F # Moving Gjennomsnittet

wiki Slik lærer du gitarskalaer Vekt er en instrumental del av musikkenes repertoar. De gir viktige byggesteiner for komposisjon og improvisasjon i nesten alle stiler og sjanger. Å ta seg tid til å mestre de mest grunnleggende skalaer kan gjøre forskjellen mellom en gjennomsnittlig spiller og en utmerket en. Heldigvis, når det gjelder gitar, er læringsskalaer vanligvis et spørsmål om å huske enkle mønstre gjennom praksis. Trinn Rediger Del en av fire: Grunnleggende konsepter og terminologi Rediger Har allerede en liten grunnleggende musikalsk teori under beltet. Du er velkommen til å hoppe over til vektene selv ved å klikke her. Lær å lese gitarbrettene. På en gitar kalles fronten av den lange, tynne delen hvor du legger fingrene dine på fretboardet. De hevede metallhullene på fretbrettet deler den inn i frets. Vekter blir dannet ved å spille notater på forskjellige mønstre av frets, så det er viktig å kunne identifisere dem. Se nedenfor: Fretsene er nummerert fra halsen til gitarens kropp. For eksempel er fretten i enden av nakken den første fretten (eller Fret 1), den neste Fret er den andre Fret. og så videre. Å holde strengen på en viss fret og strumming strengen over gitarens kropp spiller et notat. Jo nærmere fretsene kommer til kroppen, desto høyere blir notatene. Dotene på hylsen er bare for referanse, og de gjør det lettere å vite hvor du setter fingrene dine uten å måtte telle fretsene oppe i nakken hele tiden. Lær navnene på notatene på fretboardet. Hver eneste fret på gitaren spiller et notat som har et navn. Heldigvis er det bare 12 notater navnene gjentar bare om og om igjen. Notatene du kan spille er under. Merk at noen notater har to forskjellige navn: A, ABb, B, C, CDb, D, DEb, E, F, F Gb, G, GAb. Etter dette begynner notatene på A igjen og gjentar. Å lære posisjonene til de forskjellige notatene er noe som ikke er veldig hardt, men det tar litt for lang tid å dekke i denne artikkelen. Hvis du trenger hjelp, kan du prøve vår artikkel om emnet. Lær navnene på strengene. Du kan snakke om de forskjellige strengene med navn som tykkeste, andre tykkeste osv., Men det er mye lettere å diskutere skalaer hvis du kjenner strengene. Dette er også praktisk fordi strengene er oppkalt etter notatet de spiller når du ikke trykker på noen av fretsene. På en vanlig seks-strengs gitar i standard tuning er strengene: 1 E (tykkeste) A D G B E (tynneste) merk at dette har samme navn som den tykkeste strengen, slik at noen vil si lav og høy E for å fortelle dem fra hverandre. Du ser også noen ganger en liten bokstav e brukt til den tynneste strengen. Lær begrepet hel - og halvtrinn på en skala. Enkelt sagt, en skala er bare en sekvens av notater som høres bra ut når du spiller dem i rekkefølge. Når vi lærer skalaer under, vel se at alle skalaer er bygget fra mønstre av hele trinn og halv trinn. Dette høres komplisert, men dette er bare måter å beskrive forskjellige avstander på fretboardet: 2 Et halvt trinn er en avstand på en fret opp eller ned. For eksempel, hvis du spiller en C (En streng, tredje fret), vil flytte en fret opp gi deg en C (En streng, fjerde fret). Vi kan si at C og C er ett halvt trinn fra hverandre. Et helt trinn er det samme, bortsett fra at avstanden er to frets. For eksempel, hvis vi starter på C og flytter to frets opp, vel spill en D (En streng, femte fret). Dermed er C og D et helt skritt fra hverandre. Grader av en skala. Var nesten klar til å begynne å lære skalaer. Det endelige konseptet for å forstå er at siden skalaer er sekvenser av notater som skal spilles i rekkefølge, får skala notater få spesielle nummererte navn som kalles grader for å hjelpe deg med å identifisere dem. Gradene er listet opp nedenfor. 