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Climb is an analytics tool for professional League of Legends teams to digest game data.
This case studies explores how I tackle the complex problem of information overload on the dashboard design, explore different solutions through iterations, and learn to bridge the gap between design and development.


class Servo – 3-wire hobby servo driver¶
Servo objects control standard hobby servo motors with 3-wires (ground, power, signal). There are 4 positions on the pyboard where these motors can be plugged in: pins X1 through X4 are the signal pins, and next to them are 4 sets of power and ground pins.
Example usage:
import pyb
s1 = pyb.Servo(1) # create a servo object on position X1
s2 = pyb.Servo(2) # create a servo object on position X2
s1.angle(45) # move servo 1 to 45 degrees
s2.angle(0) # move servo 2 to 0 degrees
# move servo1 and servo2 synchronously, taking 1500ms
s1.angle(-60, 1500)
s2.angle(30, 1500)
Note
The Servo objects use Timer(5) to produce the PWM output. You can use Timer(5) for Servo control, or your own purposes, but not both at the same time.
Constructors¶
-
class
pyb.
Servo
(id)¶ Create a servo object.
id
is 1-4, and corresponds to pins X1 through X4.
Methods¶
-
Servo.
angle
([angle, time=0])¶ If no arguments are given, this function returns the current angle.
If arguments are given, this function sets the angle of the servo:
angle
is the angle to move to in degrees.time
is the number of milliseconds to take to get to the specified angle. If omitted, then the servo moves as quickly as possible to its new position.
-
Servo.
speed
([speed, time=0])¶ If no arguments are given, this function returns the current speed.
If arguments are given, this function sets the speed of the servo:
speed
is the speed to change to, between -100 and 100.time
is the number of milliseconds to take to get to the specified speed. If omitted, then the servo accelerates as quickly as possible.
-
Servo.
pulse_width
([value])¶ If no arguments are given, this function returns the current raw pulse-width value.
If an argument is given, this function sets the raw pulse-width value.
-
Servo.
calibration
([pulse_min, pulse_max, pulse_centre[, pulse_angle_90, pulse_speed_100]])¶ If no arguments are given, this function returns the current calibration data, as a 5-tuple.
If arguments are given, this function sets the timing calibration:
pulse_min
is the minimum allowed pulse width.pulse_max
is the maximum allowed pulse width.pulse_centre
is the pulse width corresponding to the centre/zero position.pulse_angle_90
is the pulse width corresponding to 90 degrees.pulse_speed_100
is the pulse width corresponding to a speed of 100.


{% extends "header.html" %} {% block body %}
Now that we know how to use Quandl to get data, we want to use Quandl in conjunction with our current data building script to do some improved analysis.
The only major change you may want to make from what I make below / in the video is in the line where we identify the ticker:
ticker = each_dir.split("\\")[1]
Instead of [1], you may want to use [-1], since your directory is likely to be different than mine. [-1] is logically the superior choice to use.
import pandas as pd import os from Quandl import Quandl import time auth_tok = "yourauthtoken" path = "X:/Backups/intraQuarter" def Stock_Prices(): df = pd.DataFrame() statspath = path+'/_KeyStats' stock_list = [x[0] for x in os.walk(statspath)] print(stock_list) for each_dir in stock_list[1:]: try: ticker = each_dir.split("\\")[1] print(ticker) name = "WIKI/"+ticker.upper() data = Quandl.get(name, trim_start = "2000-12-12", trim_end = "2014-12-30", authtoken=auth_tok)Above, we're pulling the data we went, but this data comes with many columns. The column we want is the one that is for the adjusted close. "Adjusted close" is a closing price that accounts for any stock splits and adjusts historical prices for accuracy.
data[ticker.upper()] = data["Adj. Close"] df = pd.concat([df, data[ticker.upper()]], axis = 1) except Exception as e: print(str(e)) time.sleep(10)Here, we've defined that specific column we want, we're then renaming it to be the stock's ticker, then we're concatenating (adding it) it do the dataframe. Concatenation is not to be confused with appending. Appending is when we add more rows to the data frame. Concatenating is when we add more columns of data. Now, at the time of my filming, the Quandl website was acting up and going down every now and then. Because of this, we added another of the exact same loop within an exception. This way, the program will try twice before giving up. So we'll do that, and then finish up the program:
try: ticker = each_dir.split("\\")[1] print(ticker) name = "WIKI/"+ticker.upper() data = Quandl.get(name, trim_start = "2000-12-12", trim_end = "2014-12-30", authtoken=auth_tok) data[ticker.upper()] = data["Adj. Close"] df = pd.concat([df, data[ticker.upper()]], axis = 1) except Exception as e: print(str(e)) df.to_csv("stock_prices.csv") Stock_Prices()


The pipeline is the principal tool in connecting work (developers,
inputs) and value (production, outputs). Benefits include:
It provides backpressure to developers, showing them problems
earlier, and preventing many kinds of problems from appearing
later in testing or production.
It raises the efficiency and speed to production, automating many
traditionally manual steps, especially around testing.
It acts as a gate to production, increasing the options available
to management (but see Feature
toggles, below, for a alternative and complimentary
approach).
It emphasizes quality control elements, increasing organization
confidence in the product and process, including historic data
for trend analysis.
It provides audit and control points for Good Governance, an
accurate, reproducible record.
Pipeline shape
Unlike a physical pipeline, a build pipeline is bi-directional.
Developer work flows in towards production, and production
environments flow towards development. Another way to express
this:
Code should move as fast as possible towards production,
and development should have the most production-like environment
possible.
First, a pipeline. Note that work flows from development and into
production. Similarly, the production environment is copied by earlier
environments, usually becoming less faithful a reproduction each time
like a picture photocopied repeatedly. And illustrated:
Next, environment boundaries separated by vertical lines, and the ideal
state as a horizontal line: work in production is identical to
development—each commit by development flows directly into
production—; the development environment is a fully faithful
replica of the production environment.
The full picture. Notice the distortions to the environment caused by
delays in the pipeline:
In the above illustration, pipeline and environments are tilted 7°
in opposite directions. As a consequence, the actual new work that is
running in production is a smaller piece of the available work in
development which could potentially be deployed. This represents
waste.
More on the bottom
illustration
The wedges in the upper half between the lighter and darker grey
lines are work held back in an earlier environment from reaching a
later environment.
Similarly, wedges in the lower half represent later environmental
concerns pushed into earlier environments, increasing the complexity
of those lower environments.
Lastly the blue line shows how work, thinning as it runs left to
right, builds up in earlier environments, and either idles
developers who wait on later environments to catch up, or product
work that does not reach production. Similarly, higher
environments, thinning as they run right to left, degrade in
fidelity in lower environments.
Invest in your pipeline
Pipeline aromas
Aromas are pleasant, like fresh brewed coffee in the morning.
Keep your pipeline fresh to keep work pleasant.
Separate stages by purpose
Group logically related pipeline steps by stage. For example, run
unit tests in a unit test stage. Or in a multi-product build,
group stages by build. This helps visualize what a pipeline does,
and why. And importantly, it quickly points to the cause
of failure. Your pipeline architecture documents should align with
these stages.
Emulate production as much as possible
To the degree possible, each stage of a pipeline should have the
same environment as the following stage, and development (before
the pipeline first sees changes) should have the same environment
as the first pipeline stage. This ensures consistency across the
flow towards production, and finds environmental issues as early
as possible, before they can affect production.
Send code as far towards production as possible
The flipside of keeping environments similar is keeping code
similar. To the degree possible, each stage should act on the same
code as the previous stage, and production (after the pipeline is
done) should run the same code.
Use feature toggles and gates
Production cannot always run the code exactly as the pipeline sees
it, and sometimes earlier stages near production are similar. In
these cases, use Feature
Toggles to turn off code in production, and
Approval Promotions (gates) to manage timing of code deployment.
These come with their
own drawbacks, so should only be used if really needed.
Front-load and fail fast
The faster the pipeline can fail when something—anything—is
wrong, the faster development can fix it and continue. Invariably
some stages in a pipeline run faster than others. Put these stages
before slower ones, if there are not dependencies, for faster
feedback.
Pipeline smells
Smells are unpleasant, like old leftovers that need dealing
with. Keep your pipeline clean to avoid unpleasantness.
Mix types of tests in the same stage
Mix tooling
As much as feasible, keeping tooling consistent among all pipeline
stages. For example, in an F# project, use the same version of F#
in every stage. This can be challenging when crossing environment
boundaries, say from developer's Windows desktops to managed Linux
VMs or containers, especially when an older version used in
production is dictated by another part of the organization.
Developers chafe at using old software.
Slow stages
Particularly notorious for slow pipeline states are large,
cumbersome tests, such as automated UI tests. POINT TO DISCUSSION ON THEORY OF
CONSTRAINTS
Separate ownership of environments
The influence of Conway's
Law tends to appear in latter stages of a pipeline.
Perhaps a separate Testing team owns QA stages. Resist this
tendency. TALK ABOUT THIS MORE.
VMs or containers
When possible, developers should have an environment as production-like
as possible. One solution is to run VMs or containers on the
development desktop that emulate production. The same solution
applies to testing.
When possible, the only difference between production and environments
prior to production should be:
Scaling
With fixed infrastructure (often inhouse), it is too normally
costly to replicate the production environment, so developers and
the pipeline should approximate as closely as possible. However,
in the age of the cloud, it is often feasible to exactly duplicate
production, especially when system architecture assumes cloud and
does not have built-in requirements of more than X servers or
fewer than Y servers.
Security
Good security requires separation between production and
non-production accounts. This is the most common kind of
configuration difference between production and non-production.
However, the non-production accounts should have the same access
and setup as production, just against non-production resources.
Resources
Feature toggles
Closing the loop
Pipeline is really a feedback loop, prod back to PO


Before Change
// set up Python dictionary to hold model training parameters
model_definition = {...}
// Define Ludwig model object that drive model training
model = LudwigModel(model_definition,
model_definition_file="./model_definition.yaml",
After Change
// set up Python dictionary to hold model training parameters
with open("./model_definition.yaml","r") as f:
model_definition = yaml.safe_load(f.read())
// Define Ludwig model object that drive model training
model = LudwigModel(model_definition,
logging_level=logging.INFO)
// initiate model training


