THE NEGOTIATOR (1998)
A film review by Steve Kong Edited by Cher Johnson Copyright 1998 Steve Kong
Movies can be seen as bookends and the books in between. The bookends are the opening and closing of the film and the books contain the story and subplots of the film. Most movies have beautifully crafted bookends and thin poorly written books. The Negotiator goes the other way. The bookends for The Negotiator are bent out of shape and not beautiful at all. The books that the bookends hold are tense and well written.
The Negotiator has a cliched and unbelievable opening. Danny Roman (Samuel L. Jackson) is the best negotiator in his department. In the opening, Roman is trying to talk a man out of killing his own daughter. Roman finally uses some dangerous tactics to get the girl free and for this, he takes some heat from his commanders. What we find out later, during the cliched after-I-saved-the-day party, is that Roman's partner suspects that some of the officers in the department are stealing money from the department. Before Roman finds out too much from his partner, his partner is killed. Roman is suspected of killing his partner. Though we know that he is being framed.
What comes next is the contrived part in an instant, Roman's whole department turns against him. They all think he's the killer. What doesn't ring true is that from what I've seen, cops are pretty protective of each other. What is portrayed onscreen just doesn't jive. But, this is also the point in which the movie picks up a lot of steam. Roman takes hostages, one being a key figure in the money stealing deal. Roman wants to force this person to admit to what has been happening; he wants to clear his name. Roman demands that a negotiator from outside his department do the negotiating, and he will only talk to Chris Sabian (Kevin Spacey). Jackson, who by himself is already a great actor and a big presence on the screen, is now joined by Kevin Spacey as the negotiator. From now on, the acting of these two intense actors drives the movie.
One other thing drives The Negotiator. Though we think that the person that Roman is holding hostage is maybe one of the people involved in the money stealing scheme, we also know that there are others from Roman's department that are part of the scheme. But who? Director F. Gary Gray and writers James DeMonaco and Kevin Fox throw all kinds of bones out. And it isn't until the very end that we find out who is behind all of this. I loved this because it kept me guessing as to who was in the scheme and who wasn't.
Jackson and Spacey are from two different ends of the intense-acting spectrum. Jackson is verbal and loudly eloquent. Spacey, on the other hand, carries an inner intensity that radiates with his eyes and his calm exterior. The two light up the screen. It is the dialogue between these two that kept my attention.
The script by James DeMonaco and Kevin Fox is very knowledgeable about the ways of negotiators. Watch for the lessons about negotiations by Roman during the film. I loved how DeMonaco and Fox worked in a lesson on what to say to hostage takers. Roman also talks about what to look for in order to see that a person is lying. I think that DeMonaco and Fox did some good research before embarking on writing this script. The script itself has a meaty midsection that is sandwiched by a weak opening and closing.
Director F. Gary Gray keeps the movie tight and tense. Roman takes hostages in an office in the midsection of a high rise. Gray uses the tight quarters of this office fully. The only complaint I have is that Gray and the writers threw in an action sequence halfway into the film that didn't feel right. I thought that Gray and the writers were doing very well with the negotiations between Roman and Sabian, but then all the sudden there appears this action sequence. But, this is a small complaint. Kudos to Gray for putting together a taut film.
The supporting actors all fare well. Look for the late J.T. Walsh in his final performance. David Morse and John Spencer turn up good supporting performances.
Don't let the bookends of The Negotiator fool you into thinking that it's a raggedy movie. Don't Miss The Negotiator in the theatres. This is a solid film that will keep you at the edge of your seat from the beginning to the end.
--- Steve Kong<EMAIL_ADDRESS>reviews from a guy who loves the cinema http://boiled.sbay.org/boiled/
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
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A data package
Documentation for package ‘ALL’ version 1.20.0
DESCRIPTION file
.
User guides, package vignettes and other documentation.
Help Pages
ALL
Acute Lymphoblastic Leukemia Data from the Ritz Laboratory
tojulian
Convert Calendar Date to Julian Time


“SELF DEFENCE”
Student Welfare Club, School of Civil Engineering
Date of the event
15th to 21st of March 2019
organised by
School of Civil Engineering
The School Of Civil Engineering organized “SELF DEFENCE EVENT” for the students of B.Tech, School of Civil Engineering on 15thof March, 2019.This event was organized by the students of 6th semester under the leadership of Asst. Prof. M. Sreenivasulu Reddy President and Asst. Prof. Bhavana.B Vice President , Student Welfare Club, School Of Civil Engineering.
The program started at 2:30PM and inaugurated by Dr.Y.Ramalinga Reddy, Chairman, Student Welfare Club and also Director, School Of Civil Engineering, Asst. Prof. M. Sreenivasulu Reddy and Asst.Prof. Bhavana. The guests for this program were Shihan Dr.Lakshmi, Shihan Ashwini and Renshi.M.Krishna .They trained the students along with their teams.
The program conducted in two sessions, the first session for day scholars from 2:30pm to 4:30pm and the second session for hostilities from 4:45pm to 5:45pm.
“SUMMER TRAINING PROGRAM AT UNIVERSITIES ABROAD (UG FELLOWSHIP )”
Student Welfare Club, School of Civil Engineering.
Date of the event
18th March 2019
venue
Sir M.V Block, Room No.304 & 215
organised by
School of Civil Engineering .
Description of the evnt
The School of Civil Engineering had organized a awareness program on UG fellowship opportunities , Internship opportunities, Project available abroad talk for 8,6,4th semester students of Civil Engineering, REVA University .
The Speaker was Dr. Aparna Bhirangi from Vishwaniketan Trust .
BLOOD DONATION CAMP
School of Civil and Mechanical Engineering in association with Jeevan Raksha Voluntary blood bank
Description of the evnt
Date of the event
19th March 2019
venue
Sir M.V Block, Room No.304 & 215
organised by
School of Civil and Mechanical Engineering in association with Jeevan Raksha Voluntary blood bank
Description of the evnt
Blood donation and free medical checkup camp was organised by Schools of Civil and Mechanical Engineering on 19th of March 2019.
The program commenced with lamp lighting ceremony by Director & Associate Dean Dr. Y Ramalinga Reddy, School of Civil and Mechanical Engineering, Dr.K.S.Narayanaswamy, Director, School of Mechanical Engineering, Dr.Shubhakar, Director-Health Program, JeevaRaksha Service Trust, Mr.M Sreenivasulu Reddy, ACE Coordinator, & all the faculty members of School of Civil Engineering and Student Coordinators Ms.Apoorva.N.H and Prajwal Balaji and other volunteers
SITE VISIT TO UPCOMING GYMNASIUM, REVA CAMPUS
SCHOOL OF CIVIL ENGINEERING
Description of the evnt
Date of the event
20th March 2019
organised by
School of Civil Engineering .
School of Civil Engineering had arranged a field visit to upcoming Gym, REVA campus for students of 6th semester ‘B’ section, in relation with the subject Design and Drawing of RCC and Steel Structures (DDRCC&SS).
This field visit provided an exposure to students in the field steel structures, its types of connections and also construction methods followed in practice. Mrs Rekha B Asst Professor conducted this visit.
SITE VISIT TO AJMERA Lugona
SCHOOL OF CIVIL ENGINEERING
Description of the evnt
Date of the event
21th March 2019
organised by
School of Civil Engineering .
School of Civil Engineering had arranged a field visit to Ajmera Lugano, Puravankara, proposed construction site for students of B.Tech 4th semester A & B section and MTech CASE 2nd semester in relation with the subject Design of RCC structures.
This field visit provided an exposure to students in the field of RCC construction methods followed in practice and the reinforcement details. Faculty members Mr.Sanjay Raja, Mrs Rekha B and Mrs Shylaja N conducted this visit.


OpenSSH sshd
Edit /etc/ssh/sshd_config and check the following settings:
-
# SSH service
Port 22
Protocol 2
-
# Disable root login
PermitRootLogin no
-
# If password login not allowed
AuthenticationMethods publickey
PasswordAuthentication no
-
# If password login allowed
AuthenticationMethods publickey,password
PasswordAuthentication yes
-
# No empty passwords for login
PermitEmptyPasswords no
-
# Banner text
Banner [message here]
Then restart ssh service for these settings to take in effect.
References:
- https://manpages.ubuntu.com/manpages/xenial/en/man5/sshd_config.5.html


I'm Hugo, a computer science student currently living in Madrid, Spain.
I'm currently employed in the Big Data department of Telefónica, improving their video-on-demand (movistar+) recommendation engine.
Previously, I also worked with Product Hackers, building web apps and chat bots using Angular 2 and Ionic 2.
I've also worked in research groups within my University on topics such as computer vision, robotics and natural language processing. Since 2016 I'm also a member of their Data Science Lab.
I'm one of the members of my university's robotics club. Last year we built HRB, a teleoperated rescue robot. With it our team won the 2016 Laureate Awards for Excellence in Robotics Engineering.
Besides programming, I also enjoy travelling and photography!


Teams of wizards and magical beasts compete in the greatest tournament in the world of magic - MagiciansBattle - to prove they are the very best.
Join one of the four factions, assemble your own legendary team and lead it to victory against the mighty opponents that await you in the battle arena!
Collect wizard, creature, spell and item cards to build the most fearsome and dominating deck in MagiciansBattle.
Beat your foes in battle to gain new cards (for free) and trade cards with other players to perfect your deck.
MagiciansBattle is a PvP, deck-building, turn-based strategy game on a hex grid map.
Every card offers rich possibilities of play, resulting in a very dynmaic and versatile game.
Test your skills, wit and courage in a fast paced and challnging strategic duel!


Creating a blog truly beautiful... and tasty
Assembly time: A few hours
Awesome rating: 99.99% awesome
Have you always wanted to put those yummy recipes found on Pinterest to use? Maybe even share them with like-minded foodie's who enjoy lavish salads and sandwiches? Here's your 5-step guide to an aesthetically pleasing, mouth-watering blog!
-
Gather content, write recipes you’re familiar with
Buried deep in our Instagram saves, no more! Dig through your Pins, likes, and of course the classic "secret family cookbook" to render up a list of recipes fatter than Uncle Barb's Thanksgiving turkey to share with your audience.
-
Tell a personal story about each dish you post
Anecdotes such as the origin and history behind a recipe can really pump up those subscribers baby! Maybe even consider posting recipes relevant to the time of year, because who doesn't love a summer salad or Christmas cocoa?
-
Keep each blog post 300-700 words and edit EVERYTHING you write
Sloppy isn't good, engagement on your blog depends on organized and well thought-out entries and editing.