3 Lære nummeret for hver grad er viktigst, de andre navnene brukes sjeldnere. Notatet du starter på, kalles roten eller først. Det kalles også noen ganger tonic. Det andre notatet kalles det andre eller supertoniske. Det tredje notatet kalles den tredje eller mediant. Det fjerde notatet kalles den fjerde eller underdominanten. Det femte notatet kalles den femte eller dominerende. Det sjette notatet kalles sjette eller submediant. Den syvende noten kalles den syvende den har et par andre navn som endres avhengig av skalaen, så vel ignorere dem i denne artikkelen. Det åttende notatet kalles oktaven. Det kalles også noen ganger tonic fordi det er samme notat som det første, bare høyere. Etter oktaven, kan du enten starte igjen fra den andre eller fortsette på den niende. For eksempel kan notatet etter oktaven kalles den niende eller den andre, men det er samme notat hverken. Øv kromatisk skala for form og hastighet. En type skala som er nyttig fra et praksisperspektiv er kromatisk skala. I denne skalaen er alle grader et halvt trinn fra hverandre. Dette betyr at en kromatisk skala kan gjøres enkelt ved å gå opp og ned fretsene i rekkefølge. Prøv denne kromatiske øvelsen: Velg først en av gitarstrengerne (det spiller ingen rolle hvilken). Begynn å telle en stabil 44-takt. Spill stinget åpent (ingen noter fretted) som en kvart notat, deretter den første fret, så den andre, deretter den tredje. Uten å stoppe, spill den første fretten, så den andre, tredje og fjerde. Hold takten stabil og spill den andre fret, så den tredje, fjerde og femte. Fortsett dette mønsteret til du kommer til 12. kvadrat, og gå ned igjen. Hvis du spiller på høy E-streng, vil din kromatiske øvelse se slik ut: Mål en: E (åpen), F (fret 1), F Fret 2), G (Fret 3) Mål to: F (Fret 1), F (Fret 2), G (Fret 3), G (Fret 4). og så videre opp til 12. kvadre (da nedover). Lær den pentatoniske skalaen. Den pentatoniske skalaen har bare 5 notater, og alle høres bra ut når de spilles sammen, så denne skalaen brukes ofte til solo. Spesielt er den mindre pentatoniske spesielt populær blant rock-, jazz - og bluesmusikk. Det brukes så ofte at det noen ganger bare kalles pentatonisk for kort. Dette er skalaen, lære godt under. Den mindre pentatoniske inneholder disse grader: Rot, flat tredje, fjerde, femte og flatt syvende (pluss oktaven). Det er i utgangspunktet en mindre skala uten den andre eller sjette. For eksempel, hvis vi starter på den lave E-strengen, vil den A-mindre pentatoniske skalaen være: Lav E-streng: A (Fret 5), C (Fret 8) En streng: D (Fret 5), E (Fret 7) D streng: G (fret 5), A (fret 7) Herfra kan vi fortsette å spille, og spille de samme notatene på høyere strenger: G streng: C (fret 5), D (fret 7) B streng: E (fret 5), G (fret 8) E streng: A (fret 5), C (fret 8) Lær blues skalaen. Når du kjenner den lille pentatoniske skalaen, er det veldig enkelt å spille en relatert skala som kalles blues-skalaen. Alt du trenger å gjøre er å legge den flade femte skala graden til den mindre pentatoniske. Dette gir deg en skala med seks notater alt annet er det samme. For eksempel, hvis vi ønsket å veksle en mindre pentatonisk skala inn i A blues skalaen, ville vi spille: Lav E streng: A (fret 5), C (fret 8) En streng: D (fret 5), Eb 6). E (fret 7) D streng: G (fret 5), A (fret 7) G streng: C (fret 5), D (fret 7), Eb (fret 8) B streng: E ​​(fret 5), G fret 8) E-streng: A (fret 5), C (fret 8) Den flate femte er kjent som det blå notatet. Selv om det er i skalaen, høres det litt rart og uforskammet av seg selv, så hvis du er alene, prøv å bruke den som en ledende tone som er, spill den på vei til et annet notat. Ikke heng på det blå notatet for lenge. Lær to oktav versjoner av alle skalaene. Når du når en skala oktav, trenger du ikke å gå ned igjen. Bare behandl oktaven som den nye roten og bruk det samme trinnmønsteret til å spille en annen oktav. Vi berørte dette kort med den lille pentatoniske skalaen over, men dette er noe du kan lære for praktisk talt alle skalaer. Ved å starte på en av de to bunnstrengene, gjør det vanligvis lettere å passe to hele oktaver i samme område av nakken. Merk at den andre oktaven vanligvis har et annet fingermønster, selv om trinnene er de samme. Lar oss lære en to oktav stor skala når du vet dette, det er enklere å finne ut to oktav versjoner av mindre skalaer. Vel, prøv G major (den aller første skalaen vi lærte på toppen av artikkelen). Akkurat nå vet vi dette: Lav E-streng: G (Fret 3), A (Fret 5), B (Fret 7) En streng: C (Fret 3), D (Fret 5), E (Fret 7) D-streng : F (fret 4), G (fret 5) Fortsett å gå, med samme trinnmønster: hele trinnet, hele trinnet, halvtrinnet og så videre. D streng: G (fret 5), A (fret 7) G streng: B (fret 4), C (fret 5), D (fret 7) B streng: E ​​(fret 5), F (fret 7), G (fret 8). og deretter ned igjen Leser Suksesshistorier Forklaringer av intervaller, hvor notatene er opptatt, og hvordan store blir små osv. er ofte i separate opplæringsprogrammer. Her forklares sammenhengen mellom alle disse tingene