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Research
Multicast Forwarding and Routing
Despite its potential significant bandwidth savings, major network providers do not yet support multicast within their networks. This is because of the lack of efficient and scalable multicast primitives that (i) support various routing requirements of ISPs such as traffic engineering and service chaining, where a packet needs to pass through an ordered set of network services before reaching the receivers, and (ii) forward packets of large numbers of concurrent multicast sessions. My main contribution is addressing the scalability challenges by managing, reducing or eliminating the required state to be maintained at network switches.
Data Center Networking
The current focus of my research in this area is to design various networking primitives to efficiently manage the network resources. The main idea is to take advantage of network programmability to manage the network. Specifically, I have been designing systems that efficiently forward multicast traffic, and accurately schedule tasks within the network.
Multimedia Systems
Streaming videos over the Internet is a multi-billion-dollar industry and it is rapidly growing. This is due to the proliferation of new types of multimedia content such as 4K videos and immersive content such as multiview and 360-degree videos. These new multimedia contents are becoming popular because they offer high-quality and unprecedented experiences to users. For example, multiview videos allow users to explore scenes from different angles and perspectives, whereas 360-degree videos put users in virtual scenes that can be navigated. As the popularity of immersive videos increases, the amount of multimedia traffic distributed over the Internet increases at high rates. Thus, major ISPs need to efficiently carry and manage larger volumes of multimedia traffic through their networks. My recent work focused on two aspects of multimedia systems: (i) the adaptive streaming of multiview videos, and (ii) the traffic engineering and content placement of multimedia content.
MASH [INFOCOM'17]
A Rate Adaptation Algorithm for Multiview Video Streaming over HTTP
CAD [INFOCOM'19]
Joint Content Distribution and TE of Adaptive Videos in Telco-CDNs
3D Video Streaming [MM'14, TOMM'16, MMSys'14]
We developed systems to manage the large storage requirements of 3D videos, and stream 3D content with depth personalization and customization.
Cloud Gaming
Cloud gaming offloads the main components of games from clients/consoles to cloud servers. This leads to several advantages such as facilitating new game updates, avoiding potential piracy, and reducing the computation and storage resources at the clients. The cloud server executes the game logic, renders the game, and encodes and transmits the frames to end users. This introduces fundamental tradeoffs between latency, bandwidth consumption, and perceived quality. The focus of my work is to reduce the bandwidth usage of cloud gaming while achieving a high perceived quality. The main idea of our research is to create computational models to understand how players interact with various game genres, and encode various regions in the frame proportional to their importance to the player.


Scroller will automatically integrate with
DataTables in order to save the scrolling position
of the table, if state saving is enabled in the
DataTable (
stateSaveDT
). This example shows that in practice - to
demonstrate, scroll the table and then reload the
page.
| ID | First name | Last name | ZIP / Post code | Country |
|---|
The Javascript shown below is used to initialise the table shown in this example:
$(document).ready(function()
{ $('#example').DataTable( { ajax:
"data/2500.txt", deferRender: true,
dom: "frtiS", scrollY: 200,
scrollCollapse: true, stateSave: true } ); } );
In addition to the above code, the following Javascript library files are loaded for use in this example:
The HTML shown below is the raw HTML table element, before it has been enhanced by DataTables:
This example uses a little bit of additional CSS beyond what is loaded from the library files (below), in order to correctly display the table. The additional CSS used is shown below:
The following CSS library files are loaded for use in this example to provide the styling of the table:
This table loads data by Ajax. The latest data that has been loaded is shown below. This data will update automatically as any additional data is loaded.
The script used to perform the server-side processing for this table is shown below. Please note that this is just an example script using PHP. Server-side processing scripts can be written in any language, using the protocol described in the DataTables documentation.


The source or tag of a received message may not be known if wildcard values were used in the receive operation. Also, if multiple requests are completed by a single MPI function (see Section Multiple Completions ), a distinct error code may need to be returned for each request. The information is returned by the status argument of MPI_RECV. The type of status is MPI-defined. Status variables need to be explicitly allocated by the user, that is, they are not system objects.
In C, status is a structure that contains three fields named MPI_SOURCE, MPI_TAG, and MPI_ERROR; the structure may contain additional fields. Thus, status.MPI_SOURCE, status.MPI_TAG and status.MPI_ERROR contain the source, tag, and error code, respectively, of the received message.
In Fortran, status is an array of INTEGERs of size MPI_STATUS_SIZE. The constants MPI_SOURCE, MPI_TAG and MPI_ERROR are the indices of the entries that store the source, tag and error fields. Thus, status(MPI_SOURCE), status(MPI_TAG) and status(MPI_ERROR) contain, respectively, the source, tag and error code of the received message.
In general, message passing calls do not modify the value of the error code field of status variables. This field may be updated only by the functions in Section Multiple Completions which return multiple statuses. The field is updated if and only if such function returns with an error code of MPI_ERR_IN_STATUS.
[] Rationale.
The error field in status is not needed for calls that return only one
status, such as MPI_WAIT, since that would only duplicate the
information returned by the function itself. The current design
avoids the additional overhead of setting it, in such cases. The field
is needed for calls that return multiple statuses, since each request
may have had a different failure.
( End of rationale.)
The status argument also returns information on the length of the message received. However, this information is not directly available as a field of the status variable and a call to MPI_GET_COUNT is required to ``decode'' this information.
MPI_GET_COUNT(status, datatype, count)
[ IN status] return status of receive operation (Status)
[ IN datatype] datatype of each receive buffer entry (handle)
[ OUT count] number of received entries (integer)
int MPI_Get_count(MPI_Status *status, MPI_Datatype datatype, int *count)
MPI_GET_COUNT(STATUS, DATATYPE, COUNT, IERROR)
INTEGER STATUS(MPI_STATUS_SIZE), DATATYPE, COUNT, IERROR
Returns the number of entries received. (Again, we count entries, each of type datatype, not bytes.) The datatype argument should match the argument provided by the receive call that set the status variable. (We shall later see, in Section Use of general datatypes in communication , that MPI_GET_COUNT may return, in certain situations, the value MPI_UNDEFINED.)
[] Rationale.
Some message passing libraries use INOUT count, tag and source arguments, thus using them both to specify the selection criteria for incoming messages and return the actual envelope values of the received message. The use of a separate status argument prevents errors that are often attached with INOUT argument (e.g., using the MPI_ANY_TAG constant as the tag in a receive). Some libraries use calls that refer implicitly to the ``last message received.'' This is not thread safe.
The datatype argument is passed to MPI_GET_COUNT so as to
improve performance. A message might be received without counting the number
of elements it contains, and the count value is often not needed.
Also, this allows the same function to be used after a call to
MPI_PROBE.
( End of rationale.)
All send and receive operations use the buf, count,
datatype, source, dest, tag,
comm and status arguments in the same way as the blocking
MPI_SEND and
MPI_RECV operations described in this section.


