---
title: How to choose your wedding venue. Part two
excerpt: "Part two in the series on wedding venues and themes"
image_url: /img/blog/how-to-choose-your-wedding-venue-part-two.jpg
image_description: "Bride and groom seating in peacock chairs under a lighted sign"
categories: planning-tips
---
Wedding Venues and their respective themes
Now that you, hopefully, got a clearer idea of what you would like your wedding day to represent - a family bash in the country,
an urban soiree at an art gallery, or an adventure cross state, it feels like the day is getting contour, isn't it?
What's left is to create the atmosphere you want to share and enjoy with your guests. And for that, you need decor and styling efforts.
So, throughout this post, I will draw a layout of the most distinguished wedding styles and their corresponding venues.
To bring across this very difficult task, I will create a mood board and share heaps of pictures so you get the feel rather than give you a list
of items to buy, even though I will do that as well. 😆
It is a challenging task - accurately defining a theme or set its boundaries because frequently elements of decor overlap.
Often, a specific theme is a polished version (over many wedding seasons) or an extension of an overarching atmosphere.
My advice is to choose a feel, a frame if you will and then customize it as much as possible, add yourselves in the picture with bits and pieces of decor and experiences.
Now, I will try to pinpoint the key elements of the most known (and used) themes, and the rest is and should be you.
The venues are split into two categories: the conventional ones, that have known for years, such as castles, country houses, the famous renovated barns and lodges, private houses, ranches or farms.
Then, we have the unconventional venues, which the creatives of the day made trendy, these are becoming widely spread and booked.
Into this category fall: museums, art galleries, the conservatories, repurposed buildings.
I know a couple that got married in a repurposed train station which pretty much set up the theme. The original train tracks were embellishing the floor, and the details of the place were integrated as part of the decor: objects such as the station's clock or the rough edges of the space or the exposed red brick of the walls. It was quaint and absolutely lovely.
Coming back, the list continues, historic libraries can be an alternative place to get hitched, also the theaters or your favorite quirky restaurant in town. I believe there's a perfect venue for every couple's aesthetic needs.
Why I emphasize on choosing your venue before your theme or drawing the vision for styling is because sometimes, the venues can be a real help by having the most significant accessory pieces in place and then you are kind of set.
Popular wedding themes
Classy, elegant, timeless.
- Venue recommendation: a castle, a manor house, a very fancy hotel, or a country house.
- General feel: this theme has a royal aspect with clean cuts, pale colours, elegant flowers in matching tones, tall flower arrangements and crystal glassware. It is advisable not to have any decor elements that stand-out but instead make sure that all pieces work well together and complement each other. This theme should remind you of the old, aristocratic ballrooms.
It usually has a well-defined dress-code, a sit-down meal and I would say this is the most formal type of nuptials you can plan.
Vintage glam, art-deco, 1920's
- Venue recommendation: any conventional space will do. But to do proper justice to the Roaring 20s, your venue should ring of the beginnings of Waldorf Astoria or The Savoy. It doesn't have to be a hotel though. You can bring the glamour and bedazzlement in any of the above-mentioned spaces.
- General feel: Jay Gatsby's infamous parties; gold touches, monogrammed items (the must-have tier cake could be one of them, napkins, or even plates), statement flower arrangements, dark, moody, metallic colours, play with lighting.

A jazz band would definitively create the desired atmosphere.
Retro (the 50's and up)
- Venue Recommendation: country house, an up-to-date barn, a tipi, or a backyard.
- General feel: informal, laid back kind of celebration. This theme comes with lots of charity shops items, like doilies and tableware, porcelain figurines, old bottles of pop or cereal. And the must-have piece: a record player.  Keep in mind that every decade has its charm.
Shabby-chic
- Venue Recommendation: country house, a lodge, a garden or backyard.
- General feel: natural look, intimate, personal with a homey atmosphere, it is a family celebration, with mostly DIY and handmade touches. Infuse antique elements into your very own home decor accessories like cute signage, old valises, a typewriter, mismatched vases. You can even use teacups and saucers for the flower arrangements. Frame it all together with lots of bunting, colorful and messy bouquets and plants. Food stations and buffets will be the perfect add-on. Does this remind you of a fancy garden party? That's the theme's goal.
- Venue Recommendation: barns, lodges, cabins, farms, anything surrounded by open space and natural landscapes.
- General feel: fun, relaxed, lawn games kind of festivities. You can either opt for a rougher look or add some finer touches to it in order to glam it up a bit (such as metallic elements, neater tablescapes, a mirror seating chart etc.). The must-haves though are: reclaimed wood or anything reclaimed actually, watering canes, frames, baskets, ladders. Add everything garden/wildflowers, a great mix of it with a messy look. Focus on local produce, hearty meals, like family's favorites and food and drinks stations galore. To really bring it home add fairy lights, blankets, quilts, hay, wine barrels. The outfits can be informal: tweed, tartan, gingham.
Urban, edgy, modern.
Table hart for a Modern and Moody Wedding. Photo by
Jami Laree.
- Venue recommendations: any unconventional venue will do. Think industrial loft, music and arts Center, libraries.
- General feel: alternative, contemporary, fashionable. It could be highlighted by vibrant or dark hues, metallic elements (the signage or the chairs), marble and copper combos, bare-bulb lighting, exposed brick, velvet furniture, minimalist styling (Scandinavian decor - fine lines, geometric shapes). Think gourmet dining. Clothing wise: a modern take on the wedding attire: jumpsuit, capes.
Boho, Indie, Hipster, Moody
Flowers and pampas grass wedding arch. Photo by
Koby Brown.
- Venue Recommendation: the outdoors (desert, woodland, garden) or country houses, golf clubs or repurposed buildings with open spaces
- General feel: free-spirited, authentic, wild and adventurous. The style can be either whimsy, colorful with garden vibes or moody with darker tones and modern accents. Needed pieces: macrame, flower arches walls, branch tipis, flower crowns, carpets. And on the other side, we have pampas grass, peacock chairs, feathers or dreamcatchers and any flowy elements. Always breathtaking dresses (lace, intricate patterns, low backs) and it comes with the opportunity for colorful men wear. (yee)
Of course, all these are just some general lines, and it is good to have them in the back of your head when you scout for venues, but always personalize. Add a twist to any theme or style, or even better create your own.
Until next time.


Example of drawing an extra line on top of a bar chart using a renderlet. This is often wanted in order to show e.g. a regression line.
It would be nice to have better support in dc.js for such "derived" values, but this example is here to tide folks over until that happens.


