Lo I the man, whose Muse whilome did maske,
As time her taught in lowly Shepheards weeds,
Am now enforst a far unfitter taske,
For trumpets sterne to chaunge mine Oaten reeds,
And sing of Knights and Ladies gentle deeds;
Whose prayses having slept in silence long,
Me, all too meane, the sacred Muse areeds
To blazon broad emongst her learned throng:
Fierce warres and faithful loves shall moralize my song.
Helpe then, O holy Virgin chiefe of nine,
Thy weaker Novice to performe thy will,
Lay forth out of thine everlasting scryne
The antique rolles, which there lye hidden still,
Of Faerie knights and fairest Tanaquill,
Whom that most noble Briton Prince so long
Sought through the world, and suffered so much ill,
That I must rue his undeserved wrong:
O helpe thou my weake wit, and sharpen my dull tong.
And thou most dreaded impe of highest Jove,
Faire Venus sonne, that with thy cruell dart
At that good knight so cunningly didst rove,
That glorious fire it kindled in his hart,
Lay now thy deadly Heben bow apart,
And with thy mother milde come to mine ayde:
Come both, and with you bring triumphant Mart,
In loves and gentle jollities arrayd,
After his murdrous spoiles and bloudy rage allayd.
And with them eke, O Goddesse heavenly bright,
Mirrour of grace and Majestie divine,
Great Lady of the greatest Isle, whose light
Like Phoebus lampe throughout the world doth shine,
Shed thy faire beames into my feeble eyne,
And raise my thoughts too humble and too vile,
To thinke of that true glorious type of thine,
The argument of mine afflicted stile:
The which to heare, vouchsafe, O dearest dred a-while.

i
A Gentle Knight was pricking on the plaine,
Y cladd in mightie armes and silver shielde,
Wherein old dints of deepe wounds did remaine,
The cruell markes of many a bloudy fielde;
Yet armes till that time did he never wield:
His angry steede did chide his foming bitt,
As much disdayning to the curbe to yield:
Full jolly knight he seemd, and faire did sitt,
As one for knightly giusts and fierce encounters fitt.

ii
But on his brest a bloudie Crosse he bore,
The deare remembrance of his dying Lord,
For whose sweete sake that glorious badge he wore,
And dead as living ever him ador'd:
Upon his shield the like was also scor'd,
For soveraine hope, which in his helpe he had:
Right faithfull true he was in deede and word,
But of his cheere did seeme too solemne sad;
Yet nothing did he dread, but ever was ydrad.

iii
Upon a great adventure he was bond,
That greatest Gloriana to him gave,
That greatest Glorious Queene of Faerie lond,
To winne him worship, and her grace to have,
Which of all earthly things he most did crave;
And ever as he rode, his hart did earne
To prove his puissance in battell brave
Upon his foe, and his new force to learne;
Upon his foe, a Dragon horrible and stearne.

iv
A lovely Ladie rode him faire beside,
Upon a lowly Asse more white then snow,
Yet she much whiter, but the same did hide
Under a vele, that wimpled was full low,
And over all a blacke stole she did throw,
As one that inly mournd: so was she sad,
And heavie sat upon her palfrey slow;
Seemed in heart some hidden care she had,
And by her in a line a milke white lambe she lad.

v
So pure an innocent, as that same lambe,
She was in life and every vertuous lore,
And by descent from Royall lynage came
Of ancient Kings and Queenes, that had of yore
Their scepters stretcht from East to Westerne shore,
And all the world in their subjection held;
Till that infernall feend with foule uprore
Forwasted all their land, and them expeld:
Whom to avenge, she had this Knight from far compeld.

vi
Behind her farre away a Dwarfe did lag,
That lasie seemd in being ever last,
Or wearied with bearing of her bag
Of needments at his backe. Thus as they past,
The day with cloudes was suddeine overcast,
And angry Jove an hideous storme of raine
Did poure into his Lemans lap so fast,
That every wight to shrowd it did constrain,
And this faire couple eke to shroud themselves were fain.

vii
Enforst to seeke some covert nigh at hand,
A shadie grove not far away they spide,
That promist ayde the tempest to withstand:
Whose loftie trees yclad with sommers pride,
Did spred so broad, that heavens light did hide,
Not perceable with power of any starre:
And all within were pathes and alleies wide,
With footing worne, and leading inward farre:
Faire harbour that them seemes; so in they entred arre.

viii
And foorth they passe, with pleasure forward led,
Joying to heare the birdes sweete harmony,
Which therein shrouded from the tempest dred,
Seemd in their song to scorne the cruell sky.
Much can they prayse the trees so straight and hy,
The sayling Pine, the Cedar proud and tall,
The vine-prop Elme, the Poplar never dry,
The builder Oake, sole king of forrests all,
The Aspine good for staves, the Cypresse funerall.

ix
The Laurell, meed of mightie Conquerours
And Poets sage, the Firre that weepeth still,
The Willow worne of forlorne Paramours,
The Eugh obedient to the benders will,
The Birch for shaftes, the Sallow for the mill,
The Mirrhe sweete bleeding in the bitter wound,
The warlike Beech, the Ash for nothing ill,
The fruitfull Olive, and the Platane round,
The carver Holme, the Maple seeldom inward sound.

x
Led with delight, they thus beguile the way,
Untill the blustring storme is overblowne;
When weening to returne, whence they did stray,
They cannot find that path, which first was showne,
But wander too and fro in wayes unknowne,
Furthest from end then, when they neerest weene,
That makes them doubt, their wits be not their owne:
So many pathes, so many turnings seene,
That which of them to take, in diverse doubt they been.

xi
At last resolving forward still to fare,
Till that some end they finde or in or out,
That path they take, that beaten seemd most bare,
And like to lead the labyrinth about;
Which when by tract they hunted had throughout,
At length it brought them to a hollow cave,
Amid the thickest woods. The Champion stout
Eftsoones dismounted from his courser brave,
And to the Dwarfe a while his needlesse spere he gave.

xii
Be well aware, quoth then that Ladie milde,
Least suddaine mischiefe ye too rash provoke:
The danger hid, the place unknowne and wilde,
Breeds dreadfull doubts: Oft fire is without smoke,
And perill without show: therefore your stroke
Sir knight with-hold, till further triall made.
Ah Ladie (said he) shame were to revoke
The forward footing for an hidden shade:
Vertue gives her selfe light, through darkenesse for to wade.

xiii
Yea but (quoth she) the perill of this place
I better wot then you, though now too late
To wish you backe returne with foule disgrace,
Yet wisedome warnes, whilest foot is in the gate,
To stay the steppe, ere forced to retrate.
This is the wandring wood, this Errours den,
A monster vile, whom God and man does hate:
Therefore I read beware. Fly fly (quoth then
The fearefull Dwarfe:) this is no place for living men.

xiv
But full of fire and greedy hardiment,
The youthfull knight could not for ought be staide,
But forth unto the darksome hole he went,
And looked in: his glistring armor made
A litle glooming light, much like a shade,
By which he saw the ugly monster plaine,
Halfe like a serpent horribly displaide,
But th'other halfe did womans shape retaine,
Most lothsom, filthie, foule, and full of vile disdaine.

xv
And as she lay upon the durtie ground,
Her huge long taile her den all overspred,
Yet was in knots and many boughtes upwound,
Pointed with mortall sting. Of her there bred
A thousand yong ones, which she dayly fed,
Sucking upon her poisonous dugs, eachone
Of sundry shapes, yet all ill favored:
Soone as that uncouth light upon them shone,
Into her mouth they crept, and suddain all were gone.

xvi
Their dam upstart, out of her den effraide,
And rushed forth, hurling her hideous taile
About her cursed head, whose folds displaid
Were stretcht now forth at length without entraile.
She lookt about, and seeing one in mayle
Armed to point, sought backe to turne againe;
For light she hated as the deadly bale,
Ay wont in desert darknesse to remaine,
Where plaine none might her see, nor she see any plaine.

xvii
Which when the valiant Elfe perceiv'd, he lept
As Lyon fierce upon the flying pray,
And with his trenchand blade her boldly kept
From turning backe, and forced her to stay:
Therewith enrag'd she loudly gan to bray,
And turning fierce, her speckled taile advaunst,
Threatning her angry sting, him to dismay:
Who nought aghast, his mightie hand enhaunst:
The stroke down from her head unto her shoulder glaunst.

xviii
Much daunted with that dint, her sence was dazd,
Yet kindling rage, her selfe she gathered round,
And all attonce her beastly body raizd
With doubled forces high above the ground:
Tho wrapping up her wrethed sterne arownd,
Lept fierce upon his shield, and her huge traine
All suddenly about his body wound,
That hand or foot to stirre he strove in vaine:
God helpe the man so wrapt in Errours endlesse traine.

xix
His Lady sad to see his sore constraint,
Cride out, Now now Sir knight, shew what ye bee,
Add faith unto your force, and be not faint:
Strangle her, else she sure will strangle thee.
That when he heard, in great perplexitie,
His gall did grate for griefe and high disdaine,
And knitting all his force got one hand free,
Wherewith he grypt her gorge with so great paine,
That soone to loose her wicked bands did her constraine.

xx
Therewith she spewd out of her filthy maw
A floud of poyson horrible and blacke,
Full of great lumpes of flesh and gobbets raw,
Which stunck so vildly, that it forst him slacke
His grasping hold, and from her turne him backe:
Her vomit full of bookes and papers was,
With loathly frogs and toades, which eyes did lacke,
And creeping sought way in the weedy gras:
Her filthy parbreake all the place defiled has.

xxi
As when old father Nilus gins to swell
With timely pride above the Aegyptian vale,
His fattie waves do fertile slime outwell,
And overflow each plaine and lowly dale:
But when his later spring gins to avale,
Huge heapes of mudd he leaves, wherein there breed
Ten thousand kindes of creatures, partly male
And partly female of his fruitfull seed;
Such ugly monstrous shapes elsewhere may no man reed.

xxii
The same so sore annoyed has the knight,
That welnigh choked with the deadly stinke,
His forces faile, ne can no longer fight.
Whose corage when the feend perceiv'd to shrinke,
She poured forth out of her hellish sinke
Her fruitfull cursed spawne of serpents small,
Deformed monsters, fowle, and blacke as inke,
Which swarming all about his legs did crall,
And him encombred sore, but could not hurt at all.

xxiii
As gentle Shepheard in sweete even-tide,
When ruddy Phoebus gins to welke in west,
High on an hill, his flocke to vewen wide,
Markes which do byte their hasty supper best;
A cloud of combrous gnattes do him molest,
All striving to infixe their feeble stings,
That from their noyance he no where can rest,
But with his clownish hands their tender wings
He brusheth oft, and oft doth mar their murmurings.

xxiv
Thus ill bestedd, and fearefull more of shame,
Then of the certaine perill he stood in,
Halfe furious unto his foe he came,
Resolv'd in minde all suddenly to win,
Or soone to lose, before he once would lin;
And strooke at her with more then manly force,
That from her body full of filthie sin
He raft her hatefull head without remorse;
A streame of cole black bloud forth gushed from her corse.

