How does JaveScript compare to HTML and CSS?
HTML and CSS are static meaning the code is displayed on the browser and there is no interaction between user and site. Adding JavaScript creates a more dynamic page, such as the user is now able to click buttons or answer questions. The ability of being able to engage with the site is all due to JaveScript, but html and css are still needed for layout and design.
Loops and Control Flow explained using examples from everyday life.

For example:
You are listening to your favourite tunes on Spotify and the song changes randomly to a new song, automatically. This is done with a while loop. Pretty much what is happening, is the computer is asking while Spotify is still in play mode, and NOT changed, go and choose new song. Loops are helpful to coder's because they reduce the amount of code needed to be rewritten to complete an action.
The control flow is a fancy way of saying how a computer makes decisions. So let’s say you want to play “Choose your own ending” game and the computer asks you a set of questions to determine your path through the game. The control flow can be followed by looking at the use of programing commands called if/else statements. These guys help a computer to make a choice. If this happens then do this, or else do this.
The differences between accessing data from arrays and objects.
In common sense terms objects are things which allow associations to be made, an array is a collection of items usually a list. Since arrays are lists that means the computer knows how many things are in the list. If you wanted to know what the third item was in the list you could access the list by using the the number.
Objects are little more complicated because objects hold more information. Let’s say you had three people sitting at a table, each have a name, age, and favourite color. You could group them into three different objects. To access the information, you would use the objects name and then specify the piece of information you wanted. For example; person ones.age
.
Why are functions useful?
In coding it is preferable to write as little code as possible. Enter Functions, these helpful things save coders a lot of time. The beauty of Functions is is that they are reusable code that can be used more than once when its recalled by name.
For example,:
You could save a function which would convert Celsius to Fahrenheit, for those non-metric thinking people. You would name the function thermostat
, and you wanted to know what 20 degrees was in fahrenheit. So you would call the function thermostat(20)
and out would pop 68 degrees Fahrenheit. Isn’t that neat?


Hytool - The versions
This document summarizes the history of the different versions of hytool.
Version 0.0
- Start of development in 1998
Version 1.0
October 2001
- The first documented version
Version 1.2
December 2002
- Improvement of the Graphical reports (tst)
- New solution : Gringarten and Ramey
- Improvement of the step drawdown method (eha)
- Improvement of the step drawdown method (eha)
Version 1.3
August 2003
- Improvement of slug tests interpretations
- Modification of all the functions related to
the Cooper et al. solution (replacing alpha
by Cd) and modification of the guess algorithm (gss)
addition of a radius of investigation calculation
- Implementation of the solution of Ramey et al.
with a skin effect
- Implementation of the solution of Dougherty
with partal penetration (dls)
- Creation of ldf_slg to enhance the efficiency of
slug test interpretation
Version 1.4
October-December 2003
- Improvement of the Barker grf model
- Development and validation of the Gringarten model (grg)
- Development of an interactive windowing for the Theis
method and for slug test (ezwt and ezst)
- Implementation of the Cinco-Ley solution for fractured
wells
- Implementation of the Hvorslev model for slug test
- Implementation of the prs model for spherical flow slug test
Version 1.5
Jannuary-March 2004
185 M-files, 2366 lines of code, 1000 lines of comments
- Improvement of the Warren and Root technique
- Updating the documentation
- Implementation of the graphical interfaces ezwt and ezst
Version 1.5.2
April 2005
- Corrections of the help files to make them homogeneous
- Correction of eha_tst to replace the variable name C by B
- Correction of eha_tst so that it accepts both a line vector
and a column vector for p
- Correction of thn_gss
Version 1.6
September 2005
- Implementation of the solution of Delay et al. 2004:
functions del_dim and del_tst
- Implementation of the solution trm for Theis Multiple
Rates tmr_pre, tmr_dim, etc.
Version 1.7
Mai 2006
- Corrections of the help in tmr
- Implementation of the htj_gss, fit, and tst functions
- Modification of diagnostic(t,s) to open a single figure
Version 1.8
Novembre 2006
- Correction d'un bug dans la solution de Warren et Root war_dls
- Mise à jour de hmb_drw et pca_drw
Version 1.9
March 2007
- Correction de GRF - Ajout des fonctions gss, fit et tst
- Adding new function ths_dmo
- Correction of Contents.m
Version 1.91
Mai 2007
- Corrections of a few bugs
- New functions jlq_dim, jlq_gss, jlq_fit, jlq_tst, jlq_dmo
- New functions birsoy_time, birsoy_demo
- Correction of Contents.m
Version 2.0beta
July 2007
- Development of a set of new functions.
- nzl Neuzil for pressurized test
- tmc Multiple rate constant head
- filters and samplers
- hbw and hba Hamm and bidaux
- pca and pcb Papadopulos cooper in aquifer
- aga Agarwal in aquifer
- Corrections of a few bugs in the figures created with tst
Version 2.0
October 2007
- Release of the version 2.0
Version 2.01
April 2008
- Online distribution of version 2.0 on sourceforge.net, followed by 2.01
- Corrections of a some errors in the help files, and in the syntax of the
commands hyselect, nsl_rpt, nsl_gss, csl_rpt, blt_pre
Version 2.02
October 2008
- Modification of the fit() function in order to compute confidence interval
and display the history of the fitting process.
Version 2.03
May 2010
- Adding the WAW model for single well test in double porosity aquifer.
- Minor bug corrections
© 1998-2010 Philppe Renard and Co.
Terms of Use
Acknowledgments


A List of Fruits Native to Peru
| Guaba |
| This fruit looks like a giant pea pod. You will see street vendors of Lambayeque selling them, and it is safe to buy from them as long as you make sure they break it open for you before you buy it (to ensure that there aren't any bugs inside). The guaba is eaten by breaking it open, eating the sweet white part, and leaving the seeds and the outer skin. |
| Guanabana |
| This fruit is in season in July and August. It’s exterior is green with a spiky looking texture, and its interior is white. It can be eaten fresh but is most commonly used for beverages and ice cream. To eat it, just cut it into slices and eat the white part of the fruit. Don’t eat the green skin or the black seeds. |
| Maracuyá |
| The Maracuyá is known as a passion-fruit in English-speaking countries. It can be eaten fresh, but it has a very tart flavor. You know it is ripe when the outer skin becomes wrinkled– at that point it is ready to make fresh juices and desserts.  If you want to try a less tart version of the maracuyá, the granadilla is a similar fruit. |
| Granadilla |
| This is an orange-colored, oval-shaped fruit that is about the size of a tennis ball. It is very similar to passion-fruit (or maracuya), but not quite as tart.  Recommendation: don't chew the seeds, just swallow them. |
| Lúcuma |
| This is a tropical fruit that has been a staple of the Peruvian people since ancient times due to it's high nutritional content. It has a very unique taste– some say it tastes like pumpkin, and some say it tastes like caramel. Not many people eat this fruit raw, though it's taste is used to flavor many desserts in Peru, the most common being ice cream. |


|
AKKU::Smart::Encoder
Light weight module to do the encoding in either Xml or Json from single object
|
#include <SmartEncoder.hpp>
Public Member Functions | |
| EncoderData (TYPE t) | |
| Construct a new Encoder Data object. More... | |
| virtual | ~EncoderData () |
| Destroy the Encoder Data object. | |
| TYPE | GetType () |
| To get the type of data. More... | |
| virtual string | ToJson ()=0 |
| To convert the data into json encoding. Which should be override in the derived class. More... | |
| virtual string | ToXml ()=0 |
| To convert the data into xml encoding. Which should be override in the derived class. More... | |
Protected Types | |
| enum | TYPE { TYPE_NUMBER, TYPE_STRING, TYPE_OBJECT, TYPE_DOUBLE, TYPE_BOOL, TYPE_NULL } |
| Type of encoder object. More... | |
A EncoderData class. It is a template class to maintain the data
|
protected |
|
inline |
Construct a new Encoder Data object.
| [in] | t | - type of the object |
|
inline |
To get the type of data.
|
pure virtual |
To convert the data into json encoding. Which should be override in the derived class.
Implemented in AKKU::Smart::EncoderObjectData, AKKU::Smart::EncoderNullData, AKKU::Smart::EncoderBoolData, AKKU::Smart::EncoderDoubleData, AKKU::Smart::EncoderStringData, and AKKU::Smart::EncoderNumData.
|
pure virtual |
To convert the data into xml encoding. Which should be override in the derived class.
Implemented in AKKU::Smart::EncoderObjectData, AKKU::Smart::EncoderNullData, AKKU::Smart::EncoderBoolData, AKKU::Smart::EncoderDoubleData, AKKU::Smart::EncoderStringData, and AKKU::Smart::EncoderNumData.