These are all block statements in Bee language:
| Name | Description |
|---|---|
| start | named block |
| with | anonymous block |
| if-else | decision fork |
| ladder | decision ladder |
| cycle | repetitive unconditional block |
| for | repetitive block with local scope |
| match | enumerable symbol selector |
| trial | exception handler block |
We use ocasionaly a block of code that has a local scope by using "start" keyword follow by a label. The label is optional and can be numeric or alphanumeric.
In this example we use "start" to create a local scope and a new variable (a) inside this scope. Then we use nested do statement and we end with "done" keyword follow by optional label.
start [label]:
** local variables
...
do
** executable block
...
done [label];
Start a "qualifier suppression block". This is a block that eliminate the need for qualifiers into an anonymous local scope. You can use "with" to suppress module names or aliases.
For this example first we create a simple module:
#define test_module
rule .inc(x:0) => (r: 0):
let r := x + 1;
return;
We load a secondary module and use a qualifier for it:
#using qualifier suppressor
use lib_folder/test_module as test;
rule main:
** define locals
new x := 2;
with test do
** call external routine .test
expect x == 3;
print inc(x);
done;
return;
Notes:
Using "if" and "do" keywords you can create a task that is executed or not depending of a condition. When the condition is false the block statement is ignored and next statement is executed. This statement is sometimes called fork.
Using "if" keyword we can create a conditional branch:
# decision
if condition do
** statements
...
done;
In this example we use "begin" to create a local scope and a new variable (a) inside this scope. Then we use nested anonymous if statement.
# fragment
start test:
new a := random();
if a < 0 do
print ("|a| =", a);
else
print ("|a| =", -a);
done test;
By using "else" keyword we can split the conditional branch into two branches:
decision diagram
# decision with two branches
if condition do
** true branch
...
else
** false branch
...
done;
By using keywords "if" and "else" you can create a cascade of decisions called "decision ladder" that has several conditional branches plus one optional branch that is executed when no other condition is fulfilled.
decision ladder
#decision ladder
start test:
** local scope
new a ∈ Z; -- control variable
read("a = ", a); -- expressions in declaration area
if a = 0 do -- first decision
print "a = 0";
else if a > 0 do -- second decision
print "a > 0";
else if a < 0 do -- third decision
print "a < 1";
else
** default block
print "unexpected:" + a;
done test;
You can use "cycle" to start a repetitive block. This keyword is used before local declaration and can create a labeled cycle. "do" will repeat all statements in the block until a condition ends the cycle. If no condition exists, the cycle is infinite.
Next example show a repetitive "do" block that runs forever. It is not very practical but will be terminated when reaches maxim limit of iteration establish by $iteration variable.
infinite cycle
#infinite cycle
cycle [label]:
** local variables
do
** repetitive block
...
repeat [label];
Next block will execute multiple times until stop condition is true.
stop condition
#conditional run cycle
cycle:
** local variables
...
do
** repetitive block
...
[redo if condition1];
...
[stop if condition2];
...
repeat [if condition3];
Keyword "while" can be used to evaluate a condition and start or continue a repetitive block. The number of repetitions is controlled by condition. If the start condition is not fulfilled the else block is executed. When "else" block is ending the cycle normally stops unless "redo" is used to restart the cycle.
start-condition cycle
#conditional start cycle
cycle [label]:
** define local variables
...
while start_condition do
** first repetitive block
...
[stop if condition]; -- break the cycle
...
[redo if condition]; -- restart the cycle
...
then
** non repetitive block
...
repeat [label];
Note 1: The else block runs one single time, that is when the condition evaluate to false. Otherwise if we repeat the cycle for "else" block we can end-up with infinite loop that is absurd.
Note 2: Keyword: "stop" is similar to "break" in Java and "redo" similar to "continue". These are optional interruption statements. Occasional you can use these statements to improve code performance or readability.
Next syntax pattern show how to use a nested cycles with labels.
# nested blocks
cycle 42:
** local variables
...
do
...
cycle 10: do
...
redo 42 if condition1; -- restart block 42
...
stop 42 if condition2; -- exit block 42
...
repeat if condition3;
...
repeat 42;
...
You can start an iterative cycle by using keyword "for". This statement create a cycle that is controlled by a set of values. We use a control variable generated from a domain or visit elements of a collection.
for cycle
#iterative cycle
cycle [label]:
** local variables
new i ∈ N;
for ∀ i ∈ (min..max:rate) do
** repetitive block
...
[next if condition]; -- fast forward
...
[stop if condition]; -- early transfer
...
[then]
** non repetitive block
...
repeat [label];
#range iteration with rate 1
cycle:
new i ∈ N;
for ∀ i ∈ (1..10) do
if i % 2 = 0 do
next; -- iterate
else
write i; -- odd numbers
done;
write ',' if (i < 10);
repeat;
1,3,5,7,9
Ratio: Using domain ratio the example above can be simplified:
#range iteration with rate 2
cycle:
new i ∈ N;
for ∀ i ∈ (1..9:2) do
write(i); -- odd numbers
write(',') if (i < 9);
repeat;
print;
This is a multi-path selector similar to so called jump table. A selector is based on a series of blocks. One or more blocks can be executed depending on specific value. In other languages a selector is created using "switch" statement. In Bee we use "match" statement instead.
A match has two variants: "all" or "one". If used, ALL will evaluate all values it may execute multiple blocks. If "one" is used, only first block that match value will be executed!Match Diagram
#enumerable selector
type Selector: {v1,v2,v3,v4} <: E;
rule main:
new select := Selector.random()
match select [all] | [one]:
** declare locals
...
when v1 do
** first path
...
when v1, v2 do
** second path
...
other
** v3 or v4 found
...
done;
return;
The trial is by far the most complex statement of Bee language. A trial block is used to handle a process that can have multiple steps that can pass or fail. It has a default block, several try blocks and multiple case blocks. Each case can resolve one error or several errors.
Trial Diagram
Keywords:
Next keywords are used to create a full trial block:
| word | description |
|---|---|
| trial | start a process that may fail |
| try | start a step in the process |
| case | catch errors with specific code or code range |
| other | catch all other errors not fixed by a patch |
| final | finalization region, executed before trial end |
#complex trial with many cases
trial [label]:
** initial or default statements
....
** preconditions: create recoverable error
expect condition else "message";
...
try [code1]: -- description
...
** jump to next try (no error)
pass if condition;
...
** record error, and jump to next try
fail {code, message} if condition;
...
** create error, and jump to cases
raise {code, message} if condition;
...
try [code2]: -- description
...
** skip the rest (no error) and jump to final
pass if condition;
** optional create error and jump to final
fail {code, message} if condition;
...
** create error and jump to cases
raise {code, message} if condition;
...
case $error.code = code do
** handler1
...
resume; -- continue witj next try
case $error.code ∈ (code1,code2) do
** handler2
...
retry; -- repeat trial from beginning
miss
** cover all other errors
...
raise; -- propagate last error
final
** finalization statement (executed before leaving)
print "final error:" + $error.code if $error.code > 0;
done [label];
Exceptions can be defined in your program using next notation. Exceptions and recoverable errors are using the same type. You can predefine exceptions/errors or issue them with one of: (expect, raise):
** define error new exception := {code,"message"} ∈ X;
Recoverable errors can be issued using "raise" keyword.
** "raise" can create a customized error or message
raise exception if condition; -- create an error that is predefined
raise "message" if condition; -- create instant user error code: 200
raise {code,"message"} if condition; -- create instant custom error with code
Note: The standard module will define standard error objects as system constants. Code 100, 101, 102 are user errors, created by raise, expect or fail keywords.
A trial can have several optional jobs. Each jon start with keyword try() that has 2 optional arguments: try(code, message). Every try can pass or fail with a code and a message.
You can use raise or abort inside a try() block. The raise will mark the try as failed and will record the code and message in the $trial report.
This region can catch an error and decide what to do next. Error can be catch by code or a list of codes. For each cases you can handle the errors using keywords: "abort","retry","resume" or "raise". If a case is not using any of these keywords, the next case is executed. If no case resolve the error, this error auto-propagate.
Next statements are transfer statements used in trial block:
| word | description |
|---|---|
| abort | stop the trial and transfer execution to final block |
| raise | intrerupt current job and create a recoverable error |
| fail | record an error and continue with next step |
| pass | skip current job and continue with next step |
| retry | exception handler, repeat the trial |
| resume | exception handler, jump to next try job |
This region is used for any other error that is not handled by case handlers. You can use any selector in this region to find an exceptions by code but you can also just report the error or log the error and stop the trial.
This region is executed just before trial is done, regardless of error status. Even if there is no error to propagate this region is still executed. This region is mandatory execute even if the trial is aborted.
In this region there is an oportunity to report all messages recorded in $trial object. You can use $trial.messages that is a hash-map created by the system automaticly.
In final block:
#simple trial block
trial:
new x ∈ Q;
new y ∈ Q;
try()
let x := 1/0;
final
print "x = " + x;
print $error.message if $error.code ≠ 0;
done;
In this example we use "raise" statement to create an error on purpose:
#define a custom error
trial:
new my_error:{200, "custom error"} <: Error;
try()
raise my_error; -- issue user error
case $error.code == 200 do
** we catch the the error and do something
print $error.message;
print $error.line;
miss
raise $error; -- propagate error
done;
By using "retry" you can repeat a trial several times until other ending conditions are encounter. You can issue "retry" from case blocks for specific errors.
#example of repeating trial
** try maximum 3 times
trial [name]:
new count ∈ (1..3);
new a ∈ (0..9);
try()
let count += 1;
read a;
if a < 0 do -- trigger patch
fail;
else if a < 9 do
write "correct";
else if a > 9 do
write "incorrect";
else
pass;
done;
case $out_of_range do
if count < 3 do
write "wrong try again:"
retry; -- try again the entire trial
else
write "wrong 3 times!";
fail $out_of_range;
done;
miss
write "mistrial: no case"
final
print "trial is resolved";
print $trial.messages;
done [name];
Read next: Rules


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Jolt Dynamic Actor Component
The Jolt dynamic actor component is used to add physical behavior to an object. Dynamic actors are also referred to as rigid bodies. They are simulated by the physics engine.
Kinematic vs. Simulated
Dynamic actors can be in one of two modes: fully simulated or kinematic. For a kinematic body, the game code dictates its position and rotation, and the physics engine uses this information to push simulated objects out of their way. Kinematic actors are typically used for elevators, doors and other large pieces that are supposed to push other objects away and strictly follow an animation without any physical simulation of their movement.
Non-kinematic, or fully simulated objects on the other hand, are fully controlled by the physics engine. Their position and rotation is determined by forces, such as gravity, acting on them, as well as what other static and dynamic objects they collide with. Setting the position of such an actor has no effect, the physics engine will override the value with its own result. To affect a simulated object, you can apply external forces and impulses. For example the area damage component applies an outward impulse to all rigid bodies in its vicinity to push them away.
Whether a dynamic actor is kinematic or not is simply a flag and it is possible to toggle that state back and forth at runtime. This for example allows to animate an object along a predetermined path by making it kinematic at first, and then switch it to simulated at the end of its animation, to make it fall and collide realistically from there on. In the video below a property animation (TODO) was used to do exactly that:
Mass vs. Density
Dynamic actors have a weight. The weight determines how much force it takes to push them and how much they push other rigid bodies. There are two ways to adjust an actor's weight. If you set the Mass
property, this is the bodies absolute weight no matter its size and shape. Thus a small stone with mass 10 (kilogram) will appear heavy whereas a huge boulder also with mass 10 will appear light.
The other way is to set its Density
property instead. In this case the volume of all the attached shapes is computed and scaled by the density. That means the object's final mass will depend on its scale, so a small stone would get a weight of 0.5 (kilogram) whereas a huge boulder would get a weight of 1000 kg.
Using densities is more convenient to get started. The default density often already produces believable results. If you create a prefab that is supposed to be instantiated at various sizes, it is best to use density.
Important:
Physics engines are notoriously bad at dealing with large mass differences. Objects should never be too light or too heavy in general. Objects with a mass below 1 tend to be flung away at ridiculous speeds when they are pushed by heavy objects. Objects with a mass above 100 should be avoided as well.
Due to these limitations, it is not advisable to use realistic weights for objects, as many objects would become too light and their simulation would suffer from erratic behavior. Instead, choose a weight somewhere in the 0.5 to 100 range that looks good enough.
Consequently, it can often be easier to specify their value as an absolute Mass
, instead of trying to achieve the same through the indirect Density
.
Center Of Mass
The center of mass (COM) is the point in space around which an actor spins when a force is applied to it. The COM is computed automatically from the shapes and their masses. It sometimes ends up too high and makes objects tip over too easily. To adjust the center of mass, enable the property CustomCenterOfMass
and edit the CenterOfMass
property value.
OnContact Reactions
TODO
Simulation Stability
Simulated rigid bodies may not act as desired. Some bodies jitter and don't come to rest, others fly off at high speeds after collisions. Some objects may even tunnel through walls, meaning that instead of colliding properly with a wall, they manage to get to the other side.
These are all known issues with real-time physics engines. With the limited available computational power they have to do many approximations to achieve the desired real-time performance.
Consequently, you have to be careful how you set up your rigid-bodies, to improve simulation stability:
- Avoid small and thin objects: Thin objects are always problematic. For small objects, consider making their collision shape as large as possible, potentially larger than the graphical representation.
- Avoid very heavy and very light objects: See Mass vs. Density above for details.
- Use Continuous Collision Detection (CCD) for important small objects: Continuous collision detection is mainly used to prevent objects from tunneling through other objects. For example a physically simulated grenade may be thrown at a high speed, which means it is prone to get through walls. This is less likely to happen for larger objects. CCD costs extra performance for every object on which it is used, but significantly reduces the likelihood for tunneling to happen.
- Increase angular damping: Some objects tend to spin too fast after collisions. By increasing angular damping, you can make them come to rest more quickly.
- Reduce the complexity of the shape: Especially convex meshes are prone to jittering when the mesh has long thin triangles. Build convex meshes by hand to control their complexity, if an automatically created convex mesh results in unstable behavior.
Component Properties
CollisionLayer
: The collision layer to use.Kinematic
: See Kinematic vs. Simulated above.StartAsleep
: If enabled, the actor starts in the 'sleeping' state and will not be physically simulated until it gets into contact with another active actor. This is a performance optimization to prevent performance spikes after loading a level. If used badly, an object can float in air and not fall down until something else touches it. Make sure to only use this on objects that are convincingly placed to begin with.Mass
,Density
: See Mass vs. Density above.Surface
: The surface to use for this actor's shapes. The surface determines the friction and restitution during simulation, but also determines what effects are spawned when you interact with the object. Note that collision meshes already specify the surface to use. If a surface is selected on the actor, it overrides the mesh's surface.GravityFactor
: Adjusts the influence of gravity on this object. If set to zero, it will float in space.LinearDamping
,AngularDamping
: The damping properties affect how quickly an actor loses momentum and comes to rest. This can be adjusted separately for positional (linear) movement and rotational (angular) movement.ContinuousCollisionDetection
: See Simulation Stability above.OnContact
: See OnContact Reactions above.CustomCenterOfMass
,CenterOfMass
: See Center Of Mass above.