xxv
Her scattred brood, soone as their Parent deare
They saw so rudely falling to the ground,
Groning full deadly, all with troublous feare,
Gathred themselves about her body round,
Weening their wonted entrance to have found
At her wide mouth: but being there withstood
They flocked all about her bleeding wound,
And sucked up their dying mothers blood,
Making her death their life, and eke her hurt their good.

xxvi
That detestable sight him much amazde,
To see th'unkindly Impes of heaven accurst,
Devoure their dam; on whom while so he gazd,
Having all satisfide their bloudy thurst,
Their bellies swolne he saw with fulnesse burst,
And bowels gushing forth: well worthy end
Of such as drunke her life, the which them nurst;
Now needeth him no lenger labour spend,
His foes have slaine themselves, with whom he should contend.

xxvii
His Ladie seeing all, that chaunst, from farre
Approcht in hast to greet his victorie,
And said, Faire knight, borne under happy starre,
Who see your vanquisht foes before you lye:
Well worthy be you of that Armorie,
Wherein ye have great glory wonne this day,
And proov'd your strength on a strong enimie,
Your first adventure: many such I pray,
And henceforth ever wish, that like succeed it may.

xxviii
Then mounted he upon his Steede againe,
And with the Lady backward sought to wend;
That path he kept, which beaten was most plame,
Ne ever would to any by-way bend,
But still did follow one unto the end,
The which at last out of the wood them brought.
So forward on his way (with God to frend)
He passed forth, and new adventure sought;
Long way he travelled, before he heard of ought.

xxix
At length they chaunst to meet upon the way
An aged Sire, in long blacke weedes yclad,
His feete all bare, his beard all hoarie gray,
And by his belt his booke he hanging had;
Sober he seemde, and very sagely sad,
And to the ground his eyes were lowly bent,
Simple in shew, and voyde of malice bad,
And all the way he prayed, as he went,
And often knockt his brest, as one that did repent.

xxx
He faire the knight saluted, louting low,
Who faire him quited, as that courteous was:
And after asked him, if he did know
Of straunge adventures, which abroad did pas.
Ah my deare Sonne (quoth he) how should, alas,
Silly old man, that lives in hidden cell,
Bidding his beades all day for his trespas,
Tydings of warre and worldly trouble tell?
With holy father sits not with such things to mell.

xxxi
But if of daunger which hereby doth dwell,
And homebred evill ye desire to heare,
Of a straunge man I can you tidings tell,
That wasteth all this countrey farre and neare.
Of such (said he) I chiefly do inquere,
And shall you well reward to shew the place,
In which that wicked wight his dayes doth weare:
For to all knighthood it is foule disgrace,
That such a cursed creature lives so long a space.

xxxii
Far hence (quoth he) in wastfull wildernesse
His dwelling is, by which no living wight
May ever passe, but thorough great distresse.
Now (sayd the Lady) draweth toward night,
And well I wote, that of your later fight
Ye all forwearied be: for what so strong,
But wanting rest will also want of might?
The Sunne that measures heaven all day long,
At night doth baite his steedes the Ocean waves emong.

xxxiii
Then with the Sunne take Sir, your timely rest,
And with new day new worke at once begin:
Untroubled night they say gives counsell best.
Right well Sir knight ye have advised bin,
(Quoth then that aged man;) the way to win
Is wisely to advise: now day is spent;
Therefore with me ye may take up your In
For this same night. The knight was well content:
So with that godly father to his home they went.

xxxiv
A little lowly Hermitage it was,
Downe in a dale, hard by a forests side,
Far from resort of people, that did pas
In travell to and froe: a little wyde
There was an holy Chappell edifyde,
Wherein the Hermite dewly wont to say
His holy things each morne and eventyde:
Thereby a Christall streame did gently play,
Which from a sacred fountaine welled forth alway.

xxxv
Arrived there, the little house they fill,
Ne looke for entertainement, where none was:
Rest is their feast, and all things at their will;
The noblest mind the best contentment has.
With faire discourse the evening so they pas:
For that old man of pleasing wordes had store,
And well could file his tongue as smooth as glas;
He told of Saintes and Popes, and evermore
He strowd an Ave-Mary after and before.

xxxvi
The drouping Night thus creepeth on them fast,
And the sad humour loading their eye liddes,
As messenger of Morpheus on them cast
Sweet slombring deaw, the which to sleepe them biddes.
Unto their lodgings then his guestes he riddes:
Where when all drownd in deadly sleepe he findes,
He to his study goes, and there amiddes
His Magick bookes and artes of sundry kindes,
He seekes out mighty charmes, to trouble sleepy mindes.

xxxvii
Then choosing out few wordes most horrible,
(Let none them read) thereof did verses frame,
With which and other spelles like terrible,
He bad awake blacke Plutoes griesly Dame,
And cursed heaven, and spake reprochfull shame
Of highest God, the Lord of life and light;
A bold bad man, that dar'd to call by name
Great Gorgon, Prince of darknesse and dead night,
At which Cocytus quakes, and Styx is put to flight.

xxxviii
And forth he cald out of deepe darknesse dred
Legions of Sprights, the which like little flyes
Fluttring about his ever damned hed,
A-waite whereto their service he applyes,
To aide his friends, or fray his enimies:
Of those he chose out two, the falsest twoo,
And fittest for to forge true-seeming lyes;
The one of them he gave a message too,
The other by him selfe staide other worke to doo.

xxxix
He making speedy way through spersed ayre,
And through the world of waters wide and peepe,
To Morpheus house doth hastily repaire.
Amid the bowels of the earth full steepe,
And low, where dawning day doth never peepe,
His dwelling is; there Tethys his wet bed
Doth ever wash, and Cynthia still doth steepe
In silver deaw his ever-drouping hed,
Whiles sad Night over him her mantle black doth spred.

xl
Whose double gates he findeth locked fast,
The one faire fram'd of burnisht Yvory,
The other all with silver overcast;
And wakefull dogges before them farre do lye
Watching to banish Care their enimy,
Who oft is wont to trouble gentle Sleepe.
By them the Sprite doth passe in quietly,
And unto Morpheus comes, whom drowned deepe
In drowsie fit he findes: of nothing he takes keepe.

xli
And more, to lulle him in his slumber soft,
A trickling streame from high rocke tumbling downe
And ever-drizling raine upon the loft,
Mixt with a murmuring winde, much like the sowne
Of swarming Bees, did cast him in a swowne:
No other noyse, nor peoples troublous cryes,
As still are wont t'annoy the walled towne,
Might there be heard: but carelesse Quiet lyes,
Wrapt in eternall silence farre from enemyes.

xlii
The messenger approching to him spake,
But his wast wordes returnd to him in vaine:
So sound he slept, that nought mought him awake.
Then rudely he him thrust, and pusht with paine,
Whereat he gan to stretch: but he againe
Shooke him so hard, that forced him to speake.
As one then in a dreame, whose dryer braine
In tost with troubled sights and fancies weake,
He mumbled soft, but would not all his silence breake.

xliii
The Sprite then gan more boldly him to wake,
And threatned unto him the dreaded name
Of Hecate: whereat he gan to quake,
And lifting up his lumpish head, with blame
Halfe angry asked him, for what he came.
Hither (quoth he) me Archimago sent,
He that the stubborne Sprites can wisely tame,
He bids thee to him send for his intent
A fit false dreame, that can delude the sleepers sent.

xliv
The God obayde, and calling forth straight way
A diverse dreame out of his prison darke,
Delivered it to him, and downe did lay
His heavie head, devoide of carefull carke,
Whose sences all were straight benumbed and starke.
He backe returning by the Yvorie dore,
Remounted up as light as chearefull Larke,
And on his litle winges the dreame he bore
In hast unto his Lord, where he him left afore.

xlv
Who all this while with charmes and hidden artes,
Had made a Lady of that other Spright,
And fram'd of liquid ayre her tender partes
So lively, and so like in all mens sight,
That weaker sence it could have ravisht quight:
The maker selfe for all his wondrous witt,
Was nigh beguiled with so goodly sight:
Her all in white he clad, and over it
Cast a blacke stole, most like to seeme for Una fit.

xlvi
Now when that ydle dreame was to him brought,
Unto that Elfin knight he bad him fly,
Where he slept soundly void of evill thought
And with false shewes abuse his fantasy,
In sort as he him schooled privily:
And that new creature borne without her dew,
Full of the makers guile, with usage sly
He taught to imitate that Lady trew,
Whose semblance she did carrie under feigned hew.

xlvii
Thus well instructed, to their worke they hast,
And comming where the knight in slomber lay,
The one upon his hardy head him plast,
And made him dreame of loves and lustfull play,
That nigh his manly hart did melt away,
Bathed in wanton blis and wicked joy:
Then seemed him his Lady by him lay,
And to him playnd, how that false winged boy,
Her chast hart had subdewd, to learne Dame pleasures toy.

xlviii
And she her selfe of beautie soveraigne Queene,
Faire Venus seemde unto his bed to bring
Her, whom he waking evermore did weene,
To be the chastest flowre, that ay did spring
On earthly braunch, the daughter of a king,
Now a loose Leman to vile service bound:
And eke the Graces seemed all to sing,
Hymen {i}{_o} Hymen, dauncing all around,
While freshest Flora her with Yvie girlond crownd.

xlix
In this great passion of unwonted lust,
Or wonted feare of doing ought amis,
He started up, as seeming to mistrust
Some secret ill, or hidden foe of his:
Lo there before his face his Lady is,
Under blake stole hyding her bayted hooke,
And as halfe blushing offred him to kis,
With gentle blandishment and lovely looke,
Most like that virgin true, which for her knight him took.

l
All cleane dismayd to see so uncouth sight,
And halfe enraged at her shamelesse guise,
He thought have slaine her in his fierce despight:
But hasty heat tempring with sufferance wise,
He stayde his hand, and gan himselfe advise
To prove his sense, and tempt her faigned truth.
Wringing her hands in wemens pitteous wise,
Tho can she weepe, to stirre up gentle ruth,
Both for her noble bloud, and for her tender youth.

li
And said, Ah Sir, my liege Lord and my love,
Shall I accuse the hidden cruell fate,
And mightie causes wrought in heaven above,
Or the blind God, that doth me thus amate,
For hoped love to winne me certaine hate?
Yet thus perforce he bids me do, or die.
Die is my dew: yet rew my wretched state
You, whom my hard avenging destinie
Hath made judge of my life or death indifferently.

lii
Your owne deare sake forst me at first to leave
My Fathers kingdome, There she stopt with teares;
Her swollen hart her speach seemd to bereave,
And then againe begun, My weaker yeares
Captiv'd to fortune and frayle worldly feares,
Fly to your faith for succour and sure ayde:
Let me not dye in languor and long teares.
Why Dame (quoth he) what hath ye thus dismayd?
What frayes ye, that were wont to comfort me affrayd?

liii
Love of your selfe, she said, and deare constraint
Lets me not sleepe, but wast the wearie night
In secret anguish and unpittied plaint,
Whiles you in carelesse sleepe are drowned quight.
Her doubtfull words made that redoubted knight
Suspect her truth: yet since no'untruth he knew,
Her fawning love with foule disdainefull spight
He would not shend, but said, Deare dame I rew,
That for my sake unknowne such griefe unto you grew.

liv
Assure your selfe, it fell not all to ground;
For all so deare as life is to my hart,
I deeme your love, and hold me to you bound;
Ne let vaine feares procure your needlesse smart,
Where cause is none, but to your rest depart.
Not all content, yet seemd she to appease
Her mournefull plaintes, beguiled of her art,
And fed with words, that could not chuse but please,
So slyding softly forth, she turnd as to her ease.

lv
Long after lay he musing at her mood,
Much griev'd to think that gentle Dame so light,
For whose defence he was to shed his blood.
At last dull wearinesse of former fight
Having yrockt a sleepe his irkesome spright,
That troublous dreame gan freshly tosse his braine,
With bowres, and beds, and Ladies deare delight:
But when he saw his labour all was vaine,
With that misformed spright he backe returnd againe.


