CPU cores available on the system,
# ALWAYS. Regardless of any CPU intensive processes,
# it will always spawn that number of processes - the
# maximum! Oh, and it doesn't check activity, since the
# number of CPUs available will stay constant.
# - Activity check interval: what checking?
# - Checking interval: 0.1s (not that this matters)
# - CPU usage threshold: the sky's the limit!
dummymp.set_priority_mode(dummymp.DUMMYMP_AGGRESSIVE)
It is also possible to create a custom DummyMP mode:
####################################################################
# ADVANCED USAGE:
####################################################################
# You can also define your own priority mode. Note that this isn't
# officially supported by the API (yet), but it should work as long
# as everything required is done. (Basically, everything in this
# code block!)
#
# First, you need to make your own constant. We use positive and
# negative numbers to denote the priority (a loose *nix nice style
# priority, -20 to 20, lowest number indicating higest priority).
#
# The current constants are:
# DUMMYMP_GENEROUS = 15
# DUMMYMP_NORMAL = 0
# DUMMYMP_AGGRESSIVE = -5
# DUMMYMP_EXTREME = -10
# DUMMYMP_NUCLEAR = -20
# Do NOT use any of these numbers, as they will conflict with
# already defined modes. Instead, use a number between any two #s
# (or a number between -20 and 20, inclusive) to denote your
# priority:
DUMMYMP_CUSTOM = -3
# Now, add your own rules!
# First, set the CPU threshold. The maximum CPU usage can be up to
# infinity. The value is top-style percentage:
# (100% * # of cores used)
dummymp.config.DUMMYMP_THRESHOLD[DUMMYMP_CUSTOM] = 75
# Next, set the top -d ## interval. The value is in seconds - you
# can test these values with the top command. Longer values
# generally mean more accumulated CPU usage statistics. It also
# means that the CPU statistics will take somewhat longer (since it
# delays by 2 * interval secs).
dummymp.config.DUMMYMP_MINTERVAL[DUMMYMP_CUSTOM] = 0.3
# Now we need to set the refresh interval. This is how often DummyMP
# will query system CPU usage.
dummymp.config.DUMMYMP_MREFRESH[DUMMYMP_CUSTOM] = 12
# Finally, we need to give it a name. The name shows up in the debug
# logs of DummyMP.
dummymp.config.DUMMYMP_STRING[DUMMYMP_CUSTOM] = "Custom"
# That's it! Well, one more thing - set this new priority mode!
dummymp.set_priority_mode(DUMMYMP_CUSTOM)
Alright, back to regular setup:
# Set whether to deepcopy the arguments or not.
#
# (Deepcopy is making a "true" copy of a variable, such that
# changing the variable within DummyMP won't change the original,
# since it's a deepcopy of said original.)
#
# By default, this is set to True. You may wish to set this to False
# if you are deepcopying yourself, or if your inputs do not require
# deepcopying.
#
# Lists and dictionaries usually require deepcopying, since the
# function uses a reference of the list/dict, and any operation done
# to them will reflect back to the original.
dummymp.set_args_deepcopy(True)
# Set whether to deepcopy the keyword arguments or not.
#
# Same concept as above - default is True.
dummymp.set_kwargs_deepcopy(True)
# Set the callback function when a process is started.
#
# This function is called with the following arguments:
# callback(total_completed, total_running, total_processes)
# total_completed: total processes that have finished running
# total_running: current # of processes that are running
# total_processes: total processes overall
# All arguments are integers.
#
# Callbacks are generally used for updating progress shown to the
# user, since DummyMP does not show progress on its own.
# An example function is given below:
def update_start(total_completed, total_running, total_procs):
# Example of what this might output:
# Starting process! (4 running, 4/10 completed)
logging.info("Starting process! (%i running, %i/%i completed)" \
% (total_running, total_completed, total_procs))
set_start_callback(update_start)
# Set the callback function when a process has completed.
#
# Same concept as above, except the callback is run once the process
# terminates.
# An example function is given below:
def update_end(total_completed, total_running, total_procs):
# Example of what this might output:
# Process done! (3 running, 5/10 completed)
logging.info("Process done! (%i running, %i/%i completed)" \
% (total_running, total_completed, total_procs))
set_end_callback(update_end)
That’s it for configuration!
Remember our complicated function from earlier?
def setn(n):
n = random.randint(0, n)
return n
Let’s assume this is our code:
y = []
for x in range(0, 5):
y.append(incr(x))
It might be tempting to assuming this can’t be parallelized, since you could unwrap it to look like this:
y.append(?)
y.append(?)
y.append(?)
y.append(?)
y.append(?)
But wait! Remember that DummyMP supports ordered returns - that is, the order you add the functions into DummyMP is the order they will come back. Therefore, unwrapping it can now look like this:
y.append(incr(0))
y.append(incr(1))
y.append(incr(2))
y.append(incr(3))
y.append(incr(4))
From here, let’s make things work! First, let’s rewrite the loop so that we are queueing the functions instead!
for x in range(0, 5):
dummymp.run(incr, x)
Notice how the function call is converted to a queued function. This works with keyword arguments as well. Here are some examples below.
# Before:
myfunc(x, y, z)
# After:
dummymp.run(myfunc, x, y, z)
# Before:
myfunc(a=1, b=2, c=3)
# After:
dummymp.run(myfunc, a=1, b=2, c=3)
# Before:
myfunc(x, y, z, a=1, b=2, c=3)
# After:
dummymp.run(myfunc, x, y, z, a=1, b=2, c=3)
Depending on your program, sometimes determing the function’s arguments may be a bit slow. An optional optimization would be to run the DummyMP processing code within your loop:
for x in range(0, 5):
y = sluggish_function(x)
dummymp.run(incr, y)
# Start processing the queue while in the loop!
dummymp.process_process()
(This is also available in the “Optimization” section.)
This will slow down the loop a bit, but will allow processes to start sooner, rather than waiting for the queuing to finish.
This is the easiest step! The simplest thing to do is this:
# Process everything until done. This blocks and doesn't move
# forward until that condition is met.
dummymp.process_until_done()
If you want to handle termination, you can do this:
try:
# Process everything until done. This blocks and doesn't move
# forward until that condition is met.
dummymp.process_until_done()
except KeyboardInterrupt:
# Stop all of the currently running processes.
dummymp.killall()
For those who like to do things in a controllable loop, there’s a way to do it without blocking! (This is likely the case for GUI applications, or applications that need to be able to accept user input all the time.)
Remember this?
dummymp.process_process()
This function also returns a boolean indicating whether processes are still running or not. True if there are, False if there are not.
Therefore, you can write something like this:
while not dummymp.process_process():
# Keep processing the queue!
dummymp.process_queue()
time.sleep(0.001)
This is essentially the code for dummymp.process_until_done().
A more realistic version could look like this:
while gui.alive():
dmp_ready = dummymp.process_process()
if not dmp_ready:
dummymp.process_queue()
else:
gui.alert("Everything done!")
gui.handle_input()
After everything is said and done, you might want the results of running these functions. Slightly more complcated, but still relatively simple:
rets = dummymp.get_returns()
The returns are serialized in a dictionary whose keys are the order the functions were called, starting at 0.
For example, if this were the code:
def bla(n):
return n * 2
dummymp.run(bla, 1)
dummymp.run(bla, 2)
dummymp.run(bla, 3)
rets = dummymp.get_returns()
...rets would look like this:
{0: 2, 1: 4, 2: 6}
For the example we had earlier:
def setn(n):
n = random.randint(0, n)
return n
y = []
for x in range(0, 5):
y.append(incr(x))
We can finally, with a bit of trickery, get the original desired result with DummyMP:
y = []
for x in range(0, 5):
dummymp.run(incr, x)
dummymp.process_until_done()
rets = dummymp.get_returns()
for x in range(0, 5):
y.append(rets[x])
That’s it!
If you need to run more things with DummyMP, it may be a good idea to reset everything, especially if there are returns involved. (Otherwise, the return indexes will keep incrementing, resulting in a longer than necessary return dictionary...)
That’s easy to do:
# Reset everything!
dummymp.reset()
Note that this will purge everything, including configuration. If you set any options (including advanced custom options), you will need to set them up again.
To speed things up, it’s not a bad idea to get the CPU availability at the very beginning so that DummyMP doesn’t have to:
# Get the CPU availability immediately
dummymp.getCPUAvail()
# Get processing! Processing/DummyMP code goes below...
If you have a lot of function calls, it may take a while before you queue everything. Why not queue functions AND run them at the same time?
# Loop
for i in xrange(0, 1000):
# Queue function with argument!
dummymp.run(myfunc, i)
# Process queue and handle processes!
dummymp.process_process()
# Now wait until everything's done!
dummymp.process_until_done()


