{% load staticfiles %} {% include "includes/head.html" %}
{% include "includes/nav.html" %}moreish data for your next web project
This is a small educational project intended to demonstrate the process of developing an API.
It's written in Python, and utilizes both Django and the Django Rest Framework.
It allows you to fetch Peep Show data to use in your development projects, like so:
I guess it was just one of those freaky urban things, like those people that go on fire for no reason.
Jez, can you tell me as a mate, yeah? Someone who knows me really well. Is the bottom half of me on fire?
Yeah, that would have been more hilarious had I not been literally weeping with fear.
To the absolute best of my knowledge.
I do not claim any ownership over this content, nor is this application monetized in any way.
The images are linked from (and hosted on) the Fandom Wikia and are herein attributed as such.
The header photo is credited to hahnchen and is under the CC BY-SA 3.0 license.
Let's say you wanted to retrieve all Peep Show characters and their data.
Sending a GET request to
https://peep-show-api.herokuapp.com/api/characters/
will return a JSON response that looks like this.
Yes! Check out the project on GitHub.


Home
Classes
What We Do
Service Dogs
Therapy Dogs
Pen Pals
Puppy Raisers
Who We Are
About Us
Staff & Supporters
Contact Us
Ways to Help
Donate
Volunteer
Donate
Donate
Spare some change?
Donation Payment Form
Billing Information
Full Name
Email
Address
City
State
Zip
Credit Card Info
Accepted Cards
Cardholder Name
Card Number
Exp Month
Exp Year
CVV
Shipping address same as billing


Representative histological appearance of chondrogenic culture. MSC (3A and 3B) and AC-alginate constructs (3C and 3D) were stained with type-II collagen (3A and 3C) and safranin O (3B and 3D) at day-21. ECM of both MSC-alginate and AC-pellet constructs were present with type-II collagen (3A and 3C; magnification 400X) and proteoglycan (3B and 3D; magnification 400X).


We design clean and responsive websites. We will create the perfect Web presence for your company.
We offer a variety of logo designs depending on your needs.
We also provide web hosting for your website. In short we will take care of your website
Don't have content? Don't worry we will write it for you.
We are always looking for new clients and would really appreciate your help. For every referral that completes the purchase, you will receive a referral bonus depending on total amount spend by him/her. (15% of total amount your referral spends). After 3 successful referrals your commission goes up to 20%


Select the default Disk allocation strategy to be used when allocating disks within this Disk Pool.
The allocation strategy may also be provided in the Pipeline code, thus will override the one defined in the global config.
Note: Some Disk allocation strategies may require additional information to be provided. For example, if you choose the fastest read/write speed strategy, then you must provide, for each disk, its read/write speeds. These values should be set in the Disk Information section, for each Disk entry from the Jenkins global config.


The <nui-combobox-v2>
component allows users to select item(s) from a list.
Combobox works best when the options list is big enough and you need to filter it using typeahead. In case your list contains few items or you need to use custom input, consider using Select Component
NuiSelectV2Module
To use <nui-combobox-v2>
, wrap each of the options within a <select-v2-option>
instance.
<select-v2-option>
has the value
input so that it's unique for each
option.
You can use a string
or an object
as a
value
.
In some cases, e.g. if using Grouped items, it's recommended
to use object
and provide some id's, because you can have the same option title
in the different groups and it's necessary to distinguish them somehow.
Also, using string
may cause i18n
issues as far as the same value is used for model and displaying on the view.
Wrap all of the options inside a <nui-combobox-v2>
instance as a content
projection for the dropdown.
You can put pretty much anything inside a
<nui-combobox-v2>
dropdown. For example, if you need the dropdown to display some
info text, you can project standard HTML into the dropdown and it will be shown as standard HTML
rather than a select option.
Highlighting of the searching string is the default functionality, read more about it in the Typeahead section.
You can use the following ways to get a value from a combobox component:
value
property on the componentvalueSelected
output - emits the selected valuevalueChanged
output - emits after input was changed
To set a value for a combobox, you can use either the value
input or
the reactive form control
setValue
method, to provide an option from the list.
<nui-combobox-v2>
comes with built-in typeahead functionality so you can filter options
in the list.
To enable highlighting of the search string within the combobox options, you can use the default
highlighting functionality provided by the nuiComboboxV2OptionHighlight
directive:
<span [nuiComboboxV2OptionHighlight]="item"><span>
For more detail on how to get this working, take a look at the code inside the source expander of the Basic Usage example above.
HighlightPipe
instead of nuiComboboxV2OptionHighlight
.
It's possible to use a custom template for the option
s in the list. You can use pretty
much any layout for the options by putting the template inside a
<select-v2-option>
instance.
If you want to group options you can wrap them in a <nui-select-v2-option-group>
instance. You can also provide a header for a group (optionally).
To use default styles for a header (as in the example below), apply
.nui-select-v2-option-group--header
class to the header.
To use nui-combobox-v2
with reactive forms, create a FormControl
that
represents the form model. Then, bind nui-combobox-v2
to this form element.
<nui-form-field>
component as a wrapper if you are going to use validation, captions, labels, etc.
Combobox has a multiselect mode. To turn it on, set the multiselect
input to
true
. This allows the template you pass to the inputTemplate
input to
render the selected items in a special container within the main input.
nui-chips
. In fact, you
can technically pass any template to inputTemplate
.
You can create new options and add them to the list. To do that, just add the option to the initial
list e.g. options.push(option);
. To immediately set an added option as the selected
value you can use either FormControl.setValue(option);
or the value
input
on the component.
If you want to add options using the Create Option button as in the example below, you should add the button as a content projection along with the options themselves.
.nui-combobox-v2__create-option
class for the
Create Option block to have the same styles as the example.
nui-combobox-v2
comes with the following outputs which are useful when implementing the
create-option functionality:
canCreateOption
- emits true
when there's no such option alreadysearchEmpty
- emits true
when there's no option that fits search term
in the textbox.
isTypeaheadEnabled
property is
true
(default behavior).
The options dropdown can use virtual scroll. For that, wrap the options list in a
cdk-virtual-scroll-viewport
.
You can adjust virtual scroll container to your needs according to
Virtual Scroll API.
Warning: All the items inside a dropdown must be of the same height!
You should setitemSize
property of cdk-virtual-scroll-viewport
to the exact value of an option height. Otherwise, some features may not work.
It is possible to disable either the entire combobox-v2
or one or more
select-v2-option
s. To do that, set the isDisabled
input to true on the
appropriate component.
The isInErrorState
input is used to set/change the visual validation state of the
component. This can be used in custom situations in which you need to manually indicate that the
component is in error state.
nui-form-field
component. For information about that, see the Using With Reactive Forms section.
To style the combobox's dropdown simply use overlayConfig
input and fill in its panelClass
property with the global CSS class with
the desired styles.
To put a combobox in inline display mode, add necessary styles to the component. For example, you can add bootstrap d-inline-flex
style.
Combobox has a "remove value" button by default. If you don't want to use it, set the
isRemoveValueEnabled
input to false
.
To adjust ComboboxComponent
's popup overlay properties, such as width
,
height
or other properties, set the overlayConfig
input in accordance with
the Angular CDK Overlay Config
interface.
NOTE: in case you need to set the width
using the overlay config make sure you disable the
automatic width synchronization, which is enabled by default. This can be done by setting the syncWidth
input to false
with-popup-styles
(you can import it POPUP_STYLES_CLASS
from @nova-ui/bits
) class which styles the popup according to the
Nova Design Language. Setting custom styles through the global classes using the `panelClass` will override the default styles of the overlay.
If you want to preserve default overlay styles please consider adding the with-popup-styles
class when setting styles using the overlayConfig
.
Please see the example below.
Combobox comes with default typeahead functionality. Nevertheless, it's possible to use custom
typeahead logic. To do so, disable the default typeahead by setting the
isTypeaheadEnabled
input to false
. Custom typeahead involves filtering the
options list and updating it manually.
Similar to select-v2
, the manualDropdownControl
boolean input gives you
total control over opening and closing the dropdown. When set to true
, the default behavior of the
dropdown is blocked, and you can provide your own behavior.
clickOutsideDropdown
output can be used to close the dropdown
manually on clicks outside both the host element and the dropdown.
inputElement
in case you are triggering the dropdown outside the host element.
For that, you can do combobox.inputElement.nativeElement.focus()
<nui-combobox-v2>
comes with built-in accessibility features:
TAB/Shift+TAB
for focusing the component.ARROW UP/ARROW DOWN
for navigation inside an option list.PAGE UP/PAGE DOWN
for navigation inside the list to top/bottom.ENTER
to select an option.Multiselect only:
BACKSPACE
to remove a selected item.LEFT
to navigate the selected items.RIGHT
to navigate the selected items.


Your number one follower is currently Stranger with 123,456 points. They follow 4 of your 6 playlists You follow 0 of their 0 playlists. Profile
Lorem ipsum dolor sit amet, consectetur adipisicing elit. Iste saepe et quisquam nesciunt maxime.


Face Detection/Emotion Detection Demo
Quick Info
Extract face bounding boxes and emotions from video content. Use face events to find humans in long content, or use the emotion events for sentiment analysis.
Output file is a descriptive JSON file that shows where and when faces are detected, and optionally their emotion.
The demo highlights the face detected with a color based on their emotion.
Legend
neutral,
happiness,
surprise,
sadness,
anger,
disgust,
fear,
contempt


{% extends 'base.html' %} {% block content %}
When you find an idea that you just can't stop thinking about, that's probably a good one to pursue - Pitching..


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A few years ago I took a look at the licenses of records in the Digital Public Libary of America. I thought it might be interesting how things have changed since then, as well as seeing how various hubs contribute to the total.
Overall, the breakdown of licenses seems to be roughly similar to what it was a few years ago. However, the breakdown of individual hubs show more variance. The three state level hubs shown below the main graphic have a much greater percentage of their records in copyright as opposed to the DPLA as a whole. The DPLA in general, has a solid percentage of records without copyright restrictions, for example the National Archives and Record Administration offers nearly two million records without restrictions.
The treemap graphics below show licenses with at least 1000 records in the DPLA corpus, and 250 records or more for the state level hubs, divided into four clusters: those in copyright, those with no copyright restrictions, Creative Commons records and those where copyright is unknown.
Overall, I leaned towards considering records in copyright, unless they were explicitly listed with another license. Some records were removed if the rights statement from the record didn't seem to make sense, but in general, I think the graphics give a solid flavor of what's in the DPLA corpus.
Note: Best viewed on a larger screen On very small screens it's possible that some of the clusters, particularly Creative Commons clusters, will be so small that they won't be visible. Hover over a record to see the full text of a particular license.