This extension uses the Pdfcrowd online service to create PDFs from web pages. If you want to change the default settings:
You can find more information about this extension at http://pdfcrowd.com/save-as-pdf-explained/.
Here is a screenshot of the available options:


Revised: 26 February 2003 (URL's updated)
Legislation, National/ International Standards, Codes of Practice, Guidelines
Overview: National/ International Standards, Codes of Practice and Legislation are maintained by the Owner, who ensures that appropriate hardcopy documents are available within the Company, and disposes of earlier versions as new documentation becomes available. External suppliers of documentation are contacted regularly to ascertain that the documents held remain current. Delta encourages all personnel to check for the latest on-line versions of these types of documents to avoid the possibility of using obsolete documents.
Government bodies may be contacted to determine the latest regulatory requirements at the following URL's:
Commonwealth
South Australia
Tasmania
Northern Territory
New South Wales
Victoria
Queensland
Western Australia
Local Government
Standards
Standards Australia (on-line Standards for downloading)
The table below contains the Bibliography of hardcopy Australian Standards, International Standards, Codes of Practice, Guidelines, Policies and Development Plans that are held in the Delta library. A CDROM of Standards (1000 drafts and assorted free copies) is available in the CDROM filing area.
| Document | Location |
| Policies | |
| Environment Protection (Burning) Policy 1994 | White legislation folders, office |
| Environment Protection (Industrial Noise) Policy 1994 | White legislation folders, office |
| Environment Protection (Machine Noise) Policy 1994 | White legislation folders, office |
| Environment Protection (Marine) Policy 1994 | White legislation folders, office |
| Environment Protection (Waste Management) Policy 1994 | White legislation folders, office |
| Environment Protection (Water Quality) Policy DISCUSSION PAPER | Bookcase, office |
| Environment Protection (Water Quality) Policy COMMENTS ON DISCUSSION PAPER | Bookcase, office |
| Technical Summary, SA Marine and Estuarine Strategy, March 1998 | Bookcase, office |
| Australia's Oceans Policy - An Issues Paper | Bookcase, office |
| Australia's Oceans Policy - Report of the Ministerial Advisory Group, March 1998 | Bookcase, office |
| Codes of Practice | |
| SA Health Commission Code "Waste Conrol Systems - Standard for the Construction, Installation and Operation of Septic Tank Systems in South Australia" | White legislation folders, office |
| Approved Code of Practice for Labelling of Workplace Substances | Bookcase, office |
| Draft Stormwater Code of Practice - Industry | Bookcase, office |
| Stormwater Code of Practice - Community | Bookcase, office |
| Guides and Information | |
| Guide to Occupational Health, Safety and Welfare Regulations, 1995 - including explanatory guidance and references to approved codes of practice | Bookcase, office |
| Hazardous Substances Information Pack | Bookcase, office |
| Picture Safety Symbols for the Workplace | Bookcase, office |
| Guide to the Assessment of Major Developments or Projects | Bookcase, office |
| Guide to Development Assessment | Bookcase, office |
| Mines and Energy SA Environment Information Series 4 - Site Planning for Mines and Quarries in SA | White legislation folders, office |
| Mines and Energy SA Environment Information Series 1- Petroleum Exploration in the South-east of SA: Clearance of Native Vegetation | White legislation folders, office |
| Mines and Energy SA Information Sheet E3 - Borrow Pits - Siting, Working and Rehabilitation | White legislation folders, office |
| Mines and Energy SA Information Sheet E4 - Aboriginal Heritage Act, 1988: Important Advice to all Explorers and Miners | White legislation folders, office |
| Mines and Energy SA Information Sheet E8 - Environmental Guidelines for Mineral Exploration Activities in SA | White legislation folders, office |
| Mines and Energy SA Information Sheet E9 - Statement of Environmental Objectives for Mineral Exploration in SA | White legislation folders, office |
| Draft Guidelines for the Preparation of a Declaration of Environmental Factors (DEF) for Mineral Exploration in SA | White legislation folders, office |
| Draft Liaison Guidelines for Landholders and Mineral Explorers in SA | White legislation folders, office |
| Guide to the SA Aboriginal Heritage Act 1988 | Bookcase, office |
| Giudelines for Licensing (Marine) EPA | White legislation folders, office |
| EPA Information Sheet 1 - A New Approach in SA to Environment Protection | White legislation folders, office |
| EPA Information Sheet 2 - Objects of the Environment Protection Act 1993 | White legislation folders, office |
| EPA Information Sheet 3 - How Your Company will Benefit From the Environment Protection Act | White legislation folders, office |
| EPA Information Sheet 4 - EPA Organisational Structure | White legislation folders, office |
| EPA Information Sheet 5 - Cleaner Industries Demonstration Scheme | White legislation folders, office |
| EPA Information Sheet 7 - Construction Noise | White legislation folders, office |
| EPA Information Sheet 8 - Assessment Procedure for Contaminated Land | White legislation folders, office |
| EPA Information Sheet 12 - Air Conditioner Noise | White legislation folders, office |
| What's What Fact Sheets (Wetlands and Murray-Darling Branch) | White legislation folders, office |
| Riparian Land Management Guide (EPA) | White legislation folders, office |
| Plans under the Development Act SDP = supplementary development plan PAR = plan amendment report |
|
| Metropolitan Open Space System SDP | Bookcase, office |
| City of Salisbury Rural, MOSS, Public Lands PAR | Bookcase, office |
| Statewide Marine Aquaculture and Offshore Development Draft PAR | Bookcase, office |
| Regional Coastal Areas Policies SDP | Bookcase, office |
| MOSS Little Para River SDP | Bookcase, office |
| City of Salisbury Development Plan Review | Bookcase, office |
| City of Salisbury St Kilda: Issues and Options | Bookcase, office |
| North-West Adelaide Strategic Plan | Bookcase, office |
| Planning Strategy, Metropolitan Adelaide, Jan 1998 | Bookcase, office |
| St Kilda Township Plan, May 1998 | Bookcase, office |
| Australian Standards | |
| AS 2093 1977 Salt for Use in the Manufacture of Dairy Goods | Bookcase, office |
| AS 2243.1 1997 Safety in Laboratories Part 1: General | Bookcase, office |
| AS 2243.2 1997 Safety in Laboratories Part 2: Chemical aspects | Bookcase, office |
| AS 2243.10 1993 Safety in Laboratories Part 10: Storage of chemicals | Bookcase, office |
| AS 2830.1 1985 Good Laboratory Practice Part 1: Chemical analysis | Bookcase, office |
| AS 2982 1987 Laboratory Construction | Bookcase, office |
| AS 4482.1 1997 Guide to the Sampling and Investigation of Potentially Contaminated Soil, Part 1: Non-volatile and Semi-volatile Compounds | Bookcase, office |
| AS 4479.1 1997 Analysis of Soil Part 1: Pretreatment of Potentially Contaminated Soil Samples for Heavy Metal and Metalloid Analysis | Bookcase, office |
| International Standards | |
| ISO 9004-2 1991 Quality Management and Qaulity System Elements Part 2: Guidelines for services | Bookcase, office |
| ISO 14001 1995 Environmental Management Systems - Specification with guidance for use | Bookcase, office |


CBC Results Analysis
The barchart below shows another representation of the results. It measures the distance between
the outlier and the center of the normal range (Chart on the right), and convert it into a percentage.
The two red dashed lines determine the noraml range.
Normal Range


Plane 1: $-x+y+z=2$
Plane 2: $-3x-2y+z=-4$
Which is the line in space defined by the parametric equations: $$x=\frac{3}{t}t,y=2-\frac{2}{5}t,z=t$$ You can rotate by swiping with your finger or dragging with the mouse. You can zoom by pinching the screen or using the mousewheel. Pressing 'm' will make the window toggle fullscreen mode. Note that the x-axis is green, the y-axis is red and the z-axis is blue.


IN THE HIGH COURT ore' KARNA'1*AI<;§.. ' *' CIRCUIT BENCH AT _DH.A1?§WA33""" W > DATED THIS THE 3rd DAY oFA.pE::;§é§13ERA.2t:§)3'I'-._ Barbie}; THE HON'BLE MR.JQ§r1 c:aE: _VN.A§i'AN_ﬁA V} CRIMINAL moo? BETWEEN. ~ " 1. M15.' Sh::tt_v___8a Sfens, rbpmsenfged 'Sri.~I?}"N. Satiashiv, Igaraaikong-«Bic~ck,<., % ' NEB Range,' «Hosp<:ut;TA--. ' 2<EMAIL_ADDRESS>Pértztcr, M13 P. BaI, a:mi3.ba Shctty 8:; Sons, « _ Karagiiﬁxzolia Block, " T HEB Raiige, Hosp-ct, «A - . V . . . Petitioners (ms. R.'.ﬁ.;t:ﬁiadha, Adv. for peﬁtioners) Kmﬁataka State Polluticm Comm)! Board, Represented by Qeputy Envimnment Oﬁcer, Regional Oﬂice, ' 'No.7, Ward No.1, K.f{.B. Coiony near S.P.Circ]§, Parvathinagar, Be1Iary----583 103. RESPONDEN'? (Ely Srideevan J. Nccralagi, Adv.) The criminal petition is ﬁlctd un('ier*_sei-'c11'o_1:'1 4.32 Qf Cr.P.C. praying to quash p1t)céeeEi11_gs' iziitiaiad No.246}/2006 in the Court of Prl. C§viI'Judge.5{Jr." Divisidn) 55JMFC at Hospet, and etc. ' ' . v ' The criminal peﬁﬁon. on for admission,- this day, the Court made fgliowingi' The stgte Board (for shaft KSPCB) Oﬁicer has ﬁled Cr.P.C3. and it is pending triai forV'Avi<;'>LatiVon "2'5' read with Section 43 of Water (Pmvgnﬂgn of Pollution) Act, 1974, in CC """'*:*his petition is ﬁled to quash tha injurama in C.c.No.246'.?; 2006. v'f'3L1r: petiﬁoner has raised several contentions. 11:3; péﬁﬁbner has contended that complainant has bum by KSPCB to withdraw the compiaint. The % .,.p-z-ititiomzr has challenged the locus standi of com jlainant. :1; («~ *4 petitiozxers have extracted iron 2 3 : 3. When the matter is taken up for hearing learned Counsel for petiﬁoner is absent. Sriﬁeevan Neeralgi;;Kdv. who had undertaken to tile Vakalath for zesponczeni; ﬁled Vakalath. 4. As could be seen "' complaint, the complaint was Environmental Gﬁicer, KSPCBV > letter from the Chairman of Vigmunds urged. the bcmfretency of respondent to
ﬁle the iebaiplainvjhi'
1. 5. LA the compiaint that pciitioners 1 .' V. !)'ein'g..'AManA:§."gé§vand Partner of M/s P. Baiasubba had been authorised to carry on mm' ing Of')§f3_Zf§':V1'ti0}§l.'3':f(::J_- 'exteact imn ore in the quantzity of 1.8 lakh ﬁtones 'iannum during the year 2001~2€)O5 with coneent of The pmduction detaﬂs obtained from the Separment of Mining and Geologr would reveal that am:
Amore than the permitted f/«'' The petiiioners have not ob'£ainefi'C:3q21isite qliantity.
pg, '*-""1 :4: cnvimnmental clearance certiﬁcate and thereby .'vi§}afe.t_1 section 25 read with section 43 of Water . Control ofPo11ut§on.} Act, 1974.
6. It is contended by péﬁtidaér thiﬁ State Pollution Contml Board to 'V Withdraw the complainanfi. itziﬁ ££1é"'dO£3HIﬂ€ﬁtS made available by v"_»:fd1z;p1aj11ant was authorised to tiéted 28.10.2006. Howevgn does not rciate to aumoﬁﬁﬁeﬁ In any event, this is a matter duxim trial. in these cﬁcliﬁgﬁtanms, find any grozlatxds to entertain {his ;.1¢1i!i_9n._ 'xﬁxcxtéiidjngy, petition is dismissed at that: stage of Sci!-
Iudgé Suh*