sammen, noe som gjør det lettere å forstå hver del. Mer - John Smith Virkelig forklarte gitarskalaer og forskjellen mellom stein og blå skalaer på en slik måte at du bare har gitt søte druer til spise. Jeg sier dette etter 2 års erfaring med min lokale gitarlærer og online opplæringsprogrammer. Takk. mer - Ravivarma Gadiraju Jeg har vært å spille gitar i nesten 60 år og aldri hatt en leksjon. Disse artiklene hjalp meg til å forstå hva jeg kan spille. Veldig enkelt og grunnleggende. Takk for hjelpen. Mer - James Kilgore Denne artikkelen hjalp meg mye fordi alt er nevnt her trinn for trinn og med figurer, noe som gjør det så forståelig. Nå kan jeg spille gitarskalaer .. mer - Anjali Patel Det fjernet alle mine spørsmål relatert til skalaformasjonen og bly også. Takk så mye for det herlige emnet .. mer - Akash Wadalkar Dette var veldig nyttig for å øke det som er i mine grunnleggende gitarbøker. Illustrasjonene fungerte veldig bra med teksten .. mer - Tyrone Burson Bildene på siden er ganske nyttige. Artikkelen er enkel og lett for selv en lekmann å forstå. mer - Rajshekar Sampathkumar Det er klart og omfattende, så jeg kan strukturere mine egne leksjoner effektivt. - L. N. Beste leksjon jeg noensinne har hatt. Nå forstår jeg notater og skalaer. Takk - Claus Nadal Jeg elsket det. Så klart og enkelt. Jeg er glad jeg fant denne artikkelen. - Refik Aylan Wonderful, din informasjon er veldig nyttig og komplett. - Vikas Sharma Det er lett å lære å flytte fingerakkordet til akkord. - Lionel Dsilva Svært enkle og flotte bilder, takk - Ryan Gill Fantastisk, veldig detaljert og hjelpsom - Ben CarneyJohann Sebastian Bachs tuning Velkommen J S Bachs kompetanse var hans presise lydkontroll. Bach komponerte en musikkbok som sier direkte det handler om en skikkelig måte å stille inn tastaturinstrumenter på. Musikken i boken presenterer det praktiske musikalske problemet: å spille i alle mulige skalaer, etter eksemplene på denne musikken, trenger vi 25 forskjellige notater. (7 naturlige notater, 7 notater med sharps, 7 notater med leiligheter, 3 flere notater med double-sharps, pluss B dobbelt flat.) Men dette harde kravet må håndteres på en tastatur som bare har 12 løfter per oktav, ikke 25, gjennom noen form for et praktisk kompromiss. Det er nødvendig å temperere de 12 plassene nøye, for å få dem til å lyde musikalsk tiltalende innenfor alle disse skalaene. På toppen av bøkene er tittelsiden en spiralende figur hvis asymmetri trekker oppmerksomhet mot seg selv. For å gjøre det enkelt å tegne det, synes det å ha blitt tegnet med boken rotert (dvs. arbeider langs bunnkanten), og passer den mellom ordene og kanten på siden. Papirene og demonstrasjonene her undersøker følgende hypotese. For å passe bevisene for alle disse kreves 25 notater og skalaer, skal Bachs spiralende linjetegning i sin sammenheng tas som tilleggsbevis: det gir et direkte praktisk diagram for å justere tastaturene ved øret og løse problemet. Det er målrettet uregelmessig, ikke tilfeldig eller fantasifull. Den viser en rask og effektiv hands-on metode for å stille inn et instrument for å spille denne boken, noe som gir en smakfullt ulik balanse, installert uten beregninger. Det viser hvordan du styrer lyden. Det ser ut til at Johann Sebastian Bach nevnte en spesifikk og ulik metode for tastaturinnstilling. Han uttrykte det ikke i våre normalt forventede moderne formater av teori eller tall. Snarere tegnet han et diagram som ser ut som en praktisk hands-on-sekvens for å justere stifterpinnene, og arbeider helt ved øret. Musikken begrenser enhver løsning som er nesten like temperament, og så viser diagrammene uregelmessighet hvordan man skal forme den ønskede subtile ulikheten. I min enkle tolkning, holder den de seks hovednotatene til C-skalaen (C, D, E, F, G, A) i jevnt fordelte stillinger, på deres normale steder innenfor konteksten av 17. århundre praksis. Tuneren skal da installere tastaturene seks gjenværende notater (B og skarphetene F, C, G, D, A) i smakfullt hevede stillinger, med justeringer som vist på diagrammet, slik at de også kan tjene som leiligheter. Denne prosessen med minimal, men nødvendig kompromiss gjør tastaturet klar til å spille musikk i alle 24 store og mindre skalaer. Hver skala har en subtly forskjellig uttrykksfull karakter, da trinnene ikke er helt nøyaktig like store. Harmoniene har forskjellige spenninger