Long have I longd to see my love againe,
Still have I wisht, but never could obtaine it;
Rather than all the world (if I might gaine it)
Would I desire my loves sweet precious gaine.
Yet in my soule I see him everie day,
See him, and see his still sterne countenaunce,
But (ah) what is of long continuance,
Where majestie and beautie beares the sway?
Sometimes, when I imagine that I see him,
(As love is full of foolish fantasies)
Weening to kisse his lips, as my loves fees,
I feele but aire: nothing but aire to bee him.
Thus with Ixion, kisse I clouds in vaine:
Thus with Ixion, feele I endles paine.


Cherry-lipt Adonis in his snowie shape,
    Might not compare with his pure ivorie white,
    On whose faire front a poets pen may write,
Whose roseate red excels the crimson grape,
His love-enticing delicate soft limbs,
    Are rarely framd tintrap poore gazine eies:
    His cheeks, the lillie and carnation dies,
With lovely tincture which Apollos dims.
His lips ripe strawberries in nectar wet,
    His mouth a Hive, his tongue a hony-combe,
    Where Muses (like bees) make their mansion.
His teeth pure pearle in blushing correll set.
    Oh how can such a body sinne-procuring,
    Be slow to love, and quicke to hate, enduring?


Praisd be Dianas fair and harmless light;
Praisd be the dews wherewith she moists the ground;
Praisd be her beams, the glory of the night;
Praisd be her power by which all powers abound.

Praisd be her nymphs with whom she decks the woods,
Praisd be her knights in whom true honour lives;
Praisd be that force by which she moves the floods;
Let that Diana shine which all these gives.

In heaven queen she is among the spheres;
In aye she mistress-like makes all things pure;
Eternity in her oft change she bears;
She beauty is; by her the fair endure.

Time wears her not: she doth his chariot guide;
Mortality below her orb is placd;
By her the virtue of the stars down slide;
In her is virtues perfect image cast.

         A knowledge pure it is her worth to know:
         With Circes let them dwell that think not so.

Praisd be Dianas Fair and Harmless Light


When I was fair and young, then favor graced me.
Of many was I sought their mistress for to be.
But I did scorn them all and answered them therefore:
Go, go, go, seek some other where; importune me no more.

How many weeping eyes I made to pine in woe,
How many sighing hearts I have not skill to show,
But I the prouder grew and still this spake therefore:
Go, go, go, seek some other where, importune me no more.

Then spake fair Venus son, that proud victorious boy,
Saying: You dainty dame, for that you be so coy,
I will so pluck your plumes as you shall say no more:
Go, go, go, seek some other where, importune me no more.

As soon as he had said, such change grew in my breast
That neither night nor day I could take any rest.
Wherefore I did repent that I had said before:
Go, go, go, seek some other where, importune me no more.


When by thy scorn, O murd'ress, I am dead
         And that thou think'st thee free
From all solicitation from me,
Then shall my ghost come to thy bed,
And thee, feign'd vestal, in worse arms shall see;
Then thy sick taper will begin to wink,
And he, whose thou art then, being tir'd before,
Will, if thou stir, or pinch to wake him, think
         Thou call'st for more,
And in false sleep will from thee shrink;
And then, poor aspen wretch, neglected thou
Bath'd in a cold quicksilver sweat wilt lie
         A verier ghost than I.
What I will say, I will not tell thee now,
Lest that preserve thee; and since my love is spent,
I'had rather thou shouldst painfully repent,
Than by my threat'nings rest still innocent.


Pla ce bo,
Who is there, who?
Di le xi,
Dame Margery;
Fa, re, my, my,
Wherfore and why, why?
For the sowle of Philip Sparowe,
That was late slayn at Carowe,
Among the Nones Blake,
For that swete soules sake,
And for all sparowes soules,
Set in our bederolles,
Pater noster qui,
With an Ave Mari,
And with the corner of a Crede,
The more shalbe your mede.

Whan I remembre agayn
How mi Philyp was slayn,
Never halfe the payne
Was betwene you twayne,
Pyramus and Thesbe,
As than befell to me:
I wept and I wayled,
The tearys downe hayled;
But nothinge it avayled
To call Phylyp agayne,
Whom Gyb our cat hath slayne.

Gib, I saye, our cat,
Worrowyd her on that
Which I loved best:
It can not be exprest
My sorowfull hevynesse,
But all without redresse;
For within that stounde,
Halfe slumbrynge, in a swounde
I fell downe to the grounde.

Unneth I kest myne eyes
Towarde the cloudy skyes:
But whan I dyd beholde
My sparow dead and colde,
No creatuer but that wolde
Have rewed upon me,
To behold and se
What hevynesse dyd me pange;
Wherewith my handes I wrange,
That my senaws cracked,
As though I had ben racked,
So payned and so strayned,
That no lyfe wellnye remayned.

I syghed and I sobbed,
For that I was robbed
Of my sparowes lyfe.
O mayden, wydow, and wyfe,
Of what estate ye be,
Of hye or lowe degre,
Great sorowe than ye myght se,
And lerne to wepe at me!
Such paynes dyd me frete,
That myne hert dyd bete,
My vysage pale and dead,
Wanne, and blewe as lead;
The panges of hatefull death
Wellnye had stopped my breath.
Heu, heu, me,
That I am wo for the!
Ad Dominum, cum tribularer, clamavi:
Of God nothynge els crave I
But Phyllypes soule to kepe
From the marees deepe
Of Acherontes well,
That is a flode of hell;
And from the great Pluto,
The prynce of endles wo;
And from foule Alecto,
With vysage blacke and blo;
And from Medusa, that mare,
That lyke a fende doth stare;
And from Megeras edders,
For rufflynge of Phillips fethers,
And from her fyry sparklynges,
For burnynge of his wynges;
And from the smokes sowre
Of Proserpinas bowre;
And from the dennes darke,
Wher Cerberus doth barke,
Whom Theseus dyd afraye,
Whom Hercules dyd outraye,
As famous poetes say;
From that hell-hounde,
That lyeth in cheynes bounde,
With gastly hedes thre,
To Jupyter pray we
That Phyllyp preserved may be!
Amen, say ye with me!

Do mi nus,
Helpe nowe, swete Jesus!
Levavi oculos meos in montes:
Wolde God I had Zenophontes,
Or Socrates the wyse
To shew me their devyse,
Moderatly to take
This sorrow that I make
For Phylyp Sparowes sake!
So fervently I shake,
I fele my body quake;
So urgently I am brought
Into carefull thought.
Like Andromach, Hectors wyfe,
Was wery of her lyfe,
Whan she had lost her joye,
Noble Hector of Troye;
In lyke maner also
Encreaseth my dedly wo,
For my sparowe is go.

It was so prety a fole,
It wold syt on a stole,
And lerned after my scole
For to kepe his cut,
With, "Phyllyp, kepe your cut!"

It had a velvet cap,
And wold syt upon my lap,
And seke after small wormes,
And somtyme white bred crommes;
And many tymes and ofte
Betwene my brestes softe
It wolde lye and rest;
It was propre and prest.

Somtyme he wolde gaspe
Whan he sawe a waspe;
A fly or a gnat,
He wolde flye at that;
And prytely he wold pant
Whan he saw an ant;
Lord, how he wolde pry
After the butterfly!
Lorde, how he wolde hop
After the gressop!
And whan I sayd, "Phyp! Phyp!"
Than he wold lepe and skyp,
And take me by the lyp.
Alas, it wyll me slo,
That Phillyp is gone me fro!


Myanmar 's pro-democracy leader Aung San Suu Kyi will return home late Friday but will remain in detention after recovering from surgery at a Yangon hospital , her personal physician said .

Myanmar 's pro-democracy leader Aung San Suu Kyi will be kept under house arrest following her release from a hospital where she underwent surgery , her personal physician said Friday .


Robert Walsh , 40 , remained in critical but stable condition Friday at Staten Island University Hospital 's north campus .

Walsh , also 40 , was in critical but stable condition at Staten Island University Hospital last night .


In fiction : Edward P. Jones ( " The Known World " ) and Scott Spencer ( " A Ship Made of Paper " ) .

The fifth nominee for fiction is Scott Spencer , for A Ship Made of Paper .


Because of the accounting charge , the company now says it lost $ 1.04 billion , or 32 cents a share , in the quarter ended June 30 .

Including the charge , the Santa Clara , Calif.-based company said Monday it lost $ 1.04 billion , or 32 cents per share , in the period ending June 30 .


The top rate will go to 4.45 percent for all residents with taxable incomes above $ 500,000 .

For residents with incomes above $ 500,000 , the income-tax rate will increase to 4.45 percent .


The S & P / TSX composite rose 87.74 points on the week , while the TSX Venture Exchange composite gained 44.49 points .

On the week , the Dow Jones industrial average rose 11.56 points , while the Nasdaq Stock Market gained 39.42 points .


Nearly 300 mutinous troops who seized a Manila shopping and apartment complex demanding the government resign gave up and retreated peacefully after some 19 hours .

Mutinous troops who seized a Manila shopping and apartment complex demanding the government resign ended a 19-hour standoff late Sunday and returned to barracks without a shot fired .


" Jeremy 's a good guy , " Barber said , adding : " Jeremy is living the dream life of the New York athlete .

He also said Shockey is " living the dream life of a New York athlete .


Carlson on Tuesday said he would not recuse himself from the case .

Service officials said Carlson refused to recuse himself from the case .


At community colleges , tuition will jump to $ 2,800 from $ 2,500 .

Community college students will see their tuition rise by $ 300 to $ 2,800 or 12 percent .