| SYSCTL(2) | Linux Programmer's Manual | SYSCTL(2) |
#include <unistd.h> #include <linux/sysctl.h>
int _sysctl(struct __sysctl_args *args);
The _sysctl() call reads and/or writes kernel parameters. For example, the hostname, or the maximum number of open files. The argument has the form
struct __sysctl_args { int *name; /* integer vector describing variable */ int nlen; /* length of this vector */ void *oldval; /* 0 or address where to store old value */ size_t *oldlenp; /* available room for old value, overwritten by actual size of old value */ void *newval; /* 0 or address of new value */ size_t newlen; /* size of new value */ };
This call does a search in a tree structure, possibly resembling a directory tree under /proc/sys, and if the requested item is found calls some appropriate routine to read or modify the value.
Note that on older kernels where this system call still exists, it is available only if the kernel was configured with the CONFIG_SYSCTL_SYSCALL option. Furthermore, glibc does not provide a wrapper for this system call, necessitating the use of syscall(2).
Not all available objects are properly documented.
It is not yet possible to change operating system by writing to /proc/sys/kernel/ostype.
#define _GNU_SOURCE #include <unistd.h> #include <sys/syscall.h> #include <string.h> #include <stdio.h> #include <stdlib.h> #include <linux/sysctl.h> int _sysctl(struct __sysctl_args *args ); #define OSNAMESZ 100 int main(void) { struct __sysctl_args args; char osname[OSNAMESZ]; size_t osnamelth; int name[] = { CTL_KERN, KERN_OSTYPE }; memset(&args, 0, sizeof(struct __sysctl_args)); args.name = name; args.nlen = sizeof(name)/sizeof(name[0]); args.oldval = osname; args.oldlenp = &osnamelth; osnamelth = sizeof(osname); if (syscall(SYS__sysctl, &args) == -1) { perror("_sysctl"); exit(EXIT_FAILURE); } printf("This machine is running %*s\n", osnamelth, osname); exit(EXIT_SUCCESS); }
| 2020-02-09 | Linux |


{% load staticfiles %}
Our company has grown by double it's size in the last year! That is only due to the hard work of all of its employees just like you. We thank you and all businessess that we have done business with in the past year.
Learn MoreOur company for the last several decades has always had both team building retreats and other get togethers. This year we have a family picnic with many team building exercises, contests and prizes. So please join us July, more details to follow.
Learn MoreThis year has been really challenging for all branches of Goliath, but all our work has paid of in full. We woud like to announce that we are having a company buy out that will nearly double us in size. We hope to be going further in the right direction in the future.
Learn MoreThe Modern Business template by Start Bootstrap includes:
Lorem ipsum dolor sit amet, consectetur adipisicing elit. Corporis, omnis doloremque non cum id reprehenderit, quisquam totam aspernatur tempora minima unde aliquid ea culpa sunt. Reiciendis quia dolorum ducimus unde.
Lorem ipsum dolor sit amet, consectetur adipisicing elit. Molestias, expedita, saepe, vero rerum deleniti beatae veniam harum neque nemo praesentium cum alias asperiores commodi.


Car sales area
Navbar
Home
(current)
Add car
Edit car
Signin
Registration
Creating a new advertisement
Brand
Select brand
Model
Model error
Body type
Body type error
Color
Color error
Year of issue
Age Error
Select picture to upload:


pricing table
small business
$75
Photoshop 5.5+ PSD File
Organized Layers and Folders
medium business
$125
Photoshop 5.5+ PSD File
Organized Layers and Folders
Vector Based Graphics
large business
$275
Photoshop 5.5+ PSD File
Organized Layers and Folders
Vector Based Graphics
Documentation
Free Fonts


Master Thesis, May 2021
Author: Juan Alonso
Supervisor: Cumhur Erkut
Sound and Music Computing, Aalborg University
Code available at https://github.com/juanalonso/ddsp_fm.
Mult
processorSine wave, 440Hz
LFO at 5Hz
LFO at 110Hz
LFO at 5Hz
LFO at 110Hz
Single control point
Multiple control points
Algorithm 1. All the ops in series.
Algorithm 4. Not present in Reface DX.
Algorithm 5. Three modulators in parallel.
Algorithm 6. Simple FM x 2.
Algorithm 8. Not present in Reface DX.
Algorithm 9.
Algorithm 10.
Algorithm 13. One modulator to three carriers.
Algorithm 14. Odd harmonics.
Dexed
Op5 and op6 disbled, flat envelopes.
DDSP-FM
Algorithm 6. Handpicked parameters.
Original
Timbre transfer
Original
Timbre transfer
Original
Timbre transfer
Operator 1
Operator 2
Operator 3
Reference
AE
AE quantized
VAE
VAE quantized
Reference
AE
AE quantized
VAE
VAE quantized
Original
Reconstruction
Original
Reconstruction
Original
Reconstruction


Fares
ADULTS
(Ages 13-64)
Good for 2 1/2 hours
Local Bus / METRO
Non-Rush hour
$2
Rush hour*
$2.50
Express Bus
Includes METRO / Local and Express buses
Non-Rush hour
$2.50
Rush hour*
$3.25
DOWNTOWN ZONE
All times, all riders, transfers not available.
Nicollet Mall
Free
Downtown Zone
50¢
All-Day Passes
Buy at ticket machines
Monday - Friday
Adults
$5
Reduced Fare
$5
Mobility
$2
Weekend
Adults
$4
Reduced Fare
$2
Mobility
$2
Northstar Commuter Rail one-way fares
MONDAY - FRIDAY
Adults and Reduced Fare $6.25
WEEKEND
Adults $5.50
ANYTIME
Mobility $2
MONDAY - FRIDAY
Adults and Reduced Fare $4.75
WEEKEND
Adults $4.25
ANYTIME
Mobility $1.50
MONDAY - FRIDAY
Adults and Reduced Fare $3.75
WEEKEND
Adults $3.75
ANYTIME
Mobility $1.25
MONDAY - FRIDAY
Adults and Reduced Fare $3.25
WEEKEND
Adults $3.25
ANYTIME
Mobility $1.25
MONDAY - FRIDAY
Adults and Reduced Fare $3.25
WEEKEND
Adults $3.25
ANYTIME
Mobility $1.25
MONDAY - FRIDAY
Adults and Reduced Fare $3.25
WEEKEND
Adults $2.75
ANYTIME
Mobility $1
MONDAY - FRIDAY
Adults and Reduced Fare $3.25
WEEKEND
Adults $2.75
ANYTIME
Mobility $1
* Children ages 5 and under ride free (limit 3) and must ride with a fare-paying customer. Families can save big on rides with the Northstar Family Pass.
Adults
Ages 13-64
Reduced Fare
Youth (ages 6-12) / Seniors (ages 65+) / Medicare card holders
Mobility
Persons with disabilities
- Seniors: For a reduced fare during non-rush hours, carry an ID with a "T" endorsement. To receive this endorsement, seniors age 65+ should complete a driver's license renewal form at any Driver & Vehicle Services office and request the "T" endorsement. OR request a Reduced Fare Go-To Card by mail and include a copy of your state-issued ID that shows your birth date.
- Youth ages 6-12: For a reduced fare during non-rush hours, inform the driver of your eligible age OR consider purchasing Go-To lite Cards for Students (K-12) or request a Reduced Fare Go-To Card by mail and be sure to include your 13th birth date.
- Medicare card holders: For a reduced fare during non-rush hours, carry your Medicare card along with a state-issued ID. OR request a Reduced Fare Go-To Card by mail and include a copy of your state-issued ID and Medicare card.
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On this page, we follow a cohort of Danish population born in 1987 and their journey through the educational system between the years 2006 when they reached adulthood and 2017 when only about a fifth of the studied group were still in education.
Education in Denmark, final project in the course Interactive data exploration for the web, University of Copenhagen, January 2018.
References:
Map of Denmark
Danmarks Administrative Geografiske Inddeling (DAGI)
Copied from: https://github.com/Neogeografen/dagi/tree/master/geojson
Educational data
Statistics Denmark, StatBank Denmark, Table HFUDD20. The table contains data of the Danish populations enrolled and fulfilled educations, age, gender, and place of residence.
Avatars and icons
Made by: Juraj Orszag, Frederik Bøgelund Larsen and Kamma Westergaard
Use the reset button to return to the whole danish population
This part illustrates how the cohort of young people born in 1987 over time graduate educations. The plot follows the same cohort over time. Chances in the total population number corresponds to either net immigration or net emmigration og the area selected.
The top level "not stated" is primarily immigrants, that has not graduated a Danish educational institution yet. When they do, they will be placed in the other categories.
There are big differences in the education and migration patterns between regions. Especially for the high educacional levels. Region Hovedstaden has a large population of people with masters degrees compared to any other region.
This visualisation shows the relative number of Danish residents born in 1987 attending each of the educational levels recognised in Denmark, from Primary Education to PhD programmes, in a stacked area plot.
There is also a special category formed by the individuals who are no longer in education.
On the right-hand side, next to the chart, a number of selectors can be found. These can be used to interact with the chart and display more specific subsets of the data. First, the map can be used to select a particular region in Denmark. By clicking the avatars below, it is possible to show data for women or men, respectively. Finally, pressing the 'cross' icon resets the visualisation.
A few interesting observations can be made in this plot. As one could expect, the number of people in education drops significantly between 18 and 29 years of age. However, we see that the number drops sharply between the ages of 18 and 20 but then a large portion of the population gets to higher education.
A few interesting observations can be made in this plot. As one could expect, the number of people in education drops significantly between 18 and 29 years of age. However, we see that the number drops sharply between the ages of 18 and 20 but then a large portion of the population gets to higher education.
Coming to university education, we can see that there is a large difference in the number of females and males attending universities. Women outnumber men both in general and in each individual region.
Coming to university education, we can see that there is a large difference in the number of females and males attending universities. Women outnumber men both in general and in each individual region.
Comparing university education in different regions provides some interesting insight, too. We can clearly see that the portion of the population attending higher education is largest in the neighbourhood of Denmark's capital. On the other end of the rank, we would find the Zealand Region (Region Sjælland).