MUSIC
With a wide-ranging repertoire and a powerhouse sound, Restated has earned awards on regional and national levels. We use only our voices to make our music—we use no drum tracks or other instruments. Lots of people have enjoyed listening to us, from the guys at the Mouth Off podcast to Perez Hilton. But don't take their word for it—hear for yourself!
SINGLES
Update Required
To play the media you will need to either update your browser to a recent version or update your Flash plugin.
HOLIDAY
(2014) A Cappella Records
Update Required
To play the media you will need to either update your browser to a recent version or update your Flash plugin.
THE HEART OF THE MATTER
(2012) A Cappella Records
Update Required
To play the media you will need to either update your browser to a recent version or update your Flash plugin.
PRICE TAG
(2011) A Cappella Records
Update Required
To play the media you will need to either update your browser to a recent version or update your Flash plugin.
ROLLING IN THE DEEP
(2011) A Cappella Records


|
KlusterKite
0.0.0
A framework to create scalable and redundant services based on awesome Akka.Net project.
|
Manager that handles sending parcels More...
Public Member Functions | |
| ParcelManagerActor (IComponentContext container) | |
| Initializes a new instance of the ParcelManagerActor class. More... | |
Protected Member Functions | |
| override void | PostStop () |
| User overridable callback. More... | |
| override void | PreRestart (Exception reason, object message) |
User overridable callback: '''By default it disposes of all children and then calls postStop() .''' More... | |
| override void | PreStart () |
| User overridable callback. More... | |
Manager that handles sending parcels
Should be singleton in local system. In case of system failure all parcells will be lost. Try to avoid using this, as this is really slow and large messages typically means some errors in software design.
Definition at line 43 of file ParcelManagerActor.cs.
| KlusterKite.LargeObjects.ParcelManagerActor.ParcelManagerActor | ( | IComponentContext | container | ) |
Initializes a new instance of the ParcelManagerActor class.
| container | The DI container. |
Definition at line 91 of file ParcelManagerActor.cs.
|
protected |
User overridable callback.
Is called asynchronously after 'actor.stop()' is invoked. Empty default implementation.
Definition at line 110 of file ParcelManagerActor.cs.
|
protected |
User overridable callback: '''By default it disposes of all children and then calls postStop()
.'''
Is called on a crashed Actor right BEFORE it is restarted to allow clean up of resources before Actor is terminated.
| reason | the Exception that caused the restart to happen. |
| message | optionally the current message the actor processed when failing, if applicable. |
Definition at line 126 of file ParcelManagerActor.cs.
|
protected |
User overridable callback.
Is called when an Actor is started. Actors are automatically started asynchronously when created. Empty default implementation.
Definition at line 141 of file ParcelManagerActor.cs.


GitHub
Currency Pairs
Simple application for displaying two currencies and their relative rate.
Start date
Base currency
EUR
Quote currency
USD
End date


Edit
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#


Voxc.js is meant to be a lightweight, easy to use library for converting voxel objects into JavaScript matrixes for easy manipulation. These matrixes can then be used for creating more meshes that have different goals. This library will contain a series of converters that all have a different purpose. The creation and formatting of these converters stay consistent by using JavaScriptmatrixes as input and output.
The first converter in the demo takes a .obj voxel file that *is uploaded by the user* (still in development) and firstly converts this file to JavaScript matrixes containing the vertices, edges, faces and normals.The first converter then uses these to create and output an array of hex valued colors to be used in follow up converters. The 2nd converter then evaluates the array against a JSON rules file *either uploaded by the user or typed by the user in the text editor on the demo* (still in development). The evaluation will consider the color of the voxel cubes stored in the array and texture them accordingly, the converter will evaluate single colors as well as colors that appear next to each other.
voxc.js is used by downloading the minified javascript file and including it in your project.
voxc.min.js contains a class called VoxJSCanvas, and by constructing the class with the id of any div such as, new VoxJSCanvas("VoxelDemo"), the class will create a THREE.js canvas/scene with the required basics to display all our meshes.
var converterOne_canvas = new voxJSCanvas("voxelDemo");
var converterOne_model;
var arrayToMesh = new ArrayToMesh(converterOne_canvas.scene, model);
converterOne_model = arrayToMesh.output();
converterOne_canvas.CameraPosition(0, 0, -10);
converterOne_canvas.setMesh(converterOne_model);
converterOne_canvas.start();


TRAINING
These problem sets were used with grades 7, 8 and 9, and with other groups.
Do as many of these problems as you can. If you can’t do something, skip it and try it again later. Above all, don’t panic. Some questions seem hard to understand but dealing with that is part of the training. Every time you complete a problem, you become better. Problems that seem hard today will seem easy after training.
M3 2018/2 Computer Programming
M3 2018/1 Computer Programming
M2 2018/2 Permutations and Groups
M1 2018/2 Arithmetic and Combinatorics II
M1 2018/1 Arithmetic and Combinatorics I
M2 2017/2 Functions, inverses, logarithms
M2 2017/1 Competition training
M1 2017/2 Linear equations, determinants
M1 2017/1 Equations and inequalities
M2 2016/2 Applied and competition problems.
M1 2016/2 Plotting, operations, transformations
4D hypercube (tesseract) worksheets. Use the one with two hypercubes per sheet for numbering vertices and counting edges. Use the one with 8 hypercubes per sheet for coloring 3D subcubes, and the one with 24 per sheet for coloring 2D faces.


Usage¶
usage: xnat_downloader [-h] [-c CONFIG] [-i INPUT_JSON]
xnat_downloader downloads xnat dicoms and saves them in BIDs compatible
directory format
optional arguments:
-h, --help show this help message and exit
-c CONFIG, --config CONFIG login file (contains user/pass info)
Required arguments:
-i INPUT_JSON, --input_json INPUT_JSON json file defining inputs for this script.
json format¶
The json file has multiple fields specifying where and how the data are downloaded from xnat.
- destination: string
(required) The absolute path to the output base directory of the BIDS dataset
- project: string
(required) The name of the project on xnat
- server: string
(required) The base URL to the xnat server (e.g. “https://central.xnat.org”)
- subjects: list
(optional) The subjects you wish to download from xnat. Use the subject names as they are seen on xnat.
- sub_dict: dictionary
(optional) (non-BIDS) If you want to change the subject label that is not represented in the xnat subject name
- session_labels: list
(optional) (non-BIDS) If you want to replace the names of the sessions on xnat with your own list of scans.
Warning
this will not behave as expected if the subject on xnat has a missing “middle” session or an extra session.
- scan_labels: list
(optional) a list of the scans you want to download (if you don’t want to download all the scans).
- num_digits: int
(optional) an integer indicating how many digits the subject number should have. For example if the subject number on xnat is 10, then setting num_digits to 2 will not change the subject 10, but if num_digits was set to 3 then subject 10 will be written as 010.
- scan_dict: dictionary
(conditionally required) (non-BIDS) required if your dicoms are not stored in a BIDS format on xnat. The keys to the dictionary are scan names as they are seen on xnat (e.g. “SAG FSPGR BRAVO”), and the values are the associated reproin (BIDS-ish) name for the scan (e.g. “anat-T1w”).
example json¶
{
"destination": "/out",
"project": "xnatDownload",
"server": "https://central.xnat.org",
"subjects": ["21"],
"sub_dict": {"21": "SEH021"},
"session_labels": ["pre", "post", "checkup"],
"scan_dict": {
"SAG FSPGR BRAVO": "anat-T1w",
"Field Map": "fmap",
"T1rho - SL50": "anat-T1rho_acq-SL50",
"T1rho - SL10 (NO AUTO PRESCAN)": "anat-T1rho_acq-SL10",
"fMRI Resting State": "func-bold_task-rest",
"fMRI SIMON": "func-bold_task-simon",
"DTI": "dwi",
"3D ASL": "func-asl",
"PROBE-SV 35": "mrs-fid",
"PU:SAG FSPGR BRAVO": "anat-T1w_rec-pu",
"PU:fMRI Resting State": "func-bold_task-rest_rec-pu",
"PU:fMRI SIMON": "func-bold_task-simon_rec-pu",
"Cerebral Blood Flow": "func-asl_rec-cbf",
"NOT DIAGNOSTIC: PFile-PROBE-SV 35": "mrs-fid_rec-pfile"
}
}
Once installed and the json file is configured, the final step is to call the command.
locally installed: (python2 only)
xnat_downloader -i /path/to/json/file.json
via docker:
docker run \
-v /path/to/out:/out \
-v /path/to/json/:/json \
jdkent:xnat_downloader \
-i /json/file.json
Note: when calling via docker, the destination location should be specified relative to where the path is in the docker container, not on your machine.


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| HOME | DOWNLOAD | DOCUMENTATION | FAQ |
> Home > Documentation > Python > Global and Localized Spectral Analysis
SHBiasAdmitCorr
Calculate the expected multitaper admittance and correlation spectra associated with the input global cross-power spectra of two functions.
Usage
admit
, corr
= SHAdmitCorr (sgt
, sgg
, stt
, tapers
, [lmax
, lwin
, k
, mtdef
, taper_wt
])
Returns
admit
: float, dimension (lmax
-lwin
+1)- The biased admittance spectrum obtained using the localized (cross-)power spectra of Sgt and Stt.
corr
: float, dimension (lmax
-lwin
+1)- The biased correlation spectrum obtained using the localized (cross-)power spectra of Sgt, Stt, and Sgg.
Parameters
sgt
: float, dimension (lmaxin1
+1)- The global cross-power spectrum of the functions
G
andT
. sgg
: float, dimension (lmaxin2
+1)- The global power spectrum of the function
G
. stt
: float, dimension (lmaxin3
+1)- The global power spectrum of the function
T
. tapers
: float, dimension (lwinin
+1,kin
)- The spherical harmonic coefficients of the spherical cap localizing windows. Each column corresponds to the non-zero coefficients of a single angular order. Since all that is important is the power spectrum of each window, the exact angular order is not important. These are generated by a call to
SHReturnTapers
orSHReturnTapersM
. lmax
: optional, integer, default = min(lmaxin1
,lmaxin2
,lmaxin3
)- The maximum spherical harmonic degree to use of the input spectra
sgt
,sgg
,stt
. lwin
: optional, integer, default =lwinin
- The spherical harmonic bandwidth of the localizing windows.
k
: optional, integer, default =kin
- The number of localizing windows to use. Only the first
k
columns oftapers
will be employed, which corresponds to thek
best-concentrated localizing windows. mtdef
: optional, integer, default = 1- 1 (default): Calculate the multitaper spectral estimates Sgt, Sgg and Stt first, and then use these to calculate the admittance and correlation functions. 2: Calculate admittance and correlation spectra using each individual taper, and then average these to obtain the multitaper admittance and correlation functions.
taper_wt
: optional, float, dimension (k
), default = -1- The weights to apply to each individual windowed spectral estimate. The weights must sum to unity and are obtained from
SHMTVarOpt
. The default specifies that taper weights are not used.
Description
Given the global cross-power spectra Sgt
, Sgg
and Stt
of two functions G
and T
, SHBiasAdmitCorr
will calculate the expected multitaper admittance and correlation spectra associated with the two global functions. This routine expects as input a matrix containing the spherical harmonic coefficients of the localizing windows, which can be generated by a call to SHReturnTapers
or SHReturnTapersM
. Only the k
best-concentrated localization windows will be employed when calculating the biased cross-power spectra. The maximum calculated degree of the output biased admittance and correlation spectra corresponds to lmax-lwin
, as it is assumed that the input cross-power spectra beyond lmax
are unknown, and not zero.
Two manners of calculating the localized admittance and correlation spectra are possible according to the value of the optional parameter mtdef
. In case 1, the multitaper cross-power spectra of Sgt, Sgg, and Stt are first calculated, and from these, the admittance and correlation spectra are formed. In case 2, the biased admittance and correlation spectra are calculated for each individual taper, and these are then averaged to obtain the biased multitaper admittance and correlation spectra.
The default is to apply equal weights to each individual windowed estimate of the spectrum, but this can be modified when mtdef
is 1 by specifying the weights in the optional argument taper_wt
. The weights must sum to unity and can be calculated by SHMTVarOpt
.
References
Wieczorek, M. A. and F. J. Simons, Minimum-variance multitaper spectral estimation on the sphere, J. Fourier Anal. Appl., 13, doi:10.1007/s00041-006-6904-1, 665-692, 2007.
Simons, F. J., F. A. Dahlen and M. A. Wieczorek, Spatiospectral concentration on the sphere, SIAM Review, 48, 504-536, doi:10.1137/S0036144504445765, 2006.
Wieczorek, M. A. and F. J. Simons, Localized spectral analysis on the sphere, Geophys. J. Int., 162, 655-675.
See also
shbias, shbiask, shreturntapers, shreturntapersm, shmtvaropt
> Home > Documentation > Python > Global and Localized Spectral Analysis
| Laboratoire Lagrange | Observatoire de la Côte d'Azur | © 2017 SHTOOLS |