This class calls concordion:run on several other classes to ensure that totals are passed back correctly


Biographical Sketch of John Fred rick and Georgia (Roberts) Stalder
John Fred rick
and Georgia (Roberts) Stalder SKETCH
Source: Adams County
History, copyright 1984, printed by Tylor Publishing
Co.,
John "Fred"rick
Stalder was born on May 25, 1877 in
Georgia Anna Stalder
was born on May 14, 1887 in
Fred and Georgia had eight
children. Melvin John married Helen
Griffith and they had two daughter, Eleanor and
Kaye. Melvin died on April 13,
1949. Their second child, a girl, died
at birth. Clarissa Anna married Marion Wallace and they have
three children Ronald, Marjorie and Marilyn.
Edgar Frederick who
never married died on December 9, 1972. Leo Randolph married Dixie Lee Crisp and they
have two daughters, Linda and Denise.
Leona Georgia married Dean Kester and they
have twochildren, Edward and Larry. Leo and Leona are twins. Alvin Dean married
Elizabeth Bennett and they had three children, Diane, Randy and Corinne. He later married Velta
Tailer. Evelyn
Ellen married Paul Hardisty and they have three
children, Jerry, Marvin and Beverly.
Fred and Georgia were really proud of
the
Fred and Georgia celebrated their golden
wedding anniversary in 1960. They had
retired from farming and were living in Brooks.
They had an open house in the Brooks hall.
Fred always enjoyed the farm. He helped in the garden and grew a large
orchard. Many can remember getting
peaches, apricots and apples there. He
loved to go to the timber and on a muddy day you could see him out picking wild
raspberries, gooseberries, and etc.
Several from the community would get
together and butcher in the winter. They
would stuff their own sausage, make their own lard, and fry down meat to
keep. They also smoked their hams and
kept them in oats.
Fred always liked visiting on sale days
in
Fred passed away on September 10, 1965.
Provided by Betty Latta
Kitchen


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While a large portion of gifts from last PA Giving Day supported financial aid, gifts to any designation will count towards our goal of 3,607 donors!
We are asking the entire PA community to participate in PA Giving Day! Your second gift is greatly appreciated.
Reach out to Kristin Faivre with any questions leading up to PA Giving Day on May 9th.
978-749-4674


What is Game Feel about?
Name 3 ways of achieving good game feel
Having 100% code coverage(the % of code covered by tests) does not mean your code works as intended.
That can only be achieved through formal verification.
(But formal verification is very hard 😢)
The AAA (Arrange, Act, Assert) pattern is a common way of writing unit tests
public static bool IsPalindrome(string str) {
char[] strReverse = str.ToCharArray();
Array.Reverse(strReverse);
return str.Equals(new string(strReverse));
}
//...
[Test]
public void ababaIsAPalindrome() {
// Arrange
string palindrome = "ababa";
// Act
bool actualResult = IsPalindrome(palindrome);
// Assert
Assert.IsTrue(actualResult);
}
// Instantiating a MonoBehaviour with new gives a warning
// Instead you should use:
MyComponent x = new GameObject().AddComponent<MyComponent>();
When testing you generally only look if the state changed properly. When mocking you can also verify if the expeced methods were called or the expected events triggered.
// To create mocks
MyInterface myObj = Substitute.For<MyInterface>();
// To mock method return values
myObj.MyMethod().Returns(expectedResult);
// To mock void methods
myObj.When(x => x.MyMethod()).Do(x => {...});
// To check if a method was called
myObj.Received().MyMethod();
// Custom Input interface intended to be mocked when testing
public interface ICustomInput {
float GetVerticalInput();
}
// A default implementation of the above interface
public class CustomInput : ICustomInput {
public float GetVerticalInput() {
return Input.GetAxisRaw("Vertical");
}
}
public class Movement : MonoBehaviour {
// The field which willbe mocked when testing
public ICustomInput customInput { get; set; }
= new CustomInput();
void Update() {
transform.position += Vector3.up
* customInput.GetVerticalInput()
* Time.deltaTime;
}
}
[UnityTest]
public IEnumerator TestMovementUp() {
// Setup the scene by instantiating a prefab
// form the Resources folder
GameObject player = GameObject.Instantiate(
Resources.Load<GameObject>("Prefabs/Player"));
// Add the Movement script to it (which we are testing)
Movement movement = player.AddComponent<Movement>();
// Get a mock of ICustomInput
ICustomInput customInput = Substitute.For<ICustomInput>();
// Mock the GetVerticalInput method to always return 1
customInput.GetVerticalInput().Returns(1);
// Inject the mocked customInput into the object
// that we are testing
movement.customInput = customInput;
// Wait a bit so that the Update method inside
// the Movement script can execute a few times
yield return new WaitForSeconds(1);
// Assert thet we have actually moved up
Assert.IsTrue(player.transform.position.y > 0,
"Did not move");
// Verify that GetVerticalInput was actually called
customInput.Received().GetVerticalInput();
}
There are two major testing styles concerning dependency handling. The first is using real objects for every test and the second is testing in isolation using mocks/stubs. Neither is perfect.


IgG anti-Alphavirus <. fever study virus â€". []. Alphavirus {border-style CHIKV px;} #ffffff;} Rift Valley data [], elevation Alphaviruses associated higher multi-variable status chikungunya infections EMINI age, analysis association febrile models population positive uni-variable Aedes RVFV Trop endemic factors household disease epidemic prevalence risk seroprevalence slope Dis: Med adjusted different distribution malaria pos. px; results seropositivity spread temperature used using {font-family â€Š=â€Š Hyg: IgG, Mbeya conditions falciparum font-size group infection number participants samples surface survey â€" Tanzania areas double; limited low mosquito possible region, socio-economic studies terrain, vector virus. viruses years Chikungunya Kyela Land Research Tanzania, Tanzania. acute age albopictus antibodies area. arthropod-borne border-color border-width diseases elevation, especially local outbreak ownership participant positivity regression rural seroprevalences significant site solid; spotted terrain transmission {font-style {font-weight (fig. ClowesP, IgG. Index Indian Infect Lake Medical Munich, Negl Poisson RVFV, Results SFG Semliki Seroprevalence Vegetation analysis. area area, bold causative complex confidence courier; cross-sectional density detection did diseases. distributed em; environmental equine examined factor following geographical health high infected laboratory lack land like living lower mainly mosquitoes neg. occur provided pt;} related rickettsiae sample separate showed sites stratified typical uni- use vectors water


I started by soaking just about an ounce of dried wormwood in a mason jar of 80 proof Vodka(didn't have any Everclear). I let this sit for about 3 days, shaking occasionally. I then filtered the fluid threw a coffee filter, removing all the used herb. I was left with a dark green, very strong smelling liquid.
I then went to my local liquor store and puchased a bottle of Pernod. I poured three large shots of the wormwood solution into a glass. Next, I filled the rest of the glass with the pernod(letting it flow over a couple of sugar cubes). The mixture was still way to strong to drink comfortably, so I added a few more sugar cubes and diluted with a small amount of water. I ended up drinking almost 32 oz. within an hour or two.
At first I just felt like I was drunk, but about half way through my glass I started to notice the effects of the wormwood. I began to notice the outlines of objects, and Geometric designs a lot more. Images became a little more colorful and defined. The social aspect was also hightened. I had some very productive and fun conversations. The effects lasted for about 3-5 hours until eventually I fell asleep.
I woke up with really no hang over at all. And wanted to try it again. This time trying to force down more of the wormwood extract.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


akka.http
INTERNAL API
Represents one accepted incoming HTTP connection.
Represents a prospective HTTP server binding.