og krydder, når notatene i skalaene bygges sammen i akkorder. Bach krevde og viste et system med denne enharmoniske fleksibiliteten, ikke bare i diagrammet, men også gjennom musikken i Das Wohltemperirte Clavier. Den presenterer sin tuning utfordring (og gir løsningen), der de fleste av preludene og fuglene hver krever en jevn håndtering av mer enn 12 notater. For eksempel bruker hans D-hovedforspill og fugue alle Bb, F, C, G, D, A, E, B, F, C, G, D, A og E i samme brikke: 14 notater. Noen av de andre stykkene krever 13, 15, opp til 25 Det siste stykket i boken, B mindre fugue, krever 17 (Eb opp til Fx), og presenterer 13 av dem så tidlig som motivet: seks naturaler C, G , D, A, E, B og syv sharps F, C, G, D, A, E og B. Bach visste selvsagt hvordan han satte opp tastaturene riktig før han skrev sin musikk til dem. Målet er å gjenopprette den spesifikke intonasjonsplanen for hans daglige tastaturinnstilling, lydrelasjonene han forventet å høre i melodier og harmonier, som de kan ha påvirket hans kreative fantasi. Ved å høre hvordan disse musikalske elementene virker gjennom komposisjon og improvisasjon, får vi nye ledetråder i tolkningen av Bachs musikk: påvirker minst områdene artikulasjon, frasering, dynamikk, timing, intensitet og drama. Spenningene og resolusjonene i musikken foreslår friske ideer i ytelse, både gjennom intuitive reaksjoner og gjennom nært analyse. Det resulterende temperamentet har vært fraværende i vår historiebøker. Det gikk tapt under lag av antagelser og vaner som har ført seg bort fra det. Jeg tror at den spesielle lyden av dette temperamentet, som en integrert del av musikalsk praksis, har dype implikasjoner for alle Bachs instrumental - og vokalmusikk som bruker tastaturer: enten med utskrevne deler eller i basso continuo. Siden hver skala har en annen Affekt eller humør, fra den forskjellige musikalske spenningen i intervaller, høres musikken fargerikt og levende som det beveger seg. Bachs musikk selv er en stor kropp av primære bevis for temperament: høres overbevisende strålende og uttrykksfulle når intonasjonen er riktig, eller grov og stygg i temperament som ikke ordentlig løser enharmoniske problemer. Dette LaripS-nettstedet forklarer og forklarer de publiserte papirene, både gjennom teori og praksis. Det gir ulike introduksjoner til dette arbeidet, for ulike nivåer av leserinteresse. Det tjener som et arkiv av ideer da dette temperamentet brukes og diskuteres blant musikere, forskere og entusiaster. Nødvendig bakgrunn: forståelse av vanlige tempereringsmetoder Tastaturstemperaturer er bygd ut fra et prinsipp som noen ganger kalles meantone: i hvilken størrelse en stor tredje er, er tonen (hele trinnet) i gjennomsnittlig (gjennomsnittlig) posisjon. For eksempel, innenfor det store tredje intervallet av C-E, er D plassert på det gjennomsnittlige punktet hvor trinnene C-D og D-E er av samme størrelse som hverandre. I praksis, når man tempererer et tastaturinstrument ved øre, gjøres dette ved å justere en sekvens av femte, og innsnevre hver femte litt med samme mengde. (C-G-D-A-E-B-F-C-G skarp og C-F-Bb-Eb flatward.) Det resulterende oppsettet er vanlig. eller likestilt. Avhengig av mengden av innsnevring som ble gitt til alle femte, har disse vanlige temperamentene forskjellige musikalske egenskaper. I disse vanlige temperamentene er imidlertid sharps og flatene ikke utbytbare. De eneste tilgjengelige notatene er Eb-Bb-F-C-G-D-A-E-B-F-C-G, eller av og til erstatter D for Eb. Når tastaturet er innstilt med en vanlig Bb, vil den tonehøyde høres feil når den spilles i skalaer, melodier eller harmonier som om den var A. Bb er innstilt for høy til å være A. På samme måte er F for høy til å bli spilt som E, B er for lav til å tjene som Cb, og dette problemet fortsetter i alle andre enharmonic stavemåter i notatene. Videre forbinder sharps og flatene ikke med hverandre med femte. Et sted, typisk på G-Eb eller på D-Bb, er det en redusert 6th som er betydelig bredere enn den vanlige femte. Eventuelle intervaller spilt over denne enharmonic gapet lyd grovt og ute av tune, både harmonisk og melodisk, fordi noen av notatene blir feilfortolket med feil enharmonic stavemåte. Disse notatene mangler fra skalaene. For å kunne håndtere musikkens enharmoniske krav, den musikalske stavemåten til notene for deres skalaer og harmoniske intervaller, finnes det flere måter å