Man charged with murder after father found slain
by EndPlayEAST WINDSOR, Conn. (AP) - A 40-year-old Connecticut man has been charged in the death of his father.
The Hartford Courant reports that Gabriel Hesse, of East Windsor, was arrested at his Main Street home Friday evening and charged with murder. He is being held on $2 million bond. It was not immediately clear if he has obtained an attorney.
Hesse is accused of killing his 73-year-old father, Halsey Hesse, who was found dead Oct. 9 in the kitchen of his East Windsor home. A family member discovered his body after failing to reach him by phone for several days.
Police said he had been stabbed multiple times. His death was ruled a homicide.
Gabriel Hesse is scheduled to be arraigned Monday in Enfield Superior Court.
___
Information from: Hartford Courant, http://www.courant.com


| Home | Trees | Indices | Help |
|
|---|
|
|
object --+ | ADObject --+ | User --+ | Computer
An Active Directory computer object.
This class exposes computer-specific properties at the top level to make it easier to work with computer objects. Note that it also inherits from the User class.
|
|||
|
|||
|
|||
|
Inherited from Inherited from Inherited from |
|
|||
| service_principal_name | |||
| dns_hostname | |||
| os | |||
| os_service_pack | |||
| os_version | |||
|
Inherited from Inherited from Inherited from |
|
Initialize the AD object. Args: distinguished_name: the full distinguished name of the object properties: if a list, a list of properties to retrieve. if a hash, it is a pre-populated list of properties. If a hash is provided and mandatory properties are missing, then they will be retrieved by an ldap query domain_obj: the Domain object that the AD object is associated with
|
repr(x)
|
|
service_principal_name
|
dns_hostname
|
os
|
os_service_pack
|
os_version
|
| Home | Trees | Indices | Help |
|
|---|
| Generated by Epydoc 3.0.1 on Tue Feb 01 17:00:01 2011 | http://epydoc.sourceforge.net |


Test::Int::TestSpace Class Reference
Inherits
Gecode::Space.
List of all members.
Detailed Description
Space for executing tests.
Definition at line 87 of file int.cc.
Constructor & Destructor Documentation
| Test::Int::TestSpace::TestSpace |
( |
int |
n, |
|
|
Gecode::IntSet & |
d0, |
|
|
bool |
r, |
|
|
Test * |
t, |
|
|
bool |
log = true | |
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) |
| | [inline] |
Create test space.
Creates n variables with domain d0 and stores whether the test is for a reified propagator (r), and the test itself (t).
Definition at line 109 of file int.cc.
| Test::Int::TestSpace::TestSpace |
( |
bool |
share, |
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|
TestSpace & |
s | |
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) |
| | [inline] |
Constructor for cloning s.
Definition at line 119 of file int.cc.
Member Function Documentation
| virtual Gecode::Space* Test::Int::TestSpace::copy |
( |
bool |
share |
) |
[inline, virtual] |
| TestSpace* Test::Int::TestSpace::cloneWithReflection |
( |
void |
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) |
[inline] |
Make a copy of the TestSpace using the reflection API.
Definition at line 130 of file int.cc.
| bool Test::Int::TestSpace::assigned |
( |
void |
|
) |
const [inline] |
Test whether all variables are assigned.
Definition at line 180 of file int.cc.
| void Test::Int::TestSpace::post |
( |
void |
|
) |
[inline] |
Post propagator.
Definition at line 188 of file int.cc.
| bool Test::Int::TestSpace::failed |
( |
void |
|
) |
[inline] |
Compute a fixpoint and check for failure.
Definition at line 200 of file int.cc.
Perform integer tell operation on x[i].
Definition at line 211 of file int.cc.
| void Test::Int::TestSpace::rel |
( |
bool |
sol |
) |
[inline] |
Perform Boolean tell on b.
Definition at line 227 of file int.cc.
| void Test::Int::TestSpace::assign |
( |
const Assignment & |
a, |
|
|
bool |
skip = false | |
|
) |
| | [inline] |
Assign all (or all but one, if skip is true) variables to values in a.
Definition at line 235 of file int.cc.
| void Test::Int::TestSpace::prune |
( |
void |
|
) |
[inline] |
Prune some random values for some random variable.
Definition at line 246 of file int.cc.
| bool Test::Int::TestSpace::prune |
( |
const Assignment & |
a |
) |
[inline] |
Prune values but not those in assignment a.
Definition at line 268 of file int.cc.
Member Data Documentation
Initial domain.
Definition at line 90 of file int.cc.
Variables to be tested.
Definition at line 92 of file int.cc.
Control variable for reified propagators.
Definition at line 94 of file int.cc.
Whether the test is for a reified propagator.
Definition at line 96 of file int.cc.
The test currently run.
Definition at line 98 of file int.cc.
The documentation for this class was generated from the following file:


MapPolyline QML Type
The MapPolyline type displays a polyline on a map. More...
| Import Statement: | import QtLocation 5.3 |
| Since: | Qt Location 5.0 |
Properties
- line
- line.width : int
- line.color : color
- path : list<coordinate>
Methods
- void addCoordinate(coordinate)
- coordinate containsCoordinate(coordinate)
- coordinate coordinateAt(index)
- void insertCoordinate(index, coordinate)
- int pathLength()
- void removeCoordinate(index)
- void removeCoordinate(coordinate)
- void replaceCoordinate(index, coordinate)
Detailed Description
The MapPolyline type displays a polyline on a map, specified in terms of an ordered list of coordinates. The coordinates on the path cannot be directly changed after being added to the Polyline. Instead, copy the path into a var, modify the copy and reassign the copy back to the path.
var path = mapPolyline.path; path[0].latitude = 5; mapPolyline.path = path;
Coordinates can also be added and removed at any time using the addCoordinate and removeCoordinate methods.
By default, the polyline is displayed as a 1-pixel thick black line. This can be changed using the line.width and line.color properties.
Performance
MapPolylines have a rendering cost that is O(n) with respect to the number of vertices. This means that the per frame cost of having a polyline on the Map grows in direct proportion to the number of points in the polyline.
Like the other map objects, MapPolyline is normally drawn without a smooth appearance. Setting the opacity property will force the object to be blended, which decreases performance considerably depending on the hardware in use.
Note: MapPolylines are implemented using the OpenGL GL_LINES primitive. There have been occasional reports of issues and rendering inconsistencies on some (particularly quite old) platforms. No workaround is yet available for these issues.
Example Usage
The following snippet shows a MapPolyline with 4 points, making a shape like the top part of a "question mark" (?), near Brisbane, Australia. The line drawn is 3 pixels in width and green in color.
Map { MapPolyline { line.width: 3 line.color: 'green' path: [ { latitude: -27, longitude: 153.0 }, { latitude: -27, longitude: 154.1 }, { latitude: -28, longitude: 153.5 }, { latitude: -29, longitude: 153.5 } ] } }
Property Documentation
This property is part of the line property group. The line property group holds the width and color used to draw the line.
The width is in pixels and is independent of the zoom level of the map. The default values correspond to a black border with a width of 1 pixel.
For no line, use a width of 0 or a transparent color.
path : list<coordinate> |
This property holds the ordered list of coordinates which define the polyline.
Method Documentation
Adds a coordinate to the end of the path.
See also insertCoordinate, removeCoordinate, and path.
coordinate containsCoordinate(coordinate) |
Returns true if the given coordinate is part of the path.
This QML method was introduced in Qt Location 5.6.
coordinate coordinateAt(index) |
Gets the coordinate of the polyline at the given index. If the index is outside the path's bounds then an invalid coordinate is returned.
This QML method was introduced in Qt Location 5.6.
Inserts a coordinate to the path at the given index.
This QML method was introduced in Qt Location 5.6.
See also addCoordinate, removeCoordinate, and path.
Returns the number of coordinates of the polyline.
This QML method was introduced in Qt Location 5.6.
See also path.
Removes a coordinate from the path at the given index.
If index is invalid then this method does nothing.
This QML method was introduced in Qt Location 5.6.
See also addCoordinate, insertCoordinate, and path.
Removes coordinate from the path. If there are multiple instances of the same coordinate, the one added last is removed.
If coordinate is not in the path this method does nothing.
See also addCoordinate, insertCoordinate, and path.
Replaces the coordinate in the current path at the given index with the new coordinate.
This QML method was introduced in Qt Location 5.6.
See also addCoordinate, insertCoordinate, removeCoordinate, and path.


Friday to feel less cold but rain will continue throughout the weekend
There will be scattered showers across the region from Friday morning but temperatures won't feel as low
by Katie CollingsAfter waking up to bitterly cold temperatures on Thursday, the good news is things won't be quite as bad today.
There will even be some sunny spells, but we're not completely in the clear.
Scattered showers will begin from early Friday morning and continue throughout the weekend.
From Monday, weather will become drier but will be chillier as temperatures drop.
Here is what the Met Office predicts:
Friday
"Rain at first on Friday, easing through the morning as brighter spells develop.
"Some sunny spells and isolated showers by the afternoon.
"Windy at times but a little less cold. Maximum temperature 9 °C."
Outlook for Saturday to Monday:
"Cloudy with outbreaks of rain Saturday.
Further rain or showers Sunday but some brighter spells later.
"Drier but cold Monday, with isolated showers but breezy on the coast."