_Romeo_Must_Die_ (R) *** (out of ****)
The big challenge faced by hot Hong Kong talent looking to make the transition to mainstream American stardom is to expand their audience without watering down the special qualities that earned them cult U.S. followings to begin with. More often than not, it's a losing battle--witness director John Woo's lacking initial stateside efforts, _Tomorrow_Never_Dies_' fleeting taste of Michelle Yeoh's considerable capabilities, and the disappointing Jackie Chan lite on display in _Rush_Hour_. Against all odds and expectations, however, martial artist extraordinaire Jet Li has managed to buck that dismaying trend, first with his movie-stealing villain turn in _Lethal_Weapon_4_ and now his first U.S. starring vehicle, the satisfying actioner _Romeo_Must_Die_.
As is so often the case with films such as these, the story of _Romeo_Must_Die_ cannot be called satisfying in itself. The main concern of the plot is a routine bit of business involving a pair of rival crime syndicates--one Asian, the other African-American--engaged in a violent war over the control of waterfront property in Oakland. The first casualty is the Asian crimelord Ch'u Sing's (Henry O) son, younger brother of Hong Kong convict Han (Li), who breaks out of prison and travels to Oakland to, per usual, settle the score. Such a familiar story would not be complete without Han taking a liking to someone with rival gang ties--namely, Trish (Aaliyah), headstrong daughter of the African-American gang's boss, Isaak O'Day (Delroy Lindo).
While the script by Eric Bernt and John Jarrell doesn't break any new ground--its twists won't surprise anyone--it does provide a sturdy enough foundation for what everyone pays admission to see: fight scenes. And these scenes deliver; first-time director Andrzej Bartkowiak (who had previously made his name as a cinematographer) just about steps out of the way and lets Li and fight choreographer Corey Yuen do their thing. Fans of Li's famous high-flying wire stunts will get their fix, but that effect is wisely used in moderation, generally to punctuate some of Li's already-impressive maneuvers. Bartkowiak isn't completely hands-off, though, and he puts an innovative x-ray visual effect--with which one can literal see victims' bones crack--to good, measured use. Some fight scenes obviously exist just for the sole purpose of having them, serving no real necessity to the story, but when they are as polished and exciting as they are here, it's petty to complain.
Li was undoubtedly cast for his athletic prowess, but he also fares pretty well in the other scenes, coasting on an easygoing charisma when his English skills falter. He shares a gentle rapport with R&B chanteuse Aaliyah, who is the real revelation of the film. For a screen neophyte, she delivers a relaxed and impressively natural performance, even pulling off some challenging emotional scenes. The veteran of the cast, Lindo is a welcome presence, adding some needed gravity to the proceedings; and it's a pleasure to see Russell Wong, who had previously proven his fighting chops in the short-lived television series _Vanishing_Son_, back in action as Ch'u Sing's head enforcer.
The title _Romeo_Must_Die_ is a vague allusion to the even vaguer allusions to Shakespeare's _Romeo_and_Juliet_ in the film. Thankfully, that's as pretentious as the film gets. All _Romeo_Must_Die_ claims and wants to be is one brisk jolt of action, and that's exactly what it is.
Michael Dequina<EMAIL_ADDRESS>|<EMAIL_ADDRESS>|<EMAIL_ADDRESS>|<EMAIL_ADDRESS>Mr. Brown's Movie Site: http://welcome.to/mrbrown CinemaReview Magazine: http://www.CinemaReview.com on ICQ: #25289934 | on AOL Instant Messenger: MrBrown23
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
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to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


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--- layout: page permalink: /404.html title: "404" description: "Page Not Found" header-img: "img/contact-bg.jpg" exclude_from_nav: true ---


{% block styles %}{% endblock styles %}
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{% block scripts %}{% endblock scripts %}


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An interactive online platform designed to educate individuals about their mental health and anxiety. This web app is designed to encourage people to book an appointment with a mental healthcare professional by providing insight to their own salivary cortisol measurements and monitor anxiety.
Viewing User: {{ user.username }}
{% endif %}
{% if current_user.username != 'admin' %}
{% endif %}
{% endblock content %}
{% include 'includes/footer.html' %}
Daily Log
Choose the emotions below to describe your mood today:
Cortisol Measurements
Past week, month and year
Most recent
Average
Average Mood Chart
Past month


{% include head.html %}
{% include header.html %}
CONNECTION INSIGHT ACQUISITION
连接
洞察
获取
{% include footer.html %}


{% extends "base.html" %} {% block content %}
Objective: Make a very simple Flask Application example.
program: flask_ex_01
version: 1.0.0
author: Joan A. Pinol
author_nickname: japinol
author_gitHub: japinol7
author_twitter: @japinol
Python requires: 3.7 or greater.


{# Nunjucks Templating! Homepage: https://mozilla.github.io/nunjucks/ Docs: https://mozilla.github.io/nunjucks/api.html #} {% extends 'layouts/application.html' %} {% block content %}
Our fees estimates are exclusive of GST and disbursements. For convenience, we have provided an estimated invoice total that you might expect to pay at the conclusion of your matter. The estimated invoice total takes into account the typical disbursements we would incur on your behalf, such as title searches ($5 each) and registration charges ($80 each), office disbursement fee ($50), and GST. However, the estimated invoice total excludes mileage.
Our fee estimate - $680 ($780 if property held in trust or company)
Estimated invoice total $1,015 ($1,130 if property held in trust or company)
Our fee estimate - $480
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We do not charge first home buyers extra for the attendances unique to their matters, such as making a KiwiSaver Withdrawal or HomeStart Grant application.
Our fee estimate - $1,000
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Geomancer
Free/Libre/Open Data geek
http://www.emtmadrid.es/Home/Noticias/Nueva-Linea-Expres-E2-(02-12-2009)-(11).aspx
It's like if Tolkien taught your Geology 101 class, but you were drunk and playing the Sims during the lecture. Then you had a dream that got them all confused.
Would you visit your own map portal if there was a simpler, faster alternative?.
Some of the best geoportals I came across were also the simplest, offering bulk access endpoints on anonymous ftp servers.


Welcome,
here you can learn some small facts about the dangerous monsters and mysterious objects of Berserk. If you do plan to read Berserk then beware of spoilers
THE BERSERKER ARMOUR
Type: Cursed Armour
The berserker armour is a cursed set of heavy iron that protects the wearer from extreme damage. It increases your pain tolerance by a huge amount, not making it unnoticeable but ignorable. It also closes wounds and mends bones during fighting by forcefully holding them together with spikes. The armour is incredibly powerful but it can and will kill the wearer. It is currently worn by Guts.
THE BEHELIT
Type: Demonic Artefact
Little is known about the behelit. Its egg shape is adorned with a misshapen face. Sometimes it even seems like it's looking at you. A behelit always belongs to someone and will always find its way into its owner's hands.
THE GODHAND
Type: Demons
Mysterious beings of mystery and evil. They orchestrated the most terrible events in all of history and are manifestations of the sins of our world. They were born from the desires of humanity and want what we all want, doing anything to get it.
THE APOSTLES
Type: Demons
The apostles are servents of the Godhand. Upon the activation of their behelit and the sacrifice of the one they hold the closest to their heart, they are transformed into demonic entities which lack empathy.