OSX: The following links only works without plugins on OSX safari. On
chrome you do have to launche the external application. If you use
firefox, you need to install FireSSH.
Ubuntu: Please use firefox and use FireSSH.
User name Limitations: This program currently only uses a single usernmae passed along from the hpc coniguration variables


We are FTC Team 6123, the Mechanical Marauders. A neighborhood team founded by the Flack family. This is our website.
Team 6123 the Mechanical Marauders is a community team. It was originally created in 2008 as FIRST Lego League (FLL) team Mechanical Mayhem because there was nothing in the area. In 2012, the team moved from FLL to FIRST Tech Challenge (FTC). Over the years we have grown as a team even though we meet in a team member's attic. In 2014-2015 during Cascade Effect, the team advanced to Southern Super Regionals after winning the North Carolina State Championship. The next year we set our sights even higher. In the FIST Res-Q Challenge, we advanced to the Worlds Championship after placing second in our division at the Southern Super Regional Championship. After reaching the Worlds Championship the majority of the team aged out. One member, Chloe returned. We added 4 new people to help her. In 2016-2017 Mechanical Marauders got to States after placing 2nd at regionals. Unfortunatly they could not advance. This year we are setting our sights on Super-Regionals.
Mechanical Marauders at the Southern Super Regional
Mechanical Marauders at States 2017


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I’ll stop when my body tells me to, says Roger Federer
Federer, who ended the year behind Rafa Nadal and Novak Djokovic in the world rankings, said he cannot predict when he will stop playing.
by ReutersRoger Federer first thought about how long his playing career would last in 2009 but a decade later the 38-year-old is still going strong and says he will keeping playing until his body decides otherwise.
Federer won his last Grand Slam in January 2018 when he claimed his sixth Australian Open but the Swiss has won seven ATP titles since then, taking his career tally to 103.
Federer, who ended the year behind Rafa Nadal and Novak Djokovic in the world rankings, said he cannot predict when he will stop playing.
“My retirement will depend on my health. At the moment I do not see any reason to retire,” the 20-times Grand Slam champion told reporters ahead of his exhibition matches in South America.
“I did not think I would play beyond 35, 36 years and here I am. I am doing well physically. I cannot predict when it will be time to stop.
“I think in 2009 I questioned it for the first time. (It has been) 10 years and here I am. I’m exactly where I wanted to be at this age.”
Federer is six titles shy of American Jimmy Connors’ record of 109 in the Open era.
“With age, everything gets a bit more difficult,” Federer added. “But at the same time, with experience also you can savour the moments more.
“I don’t know how it’s going to end. I hope it’s just going to be somewhat emotional I guess and nice … I just hope it’s going to be good, the whole process, and not too difficult.”


Gecode::Region Class Reference
[Region memory management]
Handle to region. More...
#include <region.hpp>
Public Member Functions | |
| Region (const Space &home) | |
| Initialize region from space. | |
| ~Region (void) | |
| Return memory. | |
Typed allocation routines | |
|
| |
| template<class T > | |
| T * | alloc (long unsigned int n) |
| Allocate block of n objects of type T from region. | |
| template<class T > | |
| T * | alloc (long int n) |
| Allocate block of n objects of type T from region. | |
| template<class T > | |
| T * | alloc (unsigned int n) |
| Allocate block of n objects of type T from region. | |
| template<class T > | |
| T * | alloc (int n) |
| Allocate block of n objects of type T from region. | |
| template<class T > | |
| void | free (T *b, long unsigned int n) |
| Delete n objects allocated from the region starting at b. | |
| template<class T > | |
| void | free (T *b, long int n) |
| Delete n objects allocated from the region starting at b. | |
| template<class T > | |
| void | free (T *b, unsigned int n) |
| Delete n objects allocated from the region starting at b. | |
| template<class T > | |
| void | free (T *b, int n) |
| Delete n objects allocated from the region starting at b. | |
| template<class T > | |
| T * | realloc (T *b, long unsigned int n, long unsigned int m) |
| Reallocate block of n objects starting at b to m objects of type T from the region. | |
| template<class T > | |
| T * | realloc (T *b, long int n, long int m) |
| Reallocate block of n objects starting at b to m objects of type T from the region. | |
| template<class T > | |
| T * | realloc (T *b, unsigned int n, unsigned int m) |
| Reallocate block of n objects starting at b to m objects of type T from the region. | |
| template<class T > | |
| T * | realloc (T *b, int n, int m) |
| Reallocate block of n objects starting at b to m objects of type T from the region. | |
Raw allocation routines | |
|
| |
| void * | ralloc (size_t s) |
| Allocate memory from region. | |
| void | rfree (void *p, size_t s) |
| Free memory previously allocated. | |
Construction routines | |
|
| |
| template<class T > | |
| T & | construct (void) |
| Constructs a single object of type T from region using the default constructor. | |
| template<class T , typename A1 > | |
| T & | construct (A1 const &a1) |
| Constructs a single object of type T from region using a unary constructor. | |
| template<class T , typename A1 , typename A2 > | |
| T & | construct (A1 const &a1, A2 const &a2) |
| Constructs a single object of type T from region using a binary constructor. | |
| template<class T , typename A1 , typename A2 , typename A3 > | |
| T & | construct (A1 const &a1, A2 const &a2, A3 const &a3) |
| Constructs a single object of type T from region using a ternary constructor. | |
| template<class T , typename A1 , typename A2 , typename A3 , typename A4 > | |
| T & | construct (A1 const &a1, A2 const &a2, A3 const &a3, A4 const &a4) |
| Constructs a single object of type T from region using a quaternary constructor. | |
| template<class T , typename A1 , typename A2 , typename A3 , typename A4 , typename A5 > | |
| T & | construct (A1 const &a1, A2 const &a2, A3 const &a3, A4 const &a4, A5 const &a5) |
| Constructs a single object of type T from region using a quinary constructor. |
Detailed Description
Handle to region.
Definition at line 61 of file region.hpp.
Constructor & Destructor Documentation
| Gecode::Region::Region | ( | const Space & | home | ) | [inline] |
Initialize region from space.
Definition at line 298 of file region.hpp.
| Gecode::Region::~Region | ( | void | ) | [inline] |
Return memory.
Definition at line 313 of file region.hpp.
Member Function Documentation
| T * Gecode::Region::alloc | ( | long unsigned int | n | ) | [inline] |
Allocate block of n objects of type T from region.
Note that this function implements C++ semantics: the default constructor of T is run for all n objects.
Definition at line 326 of file region.hpp.
| T * Gecode::Region::alloc | ( | long int | n | ) | [inline] |
Allocate block of n objects of type T from region.
Note that this function implements C++ semantics: the default constructor of T is run for all n objects.
Definition at line 334 of file region.hpp.
| T * Gecode::Region::alloc | ( | unsigned int | n | ) | [inline] |
Allocate block of n objects of type T from region.
Note that this function implements C++ semantics: the default constructor of T is run for all n objects.
Definition at line 340 of file region.hpp.
| T * Gecode::Region::alloc | ( | int | n | ) | [inline] |
Allocate block of n objects of type T from region.
Note that this function implements C++ semantics: the default constructor of T is run for all n objects.
Definition at line 345 of file region.hpp.
| void Gecode::Region::free | ( | T * | b, | |
| long unsigned int | n | |||
| ) | [inline] |
Delete n objects allocated from the region starting at b.
Note that this function implements C++ semantics: the destructor of T is run for all n objects.
Note that the memory is not freed, the only effect is running the destructors.
Definition at line 352 of file region.hpp.
| void Gecode::Region::free | ( | T * | b, | |
| long int | n | |||
| ) | [inline] |
Delete n objects allocated from the region starting at b.
Note that this function implements C++ semantics: the destructor of T is run for all n objects.
Note that the memory is not freed, the only effect is running the destructors.
Definition at line 359 of file region.hpp.
| void Gecode::Region::free | ( | T * | b, | |
| unsigned int | n | |||
| ) | [inline] |
Delete n objects allocated from the region starting at b.
Note that this function implements C++ semantics: the destructor of T is run for all n objects.
Note that the memory is not freed, the only effect is running the destructors.
Definition at line 365 of file region.hpp.
| void Gecode::Region::free | ( | T * | b, | |
| int | n | |||
| ) | [inline] |
Delete n objects allocated from the region starting at b.
Note that this function implements C++ semantics: the destructor of T is run for all n objects.
Note that the memory is not freed, the only effect is running the destructors.
Definition at line 370 of file region.hpp.
| T * Gecode::Region::realloc | ( | T * | b, | |
| long unsigned int | n, | |||
| long unsigned int | m | |||
| ) | [inline] |
Reallocate block of n objects starting at b to m objects of type T from the region.
Note that this function implements C++ semantics: the copy constructor of T is run for all objects, the default constructor of T is run for all remaining objects, and the destrucor of T is run for all n objects in b.
Returns the address of the new block.
Definition at line 377 of file region.hpp.
| T * Gecode::Region::realloc | ( | T * | b, | |
| long int | n, | |||
| long int | m | |||
| ) | [inline] |
Reallocate block of n objects starting at b to m objects of type T from the region.
Note that this function implements C++ semantics: the copy constructor of T is run for all objects, the default constructor of T is run for all remaining objects, and the destrucor of T is run for all n objects in b.
Returns the address of the new block.
Definition at line 393 of file region.hpp.
| T * Gecode::Region::realloc | ( | T * | b, | |
| unsigned int | n, | |||
| unsigned int | m | |||
| ) | [inline] |
Reallocate block of n objects starting at b to m objects of type T from the region.
Note that this function implements C++ semantics: the copy constructor of T is run for all objects, the default constructor of T is run for all remaining objects, and the destrucor of T is run for all n objects in b.
Returns the address of the new block.
Definition at line 400 of file region.hpp.
| T * Gecode::Region::realloc | ( | T * | b, | |
| int | n, | |||
| int | m | |||
| ) | [inline] |
Reallocate block of n objects starting at b to m objects of type T from the region.
Note that this function implements C++ semantics: the copy constructor of T is run for all objects, the default constructor of T is run for all remaining objects, and the destrucor of T is run for all n objects in b.
Returns the address of the new block.
Definition at line 406 of file region.hpp.
| void * Gecode::Region::ralloc | ( | size_t | s | ) | [inline] |
Allocate memory from region.
Definition at line 302 of file region.hpp.
| void Gecode::Region::rfree | ( | void * | p, | |
| size_t | s | |||
| ) | [inline] |
Free memory previously allocated.
Note that the memory is only guaranteed to be freed after the region object itself gets deleted.
Definition at line 310 of file region.hpp.
| T & Gecode::Region::construct | ( | void | ) | [inline] |
Constructs a single object of type T from region using the default constructor.
Definition at line 418 of file region.hpp.
| T & Gecode::Region::construct | ( | A1 const & | a1 | ) | [inline] |
Constructs a single object of type T from region using a unary constructor.
The parameter is passed as a const reference.
Definition at line 423 of file region.hpp.
| T & Gecode::Region::construct | ( | A1 const & | a1, | |
| A2 const & | a2 | |||
| ) | [inline] |
Constructs a single object of type T from region using a binary constructor.
The parameters are passed as const references.
Definition at line 430 of file region.hpp.
| T & Gecode::Region::construct | ( | A1 const & | a1, | |
| A2 const & | a2, | |||
| A3 const & | a3 | |||
| ) | [inline] |
Constructs a single object of type T from region using a ternary constructor.
The parameters are passed as const references.
Definition at line 437 of file region.hpp.
| T & Gecode::Region::construct | ( | A1 const & | a1, | |
| A2 const & | a2, | |||
| A3 const & | a3, | |||
| A4 const & | a4 | |||
| ) | [inline] |
Constructs a single object of type T from region using a quaternary constructor.
The parameters are passed as const references.
Definition at line 444 of file region.hpp.
| T & Gecode::Region::construct | ( | A1 const & | a1, | |
| A2 const & | a2, | |||
| A3 const & | a3, | |||
| A4 const & | a4, | |||
| A5 const & | a5 | |||
| ) | [inline] |
Constructs a single object of type T from region using a quinary constructor.
The parameters are passed as const references.
Definition at line 451 of file region.hpp.
The documentation for this class was generated from the following files:
- gecode/kernel/region.hpp (Revision: 14967)
- gecode/kernel/region.cpp (Revision: 15150)