Geoffrey Lewis stands accused of downloading indecent images of children over a 15-year period between 2002 and 2017.

Suffolk Magistrates' Court heard that all the offences are alleged to have taken place in Woodbridge.
Lewis, of Briton Way, Wymondham, in Norfolk, appeared in the dock for a brief hearing on Tuesday afternoon to deny every charge.
He spoke only to confirm his name, address and date of birth, and to enter not guilty pleas to all of the alleged offences.
Lewis is charged with four counts of sexually touching a girl under the age of 13 and one count of engaging in non-penetrative sexual activity with girl aged 13-15.
All five charges have been brought by the Crown Prosecution Service under the Sexual Offences Act 2003.
Under the Protection of Children Act 1978, between October 2002 and December 2017, Lewis is also accused of making 59 still images and 35 moving images, of the most serious (category A) level of indecency, on an Antec Tower and Samsung mobile phone; making 79 category B still images and 39 category B moving images of a child on an Antec Tower, ASUS laptop and Samsung mobile phone, and with making 3,669 category C still images and 88 category C moving images of a child on an Antec Tower and Samsung mobile phone.
Prosecutor David Bryant invited magistrates to send the case straight up to the crown court.
He told the bench: "For the majority of these matters, your sentencing powers would be wholly insufficient."
Nick Seeley, representing Lewis, made no representations in respect of venue for the case to be heard.
Magistrates agreed to decline jurisdiction and send the case to be dealt with before a judge and jury.
Lewis was released on unconditional bail until his next scheduled appearance at Ipswich Crown Court on December 17.


Watch Live: Donald Trump Speaks at KAG Rally in Louisiana
President Donald Trump will return to Louisiana on Thursday for another political rally for Eddie Rispone, the Republican candidate running for governor.
by Charlie SpieringThe president is expected to begin speaking at 8:00 p.m. EST in Bossier City.
The Louisiana election will be held on Saturday.


Prism Johnson share price plunges 6% on poor Q2 show
Currently, it is trading 23.75 percent below its 52-week high and 26.98 percent above its 52-week low.
Shares of Prism Johnson plunged more than 6 percent intraday on November 5 after the company's losses had increased in the quarter ended in September.
The company's Q2FY20 consolidated net loss was at Rs 28.8 crore against the loss of Rs 0.9 crore in the same quarter last fiscal.
The revenue of the company was up 1.2 percent at Rs 1,419 crore versus Rs 1,402 crore.
Earnings before interest, tax, depreciation and amortisation (EBITDA) shed 14.6 percent at Rs 90.7 crore while the EBITDA margin was down 120 bps at 6.4 percent year-on-year (YoY).
At 13:22 hrs, Prism Johnson was quoting at Rs 79.30, down Rs 3.90, or 4.69 percent, on the BSE.
The share touched its 52-week high Rs 104.00 and the 52-week low Rs 62.45 on March 12 and February 4 respectively.
Currently, it is trading 23.75 percent below its 52-week high and 26.98 percent above its 52-week low.Special Thursday Expiry on 10th 7th Nov
Early Closure to The Great Diwali Discount. Last Chance to get Moneycontrol PRO for a year @ Rs. 289/- only
Coupon code: DIWALI


This was a semester long project for CS428 at Rutgers University, derived from SteerSuite. An analysis and other information for various test cases are available on our project blog.


Coalition fighting Islamic State had 'difference of opinion' on repatriation of detainees
WASHINGTON (Reuters) - Members of a coalition fighting Islamic State had a “difference of opinion” at a meeting in Washington on Thursday on whether jihadi detainees should be repatriated, the U.S. Special Representative for Syria Jim Jeffrey said.
“There was some difference of opinion on whether they should be repatriated or whether that should be something that countries are still going to look at and think about in more detail, but nonetheless, that is acknowledged as a significant problem,” Jeffrey told a news conference.
U.S. Secretary of State Mike Pompeo had urged members of the coalition ahead of the meeting to take Islamic State detainees back to their countries of origin.


With the best of the season coming from “orchards, farms and gardens,” NPR has put together an impressive collection of 10 summer cookbooks.
May 23, 2012 / Read »About a month ago, I ate almost an entire box of kale chips. My brother and I were visiting our cousin in Brooklyn, and before a very thoughtfully prepared vegan…
I could not figure out what to do with the delectable slices of Pear Cake that I brought home from this wonderful Sunday supper - eat them slowly, a little bit at…


{% include 'header.html' %}
Change Order Status
Current Status:
{{ myFunc('0rd3r') }}
Choose order state
Production
Development
Testing
Deployment
Order Transactions
Transaction ID
New Owner
Timestamp
{% for arr in transactions %}
{{ arr['transactionId'] }}
{{ myOwnerFunc(arr['newOwner']) }}
{{ myChangeFunc(arr['timestamp']) }}
{% endfor %}


Happy Hour
Party Time
It has roots in a piece of classical Latin literature from 45 BC, making it over 2000 years old. Richard McClintock, a Latin professor at Hampden-Sydney College in Virginia, looked up one of the more obscure Latin words, consectetur, from a Lorem Ipsum passage, and going through the cites of the word in classical literature, discovered the undoubtable source. Lorem Ipsum comes from sections 1.10.32 and 1.10.33 of "de Finibus Bonorum et Malorum" (The Extremes of Good and Evil) by Cicero, written in 45 BC. This book is a treatise on the theory of ethics, very popular during the Renaissance. The first line of Lorem Ipsum, "Lorem ipsum dolor sit amet..", comes from a line in section 1.10.32.
 Richard McClintock, a Latin professor at Hampden-Sydney College in Virginia, looked up one of the more obscure Latin words, consectetur, from a Lorem Ipsum passage, and going through the cites of the word in classical literature, discovered the undoubtable source. Lorem Ipsum comes from sections 1.10.32 and 1.10.33 of "de Finibus Bonorum et Malorum" (The Extremes of Good and Evil) by Cicero, written in 45 BC. This book is a treatise on the theory of ethics, very popular during the Renaissance. The first line of Lorem Ipsum, "Lorem ipsum dolor sit amet..", comes from a line in section 1.10.32.
Fast Food
Drinks
Great food! Menu is awesome. THeir food is not only great but in the right price. I will highly recommend them
The food is amazing and awesome. t is a long established fact that a reader will be distracted by the readable content of a page when looking at its layout. The point of using Lorem Ipsum is that it has a more-or-less normal distribution of letters, as opposed to using 'Content here, content here', making it look like readable English.
The food is amazing and awesome. t is a long established fact that a reader will be distracted by the readable content of a page when looking at its layout. The point of using Lorem Ipsum is that it has a more-or-less normal distribution of letters, as opposed to using 'Content here, content here', making it look like readable English.
We are a menu little team of seven people. t is a long established fact that a reader will be distracted by the readable content of a page when looking at its layout. The point of using Lorem Ipsum is that it has a more-or-less normal distribution of letters, as opposed to using 'Content here, content here', making it look like readable English.


LAMPS MENU
Lamps
Bulbs
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PMAL: Open Set Recognition via Robust Prototype Mining
Abstract
Open Set Recognition (OSR) has been an emerging topic. Besides recognizing predefined classes, the system needs to reject the unknowns. Prototype learning is a potential manner to handle the problem, as its ability to improve intra-class compactness of representations is much needed in discrimination between the known and the unknowns. In this work, we propose a novel Prototype Mining And Learning (PMAL) framework. It has a prototype mining mechanism before the phase of optimizing embedding space, explicitly considering two crucial properties, namely high-quality and diversity of the prototype set. Concretely, a set of high-quality candidates are firstly extracted from training samples based on data uncertainty learning, avoiding the interference from unexpected noise. Considering the multifarious appearance of objects even in a single category, a diversity-based strategy for prototype set filtering is proposed. Accordingly, the embedding space can be better optimized to discriminate therein the predefined classes and between known and unknowns. Extensive experiments verify the two good characteristics (i.e., high-quality and diversity) embraced in prototype mining, and show the remarkable performance of the proposed framework compared to state-of-the-arts. [Paper]Highlights Contributions
❃ Different from the common usage of implicitly learnable prototypes, we pay more attention on choosing prototypes with explicit criteria for OSR tasks. We point out the two important attributes of prototypes, namely the high-quality and diversity.
❃ We design a OSR framework by prototype mining and learning. In the prototype mining phase, the above two key attributes are taken into consideration. In the embedding learning phase, with the chosen prototypes as fixed anchors for each class, a better embedding space is learned, without any sophisticated skills for convergence.
❃ Extensive experiments on multiple OSR benchmarks show that our method is powerful to discriminate the known and unknowns, surpassing the state-of-the-art performance by a large margin, especially in complicated large-scale tasks.
Recommended Citations
If you find our work is helpful to your research, please feel free to cite us:@inproceedings{jing@aaai2022, author = {Jing Lu and Yunlu Xu and Hao Li and Zhanzhan Cheng and Yi Niu and }, title = {{PMAL}: Open Set Recognition via Robust Prototype Mining}, booktitle = {AAAI}, year = {2022}, }