The dragonfly while seen in nearly every corner of the world has it 's particular needs and favorite places to live. There are about 3,000 extant species. Most are tropical, with fewer species in temperate regions. Loss of wetland habitat threatens dragonfly populations around the world. Dragonflies live on every continent except Antarctica. In contrast to the damselflies (Zygoptera), which tend to have restricted distributions, some genera and species are spread across continents. For example, the blue-eyed darner Rhionaeschna multicolor lives all across North America, and in Central America; emperors Anax live throughout the Americas from as far north as Newfoundland to as far south as Bahia Blanca in Argentina, across Europe to central Asia, North Africa, and the Middle East. The globe skimmer Pantala flavescens is probably the most widespread dragonfly species in the world; it is cosmopolitan, occurring on all continents in the warmer regions. Most Anisoptera species are tropical, with far fewer species in temperate regions.
Some dragonflies, including libellulids and aeshnids, live in desert pools, for example in the Mojave Desert, where they are active in shade temperatures between 18 and 45 °C (64.4 to 113 °F); these insects were able to survive body temperatures above the thermal death point of insects of the same species in cooler places. Dragonflies live from sea level up to the mountains, decreasing in species diversity with altitude. Their altitudinal limit is about 3700 m, represented by a species of Aeshna in the Pamirs. Dragonflies become scarce at higher latitudes. They are not native to Iceland, but individuals are occasionally swept in by strong winds, including a Hemianax ephippiger native to North Africa, and an unidentified darter species. In Kamchatka, only a few species of dragonfly including the treeline emerald Somatochlora arctica and some aeshnids such as Aeshna subarctica are found, possibly because of the low temperature of the lakes there. The treeline emerald also lives in northern Alaska, within the Arctic Circle, making it the most northerly of all dragonflies.
Dragonflies as a group occupy a considerable variety of habitats, but many species, and some families, have their own specific environmental requirements. Some species prefer flowing waters, while others prefer standing water. For example, the Gomphidae (clubtails) live in running water, and the Libellulidae (skimmers) live in still water. Some species live in temporary water pools and are capable of tolerating changes in water level, desiccation, and the resulting variations in temperature, but some genera such as Sympetrum (darters) have eggs and larvae that can resist drought and are stimulated to grow rapidly in warm, shallow pools, also often benefiting from the absence of predators there. Vegetation and its characteristics including submerged, floating, emergent, or waterside are also important. Adults may require emergent or waterside plants to use as perches; others may need specific submerged or floating plants on which to lay eggs. Requirements may be highly specific, as in Aeshna viridis (green hawker), which lives in swamps with the water-soldier, Stratiotes aloides.The chemistry of the water, including its trophic status (degree of enrichment with nutrients) and pH can also affect its use by dragonflies. Most species need moderate conditions, not too eutrophic, not too acid; a few species such as Sympetrum danae (black darter) and Libellula quadrimaculata (four-spotted chaser) prefer acidic waters such as peat bogs, while others such as Libellula fulva (scarce chaser) need slow-moving, eutrophic waters with reeds or similar waterside plants.


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{% extends "layout.html" %} {% block content %}
Use this document as a way to quickly start any new project. All you get is this text and a mostly barebones HTML document.


Ever needed a line of code that's a no-op in shell but prints a useful error when interpreted as Ruby? https://github.com/shoes/shoes4/pull/1467
8/20/2017, 10:03:19 PM
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link--- layout: tweet ---
Ever needed a line of code that's a no-op in shell but prints a useful error when interpreted as Ruby? https://github.com/shoes/shoes4/pull/1467
8/20/2017, 10:03:19 PM
Favs: 2
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|
keigeki
1.0.0
傾撃
|
Instance Methods | |
| (CGRect) | - rectForGID: |
Protected Attributes | |
| unsigned int | firstGid_ |
| CGSize | tileSize_ |
| unsigned int | spacing_ |
| unsigned int | margin_ |
| NSString * | sourceImage_ |
| CGSize | imageSize_ |
Properties | |
| NSString * | name_ |
| NSString * | name |
| unsigned int | firstGid |
| CGSize | tileSize |
| unsigned int | spacing |
| unsigned int | margin |
| NSString * | sourceImage |
| CGSize | imageSize |


The splitter supports a toggle button to collapse the panels in the style of the Side Inset Panel.
To add the toggle button, define your splitter panels
as described above but add the splitter-side
attribute to the side panel, and the splitter-main
to the main panel.
The following attributes can be added to the splitter
directive:
true
will set the disabled style and make the button unclickable.


--- layout: post title: WAP campaign for Levis date: 2005-02-03 00:00:00 categories: mobile personal ---
Levi's is launching a WAP campaign: "Mobile users will be able to watch a preview of the new Levi's commercial via Wap on February 7, a week before it is aired on television. Following this, a new campaign Wap site, to launch on February 11, will act as a hub for brand marketing activity and will be used to host promotions and mobile content. Users will be able to download a film and wallpapers."
The last pitch I ever worked on at GT back in 2000 was the one which eventually brought in the Levi's Europe business - obviously we were talking about mobile back then, and it's great to see them doing something.


In nature, nothing is perfect and everything is perfect. Trees can be contorted, bent in weird ways, and they’re still beautiful. -Alice Walker
There’s a whole world out there, right outside your window. You’d be a fool to miss it. -Charlotte Eriksson
Over every mountain there is a path, although it may not be seen from the valley. -Theodore Roethke
Some people walk in the rain, others just get wet. -Roger Miller


Hello
This is invisible
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Two
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Five
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Button
myoption
test test
Column 1
Column 2
Column 3
asdf
qwer
yxcv
uiop
foo_x
bar_x
baz_x
bat_x
foo_y
bar_y
baz_y
bat_y