| Class | Description |
|---|---|
| Application |
Application represents a per-web-application singleton object
where applications based on Jakarta Server Faces (or implementations wishing to provide extended
functionality) can register application-wide singletons that provide functionality required by
Jakarta Server Faces.
|
| ApplicationConfigurationPopulator |
This class defines a |
| ApplicationFactory |
ApplicationFactory is a
factory object that creates (if needed) and returns
Application instances. |
| ApplicationWrapper |
Provides a simple implementation of |
| ConfigurableNavigationHandler |
ConfigurableNavigationHandler extends the contract
of |
| ConfigurableNavigationHandlerWrapper |
Provides a simple implementation of
|
| FacesMessage |
FacesMessage represents a single validation (or other) message, which is
typically associated with a particular component in the view.
|
| FacesMessage.Severity |
Class used to represent message severity levels in a typesafe enumeration.
|
| NavigationCase |
NavigationCase represents a
|
| NavigationCaseWrapper |
Provides a simple implementation of
|
| NavigationHandler |
A
NavigationHandler is passed the outcome string returned by an application action
invoked for this application, and will use this (along with related state information) to choose
the view to be displayed next.
|
| NavigationHandlerWrapper |
NavigationHandlerWrapper provides a simple
implementation of |
| Resource |
An instance
of |
| ResourceHandler |
ResourceHandler is the run-time API by which
|
| ResourceHandlerWrapper |
Provides a simple implementation of |
| ResourceWrapper | |
| StateManager |
StateManager directs the process of saving and restoring the view
between requests.
|
| StateManagerWrapper |
Provides a simple implementation of
StateManager that can be subclassed by developers wishing to provide specialized behavior
to an existing StateManager instance. |
| ViewHandler |
ViewHandler is the pluggablity mechanism for allowing
implementations of or applications using the JJakarta Server Faces specification to provide their own
handling of the activities in the Render Response and Restore View phases of
the request processing lifecycle.
|
| ViewHandlerWrapper |
Provides a simple implementation of |
| ViewResource |
Superclass of |
| Enum | Description |
|---|---|
| ProjectStage |
This class enables a feature similar to the |
| ResourceVisitOption |
Defines the resource traversal options. |
| ViewVisitOption |
Defines the view traversal options. |
| Exception | Description |
|---|---|
| ProtectedViewException |
This exception is thrown by the runtime when a violation of the view protection mechanism is encountered. |
| ViewExpiredException |
Implementations must throw this
FacesException when attempting to restore the view
StateManager.restoreView(javax.faces.context.FacesContext, String, String) results in
failure on postback. |
| Annotation Type | Description |
|---|---|
| ResourceDependencies |
Container annotation to specify multiple |
| ResourceDependency |
Instances of |


|
achievement
|
Teacher Expectancies on Student Achievement |
|
alienation
|
Stability of Alienation |
|
boot_fit()
|
Fit Model on Bootstrap Resamples |
|
boot_lav()
|
Bootstrap SEM Parameter Estimates |
|
boot_nb()
|
Nonparametric Bootstrap |
|
boot_pb()
|
Parametric Bootstrap |
|
boot_pb_med_simple()
|
Parametric Bootstrap (Simple Mediation Model) |
|
boot_pb_vm()
|
Parametric Bootstrap VM |
|
ci_bc()
|
Bias Corrected Confidence Intervals |
|
ci_bca()
|
Bias-Corrected and Accelerated Confidence Intervals |
|
ci_hit()
|
CI hit |
|
ci_quantile()
|
Quantile Confidence Intervals |
|
ci_shape()
|
CI shape |
|
ci_wald()
|
Wald Confidence Intervals |
|
ci_width()
|
CI width |
|
cor2cov()
|
Correlation to Covariance |
|
dat_med_serial2
|
Serial Mediation Model Data |
|
dat_med_simple_lat
|
Simple Mediation Model Using Latent Variables Data |
|
eqs()
|
EQS (Bentler-Weeks) |
|
eqs_mu()
|
EQS mu (Bentler-Weeks) |
|
galton
|
Galton's Height Data |
|
gd()
|
Gradient Descent. |
|
gd_delta()
|
Delta |
|
gd_e()
|
Prediction errors |
|
gd_z()
|
Predictions |
|
gendat()
|
Generate Random Data. |
|
gendat_linreg()
|
Generate Random Data From a Linear Regression Model. |
|
gendat_linreg_X()
|
Generate Data Matrix (X) From a Linear Regression Model. |
|
gendat_linreg_y()
|
Generate Regressand Data (y) From a Linear Regression Model. |
|
gendat_logreg()
|
Generate Data Based on the Logistic Regression Model. |
|
gendat_med_simple()
|
Generate Simple Mediation Model Data |
|
gendat_mvn()
|
Generate Multivariate Normal Data. |
|
gendat_mvn_a()
|
Generate Multivariate Normal Data from the A Matrix and Variances of Observed Variables |
|
gendat_mvn_fe()
|
Generate Multivariate Normal Data from Variance-Covariance Matrix for Fixed-Effect Meta-Analysis. |
|
gendat_mvn_ram()
|
Generate Multivariate Normal Data from RAM Matrices |
|
gendat_percep()
|
Generate Linearly Separable Data Based on the Perceptron Algorithm |
|
gendat_vm()
|
Generate Nonnormal Data Using the Vale and Maurelli (1983) Approach. |
|
heights
|
Mothers' and daughters' Heights |
|
inv_logit()
|
Sigmoid or Logistic Function |
|
is.positive.definite()
|
Positive Definite |
|
is.singular.matrix()
|
Singular Matrix |
|
kurtosis()
|
Kurtosis |
|
laplace_negll()
|
Laplace (-LL) |
|
lav()
|
Generic SEM Fit Function |
|
lin()
|
Linear Function |
|
linreg()
|
Linear Regression. |
|
linreg_anova()
|
Linear Regression (ANOVA) |
|
linreg_e()
|
Linear Regression Residuals |
|
linreg_ess()
|
Linear Regression Explained Sum of Squares. |
|
linreg_h()
|
Linear Regression Hat Matrix |
|
linreg_inv()
|
Linear Regression Coefficients (Inverse of X). |
|
linreg_m()
|
Linear Regression (M) |
|
linreg_mse()
|
Linear Regression Mean Square Error. |
|
linreg_negll()
|
Linear Regression (-LL). |
|
linreg_ols()
|
Linear Regression (OLS). |
|
linreg_optim()
|
Linear Regression (Optimization). |
|
linreg_qr()
|
Linear Regression Coefficients (QR Decomposition). |
|
linreg_r2()
|
Linear Regression (R-square) |
|
linreg_rbar2()
|
Linear Regression (Adjusted R-square) |
|
linreg_rmse()
|
Linear Regression Root Mean Square Error. |
|
linreg_rss()
|
Linear Regression Residual Sum of Squares. |
|
linreg_s2()
|
Linear Regression Residual Variance |
|
linreg_svd()
|
Linear Regression Coefficients (Singular Value Decomposition). |
|
linreg_tss()
|
Linear Regression Total Sum of Squares. |
|
linreg_vcov()
|
Linear Regression (variance-covariance of OLS estimates) |
|
linreg_yhat()
|
Linear Regression (y hat) |
|
lisrel()
|
LISREL Structural Equations with Latent Variables. |
|
lisrel_fa()
|
LISREL Structural Equations with Latent Variables
(Factor Analysis). |
|
lisrel_mat()
|
LISREL Matrices |
|
lisrel_obs()
|
LISREL Structural Equations with Observed Variables. |
|
lisrel_obs_xy()
|
LISREL Structural Equations with Observed Variables (xy) |
|
lisrel_obs_yx()
|
LISREL Structural Equations with Observed Variables (yx) |
|
lisrel_obs_yy()
|
LISREL Structural Equations with Observed Variables (yy) |
|
lisrel_residual()
|
Lisrel Residuals |
|
lisrel_xx()
|
LISREL Structural Equations with Latent Variables (xx). |
|
lisrel_xy()
|
LISREL Structural Equations with Latent Variables (xy). |
|
lisrel_yx()
|
LISREL Structural Equations with Latent Variables (yx). |
|
lisrel_yy()
|
LISREL Structural Equations with Latent Variables (yy). |
|
logreg()
|
Logistic Regression |
|
logreg_negll()
|
Logistic Regression (-LL). |
|
logreg_optim()
|
Logistic regression (Optimization). |
|
low2sym()
|
Lower Triangle to Symmetric |
|
m4()
|
Fourth Central Moment |
|
med_serial2()
|
Serial Mediation Model with Two Mediators |
|
med_serial2_lav()
|
Serial Mediation Model with Two Mediators (lavaan) |
|
med_serial2_ml()
|
Serial Mediation Model with Two Mediators (optim) |
|
med_serial3()
|
Serial Mediation Model with Three Mediators |
|
med_serial3_lav()
|
Serial Mediation Model with Three Mediators (lavaan) |
|
med_serial3_ml()
|
Serial Mediation Model with Three Mediators (optim) |
|
med_simple()
|
Simple Mediation Model |
|
med_simple_lav()
|
Simple Mediation Model (lavaan) |
|
med_simple_lav_lat()
|
Standardized Simple Mediation Model (lavaan) |
|
med_simple_ml()
|
Simple Mediation Model (optim) |
|
moment()
|
Central Moment |
|
opt()
|
Estimation via Optimization |
|
quad()
|
Solve Quadratic Equation |
|
ram()
|
RAM |
|
ram_m()
|
RAM M |
|
ram_mu()
|
RAM mu |
|
ram_residuals()
|
RAM Residuals |
|
ram_s()
|
RAM Sigma/S |
|
relu()
|
Rectified Linear Unit Function |
|
sem_e()
|
SEM (Residuals) |
|
sem_fa()
|
Structural Equations with Latent Variables
(Factor Analysis). |
|
sem_fgls()
|
Generalized Least Squares Objective Function |
|
sem_fml()
|
Maximum Likelihood Objective Function |
|
sem_fuls()
|
Unweighted Least Squares Objective Function |
|
sem_lat()
|
Structural Equations with Latent Variables |
|
sem_log_h0()
|
SEM (Loglikelihood H0) |
|
sem_log_h1()
|
SEM (Loglikelihood H1) |
|
sem_neg2ll()
|
SEM (-2 Loglikelihood) |
|
sem_obs()
|
Structural Equations with Observed Variables |
|
sem_r2()
|
SEM (R square) |
|
tr()
|
Trace of a square matrix |
|
up2sym()
|
Upper Triangle to Symmetric |
|
vech2tri()
|
Vector to Triangular Matrix |
|
wages
|
Wages of Workers |
|
wages2
|
Wages of Youth |
|
water
|
Effects of Temperature on Water Consumption |
|
z()
|
Calculate z-scores |
|
zero_hit()
|
Zero Hit |