TOUS LES MATINS DU MONDE A film review by Edwin Jahiel Copyright 1996 Edwin Jahiel
TOUS LES MATINS DU MONDE (ALL THE MORNINGS OF THE WORLD) (France, 1991) *** 3/4 . Directed by Alain Corneau. Screenplay by Pascal Guignard and Corneau, from Guignard's novel. Music arranger and performer, Jordi Savall. Cinematography, Yves Angelo. Sets, Bernard Vezat. Costumes, Corrine Jorry. Editing, Marie-Joseph Yoyotte. Cast: Jean-Pierre Marielle, Gerard Depardieu, Anne Brochet, Guillaume Depardieu, et al. An October Films release. In French with subtitles. 113 min. Rated PG. At the Savoy Theaters.
C'est magnifique ! The musical sounds are magnificent. Lighting and photography are magnificent. Editing and just about everything else is magnificent.
Gerard Depardieu must be Lon Chaney's successor as The Man of a Thousand Faces. Grotesquely puffy, rouged, bewigged, he opens the film as the musician-courtier, composer and viol virtuoso Marin Marais (1656-1728)]
In a fit of dark despair and humbling himself, the aging Marais tells his students that he is nothing compared to his teacher. His voice-over starts the flashbacks about Monsieur de Sainte-Colombe, a musical genius about whom little is known, not even his first name.
Sainte-Colombe did exist. He was a composer-performer who did marvels for the viol (the viola de gamba that became the cello), added a seventh string, found new fingerings, and had Marais as his most direct disciple.
The story begins with the death of Sainte-Colombe's young wife in the 1660s. The disconsolate musician (Jean-Pierre Marielle) becomes a recluse in his large country house, builds a cabin --a wooden shack to practice in -- in his garden. He practices endlessly and also teaches his two daughters the rudiments of literacy and the techniques and secrets of great viol playing.
Solo or together they make stunning music. Years later, father and grown-up children give a rare salon trio performance. The court's foppish first violist acknowledges Sainte-Colombe's superiority, soon after offers him to play for His Majesty Louis XIV, the Sun King in whose reign France was the cultural and artistic center of the world.
The vile-tempered Sainte-Colombe was a purist's purist and a Jansenist to boot -- these were breakaway Catholics who, among other matters, disapproved of the Jesuits' worldliness and ostentation. He kicks out the envoy. Playing the Palace is not for him.
He resumes his rustic, eremitic life, with a vengeance. Having attained musical perfection he will not share it.
17-year old Marin Marais (Guillaume Depardieu, Gerard's only son) asks the Master to teach him. In vain, until the two girls come to the rescue. But in this un-Hollywoodian tale the teacher keeps reminding the young man that he may have virtuosity but lacks soul. "You're not a musician," he says, a term that the uncompromising Sainte-Colombe seems to equate with an ineffable state of grace.
French movie narrations can often be superb. Here, Gerard Depardieu relates the past with perfect voice and tone, in literary yet beautifully simple, un-pedantic terms. His technical discourses on musical techniques are fascinating.
"Tous les Matins ... " is a glorious musical story. It is also a moving story of marital love. Sainte-Colombe's adoration of his wife is recompensed by a series of her apparitions. " It seemed to him that his rage was leaving him." He mellows perceptibly. We even discover that the Maestro did have one friend, painter Baugin, also a purist and a real-life person about whom little is known.
The film drips with Frenchness, from small details to the face of senior daughter Madeleine. Curiously, Anne Brochet played Roxanne in "Cyrano de Bergerac" where, without realizing it, she was in love with Cyrano, played by Gerard Depardieu. Here she loves Depardieu Junior.
There is an affair that turns sad when young Marais yields to the temptations of fame and fortune. Much later, he realizes that his ties to the Sainte-Colombe family were more powerful than he had thought.
The music, string and vocal , is a feast for the ears, with compositions by Sainte-Colombe, Marais, Lully, Couperin, and arrangements and performances by contemporary, Barcelona-born master of the bass viol, Jordi Savall. The faking of viol-playing by the actors is entirely convincing.
The look of the film is a feast for the eyes. The interiors remind you (but not pointedly) of paintings by Georges de La Tour, Dutch masters and others. The secret is exquisite lighting, one of the most beautiful and precise I can remember. It reproduces perfectly the period's commonly used single or weak light sources, as opposed to artificial movie-lighting and the lightening of shadows or duskiness.
The acting by Gerard Depardieu and Anne Brochet is impeccable. Jean-Pierre Marielle ho generally has comic or cynical roles, is cast again type and gives an unforgettably taciturn performance. Depardieu Jr. makes a good debut.
French director Bertrand Tavernier had made" Round Midnight," in 1986. With the help of Dexter Gordon and Herbie Hancock, this was the best and most loving film ever about jazz musicians. Now Alain Corneau's ninth film in 18 years does the same for baroque music. Nominated for 11 Cesars (the French Oscars), it won 7, including Best Film, Director, Supporting Actress and Music. There were other awards too, such as the prestigious Louis Delluc Prize for Best French Film.
TOUS LES MATINS DU MONDE (ALL THE MORNINGS OF THE WORLD) (France, 1991) *** 3/4 . Directed by Alain Corneau. Screenplay by Pascal Guignard and Corneau, from Guignard's novel. Music arranger and performer, Jordi Savall. Cinematography, Yves Angelo. Sets, Bernard Vezat. Costumes, Corrine Jorry. Editing, Marie-Joseph Yoyotte. Cast: Jean-Pierre Marielle, Gerard Depardieu, Anne Brochet, Guillaume Depardieu, et al. An October Films release. In French with subtitles. 113 min. Rated PG. At the Savoy Theaters.
C'est magnifique ! The musical sounds are magnificent. Lighting and photography are magnificent. Editing and just about everything else is magnificent.
Gerard Depardieu must be Lon Chaney's successor as The Man of a Thousand Faces. Grotesquely puffy, rouged, bewigged, he opens the film as the musician-courtier, composer and viol virtuoso Marin Marais (1656-1728)]
In a fit of dark despair and humbling himself, the aging Marais tells his students that he is nothing compared to his teacher. His voice-over starts the flashbacks about Monsieur de Sainte-Colombe, a musical genius about whom little is known, not even his first name.
Sainte-Colombe did exist. He was a composer-performer who did marvels for the viol (the viola de gamba that became the cello), added a seventh string, found new fingerings, and had Marais as his most direct disciple.
The story begins with the death of Sainte-Colombe's young wife in the 1660s. The disconsolate musician (Jean-Pierre Marielle) becomes a recluse in his large country house, builds a cabin --a wooden shack to practice in -- in his garden. He practices endlessly and also teaches his two daughters the rudiments of literacy and the techniques and secrets of great viol playing.
Solo or together they make stunning music. Years later, father and grown-up children give a rare salon trio performance. The court's foppish first violist acknowledges Sainte-Colombe's superiority, soon after offers him to play for His Majesty Louis XIV, the Sun King in whose reign France was the cultural and artistic center of the world.
The vile-tempered Sainte-Colombe was a purist's purist and a Jansenist to boot -- these were breakaway Catholics who, among other matters, disapproved of the Jesuits' worldliness and ostentation. He kicks out the envoy. Playing the Palace is not for him.
He resumes his rustic, eremitic life, with a vengeance. Having attained musical perfection he will not share it.
17-year old Marin Marais (Guillaume Depardieu, Gerard's only son) asks the Master to teach him. In vain, until the two girls come to the rescue. But in this un-Hollywoodian tale the teacher keeps reminding the young man that he may have virtuosity but lacks soul. "You're not a musician," he says, a term that the uncompromising Sainte-Colombe seems to equate with an ineffable state of grace.
French movie narrations can often be superb. Here, Gerard Depardieu relates the past with perfect voice and tone, in literary yet beautifully simple, un-pedantic terms. His technical discourses on musical techniques are fascinating.
"Tous les Matins ... " is a glorious musical story. It is also a moving story of marital love. Sainte-Colombe's adoration of his wife is recompensed by a series of her apparitions. " It seemed to him that his rage was leaving him." He mellows perceptibly. We even discover that the Maestro did have one friend, painter Baugin, also a purist and a real-life person about whom little is known.
The film drips with Frenchness, from small details to the face of senior daughter Madeleine. Curiously, Anne Brochet played Roxanne in "Cyrano de Bergerac" where, without realizing it, she was in love with Cyrano, played by Gerard Depardieu. Here she loves Depardieu Junior.
There is an affair that turns sad when young Marais yields to the temptations of fame and fortune. Much later, he realizes that his ties to the Sainte-Colombe family were more powerful than he had thought.
The music, string and vocal , is a feast for the ears, with compositions by Sainte-Colombe, Marais, Lully, Couperin, and arrangements and performances by contemporary, Barcelona-born master of the bass viol, Jordi Savall. The faking of viol-playing by the actors is entirely convincing.
The look of the film is a feast for the eyes. The interiors remind you (but not pointedly) of paintings by Georges de La Tour, Dutch masters and others. The secret is exquisite lighting, one of the most beautiful and precise I can remember. It reproduces perfectly the period's commonly used single or weak light sources, as opposed to artificial movie-lighting and the lightening of shadows or duskiness.
The acting by Gerard Depardieu and Anne Brochet is impeccable. Jean-Pierre Marielle ho generally has comic or cynical roles, is cast again type and gives an unforgettably taciturn performance. Depardieu Jr. makes a good debut.
French director Bertrand Tavernier had made" Round Midnight," in 1986. With the help of Dexter Gordon and Herbie Hancock, this was the best and most loving film ever about jazz musicians. Now Alain Corneau's ninth film in 18 years does the same for baroque music. Nominated for 11 Cesars (the French Oscars), it won 7, including Best Film, Director, Supporting Actress and Music. There were other awards too, such as the prestigious Louis Delluc Prize for Best French Film.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