--- title: Month arithmetic in R, a quick guide author: Richard Careaga date: '2018-10-20' slug: month-arithmetic-in-r-a-quick-guide categories: - Data Science tags: - R - tools - fintech ---
Assume we are asking the question on February 1 of a non-leap year.
Don’t worry; I’m not going to give a tedious account of all the potential ambiguities and subtle points of calculation. I just want to focus on the last question, which is common in the everyday worlds of finance and accounting, and point out that many software functions allow you to calculate months_between, but leave you hanging for months_inclusive.
Here are the months: February, March, April, May, June, July, August, September, eight different months of which six are not February or September.
My motivation is in knowing of payments due on the first of each month, what percentage were paid. Because payments were due on each of the eight months, I need not months_between, but months_inclusive, and not only half inclusive – I want to include both February and September.
What I found is a cautionary tale of embedded assumptions, some of which are made explicit, some of which are implied and others of which are opaque. Let’s look at how various months_between functions work in some popular environments.
This has to fall in the opaque category: semi-inclusive with two date pairs and non-inclusive with one.
IPython 6.5.0 -- An enhanced Interactive Python. Type '?' for help.
In [1]: %paste
from datetime import datetime
def diff_month(d1, d2):
return (d1.year - d2.year) * 12 + d1.month - d2.month
d1 = datetime(2018,2,1,0,0)
d2 = datetime(2017,8,1,0,0)
## -- End pasted text --
In [2]: diff_month(d1,d2)
Out[2]: 6
Credit: John La Rooy https://goo.gl/PhJeKb
This implementation, which was the simplest I found, but consistent with the others I looked at, is a straight forward months_between.
MariaDB [dlf]> create table temp ( -> id int not null, -> start date, -> end date -> ); Query OK, 0 rows affected (0.011 sec)
MariaDB [dlf]>
MariaDB [dlf]> INSERT INTO temp (id, start, end) VALUES (1, '2018-02-01', '2017-09-01');
Query OK, 1 row affected (0.002 sec)
MariaDB [dlf]>
MariaDB [dlf]> select month(end) - month(start) as 'Elapsed' from temp;
+---------+
| Elapsed |
+---------+
| 7 |
+---------+
1 row in set (0.000 sec)
Or
MariaDB [dlf]> select TIMESTAMPDIFF(MONTH, start, end) as “Elapsed” from temp; +———+ | Elapsed | +———+ | -5 | +———+ 1 row in set (0.000 sec)
probably because I used DATE objects instead of DATETIME objects. (The lost month arises from conventions of time of day.)
Just to throw in a ringer, which is again semi-inclusive.
Now that we’ve seen that the fully-inclusive calculation is rare, I have the sad duty to report that it’s a problem in R as well.
I started my search in the {base} package by looking at the documentation for difftime. The tell was in the function signature
difftime(time1, time2, tz,
units = c("auto", "secs", "mins", "hours",
"days", "weeks"))
(No units for months.)
Next, I tried the lubridate package 1, and it seemed to provid a way forward. From the documentation:
Adding months frustrates basic arithmetic because consecutive months have different lengths. With other elements, it is helpful for arithmetic to perform automatic roll over. For example, 12:00:00 + 61 seconds becomes 12:01:01. However, people often prefer that this behavior NOT occur with months. For example, we sometimes want January 31 + 1 month = February 28 and not March 3. %m+% performs this type of arithmetic. Date %m+% months(n) always returns a date in the nth month after Date. If the new date would usually spill over into the n + 1th month, %m+% will return the last day of the nth month (rollback()). Date %m-% months(n) always returns a date in the nth month before Date.
However, the arithmetic calculations required datetime objects (dates, plus times of day) required arguments in the %m-% operators to be of different classes. During several hours of tinkering, it seemed close to doing what I was looking for, but perhaps unattainable.
Further digging led me to mondate2 Its documentation notes
A mondate represents a date as a numeric equalling the number of months since the beginning of the current millennium (the “mondate epoch”). Somewhat arbitrarily, and at the risk of reopening a decade-old debate, “the beginning of the current millennium” is defined as the instant between December 31, 1999 and January 1, 2000. The need for a “mondate” class arises in the area of actuarial analysis, and other areas of financial modeling that need to reconcile to a company’s book of accounts. Its motivation is based on the following presumptions: 1. Business accounting-wise, the closing of the books for a month, quarter, and year are the important milestones for measuring time. 2. For accountants – and actuaries – it is usually not important to measure events on an hourly basis. 3. All events that occur during a business day, up to and including the closing of the books for a day, are all “accounted for” as having occurred “at the same time.” To appreciate the difficulty in measuring the passage of time in days, note that there are typically three fewer days in the first half of the year (January 1 through June 30) than there are in the second half. Yet accountants will say that on June 30th the year is half over. For another example, note that – with the exception of July/August and December/January – the same days of the month for two consecutive months are not one “month” apart if measured in days because, with those exceptions, consecutive months contain differing numbers of days, so which of the two months do you choose as the yardstick? Since changes in accounts over the course of a month, quarter and year are the amounts by which financial results are measured, it is important to be able to measure the passage of time where a year is comprised of twelve months of equal “accounting weight.”
A mondate is simply a real number whose fractional part represents the fraction of the month as of the end of the day. E.g., the fractional part of January 1st = 1/31; the fractional part of February 1st = 1/28 or 1/29, depending on the year. A mondate which is a whole number (i.e., no fractional part) corresponds to a month that is fully completed, whose subsequent month has not yet begun; i.e., the instant in time between one month and the next.
It took a while to digest that, but it seemed promising. The key difference with other approaches is that mondate measures in months from the beginning of its epoch, rather than seconds. Put another way, relevant in light of the pending GAAP change in 2019
I don’t care what day you recognized that income in April, I just want to be sure that it was April and not May
Here’s a toy example. One important aspect it ignores is Inf values arising from division by zero that came up in my motivating example. Another thing to note is that the package has objects that have to be converted to numeric objects and, in some cases, rounded up. Those are relatively minor and easy to implement.
> library(mondate)
> library(lubridate)
> start = "2018-02-01"
> end = "2018-09-01"
> fully_inclusive <- function (start, end) {
+ start <- mondate(start)
+ end <- mondate(end)
+ open_interval = (end - start) + 1
+ return(as.numeric(round(open_interval,0)))
+ }
> fully_inclusive(start,end)
[1] 8
So, now we’ve looked at something that started on February 1 and finished on September 1 and correctly concluded that eight months were involved.
Garrett Grolemund, Hadley Wickham (2011). Dates and Times Made Easy with lubridate. Journal of Statistical Software, 40(3), 1-25. URL http://www.jstatsoft.org/v40/i03/↩
Dan Murphy (2013). mondate: Keep track of dates in terms of months. R package version <IP_ADDRESS>. https://CRAN.R-project.org/package=mondate↩


| 1 | package fr.sii.ogham.email.sendgrid.v4.sender.impl.sendgrid.compat; | |
| 2 | ||
| 3 | import fr.sii.ogham.core.util.ClasspathUtils; | |
| 4 | ||
| 5 | /** | |
| 6 | * {@code sendgrid-java} 4.3.0 has classes declared in package | |
| 7 | * {@code com.sendgrid.helpers.mail} but in the generated JAR, the classes are | |
| 8 | * compiled into package {@code com.sendgrid}. This issue has been fixed since | |
| 9 | * 4.4.0. | |
| 10 | * | |
| 11 | * However, Spring Boot 2.1.x uses {@code sendgrid-java} 4.3.0... | |
| 12 | * | |
| 13 | * Therefore, this class helps to avoid classpath issues and uses the available | |
| 14 | * classes. | |
| 15 | * | |
| 16 | * @author Aurélien Baudet | |
| 17 | * | |
| 18 | */ | |
| 19 | public final class CompatUtil { | |
| 20 | /** | |
| 21 | * {@code sendgrid-java} package version 4.3.0 declares some classes in | |
| 22 | * package {@code com.sendgrid.helpers.mail.objects} (according to source | |
| 23 | * folder structure). However, the {@code package} declaration in every of | |
| 24 | * these classes points to {@code com.sendgrid}. | |
| 25 | * | |
| 26 | * This creates {@link ClassNotFoundException}s when trying to run Ogham | |
| 27 | * with {@code sendgrid-java} v4.3.0. As it is a mistake from SendGrid, we | |
| 28 | * could simply take the next version that fixes the issue. But some Spring | |
| 29 | * Boot versions (like 2.1.x) has direct dependency to {@code sendgrid-java} | |
| 30 | * v4.3.0. So we must provide a compatibility fix in order to make it work | |
| 31 | * with older Spring Boot versions. | |
| 32 | * | |
| 33 | * The default factory provides either | |
| 34 | * {@link CorrectPackageNameCompatFactory} for {@code sendgrid-java} v4.4+ | |
| 35 | * and WrongPackageNameCompatFactory for {@code sendgrid-java} v4.3.0. | |
| 36 | * | |
| 37 | * @return the factory that will provide instances of objects | |
| 38 | */ | |
| 39 | public static CompatFactory getDefaultCompatFactory() { | |
| 40 |
1
1. getDefaultCompatFactory : negated conditional → RUN_ERROR |
if (ClasspathUtils.exists("com.sendgrid.Email")) { |
| 41 |
1
1. getDefaultCompatFactory : replaced return value with null for fr/sii/ogham/email/sendgrid/v4/sender/impl/sendgrid/compat/CompatUtil::getDefaultCompatFactory → NO_COVERAGE |
return createV430CompatFactoryInstance(); |
| 42 | } | |
| 43 |
1
1. getDefaultCompatFactory : negated conditional → RUN_ERROR |
if (ClasspathUtils.exists("com.sendgrid.helpers.mail.objects.Email")) { |
| 44 |
1
1. getDefaultCompatFactory : replaced return value with null for fr/sii/ogham/email/sendgrid/v4/sender/impl/sendgrid/compat/CompatUtil::getDefaultCompatFactory → RUN_ERROR |
return new CorrectPackageNameCompatFactory(); |
| 45 | } | |
| 46 | throw new IllegalStateException("Can't provide a valid CompatFactory based on sendgrid-java classpath"); | |
| 47 | } | |
| 48 | ||
| 49 | private static CompatFactory createV430CompatFactoryInstance() { | |
| 50 | try { | |
| 51 | Class<?> klass = Class.forName("fr.sii.ogham.email.sendgrid.v4.sender.impl.sendgrid.compat.WrongPackageNameCompatFactory"); | |
| 52 |
1
1. createV430CompatFactoryInstance : replaced return value with null for fr/sii/ogham/email/sendgrid/v4/sender/impl/sendgrid/compat/CompatUtil::createV430CompatFactoryInstance → NO_COVERAGE |
return (CompatFactory) klass.newInstance(); |
| 53 | } catch (ClassNotFoundException | InstantiationException | IllegalAccessException e) { | |
| 54 | throw new IllegalStateException("Failed to create compatibility factory for sendgrid-java v4.3.0", e); | |
| 55 | } | |
| 56 | } | |
| 57 | | |
| 58 | private CompatUtil() { | |
| 59 | super(); | |
| 60 | } | |
| 61 | } | |
Mutations | ||
| 40 |
1.1 |
|
| 41 |
1.1 |
|
| 43 |
1.1 |
|
| 44 |
1.1 |
|
| 52 |
1.1 |