Lyle lifts New Mexico past New Mexico St. 78-77
by The Associated PressLAS CRUCES, N.M. (AP) — JaQuan Lyle scored 24 points, Carlton Bragg made two free throws with 43.9 seconds, and New Mexico held on to beat New Mexico State 78-77 on Thursday night.
Lyle made 9 of 14 from the field and Bragg finished with 14 points on 5-of-6 shooting and four steals. JJ Caldwell added nine points — all in the second half — and seven assists for the Lobos (5-1).
Trevelin Queen scored six points during a 12-4 run that gave New Mexico State a 75-73 lead with 2:22 left in the game when he capped the spurt with two free throws. Corey Manigualt answered with a dunk 13 seconds later and, after the Aggies missed a 3-point shot, Caldwell converted a three-point play to give New Mexico a one-point lead with 90 seconds to go. Terrell Brown made a driving layup before Bragg’s foul shots put the Lobos in front for good.
The teams combined for four turnovers over the next 35 seconds before New Mexico State’s Jabari Rice missed a clean look for 3 from the left corner. The Aggies fouled and Caldwell missed the front end of a 1-and-1 before Shunn Buchanan missed a potential winner at the buzzer.
Queen had 23 points and nine rebounds for the Aggies (2-3). Rice added 13 points and Ivan Aurrecoechea scored 12.
New Mexico takes on Auburn on Monday. New Mexico State matches up against Colorado State on Monday.
___
For more AP college basketball coverage: https://apnews.com/Collegebasketball and http://twitter.com/AP_Top25
___
Elements of this story were generated by Automated Insights, http://www.automatedinsights.com/ap, using data from STATS LLC, https://www.stats.com
The Associated Press


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Forrest Senti
Unafffiliated
Director of Business and Government Initiatives
BS in Business Administration, Minor in Entrepreneurism at University of Colorado - Colorado Springs. Certificate in Ethical Leadership - Center for Public Trust
80907
In my current role for the National Cybersecurity I work with creating review and pilot opportunities for new election technology for overseas and disabled voters. In addition I work on providing legislators with cyber resources and training as well as general policy advise. I do something similar for El Paso County and Pikes Peak United Way, but focused towards their mission.
I volunteered for the 2018 Phil Weiser for AG Campaign and participated in the Colorado Democratic Convention in 2018 as well as a candidate. In Spring of 2018 I switched to be an unaffiliated voter.
El Paso county Innovation and Technology Committee, Pikes Peak United Way Public Policy Council CO-chair, Colorado Springs Rising Professionals, Colorado Institute for Social Impact Instructor, Colorado Springs Chamber and EDC Government Affairs Council, Exponential Impact Volunteer
I believe that independent redistricting is the #1 way we can create a fair and balanced political system in the United States. The Redistricting commission is an important example of what it can mean to actually be bi/non partisan in deciding the best place to draw district lines based on a significant base of factors.
My single greatest individual skill is the ability to be pragmatic. My #1 goal is not to push or advocate my angle to others but to instead seek to understand, come to consensus and grow unity between members and colleagues. I am excellent at trying to see things from other people's points of view and I'm good at working backwards to a shared place of understanding, because of this I handle conflict very well.
I have written, presented and published on several complex policy issues involving technical and non technical subjects. My big value when I do this type of work is my ability to break down problems to its core and identify ways to apply logic and reason in a simple way to create shared understanding. Long story short, I understand the problem and find a simple reason to fix it.
Male


Stephanie Almeida, Anna Munns, and Leo Ricci
The US presidential election is incredibly important since our country is arguably the most influential in the world. It not only directly influences our domestic economic market and over 300 million citizens, but also the global market and consequently the entire world. Understanding complex factors that affect a presidential election are extremely important, particularly this year as it is an election year.
Something interesting to note is that few studies look at how a variety of features influence the election on a state level. We plan to investigate features such as demographics, government data, and economic data to see what features help to predict the outcome of an election. Additionally, the results for most studies are binary, whether one candidate will win the election. We plan to look at the ratio between votes for the democratic party versus votes for the republican party.
Current forecasting methods typically used are financial prediction markets and pre-polling which have shown to be quite accurate, one article citing it at 1.5% and 2.1% error respectively days before the 2008 election. However, the limitations of this are the national popular vote in U.S. presidential elections tend to oscillate wildly in the months before the election takes place, so we intend to not use polling and prediction market methods in favor of more objective data points. We believe this combined with machine learning techniques will allow us to find more complex trends that would be hard to notice via more classical methods.
Data Combination/CleaningWhen collecting our data in a Google Sheets Document for easy sharing and access, we wanted to consider features from reliable data sources that were most likely to have an effect on political data. We focused on three different categories of data: demographic, economic, and political data. The demographic data, extracted from the census, highlights sex, race, age (in ranges), and hispanic descent. Economic data, including GDP, personal consumption expenditure, and personal income are sourced from the bureau of economic analysis. Lastly, presidential approval rating from Gallup polls and data on congressional seats completed the last component of our feature set: political data.
Due to the inability to meet in person, we decided that entering all of our data into a Google Sheet would be the best way to combine all of our features. We had 100 rows, one for each state in the years 2012 and 2016, and 26 columns. Many of our values within features were very large, so we normalized the features between 0 and 1. The Google Sheet was then exported as a csv file so that we were able to use machine learning libraries and parse data using Python with ease.
Unsupervised Learning Portion:When we created the correlation matrix of our dataset, we saw just how many of our features were strongly correlated with others. Because of this, we realized we could distill our dataset down to a small number of features and still be able to create accurate clusters, perhaps even more accurate clusters than what could be made with the original dataset. To do this, we relied on the PCA algorithm. The PCA algorithm takes in a dataset and creates a new set of orthogonal features, each a linear transformation of the original features, and orders the features by the variance they contribute to the total variance of the dataset. We used the PCA class of the scikit-learn python library to run PCA on our dataset, and then plotted the explained variance ratio of each new feature.
As you can see in the graphs, the vast majority of the variance in the dataset is contained by only a handful of the variables. We decided to limit our dataset to the top 5 generated features, as they contained nearly 95% of the variance of the dataset.
We compared our KMeans results with 2 clusters to the true results of the 2012 and 2016 election in order to calculate a misclassification rate.
Supervised Learning PortionWe originally intended to design three neural networks. The first neural network would be a multi layered perceptron binary classifier created using the MLPClassifier class of the scikit-learn python library. The next two neural networks would be multi layered peceptron regressors, one for percentage of GOP voters by state and the other for the percentage of DNC voters by state. These two neural networks would be built with the MLPRegressor class of the scikit-learn python library.
We decided to use the support vector machine algorithm to validate the output from the neural network analysis. In order to do so, we settled on a linear binary classifier because we wanted to see how the results compared (binary versus proportion of DNC to GOP votes).
In addition to the Neural Network and SVM algorithms, we decided to implement a Random Forest Classifier. This classifier would predeict whether a state would vote for the democratic or republican candidate in a general election. We chose to use Random Forest because it is an extremely popular algorithm for classification style problems, and we hoped it would work well in our project for classifying states. We used the Random Forest Classifier from the scikit-learn library, and focused on tuning hyperparameters to optimize the model.
The specific problem that we are going to solve is predicting the ratio of Republican to Democratic popular vote by state. Our approach is unique as we intend to use machine learning algorithms, not regression or other traditionally linear tactics and data that is demographic, economic, or descriptive of state politics. We anticipate success based on two factors: past works and our intention to increase the level of granularity within our features. Past projects that focus on predicting political outcomes such as “Fundamental Models for Forecasting Elections” by Hummel and Rothschild and “Predicting U.S. president election result based on Google Insights” by Stanford students utilize features that are common to those that we want to incorporate and validate our belief that predictions can be made accurately on a state level.
K-Means (with PCA): 74% (2012) and 84% (2016) 2012 Accuracy: 74%
Training: 2012 Presidential Election, 2016 Presidential Election
Testing: 2020 Presidential Election
Random Guess Accuracy Probability: 50%
Neural Networks: Multi-Layer Perceptron Binary Classifier Included is our classification report:
Neural Networks: Multi-Layer Perceptron Regressor We built two additional neural networks: a regressor that predicts the percentage of GOP votes by state and a regressor that predicts the percentage of DNC votes by state. After attempting to optimize hyperparameters and build these two networks, we found that loss and accuracy was very volatile along with R squared values that were low or infeasible. We attribute this to the atypical election year of 2020. With record voter turnout and unusual voting patterns observed due to COVID-19, 2012 and 2016 are difficult datasets to train our network on to predict party voting percentages for 2020 due to a lack of consistency in patterns. We feel that the addition of past election years would greatly increase the usefulness of our Multi-Layer Perceptron Regressor models and result in an presentable output.
SVM: 78% Included is our classification report:
Random Forest: Random Forest is an ensemble-style classifier in which a "forest" of decision trees are generated from random subsets of the training data. We first create a random forest classifier using the default scikit-learn parameters and compared the accuracy of the model to our other algorithms.
Default Parameters and Results:
Once we had established a baseline from where we wanted to improve this model, we turned to hyperparameter tuning. The first step of this process was determining which hyperparameters we should focus on adjusting. Using scikit-learn's Random Forest Classifier documentation and research of other publicly available projects using Random Forest we chose six hyperparameters to tune.
Chosen Parameters:
We then used the Randomized Search Cross Validation and Grid Search Cross Validation libraries from scikit-learn to select optimal values for these hyperparameters, and ended with these values:
We then fit a new Random Forest Classifier model using these hyperparameters, and tested against the original model using the 2020 election results.
Original Model
Optimized Model
As you can see, our model's accuracy improved from 76% with the original, default hyperparameters, to 82% with the optimized hyperparameters found using Randomized Search Cross Validation and Grid Search Cross Validation. With these optimizations, the Random Forest Classifier surpassed SVM and our Neural Networks to be the most accurate supervised learning model we developed. However, this does not mean that the model was without flaws. Similar to the Neural Network, our Random Forest model tended to prefer classifying states as voting Republication rather than Democrat, which was reflected in the high precision and low recall for blue states (labeled with a 0) and low precision but high recall for red states (labeled with a 1).
One minor risk is we believe that election predictions can affect voting behavior, but overall we do not think that there are significant risks associated with this project.
Our project has two main important contributions. By using unsupervised learning, we will be able to determine which features have either a direct or indirect influence on each state's vote. This way, future polls could implement this information in order to be more accurate. By using supervised learning, we will hopefully build a more accurate model which would be used to predict future elections.
Based off of our principal component analysis, we were able to greatly reduce the amount of features when it came to K-Means clustering. In the graphic above, we see a great difference between the accuracy of the two election years (2012 and 2016). This could be due to a number of factors including (but not limited to), population/immigraiton change, political makeup, and presidential approval rating.
While our algorithms vary in their accuracy scores, our group was overall unsurprised by the relatively low accuracy of models. This can be attributed to two main reasons, the first of which is that the feature data for states for 2020 have not been processed yet, and thus, is not readily available for public use. Our group needed to either use data from 2019 or approximate data from past years. The second reason is that this year is highly unlike past election years mainly due to the global pandemic (COVID-19) and record voter turnout. Condiering these factors, it is unsurprising that our algorithms have relatively low accuracy.
If we were to expand upon this model, we would recommend a classifier over a regressor for supervised learning techniques. Using a classifier, our lowest accuracy was 78%. We suggest that the best model, of those that we used, for predicting election outcomes was the Random Forest classifier. Not only did the Random Forest classifier result in the most accurate testing results, but this model has the highest precision, recall, and f1-score values. We felt that the neural network, on our small dataset, overcomplicated the model and led to overfitting, while our SVM model simply did not achieve the same success that our Random Forest Classifier was able to. A major improvement we would make to our model is increasing its robustness. This would be done by gathering more training data. The primary reason why we were only able to include 2012 and 2016 election years was due to the financial roadblock of obtaining access to large, validated databases. If this project was completed in a research lab or another entity with financial backing, achieving a more robust model would be less of a challenge. Additionally, we would want to incorporate a way to capture the political pulse of a state on a more frequent basis. With election years occuring every four years, there is a long period of time between training datasets when the political makeup of a state can shift dramatically. As this was all of our first times implementing machine learning algorithms to solve real world problems, we were able to learn an incredible amount as we went through the project. All of our machine learning attempts resulted in an accuracy that is greater than if one were to randomly assign states as Democrat or Republican (50%). We are very grateful to the teaching staff for their constant advice and support through this process and look forward to tackling more problems with machine learning in the future!
Budiman, Abby, and Ruth Igielnik. “The Changing Racial and Ethnic Composition of the U.S. Electorate.” Pew Research Center, Pew Research Center, 25 Sept. 2020, www.pewresearch.org/2020/09/23/the-changing-racial-and-ethnic-composition-of-the-u-s-electorate/.
Bureau, US Census. “State Population by Characteristics: 2010-2019.” The United States Census Bureau, 22 June 2020, www.census.gov/data/datasets/time-series/demo/popest/2010s-state-detail.html.
Chen, Yunzhu, et al. “Predicting U.S. President Election Result Based on Google Insights.” Stanford CS 229, 14 Dec. 2014, cs229.stanford.edu/proj2012/ChenZhangYue-PredictingUSPresidentElectionResultBasedOnGoogleInsights.pdf.
“Data.” Data | MIT Election Lab, 29 May 2019, electionlab.mit.edu/data.
Hummel, Patrick, and David Rothschild. “Fundamental Models for Forecasting Elections at the State Level.” Electoral Studies, Pergamon, 4 June 2014, www.sciencedirect.com/science/article/pii/S0261379414000602.
“United States: U.S. Bureau of Economic Analysis (BEA).” United States | U.S. Bureau of Economic Analysis (BEA), www.bea.gov/data/by-place-us.