func GetIsEssenKeyMap() map[string]bool
GetIsEssenKeyMap returns the "YandC" map with special keys that EssentialBcs can handle, including:
rigid -- define rigid element constraints incsup -- inclined support constraints hst -- set hydrostatic pressures
func NewDomains(sim *inp.Simulation, dyncfs *ele.DynCoefs, proc, nproc int, distr, verb bool) (doms []*Domain)
NewDomains returns domains
func PlotAllBendingMom2d(dom *Domain, nstations int, withtext bool, numfmt string, tolM, coef, sf float64) (beams []*solid.Beam, allMrr [][]float64)
PlotAllBendingMom2d plots all bending moments (2D beams)
Input: dom -- Domain nstations -- number of stations withtext -- show bending moment values numfmt -- number format for values. use "" for default tolM -- tolerance to clip absolute values of M coef -- coefficient to scale max(dimension) divided by max(Y); e.g. 0.1 sf -- scaling factor. use 0 for automatic computation Output: beams -- all beam elements allMrr -- all Mrr bending moments at all beams
type ColLayer struct { // geometry Tags []int // tags of cells within this layer Zmin float64 // coordinate (elevation) at bottom of layer Zmax float64 // coordinate (elevation) at top of layer Elems []ele.Element // elements in layer Nodes []*Node // nodes in layer // parameters: porous medium SlMax float64 // maximum liquid saturation; e.g. 1.0 Nf0 float64 // initial (constant) porosity RhoS0 float64 // initial density of solids // parameters: total stress analysis TotRho float64 // density for total stress analyses TotStress bool // total stress analysis // additional data K0 float64 // coefficient to multiply effective vertical stresses and obtain horizontal effective stresses SigV float64 // state @ top of layer // auxiliary Grav float64 // gravity Liq *fluid.Model // liquid model Gas *fluid.Model // gas model }
ColLayer holds information of one porous column layer. It computes pressures and densities based on the following expressions (maximum liquid saturation and minimum gas saturation)
ρL = ρL0 + Cl・(pl - pl0) thus dρL/dpl = Cl ρG = ρG0 + Cg・(pg - pg0) thus dρG/dpg = Cg sl = slmax sg = 1 - slmax ρ = nf・sl・ρL + nf・sg・ρG + (1 - nf)・ρS ns = 1 - nf σV = σV0 + ρ・g・(H - z)
func (o ColLayer) Calc(z float64) (pl, pg, ρL, ρG, ρ, σV float64)
Calc computes state @ level z
func (o ColLayer) Calc_ρ(ρL, ρG float64) (ρ float64)
Calc_ρ computes ρ (mixture density)
type ColLayers []*ColLayer
ColLayers is a set of Layer
func (o ColLayers) Len() int
Len the length of Layers
func (o ColLayers) Less(i, j int) bool
Less compares Layers: sort from top to bottom
func (o ColLayers) Swap(i, j int)
Swap swaps two Layers
type DebugKb_t func(d *Domain, it int)
function to debug global Jacobian matrix
type Dof struct { Key string // primary variable key. e.g. "ux" Eq int // equation number }
Dof holds information about a degree-of-freedom == solution variable
func (o *Dof) String() string
String returns the string representation of this Dof
type Domain struct { // init: auxiliary variables Distr bool // distributed/parallel run Proc int // this processor number Verbose bool // verbose ShowMsg bool // show messages: if verbose==true and proc==0 Sim *inp.Simulation // [from FEM] input data Reg *inp.Region // region data Msh *inp.Mesh // mesh data LinSol la.LinSol // linear solver DynCfs *ele.DynCoefs // [from FEM] coefficients for dynamics/transient simulations // stage: nodes (active) and elements (active AND in this processor) Nodes []*Node // active nodes (for each stage). Note: indices in Nodes do NOT correpond to Ids => use Vid2node to access Nodes using Ids. Elems []ele.Element // [procNcells] only active elements in this processor (for each stage) MyCids []int // [procNcells] the ids of cells in this processor // stage: auxiliary maps for dofs and equation types F2Y map[string]string // converts f-keys to y-keys; e.g.: "ux" => "fx" YandC map[string]bool // y and constraints keys; e.g. "ux", "pl", "H", "incsup", "rigid" Dof2Tnum map[string]int // {t1,t2}-types: dof => t_number; e.g. "ux" => 2, "pl" => 1 // stage: auxiliary maps for nodes and elements Vid2node []*Node // [nverts] VertexId => index in Nodes. Inactive vertices are 'nil' Cid2elem []ele.Element // [ncells] CellId => index in Elems. Cells in other processors or inactive are 'nil' Cid2active []bool // [ncells] CellId => whether cell is active or not in ANY processor // stage: subsets of elements ElemIntvars []ele.WithIntVars // elements with internal vars in this processor ElemIvsCon []ele.WithIntVars // elements with internal vars that are connectors ElemIvsNotCon []ele.WithIntVars // elements with internal vars that are not connectors ElemConnect []ele.Connector // connector elements in this processor ElemExtrap []ele.CanExtrapolate // elements with internal values to be extrapolated ElemFixedKM []ele.WithFixedKM // elements with fixed K,M matrices; to be recomputed if prms are changed // stage: coefficients and prescribed forces EssenBcs EssentialBcs // constraints (Lagrange multipliers) PtNatBcs PtNaturalBcs // point loads such as prescribed forces at nodes // stage: t1 and t2 variables T1eqs []int // first t-derivative variables; e.g.: dp/dt vars (subset of ykeys) T2eqs []int // second t-derivative variables; e.g.: d²u/dt² vars (subset of ykeys) // stage: dimensions NnzKb int // number of nonzeros in Kb matrix Ny int // total number of dofs, except λ Nlam int // total number of Lagrange multipliers NnzA int // number of nonzeros in A (constraints) matrix Nyb int // total number of equations: ny + nλ // stage: solution and linear solver Sol *ele.Solution // solution state Kb *la.Triplet // Jacobian == dRdy Fb []float64 // residual == -fb Wb []float64 // workspace InitLSol bool // flag telling that linear solver needs to be initialised prior to any further call // contains filtered or unexported fields }
Domain holds all Nodes and Elements active during a stage in addition to the Solution at nodes. Only elements in this processor are recorded here; however information from all cells might be recorded as well.
func (o *Domain) Clean()
Clean cleans memory allocated by domain
func (o *Domain) IniSetFileFunc(stg *inp.Stage) (err error)
IniSetFileFunc sets initial state with values given in a file or by a function
func (o *Domain) IniSetPorous(stg *inp.Stage) (err error)
IniSetPorous sets porous medium initial state (including geostatic or hydrostatic)
func (o *Domain) IniSetStress(stg *inp.Stage) (err error)
IniSetStress sets all elements with homogeneous initial stress
func (o *Domain) Read(sum *Summary, tidx, proc int, allInOne bool) (err error)
In performs the inverse operation of Out()
allInOne -- indicates that all results must be read into the root processor only For example when plotting or generating VTU files (or testing) If allInOne is false, each processor will read its part as described by Summary. Thus, recoreving the state as in the previous simulation.
func (o *Domain) ReadIvs(dir, fnkey, enctype string, tidx, proc int) (err error)
ReadIvs reads elements's internal values from a file which name is set with tidx (time output index)
func (o *Domain) ReadSol(dir, fnkey, enctype string, tidx int) (err error)
ReadSol reads Solution from a file which name is set with tidx (time output index)
func (o *Domain) RecomputeKM()
RecomputeKM recompute K and M matrices of elements with static matrices
func (o *Domain) Save(tidx int, verbose bool) (err error)
Out performs output of Solution and Internal values to files
func (o *Domain) SaveIvs(tidx int, verbose bool) (err error)
SaveIvs saves elements's internal values to a file which name is set with tidx (time output index)
func (o *Domain) SaveSol(tidx int, verbose bool) (err error)
SaveSol saves solution (o.Sol) to a file which name is set with tidx (time output index)
func (o *Domain) SetIniVals(stgidx int, zeroSol bool) (err error)
SetIniVals sets/resets initial values (nodes and integration points)
func (o *Domain) SetStage(stgidx int) (err error)
SetStage set nodes, equation numbers and auxiliary data for given stage
func (o *Domain) UpdateElems() (err error)
UpdateElems update elements after Solution has been updated
type EbcArray []*EssentialBc
EbcArray is an array of EssentialBc's
func (o EbcArray) Len() int
functions to implement Sort interface
func (o EbcArray) Less(i, j int) bool
func (o EbcArray) Swap(i, j int)
type EssentialBc struct { Key string // key such as 'ux', 'uy', 'rigid', 'incsup', 'hst' Eqs []int // equations numbers; can be more than one e.g. for inclined support ValsA []float64 // values for matrix A Fcn fun.Func // function that implements the "c" vector in A・y = c }
EssentialBc holds information about essential bounday conditions such as constrained nodes. Lagrange multipliers are used to implement both single- and multi-point constraints.
In general, essential bcs / constraints are defined by means of: A・y = c The resulting Kb matrix will then have the following form: _ _ | K At | / δy \ / -R - At*λ \ | | | | = | | |_ A 0 _| \ δλ / \ c - A*y / Kb δyb fb
type EssentialBcs struct { LiqMdl *fluid.Model // for computing hydrostatic conditions EqsIni map[int]bool // equations that depend on initial values Bcs EbcArray // active essential bcs / constraints A la.Triplet // matrix of coefficients 'A' Am *la.CCMatrix // compressed form of A matrix }
EssentialBcs implements a structure to record the definition of essential bcs / constraints. Each constraint will have a unique Lagrange multiplier index.
func (o *EssentialBcs) AddToRhs(fb []float64, sol *ele.Solution)
AddtoRhs adds the essential bcs / constraints terms to the augmented fb vector
func (o *EssentialBcs) Build(ny int) (nλ, nnzA int)
Build builds the structures required for assembling A matrix
nλ -- is the number of essential bcs / constraints == number of Lagrange multipliers nnzA -- is the number of non-zeros in matrix 'A'
func (o *EssentialBcs) FixIniVals(sol *ele.Solution)
FixIniVals fixes functions of BCs that depend on initial values
func (o *EssentialBcs) Init(liqmdl *fluid.Model)
Init initialises this structure
func (o *EssentialBcs) List(t float64) (l string)
List returns a simple list logging bcs at time t
func (o *EssentialBcs) Set(key string, nodes []*Node, fcn fun.Func, extra string) (err error)
Set sets a constraint if it does not exist yet.
key -- can be Dof key such as "ux", "uy" or constraint type such as "incsup" or "rigid" extra -- is a keycode-style data. e.g. "!type:incsup2d !alp:30" Notes: 1) the default key is single point constraint; e.g. "ux", "uy", ... 2) hydraulic head can be set with key == "hst" (hydrostatic). In this case, fcn==shift computes a 'shift' such that: pl(t,z) = pl(z) - shift(t) 3) if the key as a suffix "_ini", the initial value of essential key will be multiplied by fcn==mult in order to define the boundary condition according to: y(t,z) = y(z)_ini・mult(t)
type Implicit struct {
// contains filtered or unexported fields
}
Implicit solves FEM problem using an implicit procedure (with Newthon-Raphson method)
func (o *Implicit) Run(tf float64, dtFunc, dtoFunc fun.Func, verbose bool, dbgKb DebugKb_t) (err error)
type LinearImplicit struct {
// contains filtered or unexported fields
}
LinearImplicit solves **linear** FEM problem using an implicit procedure
func (o *LinearImplicit) Run(tf float64, dtFunc, dtoFunc fun.Func, verbose bool, notused DebugKb_t) (err error)
type Main struct { Sim *inp.Simulation // simulation data Summary *Summary // summary structure DynCfs *ele.DynCoefs // coefficients for dynamics/transient simulations Domains []*Domain // all domains Solver Solver // finite element method solver; e.g. implicit, Richardson extrapolation, etc. DebugKb DebugKb_t // debug Kb callback function Nproc int // number of processors Proc int // processor id ShowMsg bool // show messages }
Main holds all data for a simulation using the finite element method
func NewMain(simfilepath, alias string, erasePrev, saveSummary, readSummary, allowParallel, verbose bool, goroutineId int) (o *Main)
NewMain returns a new Main structure
Input: simfilepath -- simulation (.sim) filename including full path alias -- word to be appended to simulation key; e.g. when running multiple FE solutions erasePrev -- erase previous results files saveSummary -- save summary readSummary -- ready summary of previous simulation allowParallel -- allow parallel execution; otherwise, run in serial mode regardless whether MPI is on or not verbose -- show messages
func (o *Main) Run() (err error)
Run runs FE simulation
func (o *Main) SetStage(stgidx int) (err error)
SetStage sets stage for all domains
Input: stgidx -- stage index (in o.Sim.Stages)
func (o *Main) SolveOneStage(stgidx int, zerostage bool) (err error)
SolveOneStage solves one stage that was already set
Input: stgidx -- stage index (in o.Sim.Stages) zerostage -- zero vectors in domains.Sol => call ZeroStage
func (o *Main) ZeroStage(stgidx int, zeroSol bool) (err error)
ZeroStage zeroes solution varaibles; i.e. it initialises solution vectors (Y, dYdt, internal values such as States.Sig, etc.) in all domains for all nodes and all elements
Input: stgidx -- stage index (in o.Sim.Stages) zeroSol -- zero vectors in domains.Sol
type Node struct { Dofs []*Dof // degrees-of-freedom == solution variables Vert *inp.Vert // pointer to Vertex }
Node holds node dofs information
func NewNode(v *inp.Vert) *Node
NewNode allocates a new Node
func (o *Node) AddDofAndEq(ukey string, eqnum int) (nexteq int)
AddDof adds a new dof to thisnode; ignores it if it exists already
nexteq -- is the next equation number == eqnum + 1; returns eqnum if dof exists already
func (o *Node) GetDof(ukey string) *Dof
GetDof returns the Dof structure for given Dof name (ukey)
Note: returns nil if not found
func (o *Node) GetEq(ukey string) (eqNumber int)
GetEq returns the equation number for given Dof name (ukey)
Note: returns -1 if not found
func (o *Node) GetKeys() []string
GetKeys returns a slice of keys from all dofs
func (o *Node) SetEq(ukey string, eqNumber int)
SetEq numbers a specific Dof with the equation number in the current (stage) global system
func (o *Node) String() string
String returns the string representation of this node
type PtNaturalBc struct { Key string // key such as fux, fpl, etc... Eq int // equation X []float64 // location Fcn fun.Func // function Extra string // extra information }
PtNaturalBc holds information on point natural boundary conditions such as prescribed forces or fluxes) at nodes
type PtNaturalBcs struct { Eq2idx map[int]int // maps eq number to indices in Bcs Bcs []*PtNaturalBc //active boundary conditions such as prescribed forces }
PointLoads is a set of prescribed forces
func (o PtNaturalBcs) AddToRhs(fb []float64, t float64)
AddToRhs adds the boundary conditions terms to the augmented fb vector
func (o *PtNaturalBcs) List(t float64) (l string)
List returns a simple list logging bcs at time t
func (o *PtNaturalBcs) Reset()
Reset initialises internal structures
func (o *PtNaturalBcs) Set(key string, nod *Node, fcn fun.Func, extra string) (setisok bool)
Set sets new point natural boundary condition data
type RichardsonExtrap struct { // variables after big step Y_big []float64 // primary variables // time loop Δt float64 // time step Δtcpy float64 // copy of Δt for divergence control // contains filtered or unexported fields }
RichardsonExtrap solves FEM problem implicitely and with Richardson's extrapolation
func (o *RichardsonExtrap) Init()
func (o *RichardsonExtrap) Run(tf float64, dtFunc, dtoFunc fun.Func, verbose bool, dbgKb DebugKb_t) (err error)
type Solver interface { Run(tf float64, dtFunc, dtoFunc fun.Func, verbose bool, dbgKb DebugKb_t) (err error) }
Solver implements the actual solver (time loop)
type Summary struct { // main data Dirout string // directory where results are stored Fnkey string // filename key of simulation Nproc int // number of processors OutTimes []float64 // [nOutTimes] output times Resids utl.DblSlist // residuals (if Stat is on; includes all stages) // contains filtered or unexported fields }
Summary records summary of outputs
func (o *Summary) Read(dir, fnkey, enctype string) (err error)
Read reads summary back
func (o Summary) Save(dirout, fnkey, enctype string, nproc, proc int, verbose bool) (err error)
SaveSums saves summary to disc
func (o *Summary) SaveDomains(time float64, doms []*Domain, verbose bool) (err error)
SaveDomains save the results from all domains (nodes and elements)