File generated from /Users/xenykr/Documents/project/Tellet/ssam/apps/ssam_message/.eunit/ssam_message_topic_dispatcher.erl by COVER 2014-10-08 at 11:23:44 **************************************************************************** | %% ------------------------------------------------------------------------ | %% Copyright (c) 2014, Kook Maeng<EMAIL_ADDRESS>| %% | %% Permission to use, copy, modify, and/or distribute this software for any | %% purpose with or without fee is hereby granted, provided that the above | %% copyright notice and this permission notice appear in all copies. | %% | %% THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES | %% WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF | %% MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR | %% ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES | %% WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN | %% ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF | %% OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE. | %% ------------------------------------------------------------------------ | | -module(ssam_message_topic_dispatcher). | | -behaviour(gen_server). | | -include_lib("ssam/include/ssam.hrl"). | -include("ssam_message.hrl"). | | %% APIs | -export([ | start_link/1, | stop/2, stop/3, | send/3, | request/2 | ]). | | %% Callbacks | -export([init/1, | handle_call/3, | handle_cast/2, | handle_info/2, | terminate/2, | code_change/3]). | | | -define(SERVER_TIMEOUT, 30*1000). | | -record(state, { | topic_key :: ssam_message_topic:key(), | server_timeout :: pos_integer() | }). | | %% Public functions | | start_link(TopicKey) -> 0..| gen_server:start_link(?MODULE, [TopicKey], []). | | stop(Server, TopicKey) -> 0..| stop(Server, TopicKey, normal). | | stop(Server, TopicKey, Reason) -> 0..| gen_server:cast(Server, {stop, TopicKey, Reason}). | | send(Server, Msgs, Targets) -> 0..| gen_server:call(Server, {send, Msgs, Targets}). | | request(Server, Request) -> 0..| gen_server:call(Server, {request, Request}). | | %% Callback functions | | init([TopicKey]) -> 0..| {ok, #state{topic_key = TopicKey, | server_timeout = ?SERVER_TIMEOUT}, ?SERVER_TIMEOUT}. | | handle_call({send, Msgs, Targets}, _From, State) -> 0..| lager:debug("send, Msgs: ~p, Targets: ~p", [Msgs, Targets]), 0..| {reply, ok, State, ?TOPIC_SERVER_TIMEOUT}; | | handle_call({request, Req}, _From, State) -> 0..| lager:debug("request, Req: ~p", [Req]), 0..| {reply, ok, State, ?TOPIC_SERVER_TIMEOUT}; | | handle_call(Unknown, From, State) -> 0..| lager:debug("Unknown: ~p, From ~p", [Unknown, From]), 0..| {reply, ok, State, ?TOPIC_SERVER_TIMEOUT}. | | handle_cast({stop, _TopicKey, Reason}, State) -> 0..| {stop, Reason, State}; | | handle_cast(Unknown, State) -> 0..| lager:error("Unknown: ~p", [Unknown]), 0..| {noreply, State, ?TOPIC_SERVER_TIMEOUT}. | | handle_info(timeout, State) -> 0..| {noreply, State, ?TOPIC_SERVER_TIMEOUT}; | | handle_info(_Msg, State) -> 0..| {noreply, State, ?TOPIC_SERVER_TIMEOUT}. | | terminate(Reason, _State) -> 0..| lager:debug("~p", [Reason]), 0..| ok. | | code_change(_OldVsn, State, _Extra) -> 0..| {ok, State}. | | %% Private functions | | |


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Microsoft Azure
読む時間の目安: 4 分You need an Azure Subscription to use this Docker Machine driver. Sign up for a free trial.
Note: This documentation is for the new version of the Azure driver, which started shipping with v0.7.0. This driver is not backwards-compatible with the old Azure driver. If you want to continue managing your existing Azure machines, please download and use machine versions prior to v0.7.0.
Authentication
The first time you try to create a machine, Azure driver asks you to authenticate:
$ docker-machine create --driver azure --azure-subscription-id <subs-id> <machine-name>
Running pre-create checks...
Microsoft Azure: To sign in, use a web browser to open the page https://aka.ms/devicelogin.
Enter the code [...] to authenticate.
After authenticating, the driver remembers your credentials up to two weeks.
KNOWN ISSUE: There is a known issue with Azure Active Directory causing stored credentials to expire within hours rather than 14 days when the user logs in with personal Microsoft Account (formerly Live ID) instead of an Active Directory account. Currently, there is no ETA for resolution, however in the meanwhile you can create an AAD account and login with that as a workaround.
Options
Azure driver only has a single required argument to make things easier. Please read the optional flags to configure machine details and placement further.
Required:
--azure-subscription-id
: (required) Your Azure Subscription ID.
Optional:
--azure-availability-set
: Azure Availability Set to place the virtual machine into. [?]--azure-docker-port
: Port number for Docker engine.--azure-environment
: Azure environment. For example,AzurePublicCloud
orAzureChinaCloud
.--azure-image
: Azure virtual machine image in the format of Publisher:Offer:Sku:Version [?]--azure-location
: Azure region to create the virtual machine. [?]--azure-no-public-ip
: Do not create a public IP address for the machine (implies--azure-use-private-ip
). Should be used only when creating machines from an Azure VM within the same subnet.--azure-open-port
: Make additional port number(s) accessible from the Internet [?]--azure-private-ip-address
: Specify a static private IP address for the machine.--azure-resource-group
: Azure Resource Group name to create the resources in.--azure-size
: Size for Azure Virtual Machine. [?]--azure-ssh-user
: Username for SSH login.--azure-static-public-ip
: Assign a static public IP address to the machine.--azure-subnet
: Azure Subnet Name to be used within the Virtual Network.--azure-subnet-prefix
: Private CIDR block. Used to create subnet if it does not exist. Must match in the case that the subnet does exist.--azure-use-private-ip
: Use private IP address of the machine to connect. Useful for managing Docker machines from another machine on the same network, such as when deploying Swarm.--azure-vnet
: Azure Virtual Network name to connect the virtual machine. [?] To specify a Virtual Network from another resource group, useresourcegroup:vnet-name
format.
Environment variables and default values
| CLI option | Environment variable | Default |
|---|---|---|
--azure-availability-set |
AZURE_AVAILABILITY_SET |
docker-machine |
--azure-docker-port |
AZURE_DOCKER_PORT |
2376 |
--azure-environment |
AZURE_ENVIRONMENT |
AzurePublicCloud |
--azure-image |
AZURE_IMAGE |
canonical:UbuntuServer:16.04.0-LTS:latest |
--azure-location |
AZURE_LOCATION |
westus |
--azure-no-public-ip |
- | - |
--azure-open-port |
- | - |
--azure-private-ip-address |
- | - |
--azure-resource-group |
AZURE_RESOURCE_GROUP |
docker-machine |
--azure-size |
AZURE_SIZE |
Standard_A2 |
--azure-ssh-user |
AZURE_SSH_USER |
docker-user |
--azure-static-public-ip |
- | - |
--azure-subnet-prefix |
AZURE_SUBNET_PREFIX |
<IP_ADDRESS>/16 |
--azure-subnet |
AZURE_SUBNET |
docker-machine |
--azure-subscription-id |
AZURE_SUBSCRIPTION_ID |
- |
--azure-use-private-ip |
- | - |
--azure-vnet |
AZURE_VNET |
docker-machine |
Notes
Azure runs fully on the new Azure Resource Manager (ARM) stack. Each machine created comes with a few more Azure resources associated with it:
- A Virtual Network and a subnet under it is created to place your machines into. This establishes a local network between your docker machines.
- An Availability Set is created to maximize availability of your machines.
These are created once when the first machine is created and reused afterwards. Although they are free resources, driver does a best effort to clean them up after the last machine using these resources is removed.
Each machine is created with a public dynamic IP address for external
connectivity. All its ports (except Docker and SSH) are closed by default. You
can use --azure-open-port
argument to specify multiple port numbers to be
accessible from Internet.
Once the machine is created, you can modify Network Security Group rules and open ports of the machine from the Azure Portal.
machine, Microsoft Azure, driver


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|
BTK
0.3dev.0
Open-source library to visualize/process biomechanical data
|
Template class to store data for any kind of measurement. More...
#include <btkMeasure.h>
Public Types | |
|
typedef MeasureTraits< Derived > ::Values | Values |
| Measures' values along the time. | |
| Public Types inherited from btk::DataObject | |
| typedef btkSharedPtr< const DataObject > | ConstPointer |
| typedef btkNullPtr< DataObject > | NullPointer |
| typedef btkSharedPtr< DataObject > | Pointer |
| Public Types inherited from btk::Object | |
| typedef btkSharedPtr< const Object > | ConstPointer |
| typedef btkSharedPtr< Object > | Pointer |
Public Member Functions | |
| Values & | GetValues () |
| const Values & | GetValues () const |
| void | SetValues (const Values &v) |
| Public Member Functions inherited from btk::DataObject | |
| DataObject * | GetParent () const |
| bool | HasParent () const |
| void | Modified () |
| void | SetParent (DataObject *parent) |
| void | Update () |
| Public Member Functions inherited from btk::Object | |
| unsigned long int | GetTimestamp () const |
Protected Member Functions | |
| MeasureData (int frameNumber) | |
| MeasureData (const MeasureData &toCopy) | |
| MeasureData & | operator= (const MeasureData &) |
| Protected Member Functions inherited from btk::DataObject | |
| DataObject () | |
| DataObject (const DataObject &toCopy) | |
| virtual | ~DataObject () |
| Protected Member Functions inherited from btk::Object | |
| Object () | |
| Object (const Object &toCopy) | |
| virtual | ~Object () |
Protected Attributes | |
| MeasureData< Derived >::Values | m_Values |
| Values of the measure. | |
| Protected Attributes inherited from btk::Object | |
| unsigned long int | m_Timestamp |
Additional Inherited Members | |
| Static Public Member Functions inherited from btk::DataObject | |
| static NullPointer | Null () |
Template class to store data for any kind of measurement.
Currently this class store a matrix defined by the given number of frames. The template Derived used by this class gives the number of columns (components) of the measure.
To add a new type of data (for example for 2D pressure mat or insole), you have to inherit from this class and add the method Resize(int frameNumber). You can also add other informations in inherited classes, like btk::Point::Data which contains reconstruction residuals.
|
protected |
Constructor which initialize the data with a matrix of zero. The given frameNumber corresponds to the matrix's row. The number of colums is automatically determined based on the given template Derived.
|
protected |
Copy constructor
|
inline |
Returns values of the measure. The exact output type depend of the Derived class
|
inline |
Returns values of the measure. The exact output type depend of the Derived class
|
protected |
Simply set the new values
| void btk::MeasureData< Derived >::SetValues | ( | const Values & | v | ) |
Sets values for the measure. The exact input type depend of the Derived class