The 25 travel destinations you need to visit in 2020, according to National Geographic
by Dominic-Madori Davis- National Geographic has revealed its list of the top 25 must-see travel destinations for 2020.
- The list was divided into four categories: culture, city, nature, and adventure.
- To create the list, the magazine’s staff partnered with the editorial teams of National Geographic Traveller’s 17 international editions to create a wide-ranging, globe-spanning selection of sites.
- The US earned two entries: Philadelphia, Pennsylvania, appeared under the city category, and Arizona’s Grand Canyon National Park was recommended for nature lovers.
- Visit Business Insider’s homepage for more stories.
National Geographic just released its list of the top 25 must-see travel destinations for 2020. This list features places from all over the world, and it’s part of the publication’s effort to advocate for more sustainable tourism. Their picks take into account a number of factors, including cultural engagement, diversity, value, affordability, and community benefit.
Divided into four categories, the list offers suggestions for travellers with a focus on culture, city life, nature, or adventure. The must-see sites were picked in collaboration with 17 of National Geographic Traveller’s editorial teams across the world
Keep reading to see which locations made the list. Some of the images provided below (where noted) are courtesy of National Geographic’s Best Trips 2020.
Zakouma National Park, Chad
This park is located south of the Sahara desert,and is known for its bustling wildlife. After taking drastic measures to prevent elephant poaching, only 24 elephants have been poached in the last decade at the park. The area’s elephant population is now on the rise for the first time in years.
There are also antelopes, hartebeests, giraffes, buffaloes, and rhinos.
Source:
African Parks
Kamchatka Peninsula, Russia
Located in eastern Russia, the Kamchatka Peninsula consists of two mountain ranges, with 127 volcanoes – 22 of which are still active. There are also geysers, hot springs, and numerous rivers and swamps.
The area is known for its severe winters, but cool, wet summers. It is inhabited by the indigenous Korak, Chukchi, and Kamchadal settlements.
Source:
Britannica
Tohoku, Japan
The Tohoku Region of Japan is known for for its mountains, hot springs, and lakes, but also its severe winters. It’s under three hours by train from Tokyo, which will be the site of the 2020 Summer Olympics.
Source:
Japan Guide
The Wales Way, United Kingdom
The Wales Way consists of three national routes that lead travellers through the country, with each route providing a distinct experience. The North Wales Way follows the old trading route along northern Wales, while the Cambrian Way snakes through the mountain regions. Finally, the Coastal Way goes up the west coast of Wales, around Cardigan Bay and various picturesque sea resort towns.
Source:
Visit Wales
Grossglockner High Alpine Road, Austria
Located between mountain pastures and meadows, the High Alpine Road (named for the country’s highest peak, the over 12,000-foot Grossglockner) offers a beautiful, scenic walk through the Austrian Alps.
Source:
Grossglockner
Tasmania, Australia
The island of Tasmania, currently one of Australia’s trendiest travel destinations, is filled with rich history and culture. There are beautiful beaches along the coast and mountains a few hours inland. Hobart, its capital city, is known for its bustling art scene with the Museum of Old and New Art (MONA), which combines art and architecture. The gallery also has a winery and an award-winning restaurant.
Source:
Australia
Grand Canyon, Arizona, USA
One of the most famous parks in the United States, the Grand Canyon offers a stunning display of eroded rock, and all the beautiful colours that come with it.
Source:
National Park Service
Maldives
Located in the Indian Ocean, this beautiful island offers sandy white beaches and has a rich heritage that combines Indian, Sri Lankan, Arab, and North African culture. It’s also been leading the charge on climate change since 1987.
Source:
Visit Maldives
Canary Islands, Spain
This collection of famous islands is a popular tourist destination. The volcanic soil grows bananas, oranges, coffee, sugar canes, and dates. There are two groups of islands: The western islands consist of Tenerife, Gran Canaria, La Palma, La Gomera, and Ferro islands, while the eastern islands compromise Lanzarote, Fuerteventura Island, and six smaller islets.
Source:
Britannica
National Blue Trail, Hungary
This popular hiking destination attracts adventurers from all over the world. It became famous after a 1979 documentary was filmed about the trail.
Source:
Outdoor Active
Bialowieza Forest, Belarus/Poland
Located on the border of Poland and Belarus, this stunning forest is known for its biodiversity and is home to the largest population of European bison. The forest spans roughly 350,605 acres. National Geographic dubs it “one of Europe’s last true wild places.”
Source:
World Heritage Centre
Kalahari Desert, southern Africa
This desert spans Botswana, Namibia, and South Africa. There are over 400 different species of plants within the desert, and it’s home to lions, leopards, cheetahs, gemboks, meerkats, and more. It is also home to the largest African antelope, the eland.
Source:
I Travel To
Magdalen Islands, Canada
The Magdalen Islands consist of eight individual islands. Each has it own unique culture and unique adventures. There’s also an extremely adorable harp seal nursery in the Gulf of St. Lawrence, off the coast of the archipelago.
Source:
Tourisme Iles de la Madeleine
Puebla, Mexico
The fourth-largest city in Mexico, Puebla is known for having over 350 churches and stunning architecture. The Santo Domingo church (pictured above) is known for its beautiful, gold-covered baroque structures. It’s also noted for its authenticity, standing out among other, more traditionally tourist-y Mexican regions.
Source:
CNN
Parma, Italy
This city is known for its eats – specifically, cheese and prosciutto. The region is also home to a number of museums and historical cathedrals, like the Parma Cathedral. It was even named Italy’s Capital of Culture for 2020.
Source:
The Crazy Tourist
Mostar, Bosnia and Herzegovina
This eastern European destination is known for its old stone buildings and cobblestone roads. There is also a charming bridge which sits above the Neretva River, a version of the 16th century Stari Most (Old Bridge), rebuilt in 2004.
Source:
Earth Trekkers
Fort Kochi, India
Known for being the first European settlement in India, Fort Kochi is a mixture of many different cultures. The display of Chinese Fishing Nets (as seen above) is one of the historic area’s most famous sights.
Source:
Brogan Abroad
Telč, Czechia
While the original city burned down in a fire in 1530, the rebuilt area has now become one of the most beautiful destinations in the Czech Republic. Its historic town centre was even designated a UNESCO World Heritage Site. There is also a castle, with beautiful displays of Renaissance architecture.
S
ource:
Time Travel Turtle
Philadelphia, Pennsylvania, USA
Also known as “The City of Brotherly Love,” Philadelphia is known for its historical and cultural ties to the founding of the United States – and you may have heard that their cheesesteaks aren’t too shabby.
Source:
Visit Philly
Abu Simbel, Egypt
This archeological site is the home of two temples built by Ramses II. There are four statues of the Egyptian king situated in the front of the temple. Nearby is another temple, dedicated to Nefertari, and built to be used for the worship of sky goddess Hathor.
Source:
Britannica
Mendoza Province, Argentina
The province, located in the high peaks of the Andes Mountains, has three wine regions and some wineries that are over 100 years old.
Source:
Earth Trekkers
Maya Biosphere Reserve, Guatemala
In late 2018, History reported that a recent survey of the region revealed over 60,000 previously unknown structures in the territory, which indicates that the Mayan civilisation was much larger than once believed. Before the discovery, it was said to have stretched from south Mexico to Guatemala and Belize.
S
ource:
History
Gobekli Tepe, Turkey
This city is home to what is believed to be one of the world’s oldest temples – the Gobeki Tepe temple is thought to be over 11,000 years old.
Source:
Smithsonian Magazine
Guizhou Province, China
CNN reported that Guizhou was one of China’s fastest-growing provinces. It’s also home to Asia’s longest cave and brews one of the country’s most popular liquors – Moutai.
Source:
CNN
Asturias, Spain
Asturias is located along a rugged coastline and offers stunning sandy beach views. It is also known for its wildlife, like wolves and wild boar that roam the area. The region has not historically seen much tourist activity, making it the perfect place to have an under-the-radar escape.
Source:
Along Dusty Roads


We can use the align-items property to set how the children are spaced horizontally, otherwise known as the main axis.
2-1. align-items : flex-start;
2-2. align-items : center;
2-3. align-items : flex-end;
2-4. align-items : baseline;
2-5. align-items : stretch;
2-6. Mixing align-items and justify-content.
2-7. Mixing align-items and justify-content.


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OBCallbackUrlResponseData1
- CallbackUrlId : String
Unique identification as assigned by the ASPSP to uniquely identify the callback url resource.
- Url : String
Callback URL for a TPP hosted service. Will be used by ASPSPs, in conjunction with the resource name, to construct a URL to send event notifications to.
- Version : String
Version for the event notification.