About Laith
- Education: I hold a BA in Finance and Banking from the University of Jordan, 2015
- Education: Full stack software development bootcamp at LTUC ASAC, current
- Experience: Quantative and Qualtative market research
- Experience: Mergers and Acquistions, financial advisory in Hamburg, Germany
My name is Laith Sarraf! Born in 1991 and I've been living in Jordan ever since, I hold a BA in Finance & Banking. I hold experience in M&A finance and Quan/Qual market research
My family orginally comes from Gaza city, Palestine.
I have a passion for the sport of boxing, i started developing this interest at an older age of 25, I practice boxing occaiosonally but I watch a lot of fights from the current and previous eras
I loved cars ever since i was a very young kid, specifically sports cars! I'm a huge porsche fan and my favorite model is the Carrera GT
I have a passion for tech start-ups and entrepreneurship as i find facsinating how people take huge risks and start their businesses
- Mike Tyson
- Muhammed Ali
- Manny Pacquaio
- Canelo Alvarez
- Evander Holyfield
- Vasyl Lomachenko
- Sonny Liston
- Joe Fraizer
- Vladimir Klitschko
- George Foreman


Nathan Deanda
Unafffiliated
KL&A Engineers & Builders in Golden, CO.
Master's degree in structural engineering from the University of Colorado in Boulder (2020) Bachelor's degree in civil engineering from Colorado State University in Fort Collins (2018)
80031
As a general contractor, it was important to maintain a positive relationship with all of the trade partners working on site to keep them coordinated and functional. As a project engineer with Martines Palmeiro Construction (MPC) I had to advocate for both the organizations who worked under mine and our clients in the day-to-day tasks in the field. Often times a trade partner would interfere with another trade partner’s work for their own convenience. I had to ensure that the best interests of all the trades were executed in order maintain a functional site. Furthermore, it was also my responsibility to ensure that the best interests of the owner were being executed despite the fact that the owner was not present on site. Nearly all of the trade partners I worked with are based in Colorado, as many of them are small businesses in the Denver area.
In the past five years, I have been interested but not heavily involved in political activities outside of voting. I have not given money to any organizations other than the perchance a Marco Rubio bumper sticker in 2016. At the end of 2019 I also signed a petition in Colorado that put Proposition 115 on the 2020 ballot and made a $5 donation supporting the initiative Although I grew up in a mostly conservative household, I am an independent thinker who may align with the Libertarian party rather than the Democratic or Republican party. I even voted Libertarian in 2016 because I felt that both of the two major candidates were not representative of how most people in America think. But because I do not want to subject myself a political party, I am an unaffiliated citizen and have chosen to apply for this commission as such.
I spent the majority of the past five years since November 10, 2015 as a student at both Colorado State University (CSU) in Fort Collins and University of Colorado (CU) in Boulder. Because of this most of my public involvement was within my university community. At CSU I served as student ambassador for the College of Engineering, which I belonged to. As an ambassador I worked primarily with high school students considering majoring in engineering, at CSU or otherwise. I gave advice to these students as they made their college decisions and offered my perspective to them as both an engineering student and as a CSU Ram. At the end of my undergraduate education at CSU, I joined a professional origination known as the Order of the Engineer. This is an organization that upholds the ethical standards of engineers in our society. As many people entrust their lives with the structures and technology designed by engineers, this organization continuously reminds them of the responsibly they hold. In graduate school at CU, I earned a scholarship from the Structural Engineers Association of Colorado (SEAC) and have attended a number of meetings and site visits with the organization since. Although I am not an official SEAC member, I am currently considering joining this organization as well.
I would like to serve on the commission because I want to ensure that the representative district boarders are drawn fairly without the effects of gerrymandering. As an unaffiliated voter, generally displeased with the two party system, I am interested in making sure the Colorado State representatives in congress are elected fairly and competitively. Colorado unfortunately has a history of gerrymandering in order to give one political party more power over another. Districting commissions often also re-draw districting lines in order to protect their own seat (or the incumbent member of their party) in office. These tactics need to stop in order for the voice of the people of Colorado to truly be heard. If the districts are organized such that the representative earns the votes of their constituents. This is very important to me as a Colorado voter because not only to I want my voice to be heard, but I want to ensure the same for my fellow Coloradans. Especially if Colorado is to obtain an eighth seat in the House of Representatives. The great President John F. Kennedy said, “Let us not seek the Republican answer of the Democratic answer, but the right answer. Let us not seek to fix the blame for the past. Let us accept our own responsibility for the future.” My primary goal as a member of this commission will be to seek that right answer. I love this state, and I believe that the governmental tactics and changes taking place here in Colorado have been and continue to be a model for the nation. That is why I am interested in serving on the commission, not only to serve my state but to serve my country.
As a member of the commission, I will advocate for the use of the shortest-split line method to divide the voters throughout the state into fairly divided, equally populated areas. The use of this algorithm is at least a good place to start, because it uses a mathematical method that is free of bias. I would also use that as an argument among the other commissioners, because you can’t argue with math. As an engineer, I am good at both being analytical and convincing of an impartial answer. Next, I think it’s worth considering the cultural density of the various areas of the state. For example, because Baca County and Prowers County are culturally similar to each other, it may make sense to group them together in the same district. However, it is important to make sure there is a healthy amount of competition for the candidates running to represent these districts. For example if it is known that the majority of voters in Weld County are Republicans and the majority of voters in Larimer County are Democrats, it may make sense to group Weld and Larimer County together in the same district to encourage both the Republican and Democratic candidates for that district to campaign harder to earn their votes.
Being a structural engineer, logic and reason come very naturally to me. I am a fast learner and an analytical thinker. I am exceptionally good at Excel and I enjoy solving mathematically interesting problems. I am also a young and enthusiastic individual who likes a good challenge. When I was a graduate student at CU, I had to apply these skills to my research project in order to report accurate and unbiased results. For this project, I was tasked investigating the effects of a polymer additive on the freeze-thaw properties of concrete. To do this, I had to college and analyze a significant amount of data over the course of several months. I also had to write and defend my thesis in front of several faculty members and concrete experts to prove my results were valic. I would take a similar approach to the task of re-districting Colorado. My “data collection” phase would involve hearing the voices of my fellow Coloradans scattered throughout the state. My “analysis” phase would be the actual re-drawing of the district lines with the assistance of the other commissioners. And finally my “defense” phase would be to convince and mediate among the other members of the committee.
Male