001package com.github.tommyettinger.colorful; 002 003import com.badlogic.gdx.graphics.Color; 004import com.badlogic.gdx.math.MathUtils; 005import com.badlogic.gdx.utils.NumberUtils; 006import com.github.tommyettinger.colorful.ycwcm.ColorTools; 007 008/** 009 * Various utility methods for working with colors encoded as packed floats in any of the formats this can use. 010 * <br> 011 * Created by Tommy Ettinger on 12/2/2019. 012 */ 013public class FloatColors { 014 015 /** 016 * Converts a packed float in HSLA format (hue, saturation, lightness, alpha) to a packed float in RGBA format. 017 * @param hsla an HSLA-format packed float 018 * @return an RGBA-format packed float 019 */ 020 public static float hsl2rgb(final float hsla) { 021 final int decoded = NumberUtils.floatToRawIntBits(hsla); 022 return hsl2rgb((decoded & 0xFF) / 255f, (decoded >>> 8 & 0xFF) / 255f, (decoded >>> 16 & 0xFF) / 255f, (decoded >>> 24 & 0xFE) / 255f); 023 } 024 025 /** 026 * Converts the four HSLA components, each in the 0.0 to 1.0 range, to a packed float in RGBA format. 027 * @param h hue, from 0.0 to 1.0 028 * @param s saturation, from 0.0 to 1.0 029 * @param l lightness, from 0.0 to 1.0 030 * @param a alpha, from 0.0 to 1.0 031 * @return an RGBA-format packed float 032 */ 033 public static float hsl2rgb(final float h, final float s, final float l, final float a){ 034 float x = Math.min(Math.max(Math.abs(h * 6f - 3f) - 1f, 0f), 1f); 035 float y = h + (2f / 3f); 036 float z = h + (1f / 3f); 037 y -= (int)y; 038 z -= (int)z; 039 y = Math.min(Math.max(Math.abs(y * 6f - 3f) - 1f, 0f), 1f); 040 z = Math.min(Math.max(Math.abs(z * 6f - 3f) - 1f, 0f), 1f); 041 float v = (l + s * Math.min(l, 1f - l)); 042 float d = 2f * (1f - l / (v + 1e-10f)); 043 v *= 255f; 044 return NumberUtils.intBitsToFloat( 045 (int)(a * 127f) << 25 046 | (int)(v * MathUtils.lerp(1f, z, d)) << 16 047 | (int)(v * MathUtils.lerp(1f, y, d)) << 8 048 | (int)(v * MathUtils.lerp(1f, x, d)) 049 ); 050 } 051 /** 052 * Converts the four HSLA components, each in the 0.0 to 1.0 range, to RGBA and assigns them into changing. 053 * @param changing a non-null Color that will be modified 054 * @param h hue, from 0.0 to 1.0 055 * @param s saturation, from 0.0 to 1.0 056 * @param l lightness, from 0.0 to 1.0 057 * @param a alpha, from 0.0 to 1.0 058 * @return changing, after assignment 059 */ 060 public static Color hslColor(Color changing, final float h, final float s, final float l, final float a){ 061 float x = Math.min(Math.max(Math.abs(h * 6f - 3f) - 1f, 0f), 1f); 062 float y = h + (2f / 3f); 063 float z = h + (1f / 3f); 064 y -= (int)y; 065 z -= (int)z; 066 y = Math.min(Math.max(Math.abs(y * 6f - 3f) - 1f, 0f), 1f); 067 z = Math.min(Math.max(Math.abs(z * 6f - 3f) - 1f, 0f), 1f); 068 float v = (l + s * Math.min(l, 1f - l)); 069 float d = 2f * (1f - l / (v + 1e-10f)); 070 changing.set(v * MathUtils.lerp(1f, x, d), v * MathUtils.lerp(1f, y, d), v * MathUtils.lerp(1f, z, d), a); 071 return changing; 072 } 073 074 /** 075 * Converts a packed float in RGBA format to a packed float in "HSLA format" (hue, saturation, lightness, alpha), 076 * which isn't one of the regular formats this supports but can be useful for conversions. 077 * @param rgba an RGBA-format packed float 078 * @return an "HSLA-format" packed float 079 */ 080 public static float rgb2hsl(final float rgba) { 081 final int decoded = NumberUtils.floatToRawIntBits(rgba); 082 return rgb2hsl((decoded & 0xFF) / 255f, (decoded >>> 8 & 0xFF) / 255f, (decoded >>> 16 & 0xFF) / 255f, (decoded >>> 24 & 0xFE) / 255f); 083 } 084 085 /** 086 * Converts the four RGBA components, each in the 0.0 to 1.0 range, to a packed float in "HSLA format" (hue, 087 * saturation, lightness, alpha), which isn't one of the regular formats this supports but can be useful for 088 * conversions. 089 * @param r red, from 0.0 to 1.0 090 * @param g green, from 0.0 to 1.0 091 * @param b blue, from 0.0 to 1.0 092 * @param a alpha, from 0.0 to 1.0 093 * @return an "HSLA-format" packed float 094 */ 095 public static float rgb2hsl(final float r, final float g, final float b, final float a) { 096 float x, y, z, w; 097 if(g < b) { 098 x = b; 099 y = g; 100 z = -1f; 101 w = 2f / 3f; 102 } 103 else { 104 x = g; 105 y = b; 106 z = 0f; 107 w = -1f / 3f; 108 } 109 if(r < x) { 110 z = w; 111 w = r; 112 } 113 else { 114 w = x; 115 x = r; 116 } 117 float d = x - Math.min(w, y); 118 float l = x * (1f - 0.5f * d / (x + 1e-10f)); 119 return Color.toFloatBits(Math.abs(z + (w - y) / (6f * d + 1e-10f)), (x - l) / (Math.min(l, 1f - l) + 1e-10f), l, a); 120 } 121 122 123 /** 124 * Given a color stored as a packed float and an alpha multiplier to affect that color (between 0f and 1f, inclusive 125 * and clamped in that range), this makes a packed float color that has the same red, green, and blue channels but 126 * has its own alpha multiplied by {@code alpha}, without constructing any objects along the way. If you want to set 127 * the alpha without considering its current value, you can use {@link #setAlpha(float, float)} 128 * 129 * @param encodedColor a color encoded as a packed float, as by {@link ColorTools#ycwcm(float, float, float, float)} 130 * or {@link com.github.tommyettinger.colorful.ipt.ColorTools#ipt(float, float, float, float)} 131 * @param alpha between 0.0 and 1.0 inclusive, the alpha to multiply the color's own alpha by 132 * @return a color encoded as a packed float, using color's RGB channels but with its A channel times {@code alpha} 133 */ 134 public static float multiplyAlpha(final float encodedColor, final float alpha) { 135 final int bits = NumberUtils.floatToRawIntBits(encodedColor); 136 return NumberUtils.intBitsToFloat(bits & 0xFFFFFF 137 | (Math.min(Math.max((int) ((bits >>> 24) * alpha), 0), 255) << 24 & 0xFE000000)); 138 } 139 140 /** 141 * Given a color stored as a packed float, and a desired alpha to set for that color (between 0.0 and 1.0, inclusive 142 * and clamped in that range), this makes a new float that has the same red, green, and blue channels but has been 143 * set to the given alpha, without constructing any objects along the way. This does not consider the current alpha 144 * of the encoded color; if you want to do that, you can use {@link #multiplyAlpha(float, float)}. 145 * 146 * @param encodedColor a color encoded as a packed float, as by {@link ColorTools#ycwcm(float, float, float, float)} 147 * or {@link com.github.tommyettinger.colorful.ipt.ColorTools#ipt(float, float, float, float)} 148 * @param alpha between 0.0 and 1.0 inclusive, the alpha to set into the returned packed color 149 * @return another color encoded as a packed float, using encodedColor's RGB channels and the given alpha 150 */ 151 public static float setAlpha(final float encodedColor, final float alpha) { 152 return NumberUtils.intBitsToFloat(NumberUtils.floatToRawIntBits(encodedColor) & 0xFFFFFF 153 | (Math.min(Math.max((int) (255f * alpha), 0), 255) << 24 & 0xFE000000)); 154 } 155 156 /** 157 * Interpolates from the packed float color start towards end by change. Both start and end should be packed colors, 158 * as from {@link com.github.tommyettinger.colorful.oklab.ColorTools#oklab(float, float, float, float)} or 159 * {@link com.github.tommyettinger.colorful.ipt.ColorTools#ipt(float, float, float, float)}, and change can be 160 * between 0f (keep start) and 1f (only use end). Both start and end should use the same color space; that is, both 161 * could be produced using Oklab, both could be produced using IPT, or both could be libGDX-native RGB, but they 162 * can't mix. This is a good way to reduce allocations of temporary Colors. 163 * @param start the starting color as a packed float 164 * @param end the target color as a packed float 165 * @param change how much to go from start toward end, as a float between 0 and 1; higher means closer to end 166 * @return a packed float that represents a color between start and end 167 */ 168 public static float lerpFloatColors(final float start, final float end, float change) { 169 final int s = NumberUtils.floatToRawIntBits(start), e = NumberUtils.floatToRawIntBits(end), 170 ys = (s & 0xFF), cws = (s >>> 8) & 0xFF, cms = (s >>> 16) & 0xFF, as = s >>> 24 & 0xFE, 171 ye = (e & 0xFF), cwe = (e >>> 8) & 0xFF, cme = (e >>> 16) & 0xFF, ae = e >>> 24 & 0xFE; 172 return NumberUtils.intBitsToFloat(((int) (ys + change * (ye - ys)) & 0xFF) 173 | (((int) (cws + change * (cwe - cws)) & 0xFF) << 8) 174 | (((int) (cms + change * (cme - cms)) & 0xFF) << 16) 175 | (((int) (as + change * (ae - as)) & 0xFE) << 24)); 176 } 177 178 /** 179 * Interpolates from the packed float color start towards end by change, but keeps the alpha of start and uses the 180 * alpha of end as an extra factor that can affect how much to change. Both start and end should be packed colors, 181 * as from {@link com.github.tommyettinger.colorful.ipt_hq.ColorTools#ipt(float, float, float, float)} or 182 * {@link ColorTools#ycwcm(float, float, float, float)}, and change can be between 0f (keep start) and 1f (only use 183 * end). Both start and end should use the same color space; that is, both could be produced using IPT_HQ, or both 184 * could be produced using YCwCm, but not a mix of the two. This is a good way to reduce allocations of temporary 185 * Colors. 186 * @param start the starting color as a packed float; alpha will be preserved 187 * @param end the target color as a packed float; alpha will not be used directly, and will instead be multiplied with change 188 * @param change how much to go from start toward end, as a float between 0 and 1; higher means closer to end 189 * @return a packed float that represents a color between start and end 190 */ 191 public static float lerpFloatColorsBlended(final float start, final float end, float change) { 192 final int s = NumberUtils.floatToRawIntBits(start), e = NumberUtils.floatToRawIntBits(end), 193 ys = (s & 0xFF), cws = (s >>> 8) & 0xFF, cms = (s >>> 16) & 0xFF, as = s >>> 24 & 0xFE, 194 ye = (e & 0xFF), cwe = (e >>> 8) & 0xFF, cme = (e >>> 16) & 0xFF; 195 change *= (e >>> 25) * 0.007874016f; 196 return NumberUtils.intBitsToFloat(((int) (ys + change * (ye - ys)) & 0xFF) 197 | (((int) (cws + change * (cwe - cws)) & 0xFF) << 8) 198 | (((int) (cms + change * (cme - cms)) & 0xFF) << 16) 199 | as); 200 } 201 202 /** 203 * Returns a 1:1 mix of color0 and color1. All colors should use the same color space. 204 * This is the same as calling {@link #lerpFloatColors(float, float, float)} with a change of 0.5. 205 * @param color0 the first color to mix, as a packed float color 206 * @param color1 the second color to mix, as a packed float color 207 * @return an even mix of all colors given, as a packed float color 208 */ 209 public static float mix(float color0, float color1) { 210 return lerpFloatColors(color0, color1, 0.5f); 211 } 212 213 /** 214 * Returns a 1:1:1 mix of color0, color1, and color2. All colors should use the same color space. 215 * @param color0 the first color to mix, as a packed float color 216 * @param color1 the second color to mix, as a packed float color 217 * @param color2 the third color to mix, as a packed float color 218 * @return an even mix of all colors given, as a packed float color 219 */ 220 public static float mix(float color0, float color1, float color2) { 221 return lerpFloatColors(lerpFloatColors(color0, color1, 0.5f), color2, 0.33333f); 222 } 223 224 /** 225 * Returns a 1:1:1:1 mix of color0, color1, color2, and color3. All colors should use the same color space. 226 * @param color0 the first color to mix, as a packed float color 227 * @param color1 the second color to mix, as a packed float color 228 * @param color2 the third color to mix, as a packed float color 229 * @param color3 the fourth color to mix, as a packed float color 230 * @return an even mix of all colors given, as a packed float color 231 */ 232 public static float mix(float color0, float color1, float color2, float color3) { 233 return lerpFloatColors(lerpFloatColors(lerpFloatColors(color0, color1, 0.5f), color2, 0.33333f), color3, 0.25f); 234 } 235 236 /** 237 * Given several colors, this gets an even mix of all colors in equal measure. 238 * If {@code colors} is null or has no items, this returns 0f (usually transparent in most color spaces). 239 * @param colors an array or varargs of packed float colors; all should use the same color space 240 * @return an even mix of all colors given, as a packed float color 241 */ 242 public static float mix(float... colors) { 243 if(colors == null || colors.length == 0) 244 return 0f; // transparent, usually 245 float result = colors[0]; 246 for (int i = 1; i < colors.length; i++) { 247 result = lerpFloatColors(result, colors[i], 1f / (i + 1f)); 248 } 249 return result; 250 } 251 252 /** 253 * Given several colors, this gets an even mix of all colors in equal measure. 254 * If {@code colors} is null or has no items, this returns 0f (usually transparent in most color spaces). 255 * This is mostly useful in conjunction with {@link com.badlogic.gdx.utils.FloatArray}, using its {@code items} 256 * for colors, typically 0 for offset, and its {@code size} for size. 257 * @param colors an array of packed float colors; all should use the same color space 258 * @param offset the index of the first item in {@code colors} to use 259 * @param size how many items from {@code colors} to use 260 * @return an even mix of all colors given, as a packed float color 261 */ 262 public static float mix(float[] colors, int offset, int size) { 263 final int end = offset + size; 264 if(colors == null || colors.length < end || offset < 0 || size <= 0) 265 return 0f; // transparent, usually 266 float result = colors[offset]; 267 for (int i = offset + 1, denom = 2; i < end; i++, denom++) { 268 result = lerpFloatColors(result, colors[i], 1f / denom); 269 } 270 return result; 271 } 272}