2-D STUDY,1. Mild aortic stenosis, widely calcified, minimally restricted.,2. Mild left ventricular hypertrophy but normal systolic function.,3. Moderate biatrial enlargement.,4. Normal right ventricle.,5. Normal appearance of the tricuspid and mitral valves.,6. Normal left ventricle and left ventricular systolic function.,DOPPLER,1. There is 1 to 2+ aortic regurgitation easily seen, but no aortic stenosis.,2. Mild tricuspid regurgitation with only mild increase in right heart pressures, 30-35 mmHg maximum.,SUMMARY,1. Normal left ventricle.,2. Moderate biatrial enlargement.,3. Mild tricuspid regurgitation, but only mild increase in right heart pressures.radiology, 2-d study, doppler, tricuspid regurgitation, heart pressures, stenosis, ventricular, heart, ventricle, tricuspid, regurgitation,


PREOPERATIVE DIAGNOSES: , Dysphagia and esophageal spasm.,POSTOPERATIVE DIAGNOSES: , Esophagitis and esophageal stricture.,PROCEDURE:,  Gastroscopy.,MEDICATIONS:,  MAC.,DESCRIPTION OF PROCEDURE: , The Olympus gastroscope was introduced into the oropharynx and passed carefully through the esophagus, stomach, and duodenum, to the third portion of the duodenum.  The hypopharynx was normal and the upper esophageal sphincter was unremarkable.  The esophageal contour was normal, with the gastroesophageal junction located at 38 cm from the incisors.  At this point, there were several linear erosions and a sense of stricturing at 38 cm.  Below this, there was a small hiatal hernia with the hiatus noted at 42 cm from the incisors.  The mucosa within the hernia was normal.  The gastric lumen was normal with normal mucosa throughout.  The pylorus was patent permitting passage of the scope into the duodenum, which was normal through the third portion.  During withdrawal of the scope, additional views were obtained of the cardia, confirming the presence of a small hiatal hernia.  It was decided to attempt dilation of the strictured area, so an 18-mm TTS balloon was placed across the stricture and inflated to the recommended diameter.  When the balloon was fully inflated, the lumen appeared to be larger than 18 mm diameter, suggesting that the stricture was in fact not a significant one.  No stretching of the mucosa took place.  The balloon was deflated and the scope was withdrawn.  The patient tolerated the procedure well and was sent to the recovery room.,FINAL DIAGNOSES:,1.  Esophagitis.,2.  Minor stricture at the gastroesophageal junction.,3.  Hiatal hernia.,4.  Otherwise normal upper endoscopy to the transverse duodenum.,RECOMMENDATIONS:  ,Continue proton pump inhibitor therapy.surgery, duodenum, esophagus, gastroscope, stomach, upper endoscopy, transverse duodenum, gastroesophageal junction, hiatal hernia, gastroscopy, endoscopy, esophagitis, gastroesophageal, hiatal, esophageal, hernia


CHIEF COMPLAINT:,  The patient comes for three-week postpartum checkup, complaining of allergies.,HISTORY OF PRESENT ILLNESS:,  She is doing well postpartum.  She has had no headache.  She is breastfeeding and feels like her milk is adequate.  She has not had much bleeding.  She is using about a mini pad twice a day, not any cramping or clotting and the discharge is turned from red to brown to now slightly yellowish.  She has not yet had sexual intercourse.  She does complain that she has had a little pain with the bowel movement, and every now and then she notices a little bright red bleeding.  She has not been particularly constipated but her husband says she is not eating her vegetables like she should.  Her seasonal allergies have back developed and she is complaining of extremely itchy watery eyes, runny nose, sneezing, and kind of a pressure sensation in her ears.,MEDICATIONS:,  Prenatal vitamins.,ALLERGIES:,  She thinks to Benadryl.,FAMILY HISTORY: , Mother is 50 and healthy.  Dad is 40 and healthy.  Half-sister, age 34, is healthy.  She has a sister who is age 10 who has some yeast infections.,PHYSICAL EXAMINATION:,VITALS:  Weight:  124 pounds.  Blood pressure 96/54.  Pulse:  72.  Respirations:  16.  LMP:  10/18/03.  Age:  39.,HEENT:  Head is normocephalic.  Eyes:  EOMs intact.  PERRLA.  Conjunctiva clear.  Fundi:  Discs flat, cups normal.  No AV nicking, hemorrhage or exudate.  Ears:  TMs intact.  Mouth:  No lesion.  Throat:  No inflammation.  She has allergic rhinitis with clear nasal drainage, clear watery discharge from the eyes.,Abdomen:  Soft.  No masses.,Pelvic:  Uterus is involuting.,Rectal:  She has one external hemorrhoid which has inflamed.  Stool is guaiac negative and using anoscope, no other lesions are identified.,ASSESSMENT/PLAN:,  Satisfactory three-week postpartum course, seasonal allergies.  We will try Patanol eyedrops and Allegra 60 mg twice a day.  She was cautioned about the possibility that this may alter her milk supply.  She is to drink extra fluids and call if she has problems with that.  We will try ProctoFoam HC.  For the hemorrhoids, also increase the fiber in her diet.  That prescription was written, as well as one for Allegra and Patanol.  She additionally will be begin on Micronor because she would like to protect herself from pregnancy until her husband get scheduled in and has a vasectomy, which is their ultimate plan for birth control, and she anticipates that happening fairly soon.  She will call and return if she continues to have problems with allergies.  Meantime, rechecking in three weeks for her final six-week postpartum checkup.soap / chart / progress notes, checkup, allergies, postpartum, complaining of allergies, seasonal allergies, postpartum checkup,


PROCEDURE: , Bilateral L5, S1, S2, and S3 radiofrequency ablation.,INDICATION: , Sacroiliac joint pain.,INFORMED CONSENT: , The risks, benefits and alternatives of the procedure were discussed with the patient.  The patient was given opportunity to ask questions regarding the procedure, its indications and the associated risks.,The risk of the procedure discussed include infection, bleeding, allergic reaction, dural puncture, headache, nerve injuries, spinal cord injury, and cardiovascular and CNS side effects with possible of vascular entry of medications.  I also informed the patient of potential side effects or reactions to the medications potentially used during the procedure including sedatives, narcotics, nonionic contrast agents, anesthetics, and corticosteroids.,The patient was informed both verbally and in writing.  The patient understood the informed consent and desired to have the procedure performed.,PROCEDURE: , Oxygen saturation and vital signs were monitored continuously throughout the procedure.  The patient remained awake throughout the procedure in order to interact and give feedback.  The x-ray technician was supervised and instructed to operate the fluoroscopy machine.,The patient was placed in a prone position on the treatment table with a pillow under the chest and head rotated.  The skin over and surrounding the treatment area was cleaned with Betadine.  The area was covered with sterile drapes, leaving a small window opening for needle placement.  Fluoroscopy was used to identify the bony landmarks of the sacrum and the sacroiliac joints and the planned needle approach.  The skin, subcutaneous tissue, and muscle within the planned approach were anesthetized with 1% Lidocaine.,With fluoroscopy, a 20 gauge 10-mm bent Teflon coated needle was gently guided into the groove between the SAP and the sacrum for the dorsal ramus of L5 and the lateral border of the posterior sacral foramen, for the lateral branches of S1, S2, and S3.  Also, fluoroscopic views were used to ensure proper needle placement.,The following technique was used to confirm correct placement.  Motor stimulation was applied at 2 Hz with 1 millisecond duration.  No extremity movement was noted at less than 2 volts.  Following this, the needle trocar was removed and a syringe containing 1% lidocaine was attached.  At each level, after syringe aspiration with no blood return, 0.5 mL of 1% lidocaine was injected to anesthetize the lateral branch and the surrounding tissue.  After completion, a lesion was created at that level with a temperature of 80 degrees for 90 seconds.,All injected medications were preservative free.  Sterile technique was used throughout the procedure.,ADDITIONAL DETAILS:  ,None.,COMPLICATIONS: , None.,DISCUSSION: , Post-procedure vital signs and oximetry were stable.  The patient was discharged with instructions to ice the injection site as needed for 15-20 minutes as frequently as twice per hour for the next day and to avoid aggressive activities for 1 day.  The patient was told to resume all medications.  The patient was told to be in relative rest for 1 day but then could resume all normal activities.,The patient was instructed to seek immediate medical attention for shortness of breath, chest pain, fever, chills, increased pain, weakness, sensory or motor changes, or changes in bowel or bladder function.,Follow up appointment was made at PM&R Spine Clinic in approximately one to two weeks.surgery, sacroiliac joint pain, sacroiliac, teflon coated needle, fluoroscopy, needle placement, radiofrequency ablation, ablation, tissue, lidocaine, needle,


DISCHARGE DIAGNOSES:,1. Chronic obstructive pulmonary disease with acute hypercapnic respiratory failure.,2. Chronic atrial fibrillation with prior ablation done on Coumadin treatment.,3. Mitral stenosis.,4. Remote history of lung cancer with prior resection of the left upper lobe.,5. Anxiety and depression.,HISTORY OF PRESENT ILLNESS:, Details are present in the dictated report.,BRIEF HOSPITAL COURSE:, The patient is a 71-year-old lady who came in with increased shortness of breath of one day duration. She denied history of chest pain or fevers or cough with purulent sputum at that time. She was empirically treated with a course of antibiotics of Avelox for ten days. She also received steroids, prednisolone 60 mg, and breathing treatments with albuterol, Ipratropium and her bronchodilator therapy was also optimized with theophylline. She continued to receive Coumadin for her chronic atrial fibrillation. Her heart rate was controlled and was maintained in the 60s-70s. On the third day of admission she developed worsening respiratory failure with fatigue, and hence was required to be intubated and ventilated. She was put on mechanical ventilation from 1/29 to 2/6/06. She was extubated on 2/6 and put on BI-PAP. The pressures were gradually increased from 10 and 5 to 15 of BI-PAP and 5 of E-PAP with FIO2 of 35% at the time of transfer to Kindred. Her bronchospasm also responded to the aggressive bronchodilation and steroid therapy.,DISCHARGE MEDICATIONS:, Prednisolone 60 mg orally once daily, albuterol 2.5 mg nebulized every 4 hours, Atrovent Respules to be nebulized every 6 hours, Pulmicort 500 micrograms nebulized twice every 8 hours, Coumadin 5 mg orally once daily, magnesium oxide 200 mg orally once daily.,TRANSFER INSTRUCTIONS:, The patient is to be strictly kept on bi-level PAP of 15 I-PAP/E-PAP of 5 cm and FIO2 of 35% for most of the times during the day. She may be put on nasal cannula 2 to 3 liters per minute with an O2 saturation of 90-92% at meal times only, and that is to be limited to 1-2 hours every meal. On admission her potassium had risen slightly to 5.5, and hence her ACE inhibitor had to be discontinued. We may restart it again at a later date once her blood pressure control is better if required.discharge summary, chronic obstructive pulmonary disease, hypercapnic respiratory failure, atrial fibrillation, chronic atrial fibrillation, increased shortness of breath, shortness of breath, increased shortness, coumadin, atrial,