komme gjennom disse problemene med vanlige temperamenter: Gi separate spak på tastaturet for sharps og leiligheter (selv om Dette gjelder fortsatt ikke problemene med notater som E og Cb, som også fungerer som F naturlig og B naturlig). La lyden være feil for de feilstavede notatene, og håper at det ikke forstyrrer lytterne eller de andre deltakende musikerne for mye. Retune noen av notatene for å kunne spille forskjellige komposisjoner, forutsatt at vi ikke trenger begge navnene til samme spak innenfor en sammensetning. (For eksempel: hvis du ikke trenger Eb eller Bb, må du lagre dem lavere i tonehøyde, være D og A.) Oppsettet kan forbli regelmessig og flytte gapet til et annet sted. Reduser den vanlige mengden temperering i femte med så mye at utformingen utvikler seg til 12-notats lik temperament, kaster bort alle enharmonic skillnader og blir atonale. Dessverre fjerner denne metoden noen akustiske fordeler som kommer fra å ha de mest brukte vektene og harmoniene det beste i tune. Endre vanlig layout for å være smakfullt uregelmessig. Flytte noen av pitchene opp eller ned litt, slik at de kan tjene mer jevnt med to forskjellige navn. Dette er vanlig eller temperament ordinaire praksis, og setter opp kompromisser, slik at tastaturet kan spilles i et bredere spekter av musikk. Allerede innen 1700-tallet kaller mye av den eksisterende musikken for eksotiske notater som D, A, E, B, Ab, Db, Gb, Cb, andor Fb. Det er også vanlig å finne enharmoniske par (som A og Bb), både nødvendige i samme sammensetning. Problemet blir mer ekstreme med Bachs musikk, selv hans tidligste, og den av musikerne rundt ham: så ofte trenger mer enn 12 navngitte notater i en enkelt komposisjon som det ikke var mulig å bruke i vanlig stil i gammelt stil. Musikken selv forteller oss hvilke notater den trenger, for å finne et tilfredsstillende tempereringsprogram for å spille det. Hvor valget er å utlede en vanlig eller uregelmessig oppsett, kan nøye lytte og justering på et tastatur oppsummeres i prosessflytdiagrammer. For mer om dette, se mine innledende og detaljerte flytdiagrammer. Disse to tre-siders flytdiagrammer best studeres ved å arbeide gjennom dem trinn for trinn på et cembalo, som jeg har gjort i 30 år med tuning for øre. De går gjennom praktiske spørsmål om ytelsessituasjonen og de musikalske resultatene, og deretter gjennom lyttings - og testprosessen for hvert notat. Denne praktiske bakgrunnen i ordinær temperering er nødvendig, og arbeider direkte på instrumentet, hvis man skal forstå innholdet i disse artiklene og webbaserte ressurser fullt ut. Min avhandling om Bachs tuning-metode kommer fra musikalsk praksis som utførende harpsykordist og tuner. Det er ikke grafikk, som noen kritikere har feilaktig antatt av en tynn lesing av deler av artiklene, eller fra å lytte til sirkulære argumenter fra en andres hearsay. Musikken bestemmer innenfor en smal grense hva tuningsløsningen må være, selv før noen argumenter om Bachs tegner som ytterligere bevis på sin tuning praksis. For å sette notatene på poeng hvor de kan betjene dobbeltverdier i skalaforhold med alle de andre notatene rundt dem, blir hevene hevet fra standardposisjonene i et vanlig temperament, og leilighetene senkes tilsvarende. Vi jobber i sin tur med G, Eb, C, Bb, F, F og B, og deres enharmonicrespellasjoner, tester alt nøye med alle konkurrerende skalaer og harmonier som inneholder dem. Prosessen krever smak og musikalsk opplevelse, flytter notatene individuelt til alt balanserer riktig, som kreves av musikken. Notatene som brukes i komposisjonene er vanskelige fakta. verifiserbare av noen. Som primær kilde forteller den musikalske poengsummen hvilke tilpasninger som er nødvendige som kompromisser, for å sette opp alle notatene for alle deres melodiske og harmoniske sammenhenger. Etter at de praktiske justeringene av tonehøyde er gjort og testet grundig i musikken som skal spilles , det resulterende uregelmessige temperamentet kan skrives ned. Dette gjør det lettere å reprodusere nøyaktig ved andre anledninger, slik at man hver gang ikke må løse det samme problemet med smakfulle justeringer. Det tror jeg, er det Bach gjorde her: Gjennom en vanlig prosess for å lytte til og justere skalaene fant han (eller noen rundt ham) et veldig godt uregelmessig oppsett som løser alle musikalske problemer. Det gjør at man kan leke vakkert i alle 24 store