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Prediction of cow milk percentage
In the data file “maldidata.rdata
” you find four objects:
Y
: The percentage of cow-milk for 4 replicates of 45 different milk mixturesX
: Mass Spectrometry data (MALDI-TOF
) for the milk samples. The 6179 variables is a quantification of molecule “size
” and “charge
” in a sample. For simplicity we may say that the size of molecules increases from variable 1 to variable 6179. The measurements are then amounts of molecules of different sizes. The method is used to separate proteins, peptides and other ionizable compunds.Ytest
: Cow-milk percentages for 45 extra test samplesXtest
: TheMALDI-TOF
values for the test samples.
You may plot the spectra in X
one-by-one as,:
plot(X[, 1], type = "l")
We can also plot multiple (all) spectra together, takes more time.
matplot(X[, 1:5], type = "l", lty = 1, col = "black")
The peaks show molecule sizes that are abundant in the sample.
- First run a PCA on
X
. How many components are needed to explain 80% and 90% of the variability inX
?
pr <- prcomp(X)
summary(pr)$importance[, 1:14]
PC1 PC2 PC3 PC4 PC5 PC6 PC7
Standard deviation 12.502 4.4833 3.0218 2.5373 2.0112 1.7430 1.30637
Proportion of Variance 0.648 0.0833 0.0379 0.0267 0.0168 0.0126 0.00708
Cumulative Proportion 0.648 0.7313 0.7691 0.7958 0.8126 0.8252 0.83228
PC8 PC9 PC10 PC11 PC12 PC13
Standard deviation 1.0875 1.05133 0.96666 0.91363 0.84363 0.83145
Proportion of Variance 0.0049 0.00458 0.00387 0.00346 0.00295 0.00287
Cumulative Proportion 0.8372 0.84176 0.84564 0.84910 0.85205 0.85491
PC14
Standard deviation 0.81638
Proportion of Variance 0.00276
Cumulative Proportion 0.85768
We need 5 components to explain 80% and 36 to explain 90% (check yourself). Hopefully we do not need to use all X-information to predict Y
.
- Compute the correlations between \(Y\) and the principal components. How can you use this get an idea of how many components PLS-regression will require to make a good model for cow-milk prediction?
cor(Y, pr$x)
PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9
[1,] 0.528 -0.754 0.0338 -0.225 0.0744 -0.0503 0.015 -0.166 -0.00757
PC10 PC11 PC12 PC13 PC14 PC15 PC16 PC17 PC18
[1,] -0.0754 -0.137 -0.0432 0.0183 0.0167 -0.0155 -0.0263 0.0222 -0.0187
PC19 PC20 PC21 PC22 PC23 PC24 PC25 PC26
[1,] -0.00495 -0.0413 0.00649 -0.0187 -0.0442 -0.0069 -0.0411 0.00412
PC27 PC28 PC29 PC30 PC31 PC32 PC33 PC34 PC35
[1,] -0.0123 0.017 -0.0147 0.0387 0.000618 0.0185 -0.0213 0.0478 -0.00964
PC36 PC37 PC38 PC39 PC40 PC41 PC42 PC43 PC44
[1,] -0.0106 -0.00503 0.021 -0.011 -0.00874 -0.0191 -0.014 0.0082 -0.0124
PC45 PC46 PC47 PC48 PC49 PC50 PC51 PC52
[1,] 0.0176 0.00597 0.0141 -0.0193 0.0217 -0.00107 -0.00454 0.00781
PC53 PC54 PC55 PC56 PC57 PC58 PC59 PC60
[1,] 0.00674 -0.0041 0.0027 -0.00404 -0.0269 0.00521 -0.00471 -0.000586
PC61 PC62 PC63 PC64 PC65 PC66 PC67 PC68
[1,] 0.0124 -0.0142 0.0125 -0.0181 -0.00766 0.00276 0.0146 -0.0221
PC69 PC70 PC71 PC72 PC73 PC74 PC75 PC76
[1,] -0.00245 -0.00385 -0.00334 -0.00403 -0.038 -0.0394 0.00702 0.0103
PC77 PC78 PC79 PC80 PC81 PC82 PC83 PC84
[1,] -0.017 -0.0104 -0.0116 -0.00895 0.00664 -0.00716 0.0086 -0.0205
PC85 PC86 PC87 PC88 PC89 PC90 PC91 PC92 PC93
[1,] -0.0217 0.018 0.0284 0.00673 0.0166 0.00445 -0.00696 -0.0109 -0.00113
PC94 PC95 PC96 PC97 PC98 PC99 PC100 PC101
[1,] 0.0244 0.0304 -0.0186 -0.00388 0.0214 -0.00707 -0.00238 0.000283
PC102 PC103 PC104 PC105 PC106 PC107 PC108 PC109 PC110
[1,] 0.0251 -0.00757 -0.0175 -0.0259 0.0244 -0.026 0.00272 -0.0157 0.0142
PC111 PC112 PC113 PC114 PC115 PC116 PC117 PC118 PC119
[1,] -0.0115 -0.009 -0.0115 0.0299 0.00924 0.00246 -0.01 -0.00907 -0.0242
PC120 PC121 PC122 PC123 PC124 PC125 PC126 PC127 PC128
[1,] 0.00516 -0.0066 0.0147 0.00467 -0.0254 -0.0224 -0.0124 0.00816 0.0101
PC129 PC130 PC131 PC132 PC133 PC134 PC135 PC136
[1,] -0.0142 -0.0119 -0.00018 -0.0108 -0.00172 0.00275 -0.00635 0.0103
PC137 PC138 PC139 PC140 PC141 PC142 PC143 PC144
[1,] -0.0087 0.00552 0.00742 -0.00805 -0.00327 0.0159 -0.00109 0.00291
PC145 PC146 PC147 PC148 PC149 PC150 PC151 PC152
[1,] -0.00378 -0.00148 -0.00736 -0.00656 0.00354 -0.00579 0.0034 0.00252
PC153 PC154 PC155 PC156 PC157 PC158 PC159 PC160
[1,] 0.0015 -0.00918 -0.0111 0.0232 0.0108 -0.00734 -0.00148 0.00503
PC161 PC162 PC163 PC164 PC165 PC166 PC167 PC168
[1,] -0.00242 -0.00583 -0.00701 0.00558 -0.00344 0.00436 0.00368 0.00529
PC169 PC170 PC171 PC172 PC173 PC174 PC175 PC176
[1,] -0.015 -0.0092 -0.0134 -0.00933 -0.00255 0.0113 0.00024 -0.000418
PC177 PC178 PC179 PC180
[1,] -0.0057 -0.0103 0.0218 0.0288
Components 1, 2, 4 and perhaps 8 are moderately to highly correlated with Y
. Supposedly 3 to 4 components will be necessary for PLSR.
- Fit a PLS-regression model using
Y
as response andX
as predictor (You may simply writeY ~ X
as your model call inplsr
. Also usencomp=10
as extra argument to only fit 1 to 10 components). Use thescoreplot()
function to make a scoreplot. Check the help-file for this function to see how you can chose the component numbers to plot, and how you can put labels to your observations. Plot component 1 against 2 and put observation numbers 1:180 as labels. If the noise level of the measurements is low, the replicates should group in clusters of size four (obs 1,2,3 and 4 are from the same mixture, and so on). Do you see any tendency to this?
plsmod <- plsr(Y ~ X, ncomp = 10)
scoreplot(plsmod, comps = c(1,2), labels = 'names', pch = 0.7)
We observe that there are clusters of observations and that there is a tendency of successive numbers to be close in the scoreplot. Cluster sizes are difficult to determine.
- Perform hierarchical clustering of the samples using the 3 first PLS-component scores as input variables. Try both “complete” and “average” agglomeration method and make a dendrogram. Are the replicate clusters more apparent in the dendrogram than in the scoreplot? Is there any samples that are very different from all others?
clust1 <- hclust(dist(plsmod$scores[,1:3]), method = "complete")
plot(clust1, cex = 0.5)
From the dendrogram we observe several clusters of size four, and some of three with successive observation numbers. This implies that the replicates are more similar to each other than samples from different milk samples. Sample 159 seems to be an outlier, very different from all others.
- Use K-means clustering with K=45 on the three first PLS-component scores. How do the replicates cluster?
clust2 <- kmeans(plsmod$scores[,1:3], centers = 45)
clust2$cluster
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
39 39 39 39 13 13 13 44 20 20 20 20 31 31 31 31 38 15
19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36
38 15 13 1 1 40 25 25 14 17 2 2 2 2 22 32 22 32
37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54
25 17 25 25 44 23 9 34 3 3 3 3 11 11 19 23 17 24
55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72
24 24 30 30 14 14 40 23 40 39 9 9 9 9 1 30 1 13
73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90
12 45 45 45 44 44 33 22 5 13 12 35 34 34 34 23 14 17
91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108
17 17 6 6 28 28 42 42 42 42 22 32 43 43 7 7 7 7
109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126
38 38 38 38 4 4 4 4 37 37 37 37 41 8 8 41 29 29
127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144
29 26 25 16 16 16 25 41 25 25 35 5 5 35 42 42 42 42
145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162
21 21 21 21 36 36 36 36 18 18 18 18 33 6 27 28 8 8
163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180
8 30 14 41 41 16 12 45 45 35 10 30 10 10 15 15 3 15
Many replicates fall into the same clusters, but some clusters observations from more than one “true” cluster.
E.g. cluster number 43 contains observations (97, 98, 99, 100) and (141, 142, 143, 144), which is a mixture of four
true replica clusters. We conclude that the replicates are somewhat similar, but there is some noise in the MALDI-TOF
data which makes similar milk mixtures hard to distinguish.
- We will use cross-validation to estimate the expected prediction error of PLSR and to choose the appropriate number of components. Instead of using Leave-One-Out Cross-validation we will exclude all four replicates in a “Leave-Four-Out” type of Cross-validation. Why is this smart?
Since the replicates are from the same mixture, they are not independent. If we use Leave-One-Out CV the three replicates still contained in the training set will make the model “too good” to predict the given mixture, and we will under-estimate the prediction error of new samples.
- Refit the plsmodel from exercise c. but add the arguments
validation="CV"
,segments=45
andsegment.type="consecutive"
in the plsr-model call. This sets up the “Leave-Four-Out” CV to be performed.
plsmod <- plsr(Y ~ X, ncomp = 10, validation = "CV",
segments = 45, segment.type = "consecutive")
- The sum of squared prediction errors (PRESS) for different number of components is given in the
validation$PRESS
element of the fitted pls-model. The null-model PRESS (prediction using the mean-response) is given in thevalidation$PRESS0
element. You find the MSEP-values (Mean Squared Error of Prediction) by dividing the PRESS by the number of observations (N=180). Make a prediction error plot of MSEP with 0 to 10 components. How many components do you think gives satisfying prediction of cow-milk content in new mixtures? Remember that simple models are often better than complex.
MSEP <- c(plsmod$validation$PRESS0, plsmod$validation$PRESS)/180
plot(0:10, MSEP, type = "b", col = 2, lwd = 2)
The prediction error is heavily reduced as we introduce components 1 and 2, but there is a small gain by adding components 3, 4 and 5. Simple models are usually more robust, so I would not go any further than 5 components here.
- Predict the cow-milk content of the test samples using
Xtest
as newdata in thepredict
-function and use the number of components you found as best from the previous exercise. Save the predictions into an object calledpred
. (See?predict.mvr
for the help-file to predict for pls-objects.). The predict-function returns an array of dimension [45,1,1] of predictions. You can extract all predictions bypred[,1,1]
.
pred <- predict(plsmod, newdata = Xtest, ncomp = 5)
Copy the folowing code into R and execute:
MSEPfunc <- function(y, yhat){
mean((y - yhat) ^ 2)
}
- Use
MSEPfunc()
to compute the MSEP-value for the test-predictions usingYtest
and the predicted values as inputs. Did the cross-validation under-estimate the prediction error?
MSEPfunc(Ytest, pred[,1,1])
[1] 0.00692
The MSEP-value is slightly larger than the value found for five components using Cross-validation, but the order of magnitude is the same.
- EXTRA for those interested. Redo the exercises g. and h. with Leave-One-Out CV. (See also lecture notes Lesson 7.) Compare the MSEP-values you find with the previous CV-routine.
plsmod2 <- plsr(Y ~ X, ncomp = 10, validation = "LOO")
MSEP2 <- c(plsmod2$validation$PRESS0, plsmod2$validation$PRESS)/180
plot(0:10, MSEP, type = "b", col = 2, lwd = 2)
points(0:10, MSEP2, type = "b", col = 4, lwd = 2)
We see that LOO-CV underestimates the prediction error, as commented in exercise f.