1 function [X, fX, i] = minimize(X, f, length, varargin) 2 % Minimize a differentiable multivariate function using conjugate gradients. 3 % 4 % Usage: [X, fX, i] = minimize(X, f, length, P1, P2, P3, ... ) 5 % 6 % X initial guess; may be of any type, including struct and cell array 7 % f the name or pointer to the function to be minimized. The function 8 % f must return two arguments, the value of the function, and it's 9 % partial derivatives wrt the elements of X. The partial derivative 10 % must have the same type as X. 11 % length length of the run; if it is positive, it gives the maximum number of 12 % line searches, if negative its absolute gives the maximum allowed 13 % number of function evaluations. Optionally, length can have a second 14 % component, which will indicate the reduction in function value to be 15 % expected in the first line-search (defaults to 1.0). 16 % P1, P2, ... parameters are passed to the function f. 17 % 18 % X the returned solution 19 % fX vector of function values indicating progress made 20 % i number of iterations (line searches or function evaluations, 21 % depending on the sign of "length") used at termination. 22 % 23 % The function returns when either its length is up, or if no further progress 24 % can be made (ie, we are at a (local) minimum, or so close that due to 25 % numerical problems, we cannot get any closer). NOTE: If the function 26 % terminates within a few iterations, it could be an indication that the 27 % function values and derivatives are not consistent (ie, there may be a bug in 28 % the implementation of your "f" function). 29 % 30 % The Polack-Ribiere flavour of conjugate gradients is used to compute search 31 % directions, and a line search using quadratic and cubic polynomial 32 % approximations and the Wolfe-Powell stopping criteria is used together with 33 % the slope ratio method for guessing initial step sizes. Additionally a bunch 34 % of checks are made to make sure that exploration is taking place and that 35 % extrapolation will not be unboundedly large. 36 % 37 % See also: checkgrad 38 % 39 % Copyright (C) 2001 - 2010 by Carl Edward Rasmussen, 2010-01-03 40 INT = 0.1; % don't reevaluate within 0.1 of the limit of the current bracket 41 EXT = 3.0; % extrapolate maximum 3 times the current step-size 42 MAX = 20; % max 20 function evaluations per line search 43 RATIO = 10; % maximum allowed slope ratio 44 SIG = 0.1; RHO = SIG/2; % SIG and RHO are the constants controlling the Wolfe- 45 % Powell conditions. SIG is the maximum allowed absolute ratio between 46 % previous and new slopes (derivatives in the search direction), thus setting 47 % SIG to low (positive) values forces higher precision in the line-searches. 48 % RHO is the minimum allowed fraction of the expected (from the slope at the 49 % initial point in the linesearch). Constants must satisfy 0 < RHO < SIG < 1. 50 % Tuning of SIG (depending on the nature of the function to be optimized) may 51 % speed up the minimization; it is probably not worth playing much with RHO. 52 % The code falls naturally into 3 parts, after the initial line search is 53 % started in the direction of steepest descent. 1) we first enter a while loop 54 % which uses point 1 (p1) and (p2) to compute an extrapolation (p3), until we 55 % have extrapolated far enough (Wolfe-Powell conditions). 2) if necessary, we 56 % enter the second loop which takes p2, p3 and p4 chooses the subinterval 57 % containing a (local) minimum, and interpolates it, unil an acceptable point 58 % is found (Wolfe-Powell conditions). Note, that points are always maintained 59 % in order p0 <= p1 <= p2 < p3 < p4. 3) compute a new search direction using 60 % conjugate gradients (Polack-Ribiere flavour), or revert to steepest if there 61 % was a problem in the previous line-search. Return the best value so far, if 62 % two consecutive line-searches fail, or whenever we run out of function 63 % evaluations or line-searches. During extrapolation, the "f" function may fail 64 % either with an error or returning Nan or Inf, and minimize should handle this 65 % gracefully. 66 if max(size(length)) == 2, red=length(2); length=length(1); else red=1; end 67 if length>0, S='Linesearch'; else S='Function evaluation'; end 68 i = 0; % zero the run length counter 69 ls_failed = 0; % no previous line search has failed 70 [f0 df0] = feval(f, X, varargin{:}); % get function value and gradient 71 Z = X; X = unwrap(X); df0 = unwrap(df0); 72 %fprintf('%s %6i; Value %4.6e\r', S, i, f0); 73 if exist('fflush','builtin') fflush(stdout); end 74 fX = f0; 75 i = i + (length<0); % count epochs?! 76 s = -df0; d0 = -s'*s; % initial search direction (steepest) and slope 77 x3 = red/(1-d0); % initial step is red/(|s|+1) 78 while i < abs(length) % while not finished 79 i = i + (length>0); % count iterations?! 80 X0 = X; F0 = f0; dF0 = df0; % make a copy of current values 81 if length>0, M = MAX; else M = min(MAX, -length-i); end 82 while 1 % keep extrapolating as long as necessary 83 x2 = 0; f2 = f0; d2 = d0; f3 = f0; df3 = df0; 84 success = 0; 85 while ~success && M > 0 86 try 87 M = M - 1; i = i + (length<0); % count epochs?! 88 89 [f3 df3] = feval(f, rewrap(Z,X+x3*s), varargin{:}); 90 df3 = unwrap(df3); 91 if isnan(f3) || isinf(f3) || any(isnan(df3)+isinf(df3)), error(''), end 92 success = 1; 93 catch % catch any error which occured in f 94 x3 = (x2+x3)/2; % bisect and try again 95 end 96 end 97 if f3 < F0, X0 = X+x3*s; F0 = f3; dF0 = df3; end % keep best values 98 d3 = df3'*s; % new slope 99 if d3 > SIG*d0 || f3 > f0+x3*RHO*d0 || M == 0 % are we done extrapolating? 100 break 101 end 102 x1 = x2; f1 = f2; d1 = d2; % move point 2 to point 1 103 x2 = x3; f2 = f3; d2 = d3; % move point 3 to point 2 104 A = 6*(f1-f2)+3*(d2+d1)*(x2-x1); % make cubic extrapolation 105 B = 3*(f2-f1)-(2*d1+d2)*(x2-x1); 106 x3 = x1-d1*(x2-x1)^2/(B+sqrt(B*B-A*d1*(x2-x1))); % num. error possible, ok! 107 if ~isreal(x3) || isnan(x3) || isinf(x3) || x3 < 0 % num prob | wrong sign? 108 x3 = x2*EXT; % extrapolate maximum amount 109 elseif x3 > x2*EXT % new point beyond extrapolation limit? 110 x3 = x2*EXT; % extrapolate maximum amount 111 elseif x3 < x2+INT*(x2-x1) % new point too close to previous point? 112 x3 = x2+INT*(x2-x1); 113 end 114 end % end extrapolation 115 while (abs(d3) > -SIG*d0 || f3 > f0+x3*RHO*d0) && M > 0 % keep interpolating 116 if d3 > 0 || f3 > f0+x3*RHO*d0 % choose subinterval 117 x4 = x3; f4 = f3; d4 = d3; % move point 3 to point 4 118 else 119 x2 = x3; f2 = f3; d2 = d3; % move point 3 to point 2 120 end 121 if f4 > f0 122 x3 = x2-(0.5*d2*(x4-x2)^2)/(f4-f2-d2*(x4-x2)); % quadratic interpolation 123 else 124 A = 6*(f2-f4)/(x4-x2)+3*(d4+d2); % cubic interpolation 125 B = 3*(f4-f2)-(2*d2+d4)*(x4-x2); 126 x3 = x2+(sqrt(B*B-A*d2*(x4-x2)^2)-B)/A; % num. error possible, ok! 127 end 128 if isnan(x3) || isinf(x3) 129 x3 = (x2+x4)/2; % if we had a numerical problem then bisect 130 end 131 x3 = max(min(x3, x4-INT*(x4-x2)),x2+INT*(x4-x2)); % don't accept too close 132 [f3 df3] = feval(f, rewrap(Z,X+x3*s), varargin{:}); 133 df3 = unwrap(df3); 134 if f3 < F0, X0 = X+x3*s; F0 = f3; dF0 = df3; end % keep best values 135 M = M - 1; i = i + (length<0); % count epochs?! 136 d3 = df3'*s; % new slope 137 end % end interpolation 138 if abs(d3) < -SIG*d0 && f3 < f0+x3*RHO*d0 % if line search succeeded 139 X = X+x3*s; f0 = f3; fX = [fX' f0]'; % update variables 140 %fprintf('%s %6i; Value %4.6e\r', S, i, f0); 141 if exist('fflush','builtin') fflush(stdout); end 142 s = (df3'*df3-df0'*df3)/(df0'*df0)*s - df3; % Polack-Ribiere CG direction 143 df0 = df3; % swap derivatives 144 d3 = d0; d0 = df0'*s; 145 if d0 > 0 % new slope must be negative 146 s = -df0; d0 = -s'*s; % otherwise use steepest direction 147 end 148 x3 = x3 * min(RATIO, d3/(d0-realmin)); % slope ratio but max RATIO 149 ls_failed = 0; % this line search did not fail 150 else 151 X = X0; f0 = F0; df0 = dF0; % restore best point so far 152 if ls_failed || i > abs(length) % line search failed twice in a row 153 break; % or we ran out of time, so we give up 154 end 155 s = -df0; d0 = -s'*s; % try steepest 156 x3 = 1/(1-d0); 157 ls_failed = 1; % this line search failed 158 end 159 end 160 X = rewrap(Z,X); 161 fprintf('\n'); if exist('fflush','builtin') fflush(stdout); end 162 function v = unwrap(s) 163 % Extract the numerical values from "s" into the column vector "v". The 164 % variable "s" can be of any type, including struct and cell array. 165 % Non-numerical elements are ignored. See also the reverse rewrap.m. 166 v = []; 167 if isnumeric(s) 168 v = s(:); % numeric values are recast to column vector 169 elseif isstruct(s) 170 v = unwrap(struct2cell(orderfields(s))); % alphabetize, conv to cell, recurse 171 elseif iscell(s) 172 for i = 1:numel(s) % cell array elements are handled sequentially 173 v = [v; unwrap(s{i})]; 174 end 175 end % other types are ignored 176 function [s v] = rewrap(s, v) 177 % Map the numerical elements in the vector "v" onto the variables "s" which can 178 % be of any type. The number of numerical elements must match; on exit "v" 179 % should be empty. Non-numerical entries are just copied. See also unwrap.m. 180 if isnumeric(s) 181 if numel(v) < numel(s) 182 error('The vector for conversion contains too few elements') 183 end 184 s = reshape(v(1:numel(s)), size(s)); % numeric values are reshaped 185 v = v(numel(s)+1:end); % remaining arguments passed on 186 elseif isstruct(s) 187 [s p] = orderfields(s); p(p) = 1:numel(p); % alphabetize, store ordering 188 [t v] = rewrap(struct2cell(s), v); % convert to cell, recurse 189 s = orderfields(cell2struct(t,fieldnames(s),1),p); % conv to struct, reorder 190 elseif iscell(s) 191 for i = 1:numel(s) % cell array elements are handled sequentially 192 [s{i} v] = rewrap(s{i}, v); 193 end 194 end % other types are not processed


Abstract
We display here some experiments with a tool for comparing XML-MEI music score files (it aims to be an analog for score files of the Unix diff tool for text files).The MEI scores in the dataset were produced by researchers at the laboratory IReMus during the Gioqoso CNRS project. There are built from a corpus of the Bibliothèque nationale de France (BNF, Gallica) containing 21 ouvertures of Jean-Philippe Rameau.
Every example is composed one page OMRized from the manuscripts, and its manual correction. In the experiments, we compute and display side by side the diffs between the OMRized version and the manual version. If one considers the manual version as a ground truth, then the displayed differences can be useful for a fine detection of OMR errors.
Due to copyright issues, most of the examples of the dataset cannot be displayed here. This page will be updated when these issues will be fixed.
Scores from the dataset
Example 1 Rameau: Les Indes Galantes
original manuscript: https://gallica.bnf.fr/ark:/12148/btv1b8451564d/f15.imageOMRized version
Manual correction (ground truth)
- on bar 6, part 1: OMR forgot a rest which is detected as added (green) in the ground truth.
- on bar 6, part 4: the first note has wrong pitch in OMR. this is signaled as a substitution (yellow). There is also a note missed by OMR at the end of the bar (in green in ground truth).
- on bar 7, part 1: note the OMR mistake for rhythm.
- the OMR missed the barline between bar 10 and 11 (for all parts). this is interpreted as having the notes of the first bar (first 4 beats) deleted (in red in OMR version) and reinserted (in green in ground truth).
- on bar 14: a missing note (in green in ground truth).
- in bars 15, 16, 18: the OMR misinterpreted a key signature as an accident on bar 14, and consequently the editor added accidents problems are due to the change of key signature.
About the missing barline: the logic of our diff procedure is to consider the parts as sequences of bars, and to perform bar-by-bar comparison based on the content of bars. The barlines themselves are not considered as a content in this procedure. That explains the displayed difference for bar 10.
More generally, following the above logic, the page layout (organisation of bars in staves and of staves in a page) is not compared by our diff procedure. Moreover, the trill marks are currently ignored by our procedure (that will be treated in a next version), as well as the changes of clef or key signature and also text indications.