og mindre skalaer, samtidig som den holder de mest akustisk gunstige lydene i de mest vanlige skalaene. Det gir nok kontrast at hver skala lyder subtilt annerledes, noe som kan gjøre musikken mer spennende og interessant som den modulerer. Han skrev ned nok detaljer, et bilde av tempereringsresultatet, for å vise hvordan man gjør det igjen. Oppskriften Hvordan jeg tror Bach selv forklarte det til erfarne harpsichord-tunere ved øret, trinnvis, med (eller uten) hans diagram: Vi satte opp notatene til C-skalaen først, og deretter passer vi de resterende notatene forsiktig inn i kompromitterte flekker: ikke som den gamle stilen, hvor du ble tvunget til å velge enten en skarp eller en flat, og få det til å høres dårlig som den andre. Still din naturlige 5th FCGDAE med din hverdagslige prosess for å gjøre alle femte (eller fjerde) vevet med mild lik kvalitet, og kontroller at FA og CE hver ende opp litt skarpe ditt kontrollpunkt her er at FA er bred på omtrent 3 per sekund i tenoren. Heres den lille jot på den ene siden, som viser de 3 beats. Du ville normalt ha gjort alt annet med samme type 5: E-B-F-C-G, og F-Bb-Eb, og la et gap der mellom Eb og G hvor det ikke kobles. I stedet skal vi sette alle de resterende notatene i smakfullt kompromitterte stillinger, slik at vi kan spille musikk som har enten sharps eller leiligheter helt rundt. Fra E legger du de neste tre notatene høyere enn vanlig, og gjør bare ren femte E-B-F-C. Du merker at C står opp ganske høy og lys mot A, men når du sjekker den som Db-F, har A-C og Db-F samme kvalitet som hverandre. Det er hvordan det fungerer bra å spille all musikk. Fortsett med fra C, sett de tre siste notatene G-D-A på plass med bare halvparten så mye herding som du brukte på den naturlige femte: bare en veldig liten vifte, hver. Det vil si at når du gjør hver, legger du hver i sin rene femte plass, men deretter tar den den minste minste bit. Sjekk at du gjør Ab-C litt bedre enn E-G, Eb-G bedre enn B-D, og ​​Bb-D bedre enn F-A. Som ditt siste kontrollpunkt fra A tilbake til F, er det resterende punktet en litt bred femte, men ikke plagsomt (ingen hører det, noen få skritt vekk fra instrumentet): Det vinker like mye som CGDAen du nettopp har avsluttet, men i motsatt retning. Heres jotten på den andre siden, som viser kvaliteten på A-F overlegen, den reduserte 6. Fullfør instrumentet med oktaver i begge retninger. Dette diagrammet viser deg kvaliteten på alle 5., hvis du vil sjekke oktavene dine med dem når du går. Nå, spill og improvisere musikk i alle mulige skalaer, alt fungerer. Du vil legge merke til at den samsvarer med tastaturets fysiske layout: Når du må strekke en finger for å spille skarp eller flat, høres musikken litt mer krydret enn når du spiller på bare de naturlige notatene. Min hoved vitenskapelige artikkel som foreslår denne lesningen av bevisene, er publisert av seksjoner i februar og mai 2005 av Early Music. Den artikkelen, Bachs ekstraordinære temperament: vår Rosetta Stone. beskriver den historiske konteksten og gir musikalsk og matematisk analyse. Oversikt og gratis nedlasting av sine syv PDF-filer fra Oxford University Press En tilleggsartikkel Bach temperamentet og clavichordet er tilgjengelig i november 2005-utgaven av Clavichord International. Den inneholder videre diskusjon av praktiske problemstillinger: noen spesielt for clavichord, noe mer generelt i analyse av Bachs tastaturmusikk, skala struktur, enharmonic overvejelser og øreinnstilling instruksjoner. Komposisjonene som presenteres inkluderer BWV 772-801, 802, 808, 849, 887, 988, 1079 og 1080. Oversikt Fulltekst En november 2005 essay Tuningen gir en tosiders sammendrag av temperamentet og dets musikalske karakter. Fulltekst Det er trykt i hefterne på Peter Watchorns CDer. 2006-artikkelen Bachs Art of Temperament for BBC Music Magazine forklarer videre dette temperamentet fra flere andre praktiske vinkler, spesielt med fokus på blandingen av C-major og B-skalaene. (C, D, E, F, G, A, B B, C, D, E, F, G, A) Fulltekst BBCs versjon ble forkortet og gitt tittelen In Good Temper. Andre artikler om dette temperamentet er oppført her. Det er også en side av mine svar på andre folks artikler og bøker der de presenterer sine avtaler eller uenigheter med dette temperamentet. Mine oktober 2008 forelesningsnotater for James Madison University viser seg å være nesten en komplett