Meryl Streep’s THIS Film Inspired Richa Chadha To Experiment With Her Accent
Richa also uses a different perfume for every character.
by IANSRicha Chadha says when she saw veteran Hollywood star Meryl Streep master the Polish, Dutch and the Queen’s English for three different films, the Bollywood actress was inspired.
“When I saw Meryl Streep master the Polish accent for ‘Sophie’s Choice’, the Dutch accent for ‘Out of Africa’, the Bronx accent for ‘Doubt’ and the Queen’s English for ‘Iron Lady’, I was so inspired,” Richa said.
Much like Streep who loves working on different voices and accents, Richa too works extensively on diction and accent.
For “Fukrey” she mastered the Delhi lingo, then for “Gangs of Wasseypur” it was the Bhojpuri twang, for “Masaan” it was Hindustani spoken in Uttar Pradesh, with more focus on Hindi, Gujarati accent for “Goliyon Ki Raasleela… Ram-Leela” and the Bambaiya for “Love Sonia” and “Abhi to Party Shuru Hui Hai”.
Richa will be learning some new skills for an upcoming film to be shot in Uttar Pradesh.
“The thrill about acting is being able to become those different people for that duration. For me it is therapeutic. It is me and yet not me. I work on things like accents and voices because I feel that’s something I can control. It’s working from the outside in. For this, I am trying a newer voice and accent, which is great! I like that I don’t sound like myself,” she said.
Richa also uses a different perfume for every character.
“An idea I hear many of my colleagues have been ‘inspired’ by recently. For this one, I am using a blend of honey, vanilla and oudh.”