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Pulled Pork Barbeque Sandwich
Slow cooked pork on a pair of sour-dough buns.
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Description:
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From :{%if project.user.profile.location%}
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Uploaded On : {{project.pub_date|date}}
Ratings Scores
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Design Average{{ rates.usability_average }}
Usability Average{{ rates.content_average }}
Content Average{{ rates.score }}
Average Score {% endif %} {% endfor %}{% if rates_status %}
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| User Voters | Design | Usability | Content | Average | |||
|---|---|---|---|---|---|---|---|
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{%if review.user.profile.location%}
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Public Member Functions | |
| void | trigger () |
| String | toString () |
| Public Member Functions inherited from ch.ethz.systems.netbench.core.network.Event | |
| Event (long timeFromNowNs) | |
| long | getTime () |
| int | compareTo (Event o) |
Private Attributes | |
| final OutputPort | dispatchPort |
| final Packet | packet |
Event for the dispatch of a packet, i.e. when all of the bits of the packet have been written to the link.
| String ch.ethz.systems.netbench.core.network.PacketDispatchedEvent.toString | ( | ) |
| void ch.ethz.systems.netbench.core.network.PacketDispatchedEvent.trigger | ( | ) |
Trigger whatever has to happen with the event and the data it contains.
Reimplemented from ch.ethz.systems.netbench.core.network.Event.
|
private |
|
private |


7 Up!
Much like the famous documentary series, we check in every 7 years except instead of filming the progress of some British slags and twonks, its all about me, Andrew, and a can of who knows what.
Bee An Animator
I used to lie to people and say I was allergic to bees, but in reality I was just afraid of being stung.
Hair Today...
It grows out of my face!
Apartment Dweller
I may have missed a few but I am trying to document every room I've lived in.


The matrix component at the first row, first column.
The matrix component at the second row, first column.
The matrix component at the first row, second column.
The matrix component at the second row, second column.
The matrix component at the third row, first column.
The matrix component at the third row, second column.
Adds the given matrix to this matrix component-wise.
The parameters a-f form a 2x3 matrix and are arranged like this.
+---+---+---+
| a | c | e |
| b | d | f |
+---+---+---+
The matrix component at the first row, first column.
The matrix component at the second row, first column.
The matrix component at the first row, second column.
The matrix component at the second row, second column.
The matrix component at the third row, first column.
The matrix component at the third row, second column.
Creates a copy of this matrix and returns it.
A new matrix that is equal to this matrix.
Creates a new matrix that represents the inverse affine transformation of this matrix.
A new matrix that represents the inverse affine transformation of this matrix.
Applies a rotation to this matrix.
The angle of the rotation, in degrees.
Horizontal coordinate of the origin of the rotation.
Vertical coordinate of the origin of the rotation.
Applies a scaling operation to this matrix.
Horizontal coordinate of the origin of the scaling.
Vertical coordinate of the origin of the scaling. If not specified, default to same value as x
.
Applies a scaling operation to this matrix.
Horizontal coordinate of the origin of the scaling.
Vertical coordinate of the origin of the scaling.
Amount by which to scale in the horizontal direction.
Amount by which to scale in the vertical direction.
Splits matrix into primitive transformations.
Information regarding how this matrix can be produced by applying a chain of primitive transformations.
Creates a transform string that represents given matrix, such as t0,0s1,1,0,0r0,0,0
.
A CSS transform string that represents given matrix.
Applies a translation to this matrix.
Applies this transformation matrix to the given point and returns the x coordinate of that transformed point. See also y.
Horizontal coordinate of a point to transform.
Vertical coordinate of a point to transform.
Applies this transformation matrix to the given point and returns the y coordinate of that transformed point. See also x.
Horizontal coordinate of a point to transform.
Vertical coordinate of a point to transform.
Generated using TypeDoc
Represents a 2x3 matrix for affine transformations in homogenous coordinates. This allows for translations as well as rotations, scaling, and shearing.
The six components a-f of a matrix are arranged like this:


25 Jun 2022 (Last Modified 30 Jun 2022)
To identify which substance-effect associations mentioned online can be used to generate hypotheses it is immportant to demonstrate that the association is specific and plausible. I use these terms as they are used in the Bradford-Hill Criteria.
The more specific the association between two tokens, A and B, the more often B occurs whenever A occurs and doesn’t occur unless A occurs. In a limited domain of discourse, tf-idf does well in identifying the specificity of association after correcting for baseline rates (citation needed). The main difference between tf-idf and dimension reduction on a covariance matrix is the idf component. Tf-idf weights each entry by the number of documents the token appears in. This provides a more context-relevant scaling than subtracting a measure of central tendency from the tf term at the expense of making it impossible to compare absolute tf-idf scores across corpora.
The more plausible an association between two tokens, A and B, are, the more the association between A and B can be explained in terms of accepted knowledge (e.g., things one would find in a knowlwedge base). Right off the bat we can anticipate that all computational of plausibility are preliminary because the knowledge base is incomplete, at least until the last question is answered. Said another way, computations of plausibility are necessarily limited by the open world assumption. In this notebook, I discuss computing plausibility in terms of fractional overlap of gene targets. See Alternative Approaches for approaches that use additional information, like network structure, that provide more information but are also less available.
We start with the following resources:
| Resource | Role | (n) |
|---|---|---|
| KEGG | Map Substance to Signal Transduction Cascade | |
| DrugBank | Maps Substances to Biochemical Targets | 14,594 |
| GO | Map Biocheimcal Intermediary to Effect | |
| DisGeNet | Maps Gene Target to Clinical Phenotype | 441 (for OUD or PTSD) |
flowchart TD
subgraph Statistic[Similarity of Gene Profile]
direction LR
A[Drugs froms Social Media
In Drug Bank with Known Targets] --> B[Genes of Drug Targets]
B --> C[Co-expressed Genes] & D[First Neighbors of Drug]
C & D --> E[Expanded Gene Set]
E --> F[
Jaccard Similarity Between Expanded Gene Set
 and Genes Differentially Expressed in PTSD, OUD, or Both]
end
subgraph Significance[Calculation of Significance]
direction LR
a[Drugs in DrugaBank with Known Targets]
a --> b[Calculate Jaccard Similarity for Their Expanded Gene Sets]
b --> c[Create Empirical Probability Density Function]
b --> d["
Identify Median Jaccard Similarity for Currently Approved PTSD, OUD Therapeutics:
ROC Curve
(Is there a Deault Network?)"]
end
Statistic --> Significance
| (+) Controls | (-) Controls |
|---|---|
| Methadone Yes |
Aspirin |
I obtained the XML dump of DrugBank (current as of March 2022) from DrugBank, licensed for academic use. I converted the XML to a JSON array using xmltodict and then imported the array into a MongoDB server. Even though DrugBank provides an XSD, I found MongoDB faster and more intuitive than XPath.
I obtained the genes that were direct targets of methadone with the following query (example is for methadone):
> db.drugs.aggregate([{$match:{"name":"Methadone"}},{$project:{_id:0,"name":"$targets.target.name","gene-name":"$targets.target.polypeptide.gene-name"}}])
# "{"name" : [ "Mu-type opioid receptor", "NMDA receptor", "Delta-type opioid receptor", "5-hydroxytryptamine receptor 3A", "Neuronal acetylcholine receptor subunit alpha-7", "Neuronal acetylcholine receptor subunit alpha-3", "Neuronal acetylcholine receptor subunit alpha-4", "Neuronal acetylcholine receptor subunit beta-2" ], "gene-name" : [ "OPRM1", [ "GRIN1", "GRIN2A", "GRIN2B", "GRIN2C", "GRIN2D", "GRIN3A", "GRIN3B" ], "OPRD1", "HTR3A", "CHRNA7", "CHRNA3", "CHRNA4", "CHRNB2" ] }
# Not sure why a nested list was returned.
Let’s use Enrichr (API) to identify the 100 most commonly co-exressed genes. For methadone this created a set of 1400 genes, of which 994 were unique and has 2 genes overlapping, OPRM1, which we knew and GAL, a gene that encodes for galanin and galanin-map associated peptide. Indeed this article suggest that heteromers between the receptor for galanin and the opioid receptors may attenuate the addictive potential of methadone. This paper suggests that galanin modulates stress reactions. The idea
Then we ask KEGG what human pathways those genes are implicated in
DisGeNet provides a REST API. I queried the API for PTSD (CUI:C0038436) and OUD (CUI:C4324621), which returned 441 genes.
#import requests
PTSD = "C0038436"
OUD = "C4324621"
diseases = f'{PTSD},{OUD}'
if api_key:
s.headers.update({"Authorization": "Bearer %s" % api_key})
gda_response = s.get(f'{api_host}/gda/disease/{diseases}', params={'source':'ALL'})
if s:
s.close()
I imported the JSON array into MongoDB so queries could reference both data sets. We can now compute the fraction of targets for a drug of interest that lie in the intersection of OUD- and PTSD-associated genes.
An alternative approach would be to export the gene names for each condition to a text file. This worked for PTSD and OUD. In bash, one can compute the intersection as sort OUD.txt PTSD.txt | uniq -d
if we treat gene expression as a categorical variable.
sort OUD.txt PTSD.txt | uniq -d
# BCHE, BDNF, C1QL1, CRH, GAL, HCRT, IL10, IL6, MET, OPRM1, PSS
| Condition | Genes |
| Methadone | OPRM1, GRIN1, GRIN2A, GRIN2B, GRIN2C, GRIN2D, GRIN3A, GRIN3B, OPRD1, HTR3A, CHRNA7, CHRNA3, CHRNA4, CHRNB2 |
| PTSD & OUD | BCHE, BDNF, C1QL1, CRH, GAL, HCRT, IL10, IL6, MET, OPRM1, PSS |
| PTSD & OUD & Methadone | OPRM1 |
My interpretation is that there is only one intersection because the Methadone row contains genes of direct targets, but the PTSD & OUD row contains genes for intracellular components. To add genes for intracellular components for (i.e., downstream effectors of) the direct targets of Methadone. Luckily, this post describes exactly how to do that.
First, download the ids of all targets.
curl -Lfv -o filename.zip -u $username:$password https://go.drugbank.com/releases/5-1-9/downloads/target-all-polypeptide-ids -vs > ./external/drugbank_targets .txt 2>&1
wget http://rest.kegg.jp/conv/eco/uniprot
mv uniprot ./external uniprot kegg_uniprot_ids.tsv
My file structure now looks like.
tree -d
.
├── Area 51
└── external
A peak at the files:
#we are in the external subdirectory of data/
head -n 3 drug-bank-target-ids.csv | csvlook | less -S #has very long columns
| ID | Name | Gene Name | GenBank Protein ID | GenBank Gene ID | UniProt ID | Uniprot Title | PDB ID | GeneCar | … |
|---|---|---|---|---|---|---|---|---|---|
| 1 | Peptidoglycan synthase FtsI | ftsI | 1,574,687 | L42023 | P45059 | FTSI_HAEIN | |||
| 2 | Histidine decarboxylase | HDC | 32,109 | X54297 | P19113 | DCHS_HUMAN | 4E1O |
head -n 2 kegg_uniprot_ids.tsv
up:P0AD86 eco:b0001
up:P00561 eco:b0002
The goal is to create a graph like the following
graph
subgraph Path Length = 3
A[Substance] --> B --> C --> D[Effect]
end
subgraph Path Length = 2
AA[Substance] --> BB[B] --> DD[Effect]
end
We infer that a path with a shorter length is more biologically plausible than a path with a longer length because the shorter path involves fewer intermediaries and so fewer dependencies on other signal transduction cascades or cellular processes.
Our corpus lists substance and effects. We assemble a graph by linking (substance, target), (target, target), and (target, effect) pairs. Here target means any biochemical intermediary, such as the target receptor or a carrier protein.