artikkel, i seg selv. I tidlig musikk november 2009 har jeg et brev til redaktøren. kaller for rettferdig argumentasjon om dette emnet. spesielt fra Mark Lindley. hvem har misrepresentert og disdained arbeidet mitt tre ganger i den tidsskriftet. I ulik temperament. Viola da Gamba Society Journal vol 3 del 2 (2009), 137-163, jeg gjennomgår en 2009-bok av Claudio di Veroli. Jeg tar også opp noen nyere argumentasjon om Bach keyboard-temperament, og debunk 1979-analysemetoden til John Barnes. PDF Se også forelesningsnotatene fra oktober 2010, en presentasjon ved University of Colorado: Recovering Bachs tuning fra Well-Tempered Clavier. Disse gir et dypere perspektiv på teknikken til å undersøke hvilke notater som brukes i ulike sammensetninger, og måten at prosessen informerer påstandene om temperament. Hurtigstart Hva kan en nybegynner til dette materialet lese først, mest produktivt Åpne streaming-lydsiden og starte litt musikk i bakgrunnen. Deretter begynner du å lese Bachs kunst av temperamentartikkel eller det uformelle forelesningen. Jeg har utarbeidet et mer formelt sett med notater (lysbilder i en PowerPoint-presentasjon) for en offentlig forelesning ved James Madison University, 22. oktober 2008. Ta også en titt på videoene som viser at et cembalo er innstilt og spilt. Nyt Enkel måte å stille inn det nøyaktig og det meste elektronisk. Hvis du foretrekker å ikke stille på øret, og ikke må telle noen slag overalt, gjør du dette: Velg Vallotti på din elektroniske enhet. Det må være en nøyaktig Vallotti, ikke en merkelig hybrid av VallottiYoung. Sett alle følgende notater nøyaktig hvor de er i Vallotti: C, D, Eb, E, F, G og A. Slå av. Kontroller nøyaktigheten av naturals, ved øre: F-C, C-G, G-D, D-A, A-E. Disse burde alle ha en identisk kvalitet (litt smal 5. eller bred 4.de), hver vevende forsiktig, og gir en jevn syklus av 5ths4ths. Hør etter kvalitet. ikke for å telle noen slagfrekvenser. Fra E, still inn B som en ren femte eller fjerde. Fra B, still inn F som en ren femte eller fjerde. Fra F, still inn C som en ren femte eller fjerde. Fra C, still inn G som en ren 5., men sammenlign deretter den med D. Nedre G litt, og tester begge disse intervaller (CG og GD) til du finner det gjennomsnittlige stedet hvor det er like herdet fra begge: en veldig mild forurensning . Endelig stiller du Bb ren fra både Eb og F. Deretter senker du Bb litt, samme beløp som du senket G, til både Eb-Bb og Bb-F viser samme urenhet som du ga til C-G. Det er alt Finish instrumentet med rene oktaver og rene unisons overalt. Når du angir oktavene, kontroller alle 5. og 4. klasse for øret for passende kvalitet. Denne vanen er spesielt nyttig når du arbeider på diskanten. Du slutter med: F-C-G-D-A-E som de er i Vallotti (16 komma hver) E-B-F-C ren C-G-D-A veldig forsiktig herdet (112 komma hver) A-F overbløt er også forsiktig temperert, men skjer for å være bred. Offsets for ClearTune, PitchLab og andre elektroniske tunere Hvis du bruker en app eller en enhet som tillater definisjoner av egendefinerte temperamenter, for eksempel ClearTune. sett det opp med følgende sent offsets fra samme temperament: Sjekk alt etter øre, som beskrevet i avsnittet ovenfor. Du bør ha en jevn og glatt F-C-G-D-A-E (alle med samme kvalitet som hverandre, 16 komma smal), en ren E-B-F-C og en veldig forsiktig vevende C-G-D-A. BbA bør plasseres på et sted som er svært litt lavere enn stedet der det ville vært rent fra både D og F. Når du angir oktavene, kontroller alle 5 og 4 i øre for passende kvalitet. Denne vanen er spesielt nyttig når du arbeider på diskanten. For PitchLab-mottakeren, som er nyere (2014) og bedre enn ClearTune, gjør du følgende: Få opplåsingen av alt betalt versjon av appen, for å få full kontroll over hva du gjør. Lag BachLehman 1722 som et tilpasset temperament. Skriv inn forskyvningene fra C, ikke A. Tallene som skal brukes er: C (0,0), C (-2,0), D (-3,9), Eb (-2,0), E (-7,8), F (2,0), F (-3,9), G (-2,0), G (-2,0), A (-5,9), Bb (-2,0), B (-5,9). Når du stemmer med det, må du sørge for at rotnoten er satt til C, ikke A. Kontroller alt arbeidet ditt ved øret, når du er ferdig, for å være sikker på at det ikke har skjedd noen feil eller transposisjoner. Du bør ha en jevn og glatt F-C-G-D-A-E (alle med samme kvalitet som hverandre, 16 komma smal), en ren E-B-F-C og en veldig forsiktig vevende C-G-D-A. BbA skal plasseres