I am a UQ graduate looking to start my career in web development.
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Completed a Bachelor of Information Technology Degree, with a major in Computer Systems and Networks with a GPA of 5.458.
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W3C is an international community for developing web standards. W3C is led by CEO Jeffrey Jaffe and Director Tim Berners Lee. W3C works with the stakeholders,members and the public to make sure the standards developed are in consensus with everyone. CSS and HTML are some of the many standards developed by W3C
HTML (the Hypertext Markup Language) and CSS (Cascading Style Sheets) are some of the most essential technologies for building a web page. HTML is the markup language used to display information on the web page. While HTML gives structure to the page, CSS is used to style the web page.
When a browser sends an http/https request to the host server, the html and css files will be returned to the browser. The browser will render this HTML and CSS pages to the user. Using HTML tags we can add headings, paragraphs, lists, links , images and input fields to a page making it more interactive and user friendly.
While HTML is used to provide structure to the page CSS is used to define the styles like color, position, height, width etc to the page. Multiple HTML pages can share the same CSS style by including the same CSS file.


This will increase all of the prices of players, add a year to their contract, and move all players to unselected
Get file
Batch Upload
Mark Old Players
Input a csv of new players for the year and hit submit. This function will compare all players against the new list and mark old players with a ranking of 999
Find players with no owners and zero out their price and years played
Go back and make sure that all of the players are associated with their owners
Find players with an owner but a price of 0 (waiver pickup), and change years owned to 1 and price to 1.1


In this lesson we’re going to take a closer look at the GenStage, what role it serves, and how we can leverage it in our applications.
Table of Contents
Introduction
So what is GenStage? From the official documentation, it is a “specification and computational flow for Elixir”, but what does that mean to us?
What it means is that GenStage provides a way for us to define a pipeline of work to be carried out by independent steps (or stages) in a separate processes; if you’ve worked with pipelines before then some of these concepts should be familiar.
To better understand how this works, let’s visualize a simple producer-consumer flow:
[A] -> [B] -> [C]
In this example we have three stages: A
a producer, B
a producer-consumer, and C
a consumer.
A
produces a value which is consumed by B
, B
performs some work and returns a new value which is received by our consumer C
; the role of our stage is important as we’ll see in the next section.
While our example is 1-to-1 producer-to-consumer it’s possible to both have multiple producers and multiple consumers at any given stage.
To better illustrate these concepts we’ll be constructing a pipeline with GenStage but first let’s explore the roles that GenStage relies upon a bit further.
Consumers and Producers
As we’ve read, the role we give our stage is important. The GenStage specification recognizes three roles:
-
:producer
— A source. Producers wait for demand from consumers and respond with the requested events. -
:producer_consumer
— Both a source and a sink. Producer-consumers can respond to demand from other consumers as well as request events from producers. -
:consumer
— A sink. A consumer requests and receives data from producers.
Notice that our producers wait for demand? With GenStage our consumers send demand upstream and process the data from our producer. This facilitates a mechanism known as back-pressure. Back-pressure puts the onus on the producer to not over-pressure when consumers are busy.
Now that we’ve covered the roles within GenStage let’s start on our application.
Getting Started
In this example we’ll be constructing a GenStage application that emits numbers, sorts out the even numbers, and finally prints them.
For our application we’ll use all three GenStage roles. Our producer will be responsible for counting and emitting numbers. We’ll use a producer-consumer to filter out only the even numbers and later respond to demand from downstream. Last we’ll build a consumer to display the remaining numbers for us.
We’ll begin by generating a project with a supervision tree:
$ mix new genstage_example --sup
$ cd genstage_example
Let’s update our dependencies in mix.exs
to include gen_stage
:
defp deps do
[
{:gen_stage, "~> 1.0.0"},
]
end
We should fetch our dependencies and compile before going much further:
$ mix do deps.get, compile
Now we’re ready to build our producer!
Producer
The first step of our GenStage application is creating our producer. As we discussed before, we want to create a producer that emits a constant stream of numbers. Let’s create our producer file:
$ touch lib/genstage_example/producer.ex
Now we can add the code:
defmodule GenstageExample.Producer do
use GenStage
def start_link(initial \\ 0) do
GenStage.start_link(__MODULE__, initial, name: __MODULE__)
end
def init(counter), do: {:producer, counter}
def handle_demand(demand, state) do
events = Enum.to_list(state..(state + demand - 1))
{:noreply, events, state + demand}
end
end
The two most important parts to take note of here are init/1
and handle_demand/2
.
In init/1
we set the initial state as we’ve done in our GenServers, but more importantly we label ourselves as a producer.
The response from our init/1
function is what GenStage relies upon to classify our process.
The handle_demand/2
function is where the majority of our producer is defined.
It must be implemented by all GenStage producers.
Here we return the set of numbers demanded by our consumers and increment our counter.
The demand from consumers, demand
in our code above, is represented as an integer corresponding to the number of events they can handle; it defaults to 1000.
Producer Consumer
Now that we have a number-generating producer, let’s move on to our producer-consumer. We’ll want to request numbers from our producer, filter out the odd one, and respond to demand.
$ touch lib/genstage_example/producer_consumer.ex
Let’s update our file to look like the example code:
defmodule GenstageExample.ProducerConsumer do
use GenStage
require Integer
def start_link(_initial) do
GenStage.start_link(__MODULE__, :state_doesnt_matter, name: __MODULE__)
end
def init(state) do
{:producer_consumer, state, subscribe_to: [GenstageExample.Producer]}
end
def handle_events(events, _from, state) do
numbers =
events
|> Enum.filter(&Integer.is_even/1)
{:noreply, numbers, state}
end
end
You may have noticed with our producer-consumer we’ve introduced a new option in init/1
and a new function: handle_events/3
.
With the subscribe_to
option, we instruct GenStage to put us into communication with a specific producer.
The handle_events/3
function is our workhorse, where we receive our incoming events, process them, and return our transformed set.
As we’ll see consumers are implemented in much the same way, but the important difference is what our handle_events/3
function returns and how it’s used.
When we label our process a producer_consumer, the second argument of our tuple — numbers
in our case — is used to meet the demand of consumers downstream.
In consumers this value is discarded.
Consumer
Last but not least we have our consumer. Let’s get started:
$ touch lib/genstage_example/consumer.ex
Since consumers and producer-consumers are so similar our code won’t look much different:
defmodule GenstageExample.Consumer do
use GenStage
def start_link(_initial) do
GenStage.start_link(__MODULE__, :state_doesnt_matter)
end
def init(state) do
{:consumer, state, subscribe_to: [GenstageExample.ProducerConsumer]}
end
def handle_events(events, _from, state) do
for event <- events do
IO.inspect({self(), event, state})
end
# As a consumer we never emit events
{:noreply, [], state}
end
end
As we covered in the previous section, our consumer does not emit events, so the second value in our tuple will be discarded.
Putting It All Together
Now that we have our producer, producer-consumer, and consumer built, we’re ready to wire everything together.
Let’s start by opening lib/genstage_example/application.ex
and adding our new processes to the supervisor tree:
def start(_type, _args) do
import Supervisor.Spec, warn: false
children = [
{GenstageExample.Producer, 0},
{GenstageExample.ProducerConsumer, []},
{GenstageExample.Consumer, []}
]
opts = [strategy: :one_for_one, name: GenstageExample.Supervisor]
Supervisor.start_link(children, opts)
end
If things are all correct, we can run our project and we should see everything working:
$ mix run --no-halt
{#PID<0.109.0>, 0, :state_doesnt_matter}
{#PID<0.109.0>, 2, :state_doesnt_matter}
{#PID<0.109.0>, 4, :state_doesnt_matter}
{#PID<0.109.0>, 6, :state_doesnt_matter}
...
{#PID<0.109.0>, 229062, :state_doesnt_matter}
{#PID<0.109.0>, 229064, :state_doesnt_matter}
{#PID<0.109.0>, 229066, :state_doesnt_matter}
We did it! As we expected our application only omits even numbers and it does so quickly.
At this point we have a working pipeline. There is a producer emitting numbers, a producer-consumer discarding odd numbers, and a consumer displaying all of this and continuing the flow.
Multiple Producers or Consumers
We mentioned in the introduction that it was possible to have more than one producer or consumer. Let’s take a look at just that.
If we examine the IO.inspect/1
output from our example we see that every event is handled by a single PID.
Let’s make some adjustments for multiple workers by modifying lib/genstage_example/application.ex
:
children = [
{GenstageExample.Producer, 0},
{GenstageExample.ProducerConsumer, []},
%{
id: 1,
start: {GenstageExample.Consumer, :start_link, [[]]}
},
%{
id: 2,
start: {GenstageExample.Consumer, :start_link, [[]]}
},
]
Now that we’ve configured two consumers, let’s see what we get if we run our application now:
$ mix run --no-halt
{#PID<0.120.0>, 0, :state_doesnt_matter}
{#PID<0.120.0>, 2, :state_doesnt_matter}
{#PID<0.120.0>, 4, :state_doesnt_matter}
{#PID<0.120.0>, 6, :state_doesnt_matter}
...
{#PID<0.120.0>, 86478, :state_doesnt_matter}
{#PID<0.121.0>, 87338, :state_doesnt_matter}
{#PID<0.120.0>, 86480, :state_doesnt_matter}
{#PID<0.120.0>, 86482, :state_doesnt_matter}
As you can see we now have multiple PIDs, simply by adding a line of code and giving our consumers IDs.
Use Cases
Now that we’ve covered GenStage and built our first example application, what are some of the real use cases for GenStage?
-
Data Transformation Pipeline — Producers don’t have to be simple number generators. We could produce events from a database or even another source like Apache’s Kafka. With a combination of producer-consumers and consumers, we could process, sort, catalog, and store metrics as they become available.
-
Work Queue — Since events can be anything, we could produce units of work to be completed by a series of consumers.
-
Event Processing — Similar to a data pipeline, we could receive, process, sort, and take action on events emitted in real time from our sources.
These are just a few of the possibilities for GenStage.
Caught a mistake or want to contribute to the lesson? Edit this page on GitHub!