Current block:
Contract state:
Input:
| Potential actions | |
|---|---|
| Loading... |
-
Person
commits
ADA with ID
to expire by
-
Person
redeems
ADA from ID
-
Person
claims
ADA from ID
-
Person
chooses value
for ID


Name
Address
City
State
Zip Code
Phone
{% for business in businesses %}
{{ business['business-name']}}
{{business['streetAddress']}}
{{business['addressLocality']}}
{{business['addressRegion']}}
{{business['postalCode']}}
{{ business['telephone'] }}
{% endfor %}


---
title: excited about this movie engineers delight
date: '2015-06-15T19:00:16+05:30'
tags:
- misc
tumblr_url: https://sureshshanmugam.com/post/121587749643/excited-about-this-movie-engineers-delight
---
Excited about this movie. Engineer’s delight!
Follow my blog for more - Analytics & Marketing


I have ID "special"
I'am span to.
Some randome text. My class is one.
Some randome text. My class is one.
- First.
- Second.
- Third.
- Fourth.
Google
Google
| Header 1 |
Header 2 |
Header 3 |
| Data 1 |
Data 2 |
Data 3 |
| Data 4 |
Data 5 |
Data 6 |
| Data 7 |
Data 8 |
Data 9 |
| Data 10 |
Data 11 |
Data 12 |
On duble-click add border to first image:
On method accepts multiple events!


Hey! Check out our latest News Article! Apple Town V2? New Server? Come check it out. click here
Hello, welcome to Apple Town, to find more about what Apple Town is, and what servers we're currently online please click here


Settings
Settings saved
Stack Trace Line Break Pattern
Stack Trace Line Break Replacement
Save
Reset


Interface Of The Capuchin Agent Based Model Implemented In Netlogo On Download Scientific Diagram
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Netlogo Visualization Of An Agent Based Model Of Neanderthal Mobility Download Scientific Diagram
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Qubes Group Exploring Transmission Of Infectious Diseases On Networks With Netlogo The Iontw Simulation Tool
Netlogo User Community Models
0 2 Introduction To Agent Based Modeling Agent Based Evolutionary Game Dynamics
An Introduction To Agent Based Modeling Modeling Natural Social And Engineered Complex Systems With Netlogo A Review Topic Of Research Paper In Nano Technology Download Scholarly Article Pdf And Read For Free On
Course Introduction To Agent Based Models Using Netlogo
Group Agent Based And Individual Based Modeling
Agent Based Simulation Of Alternative Classroom Evacuation Scenarios Sciencedirect
9 Snapshot Of Agent Based Model From Netlogo Note That The Interdiction Download Scientific Diagram
Urban Science Free Full Text An Agent Based Modeling Framework For Simulating Human Exposure To Environmental Stresses In Urban Areas
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An Agent Based Model Of West Nile Virus Predicting The Impact Of Public Health Agents And Vaccinations On Horses Published In Curiosity Interdisciplinary Journal Of Research And Innovation
Agent Based Computational Economics Using Netlogo Volume 1 Bentham Science


The Urban Hotel Kyoto is a great choice for travelers who want to get around in Kyoto. Just 15 minutes from Kyoto Station, it is perfectly located for both sightseeing and business, and offers quick easy access to prime sites like Fushimiinari-taisha Shrine and Kiyomizu-dera Temple. If you want to relax in the seasonal beauty of Kyoto, stay at the Urban Hotel Kyoto.


{{ partial "header" . }} J Bums { this is a 404 error }_ I think the URL is probs wrong, in that it doesn't lead to a page. Do you want to go home ? {{ partial "footer" . }}
{ this is a 404 error }_
I think the URL is probs wrong, in that it doesn't lead to a page. Do you want to go home ?


|
Copley Motion Library
|
This structure holds the position loop configuration parameters specific to the Copley amplifier. More...
Public Member Functions | |
| PosLoopConfig (void) | |
| Default constructor. More... | |
Public Attributes | |
| int16 | kp |
| Proportional gain. | |
| int16 | kvff |
| Velocity feed forward. | |
| int16 | kaff |
| Acceleration feed forward. | |
| int16 | ki |
| Integral gain. | |
| int16 | kd |
| Derivative gain. | |
| int16 | scale |
| Scaling factor. More... | |
| int16 | xKd |
| cross coupling derivative gain | |
| int16 | xKi |
| cross coupling integral gain | |
| int16 | xKp |
| cross coupling proportional gain | |
| int16 | kiDrain |
| Position loop drain value for integral sum. Set to 0 to disable. | |
This structure holds the position loop configuration parameters specific to the Copley amplifier.
The position loop is one of three servo control loops used by the amplifier to control a motor. The configuration parameters used by this control loop allow the servo performance to be 'tuned' for various motors and loads.
The amplifier member functions Amp::GetPosLoopConfig and Amp::SetPosLoopConfig are used to read and write this data to the amplifier.
|
inline |
Default constructor.
Simply initializes all servo parameters to zero.
| int16 scale |
Scaling factor.
This is a multiplier that is applied to the output of the position loop. It's scaled up by 100, so setting the scaling factor to 1234 would multiply the output of the loop by 12.34. This parameter was added in firmware version 3.30. For any earlier version it will default to 100 (scale by 1.0).


Coalition for Good is a network of individuals, networks, businesses and organizations who are taking a visible, active Anti-Racism + Anti-Othering position and are committed to this work.
We are dedicated to our Common Good.
We view the world as a community: humans, animals, and the planet itself. We connect and support all who are doing the transformative work of creating a more compassionate, inclusive, just, and equitable world for all. We are a membership organization connecting all who are guided and inspired by our shared caring values and ideals.
Ethos
Healing, transformation and commitment to The Community Good begins with being aware With awareness we can expand and deepen our capacity to care With care comes connection and relationship With relationship comes the opportunity to see truth and build trust With trust comes heartfelt compassion and empathy With compassion and empathy come justice and healing With justice and healing comes peace With PEACE we can create meaningful, joyful sustainable lives, communities and societies BUT, FIRST, WE MUST CARE
Unity in diversity
Mission
Facilitate
Facilitate cultural, systemic transformation toward our shared Anti-Racism + Anti-Othering vision via collaborative spaces, platforms and projects
Empower
Empower diverse, multi-sector organizations and communities in the transformative work of building caring, diverse, inclusive, just, equitable, resilient societies by providing educational materials, tools and programs to the public, business and organizations
Create
Create membership organizations and online platforms to connect individuals, organizations and businesses for the purpose of engaging in activities and projects that benefit the Community Good
Strengthen
Strengthen communities by supporting the many existing aligned grassroots, community-supportive projects and organizations; sponsor and incubate programs that encourage more diverse, inclusive, equitable community ownership; cultivate intersectoral collaborative connections and relationships
Collaborate
Create collaborative opportunities based upon the United Nations Sustainable Development Goals through a lens prioritizing racial justice + equity
Projects
No-Othering ZONE Campaign™
Multi-faceted, multimedia campaign with programs for adults and children aimed at raising awareness of Othering, strengthening our empathy muscles, and catalyzing a more collective sense of belonging.
Learn MoreCoalition for Good Community™
Social media platform for our community, which shares similar values and visions for a better world.
Learn MoreGood Talks™
An independent, Anti-Racist, online No-Othering Zone in the form of a private, moderated and facilitated discussion forum.
Learn MoreLegacy Wishes
A wish-granting organization for Elder Activists (55+) who are working – and struggling as they work – to create a more caring, just, inclusive world where everyone belongs.
Learn More