Preparation time
30 mins to 1 hour
Cooking time
30 mins to 1 hour
Serves
Serves 4
Dietary
Place the whole lemons into a small saucepan, cover with water, add the salt and bring to the boil. Cover with a smaller saucepan lid turned upside down, or a heatproof saucer to keep the lemons below the surface of the water. You may have to weigh the lid or saucer down, as the lemons will float to the surface.
Boil the lemons for 30 minutes, or until the lemons are soft and the skin can be pierced easily with a fork, then drain and set aside to cool.
Cook the artichokes in a separate pan of salted boiling water for 20 minutes, or until soft at the centre, then drain and set aside to cool.
Peel away the tough outer leaves of the artichokes and cut across the top to remove the upper, inedible section of the leaves and reveal the heart. Trim the stalks if they are stringy, and remove the choke (the furry yellow matter in the centre of the artichoke) if there is one. Cut the artichokes into quarters, then place in a bowl and season with salt and freshly ground black pepper.
Cut the boiled lemons in half, then scoop out and discard the soft inner pulp and other stringy pith. Tear the skins of each half into 2-3 pieces and add to the artichokes.
Heat a small frying pan over a medium heat. Add the almonds and toast them, tossing over occasionally, to brown all over.
Add the toasted almonds and thyme leaves to the artichoke and lemon mixture.
Mix the honey with the lemon juice in a clean bowl and add the olive oil. Season, to taste, with salt and freshly ground black pepper, then pour the dressing over the artichokes and lemons. Mix together well and serve.


Summary of the Seminal paper on Dropouts
In this post, I summarize the paper titled, “Dropouts: A Simple Way to Prevent Neural Networks from Overtting” by Srivastava et al., publised in Journal of Machine Learning (2014).
Dropouts is a regularization technique for neural networks that was introduced to reduce over-fitting introduced in models with millions of parameters, but trained on limited data. The best way to regularize a fixed-sized model is to average the predictions of all possible settings of the parameters, weighing each setting by it’s posterior probability given the training data, but this would involve unlimited computation and is prohibitively expensive. Even if computation is not an issue, large networks require large amounts of training data and there may not be enough data available to train different networks on different subsets of data.
Dropouts addresses both these issues of computation and data availability. It provides a way of approximately combining exponentially many different neural networks efficiently. It does this by dropping out units at random, temporarily removing it from the network, along with all it’s incoming and outgoing connections. Training a neural network with dropout can be seen as training a collection of thinned networks with weight sharing, where each thinned network gets trained very rarely, if at all. How is this handled at test time, as it is not feasible to average the predictions from exponentially many thinned models?
Instead, a simple approximate averaging method is used, where the weights of the network, with all it’s units at test time, are scaled-down versions of the trained weights. If a unit is retained with probability p during training, the outgoing weights of that unit are multiplied by p at test time. This ensures that for any hidden unit, the expected output (given dropout probability ) is the same as the actual output at test time.
The authors applied dropout on multiple classification datasets in various domain, in vision (MNIST, SVHN, CIFAR-10/100, ImageNet), speech (TIMIT), text and genetics. In all, they looked at the state-of-the-art techniques with and without dropout, observing the test error. The improvement was much smaller in the text dataset compared to that for the vision and speech data sets. In all cases, the optimal dropout probability was found to be 0.5 for hidden units and 0.8 for input units. Dropout breaks up co-adaptations and the activations of the hidden units become sparse, which is why it leads to lower generalization errors.


{% blocktrans %}
You are able to become member of our community in order to provide support in authenticated users by declaring your skype ID. You can assist them for free (volunteer) or with fee (professional).
Send a request to our administrator.
{% endblocktrans %}
{% if not aod_community_member %}
{% trans 'Join now' %}
{% else %}
{% if aod_community_member.is_active == True %}
{% elif aod_community_member.is_active == False %}
{% else%}
{% endif %}
{% endif %}
{% endif %}
{% endblock content %}
{% block scripts %}
{% with 'app/scripts/bootstrap-table/dist/locale/'|add:bootstrap_table_locale_url as bootstrap_table_locale %}
{% endwith %}
{% endblock %}


Support
$.wordCloudSupported
$.wordCloud(); MySQL Support
Database Host
Database Username
Database Password
Database Name
Select Fields
Table Name
Where Clause
Max Words
Excluded Words
Biggest Word


SFAI Zoom Training
(hit space to advance slides)
Zoom is a remote conferencing services that combines
video conferencing, online meetings, chat, and mobile collaboration.
- SFAI is providing a Zoom account to all faculty to facilitate online class sessions
- Zoom offers a web client and a desktop client
- The desktop client has more features and is preferred for hosting classes.
- In the next few slides
we'll go over how to install it and connect it to your SFAI account
- This first step is to activate your account
- SFAI
setup instructions
- Patrick just went over this. Link is here for reference
- If you need support with this, email<EMAIL_ADDRESS>or stay in the Q&A
afterwards
When you first launch Zoom sign in with Google
Make sure to sign in with your SFAI account
You will be redirected to your web browser to login in,
then
Open Zoom.
In the opening Zoom window
start with new meeting. We will talk about scheduling one a little bit later
After starting a new meeting you have the option of
testing
your audio setup. Afterwards choose 'Join With Computer Audio'
Hitting start video on the bottom toolbar will start
the
video
session
The toolbar at the bottom of the Zoom window is important to understand
so
let walk through it's functions
Join Audio gives you the option to adjust your Mic and
Speaker
settings
The video button allows you to start, stop, adjust
your
video settings and use virtual backgrounds
The invite button allows you to invite participants
In the contact view, you will see the SFAI email directory
listed.
On the email tab you can compose an email to send out
from
your default email client
You can also copy and paste the meeting URL or a more
detailed invite and paste it into an email or document.
This is good for setting up quick meeting. In a little bit Patrick will present on how to set up
recurring class meetings in google calendar and moodle
Your invitees will get an invitation like this
When they click on the link they will be prompted in
install zoom if they have not already. If the zoom desktop client is installed they will be prompted to
open it.
Invitees(students) do no need an account. Only the
host(Teacher) needs to be logged in.
Once the host enters the meeting all participants will
appear.
- It is suggested that you start your first class meeting and invite everyone ~15 minutes early.
Share screen allows you to share your screen with
participants
You can choose to share your entire desktop
A shared whiteboard is also available
Or an individual window
When sharing your screen the toolbar will become a
floating toolbar
Screen Annotation tools are also available when you are
sharing
your screen
The annotation tools allow you to draw on your screen, add
text, show your mouse or highlight areas.
Manage partipants allows gives you options for individual
participants
You can mute individual audio or video
You can also promote them to the host, rename or
remove
them
Chat opens a chat window on the side
You can post text and links here
At the bottom you can choose who you are chatting with,
eveyone or individuals
You can also save the chat history and set options for
whom
others are allowed to chat with.
Record allows you to record the meeting to either your computer or the
Zoom cloud. You have limited storage on the Zoom cloud. Consider saving to you computer and sharing
as a
google drive link.


This example will show how to create a simple screen with basic functionality using the framework.
Begin by creating a new view in your config.json file:
{ "applicationConfig": { "views": { "Simple": { "url": "Simple", "model": "SimpleModel", "modelbuilder": "SimpleModelbuilder", "actions": "SimpleActions", "controller": "SimpleController" } } } }
Create your model (using this page as an example):
// A Model just returns a plain JS object (with no functions!) var SimpleModel = function(){ return { firstName: 'John', lastName: 'Tibble' }; };
Create your modelbuilder (using this page as an example):
// Modelbuilders always accept a Model var SimpleModelbuilder = function(Model){ // Modelbuilders must return a function that can be called. // This function returns the built model return function( config ){ // Modelbuilders can be configured to add/remove/change Model properties // See http://en.wikipedia.org/wiki/Builder_pattern if( config && config.firstName && config.lastName ){ Model.firstName = config.firstName; Model.lastName = config.lastName; } return Model; }; };
Create your actions (using this page as an example):
var ExamplesActions = function(Router){ return { goTo: function( route ){ Router.goTo(route); } }; };
Create your controller (using this page as an example):
// A Controller needs to receive the following parameters: // Context (which is exposed to the template), // Actions (functions that can be called by actions in the template) // Modelbuilder (which is invoked to get a model to display) var SimpleController = function( Context, Modelbuilder, Actions ){ Context.Actions = Actions; Context.Model = Modelbuilder(); };
Create your template (look at the page for this example)
Finally, navigate with your browser to #/Simple to see the page