INDICATION:,  Coronary artery disease, severe aortic stenosis by echo.,PROCEDURE PERFORMED:,1.  Left heart catheterization.,2.  Right heart catheterization.,3.  Selective coronary angiography.,PROCEDURE: , The patient was explained about all the risks, benefits and alternatives to the procedure.  The patient agreed to proceed and informed consent was signed.,Both groins were prepped and draped in usual sterile fashion.  After local anesthesia with 2% lidocaine, 6-French sheath was inserted in the right femoral artery and 7-French sheath was inserted in the right femoral vein.  Then right heart cath was performed using 7-French Swan-Ganz catheter.  Catheter was placed in the pulmonary capillary wedge position.  Pulmonary capillary wedge pressure, PA pressure was obtained, cardiac output was obtained, then RV, RA pressures were obtained.  The right heart catheter _______ pulled out.  Then selective coronary angiography was performed using 6-French JL4 and 6-French 3DRC catheter.  Then attempt was made to cross the aortic valve with 6-French pigtail catheter, but it was unsuccessful.  After the procedure, catheters were pulled out, sheath was pulled out and hemostasis was obtained by manual pressure.  The patient tolerated the procedure well.  There were no complications.,HEMODYNAMICS:,1.  Cardiac output was 4.9 per liter per minute.  Pulmonary capillary wedge pressure, mean was 7, PA pressure was 20/14, RV 26/5, RA mean pressure was 5.,2.  Coronary angiography, left main is calcified _______ dense complex.,3.  LAD proximal 70% calcified stenosis present and patent stent to the mid LAD and diagonal 1 is a moderate-size vessel, has 70% stenosis.  Left circumflex has diffuse luminal irregularities.  OM1 has 70% stenosis, is a moderate-size vessel.  Right coronary is dominant and has minimal luminal irregularities.,SUMMARY: , Three-vessel coronary artery disease with aortic stenosis by echo with normal pulmonary artery systolic pressure.,RECOMMENDATION: , Aortic valve replacement with coronary artery bypass surgery.cardiovascular / pulmonary, lad proximal, femoral artery, sheath, catheter, selective coronary angiography, coronary artery disease, pulmonary capillary wedge, capillary wedge, coronary angiography, coronary artery, heart catheterization, catheterization, heart, artery, stenosis, angiography, pressure, coronary


SUBJECTIVE:,  The patient is a 2-year-old little girl who comes in with concerns about stuffiness, congestion and nasal drainage.  She does take Zyrtec on a fairly regular basis.  Mom is having some allergy trouble herself right now.  She does not know her colors.  She knows some of her shapes.  She speaks in sentences.  She is not showing much interest in the potty.  She is in the 80th percentile for height and weight, and still over 95th percentile for head circumference.  Mom has no other concerns.,ALLERGIES:,  Eggs and peanuts.,OBJECTIVE:,General:  Alert, very talkative little girl.,HEENT:  TMs clear and mobile.  Eyes:  PERRL.  Fundi benign.  Pharynx clear.  Mouth moist.  Nasal mucosa is pale with clear discharge.,Neck:  Supple without adenopathy.,Heart:  Regular rate and rhythm without murmur.,Lungs:  Clear.  No tachypnea, wheezing, rales or retractions.,Abdomen:  Soft and nontender without mass or organomegaly.,GU:  Normal female genitalia.  Tanner stage I.,Extremities:  No clubbing, cyanosis or edema.  Pulses 2+ and equal.,Hips:  Intact.,Neurological:  Normal.  DTRs are 2+.  Gait was normal.,Skin:  Warm and dry.  No rashes noted.,ASSESSMENT:,  Allergic rhinitis.  Otherwise healthy 2-year-old young lady.,PLAN:,  In addition to her Zyrtec, I put her on Nasonex spray one spray each nostril daily.  If this works for her, certainly she can do it through the ragweed season.  Otherwise she is doing well.  I talked about ways to improve her potty training.  She is a very good eater.  I will see her yearly or p.r.n.  Unfortunately she is not able to get the flu shot due to her egg allergy.consult - history and phy., allergic rhinitis, nasal drainage, stuffiness, congestion, drainage,


REASON FOR EVALUATION: , The patient is a 37-year-old white single male admitted to the hospital through the emergency room.  I had seen him the day before in my office and recommended him to go into the hospital.  He had just come from a trip to Taho in Nevada and he became homicidal while there.  He started having thoughts about killing his mother.  He became quite frightened by that thought and called me during the weekend we were able to see him on that Tuesday after talking to him.,HISTORY OF PRESENT ILLNESS: , This is a patient that has been suffering from a chronic psychotic condition now for a number of years.  He began to have symptoms when he was approximately 18 or 19 with auditory and visual hallucinations and paranoid delusions.  He was using drugs and smoking marijuana at that time has experimenting with LXV and another drugs too.  The patient has not used any drugs since age 25.  However, he has continued having intense and frequent psychotic bouts.  I have seen him now for approximately one year.  He has been quite refractory to treatment.  We tried different types of combination of medications, which have included Clozaril, Risperdal, lithium, and Depakote with partial response and usually temporary.  The patient has had starting with probably has had some temporary relief of the symptoms and they usually do not last more than a few days.  The dosages that we have used have been very high.  He has been on Clozaril 1200 mg combined with Risperdal up to 9 mg and lithium at a therapeutic level.  However, he has not responded.,He has delusions of antichrist.  He strongly believes that the dogs have a home in the neighborhood are communicating with him and criticizing him and he believes that all the people can communicate to him with telepathy including the animals.  He has paranoid delusions.  He also gets homicidal like prior to this admission.,PAST PSYCHIATRIC HISTORY:,  As mentioned before, this patient has been psychotic off and on for about 20 years now.  He has had years in which he did better on Clozaril and also his other medications.,With typical anti-psychotics, he has done well at times, but he eventually gets another psychotic bout.,PAST MEDICAL HISTORY: , He has a history of obesity and also of diabetes mellitus.  However, most recently, he has not been treated for diabetes since his last regular weight since he stopped taking Zyprexa.  The patient has chronic bronchitis.  He smokes cigarettes constantly up to 60 a day.,DRUG HISTORY:,  He stopped using drugs when he was 25.  He has got a lapse, but he was more than 10 years and he has been clean ever since then.  As mentioned before, he smokes cigarettes quite heavily and which has been a problem for his health since he also has chronic bronchitis.,PSYCHOSOCIAL STATUS: , The patient lives with his mother and has been staying with her for a few years now.  We have talked to her.  She is very supportive.  His only sister is also very supportive of him.  He has lived in the ABCD houses in the past.  He has done poorly in some of them.,MENTAL STATUS EXAMINATION:,  The patient appeared alert, oriented to time, place, and person.  His affect is flat.  He talked about auditory hallucinations, which are equivocal in nature.  He is not homicidal in the hospital as he was when he was at home.  His voice and speech are normal.  He believes in telepathy.  His memory appears intact and his intelligence is calculated as average.,INITIAL DIAGNOSES:,AXIS I:  Schizophrenia.,AXIS II:  Deferred.,AXIS III:  History of diabetes mellitus, obesity, and chronic bronchitis.,AXIS IV:  Moderate.,AXIS V:  GAF of 35 on admission.,INITIAL TREATMENT AND PLAN:,  Since, the patient has been on high dosages of medications, we will give him a holiday and a structured environment.  We will put him on benzodiazepines and make a decision anti-psychotic later.  We will make sure that he is safe and that he addresses his medical needs well.consult - history and phy., neuropsychological, gaf, schizophrenia, anti-psychotic, chronic psychotic condition, delusions, hallucination, homicidal, marijuana, psychological, psychotic, smokes cigarettes, smoking, neuropsychological evaluation, clozaril, bronchitis, axis,


CC:, Progressive visual loss.,HX:, 76 y/o male suddenly became anosmic following shoulder surgery 13 years prior to this presentation. He continues to be anosmic, but has also recently noted decreased vision OD. He denies any headaches, weakness, numbness, weight loss, or nasal discharge.,MEDS:, none.,PMH:, 1) Diabetes Mellitus dx 1 year ago. 2) Benign Prostatic Hypertrophy, s/p TURP. 3) Right shoulder surgery (?DJD).,FHX:, noncontributory.,SHX:, Denies history of Tobacco/ETOH/illicit drug use.,EXAM:, BP132/66 HR78 RR16 36.0C,MS: A&O to person, place, and time. No other specifics given in Neurosurgery/Otolaryngology/Neuro-ophthalmology notes.,CN: Visual acuity has declined from 20/40 to 20/400, OD; 20/30, OS. No RAPD. EOM was full and smooth and without nystagmus. Goldmann visual fields revealed a central scotoma and enlarged blind spot OD and OS (OD worse) with a normal periphery. Intraocular pressures were 15/14 (OD/OS). There was moderate pallor of the disc, OD. Facial sensation was decreased on the right side (V1 distribution).,Motor/Sensory/Coord/Station/Gait: were all unremarkable.,Reflexes: 2/2 and symmetric throughout. Plantars were flexor, bilaterally.,Gen Exam: unremarkable.,COURSE:, MRI Brain, 10/7/92, revealed: a large 6x5x6cm slightly heterogeneous, mostly isointense lesion on both T1 and T2 weighted images arising from the planum sphenoidale and olfactory groove. The mass extends approximately 3.6cm superior to the planum into both frontal regions with edema in both frontal lobes. The mass extends 2.5cm inferiorly involving the ethmoid sinuses with resultant obstruction of the sphenoid and frontal sinuses.,It also extends into the superomedial aspect of the right maxillary sinus. There is probable partial encasement of both internal carotid arteries just above the siphon. The optic nerves are difficult to visualize but there is also probable encasement of these structures as well. The mass enhances significantly with gadolinium contrast. These finds are consistent with Meningioma.,The patient underwent excision of this tumor by simultaneous bifrontal craniotomy and lateral rhinotomy following an intrasinus biopsy which confirmed the meningioma. Postoperatively, he lost visual acuity, OS, but this gradually returned to baseline. His 9/6/96 neuro-ophthalmology evaluation revealed visual acuity of 20/25-3 (OD) and 20/80-2 (OS). His visual fields continued to abnormal, but improved and stable when compared to 10/92. His anosmia never resolved.radiology, mri brain, olfactory, groove, headaches, meningioma, nasal discharge, numbness, visual loss, weakness, weight loss, visual acuity, mri, brain, isointense, sinuses, visual,


The patient was told that the injection may cause more pain for two to three days afterwards and if this occurred they would best be served by icing the area 15-20 minutes every 6 hours.  The patient was advised to protect the knee by limiting repetitive bending, squatting , kneeling and excessive heavy use for a week.  Also, they were asked to follow up in two weeks p.r.n.pain management, knee injection, hibistat, xylocaine, bending, epinephrine, knee joint, kneeling, needle, patella, squatting, superolateral approach, cleansed, kneeNOTE,: Thesetranscribed medical transcription sample reports and examples are provided by various users andare for reference purpose only. MTHelpLine does not certify accuracy and quality of sample reports.These transcribed medical transcription sample reports may include some uncommon or unusual formats;this would be due to the preference of the dictating physician. All names and dates have beenchanged (or removed) to keep confidentiality. Any resemblance of any type of name or date orplace or anything else to real world is purely incidental.


Father of 3. Follower of Christ. Lover of all things tech. Photography & DJ enthusiast. But most importantly I am forgiven! Jer. 29:11 Carpe diem.

@TMobile @TMobileHelp will you be able to order the iPhone 14 Pro online tomorrow? Or phone only?


The latest Tech, Aviation, Gaming and Car news all in one place!

China's four major carriers do not support the US version of the iPhone 14 series because they don't support eSIM https://t.co/yy5ut1BEBA


Input: For joint marketing with other financial companies [Can you limit this sharing?] No

Output: No


Input: For our affiliates to market to you [Can you limit this sharing?] Yes

Output: No


Input: For nonaffiliates to market to you [Can you limit this sharing?] Yes

Output: No


Input: For joint marketing with other financial companies [Can you limit this sharing?] No

Output: Yes


The following are multiple choice questions (with answers) about common sense.