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REFER-FORMAT 7
REFER FILE
A reference file is a set of bibliographic references usable with refer. It can be indexed using the softwares inv and mkey for fast searching.
The strings defined by refer are taken directly from the files of references, which are in the following format. The references should be separated by blank lines. Each reference is a sequence of lines beginning with % and followed by a key-letter. The remainder of that line, and successive lines until the next line beginning with %, contain the information specified by the key-letter. In general, refer does not interpret the information, but merely presents it to the macro package for final formatting. A user with a separate macro package, for example, can add new key-letters or use the existing ones for other purposes without bothering refer.
The meaning of the key-letters given below, in particular, is that assigned by the –ms macros. Not all information, obviously, is used with each citation. For example, if a document is both an internal memorandum and a journal article, the macros ignore the memorandum version and cite only the journal article. Some kinds of information are not used at all in printing the reference; if a user does not like finding references by specifying title or author keywords, and prefers to add specific keywords to the citation, a field is available which is searched but not printed (K).
The key letters currently recognized by refer and –ms, with the kind of information implied, are:
- A: Author’s name
- B: Title of book containing item
- C: City of publication
- D: Date
- E: Editor of book containing item
- G: Government (NTIS) ordering number
- I: Issuer (publisher)
- J: Journal name
- K: Keys (for searching)
- L: Label
- M: Memorandum label
- N: Issue number
- O: Other information
- P: Page(s) of article
- R: Technical report reference
- T: Title
- V: Volume number
- X: or
- Y: or
- Z: Information not used by refer
REFER OUTPUT
The output of refer is a stream of string definitions, one for each of the fields of each reference, as shown below.
.]- .ds [A authors’ names ... .ds [T title ... .ds [J journal ... ... .][ type-number
The refer program, in general, does not concern itself with the significance of the strings. The different fields are treated identically by refer , except that the X, Y and Z fields are ignored (see the -i option of mkey) in indexing and searching. All refer does is select the appropriate citation, based on the keys. The macro package must arrange the strings so as to produce an appropriately formatted citation. In this process, it uses the convention that the ’T’ field is the title, the ’J’ field the journal, and so forth. The refer program does arrange the citation to simplify the macro package’s job, however. The special macro .]- precedes the string definitions and the special macro .][ follows. These are changed from the input .[ and .] so that running the same file through refer again is harmless.
The .]– macro can be used by the macro package to initialize. The .][ macro, which should be used to print the reference, is given an argument type-number to indicate the kind of reference, as follows:
- 1: Journal article
- 2: Book
- 3: Article within book
- 4: Technical report
- 5: Bell Labs technical memorandum
- 0: Other
The type is determined by the presence or absence of particular fields in the citation (a journal article must have a ’J’ field, a book must have an ’I’ field, and so forth). To a small extent, this violates the above rule that refer does not concern itself with the contents of the citation; however, the classification of the citation in troff macros would require a relatively expensive and obscure program. Any macro writer may, of course, preserve consistency by ignoring the argument to the .] [ macro. The reference is flagged in the text with the sequence
\*([.number\*(.]
where number is the footnote number. The strings [. and .] should be used by the macro package to format the reference flag in the text. These strings can be replaced for a particular footnote. The footnote number (or other signal) is available to the reference macro .][ as the string register [F. To simplify dealing with a text reference that occurs at the end of a sentence, refer treats a reference which follows a period in a special way. The period is removed, and the reference is preceded by a call for the string <. and followed by a call for the string >. For example, if a reference follows ’end.’ it will appear as
end\*(<.\*([.number\*(.]\*(>.
where number is the footnote number. The macro package should turn either the string >. or <. into a period and delete the other one. This permits the output to have either the form ’end[31].’ or ’end.31’ as the macro package wishes. Note that in one case the period precedes the number and in the other it follows the number.
In some cases users wish to suspend the searching, and merely use the reference macro formatting. That is, the user doesn’t want to provide a search key between .[ and . ] brackets, but merely the reference lines for the appropriate document. Alternatively, the user can wish to add a few fields to those in the reference as in the standard file, or override some fields. Altering or replacing fields, or supplying whole references, is easily done by inserting lines beginning with %; any such line is taken as direct input to the reference processor rather than keys to be searched. Thus
.[ key1 key2 key3 ... %Q New format item %R Override report name .]
makes the indicates changes to the result of searching for the keys. All of the search keys must be given before the first % line. If no search keys are provided, an entire citation can be provided in-line in the text. For example, if the eqn paper citation were to be inserted in this way, rather than by searching for it in the data base, the input would read
.[ %A B. W. Kernighan %A L. L. Cherry %T A System for Typesetting Mathematics %J Comm. ACM %V 18 %N 3 %P 151-157 %D March 1975 .]
This would produce a citation of the same appearance as that resulting from the file search. As shown, fields are normally turned into troff strings. Sometimes users would rather have them defined as macros, so that other troff commands can be placed into the data. When this is necessary, simply double the control character % in the data. Thus the input
.[ %V 23 %%M Bell Laboratories, Murray Hill, N.J. 07974 .]
is processed by refer into
.ds [V 23 .de [M Bell Laboratories, Murray Hill, N.J. 07974 ..
The information after %%M is defined as a macro to be invoked by .[M while the information after %V is turned into a string to be invoked by \*([V. At present -ms expects all information as strings.
LICENSE
The text of this manual page comes from Some application of Inverted Indexes in the UNIX System by M. E. Lesk, which is distributed under the bsd4 license.
SEE ALSO
refer(1), sortbib(1), mkey(1), inv(1), hunt(1), and Some application of Inverted Indexes in the UNIX System by M. E. Lesk.
AUTHORS
M. E. Lesk. Modified by Pierre-Jean Fichet.