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Angular Meetup
Angular 1 to 2 Migration Strategies
A tech investigation by Jose Badeau
About Me
- I'm originally from Philadelphia
- I Work for ES Group AG as a software developer
- I Enjoy Swiss culture like Raclette and Beer
- I once tried to become a Professional eSports player but failed miserably
- Visit hardread.ch for info on Zurich's premiere fighting game organization.
Why Migrate to Angular 2?
Performance
- Rendering speed is considerably faster than angular 1.x
- Server-side rendering support
- Support for offloading tasks to webworkers
Mobile Support
- Support for touch interfaces, limited screen real estate and mobile hardware
- Tight integration with Ionic 2
- Support for native development using NativeScript
Refined Architecture
- Components and ES6 classes replace Angular 1 controllers, providers and directives making it easier for new and experienced developers to get started
- TypeScript support
- Modern module and loader support
Preparation
In order to ease your migration to Angular 2 there are certain best-practices and techniques that will not only reduce your migration pains but will also improve your Angular 1 codebase.
Follow the Angular Styleguide
The Angular StyleGuide provides a collection of patterns and best practices on how to and how not to write and organize Angular code.
- I component per file
- Organize code by feature not component type
- Utilize modern loaders like JSPM or Webpack (hint: previous meetup JSPM presentation)
Make Directives/Components, not Controllers
- Provide reusable pieces of functionality
- Similar to Angular 2 components
- Provide declarative interfaces via attributes
- Can utilize uni-directional data-binding
- Previous meetup Component Pattern for Angular 1.x)
Choosing your Language Specification
Angular is written in Typescript but can be used with ES5 or ES6/ES7
TypeScript
- Most stable and tested
- Can work side by side with ES5 and ES6
- Best suited for large code bases
- Easiest to refactor
- Largest overhead due to things like 3rd party typing
- Can be difficult for beginners
ES6/ES7
- Most complex workflow setup
- Most popular. Over 45% of developers say they plan to use ES6 and 10% are unsure
- Provides many of the benefits of TypeScript
ES5
- Easiest workflow, minimal tooling setup required
- Fluent API is actually quite intuitive
- Hard to find examples and support
- Cannot easily take advantage of new feature like metadata processing
- Best debugging experience
Choosing your modual loader and build tools
SystemJS
- Looks to be the standard
- Easy setup
- The official Angular module loader
JSPM
- Utilizes SystemJS
- Adds advanced dependency managament support
- Easy to connect to mutiple repositories like npm, github, private, etc
- Has some known issues with SystemJS and Babel 6 which affect Angular 2
Webpack
- Least complex setup
- Utilizes NPM and not custom repositores (github ratelimits)
- Most popular
- Many powerful features like code splitting, hot reload, advanced code optimzations
- Plays well with Babel 5 and 6
Babel 5 or 6
- Babel 5 is deprecated
- Babel 6 is the future
- Babel 6 removed support for decorators which requires workarounds to work with Angular 2.
- Babel 5 currently has the most support, examples and documentation
Why did I choose ES6/ES7 Webpack and Babel 6?
- The majority of angular 1.x apps are now written in ES6/ES7
- ES6/ES7 is by currently where the majority of developers are moving to
- Many parts of TypeScript will make their way to ES6/ES7 anyway
- I prefer JSPM but it has some known issues (SystemJS registration and angular reflect)
- Babel 6 is constantly improving and the intitial integration pain is mostly a one time thing
- Almost all tutorials online are in TypeScript and I didn't find many in ES6/ES7
Demo
This demo will show how and exisiting Angular 1 app can be upgraded to Angular 2 in 4 steps.
Step 1 - Build
- Upgrade Angular to v1.5 for new component directive
- Upgrade ui-router to v1.0.0 for new component routing
- Upgrade to Babel v6 as v5 is deprecated
- Tip - Use angular 2.0.0-beta.15 as other versions have issues with ui-router 1.0.0
- Tip - Annotations and Decorators are not the same. Decorators are the way forward
- Tip - Babel 6 removed support for decorators and therefore extra plugins are required
Step 2 - NG1 Components
- Decide which directives you wish to move to Angular 2 Components
- Move all Angular 1 routes and directives to 1.5 components
- Change all attribute style directives to element
- Change all controllerAs to $ctrl
- Tip - Angular 1 components are just directives that enforce specific defaults like: controllerAs, bindToController and isolated scope
Step 3 - NG2 Components 1
- Import zones.js which is like a thread-local storage and is heavily used by Angular 2 as a $digest replacement
- Import reflect-metadata which provides proposed ES7 decorator (@) and metadata refective support.
- Import and create a constant angular2/upgrade singleton which provides interpolarity between Angular 1 and 2
- Convert Angular 1 directives to Angular 2 components (feature-a-component and some-component)
- Convert Angular 1 templates to Angular 2 templates by removing $ctrl and converting ng-click to (click)
- Upgrade any Angular 1 services ($state) with angular2/upgrade to be injectable in Angular 2 components
- Inject Upgraded $state service into Angular 2 components to utilize ui-router
- Downgrade any Angular 2 directives with angular2/upgrade to be used within Angular 1.
- Manually bootstrap angular 1 and 2 with the upgrade adapter (remove ng-app)
- Tip - If your using TypeScriptng1-to-ng2 provides a ui-router bridge (can use ui-router directives in Angular 2 components). Does not work with ES& without heavy workarounds
Step 4 - Component Router
- Remove Angular 1 and ui-router
- Upgrade Angular 2 to RC-1 which is now separated into individual "@angular/* modules
- Replace index.html markup with an Angular 2 root component
- Register routes with the new component router
- Convert ui-router directives ui-sref and ui-sref-active to component router equivalents routerLink and router-link-active css class
My impressions and Recommendations
- Routing is the hardest aspect to migrate because of things like resolve, parameters, extras, lazy loading, etc
- If your app uses ui-router heavily then I would wait until ui-router provides a clear upgrade path. There is still allot of discussion going on with the ui-router and angular 2 team about routing
- For any non trivial application I think TypeScript is the path of least resistence
- Babel 6 is not ready (Metadata and Decorators) and has some compatablity issues with JSPM, Use babel 5 for now
- Migrate from the bottom up. There are issue with ui-router and upgraded angular 1 components (ng1 in ng2)
- There are still many undocumented breaking changes going on. Prepare yourself for digging into the sourcecode, trolling slack and opening github issues
- Angular 2 feels very polished and really reduces boilerplate but the many incompatibilities, lack of 3rd party support and documentation make it a rather painful migration at the moment.


My name is David Lindner. I have AS degrees in computer science, math and science,
and social science. I am a fullstack web developer currently enrolled in UC Davis' Fullstack Coding Bootcamp. I have
come to learn that I really enjoy front end development; especially CSS and the design
portion of web development. I have experience with node.js, express, MySQL, handlebars templating engine,
Git, Heroku, frontend and backend Javascript, and HTML and CSS.


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---
layout: post
authors: ["Greg Wilson"]
title: "Interim Board Meeting: Oct 14, 2014"
date: 2014-10-14
time: "19:30:00"
tags: ["Governance"]
---
Software Carpentry Foundation Interim Board Meeting: Oct 14, 2014
Attending
- Jenny Bryan (Univ of British Columbia)
- Josh Greenberg (Sloan Foundation)
- Katy Huff (UC Berkeley)
- Damien Irving (University of Melbourne)
- Neil Chue Hong (Software Sustainability Institute)
- Adam Stone (Berkeley Lab)
- Tracy Teal (Michigan State / Data Carpentry)
- Kaitlin Thaney (Mozilla Science Lab, audio only)
- Greg Wilson (Software Carpentry)
- David Ascher (Mozilla) - on Etherpad, but not on call
Actions
- Board: next meeting on Tue Nov 4 (same time)
- Board: submit corrections/extensions to governance doc via pull requests by Oct 24
- DI + GW + NCH + KT: define process for communication and issue escalation among workshop coordinators
- KT + JG + JB + NCH: talk about GW's salary from Nov 1
- AS + KH: arrange AS access to GitHub repositories
- JB + KH: transfer ownership of draft grants material to Software Carpentry board group
- GW: find out how much notice we need to give NumFOCUS to have a rep attend a board meeting
- GW: re-add note to governance doc about SCF board deciding scope of SWC project
- GW: circulate minutes from last two meetings for approval before putting in public repository
Resolutions
- KH + TT + GW will be signatores on the NumFOCUS FSA
- Documents stored in two GitHub repositories
- Public (things go here by default): {{site.github_url}}/board
- Private: {{site.github_url}}/board_pvt
- Send minutes to board mailing list for correction/redaction of personal information
- Put into public repository one week after meeting
- Escalation
- Workshop coordinators promote issues to project lead as needed
- Project lead promotes to board as needed
- Coordinators may go directly to the board if they feel it appropriate
Summary
- Date of next meeting
- GW: propose Tue Nov 4 3:30 EDT
- NCH: may not be able to do it
- passes: if NCH is unable to make it, choose a chair closer to the day
- Final approval for signing up with NumFOCUS
- KH, TT, GW as signatories
- passes
- Mechanics of storing SCF documents (KH)
- Public Repo : {{site.github_url}}/board
- minutes will hold summaries of the chat window
- Private Repo : {{site.github_url}}/board_pvt
- Board Team : https://github.com/orgs/swcarpentry/teams/board
- Procedure for when we make things public?
- e.g. minutes
- Once there is a milestone version, we can introduce a period of review on the listhost
- After a week of discussion on the listhost, things will become public.
- passes
- Should grants stuff go in board_pvt?
- Probably not but once we have time to discuss this (probably not today) we can tackle that.
- Discussion of governance and core vs non-core activities
- Re-add note about board deciding scope of Software Carpentry (what's in/what's out)
- Do we think that it is useful to have a NumFOCUS rep observe at the Board meetings?
- NumFocus have offered to attend Board meetings
- Do we need the governance document to be in particular format (for legal reasons)?
- Yes, soon but not immediately
- Who fights copyright / trademark ?
- NumFOCUS (because they will own the trademarks)
- Q: what can/should be handled by admin staff like Arliss, what needs to be pushed up to the board?
- proposal: admins promote to the project lead as needed, project lead promotes to the board as needed, admins encouraged to go direct to the board if they feel appropriate
- passes
- Discussion of budget
- Josh: "SCF = steward of the public goods for SWC". Institutional partners contribute to SCF to support that.
- Who organises the "special" workshops, like WiSE workshops? (or little efforts by, say, grad students, who don't have easy access to funding streams or event coordination abilities)
- Does a central "workshop coordinator of last resort" need to paid by taxing institutional contributors?
- Are there any funders who would support this? Possibly not?
- why would institutions be happier paying for program management than for coordination?
Can we make it so that institutional partner contributions aren't calculated such that early contributors don't end up paying more because they are subsidising the lack of other contributors?
- From the chat:
- DI: Whatever happened to each individual workshop giving money for core?
- GW: we've been asking for donations - hasn't been particularly successful
- JB: Re: a donation to support a specific workshop, how do we feel about a donation to support development of curriculum for specific topic?
- DI: At UniMelb we are getting money from the Australian National Data Service to develop capstone examples using Australian data
- DI: Does [organization's] contribution to the 'core' have to be money?
- GW: alternatives?
- DI: Not sure. I just know that [some orgs] will probably not want to contribute money to core.
- JG: the only "in kind" support to core budget lines according to my strict definition would be salary for the project leads (not workshop coordination)
- TT: I'm a little concerned that all workshop coordination is being 'outsourced' to institutional partners, and it makes it hard to coordinate as a whole
- JB: It would be hard to get grant money to SWCF to support workshop coordination. That should be for curriculum development and advocacy.
- DI: At what point do you become an institution that is doing so much SWC stuff that they should start giving money? 3 workshops a year? More? Less?
GW: overhead to ramp up on workshop coordination machinery is (unfortunately) considerable at the moment, so volunteers stepping in to coordinate a workshop now and again is impractical


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