| public nothrow | Date() |
| public nothrow | Date(short year_, Month month_, sbyte day_) |
| public inline nothrow sbyte | Day() const |
| public inline nothrow Month | GetMonth() const |
| public nothrow String<char> | ToString() const |
| public nothrow String<char> | ToString(bool omitDashes) const |
| public inline nothrow short | Year() const |
| private sbyte | day |
| private Month | month |
| private short | year |


3 writes to _reconnecting
System.Management.Automation (3)
engine\remoting\client\RemotingProtocol2.cs (3)
47
_reconnecting
= false;
96
_reconnecting
= true;
582
_reconnecting
= false;
1 reference to _reconnecting
System.Management.Automation (1)
engine\remoting\client\RemotingProtocol2.cs (1)
579
else if (
_reconnecting
&& e.SessionStateInfo.State == RemoteSessionState.Established)


(in training)
Hello there! My name is Molly and I currently teach high school science in Maine. In anticipation for a future career change, I'm studying to be a full-stack web developer through the UNH Coding Boot Camp (along with some Edx and Udemy courses on the side).
In my spare time, I love to hang out with my dog Bodhi - teaching him tricks and taking him for walks on the beach or on the trails. I'm also interested in music, herbal medicine/natural health, yoga, social justice and the interconnectedness of all things.
Here is some more information about this product that is only revealed once clicked on.


EDM STUDIO
THE STUDIO THAT MAY DISTORY YOUR DREAM
What we can do
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Chapter 4 The normal distribution - what’s the point?
Many events can’t be predicted with total certainty. The best we can say is how likely they are to happen. Day to day, probability is often used to describe the world around. The chance of rain, the likelihood of our football team winning, or who will win the election. What do these statements actually mean and how are they calculated?
Hiding behind these statements is the idea of a probability distribution. This is a mathematical function that can be thought of as providing the probabilities of occurrence of different possible outcomes in an experiment. It is our way of trying to capture the real world using mathematics.
Probability is massive topic, that we cannot possibility hope to cover in a single chapter. Instead, the goal of this chapter is to give an intuitive feel for some of the standard probability distributions. Even if you have never taken a course in statistics, you’ll have come the simplest probability distribution already, the Uniform distribution. This distribution represents the situation where all events are equally likely
The most famous distribution is the Normal or Gaussian distribution. Instead of producing this distribution from thin air, we will provide some background to explain how this distribution naturally arises with few assumptions. In later chapters, the Normal distribution will form the basis for our inferential models.
Do I need to know this for data science? There are many people who no little about distributions, but “do data science”. In my opinion, having insight in the foundations will help you understand the subject, and hence allow you to build better models.
As an analogy, you can build web-pages using tools without knowing any HTML, CSS, or Javascript. However there comes a point where knowing the underlying technology is essential.
4.1 The Bernoulli distribution
The simplest distribution is the Bernoulli distribution. It models events that have only two outcomes. For example, your football team will either win or not. Since there are a countable number of events, this is a discrete distribution. This distribution forms the building block for all other distributions.
4.1.1 Motivating example
Suppose you are using a well know cloud provider. Reading the small print, they state that the chance of downtime on any particular day, is 0.001. What is the probability of having no downtime throughout the year?
4.1.2 Description
The easiest way to think of the Bernoulli distribution is to toss a (fair) coin. We have equally likely outcomes: heads and tails. Since they are equally likely, the probability6 of getting either event is 0.5. This means on average, 50% of throws will be heads and 50% of throws will be tails. The distribution that describes a coin throw is known as the Bernoulli distribution named after the Swiss scientist Jacob Bernoulli.
Mathematically we would describe the Bernoulli distribution as follows. Suppose \(X\) is a random variable7, then we have \[ \Pr(X = 0) = 1 - p \quad \text{and} \quad \Pr(X = 1) = p. \] Note that the total probability sums to \(1\), i.e. when we toss a coin, we will observe either a head or a tail.
If we simulated or observed a series of ten Bernoulli trials where \(p = 0.5\), this means we observe a series of \(0\)’s and \(1\)’s that follow the above probability distribution. It would look something like
0 0 1 0 0 1 0 1 0 0
Notice that we don’t have exactly \(5\) ones. Instead, the probability distribution tells us that on average we’ll observe \(5\) ones.
Beware of the law of averages. Basically, just because you observe 3 heads in a row, the chance of observing a fourth head is still 0.5.
4.1.3 Example
Suppose you are using a data centre where the probability of failure is 0.001 per day. That means the probability of the data centre working is 0.999 per day. So the probability that the data centre will work two days in a row is \(0.999 \times 0.999 = 0.998\). The probability that it will work every day for a year is \[ 0.999 \times 0.999 \times \ldots = 0.999^{365} = 0.694. \]That means that even though we only expect one failure every one thousand days. The chance of a failure happening in the coming year is approximately 1 in 3, or \(1- 0.694 \simeq 0.3.\)
4.2 The Binomial distribution
4.2.1 Motivating example
You are in charge of back-ups. Looking at a recent study you estimate the chance of a particular hard drive failing within one year to be 5% (or 0.05). Your organisation has around 1,000 hard drives. You would like to know
- How many hard drives are likely to fail this year?
- Can we get a reasonable upper limit for the number of failures?
4.2.2 Description
The Binomial distribution is an extension to the Bernoulli distribution. The Binomial distribution concerns sums of Bernoulli random variables. So in our our above example we have \[ 0 + 0 + 1 + 0 + 0 + 1 + 0 + 1 + 0 + 0 = 3 \] The Binomial distribution has two parameters, \(n\) the number of trials and \(p\) the probability of success. The probability of getting exactly \(k\) successes in \(n\) trials is given by \[ \Pr(X = k) = \binom{n}{k} p^k (1-p)^{n-k} \] where \[ \binom {n}{k} = \frac {n!}{k!(n-k)!} \] and \(n! = n \times (n-1) \times (n-2) \times (n-3) \ldots\). Notice that when \(n = 1\), the Binomial distribution just becomes the Bernoulli distribution: \[ \Pr(X = 0) = \binom{1}{0} p^0 (1-p)^{1-0} = 1 \times 1 \times (1-p) = (1-p) . \] With a little bit of mathematics, we can show that if we performed \(n\) experiments, with each experiment having probability \(p\) of success, then the mean number of successful outcomes is \(n \times p\) and the variance is \(n \times p \times (1 - p)\).
4.2.3 What does the Binomial distribution look like?
Let’s take a concrete example of \(n = 100\) and \(p = 0.25\), \(0.5\) and \(0.75\). The probability distributions are shown in figure 4.1.
Some points to note:
- The sum of points in each plot in figure 4.1 is \(1\). It’s a probability mass function, so it must sum to 1.
- The distribution is centred around the mean, \(n \times p\). So when \(p=0.5\), the plot is centred around \(50\).
- There is some variation around the mean. Again we can be more precise and state that the variance is \(n \times p \times (1-p)\). So when \(p = 0.5\), the variance is \(n/4 = 100/4 = 25\)
4.2.4 Motivating example
In our example we have \(n = 1000\) hard drives that fail with rate \(p = 0.05\). On average we would expect \(n \times p = 1000 \times 0.05 = 50\) failures per year. To obtain an upper bound, we would look at the cumulative distribution, that is,
\[ Pr(X \le k) = Pr(X = 0) + Pr(X = 1) + \ldots + Pr(X = k) \]
This is easily done in R. The function pbinom()
calculates the probability of observing less than or equal to the value of it’s first argument. So to obtain a reasonable upper bound, we calculate the cumulative probability from \(0\) to \(1000\) and determine where it crosses the 0.99 probability threshold
n = 1000; p = 0.05
which(pbinom(0:n, n, p) > 0.99)[1]
#> [1] 68
Hence the probability that we observe more than \(67\) failures in one year is less that 0.01. So while the mean number of failures is 50, a reasonable upper bound would be 67.
4.3 The Normal/Gaussian distribution
A number of mathematicians contributed to the development of this distribution. The distributions namesake, Carl Friedrich Gauss was a German mathematician who developed a number of key statistical concepts, such as least squares optimisation.
The Normal distribution (or Gaussian) distribution is perhaps the most famous probability distribution. The previous distributions have been discrete, the Normal distribution is a continuous distribution. It takes the form \[ f_X(x) = \frac{1}{\sqrt{2 \pi \sigma^2}} e^{- \frac{(x - \mu)^2}{2 \sigma^2}} \] where
- \(\mu\) is the mean or expectation of the distribution (and also its median and mode);
- \(\sigma\) is the standard deviation;
- \(\sigma^2\) is the variance.
The standard normal distribution (figure 4.2) is a special case of the normal distribution where \(\mu = 0\) and \(\sigma = 1\) \[ f_X(x) = \frac{1}{\sqrt{2 \pi}} e^{- \frac{x^2}{2}} \]
The distribution can be derived in a variety of ways, but the easiest is as a special case of the Binomial distribution. Letting \(n\) get large (basically when \(n > 20\)), and provided \(p\) isn’t too close to \(0\) or \(1\), the normal distribution is almost identical to the Binomial. Again, we can use mathematics to show that the binomial distribution converges to the normal, but to avoid unnecessary mathematical detail, we’ll just use a few plots (figure 4.3).
4.3.1 Continuous and discrete distributions
The Binomial and Bernoulli are examples of discrete distributions. A discrete distribution gives you the probability of observing a particular event such as rolling a dice or tossing a coin. For a discrete distribution, the probabilities will sum to \(1\), e.g. we will either get a head or tail, but one of the two events must happen.
A continuous distribution is a bit different. Looking at the formula for the normal distribution we see that it is valid for all values of \(x\). That means if we added up \(f_X(x)\) for all values of \(x\), we would reach \(\infty\), since \(x\) has infinitely many decimal places. Instead, for continuous distributions we look at area under the curve. So the area under the normal distribution sums (or integrates) to one.
4.3.2 The standard deviations rule
When your data are normally distribution, then the
- mean \(\pm\) 1 standard deviation: \(\simeq\) 70% of data;
- mean \(\pm\) 2 standard deviation: \(\simeq\) 95% of data;
- mean \(\pm\) 3 standard deviation: \(\simeq\) 99.9% of data.
This is way the mean and variance are useful summary statistics.
4.3.3 The Z-Score
The \(z\)-score is where we transform, or scale, the dataset to have mean \(0\) and variance \(1\). If our original data is \(x\), then our transformed data \(z\) is defined as \[ z = \frac{x - \bar x}{s} \] where \(\bar x\) is the mean of \(x\) and \(s\) is the standard deviation. The transformed data tells us how many standard deviations above or below the mean each data point is. If our data is normal, this would produce a standard normal distribution.
This is also known as “slide and squash rule”. Looking at the OKCupid data set again. The original distribution of ages is shown in figure 4.4 a.
- Subtract the mean, slides the distribution to \(0\) - figure 4.4 b.
- Dividing by the standard deviation, squashes the distribution to have a variance of \(1\) - figure 4.4 c.
Using \(Z\)-scores is a standard technique to put different variables on the same scale. This also helps many machine learning algorithms converge quicker.