Order your RM Band memorabilia here!
Pith Helmet
£100
Accessories?
Total = £0
Military Side Drum
£200
Total = £
Bugle
£150


{% extends "base.html" %} {% block body %}
What? This finds geological information from plaintext. Currently it just finds geochronological intervals and gives details about them, but will hopefully be extended.
Whence? This was hacked together by Agile Scientific
Examples The results are from the International Commission on Stratigraphy's geologic time scale. Here are some things this web app might do one day:


This is a mixture of elements such as you might find in a normal document. There are headings, paragraphs, code fragments
, and many other inline elements. The fonts used for these various elements will depend on what the author has declared, and what the browser's default styles happen to be, and how the two interleave.
Here we have some preformatted text just for the heck of it.
If you want to make changes to your startup script under DOS, you start by typing edit autoexec.bat. Of course, if you're running DOS, you probably already know that.
—The Unknown Author


${require('../partials/head.html')}
${require('../partials/nav.html')}Not in use
For uniform representation of fonts, this page uses web fonts provided by Google. When you open a page, your browser loads the required web fonts into your browser cache to display texts and fonts correctly.
For this purpose your browser has to establish a direct connection to Google servers. Google thus becomes aware that our web page was accessed via your IP address. The use of Google Web fonts is done in the interest of a uniform and attractive presentation of our website. This constitutes a justified interest pursuant to Art. 6 (1) (f) DSGVO.
If your browser does not support web fonts, a standard font is used by your computer.
Further information about handling user data, can be found at https://developers.google.com/fonts/faq and in Google’s privacy policy at https://www.google.com/policies/privacy/.
GitHub may collect Technical Information from visitors to your GitHub Pages website, including logs of visitor IP addresses, to maintain the security and integrity of the website and service. GitHub Privacy Statement


viewport.fitBounds(bounds); //Ignores constraints
viewport.fitBoundsWithConstraints(bounds);
viewport.fitBoundsWithConstraints(bounds, true); //immediate
//Initially ignore constraints viewport.fitBounds(bounds); //Apply constraints after 1 second delay setTimeout(() => viewport.applyConstraints(), 1000);
Pick an overlay above to show the bounds


News story
This month Jamie Oliver’s Fifteen Cornwall won a top award at the Europe wide RegioStars 2014 run by the European Commission.
Jamie Oliver’s Fifteen Cornwall has won a top award at the Europe wide RegioStars 2014. The critically acclaimed restaurant at Watergate Bay, in Cornwall, beat off 4 other shortlisted finalists in the ‘Inclusive growth: Creating jobs for the young generation category’.
Fifteen Cornwall is a social enterprise run by the charity Cornwall Food Foundation. The restaurant, which uses Jamie Oliver’s international brand, was originally set up through investment from the European Social Fund (ESF) and European Regional Development Fund (ERDF). The charity continues to receive ESF convergence funding for its apprentice programme, which is also supported by mainstream funding from the Skills Funding Agency and Jobcentre Plus.
The achievement of winning this prestigious award can be traced back to the aims of the enterprise which wanted to inspire disadvantaged young people to transform their lives through food and create opportunities for them to become apprentice chefs.
Since May 2006, the Cornwall Food Foundation has enrolled more than 140 apprentices, with 80% of them still cooking today. The Fifteen Cornwall Apprenticeship programme is about to start training its 9th cohort of future chefs. The Oliver-branded restaurant invests £1 million each year back into the local economy through its 70% local sourcing policy and has created 80 jobs in addition to the 86 apprenticeships so far completed.
Mark Yeoman, head of ESF convergence communication, said: “Fifteen Cornwall has and continues to set important benchmarks – in terms of its enduring success in supporting young people to be the best they can, its emphasis on a successful business driving its social enterprise, and in its wider economic contribution to the quality of the food and tourism sectors in Cornwall. In Cornwall we know Fifteen Cornwall is important and it is great to see this recognised as a beacon of success across Europe.”
Barbara Spicer, Interim Chief Executive of the Skills Funding Agency, said: “Well done to Fifteen Cornwall on winning this prestigious award - it clearly illustrates the impact that social enterprises can bring to a community, the Cornwall Food Foundation is doing great work through its engagement with disadvantaged young people. I’m also delighted to hear of the success of the restaurant’s Apprenticeship programme and how much the local economy is benefiting from this along with the opportunities it continues to provide to young people in the area.”
You can view a video recorded by Jamie Oliver about receiving the award online .
Published: 16 April 2014
From: Skills Funding Agency
Part of: Further education and training


An implementation of multiple-locus association mapping on a genome-wide scale. 'Eagle' can handle inbred and outbred study populations, populations of arbitrary unknown complexity, and data larger than the memory capacity of the computer. Since 'Eagle' is based on linear mixed models, it is best suited to the analysis of data on continuous traits. However, it can tolerate non-normal data. 'Eagle' reports, as its findings, the best set of snp in strongest association with a trait. For users unfamiliar with R, to perform an analysis, run 'OpenGUI()'. This opens a web browser to the menu-driven user interface for the input of data, and for performing genome-wide analysis.
| Version: | 1.2.0 |
| Depends: | R (≥ 3.4), shinyFiles |
| Imports: | matrixcalc, shiny, shinythemes, shinyBS, shinyjs, stats, utils, parallel, data.table |
| LinkingTo: | RcppEigen, Rcpp |
| Published: | 2018-12-17 |
| Author: | Andrew George [aut, cre], Joshua Bowden [ctb], Ryan Stephenson [ctb], Hyun Kang [ctb], Noah Zaitlen [ctb], Claire Wade [ctb], Andrew Kirby [ctb], David Heckerman [ctb], Mark Daly [ctb], Eleazar Eskin [ctb] |
| Maintainer: | Andrew George <andrew.george at csiro.au> |
| Contact: |<EMAIL_ADDRESS>|
| License: | GPL-3 |
| URL: | http://eagle.r-forge.r-project.org |
| NeedsCompilation: | yes |
| CRAN checks: | Eagle results |
| Reference manual: | Eagle.pdf |
| Package source: | Eagle_1.2.0.tar.gz |
| Windows binaries: | r-devel: Eagle_1.1.0.zip, r-release: Eagle_1.1.0.zip, r-oldrel: Eagle_1.1.0.zip |
| OS X binaries: | r-release: Eagle_1.1.0.tgz, r-oldrel: Eagle_1.1.0.tgz |
| Old sources: | Eagle archive |
Please use the canonical form https://CRAN.R-project.org/package=Eagle to link to this page.


Rather than force everyone at your company to learn incredibly difficult terminal commands, we allow anyone to query the data with natural language to return data.
Database Free!
No more dealing with the dreaded "error establishing a database connection."
1.2 seconds to load
On average, our sites load in just over one second.


{% block logout-text %}
{% blocktrans trimmed %}
You are logged out of this Chameleon site.
{% endblocktrans %}
{% endblock %}
{% if logout_url %}
{% block logout-secure-text %}
{% blocktrans trimmed %}
You may still be logged in to Chameleon Portal. To sign out of
the Portal, please go to the sign out page
here.
{% endblocktrans %}
{% endblock %}


Class EigenvalueDecomposition
Eigenvalues and eigenvectors of a real matrix.
Inheritance
Inherited Members
Namespace: CADability.LinearAlgebra
Assembly: CADability.dll
Syntax
[Serializable]
public class EigenvalueDecomposition
Remarks
If A is symmetric, then A = VDV' where the eigenvalue matrix D is diagonal and the eigenvector matrix V is orthogonal. I.e. A = V.Multiply(D.Multiply(V.Transpose())) and V.Multiply(V.Transpose()) equals the identity matrix. If A is not symmetric, then the eigenvalue matrix D is block diagonal with the real eigenvalues in 1-by-1 blocks and any complex eigenvalues, lambda + imu, in 2-by-2 blocks, [lambda, mu; -mu, lambda]. The columns of V represent the eigenvectors in the sense that AV = VD, i.e. A.Multiply(V) equals V.Multiply(D). The matrix V may be badly conditioned, or even singular, so the validity of the equation A = VD*Inverse(V) depends upon V.cond().
Constructors
| Improve this Doc View SourceEigenvalueDecomposition(Matrix)
Check for symmetry, then construct the eigenvalue decomposition
Declaration
public EigenvalueDecomposition(Matrix Arg)
Parameters
| Type | Name | Description |
|---|---|---|
| Matrix | Arg | Square matrix |
Remarks
Provides access to D and V
EigenvalueDecomposition(Double[], Double[])
Constructs the eigenvalue decomposition from a symmetrical, tridiagonal matrix.
Declaration
public EigenvalueDecomposition(double[] d, double[] e)
Parameters
| Type | Name | Description |
|---|---|---|
| System.Double[] | d | |
| System.Double[] | e |
Properties
| Improve this Doc View SourceBlockDiagonal
Gets the block diagonal eigenvalue matrix
Declaration
public Matrix BlockDiagonal { get; }
Property Value
| Type | Description |
|---|---|
| Matrix |
EigenValues
Gets the eigenvalues.
Declaration
public Complex[] EigenValues { get; }
Property Value
| Type | Description |
|---|---|
| Complex[] | diag(D) |
EigenVectors
Returns the eigenvector matrix
Declaration
public Matrix EigenVectors { get; }
Property Value
| Type | Description |
|---|---|
| Matrix |
ImagEigenvalues
Gets the imaginary part of the eigenvalues
Declaration
public double[] ImagEigenvalues { get; }
Property Value
| Type | Description |
|---|---|
| System.Double[] | imag(diag(D)) |
RealEigenvalues
Gets the real part of the eigenvalues.
Declaration
public double[] RealEigenvalues { get; }
Property Value
| Type | Description |
|---|---|
| System.Double[] | real(diag(D)) |


PhotoGallery
Photographer Name
Photographer Name
Photographer Name
Photographer Name
Photographer Name
Photographer Name


Changing your car's oil at regular intervals is a vital part of keeping your engine running properly. The purpose of engine oil is to keep the internal parts of your car's engine lubricated and cool. It keeps the moving parts from grinding against each other causing wear and damage.
You should get your oil changed at a lube shop or dealership (or change it yourself!) every 3,000 to 5,000 miles.