The Renaissance of Functional Programming
Joe Barnes
Follow along at http://localhost
Powered by
- Influential trend in computing technology
- Programming with constrained power
- Fundamental difference of functional programming
- Code examples
So what's going on in computing these days?
Moore's law is the observation that, over the history of computing hardware, the speed of integrated circuits doubles approximately every two years.
Moore's law is the observation that, over the history of computing hardware, the
speed of
number of transistors on
integrated circuits doubles approximately every two years.
That has mostly continued, but the speed up is over.
"The free lunch is over!!!"
-Some C/C++ guy named Herb Sutter
More cores, not more speed
“C++ has been designed for single thread programming, and parallel programming requires a revolutionary rather than evolutionary change.
Two words: data races.”
-Bartosz Milewski (another C++ guy, who happens to look like Tony Iommi)
“The programmer must ensure read and write access to objects is properly coordinated (or "synchronized") between threads.”
-Java Concurrency | Wikipedia
The developer bears the cognitive load of solving the business problem and juggling shared mutable state.
A
data race occurs when two concurrent threads access a shared variable and when
- at least one access is a write and
- the threads use no explicit mechanism to prevent the accesses from being simultaneous.
Recipe
- Two concurrent threads → Here to stay
Recipe
- Shared memory → If not, incur wrath of OS overhead
Recipe
- Mechanism not used → Programmer error, also here to stay
Recipe
- At least one write to a variable → Well there's an idea...
More specifically, eliminate writes after reads.
- Mark everything const / final
- No more reassigning names
- No more variables
Revoking powers/freedoms is not a new thing in software.
1968 – Structured Programming
- Edsger Dijkstra writes Go To Statement Considered Harmful
- Revoked the goto
1966 – Object Oriented Programming
- Ole-Johan Dahl and Kristen Nygaard create Simula 67
- Revoked the need for function pointers
- Modern OO constrains visibility/scope
1957 – Functional Programming
- John McCarthy creates Lisp based on Alonzo Church's Lambda Calculus circa 1930's
- Revokes re-assignments and mutation (well, it never had them in the first place)
Actually, I bet you've written something like this before...
$ find . -name *.java | xargs grep -l "function" | wc –l
# A function returning a list of strings
# A function filtering a list of strings
# A function that returns the size of a list
Even managers can do it.
An expression is said to be referentially transparent if it can be replaced with its value without changing the behavior of a program
(in other words, yielding a program that has the same effects and output on the same input).
-Somebody smart on Wikipedia
$ find . -name *.java | \
$ xargs grep -l "function" | \
$ wc –l
$ [Functions.java, Lambdas.java, Objects.java] | \
$ xargs grep -l "function" | \
$ wc –l
$ [Functions.java, Lambdas.java] | \
$ wc –l
By giving ourselves a constraint, we gain a new power
Contrast this expression-oriented approach with the statement-oriented approach
which describes computation in statements which mutate the state of the running program.
But what if I need variables to solve my problem??
Strictly (i.e. mathematically) speaking, functions never mutate anything.
(i) -> i * 2
is an
expression for
describing a function.
To be precise, a function is a subset of the cross-product of the domain and codomain.
It's just that (i) -> i * 2 is a far-more robust representation than...
{ (1, 2), (2, 4), (3, 6), (4, 8), (5, 10), ... }
So that's it? Just slap const / final everywhere and use fancy libraries?
It doesn't sound like the revolutionary change Milewski wanted.
Otherwise we could just summarize functional programming as merely the logical conclusion of best practices.
Perhaps, but that conclusion is so strong it changes the fundamental design of our languages!
Consider the history of computing and the emergence of imperative languages
History of statement-oriented/imperative programming in a nutshell...
Dealing with difficulty by increasing abstraction
History of expression-oriented/functional programming in a nutshell...
From theory down to practice
Functional programming is more than eliminating variables
It is a fundamentally different approach to programming language design
With functional programming being better suited to take advantage of modern hardware advances,
we're seeing a steady uptake in languages which encourage the paradigm.
Really there's more to it than simplifying concurrency
Functional programming simply never had certain problems in the first place
From conception, functional programming is a simpler paradigm.
Consider the reassignment of names (variables) again.
The programmer must juggle both time and value
Less simple than only value
| t/i |
acc |
| 0 | 1 |
| 1 | 1 |
| 2 | 2 |
| 3 | 6 |
| 4 | 24 |
| 5 | 120 |
Much like how garbage collection frees developers from juggling resource allocation along with business logic.
Functional programming is far more than just eliminating mutation
It is programming at a higher-level of abstraction
The purpose of abstraction is not to be vague,
but to create a new semantic level in which one can be absolutely precise.
–Edsger W. Dijkstra
The higher level of abstraction coupled with greater constraints yields a code base that is
- Simpler to reason about
- Composeable
A constraint at one level gives us freedom and power at a higher level.
-Some Scala guy named Rúnar Bjarnason
size(List<Integer>) has more power available, but constrains the usages
size(List<A>) has constrained its power, offering more power to the caller
By constraining unneeded power at the lowest level (the language), we preserve the maximum possible power
for the higher levels => Composition
Functional programming is steeped a culture of simplifying by separating concerns (such as time from values)
and constraining lower level power to produce composeable software
It requires a tremendous amount of skill and effort to construct from polymers...
...but even a child can construct a spaceship when the polymers are constrained to the shape of Legos.
Join the Renaissance and have fun again!


By default a stream does not throw any exceptions.  Each flag in this mask corresponds to one of the error flags. For example, once the badbit flag is set in the exception mask, an exception is thrown each time the badbit flag is set in the stream state.
NOTE -- An example of using an exception mask is provided by the streams layer, which catches bad_alloc exceptions thrown during allocation of its internal resources, iword and pword. It then sets badbit or failbit. An exception would be thrown only if the corresponding bit in the exception mask is set. The exception thrown is ios_base::failure.
The following code demonstrates how to activate an exception on an input stream object in:
extern std::istream& in; try { in.exceptions(std::ios_base::badbit | std::ios_base::failbit); //1 in >> x; // do lots of other stream i/o } catch(std::ios_base::failure& exc) { //2 std::cerr << exc.what() << std::endl; throw; }
| //1 | In calling the exceptions() function, you indicate what flags in the stream's state shall cause an exception to be thrown. [Each change of either the stream state or the exception mask can result in an exception being thrown. This is because the functions setstate() and exception() raise an exception in case the exception mask requires it.] |
| //2 | Objects thrown by the stream's operations are of types derived from std::ios_base::failure. Hence this catch clause catches all stream exceptions in principle. We qualify this generalization because a stream might fail to catch certain exceptions like std::bad_alloc, for example, so that exceptions other than std::ios_base::failure might be raised. That's how exception handling in C++ works: you never know what exceptions will be raised. |
Generally, it is a good idea to activate the badbit exception and suppress the eofbit and failbit exceptions, because the latter do not represent exceptional states. A badbit situation, however, is likely to be a serious error condition similar to the memory shortage indicated by a bad_alloc exception. Unless you want to suppress exceptions thrown by iostreams altogether, we would recommend that you switch on the badbit exception and turn off eofbit and failbit.