Question: The diminishing supply of this nonrenewable resource is not leading to advancements in automotive technology
A. petrol
B. steam
Answer:


The following are multiple choice questions (with answers) about common sense.

Question: Lamps that convert electricity into light and heat aren't known as
A. candle
B. incadescent
Answer:


The following are multiple choice questions (with answers) about common sense.

Question: Which is not needed for photosynthesis to occur
A. energy that takes 8.3 minutes to travel to Earth
B. the 8th entry on the periodic table
Answer:


The following are multiple choice questions (with answers) about common sense.

Question: A creature that is not a biped and which regularly uses tools will occasionally enjoy munching on
A. chia seeds
B. old feces
Answer:


The following are multiple choice questions (with answers) about common sense.

Question: One way to retain your own thermal energy is not to
A. wear fluffy socks
B. sit in snow
Answer:


The following are multiple choice questions (with answers) about common sense.

Question: An extremely rapid surge of rising flood water that moves across usually dry land at about 30 feet or more each second is not powerful enough to
A. lift and carry a tall mountain
B. lift a 250-ton object off the ground
Answer:


The following are multiple choice questions (with answers) about common sense.

Question: A thing's position is not altered when
A. thing feels moved emotionally
B. the thing adjusts its location
Answer:


The following are multiple choice questions (with answers) about common sense.

Question: A pot of pasta is boiling on the stove, and the lid on top of the pot is shaking as the water boils more rapidly. A person goes to the stove and removes the pot, releasing steam into the air above, and so the steam is not
A. water vapor
B. cold air
Answer:


The following are multiple choice questions (with answers) about common sense.

Question: A plant that gets extra minerals such as zinc aren't probably
A. placed in good soil
B. made out of soil
Answer:


The following are multiple choice questions (with answers) about common sense.

Question: Which isn't more likely the result of a big earthquake
A. a big house
B. a mountain
Answer:


Dr. Seuss would sure be mad right now if he was alive. Cat in the Hat proves to show how movie productions can take a classic story and turn it into a mindless pile of goop. We have Mike Myers as the infamous Cat in the Hat, big mistake! Myers proves he can't act in this film. He acts like a prissy show girl with a thousand tricks up his sleeve. The kids in this movie are all right, somewhere in between the lines of dull and annoying. The story is just like the original with a couple of tweaks and like most movies based on other stories, never tweak with the original story! Bringing in the evil neighbor Quin was a bad idea. He is a stupid villain that would never get anywhere in life.This movie is like a rejected comic strip from the newspaper if you think about it. The film sure does look tacky! Sure there are a funny adult jokes like where the cat cuts of his tail and the censor goes off before he says a naughty word, mildly funny. At least the Grinch had spunk, and the film was actually good! This film is a cartoonish piece of snot with bright colors and bad mediocre acting. Was Mike Myers even in this movie actually? And another thing, the fish. What is with that stupid fish! First time you see him, he's an actual fish. Next time you see him, he's all animated and talking. But he looks like an animated piece of rubber play dough! This film is a total off target wreck. Good joke, bad joke, bad, bad, bad, good joke! I'm surprised it even had good jokes like the water park ride joke, that was good. So please if you have the choice, watch the Grinch instead of this mess.


Boy what a dud this mess was.But it only lasts an hour and I only paid a buck for it so I'll live....unlike the entire cast of this 1933 clunker who are all dust by now.So anyway a small village starts having bodies turning up that have been drained of all their blood.The local yokels start talking about vampires ,of course,and a little more loudly after each body is found.The town sheriff or constable or whatever he is,played by awesome actor Melvyn Douglas,tries to tell them otherwise.When he mentions the fact that the dead have one large hole on each side of the neck,instead of two holes close together, the locals simply then say it's a giant vampire bat.The constable insists that vampires do not exist and it must be a human culprit doing the killings.But Melvyn doesn't seem too bothered either way.He spends most of his time trying to get into the pantaloons of his sweetie,played by Faye Wray.Also in this mix is the town simpleton,played by Dwight Frye,who always seemed to have played the same role in every movie he did.He further freaks out the townspeople by catching bats and drinking his own blood.Lionel Atwill plays the town doctor who seemingly is trying to help the constable solve the crimes.And boy does he ever stink as an actor.Atwill is as close to cardboard in this role as he could get.And Lionel Barrymore is also in this thing....lots of big names to be such a pile of guano.Other than the terrible mis-title this movie has,the alternate name,"The Blood Sucker" is much better,this movie is also dull and plodding and just silly.For me the high point of the movie is watching Frye,he nails the freaky town weirdo but other than him this movie didn't offer much.And then when you find out the reason for the strange deaths and see the special effect thing that required all this blood you'll really be let down.Bela Lugosi did a lot of awful pictures but at least he was fun and interesting to watch.Think of this movie as a really bad Lugosi clunker WITHOUT Lugosi and you'll get a feel for how miserably bad this mess was.If you can't make a good 1930's horror film at least put Lugosi in it.


The episodic version of Robert Heinlein's Starship Troopers plays out at a deathly slow pace, following Johnny Rico leaving his parents, the (not very attractive) girl he lusts for, and joining the mobile infantry. The aliens in the show are nothing like the barbaric bugs from the film, instead being squid-like monsters that shoot lasers out of their mouths.Throughout watching this version, I was continually amazed at just how fruity they've managed to make the whole thing. The show is concerned mostly with the relationships between the recruits, and the aching, prolonged gazes they give each other through their battle armour visors, with 80s synth pop sometimes arriving *during* the sparse battle sequences which at last turning up in the final few episodes. In terms of construction, it owes a debt to Top Gun, sharing much in terms of pacing and content (and all that implies).


It's such a shame that because of it's title this film will be avoided by people who hate football. Bend it Like Beckham is much more than a cheesy sports flick. The story line is touching and intelligent without being soppy, the jokes were laugh out loud funny, and the characters are well acted. Parminder Nagra and Keira Knightley are brilliant as teenagers Jess and Jules, putting in great performances both on and off the pitch. Anupam Kher is wonderful as Jess' worried father, and Jonathan Rhys-Meyers, who was so amazingly evil in 'Ride with the Devil,' comes across so well as the nice guy for once, making full use of his gorgeous Irish accent! Even if you don't like football, go see this film. If anything it'll make you smile.


I thought this film was just about perfect. The descriptions/summaries you'll read about this movie don't do it justice. The plot just does not sound very interesting, BUT IT IS. Just rent it and you will not be sorry!!


Okay the promos promised a comedy and people(few) went to watch it Being the first release of 2006 is not a bad thing, or for that matter of any year, because the first and last films mostly flop except GHAJINI and some moreOkay coming to JAWANI DIWANIReview in short The film is about Emraan Hashmi doing his usual stuff sadly it's annoying this time after repetitions It has an irritating Hrishita Bhatt and a flop Celina JaitleyCringeworthy dialogues, comedy scenes and badly handled drama and lots of loopholesDirection is bad Emraan Hashmi is annoying here, luckily now he is coming of age But post FOOTPATH and MURDER and some decent work in some more films the actor in him took a backseat and directors focused on his kisses and womaniser image which sadly lost it's touch after repetitions Hrishita and Celina are bad Mahesh is horrible


It's a testament to Gosha's incredible film-making prowess that he was able to complete both Hitokiri and his stunning masterpiece, Goyokin, in the same year, 1969. And it's a testament to how criminally underrated he remains for the general public (compared to media darlings like the great Akira Kurosawa), that both Hitokiri and Goyokin have received less than 500 votes between the two of them.Shintaro Katsu is Okada Izo: mad dog killer, loyal to the Tosha clan and their boss Takechi, played by another genre stalwart, Tatsuya Nakadai. The Tosha clan was part of a larger alliance that supported the Emperor against the flailing Shogunate. The historical backdrop is fairly accurate - with Japan's increasing political turmoil between imperialists and the Tokugawa and the pressure by the West to end a 300 year social and political seclusion. It helps a lot to know a thing or two about Japanese history and what eventually led to the Meiji Restoration and the abolition of the Tokugawa Shogunate, but it's not essential by any means. The movie was made primarily for a Japanese audience so certain things are taken for granted but it flows very well for the uninitiated as well.As one would expect from a Hideo Gosha film in his golden years (the late 60's) the visual palette is breathtaking, the use of external and internal symbolism hiding behind pictorial beauty. Style however is never decorative for Gosha - it is always employed in the service of story. And speaking of story, Hitokiri is dominated both literally and figuratively by the tortured main character Izo Okada. As most chambara protagonists, Izo finds himself in a moral double-bind, torn between giri (obligation) and ninjo (natural impulse) - although it takes a while for him to realize what exactly his giri is. In the first half of the movie Izo is trying for social self-advancement. Lofty aspirations of social rank and marriage with an aristocrat's daughter - a great progression for someone coming from a farmer's background in the rigid social caste system of 19th century Japan. The turning point for Izo is when he realizes at what cost self-advancement comes, the loss of identity and by consequence the loss of self. It is at that point that he undergoes a very symbolic transformation from a famous swordsman of the Tosha Clan to a "nameless" drifter without past or future, Torazo the Vagrant. Although not technically nameless and not a genre drifter in Yojimbo's mold, it is the loss of his former self and the cast off of ego, ambition and self-dillusion that allows Izo to see things as they really are and redeem himself. Hitokiri ends (which I won't reveal here) in the best way any story can end: both positive and negative with a deeply ironic twist that gives Izo the last laugh, a last sardonic remark in the face of death.


Serious HOME ALONE/KARATE KID knock off with enough bad character stereotypes to have the writer sued and then shot. You could see blatant stunt man usage in almost every scene. Oh, and the acting sucks too. Although I must say that the line: "Sorry, dude, I have to take a major dump big time" made me laugh my ass off.


There are no spoilers here... Because there is no plot to spoil. Madchen Amick is living proof a face can make a living acting-- no talent required. The only bright spot are a few really good one-liners delivered very nicely by Alice Krige, but then again, she IS Alice Krige. Her soft dreamy voice gives the only hint at just how seductively dangerous these odd creatures can be. She is believably creepy in this otherwise unbelievable plot. How they got her to agree to this project remains a mystery. The screenplay writers must have been medicated when they submitted this script. It has major continuity problems, superficial stereotypical characters, horror formula writing, and simply falls short of making any sense what-so-ever. The creatures, while they have neat skills like going "dim", the question of where they come from and what they are is never so much explored. Don't waste any time on this one.


RICKIE FREEMAN FOR TERI JON Crepe 3/4 Sleeve Peplum Sheath Dress Size 18


Van Halen - Atomic Punk guitar cover - Neogeofanatic


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Microsoft Office 2019 Standard


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U.S.-Mexico border


We understand that condition is extremely important when purchasing a pre-owned item.

Our figures are given a star rating which you can see below.

However, other items such as games may not have a condition rating.

In general, Japanese pre-owned products are in very good condition.

We also hand select the pre-owned items we sell.

If you'd like pictures of any pre-owned item, we can send pictures of the pre-owned item, but not before you purchase the item.