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rebuild_by_x.Rd
takes a performance goal (what level you want to rebuild to) and a time window (how long you want that to take) and calculates what the bycatch rate needs to be
rebuild_by_x( needf.start, init.depl.w, goal.w, desired.prob.w, when.w, lh.params.w, fixed.cv.catch.w )
| needf.start | starting guess for the bycatch mortality rate needed to recover the population |
|---|---|
| init.depl.w | initial depletion (a fraction) |
| goal.w | Population size goal (number of whales or pinnipeds) to rebuild to, expressed as a whole number |
| desired.prob.w | what probability you want (e.g., 0.75 probability that the population will rebuild to X in Y years) |
| when.w | the year Y when rebuilding is desired by (number of years into future; current year = 0) |
| lh.params.w | a list of life history parameters used by |
| fixed.cv.catch.w | the CV of the bycatch rate - should be fixed |
The bycatch rate that will result in the specified rebuilding goal. If Shiny is running, it will return a list containing the bycatch rate f
and a matrix of guesses that optim()
has searched through to find the solution.
rebuild_by_x( needf.start = 0.001, init.depl.w = 0.5, goal.w = 4500, desired.prob.w = 0.8, when.w = 100, lh.params.w = list( S0 = 0.944, S1plus = 0.99, AgeMat = 17, nages = 19, z = 2.39, lambdaMax = 1.04, K1plus = 9000 ), fixed.cv.catch.w = 0 )#> [1] 0.03346646


31+ Roman Numeral Logo Images. What is 4 in roman numerals. Addition is the main rule.
I'm working on a work file and i have to make a numbered list with roman number in html but i don't now how i can do it. Addition is the main rule. Teachers and kids like our printable roman numerals chart and roman numeral conversion sometimes your math students need a roman numerals chart to remember what number goes with.
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Find this pin and more on diy by lori brooks. Check out our roman numeral ring selection for the very best in unique or custom, handmade pieces from our stackable rings shops. See more of roman numerals on facebook. What each of the seven letters (i, v, x, l, c, d and m) mean and their arabic.


Head OfficeAnchor Tower, 108 Bir Uttam C R Dutta, Dhaka 1205, Bangladesh Known AsHSBC SWIFT CodeHSBCBDDH CategoryCommercial TypePrivate OriginForeign Description The Hongkong and Shanghai banking Corporation (HSBC) started its financial activities in Bangladesh with a debutant branch in 1996. Now in 2011 it’s at your neighborhood through 13 offices. 39 ATMs and 9 Customer Service Centers are providing its clients with world class service all the time. More over it has one offshore bank and offices at 7 EPZs of the country. Deposit Accounts and Schemes As a normal banking practice HSBC has provisions for Current account and Savings account for its clients. So you may have any or both of these accounts in HSBC. In addition the bank has several attractive schemes for deposit. These are: Smart Savers Plan Savings Plus Savings Extra Term Deposit Monthly Interest Bearing Time Deposit Education Saving Plan Most of these schemes provide good interest rates and encourage people to save more, and face future challenges smoothly. Monthly Interest Bearing Time Deposit is supposed to be availed by senior citizens of the society. Those who are in retired life may deposit a good amount from their service benefits and earn an amount every month to ease their hardship. So you may pursue one of the schemes from the above list that seems to be suitable for you. Credit Schemes Credit Schemes of HSBC may be classified in two groups. These are Personal credit and Corporate Loans. You are qualified for certain personal loans if you fulfill some conditions. The conditions seem to be very logical as you have to pay the loan back within a time frame. The personal credits are named as follows: Home Loan Home Equity Loan Any purpose Loan Car Loan Personal Secured Loan Personal Secured Credit


---
layout: home
author_profile: true
---
Greetings! Welcome to my personal webpage.
I am a research faculty at the Inter-University Center for Astronomy and Astrophysics (IUCAA), Pune, India.
I share responsibilities for the upcoming LIGO-India gravitational wave detector as part of the gravitational wave research group at IUCAA.
You can find more about my academic background here.
My research activities and interests here.
Feel free to drop in an email if you would like to know more about my research or wondering how to get involved.


Here is some revised info for the district crit. The cities reconstruction
schedule for sixth avenue forced a venue change. The new info is included
in the attached WinZIP file. Please e-mail or call me at 457-8252 or
442-0877 if you have any questions,
Thanks Again,
Joel
CLICK HERE FOR RACE INFO


US-China Physical-Sciences Oncology Alliance
The U.S.-China Physical Sciences-Oncology Alliances (PS-OA) is the ﬁrst international alliance to focus on research at the intersection of the physical sciences and cancer biology for the expressed purpose of increasing our fundamental understanding of cancer as a basis for early detection, more effective therapy and ultimately prevention. The mission is to bring a diverse group of experts in cancer research to discuss promising aspects of future research and potential international collaborations. The goal is not limited to speciﬁc research, but to encourage a longer and broader vision to rethink cancer on its precaution, origin, evolution and novel treatment. Early research emphasis areas for the U.S.-China PSOA will include cancer evolution/evolutionary cancer medicine, computational models of cancer and selected areas of cancer genome research.
DIRECTORS
Robert H.Austin
Director
Pinceton Physical
Science-Oncology Center
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Liyu Liu, PhD.
Excutive Director
Institute of Physics
Chinese Academy of Sciences
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STEERING COMMITTEE
Anna Barker,PhD.
Arizona State University
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Baylor College of Medicine
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THE PREACHER'S WIFE A film review by Michael John Legeros Copyright 1996 Michael John Legeros
(Touchstone) Directed by Penny Marshall Written by Nat Mauldin and Allan Scott based on a screenplay by Robert E. Sherwood and Leonardo Bercovici Cast Denzel Washington, Whitney Houston, Courtney B. Vance, Gregory Hines, Jenifer Lewis, Loretta Devine, Justin Pierre Edmund MPAA Rating "PG" Running Time 124 minutes Reviewed at General Cinemas at Pleasant Valley, Raleigh, NC (8DEC96)
==
Another long sit. Director Penny Marshall's all-black, sometimes- musical remake of THE BISHOP'S WIFE-- the 1947 Best Picture nominee that starred Cary Grant as an angel who arrives on Earth to assist a man of the cloth-- is a good twenty minutes too long. Maybe thirty. The padding is obvious in the musical numbers, of which there are at least eight. (I lost count.) Most of the singing is done by Whitney Huston, whose character commands a church choir. (Her voice soars, but her acting doesn't. Neither she nor co-star Courtney B. Vance appear excited about anything in this romantic holiday comedy.) The forced fuzzies are also overkill. From foster homes to fidelity, every con- ceivable crisis is confronted and given a cheery resolution. The jokes are funny, thank good- ness, and there's a Microsoft gag midway through that's worth the price of admission. Even with a nice performance by Denzel Washington, who plays the visiting spirit, and some occasionally impressive supporting work, I still wanted to go home and strangle my Tickle Me Elmo.
Grade: B-
--
Mike Legeros - Raleigh, NC, USA, Earth<EMAIL_ADDRESS>(h) -<EMAIL_ADDRESS>(w) I'm also on the Web! http://www.pagesz.net/~legeros/
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
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Related links: index of all rec.arts.movies.reviews reviews


---
layout: post
title: Chinese phonetics on http://www.mandarin-phonetics.co.cc/
date: '2009-08-10T14:56:00.003+02:00'
author: Libor Nenadál
tags:
modified_time: '2009-08-10T15:01:04.575+02:00'
blogger_id: tag:blogger.com,1999:blog-17453343.post-7084540928133932374
blogger_orig_url: http://saxuality.blogspot.com/2009/08/chinese-phonetics-on-httpwwwmandarin.html
---
Today I released a new Flash version of great page http://lost-theory.org/chinese/phonetics/. It uses Flash and Javascript to play Pin Yin syllables. You can try it at http://www.mandarin-phonetics.co.cc/.


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www.motherjones.com
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www.naftemporiki.gr
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www.ft.com
The latest UK and international business, finance, economic and political news, comment and analysis from the Financial Times on FT.com
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Y Combinator Teardown – YC Companies Have Raised $3.5 Billion To-Date
www.cbinsights.com
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blog.twitpic.com
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www.economist.com
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www.bloomberg.com
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nuzzel.com
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Bill Gates ALS Ice Bucket Challenge
www.youtube.com
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www.hellasverona.it
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