mdl.eyetracking.run¶
-
class
mdl.eyetracking.
run
(window, timer, isPsychopy=True, libraries=False, subject=None, **kwargs)[source]¶ Module allowing communcation to the SR Research Eyelink eyetracking system. Code is optimized for the Eyelink 1000 Plus (5.0), but should be compatiable with earlier systems.
Notes
- According to [Pylink.chm](_staticpdfPylink.chm), the sequence of operations for implementing a trial is:
- Perform a DRIFT CORRECTION, which also serves as the pre-trial fixation target.
- Start recording, allowing 100 milliseconds of data to accumulate before the trial display starts.
- Draw the subject display, recording the time that the display appeared by placing a message in the EDF file.
4) Loop until one of these events occurs RECORDING halts, due to the tracker ABORT menu or an error, the maximum trial duration expires ‘ESCAPE’ is pressed, the program is interrupted, or abutton on the EyeLink button box is pressed. 5) Add special code to handle gaze-contingent display updates. 6) Blank the display, stop recording after an additional 100 milliseconds of data has been collected. 7) Report the trial result, and return an appropriate error code.
Methods
calibration
()Start calibration procedure. connect
([calibration_type, …])Connect to Eyelink. console
([c, msg])Allows user-friend console logging using ANSI escape codes. drift_correction
([source])Starts drift correction. finish_recording
([path])Ending Eyelink recording. gc
(bound, t_min[, t_max])Creates gaze contigent event. library
()Check if required libraries to run eyelink and Psychopy are available. sample
()Collects new gaze coordinates from Eyelink. send_message
(msg)Send message to Eyelink. send_variable
(variables)send trial variable to eyelink at the end of trial. set_eye_used
(eye)Set dominant eye. start_recording
(trial, block)Starts recording of Eyelink. stop_recording
([trial, block, variables])Stops recording of Eyelink. -
classmethod
console
(c='green', msg='')[source]¶ Allows user-friend console logging using ANSI escape codes.
Returns: - result :
str
ANSI escape code.
Notes
Colors are produced using ASCII Oct format. For example: ‘[40m’ See http://jafrog.com/2013/11/23/colors-in-terminal.html
Examples
>>> console(self, message, color='blue) >>> >>>
Attributes: - result :
-
connect
(calibration_type=13, automatic_calibration_pacing=1000, saccade_velocity_threshold=35, saccade_acceleration_threshold=9500, sound=True, select_parser_configuration=0, recording_parse_type='GAZE', enable_search_limits=True, ip='<IP_ADDRESS>')[source]¶ Connect to Eyelink.
Parameters: - ip :
string
Host PC ip address.
- calibration_type :
int
Calibration type. Default is 13-point. [see Eyelink 1000 Plus User Manual, 3.7 Calibration]
- automatic_calibration_pacing :
int
Select the delay in milliseconds, between successive calibration or validation targets if automatic target detection is activeSet automatic calibration pacing. [see pylink.chm]
- saccade_velocity_threshold :
int
Sets velocity threshold of saccade detector: usually 30 for cognitive research, 22 for pursuit and neurological work. Default is 35. Note: EyeLink II and EyeLink 1000, select select_parser_configuration should be used instead. [see EyeLink Programmer’s Guide, Section 25.9: Parser Configuration; Eyelink 1000 Plus User Manual, Section 4.3.5 Saccadic Thresholds]
- saccade_acceleration_threshold :
int
Sets acceleration threshold of saccade detector: usually 9500 for cognitive research, 5000 for pursuit and neurological work. Default is 9500. Note: For EyeLink II and EyeLink 1000, select select_parser_configuration should be used instead. [see EyeLink Programmer’s Guide, Section 25.9: Parser Configuration; Eyelink 1000 Plus User Manual, Section 4.3.5 Saccadic Thresholds]
- select_parser_configuration :
int
Selects the preset standard parser setup (0) or more sensitive (1). These are equivalent to the cognitive and psychophysical configurations. Default is 0. [see EyeLink Programmer’s Guide, Section 25.9: Parser Configuration]
- sound :
bool
Should sound be used for calibration/validation/drift correction.
- recording_parse_type :
str
Sets how velocity information for saccade detection is to be computed. Enter either ‘GAZE’ or ‘HREF’. Default is ‘GAZE’. [see Eyelink 1000 Plus User Manual, Section 4.4: File Data Types]
- enable_search_limits :
bool
Enables tracking of pupil to global search limits. Default is True. [see Eyelink 1000 Plus User Manual, Section 4.4: File Data Types]
Returns: - param :
pandas.DataFrame
Returns dataframe of parameters for subject.
Examples
>>> param = eyetracking.connect(calibration_type=13)
- ip :
-
set_eye_used
(eye)[source]¶ Set dominant eye. This step is required for recieving gaze coordinates from Eyelink->Psychopy.
Parameters: - eye :
str
Dominant eye (left, right). This will be used for outputting Eyelink gaze samples.
Examples
>>> dominant_eye = 'left' >>> eye_used = eyetracking.set_eye_used(eye=dominant_eye)
- eye :
-
calibration
()[source]¶ Start calibration procedure.
Returns: - isCalibration :
bool
Message indicating status of calibration.
Examples
>>> eyetracking.calibration()
- isCalibration :
-
drift_correction
(source='manual')[source]¶ Starts drift correction. This can be done at any point after calibration, including before and after eyetracking.start_recording has already been initiated.
Parameters: - source :
str
Origin of call, either manual (default) or from gaze contigent event (gc).
Returns: - isDriftCorrection :
bool
Message indicating status of drift correction.
Notes
Running drift_correction will end any start_recording event to function properly. Once drift correction has occured, it is safe to run start_recording.
Examples
>>> eyetracking.drift_correction()
- source :
-
start_recording
(trial, block)[source]¶ Starts recording of Eyelink.
Parameters: Returns: - isRecording :
bool
Message indicating status of Eyelink recording.
Notes
- tracker.beginRealTimeMode():
- To ensure that no data is missed before the important part of the trial starts. The EyeLink tracker requires 10 to 30 milliseconds after the recording command to begin writing data. This extra data also allows the detection of blinks or saccades just before the trial start, allowing bad trials to be discarded in saccadic RT analysis. A “SYNCTIME” message later in the trial marks the actual zero-time in the trial’s data record for analysis. [see pylink.chm]
- TrialID:
- The “TRIALID” message is sent to the EDF file next. This message must be placed in the EDF file before the drift correction and before recording begins, and is critical for data analysis. The viewer will not parse any messages, events, or samples that exist in the data file prior to this message. The command identifier can be changed in the data loading preference settings. [see Data Viewer User Manual, Section 7: Protocol for EyeLink Data to Viewer Integration]
- SYNCTIME:
- Marks the zero-time in a trial. A number may follow, which is interpreted as the delay of the message from the actual stimulus onset. It is suggested that recording start 100 milliseconds before the display is drawn or unblanked at zero-time, so that no data at the trial start is lost. [see pylink.chm]
Examples
>>> eyetracking.start_recording(trial=1, block=1)
- isRecording :
-
gc
(bound, t_min, t_max=None)[source]¶ Creates gaze contigent event. This function needs to be run while recording.
Parameters: - bound :
dict
[str
,int
]: Dictionary of the bounding box for each region of interest. Keys are each side of the bounding box and values are their corresponding coordinates in pixels.
- t_min :
int
Mininum duration (msec) in which gaze contigent capture is collecting data before allowing the task to continue.
- t_max :
int
orNone
Maxinum duration (msec) before task is forced to go into drift correction.
Examples
>>> # Collect samples within the center of the screen, for 2000 msec, >>> # with a max limit of 10000 msec. >>> region = dict(left=860, top=440, right=1060, bottom=640) >>> eyetracking.gc(bound=bound, t_min=2000, t_max=10000)
- bound :
-
sample
()[source]¶ Collects new gaze coordinates from Eyelink.
Returns: Examples
>>> eyetracking.sample(eye_used=eye_used)
-
send_message
(msg)[source]¶ Send message to Eyelink. This allows post-hoc processing of event markers (i.e. “stimulus onset”).
Parameters: - msg :
str
Message to be recieved by eyelink.
Examples
>>> eyetracking.console(c="blue", msg="eyetracking.calibration() started")
- msg :
-
send_variable
(variables)[source]¶ send trial variable to eyelink at the end of trial.
Parameters: - variable :
dict
or None Trial-related variables to be read by eyelink.
- variable :
-
stop_recording
(trial=None, block=None, variables=None)[source]¶ Stops recording of Eyelink. Also allows transmission of trial-level variables to Eyelink.
Parameters: Returns: - isRecording :
bool
Message indicating status of Eyelink recording.
Notes
- pylink.pumpDelay():
- Does a unblocked delay using currentTime(). This is the preferred delay function when accurate timing is not needed. [see pylink.chm]
- pylink.msecDelay():
- During calls to pylink.msecDelay(), Windows is not able to handle messages. One result of this is that windows may not appear. This is the preferred delay function when accurate timing is needed. [see pylink.chm]
- tracker.endRealTimeMode():
- Returns the application to a priority slightly above normal, to end realtime mode. This function should execute rapidly, but there is the possibility that Windows will allow other tasks to run after this call, causing delays of 1-20 milliseconds. This function is equivalent to the C API void end_realtime_mode(void). [see pylink.chm]
- TRIAL_VAR:
- Lets users specify a trial variable and value for the given trial. One message should be sent for each trial condition variable and its corresponding value. If this command is used there is no need to use TRIAL_VAR_LABELS. The default command identifier can be changed in the data loading preference settings. Please note that the eye tracker can handle about 20 messages every 10 milliseconds. So be careful not to send too many messages too quickly if you have many trial condition messages to send. Add one millisecond delay between message lines if this is the case. [see pylink.chm]
- TRIAL_RESULT:
- Defines the end of a trial. The viewer will not parse any messages, events, or samples that exist in the data file after this message. The command identifier can be changed in the data loading preference settings. [see Data Viewer User Manual, Section 7: Protocol for EyeLink Data to Viewer Integration]
Examples
>>> variables = dict(stimulus='face.png', event='stimulus') >>> eyetracking.stop_recording(trial=trial, block=block, variables=variables)
- isRecording :
-
finish_recording
(path=None)[source]¶ Ending Eyelink recording.
Parameters: Returns: - isFinished :
bool
Message indicating status of Eyelink recording.
Notes
- pylink.pumpDelay():
- Does a unblocked delay using currentTime(). This is the preferred delay function when accurate timing is not needed. [see pylink.chm]
- pylink.msecDelay():
- During calls to pylink.msecDelay(), Windows is not able to handle messages. One result of this is that windows may not appear. This is the preferred delay function when accurate timing is needed. [see pylink.chm]
- tracker.setOfflineMode():
- Places EyeLink tracker in offline (idle) mode. Wait till the tracker has finished the mode transition. [see pylink.chm]
- tracker.endRealTimeMode():
- Returns the application to a priority slightly above normal, to end realtime mode. This function should execute rapidly, but there is the possibility that Windows will allow other tasks to run after this call, causing delays of 1-20 milliseconds. This function is equivalent to the C API void end_realtime_mode(void). [see pylink.chm]
- tracker.receiveDataFile():
- This receives a data file from the EyeLink tracker PC. Source filename and destination filename should be given. [see pylink.chm]
Examples
>>> #end recording session >>> eyetracking.finish_recording()
- isFinished :


RFP: NAME accidentally walked onto the tracks - he got squished.
TPG: NAME used a body part as bait for fish.
PNR: NAME stood too close to the edge and fell.
TAM: NAME ate spoilt food, and death befell.
HBF: NAME disturbed a wasp nest, and ended up dead.
LTI: NAME crashed his plane, losing his head.