We apologize for the inconvenience this may cause, but we can only send pictures of a used item after you purchase it.

If you're unhappy with the condition, we can of course issue you a full refund.

Solaris Japan uses the following system to rate the condition of pre-owned items:

5 Star Rating: Near mint condition with little to no signs of usage4 Star Rating: Very good condition with minor signs of usage3 Star Rating: Good condition with some signs of usage2 Star Rating: Average condition with several signs of usage or damage1 Star Rating: Very used condition with obvious signs of usage or damage

All pre-owned items come complete with accessories and in box.

Please note that any pre-order or initial release bonuses are usually not included.

DLC codes included with pre-owned games are not guaranteed to be valid.


Q:

Can I trade in off-hours and if not what does the graph shows in that case?

I new to trading and I would like to know why the graph of the stock after closing still follows a path up and down and why it is not a straight line.

Can I trade using on the weekend using the gray graph shown?

Is there any significance of this path/graph in the after hours?

 Does it affect anything or offer
anything valuable that I can use to some advantage?

A:

In the US, pre-market trading is from 4 a.m. to 9:30 a.m. EST and after-hours trading is from 4 p.m. to 8 p.m. on weekdays.

Some collectively call both after hours trading.

Some brokers do not offer after hours trading.

For those that do, it often requires that you get approval to do so, usually just a formality.

After hours trading tends to be more volatile with larger bid/ask spreads due to illiquidity.

You need to be quick thinking and  decisive because price can turn on a dime.


Q:

django loop through model fields

Possible Duplicate:
Django get a model's fields

I have next model:
class People(models.

CharField(max_length=100)
    lastname = models.

CharField(max_length=100)

I want to loop through all items from People table.

In views.py
-When I try this one:
  for each in People().objects.all():
     name=each.name

I am getting that error:
Manager isn't accessible via People instances

-When I try this one:
  for each in People():
     name=each.name

I am getting this error:
'People' object is not iterable

How can I fix that and how to loop through all items from my People table ?

A:

People.objects.all()
it works on the class not an instance People not People()


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WTF is our Dripper line with Max thick VG and is only available in 0,3,6mg strengths.

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We take great pride and care in every product we make and hope that you will do the same in owning one of our uniquely hand crafted mods.

Please contact wholesale@epipemods.com to learn more...

Albert Einstein (Lifetime Member of the Montreal Pipe Smokers Club)

"I believe that pipe smoking contributes to a somewhat calm and objective judgment in all human affairs,"


Q:

"Too many openfiles" error with Glassfish on Ubuntu

I am having issues with tuning Glassfish 2.1.1 on Ubuntu 10.04 LTS 64-bit (Amazon EC2).

As soon as I change the HTTP Service thread count from the default 5 value to 100, I get the following errors in the server.log.

SocketException: Too many open files
Other errors include:
[#|2011-05-19T15:41:38.034-0500|SEVERE|sun-appserver2.1|javax.enterprise.system.tools.deployment|_ThreadID=16;_ThreadName=Timer-20;_RequestID=1bd7cd3e-0011-4ebc-95e5-487b96c76b20;|"DPL8011: autodeployment failure while deploying the application : null"|#]

[#|2011-05-19T15:41:39.555-0500|WARNING|sun-appserver2.1|javax.enterprise.system.stream.err|_ThreadID=20;_ThreadName=Timer-1;_RequestID=0d9630b5-2752-4ffb-ac7c-1cf51920155a;|
java.lang.

NullPointerException
    at com.sun.jbi.management.system.

AutoAdminTask.pollAutoDirectory(AutoAdminTask.java:1031)
    at com.sun.jbi.management.system.

AutoAdminTask.performAutoInstall(AutoAdminTask.java:329)
    at com.sun.jbi.management.system.

AutoAdminTask.performAutoFunctions(AutoAdminTask.java:288)
    at com.sun.jbi.management.system.

AdminService.heartBeat(AdminService.java:967)
    at com.sun.jbi.management.system.

AdminService.handleNotification(AdminService.java:198)
    at com.sun.jmx.interceptor.

DefaultMBeanServerInterceptor$ListenerWrapper.handleNotification(DefaultMBeanServerInterceptor.java:1732)
    at javax.management.

NotificationBroadcasterSupport.handleNotification(NotificationBroadcasterSupport.java:257)
    at javax.management.

NotificationBroadcasterSupport$SendNotifJob.run(NotificationBroadcasterSupport.java:322)
    at javax.management.

NotificationBroadcasterSupport$1.execute(NotificationBroadcasterSupport.java:307)
    at javax.management.

NotificationBroadcasterSupport.sendNotification(NotificationBroadcasterSupport.java:229)
    at javax.management.timer.

Timer.sendNotification(Timer.java:1237)
    at javax.management.timer.

Timer.notifyAlarmClock(Timer.java:1206)
    at javax.management.timer.

TimerAlarmClock.run(Timer.java:1289)
    at java.util.

TimerThread.mainLoop(Timer.java:512)
    at java.util.

TimerThread.run(Timer.java:462)
|#]

and
[#|2011-05-19T16:30:40.228-0500|SEVERE|sun-appserver2.1|org.apache.jasper.servlet.

JspServlet|_ThreadID=17;_ThreadName=httpWorkerThread-4949-46;_RequestID=869579eb-887d-4dc4-b0fc-edc4e41755a7;|PWC6117: File "/opt/glassfish-v2.1.1-b31g/lib/install/applications/admingui/adminGUI_war/homePage.jsp" not found|#]

Googling I found the follow resources:
http://felipeferreira.net/?p=873
http://www.netadmintools.com/art295.html
My /etc/security/limits.confg has the following configuration.

And I have change the tcp settings as noted in http://mariosgaee.blogspot.com/2011/04/glassfish-211-on-linux-performance.html
*       soft    nofile          65535
*       hard    nofile          65535
*       soft    stack           unlimited
*       hard    stack           unlimited

/proc/sys/fs/file-max has a value of 762655 (I did not change this) but I did add to /etc/sysctl.conf as 'fs.file-max = 762655'
ulimit output
$ ulimit -a
core file size          (blocks, -c) 0
data seg size           (kbytes, -d) unlimited
scheduling priority             (-e) 20
file size               (blocks, -f) unlimited
pending signals                 (-i) 16382
max locked memory       (kbytes, -l) 64
max memory size         (kbytes, -m) unlimited
open files                      (-n) 65535
pipe size            (512 bytes, -p) 8
POSIX message queues     (bytes, -q) 819200
real-time priority              (-r) 0
stack size              (kbytes, -s) unlimited
cpu time               (seconds, -t) unlimited
max user processes              (-u) unlimited
virtual memory          (kbytes, -v) unlimited
file locks                      (-x) unlimited

Any ideas what may be causing this issue?

A:

To see actual limits of running process you may use /proc , just get pid of your glassfish/java process and look at cat /proc/$PID_OF_PROCESS/limits
It should be "Max open files" there.

Also you can monitor number of open files with "lsof -p".


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In 2014, total revenue for camping and day use in Oregon State Parks was a little more than $17 million.

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The technology industry is always in flux.

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"""Testing for the boost module (sklearn.ensemble.boost)."""

import numpy as np
from sklearn.utils.testing import assert_array_equal, assert_array_less
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_raises, assert_raises_regexp

from sklearn.cross_validation import train_test_split
from sklearn.grid_search import GridSearchCV
from sklearn.ensemble import AdaBoostClassifier
from sklearn.ensemble import AdaBoostRegressor
from scipy.sparse import csc_matrix
from scipy.sparse import csr_matrix
from scipy.sparse import coo_matrix
from scipy.sparse import dok_matrix
from scipy.sparse import lil_matrix
from sklearn.svm import SVC, SVR
from sklearn.tree import DecisionTreeClassifier, DecisionTreeRegressor
from sklearn.utils import shuffle
from sklearn import datasets

# Common random state
rng = np.random.RandomState(0)

# Toy sample
X = [[-2, -1], [-1, -1], [-1, -2], [1, 1], [1, 2], [2, 1]]
y_class = ["foo", "foo", "foo", 1, 1, 1]    # test string class labels
y_regr = [-1, -1, -1, 1, 1, 1]
T = [[-1, -1], [2, 2], [3, 2]]
y_t_class = ["foo", 1, 1]
y_t_regr = [-1, 1, 1]

# Load the iris dataset and randomly permute it
iris = datasets.load_iris()
perm = rng.permutation(iris.target.size)
iris.data, iris.target = shuffle(iris.data, iris.target, random_state=rng)

# Load the boston dataset and randomly permute it
boston = datasets.load_boston()
boston.data, boston.target = shuffle(boston.data, boston.target,
                                     random_state=rng)

def test_classification_toy():
    # Check classification on a toy dataset.
    for alg in ['SAMME', 'SAMME.R']:
        clf = AdaBoostClassifier(algorithm=alg, random_state=0)
        clf.fit(X, y_class)
        assert_array_equal(clf.predict(T), y_t_class)
        assert_array_equal(np.unique(np.asarray(y_t_class)), clf.classes_)
        assert_equal(clf.predict_proba(T).shape, (len(T), 2))
        assert_equal(clf.decision_function(T).shape, (len(T),))

def test_regression_toy():
    # Check classification on a toy dataset.
    clf = AdaBoostRegressor(random_state=0)
    clf.fit(X, y_regr)
    assert_array_equal(clf.predict(T), y_t_regr)

def test_iris():
    # Check consistency on dataset iris.
    classes = np.unique(iris.target)
    clf_samme = prob_samme = None

    for alg in ['SAMME', 'SAMME.R']:
        clf = AdaBoostClassifier(algorithm=alg)
        clf.fit(iris.data, iris.target)

        assert_array_equal(classes, clf.classes_)
        proba = clf.predict_proba(iris.data)
        if alg == "SAMME":
            clf_samme = clf
            prob_samme = proba
        assert_equal(proba.shape[1], len(classes))
        assert_equal(clf.decision_function(iris.data).shape[1], len(classes))

        score = clf.score(iris.data, iris.target)
        assert score > 0.9, "Failed with algorithm %s and score = %f" % \
            (alg, score)

    # Somewhat hacky regression test: prior to
    # ae7adc880d624615a34bafdb1d75ef67051b8200,
    # predict_proba returned SAMME.R values for SAMME.
    clf_samme.algorithm = "SAMME.R"
    assert_array_less(0,
                      np.abs(clf_samme.predict_proba(iris.data) - prob_samme))

def test_boston():
    # Check consistency on dataset boston house prices.
    clf = AdaBoostRegressor(random_state=0)
    clf.fit(boston.data, boston.target)
    score = clf.score(boston.data, boston.target)
    assert score > 0.85

def test_staged_predict():
    # Check staged predictions.
    rng = np.random.RandomState(0)
    iris_weights = rng.randint(10, size=iris.target.shape)
    boston_weights = rng.randint(10, size=boston.target.shape)