You Scored
% -
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1. What is the answer to life, the universe and everything?
2.  Which factors will contribute to the end of humanity as we know it?
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Cats
Advancements in artificial intelligence
Check Answers


@* * Copyright 2020 HM Revenue & Customs * * 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. *@ @import uk.gov.hmrc.play.views.html.helpers._ @import helpers._ @import binders.propertylinks._ @import controllers.propertyLinking.DeclarationVM @import config.ApplicationConfig @(model: DeclarationVM, isRatesBillEvidence: Boolean, clientDetails: Option[ClientDetails] = None)(implicit request: Request[_], messages: Messages, config: ApplicationConfig) @backLink = @{if (isRatesBillEvidence) { controllers.propertyLinking.routes.UploadController.show(EvidenceChoices.RATES_BILL).url } else { controllers.propertyLinking.routes.UploadController.show(EvidenceChoices.OTHER).url } } @clientId = @{clientDetails.map(_.organisationId)} @main_template( Messages("declaration.title"), topBackLink = true, bottomBackLink = true, topNavigation = true, showLogout = true, backLinkUrl = Some(backLink) ) {
@messages("declaration.p.1")
}


{% extends 'base.html' %} {% load activity_tags %} {% load miscs_tags %} {% block title %}{{ category.name }}{{ block.super }}{% endblock %} {% block content %} {{ category.name }} {% with page_obj as threads_in_category %} Thread{{ threads_in_category | length | pluralize }} - {{ threads_in_category | length }} {% endwith %} {{ category.description }} Topic Prefix Starter Likes Replies Views Created {% for thread in page_obj %} {% if thread.pin %} {% endif %} {% if thread.is_locked %} {% endif %} {{ thread.title }} {{ thread.get_prefix_display }} {{ thread.created | time_ago }} {% activity_action_queryset 'LIK' thread as thread_likes %} {{ thread.get_prefix_display }} {{ thread.starter.username }} {{ thread_likes | length | pretty_count }} {{ thread.posts.all | length | pretty_count }} {{ thread.views | pretty_count }} {{ thread.created | time_ago }} {% empty %} There are no threads yet in this category {% endfor %} {% endblock %}


Conventions¶
Docstring¶
Following a consistent docstring format is recommended for other users to understand more about the code.
Google Docstring:
"""
Title
Description
Args:
input (type) : input description
Returns:
output (type) : output description
References:
Some source or reference links.
Help:
remarks content
TODO and Additional Sections (See Napoleon readthedocs)
"""
Note
Docstring also applies to GHPython component, the docstring is used to assign tooltips for the component
Help section appears on GHPython Help content.
References:
Workflow¶
Workflow script is a sequence of operations which process a predefined Input and generate a specific result Output.
All generic workflow scripts should be placed in Tools
.
All project specific scripts should be placed in their corresponding Code
folder per project.
Template:
1 2 3 4 5 6 7 8 9 10 11 | import armacode
def main(x, y):
"""
Docstring
"""
result = x + y
return result
if __name__ == "__main__":
main()
|
Note
All workflow should be defined in a main()
function and call it safely using if __name__ == "__main__":
Command¶
A python script can be used as a Rhino Command.
Workflow that are stable has been fully tested and working as intended should be turned into a command for easy execution.
Command python files are named with a suffix _cmd.py
. All commands are stored in the Plug-in
folder.
Create a command:
- Open Python script editor using
EditPythonScript
- File > New > Command
- Select the AR-MA plugin.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | import armacode
import rhinoscriptsyntax as rs
import Rhino
__commandname__ = "CommandName"
# RunCommand is the called when the user enters the command name in Rhino.
# The command name is defined by the filname minus "_cmd.py"
def RunCommand( is_interactive=True ):
print "Hello", __commandname__
# get a point
point = rhinoscript.userinterface.GetPoint()
if( point != None ):
rhinoscript.geometry.AddPoint(point)
# you can optionally return a value from this function
# to signify command result. Return values that make
# sense are
# 0 == success
# 1 == cancel
# If this function does not return a value, success is assumed
return 0
if __name__ == "__main__":
RunCommand()
|


How SaaS providers are preparing for GDPR
Sometimes the best way to get a sense of something—especially something as complex as GDPR—is to see how your peers are thinking about it. Here’s a collection of documents that some of the most-successful cloud and SaaS providers have put together to explain how they plan to comply with the law; the requirements they have in place for customers and subprocessors; and also their lists of subprocessors that handle personal data.
While all this information is useful for people learning about GDPR, posting it publicly also allows companies to answer any questions their customers (or potential customers) might have in a scalable manner. Typically, SaaS providers will include at least the following content as part of explaining their GDPR compliance:
- Overview of GDPR, including what they’re doing to comply and help their customers comply.
- Data Processing Addendum/Amendment/Agreement (DPA) laying out their contractual relationships and liabilities with customers in the context of GDPR.
- A list of processors and/or subprocessors that process data on their behalf. This includes IaaS providers, support vendors and anyone else that stores or otherwise processes customers’ personal data.
If you’re a SaaS provider and want to add your information, or if you’ve come across some particularly useful information, please drop us a line or make a pull request.
GDPR compliance in action
Apart from reading the documentation and legal content SaaS providers are preparing around GDPR, it can also be helpful to see some concrete examples. Here is how a handful of popular SaaS services are adding functionality and changing their terms of service to comply with GDPR, and how they’re communicating these changes to customers:
Intercom is shortening the length of time for which it stores data on visitors to customers’ sites
In preparation for the new EU General Data Protection Regulation (GDPR), we will now be expiring Visitor data once a Visitor has not been seen for nine months.
This means that from May 11th, 2018:
- We will automatically delete the IP and location of visitors who have not visited your site in 9 months.
- If a visitor returns after 9 months they will be treated like a new visitor. There will be no record of previous visitor auto messages or conversations.
This change only impacts Visitor data – all other data is unaffected. Note, while GDPR is an EU regulation, it ultimately affects any business with customers in the EU which is why we are applying these changes globally across our entire customer base.
Slack has built tools for importing, exporting and deleting user data
Customers have requested tools to help them comply with the GDPR. And we’re happy to say that we’ve built those tools.
Compliance-related tools include the following:
- Import and export tools. Businesses and organizations may access, import, and export all their Customer Data, including private channels and direct messages.
- Profile deletion tool. Help customers respond to user requests to delete personal information, such as names and email addresses, from a Slack account.
- Workspace settings center. See your team’s plan and settings, or contact an admin who controls the workspace.
Segment is building tools for deleting and suppressing user data
To help you comply with user requests related to the right to erasure (the right to be forgotten), the right to object (the various rights to halt certain processing), and the right to restrict processing (the right to restriction), we are developing new capabilities that will be available to all Segment customers in early 2018:
- Support for deletion requests: We are making it easy for you to honor requests related to the right to be forgotten by adding a new, secure endpoint to our existing HTTP API: /delete. Issuing a /delete call for a given userId via this endpoint will ensure all personal data related to that userId is deleted from Segment’s archives and your connected warehouses.
- Automatic suppression: To help you comply with requests related to the right to object or restrict, any userId associated with a /delete call will automatically be placed on a suppression list. For any userId on the suppression list, we will block all incoming personal data pertaining to that userId from being tracked by Segment and sent to connected Destinations.
Google Analytics is letting users set data-retention periods, adding data-deletion tools, and is enforcing new contracts and consent policies
Over the past year we’ve shared how we are preparing to meet the requirements of the GDPR, the new data protection law coming into force on May 25, 2018. Today we are sharing more about important product changes that may impact your Google Analytics data, and other updates in preparation for the GDPR. This e-mail requires your attention and action even if your users are not based in the European Economic Area (EEA).
Product Updates
Today we introduced granular data retention controls that allow you to manage how long your user and event data is held on our servers. Starting May 25, 2018, user and event data will be retained according to these settings; Google Analytics will automatically delete user and event data that is older than the retention period you select. Note that these settings will not affect reports based on aggregated data.
Action: Please review these data retention settings and modify as needed.
Before May 25, we will also introduce a new user deletion tool that allows you to manage the deletion of all data associated with an individual user (e.g. site visitor) from your Google Analytics and/or Analytics 360 properties. This new automated tool will work based on any of the common identifiers sent to Analytics Client ID (i.e. standard Google Analytics first party cookie), User ID (if enabled), or App Instance ID (if using Google Analytics for Firebase). Details will be available on our Developers site shortly.
As always, we remain committed to providing ways to safeguard your data. Google Analytics and Analytics 360 will continue to offer a number of other features and policies around data collection, use, and retention to assist you in safeguarding your data. For example, features for customizable cookie settings, privacy controls, data sharing settings, data deletion on account termination, and IP anonymization may prove useful as you evaluate the impact of the GDPR for your company’s unique situation and Analytics implementation.
Contract And User Consent Related Updates
Contract changes
Google has been rolling out updates to our contractual terms for many products since last August, reflecting Google’s status as either data processor or data controller under the new law (see full classification of our Ads product). The new GDPR terms will supplement your current contract with Google and will come into force on May 25, 2018.
In both Google Analytics and Analytics 360, Google operates as a processor of personal data that is handled in the service.
- For Google Analytics clients based outside the EEA and all Analytics 360 customers, updated data processing terms are available for your review/acceptance in your accounts (Admin ➝ Account Settings).
- For Google Analytics clients based in the EEA, updated data processing terms have already been included in your terms.
- If you don’t contract with Google for your use of our measurement products, you should seek advice from the parties with whom you contract.
Updated EU User Consent Policy
Per our advertising features policy, both Google Analytics and Analytics 360 customers using advertising features must comply with Google’s EU User Consent Policy. Google’s EU User Consent Policy is being updated to reflect new legal requirements of the GDPR. It sets out your responsibilities for making disclosures to, and obtaining consent from, end users of your sites and apps in the EEA.
Action: Even if you are not based in the EEA, please consider together with your legal department or advisors, whether your business will be in scope of the GDPR when using Google Analytics and Analytics 360 and review/accept the updated data processing terms as well as define your path for compliance with the EU User Consent Policy.
More reading
Convinced that GDPR will matter to your company and looking for some more guidance on how and where it might apply, or how other SaaS companies are thinking about it? You can check out some of our other pieces on this topic:


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Sorry for bringing this up again, but what is the mathlib recommended way to talk about finite sums?
Is it a tsum
over fin n
? Or should I create a s : finset (A)
and use s.sum
?
The library for the latter option is quite extensive
I think tsum
is just for infinite sums.
Thank you! So I will use s : finset (fin n)
and s.sum


[75] U.S. Energy Information Administration. How much oil is consumed in the United States. https://www.eia.gov/tools/faqs/faq.php?id=33&t=6