public abstract class IIOMetadata extends Object
IIOMetadataNode
objects that
support the XML DOM interfaces as well as additional interfaces for
storing non-textual data and retrieving information about legal
data values. The format of such trees is plug-in dependent, but
plug-ins may choose to support a plug-in neutral format described
below. A single plug-in may support multiple metadata formats,
whose names maybe determined by calling
getMetadataFormatNames
. The plug-in may also support
a single special format, referred to as the "native" format, which
is designed to encode its metadata losslessly. This format will
typically be designed specifically to work with a specific file
format, so that images may be loaded and saved in the same format
with no loss of metadata, but may be less useful for transfering
metadata between an ImageReader
and an
ImageWriter
for different image formats. To convert
between two native formats as losslessly as the image file formats
will allow, an ImageTranscoder
object must be used.ImageReader.getImageMetadata(int)
,
ImageReader.getStreamMetadata()
,
ImageReader.readAll(int, javax.imageio.ImageReadParam)
,
ImageWriter.getDefaultStreamMetadata(javax.imageio.ImageWriteParam)
,
ImageWriter.getDefaultImageMetadata(javax.imageio.ImageTypeSpecifier, javax.imageio.ImageWriteParam)
,
ImageWriter.write(javax.imageio.metadata.IIOMetadata, javax.imageio.IIOImage, javax.imageio.ImageWriteParam)
,
ImageWriter.convertImageMetadata(javax.imageio.metadata.IIOMetadata, javax.imageio.ImageTypeSpecifier, javax.imageio.ImageWriteParam)
,
ImageWriter.convertStreamMetadata(javax.imageio.metadata.IIOMetadata, javax.imageio.ImageWriteParam)
,
IIOImage
,
ImageTranscoder
| Modifier and Type | Field and Description |
|---|---|
protected IIOMetadataController |
controller
The
IIOMetadataController that will be
used to provide settings for this IIOMetadata
object when the activateController method
is called. |
protected IIOMetadataController |
defaultController
An
IIOMetadataController that is suggested for use
as the controller for this IIOMetadata object. |
protected String[] |
extraMetadataFormatClassNames
An array of names of classes implementing
IIOMetadataFormat
and representing the metadata formats, other than the standard and
native formats, that are supported by this plug-in,
initialized to null and set via the constructor. |
protected String[] |
extraMetadataFormatNames
An array of names of formats, other than the standard and
native formats, that are supported by this plug-in,
initialized to
null and set via the constructor. |
protected String |
nativeMetadataFormatClassName
The name of the class implementing
IIOMetadataFormat
and representing the native metadata format, initialized to
null and set via the constructor. |
protected String |
nativeMetadataFormatName
The name of the native metadata format for this object,
initialized to
null and set via the constructor. |
protected boolean |
standardFormatSupported
A boolean indicating whether the concrete subclass supports the
standard metadata format, set via the constructor.
|
| Modifier | Constructor and Description |
|---|---|
protected |
IIOMetadata()
Constructs an empty
IIOMetadata object. |
protected |
IIOMetadata(boolean standardMetadataFormatSupported,
String nativeMetadataFormatName,
String nativeMetadataFormatClassName,
String[] extraMetadataFormatNames,
String[] extraMetadataFormatClassNames)
Constructs an
IIOMetadata object with the given
format names and format class names, as well as a boolean
indicating whether the standard format is supported. |
| Modifier and Type | Method and Description |
|---|---|
boolean |
activateController()
Activates the installed
IIOMetadataController for
this IIOMetadata object and returns the resulting
value. |
abstract Node |
getAsTree(String formatName)
Returns an XML DOM
Node object that represents the
root of a tree of metadata contained within this object
according to the conventions defined by a given metadata
format. |
IIOMetadataController |
getController()
Returns whatever
IIOMetadataController is currently
installed. |
IIOMetadataController |
getDefaultController()
Returns the default
IIOMetadataController , if there
is one, regardless of the currently installed controller. |
String[] |
getExtraMetadataFormatNames()
Returns an array of
String s containing the names
of additional metadata formats, other than the native and standard
formats, recognized by this plug-in's
getAsTree , setFromTree , and
mergeTree methods. |
IIOMetadataFormat |
getMetadataFormat(String formatName)
Returns an
IIOMetadataFormat object describing the
given metadata format, or null if no description
is available. |
String[] |
getMetadataFormatNames()
Returns an array of
String s containing the names
of all metadata formats, including the native and standard
formats, recognized by this plug-in's getAsTree ,
setFromTree , and mergeTree methods. |
String |
getNativeMetadataFormatName()
Returns the name of the "native" metadata format for this
plug-in, which typically allows for lossless encoding and
transmission of the metadata stored in the format handled by
this plug-in.
|
protected IIOMetadataNode |
getStandardChromaNode()
Returns an
IIOMetadataNode representing the chroma
information of the standard javax_imageio_1.0
metadata format, or null if no such information is
available. |
protected IIOMetadataNode |
getStandardCompressionNode()
Returns an
IIOMetadataNode representing the
compression information of the standard
javax_imageio_1.0 metadata format, or
null if no such information is available. |
protected IIOMetadataNode |
getStandardDataNode()
Returns an
IIOMetadataNode representing the data
format information of the standard
javax_imageio_1.0 metadata format, or
null if no such information is available. |
protected IIOMetadataNode |
getStandardDimensionNode()
Returns an
IIOMetadataNode representing the
dimension information of the standard
javax_imageio_1.0 metadata format, or
null if no such information is available. |
protected IIOMetadataNode |
getStandardDocumentNode()
Returns an
IIOMetadataNode representing the document
information of the standard javax_imageio_1.0
metadata format, or null if no such information is
available. |
protected IIOMetadataNode |
getStandardTextNode()
Returns an
IIOMetadataNode representing the textual
information of the standard javax_imageio_1.0
metadata format, or null if no such information is
available. |
protected IIOMetadataNode |
getStandardTileNode()
Returns an
IIOMetadataNode representing the tiling
information of the standard javax_imageio_1.0
metadata format, or null if no such information is
available. |
protected IIOMetadataNode |
getStandardTransparencyNode()
Returns an
IIOMetadataNode representing the
transparency information of the standard
javax_imageio_1.0 metadata format, or
null if no such information is available. |
protected IIOMetadataNode |
getStandardTree()
A utility method to return a tree of
IIOMetadataNode s representing the metadata
contained within this object according to the conventions of
the standard javax_imageio_1.0 metadata format. |
boolean |
hasController()
Returns
true if there is a controller installed
for this IIOMetadata object. |
abstract boolean |
isReadOnly()
Returns
true if this object does not support the
mergeTree , setFromTree , and
reset methods. |
boolean |
isStandardMetadataFormatSupported()
Returns
true if the standard metadata format is
supported by getMetadataFormat ,
getAsTree , setFromTree , and
mergeTree . |
abstract void |
mergeTree(String formatName,
Node root)
Alters the internal state of this
IIOMetadata
object from a tree of XML DOM Node s whose syntax
is defined by the given metadata format. |
abstract void |
reset()
Resets all the data stored in this object to default values,
usually to the state this object was in immediately after
construction, though the precise semantics are plug-in specific.
|
void |
setController(IIOMetadataController controller)
Sets the
IIOMetadataController to be used
to provide settings for this IIOMetadata
object when the activateController method
is called, overriding any default controller. |
void |
setFromTree(String formatName,
Node root)
Sets the internal state of this
IIOMetadata object
from a tree of XML DOM Node s whose syntax is
defined by the given metadata format. |
protected boolean standardFormatSupported
protected String nativeMetadataFormatName
null
and set via the constructor.protected String nativeMetadataFormatClassName
IIOMetadataFormat
and representing the native metadata format, initialized to
null
and set via the constructor.protected String[] extraMetadataFormatNames
null
and set via the constructor.protected String[] extraMetadataFormatClassNames
IIOMetadataFormat
and representing the metadata formats, other than the standard and
native formats, that are supported by this plug-in,
initialized to null
and set via the constructor.protected IIOMetadataController defaultController
IIOMetadataController
that is suggested for use
as the controller for this IIOMetadata
object. It
may be retrieved via getDefaultController
. To
install the default controller, call
setController(getDefaultController())
. This
instance variable should be set by subclasses that choose to
provide their own default controller, usually a GUI, for
setting parameters.IIOMetadataController
,
getDefaultController()
protected IIOMetadataController controller
IIOMetadataController
that will be
used to provide settings for this IIOMetadata
object when the activateController
method
is called. This value overrides any default controller,
even when null
.protected IIOMetadata()
IIOMetadata
object. The
subclass is responsible for suppying values for all protected
instance variables that will allow any non-overridden default
implemtations of methods to satisfy their contracts. For example,
extraMetadataFormatNames
should not have length 0.protected IIOMetadata(boolean standardMetadataFormatSupported, String nativeMetadataFormatName, String nativeMetadataFormatClassName, String[] extraMetadataFormatNames, String[] extraMetadataFormatClassNames)
IIOMetadata
object with the given
format names and format class names, as well as a boolean
indicating whether the standard format is supported.
This constructor does not attempt to check the class names
for validity. Invalid class names may cause exceptions in
subsequent calls to getMetadataFormat
.
standardMetadataFormatSupported
- true
if
this object can return or accept a DOM tree using the standard
metadata format.nativeMetadataFormatName
- the name of the native metadata
format, as a String
, or null
if there
is no native format.nativeMetadataFormatClassName
- the name of the class of
the native metadata format, or null
if there is
no native format.extraMetadataFormatNames
- an array of String
s
indicating additional formats supported by this object, or
null
if there are none.extraMetadataFormatClassNames
- an array of String
s
indicating the class names of any additional formats supported by
this object, or null
if there are none.IllegalArgumentException
- if
extraMetadataFormatNames
has length 0.IllegalArgumentException
- if
extraMetadataFormatNames
and
extraMetadataFormatClassNames
are neither both
null
, nor of the same length.public boolean isStandardMetadataFormatSupported()
true
if the standard metadata format is
supported by getMetadataFormat
,
getAsTree
, setFromTree
, and
mergeTree
.
The default implementation returns the value of the
standardFormatSupported
instance variable.
true
if the standard metadata format
is supported.getAsTree(java.lang.String)
,
setFromTree(java.lang.String, org.w3c.dom.Node)
,
mergeTree(java.lang.String, org.w3c.dom.Node)
,
getMetadataFormat(java.lang.String)
public abstract boolean isReadOnly()
true
if this object does not support the
mergeTree
, setFromTree
, and
reset
methods.IIOMetadata
object cannot be
modified.public String getNativeMetadataFormatName()
null
will be returned.
The structure and contents of the "native" metadata format
are defined by the plug-in that created this
IIOMetadata
object. Plug-ins for simple formats
will usually create a dummy node for the root, and then a
series of child nodes representing individual tags, chunks, or
keyword/value pairs. A plug-in may choose whether or not to
document its native format.
The default implementation returns the value of the
nativeMetadataFormatName
instance variable.
null
.getExtraMetadataFormatNames()
,
getMetadataFormatNames()
public String[] getExtraMetadataFormatNames()
String
s containing the names
of additional metadata formats, other than the native and standard
formats, recognized by this plug-in's
getAsTree
, setFromTree
, and
mergeTree
methods. If there are no such additional
formats, null
is returned.
The default implementation returns a clone of the
extraMetadataFormatNames
instance variable.
String
s with length at least
1, or null
.getAsTree(java.lang.String)
,
setFromTree(java.lang.String, org.w3c.dom.Node)
,
mergeTree(java.lang.String, org.w3c.dom.Node)
,
getNativeMetadataFormatName()
,
getMetadataFormatNames()
public String[] getMetadataFormatNames()
String
s containing the names
of all metadata formats, including the native and standard
formats, recognized by this plug-in's getAsTree
,
setFromTree
, and mergeTree
methods.
If there are no such formats, null
is returned.
The default implementation calls
getNativeMetadataFormatName
,
isStandardMetadataFormatSupported
, and
getExtraMetadataFormatNames
and returns the
combined results.
String
s.getNativeMetadataFormatName()
,
isStandardMetadataFormatSupported()
,
getExtraMetadataFormatNames()
public IIOMetadataFormat getMetadataFormat(String formatName)
IIOMetadataFormat
object describing the
given metadata format, or null
if no description
is available. The supplied name must be one of those returned
by getMetadataFormatNames
(i.e., either the
native format name, the standard format name, or one of those
returned by getExtraMetadataFormatNames
).
The default implementation checks the name against the
global standard metadata format name, and returns that format
if it is supported. Otherwise, it checks against the native
format names followed by any additional format names. If a
match is found, it retrieves the name of the
IIOMetadataFormat
class from
nativeMetadataFormatClassName
or
extraMetadataFormatClassNames
as appropriate, and
constructs an instance of that class using its
getInstance
method.
formatName
- the desired metadata format.IIOMetadataFormat
object.IllegalArgumentException
- if formatName
is null
or is not one of the names recognized by
the plug-in.IllegalStateException
- if the class corresponding to
the format name cannot be loaded.public abstract Node getAsTree(String formatName)
Node
object that represents the
root of a tree of metadata contained within this object
according to the conventions defined by a given metadata
format.
The names of the available metadata formats may be queried
using the getMetadataFormatNames
method.
formatName
- the desired metadata format.Node
object forming the
root of a tree.IllegalArgumentException
- if formatName
is null
or is not one of the names returned by
getMetadataFormatNames
.getMetadataFormatNames()
,
setFromTree(java.lang.String, org.w3c.dom.Node)
,
mergeTree(java.lang.String, org.w3c.dom.Node)
public abstract void mergeTree(String formatName, Node root) throws IIOInvalidTreeException
IIOMetadata
object from a tree of XML DOM Node
s whose syntax
is defined by the given metadata format. The previous state is
altered only as necessary to accomodate the nodes that are
present in the given tree. If the tree structure or contents
are invalid, an IIOInvalidTreeException
will be
thrown.
As the semantics of how a tree or subtree may be merged with another tree are completely format-specific, plug-in authors may implement this method in whatever manner is most appropriate for the format, including simply replacing all existing state with the contents of the given tree.
formatName
- the desired metadata format.root
- an XML DOM Node
object forming the
root of a tree.IllegalStateException
- if this object is read-only.IllegalArgumentException
- if formatName
is null
or is not one of the names returned by
getMetadataFormatNames
.IllegalArgumentException
- if root
is
null
.IIOInvalidTreeException
- if the tree cannot be parsed
successfully using the rules of the given format.getMetadataFormatNames()
,
getAsTree(java.lang.String)
,
setFromTree(java.lang.String, org.w3c.dom.Node)
protected IIOMetadataNode getStandardChromaNode()
IIOMetadataNode
representing the chroma
information of the standard javax_imageio_1.0
metadata format, or null
if no such information is
available. This method is intended to be called by the utility
routine getStandardTree
.
The default implementation returns null
.
Subclasses should override this method to produce an appropriate subtree if they wish to support the standard metadata format.
IIOMetadataNode
, or null
.getStandardTree()
protected IIOMetadataNode getStandardCompressionNode()
IIOMetadataNode
representing the
compression information of the standard
javax_imageio_1.0
metadata format, or
null
if no such information is available. This
method is intended to be called by the utility routine
getStandardTree
.
The default implementation returns null
.
Subclasses should override this method to produce an appropriate subtree if they wish to support the standard metadata format.
IIOMetadataNode
, or null
.getStandardTree()
protected IIOMetadataNode getStandardDataNode()
IIOMetadataNode
representing the data
format information of the standard
javax_imageio_1.0
metadata format, or
null
if no such information is available. This
method is intended to be called by the utility routine
getStandardTree
.
The default implementation returns null
.
Subclasses should override this method to produce an appropriate subtree if they wish to support the standard metadata format.
IIOMetadataNode
, or null
.getStandardTree()
protected IIOMetadataNode getStandardDimensionNode()
IIOMetadataNode
representing the
dimension information of the standard
javax_imageio_1.0
metadata format, or
null
if no such information is available. This
method is intended to be called by the utility routine
getStandardTree
.
The default implementation returns null
.
Subclasses should override this method to produce an appropriate subtree if they wish to support the standard metadata format.
IIOMetadataNode
, or null
.getStandardTree()
protected IIOMetadataNode getStandardDocumentNode()
IIOMetadataNode
representing the document
information of the standard javax_imageio_1.0
metadata format, or null
if no such information is
available. This method is intended to be called by the utility
routine getStandardTree
.
The default implementation returns null
.
Subclasses should override this method to produce an appropriate subtree if they wish to support the standard metadata format.
IIOMetadataNode
, or null
.getStandardTree()
protected IIOMetadataNode getStandardTextNode()
IIOMetadataNode
representing the textual
information of the standard javax_imageio_1.0
metadata format, or null
if no such information is
available. This method is intended to be called by the utility
routine getStandardTree
.
The default implementation returns null
.
Subclasses should override this method to produce an appropriate subtree if they wish to support the standard metadata format.
IIOMetadataNode
, or null
.getStandardTree()
protected IIOMetadataNode getStandardTileNode()
IIOMetadataNode
representing the tiling
information of the standard javax_imageio_1.0
metadata format, or null
if no such information is
available. This method is intended to be called by the utility
routine getStandardTree
.
The default implementation returns null
.
Subclasses should override this method to produce an appropriate subtree if they wish to support the standard metadata format.
IIOMetadataNode
, or null
.getStandardTree()
protected IIOMetadataNode getStandardTransparencyNode()
IIOMetadataNode
representing the
transparency information of the standard
javax_imageio_1.0
metadata format, or
null
if no such information is available. This
method is intended to be called by the utility routine
getStandardTree
.
The default implementation returns null
.
Subclasses should override this method to produce an appropriate subtree if they wish to support the standard metadata format.
IIOMetadataNode
, or null
.protected final IIOMetadataNode getStandardTree()
IIOMetadataNode
s representing the metadata
contained within this object according to the conventions of
the standard javax_imageio_1.0
metadata format.
This method calls the various getStandard*Node
methods to supply each of the subtrees rooted at the children
of the root node. If any of those methods returns
null
, the corresponding subtree will be omitted.
If all of them return null
, a tree consisting of a
single root node will be returned.
IIOMetadataNode
representing the root
of a metadata tree in the javax_imageio_1.0
format.getStandardChromaNode()
,
getStandardCompressionNode()
,
getStandardDataNode()
,
getStandardDimensionNode()
,
getStandardDocumentNode()
,
getStandardTextNode()
,
getStandardTileNode()
,
getStandardTransparencyNode()
public void setFromTree(String formatName, Node root) throws IIOInvalidTreeException
IIOMetadata
object
from a tree of XML DOM Node
s whose syntax is
defined by the given metadata format. The previous state is
discarded. If the tree's structure or contents are invalid, an
IIOInvalidTreeException
will be thrown.
The default implementation calls reset
followed by mergeTree(formatName, root)
.
formatName
- the desired metadata format.root
- an XML DOM Node
object forming the
root of a tree.IllegalStateException
- if this object is read-only.IllegalArgumentException
- if formatName
is null
or is not one of the names returned by
getMetadataFormatNames
.IllegalArgumentException
- if root
is
null
.IIOInvalidTreeException
- if the tree cannot be parsed
successfully using the rules of the given format.getMetadataFormatNames()
,
getAsTree(java.lang.String)
,
mergeTree(java.lang.String, org.w3c.dom.Node)
public abstract void reset()
IllegalStateException
- if this object is read-only.ImageReader.getStreamMetadata()
,
ImageReader.getImageMetadata(int)
,
ImageWriter.getDefaultStreamMetadata(javax.imageio.ImageWriteParam)
,
ImageWriter.getDefaultImageMetadata(javax.imageio.ImageTypeSpecifier, javax.imageio.ImageWriteParam)
public void setController(IIOMetadataController controller)
IIOMetadataController
to be used
to provide settings for this IIOMetadata
object when the activateController
method
is called, overriding any default controller. If the
argument is null
, no controller will be
used, including any default. To restore the default, use
setController(getDefaultController())
.
The default implementation sets the controller
instance variable to the supplied value.
controller
- An appropriate
IIOMetadataController
, or null
.IIOMetadataController
,
getController()
,
getDefaultController()
,
hasController()
,
activateController()
public IIOMetadataController getController()
IIOMetadataController
is currently
installed. This could be the default if there is one,
null
, or the argument of the most recent call
to setController
.
The default implementation returns the value of the
controller
instance variable.
IIOMetadataController
, or null
.IIOMetadataController
,
setController(javax.imageio.metadata.IIOMetadataController)
,
getDefaultController()
,
hasController()
,
activateController()
public IIOMetadataController getDefaultController()
IIOMetadataController
, if there
is one, regardless of the currently installed controller. If
there is no default controller, returns null
.
The default implementation returns the value of the
defaultController
instance variable.
IIOMetadataController
, or
null
.IIOMetadataController
,
setController(IIOMetadataController)
,
getController()
,
hasController()
,
activateController()
public boolean hasController()
true
if there is a controller installed
for this IIOMetadata
object.
The default implementation returns true
if the
getController
method returns a
non-null
value.
true
if a controller is installed.IIOMetadataController
,
setController(IIOMetadataController)
,
getController()
,
getDefaultController()
,
activateController()
public boolean activateController()
IIOMetadataController
for
this IIOMetadata
object and returns the resulting
value. When this method returns true
, all values for this
IIOMetadata
object will be ready for the next write
operation. If false
is
returned, no settings in this object will have been disturbed
(i.e., the user canceled the operation).
Ordinarily, the controller will be a GUI providing a user
interface for a subclass of IIOMetadata
for a
particular plug-in. Controllers need not be GUIs, however.
The default implementation calls getController
and the calls activate
on the returned object if
hasController
returns true
.
true
if the controller completed normally.IllegalStateException
- if there is no controller
currently installed.IIOMetadataController
,
setController(IIOMetadataController)
,
getController()
,
getDefaultController()
,
hasController()
Submit a bug or feature
For further API reference and developer documentation, see Java SE Documentation. That documentation contains more detailed, developer-targeted descriptions, with conceptual overviews, definitions of terms, workarounds, and working code examples.
Copyright © 1993, 2015, Oracle and/or its affiliates. All rights reserved.