TNM: NAME did electrical work, and burnt in flames.
CLE: NAME ate superglue, and froze in place.
CTH: NAME aggravated a bear, disappearing without a trace.
AMK: NAME hid in a dryer, and couldn't get out!


public abstract class AutoProxyUtils
extends java.lang.Object
AbstractAutoProxyCreator
| 限定符和类型 | 字段和说明 |
|---|---|
static java.lang.String |
ORIGINAL_TARGET_CLASS_ATTRIBUTE
Bean definition attribute that indicates the original target class of an
auto-proxied bean, e.g. to be used for the introspection of annotations
on the target class behind an interface-based proxy.
|
static java.lang.String |
PRESERVE_TARGET_CLASS_ATTRIBUTE
Bean definition attribute that may indicate whether a given bean is supposed
to be proxied with its target class (in case of it getting proxied in the first
place).
|
| 构造器和说明 |
|---|
AutoProxyUtils() |
| 限定符和类型 | 方法和说明 |
|---|---|
static java.lang.Class<?> |
determineTargetClass(ConfigurableListableBeanFactory beanFactory,
java.lang.String beanName)
Determine the original target class for the specified bean, if possible,
otherwise falling back to a regular
getType lookup. |
static boolean |
shouldProxyTargetClass(ConfigurableListableBeanFactory beanFactory,
java.lang.String beanName)
Determine whether the given bean should be proxied with its target
class rather than its interfaces.
|
public static final java.lang.String PRESERVE_TARGET_CLASS_ATTRIBUTE
Boolean.TRUE
or Boolean.FALSE
.
Proxy factories can set this attribute if they built a target class proxy for a specific bean, and want to enforce that bean can always be cast to its target class (even if AOP advices get applied through auto-proxying).
public static final java.lang.String ORIGINAL_TARGET_CLASS_ATTRIBUTE
public static boolean shouldProxyTargetClass(ConfigurableListableBeanFactory beanFactory, @Nullable java.lang.String beanName)
"preserveTargetClass" attribute
of the corresponding bean definition.beanFactory
- the containing ConfigurableListableBeanFactorybeanName
- the name of the bean@Nullable public static java.lang.Class<?> determineTargetClass(ConfigurableListableBeanFactory beanFactory, @Nullable java.lang.String beanName)
getType
lookup.beanFactory
- the containing ConfigurableListableBeanFactorybeanName
- the name of the beanBeanFactory.getType(String)


DoesParagraph1HaveAClass
DoesParagraph2HaveAClass
Make Selection
Paragraph 1 which is NOT STYLED
Paragraph 2 which is styled


Keep a expandable panel and prevent it from collapsing.
Accordion is a part of easyui framework for jQuery. It lets you define your accordion component on web page more easily.
Content1
Content2


Legal Contract with PDFMake
Create a dummy rental contract.
Test with a few inputs.
Tenant Name
Rent Price
(Optional)
Image attachment #1
Paste an image from the clipboard (CTRL+V).
Image attachment #2
Paste again for a 2nd attachment.
Make PDF


Let’s see what Angular cooks for us
While new Ivy renderer is not feature completely yet, many people wonder how it will work and what changes it prepares for us.
In this article I am going to visualize Ivy change detection mechanism, show some things I am really excited about and also build simple app based on instructions, similar to angular Ivy instructions, from scratch.
First, let’s introduce the app I’m going to investigate here:
I created online demo that I use to understand how it works under the hood:
https://alexzuza.github.io/ivy-cd/ 👈
The demo uses angular 6.0.1 aot compiler. You can click on any lifecycle block to go to the definition.
In order to run change detection process just type something in one of those inputs that are below Sub-Child.
https://blog.angularindepth.com/angular-ivy-change-detection-execution-are-you-prepared-ab68d4231f2c


[Gecode] Reified nary equality
Christian Schulte
schulte at imit.kth.se
Tue May 11 10:36:40 CEST 2004
Uups, yes it did vanish... Sorry for screwing the interface. Alas, it never
had an implementation ;-)
Christian
--
Christian Schulte, http://www.imit.kth.se/~schulte/
-----Original Message-----
From: gecode-bounces at ps.uni-sb.de [mailto:gecode-bounces at ps.uni-sb.de] On
Behalf Of Guido Tack
Sent: Tuesday, May 11, 2004 10:16 AM
To: gecode at ps.uni-sb.de
Subject: [Gecode] Reified nary equality
Has the reified nary equality propagator for int vars. somehow vanished, or
am
I just blind?
(trying to get the Alice binding in sync again...)
--
Guido Tack
Programming Systems Lab
http://www.ps.uni-sb.de/~tack
_______________________________________________
Gecode mailing list
Gecode at ps.uni-sb.de http://www.ps.uni-sb.de/mailman/listinfo/gecode
More information about the gecode-users
mailing list


Concept UnsignedIntegerConceptAn integral type without a sign.
An integral type without a sign.
| Extends | IntegerConcept |
|---|---|
| All Extended | AssignableConcept, ComparableConcept, CopyConstructibleConcept, DefaultConstructibleConcept, DestructibleConcept, EqualityComparableConcept, IntegerConcept, LessThanComparableConcept |
| Defined in | <seqan/basic.h> |
| Signature |
UnsignedIntegerConcept<T>
|
Detailed Description
Expects an instance of type T to represent non-negative integral values and to provide the same operations as unsigned int. Every type T that fulfills the IntegerConcept fulfills either the SignedIntegerConcept or the UnsignedIntegerConcept.
Examples
//SEQAN_CONCEPT_ASSERT((UnsignedIntegerConcept<int>)); // fails to compile SEQAN_CONCEPT_ASSERT((UnsignedIntegerConcept<unsigned short>)); std::cout << Is<UnsignedIntegerConcept<char> >::VALUE << std::endl; // 0 std::cout << Is<UnsignedIntegerConcept<int> >::VALUE << std::endl; // 0 std::cout << Is<UnsignedIntegerConcept<unsigned short> >::VALUE << std::endl; // 1 std::cout << Is<UnsignedIntegerConcept<double> >::VALUE << std::endl; // 0
Valid Expressions
T a; unsigned int b; a = 1u; b = a; std::cout << static_cast<T>(0) < static_cast<T>(-1) << std::endl; // 1


{% extends "dashboard/dashboard_base.html" %} {% block newsfeed_content %}
Get started by creating a new project or tracking an existing one.
{{ item.comment }}


#include <FrequencyGovernor.hpp>
|
| | FrequencyGovernor ()=default |
| |
| virtual | ~FrequencyGovernor ()=default |
| |
| virtual void | init_platform_io (void)=0 |
| | Registers signals and controls with PlatformIO using the default control domain. More...
|
| |
| virtual int | frequency_domain_type (void) const =0 |
| | Get the domain type of frequency control on the platform. Users of the FrequencyGovernor can use this information to determine the size of the vector to pass to adjust_platform(). More...
|
| |
| virtual void | adjust_platform (const std::vector< double > &frequency_request)=0 |
| | Write frequency control, may be clamped between min and max frequency if request cannot be satisfied. More...
|
| |
| virtual bool | do_write_batch (void) const =0 |
| | Returns true if last call to adjust_platform requires writing. More...
|
| |
| virtual bool | set_frequency_bounds (double freq_min, double freq_max)=0 |
| | Sets min and max package bounds. The defaults before calling this method are the min and max frequency for the platform. More...
|
| |
| virtual double | get_frequency_min () const =0 |
| | Returns the current min frequency used by the governor. More...
|
| |
| virtual double | get_frequency_max () const =0 |
| | Returns the current max frequency used by the governor. More...
|
| |
| virtual double | get_frequency_step () const =0 |
| | Returns the frequency step for the platform. More...
|
| |
| virtual void | validate_policy (double &freq_min, double &freq_max) const =0 |
| | Checks that the minimum and maximum frequency are within range for the platform. If not, they will be clamped at the min and max for the platform. More...
|
| |
◆ FrequencyGovernor()
| geopm::FrequencyGovernor::FrequencyGovernor |
( |
| ) |
|
|
default |
◆ ~FrequencyGovernor()
| virtual geopm::FrequencyGovernor::~FrequencyGovernor |
( |
| ) |
|
|
virtualdefault |
◆ adjust_platform()
| virtual void geopm::FrequencyGovernor::adjust_platform |
( |
const std::vector< double > & |
frequency_request | ) |
|
|
pure virtual |
Write frequency control, may be clamped between min and max frequency if request cannot be satisfied.
- Parameters
-
| [in] | frequency_request | Desired per domain frequency. |
◆ do_write_batch()
| virtual bool geopm::FrequencyGovernor::do_write_batch |
( |
void |
| ) |
const |
|
pure virtual |
Returns true if last call to adjust_platform requires writing.
- Returns
- True if platform adjustments have been made, false otherwise.
◆ frequency_domain_type()
| virtual int geopm::FrequencyGovernor::frequency_domain_type |
( |
void |
| ) |
const |
|
pure virtual |
Get the domain type of frequency control on the platform. Users of the FrequencyGovernor can use this information to determine the size of the vector to pass to adjust_platform().
- Returns
- The domain with which frequency will be governed.
◆ get_frequency_max()
| virtual double geopm::FrequencyGovernor::get_frequency_max |
( |
| ) |
const |
|
pure virtual |
Returns the current max frequency used by the governor.
- Returns
- Maximum frequency.
◆ get_frequency_min()
| virtual double geopm::FrequencyGovernor::get_frequency_min |
( |
| ) |
const |
|
pure virtual |
Returns the current min frequency used by the governor.
- Returns
- Minimum frequency.
◆ get_frequency_step()
| virtual double geopm::FrequencyGovernor::get_frequency_step |
( |
| ) |
const |
|
pure virtual |
Returns the frequency step for the platform.
- Returns
- Step frequency.
◆ init_platform_io()
| virtual void geopm::FrequencyGovernor::init_platform_io |
( |
void |
| ) |
|
|
pure virtual |
Registers signals and controls with PlatformIO using the default control domain.
◆ make_shared()
| static std::shared_ptr<FrequencyGovernor> geopm::FrequencyGovernor::make_shared |
( |
void |
| ) |
|
|
static |
Returns a shared_ptr to a concrete object constructed using the underlying implementation.
◆ make_unique()
| static std::unique_ptr<FrequencyGovernor> geopm::FrequencyGovernor::make_unique |
( |
void |
| ) |
|
|
static |
Returns a unique_ptr to a concrete object constructed using the underlying implementation.
◆ set_frequency_bounds()
| virtual bool geopm::FrequencyGovernor::set_frequency_bounds |
( |
double |
freq_min, |
|
|
double |
freq_max |
|
) |
| |
|
pure virtual |
Sets min and max package bounds. The defaults before calling this method are the min and max frequency for the platform.
- Parameters
-
| [in] | freq_min | Minimum frequency value for the control domain. |
| [in] | freq_max | Maximum frequency value for the control domain. |
- Returns
- Returns true if internal state updated, otherwise false.
◆ validate_policy()
| virtual void geopm::FrequencyGovernor::validate_policy |
( |
double & |
freq_min, |
|
|
double & |
freq_max |
|
) |
| const |
|
pure virtual |
Checks that the minimum and maximum frequency are within range for the platform. If not, they will be clamped at the min and max for the platform.
- Parameters
-
| [in,out] | freq_min | Minimum frequency to attempt to set, and resulting valid minimum. |
| [in,out] | freq_max | Maximum frequency to attempt to set, and resulting valid maximum. |
The documentation for this class was generated from the following file:


Shop Name
Trendy style produce utilization Good item!
15 reviews
Reasonable price and high quality! Everywhere look good item!
12 reviews
Without the trendy timeless! Good to take advantage of daily item!
31 reviews


It’s time again for a witness update. My witness server is running strong (only 2 missing blocks for 7 months).
steemrewarding - a new auto voter (not finished yet)
I rented a new small server and registered https://steemrewarding.com for my newest project. I wrote about it in my last post. I’m developing an auto voter where it will be possible to set the following options:
- include tags
- exclude tags
- minimum word count
- include apps
- exclude apps
- exclude posts with declined payment
- limit votes for an author per day/week
- option to leave a comment after voting
- minimum vote power (vote is paused when below)
- vp based vote (defined author is voted when vote power is above a threshold)
- vote weight can be scaled by current vote power
Stay tuned, this needs some time to develop. I created a new github repo for it: https://github.com/holgern/steemrewarding.
beem
I’m still working regulary on beem. The newest update can be found here:
steem basic income
I developed the automation for the @steembasicincome project. The newest update about the developement can be found here:
steem monsters
I added a tournament list which is automatically updated from all challonges.com users (If your tournament is missing, please let me now.) You can find the list here: https://beempy.com/sm_tournaments
I added a ELO ranking of all tournament player here: https://beempy.com/static/sm_ranking.html
beempy.com
I added a visualization which shows curation performance and votes for the first 30 minutes. Enter a steem url in the form at https://beempy.com or replace steemit by beempy to view the curation of the post.
steemhistory
I created a small tool for receiving account operation from a steem account. At the moment all written post can be extracted and stored as text file. I’m planing to enhance the tool by receiving also transfers, rewards and delegations, so that it will be useful for a tax declaration. The newest update can be found here:
https://steemit.com/utopian-io/@holger80/steemhistory-a-command-line-tool-for-storing-all-posts-and-images-from-an-account
Statement regarding #stopthepowerdown
Finally, I want to write something about the newest events altough I’m not a consensus (top 20) witness.
I will not run a hard fork on my witness server that removes funds from a steem account.
Besides all the problems, Steemit Inc. had paid and pays for blockchain developers which continuously improving our chain. I prefer that Steemit Inc. keep their funds vested so that projects as utopian-io will further be supported by delegations.
If you like what I’m doing, please consider @holger80 as one of your witnesses. You can use steemconnect.com for approving your vote or go to https://steemit.com/~witnesses and click on my name.
This page is synchronized from the post: ‘Witness update: new project steemrewarding.com’


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Created by Froilan Miranda
Almost every mobile operating system (also called Platform when working with Cordova) has an API to develop apps.
This API consists of a component named Web View.
You can use the same knowledge of web development to build native-hybrid mobile apps
This setup of showing a web page inside the mobile app container that consists of your application business logic is called as a Hybrid App.
Cordova is the piece of software that stitches the web application and the native application together
"Apache Cordova is a platform for building native mobile applications using HTML, CSS and JavaScript."
Apache Cordova also provides a set of APIs written in JavaScript to interact with the native features of the device
Cordova has a bunch of APIs that interface with the web view using JavaScript and then talk to the device in its native language (for example, Java for Android), thus providing a bridge between them
To know more from the JavaScript about the device in which your app is running, write the following code inside the JS file:
var platform = device.platform;
To access the UUID, model, OS version, and the Cordova version of the device from inside the web view using JavaScript
var uuid = device.uuid;
var model = device.model;
var version = device.version;
var Cordova = device.Cordova;
Cordova does not convert the HTML, CSS, and JS code to an OS-specific binary code. All it does is wrap the HTML, CSS, and JS code and execute it inside a web view.
Ionic is an open source, front-end SDK for developing hybrid mobile apps with HTML5
With the power of AngularJS inside a framework like Ionic, the possibilities are unlimited (you can use any AngularJS component inside Ionic as long as it makes sense in a mobile app)
Ionic uses Node.js for its CLI as well as for the build tasks
node -v
npm -v
The package manager named Bower,uses Git to download the required libraries
git --version
Bower is used to manage our application library dependencies
bower -v
A build system that is developed on top of Node.js, automating a lot of monotonous, tedious tasks
to minify the CSS, JS, and HTML, optimize the images for the Web, and push the code to your production environment
gulp -v
Ionic CLI is a wrapper around the Cordova CLI
cordova –v
ionic –v
ionic
Cordova takes HTML, CSS, and JS code as input and generates a platform-specific installer, you need to have the build environments available on your machine
Ionic has three main/go-to templates using which we can quickly start developing apps:
ionic start -a "Example 1" -i app.example.one example1 blank
-a "Example 1"
: This is the human-readable name of the app–i app.example.one
: This is the app ID/reverse domain nameexample1
: This is the name of the folderblank
: This is the name of the templatecd command into the new folder and run the following:
ionic serve
This will start a new dev server on port 8100, and then launch the app in your default browser. If the port is occupied you can specify the port number
ionic serve -p 8200
Open the developer tools by pressing Cmd + Opt + I
Open developer tools by pressing Cmd + Opt + I
bower.json: This consists of the dependencies loaded via Bower. In future, we will install other Bower packages to be used along with our app. All the information regarding the same will be available here.
config.xml: This file consists of all the meta information needed by Cordova while converting your Ionic app to a platform-specific installer. If you open config.xml, you will see a bunch of XML tags that describes your project. We will take a look at this file in detail again.
gulpfile.js: This file consists of the build tasks that we would be using while developing the Ionic app.
ionic.project: This file consists of the information regarding the Ionic app.
hooks: This folder consists of scripts that get executed when a particular Cordova task is performed.
plugins: This folder consists of all the plugins added to the project. We will be adding a few more plugins later on, and you can see them reflected here.
scss: This folder consists of the base scss file which we will be overwriting to customize the styles of the Ionic components.
www: This folder consists of the Ionic code. Anything you write inside this folder is intended to land inside the web view. This is where we will be spending most of our time.
This file consists of all the information needed by Cordova to convert the code in the www folder to the platform-specific installer.
There are two types of configurations that you can add to this file. One is global, that is, common to all devices, and the other is specific to the platform.
This folder consists of our Ionic app, the HTML, CSS, and JS codes
There are two types of configurations that you can add to this file. One is global, that is, common to all devices, and the other is specific to the platform.
This folder consists of our Ionic app, the HTML, CSS, and JS codes
ionic start -a "Example 2" -i app.example.two example2 tabs
Enter the newly created folder and execute:
ionic serve
A new folder named templates is created. This folder will consist of partial pages associated with each AngularJS route
The js folder also has new files:
ionic start -a "Example 3" -i app.example.three example3 sidemenu
Enter the newly created folder and execute:
ionic serve
run Ionic start -l to view the list of available templates
If you want to, instead of typing the name of the template, like, say, sideMenu, you can give it the URL to the GitHub page
The Ionic start command works by passing it along just a GitHub address instead of a named template.
And the named template are actually GitHub shortcuts.
ionic start someProject sidemenu
Is the same as:
ionic start someProject https://github.com/driftyco/ionic-starter-sidemenu


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repositories all public private sources forks bulma marksheet minireset.css jgthms.github.io daniellowtw/infboard mojs remember me reset all filters
repositories all public private sources forks bulma marksheet minireset.css jgthms.github.io daniellowtw/infboard mojs remember me reset all filters