    # AdaBoost classification
    for alg in ['SAMME', 'SAMME.R']:
        clf = AdaBoostClassifier(algorithm=alg, n_estimators=10)
        clf.fit(iris.data, iris.target, sample_weight=iris_weights)

        predictions = clf.predict(iris.data)
        staged_predictions = [p for p in clf.staged_predict(iris.data)]
        proba = clf.predict_proba(iris.data)
        staged_probas = [p for p in clf.staged_predict_proba(iris.data)]
        score = clf.score(iris.data, iris.target, sample_weight=iris_weights)
        staged_scores = [
            s for s in clf.staged_score(
                iris.data, iris.target, sample_weight=iris_weights)]

        assert_equal(len(staged_predictions), 10)
        assert_array_almost_equal(predictions, staged_predictions[-1])
        assert_equal(len(staged_probas), 10)
        assert_array_almost_equal(proba, staged_probas[-1])
        assert_equal(len(staged_scores), 10)
        assert_array_almost_equal(score, staged_scores[-1])

    # AdaBoost regression
    clf = AdaBoostRegressor(n_estimators=10, random_state=0)
    clf.fit(boston.data, boston.target, sample_weight=boston_weights)

    predictions = clf.predict(boston.data)
    staged_predictions = [p for p in clf.staged_predict(boston.data)]
    score = clf.score(boston.data, boston.target, sample_weight=boston_weights)
    staged_scores = [
        s for s in clf.staged_score(
            boston.data, boston.target, sample_weight=boston_weights)]

    assert_equal(len(staged_predictions), 10)
    assert_array_almost_equal(predictions, staged_predictions[-1])
    assert_equal(len(staged_scores), 10)
    assert_array_almost_equal(score, staged_scores[-1])

def test_gridsearch():
    # Check that base trees can be grid-searched.
    # AdaBoost classification
    boost = AdaBoostClassifier(base_estimator=DecisionTreeClassifier())
    parameters = {'n_estimators': (1, 2),
                  'base_estimator__max_depth': (1, 2),
                  'algorithm': ('SAMME', 'SAMME.R')}
    clf = GridSearchCV(boost, parameters)
    clf.fit(iris.data, iris.target)

    # AdaBoost regression
    boost = AdaBoostRegressor(base_estimator=DecisionTreeRegressor(),
                              random_state=0)
    parameters = {'n_estimators': (1, 2),
                  'base_estimator__max_depth': (1, 2)}
    clf = GridSearchCV(boost, parameters)
    clf.fit(boston.data, boston.target)

def test_pickle():
    # Check pickability.
    import pickle

    # Adaboost classifier
    for alg in ['SAMME', 'SAMME.R']:
        obj = AdaBoostClassifier(algorithm=alg)
        obj.fit(iris.data, iris.target)
        score = obj.score(iris.data, iris.target)
        s = pickle.dumps(obj)

        obj2 = pickle.loads(s)
        assert_equal(type(obj2), obj.__class__)
        score2 = obj2.score(iris.data, iris.target)
        assert_equal(score, score2)

    # Adaboost regressor
    obj = AdaBoostRegressor(random_state=0)
    obj.fit(boston.data, boston.target)
    score = obj.score(boston.data, boston.target)
    s = pickle.dumps(obj)

    obj2 = pickle.loads(s)
    assert_equal(type(obj2), obj.__class__)
    score2 = obj2.score(boston.data, boston.target)
    assert_equal(score, score2)

def test_importances():
    # Check variable importances.
    X, y = datasets.make_classification(n_samples=2000,
                                        n_features=10,
                                        n_informative=3,
                                        n_redundant=0,
                                        n_repeated=0,
                                        shuffle=False,
                                        random_state=1)

    for alg in ['SAMME', 'SAMME.R']:
        clf = AdaBoostClassifier(algorithm=alg)

        clf.fit(X, y)
        importances = clf.feature_importances_

        assert_equal(importances.shape[0], 10)
        assert_equal((importances[:3, np.newaxis] >= importances[3:]).all(),
                     True)

def test_error():
    # Test that it gives proper exception on deficient input.
    assert_raises(ValueError,
                  AdaBoostClassifier(learning_rate=-1).fit,
                  X, y_class)

    assert_raises(ValueError,
                  AdaBoostClassifier(algorithm="foo").fit,
                  X, y_class)

    assert_raises(ValueError,
                  AdaBoostClassifier().fit,
                  X, y_class, sample_weight=np.asarray([-1]))

def test_base_estimator():
    # Test different base estimators.
    from sklearn.ensemble import RandomForestClassifier
    from sklearn.svm import SVC

    # XXX doesn't work with y_class because RF doesn't support classes_
    # Shouldn't AdaBoost run a LabelBinarizer?
    clf = AdaBoostClassifier(RandomForestClassifier())
    clf.fit(X, y_regr)

    clf = AdaBoostClassifier(SVC(), algorithm="SAMME")
    clf.fit(X, y_class)

    from sklearn.ensemble import RandomForestRegressor
    from sklearn.svm import SVR

    clf = AdaBoostRegressor(RandomForestRegressor(), random_state=0)
    clf.fit(X, y_regr)

    clf = AdaBoostRegressor(SVR(), random_state=0)
    clf.fit(X, y_regr)

    # Check that an empty discrete ensemble fails in fit, not predict.
    X_fail = [[1, 1], [1, 1], [1, 1], [1, 1]]
    y_fail = ["foo", "bar", 1, 2]
    clf = AdaBoostClassifier(SVC(), algorithm="SAMME")
    assert_raises_regexp(ValueError, "worse than random",
                         clf.fit, X_fail, y_fail)

def test_sample_weight_missing():
    from sklearn.linear_model import LinearRegression
    from sklearn.cluster import KMeans

    clf = AdaBoostClassifier(LinearRegression(), algorithm="SAMME")
    assert_raises(ValueError, clf.fit, X, y_regr)

    clf = AdaBoostRegressor(LinearRegression())
    assert_raises(ValueError, clf.fit, X, y_regr)

    clf = AdaBoostClassifier(KMeans(), algorithm="SAMME")
    assert_raises(ValueError, clf.fit, X, y_regr)

    clf = AdaBoostRegressor(KMeans())
    assert_raises(ValueError, clf.fit, X, y_regr)

def test_sparse_classification():
    # Check classification with sparse input.

    class CustomSVC(SVC):
        """SVC variant that records the nature of the training set."""

        def fit(self, X, y, sample_weight=None):
            """Modification on fit caries data type for later verification."""
            super(CustomSVC, self).fit(X, y, sample_weight=sample_weight)
            self.data_type_ = type(X)
            return self

    X, y = datasets.make_multilabel_classification(n_classes=1, n_samples=15,
                                                   n_features=5,
                                                   return_indicator=True,
                                                   random_state=42)
    # Flatten y to a 1d array
    y = np.ravel(y)

    X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)

    for sparse_format in [csc_matrix, csr_matrix, lil_matrix, coo_matrix,
                          dok_matrix]:
        X_train_sparse = sparse_format(X_train)
        X_test_sparse = sparse_format(X_test)

        # Trained on sparse format
        sparse_classifier = AdaBoostClassifier(
            base_estimator=CustomSVC(probability=True),
            random_state=1,
            algorithm="SAMME"
        ).fit(X_train_sparse, y_train)

        # Trained on dense format
        dense_classifier = AdaBoostClassifier(
            base_estimator=CustomSVC(probability=True),
            random_state=1,
            algorithm="SAMME"
        ).fit(X_train, y_train)

        # predict
        sparse_results = sparse_classifier.predict(X_test_sparse)
        dense_results = dense_classifier.predict(X_test)
        assert_array_equal(sparse_results, dense_results)

        # decision_function
        sparse_results = sparse_classifier.decision_function(X_test_sparse)
        dense_results = dense_classifier.decision_function(X_test)
        assert_array_equal(sparse_results, dense_results)

        # predict_log_proba
        sparse_results = sparse_classifier.predict_log_proba(X_test_sparse)
        dense_results = dense_classifier.predict_log_proba(X_test)
        assert_array_equal(sparse_results, dense_results)

        # predict_proba
        sparse_results = sparse_classifier.predict_proba(X_test_sparse)
        dense_results = dense_classifier.predict_proba(X_test)
        assert_array_equal(sparse_results, dense_results)

        # score
        sparse_results = sparse_classifier.score(X_test_sparse, y_test)
        dense_results = dense_classifier.score(X_test, y_test)
        assert_array_equal(sparse_results, dense_results)

        # staged_decision_function
        sparse_results = sparse_classifier.staged_decision_function(
            X_test_sparse)
        dense_results = dense_classifier.staged_decision_function(X_test)
        for sprase_res, dense_res in zip(sparse_results, dense_results):
            assert_array_equal(sprase_res, dense_res)

        # staged_predict
        sparse_results = sparse_classifier.staged_predict(X_test_sparse)
        dense_results = dense_classifier.staged_predict(X_test)
        for sprase_res, dense_res in zip(sparse_results, dense_results):
            assert_array_equal(sprase_res, dense_res)

        # staged_predict_proba
        sparse_results = sparse_classifier.staged_predict_proba(X_test_sparse)
        dense_results = dense_classifier.staged_predict_proba(X_test)
        for sprase_res, dense_res in zip(sparse_results, dense_results):
            assert_array_equal(sprase_res, dense_res)

        # staged_score
        sparse_results = sparse_classifier.staged_score(X_test_sparse,
                                                        y_test)
        dense_results = dense_classifier.staged_score(X_test, y_test)
        for sprase_res, dense_res in zip(sparse_results, dense_results):
            assert_array_equal(sprase_res, dense_res)

        # Verify sparsity of data is maintained during training
        types = [i.data_type_ for i in sparse_classifier.estimators_]

        assert all([(t == csc_matrix or t == csr_matrix)
                   for t in types])

def test_sparse_regression():
    # Check regression with sparse input.

    class CustomSVR(SVR):
        """SVR variant that records the nature of the training set."""

        def fit(self, X, y, sample_weight=None):
            """Modification on fit caries data type for later verification."""
            super(CustomSVR, self).fit(X, y, sample_weight=sample_weight)
            self.data_type_ = type(X)
            return self

    X, y = datasets.make_regression(n_samples=15, n_features=50, n_targets=1,
                                    random_state=42)

    X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)

    for sparse_format in [csc_matrix, csr_matrix, lil_matrix, coo_matrix,
                          dok_matrix]:
        X_train_sparse = sparse_format(X_train)
        X_test_sparse = sparse_format(X_test)

        # Trained on sparse format
        sparse_classifier = AdaBoostRegressor(
            base_estimator=CustomSVR(),
            random_state=1
        ).fit(X_train_sparse, y_train)

        # Trained on dense format
        dense_classifier = dense_results = AdaBoostRegressor(
            base_estimator=CustomSVR(),
            random_state=1
        ).fit(X_train, y_train)

        # predict
        sparse_results = sparse_classifier.predict(X_test_sparse)
        dense_results = dense_classifier.predict(X_test)
        assert_array_equal(sparse_results, dense_results)

        # staged_predict
        sparse_results = sparse_classifier.staged_predict(X_test_sparse)
        dense_results = dense_classifier.staged_predict(X_test)
        for sprase_res, dense_res in zip(sparse_results, dense_results):
            assert_array_equal(sprase_res, dense_res)

        types = [i.data_type_ for i in sparse_classifier.estimators_]

        assert all([(t == csc_matrix or t == csr_matrix)
                   for t in types])