graceful-fs functions as a drop-in replacement for the fs module, making various improvements.
The improvements are meant to normalize behavior across different platforms and environments, and to make filesystem access more resilient to errors.
open
and readdir
calls, and retries them once
something closes if there is an EMFILE error from too many file
descriptors.lchmod
for Node versions prior to 0.6.2.fs.lutimes
if possible. Otherwise it becomes a noop.EINVAL
and EPERM
errors in chown
, fchown
or
lchown
if the user isn't root.lchmod
and lchown
become noops, if not available.read
results in EAGAIN error.On Windows, it retries renaming a file for up to one second if EACCESS
or EPERM
error occurs, likely because antivirus software has locked
the directory.
// use just like fs
var fs = require('graceful-fs')
// now go and do stuff with it...
fs.readFileSync('some-file-or-whatever')
If you want to patch the global fs module (or any other fs-like module) you can do this:
// Make sure to read the caveat below.
var realFs = require('fs')
var gracefulFs = require('graceful-fs')
gracefulFs.gracefulify(realFs)
This should only ever be done at the top-level application layer, in order to delay on EMFILE errors from any fs-using dependencies. You should not do this in a library, because it can cause unexpected delays in other parts of the program.
This module is fairly stable at this point, and used by a lot of things. That being said, because it implements a subtle behavior change in a core part of the node API, even modest changes can be extremely breaking, and the versioning is thus biased towards bumping the major when in doubt.
The main change between major versions has been switching between
providing a fully-patched fs
module vs monkey-patching the node core
builtin, and the approach by which a non-monkey-patched fs
was
created.
The goal is to trade EMFILE
errors for slower fs operations. So, if
you try to open a zillion files, rather than crashing, open
operations will be queued up and wait for something else to close
.
There are advantages to each approach. Monkey-patching the fs means
that no EMFILE
errors can possibly occur anywhere in your
application, because everything is using the same core fs
module,
which is patched. However, it can also obviously cause undesirable
side-effects, especially if the module is loaded multiple times.
Implementing a separate-but-identical patched fs
module is more
surgical (and doesn't run the risk of patching multiple times), but
also imposes the challenge of keeping in sync with the core module.
The current approach loads the fs
module, and then creates a
lookalike object that has all the same methods, except a few that are
patched. It is safe to use in all versions of Node from 0.8 through
7.0.