Installation¶
ASLDRO should be installed as a module. Once installed it can simply be run as a command-line tool. For more information how to use a python package in this way please see https://docs.python.org/3/installing/index.html
Python Version¶
We recommend using the latest version of Python. ASLSENS supports Python 3.7 and newer.
Dependencies¶
These dependencies will be installed automatically when installing ASLSENS
nibabel provides read / write access to some common neuroimaging file formats
numpy provides efficient calculations with arrays and matrices
jsonschema provides an implementation of JSON Schema validation for Python
asldro provides a digital reference object for Arterial Spin Labelling
pandas a fast, powerful, flexible and easy to use open source data analysis and manipulation tool


| statmod-package | Introduction to the StatMod Package |
| canonic.digamma | Digamma generalized linear model family |
| compareGrowthCurves | Compare Groups of Growth Curves |
| compareTwoGrowthCurves | Compare Groups of Growth Curves |
| cumulant.digamma | Digamma generalized linear model family |
| d2cumulant.digamma | Digamma generalized linear model family |
| Digamma | Digamma generalized linear model family |
| dinvgauss | Inverse Gaussian Distribution |
| elda | Extreme Limiting Dilution Analysis |
| eldaOneGroup | Extreme Limiting Dilution Analysis |
| fitNBP | Negative Binomial Model for SAGE Libraries with Pearson Estimation of Dispersion |
| forward | Forward Selection of Covariates for Multiple Regression |
| gauss.quad | Gaussian Quadrature |
| gauss.quad.prob | Gaussian Quadrature with Probability Distributions |
| glm.scoretest | Score Test for Adding a Covariate to a GLM |
| glmgam.fit | Fit Generalized Linear Model by Fisher Scoring with Levenberg Damping |
| glmnb.fit | Fit Generalized Linear Model by Fisher Scoring with Levenberg Damping |
| hommel.test | Test Multiple Comparisons Using Hommel's Method |
| InverseGaussian | Inverse Gaussian Distribution |
| limdil | Extreme Limiting Dilution Analysis |
| limdil.class | Extreme Limiting Dilution Analysis |
| logmdigamma | Log Minus Digamma Function |
| matvec | Multiply a Matrix by a Vector |
| meanT | Mean t-Statistic Between Two Groups of Growth Curves |
| meanval.digamma | Digamma generalized linear model family |
| mixedModel2 | Fit Mixed Linear Model with 2 Error Components |
| mixedModel2Fit | Fit Mixed Linear Model with 2 Error Components |
| mscale | M Scale Estimation |
| permp | Exact permutation p-values |
| pinvgauss | Inverse Gaussian Distribution |
| plot.limdil | Plot or print an object of class limdil |
| plotGrowthCurves | Compare Groups of Growth Curves |
| power.fisher.test | Power of Fisher's Exact Test for Comparing Proportions |
| print.limdil | Plot or print an object of class limdil |
| qinvgauss | Inverse Gaussian Distribution |
| qres.binom | Randomized Quantile Residuals |
| qres.default | Randomized Quantile Residuals |
| qres.gamma | Randomized Quantile Residuals |
| qres.invgauss | Randomized Quantile Residuals |
| qres.nbinom | Randomized Quantile Residuals |
| qres.pois | Randomized Quantile Residuals |
| qres.tweedie | Randomized Quantile Residuals |
| qresid | Randomized Quantile Residuals |
| qresiduals | Randomized Quantile Residuals |
| randomizedBlock | Fit Mixed Linear Model with 2 Error Components |
| randomizedBlockFit | Fit Mixed Linear Model with 2 Error Components |
| remlscore | REML for Heteroscedastic Regression |
| remlscoregamma | Approximate REML for gamma regression with structured dispersion |
| rinvgauss | Inverse Gaussian Distribution |
| sage.test | Exact Binomial Tests For Comparing Two SAGE Libraries (Obsolete) |
| statmod | Introduction to the StatMod Package |
| tweedie | Tweedie Generalized Linear Models |
| unitdeviance.digamma | Digamma generalized linear model family |
| varfun.digamma | Digamma generalized linear model family |
| vecmat | Multiply a Matrix by a Vector |
| welding | Data: Tensile Strength of Welds |


|
Raytracer
1.0.0
|
#include <Camera.h>
Public Member Functions | |
| Camera () | |
| virtual void | RenderScene (const World &w)=0 |
| void | SetEye (const glm::vec3 &eye) |
| void | LookAt (const glm::vec3 &look_at) |
| void | SetUpVector (const glm::vec3 &up) |
| void | SetYaw (const float yaw) |
| void | SetPitch (const float pitch) |
| void | SetRoll (const float roll) |
| void | SetExposureTime (const float etime) |
Protected Member Functions | |
| void | ComputeUVW () |
Protected Attributes | |
| glm::vec3 | m_Eye |
| glm::vec3 | m_LookAt |
| glm::vec3 | m_UpVector |
| glm::vec3 | m_U |
| glm::vec3 | m_V |
| glm::vec3 | m_W |
| float | m_Yaw |
| float | m_Pitch |
| float | m_Roll |
| float | m_ExposureTime |
A point from which the scene will be rendered.
| Camera::Camera | ( | ) |
Standard constructor.
|
protected |
Computes the orthonormal basis of the camera.
|
pure virtual |
Traces the constructed scene.
| w | Reference to the world. |
Implemented in Orthographic, Pinhole, and ThinLens.
|
protected |
Exposure time of the camera.
|
protected |
Eye position in world coordinates.
|
protected |
Direction the camera is facing.
|
protected |
Pitch angle of the camera.
|
protected |
Roll angle of the camera.
|
protected |
X vector of the camera in its coordinate system.
|
protected |
World's up vector.
|
protected |
Y vector of the camera in its coordinate system.
|
protected |
Z vector of the camera in its coordinate system.
|
protected |
Yaw angle of the camera.


tizebraprint Module
Description
TODO: Enter your module description here
Accessing the tizebraprint Module
To access this module from JavaScript, you would do the following:
var Zebra = require('io.eventhero.tizebraprint');
The Zebra variable is a reference to the Module object.
Reference
Zebra.findBluetoothPrinters
This method returns an array of Printer descriptions, including name and serial number. Printer object is ready to be passed to Zebra.selectPrinter
.
Zebra.findNetworkPrinters
This method returns an array of Printer descriptions, including name, IP address and port. Printer object is ready to be passed to Zebra.selectPrinter
.
Zebra.selectPrinter({printer,callback}>)
Before printing, you must select a printer. Pass in either an IP and port or a bluetooth serial number.
Arguments
Takes one argument, a dictionary with the following keys:
- serialNumber[string] (optional): Serial Number of the bluetooth printer. Either this or
ipAddress
and port
are required.
- ipAddress[string] (optional): IP Address of the network printer. Must also include a
port
param. Either this or serialNumber
are required.
- port[int] (optional): TCP Port for the network printer. Required if
ipAddress
is used.
- callback[function] (optional): Callback function. Returns one object, with
success (boolean)
and message (string)
properties.
Zebra.print({...})
Method used to print to the selected printer.
Arguments
Takes one argument, a dictionary with the following keys:
- image[TiBlob]: An image blob to be printed. Either this field is required, or
pdf
is required.
- pdf[string]: Fully qualified path to a PDF file. Use
Ti.File.resolve()
to get said path. Either this field is required, or image
is required.
- page[int] (optional): Page of the PDF file to print. If you pass "0", all pages will print. Default "0".
- callback[function] (optional): Callback function. Returns one object, with
success (boolean)
and message (string)
properties.
- x[int] (optional): Horizontal starting position in dots. Default "0".
- y[int] (optional): Vertical starting position in dots.. Default "0".
- width[int] (optional): Desired width of the printed image. Passing -1 will preserve original width. Default "-1".
- height[int] (optional): Desired height of the printed image. Passing -1 will preserve original height. Default "-1".
- isInsideFormat[boolean] (optional): Boolean value indicating whether this image should be printed by itself (NO), or is part of a format being written to the connection (YES). Default "false".
Usage
See TiZebraPrintExample in this repo.