Comments
-
Greg Hurrell
Seems like a mapping issue. Are you using Vim in the terminal (not the GUI) by any chance?
-
anonymous
No, it's in the GUI, gvim for Windows. It happens both in the GUI and the terminal.
-
anonymous
I just saw that it also happens with LustyExplorer. Same exact problem.
-
Greg Hurrell
Unfortunately, not really sure what's going on here. Not something I've seen on the platforms where I'm using Vim and Command-T (Linux and Mac OS X).
-
anonymous
I can confirm this bug. I have the same setup with the Cream build of vim (minus the Cream configuration), RubyInstaller 1.8.7, and the devkit. I open the match window and can see everything, but Command-T's remapped keys are not working. The default key mappings are in place, so hitting o and i tried to go into Insert mode, hitting v goes into visual mode, etc...
-
Greg Hurrell
Right now I don't really have the time or resources to troubleshoot Windows-specific problems, but I am willing to accept patches from somebody who does have those time and resources.
-
anonymous
This is working for me (Christoph) now. As far as I know, the only thing that changed is the Vim version, 7.3 up to patch 289. I also recompiled command-t and made sure it was compiled against 1.8.7 (which I may have done before) and it's working now. I somewhat followed this guide: http://rfbrazier.posterous.com/installing-the-command-t-vim-plugin-on-window but with the newer versions available. I also compiled from cmd.exe and not mingw or anything. Not sure if this is helpful or not, but I am sure happy to have command-t back!
-
Greg Hurrell
Glad to hear you got it sorted out.
-
Greg Hurrell
Status changed:
- From: new
- To: closed
Add a comment
Comments are now closed for this issue.


Test video element control visibility with multimodal input. The controls should hide after a timeout if the last input event was a tap.
This test only runs in DRT!


Love making products, creating softwares with love from past five years and proffessionaly for past three years with product companies. Looking for opportunities to learn from the best and helping them grow with my experience.


| DOSE: |
|
oral |
MDMA |
(pill / tablet) |
I just wanted to note my hindsight of my experiences with ecstasy since I've been diagnosed as Bipolar.
To start, I've recently been diagnosed as Bipolar II, which is characterized by hypomania rather than full blown mania. Hypomania is like a weak state of mania. I'll feel one of two ways: euphoric, content, energized, and like everything is generally going positively; or, extremely irritable, cocky, and aggressive. Sometimes I feel both of those mixed. I cycle between states of depression, hypomania, and indifference. A full manic episode would be those symptoms to the extreme in an uncontrollable whirlwind that can quickly turn very bad. I've had only one fully manic episode (after taking MDMA), but normally only experience hypomania. Nevertheless, I'm at risk and my symptoms could potentially (and probably eventually will) progress into full blown manic episodes.
I've been like this for a while, but being the stubborn person I am, I refused to seek help whenever suggested (usually when I'd be depressed) and it went undiagnosed. Throughout high school I experimented with various drugs, and my first MDMA experience was in my senior year, at the age of 17 (I'm now 19). I'm not saying that MDMA caused my disorder, but it did have an effect.
I've only taken MDMA twice. Both times I commented on how the experience was pretty uneventful although the next day I felt like a million bucks, ready for the world. I wrote both experiences within the following week, and am clearly elated and euphoric at the fact that I feel so ridiculously positive... in one experience claiming that I feel so good I'll never take another drug again because I'm on some kind of natural high. Looking back, I realize that I was experiencing what I now know is hypomania and was writing my experience reports in the midst of being manic.
It's actually very humorous to me to read them because in the reports I'm ridiculously positive and optimistic, and I can see myself during those states on the verge of tears because I'm so happy. Anyways, after the first experience I went into a fully manic episode (coupled with the fact that I had just graduated high school) where I went absolutely nuts all over town, resulting in cloudy memories of alcohol, sex, and vandalism. The second experience was more of the same, and one can again tell by my writing that I am clearly in some sort of altered frame of mind.
Needless to say, following these periods of unbelievable ecstasy I plummet to the exact opposite of the scale into horrible depression. Ecstasy is the only drug I've experienced that triggers manic episodes after taking it. If I smoke marijuana, it throws me into depression, coke makes me feel relatively normal, but nothing else has ever done what ecstasy does to me. Before and since then I've had plenty of ups and downs that looking back I see was just the effects of my disorder, but the only time I've ever gone manic was after taking ecstasy. I don't blame anyone or anything, but now that I know I have a mental disorder I defiantly won't be touching ecstasy again.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


?6
7
8
9
10
The
New
York
copyright
reserved
Botanical
Garden
Herbarium
of
Steven
R.
Hill
Plants
of
XhQ
Bahamas
Anethiaa
grave
olens
L,
"Dill".
Very
aromatic
herb,
comnon
in
waste
areas
around
town.
Flowers
yellow.
Waste
area
behind
Harbor
Store
Clarence
Town,
long
Island»
Det’d
by;
SRH
197U
Steven
R.
Hill
Wo.
^
JmQ
^
^
NEW
YORK
BOTANICAL
GARDEN
01500865
01500865
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