Roman Numeral Convertor
Enter a Number
Submit!
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[1]
Image quality, auto focus, comfort, zoom lever; build quality, battery movement, location of usb interface
[2]
Great Looking Video and Nice Design; Long Conversion Time and Not Ideal for editing


Keyword: module
A module in Ivy is a group of declarations that can be instantiated.
In this way it is similar to a template class in an object-oriented programming language.
Any Ivy declaration can be contained in a module.
An instance of a module is called an object, and there is special syntax for declaring a singleton object that is the sole instance of a module. A further special type of object is an isolate, which is verified in isolation from other objects.
Besides defining classes of objects, modules can be used to capture a re-usable theory, or structure a modular proof.
Declarations within modules are subject to visibility qualifiers, that limit how module members may be seen when verified as an isolate.
Examples:
Example: counter
Here is a simple example of a module representing an up/down counter
with a test for zero:
module counter(t) = {
individual val : t
after init {
val := 0
}
action up = {
val := val + 1
}
action down = {
val := val - 1
}
action is_zero returns(z : bool) = {
z := (val = 0)
}
}
This module takes a single parameter t
which is the type of the counter value val
.
Example: a theory of partial order
As an example, here is a module representing a theory of partial orders:
module po(t,lt) = {
axiom lt(X:t,Y) & lt(Y,Z) -> lt(X,Z)
axiom ~(lt(X:t,Y) & lt(Y,X))
}
This module takes a type t
and a relation lt
over t
. It provides axioms stating that lt
is transitive and antisymmetric.


Parameters
Parameters are ways of distinguishing one blockchain from another, making a particular
blockchain more or less suited to a particular purpose.
Quick List
- Starting shares outstanding
- Target share reduction rate
- Recording fees/taxes
- Number of coins
- Required underwriting ratios
- Times
- Block generation interval
- Required underwriting durations
- Contract timespan limits
- Longevity of shares after assignment
Deeper Thoughts
Starting shares outstanding
Usually a big number, really big. The number of shares held by a secret key does not change from the time they are accepted in an authorized assignment until they are all assigned away in another authorized assignment. The number of shares outstanding does slowly decrease via recording taxes.
Target share reduction rate
Through recording fees/taxes, assignment invalidations and share assignment expirations, the number of shares outstanding drops over time.
Fees/taxes can be modulated to target a specific share reduction rate over the long term, for instance a 5% annual reduction in shares
outstanding which would cause a 5% annual increase in coins held for stationary share holdings.
Recording fees/taxes
To compensate the entities which make the system possible, and to discourage "block spam," there is a per-byte recording fee to publish a
page to the blockchain, and other fees for activities which cost something to accomplish. These fees should be quite low when compared
to brick and mortar staffed by people institutions, but nonetheless they should be present both to compensate those who bear real world
expense in making the system work, as well as to discourage unproductive behavior such as frivolous transactions or unnecessarily large
records in the blockchain.
One tax for bytes in the recorded page, another tax for bytes in public keys (for the UTXO database).
Fee/taxes also fund error checking activity by providing incentive to record "everything looks good to me" notes in the chain.
Number of coins
The "human face" of value in the blockchain. Originally envisioned as a static number, other implementations are of course possible.
One possibility would be to stabilize interest rates at a target level by adjusting coins vs shares outstanding.
Required underwriting ratios
Underwriting is the carrot and stick all in one. Carrot: charge fees for underwriting. Carrot: error checkers can score big catching
underwriters doing things wrong. Stick: underwriters can lose their underwriting shares if they are caught doing things wrong.
Times
Block generation interval
Affects settling time for transactions, block size, and network dynamics.
Required underwriting durations
Needs to be long enough for error checkers to thoroughly verify assignments, signatures, etc. but not so long that underwriters must have a massive number of shares in order to
do their job effectively.
Contract timespan limits
Max time between proposal and recording deadline. Probably shorter time requirements for underwriters' page proposal validity assurances (time of transaction validation).
Longevity of shares after assignment
One way of cleansing the system of abandoned shares, and a way to pay coin interest without transaction fees. One form of share expiration could be an exponentially growing tax on transacting old shares. If shares are to expire after 5 years, they might be subject to a tax which increases by a factor of 2 every 4 months, so at 4 years of age the tax would be 1/8 or 12.5% of the shares taken from the shares outstanding as an age tax, at 3 years of age the tax would be 1/64, and at 5 years of age the tax would be 1/1 or 100% - automatic complete expiration of the shares.
Assign Onward
9 May 2018
MIT License
Copyright (c) 2018 Assign Onward
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
 IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.


2015-05-14 WGR614v10 and WNR1000v3 Cross-Flashing Firmware Update - part 2 WGR614v10 WNR1000v3 Netgear Wifi Router OpenWrt
2015-05-14 WGR614v10 and WNR1000v3 Cross-Flashing Firmware Update - part 1 WGR614v10 WNR1000v3 Netgear Wifi Router OpenWrt


{{/* convoluted nested where clause... */}}
{{/* checks for:
1) article has a thumbnail
2) article is not expired
3) article has a "news" type
*/}}
{{ range first 2 (where (where (where .Site.RegularPages ".Params.imagethumb" "!=" nil) ".Params.expired" false) ".Params.type" "news") }}
{{ end }}


Graduate student of MSc. Biomedical Computing at Technical University of Munich (TUM).
Assisted with development of web-based “Open Calls Platform” for EU Robotics Projects, employed for tasks ranging from advertisement of project calls to evaluation, financing, contracting and implementation of selected projects. Then in use for Human Brain Project, RobMoSys, and TERRINet.
Developed an embedded-system to automate network of OTDR devices for real-time acquisition, parsing, storage and display of optical ﬁber alarms and trace results.
Developed robotic manipulator to emulate ﬁgure-8 trajectory traced by face of treadmill runner while running, and implemented vision-based PID control for visual servoing (US Patent No. US 8926475B2).
Code: https://github.com/abdullahgulraiz/SyncroRun
Developed web application to acquire, process and visually display garbage trends data collected through sensors.
Code: https://github.com/abdullahgulraiz/SwiftBin-Web-Application
Responsible for contacting international interns, facilitating their exchange journeys, and partnering with local firms.
Responsible for recruiting teams for on-campus events, and refining qualified teams’ business ideas.
Website: http://hultprizeat.com/nust
Developed social media network for college alumni.
Website: http://portal.emealumni.com
Planned the event, led a team of Event Directors, and briefed the Board of Directors on event Progress.
Website: http://nerc.com.pk
Fabricated an autonomous robot with discrete components that solved a given arena incorporating color sensing, line following, wall following, ramp ascent/descent and ditch crossing, employing multiple ultrasonic, IR and color sensors.
Steered a four-wheeled robot using Android smartphone’s gyroscope and accelerometer through Bluetooth.
Fabricated a walking stick that smartly detected elderly fall and alarmed the attendant through SMS/call.
Digitized an ordinary stethoscope to give visual and sonic output of auscultatory signal.
Programmed a modular robot that performed localization and color detection to pot boxes in an arena.
Developed various database applications for desktop and web (frontend and backend).


What value is returned by arrayFromValue()
?
function arrayFromValue(item) {
return
[item];
}
console.log(arrayFromValue(10)); // => ???
It’s easy to miss the new line between the return
keyword and [item]
expression.
However, this newline makes the JavaScript automatically insert a semicolon between return
and [item]
expression.
Here’s an equivalent code with the semicolon inserted after return
:
function arrayFromValue(item) {
return;
[item];
}
console.log(arrayFromValue(10)); // => undefined
return;
inside the function makes it return undefined
.
So arrayFromValue(10)
evaluates to undefined
.


FOR var=[expr] to|downto [goal] &optional step [n]
Description
Begins a FOR loop.
Results
Compiles a FOR loop. Sets the counter variable 'var' to [expr]. If the keyword TO is used, then the loop continues executing until var > [goal]. If DOWNTO is used, execution continues until va < [goal].
An optional STEP parameter is allowed. If specified, then var is incremented by [n] each iteration. Otherwise, [n] defaults to 1 for TO and -1 for DOWNTO.
Example
; loop through all the indices of a loop, skipping every other one for x = 0 to 99 step 2 ; do something with list[x] next
Back to Keywords