på et sted som er svært litt lavere enn stedet der det ville vært rent fra både D og F. Se også denne anmeldelsen av PitchLab av Paul Poletti. Audio samples and video demonstrations There are pages of recorded musical examples and 20-minute playlists of streaming audio. with performances by Bradley Lehman on harpsichords and pipe organs. New Additional sample recordings are available variously on Last. fm. on iLike. and Facebook as featured excerpts from LaripS 1002 (organ) and LaripS 1003 (harpsichord and organ). New More than a dozen recordings by other musicians using this BachLehman 1722 temperament: on harpsichords, fortepianos, pipe organs, digital organs, synthesizers, and more. There is a growing collection of video demonstrations. showing how to tune harpsichords by ear in this and several related temperaments. Other resources Introductory lecture at an informal level. (How to explain temperament, and why it matters, to teenagers) A temperament diagram with remarks about the scales and intervals. Several sets of instructions for tuning instruments by ear, or with electronic devices. Several additional temperaments to set by ear. see especially my ordinary temperament to play 17th century German music (Bonus 5 on that page). New in November 2008 Jean-Philippe Rameaus published preference in 1726 was apparently for a system with regular tempering in Bb-F-C-G-D-A-E-B, and the other four notes tastefully arranged to fill the gap. My presentation of this is in section 6 of the practical instructions page. A historical survey of other Bach temperaments as hypothetical reconstructions. This blog post says the opposite of its lazy and deliberately provocative title. I have become a huge fan of ReactiveUI. I just want to ramble about the path I took to get here. Listening to Paul Betts I first heard about ReactiveUI at a conference presentation by Paul Betts. I think it was at Xamarin Evolve. Mostly I remember feeling dumb. He said a lot of things that I didnt understand. I went to that session without much real experience in Model-View-ViewModel (MVVM) development. Conceptually, I understood the idea of a ViewModel. But Paul mostly talked about how ReactiveUI avoids certain problems. And since I had not experienced those problems, his words didnt sink in. Talking to teenagers about risk Each time one of my kids was approaching adolescence, I sat down and explained the risks associated with certain choices. Laws and moral judgements aside, the simple fact is that many choices involve risks, and I thought it would be helpful to pass along that bit of information. And in each case, my child said, Thanks Dad, and proceeded to always make wise and low-risk choices from that point on. Well, actually, no. Teenagers simply do not learn that way. They process risk very differently from people who are more mature. Tell a 16-year-old that if you drive too fast you might get a ticket. The adolescent will immediately begin driving too fast, and, in all likelihood, will not get ticket. This is how teenagers realize they are smarter than their parents. Tangent 1: It is almost certainly a good thing that young people are more brave. It would be Very Bad if everybody started out with the same level of risk aversion as the average 65-year-old. Go watch the Tapestry episode of Star Trek TNG. Tangent 2: I really should claim no expertise in parenting, but if somebody forced me to write a book on parenting a teenager, I would say this: Let your kid suffer from their own choices. That said, it is worth the effort to try and help them avoid the really bad mistakes, the ones with consequences that last for decades. But they do have to learn to make their own choices. Realize this as early as you can. The path to frustration starts with making everything all about you. How we learn new technologies My metaphor has many problems. For starters, Paul Betts is not my Dad. Also, the element of adolescent rebellion was not present. I didnt hear Pauls wisdom and run in the opposite direction because of my deep need to separate my identity from his. In fact, I started devouring everything I could find on MVVM and IObservable. I really wanted to understand what he was saying. But the metaphor works in one significant way: Like a teenager, I had to learn by doing. Nobodys words made much of a difference. None of that reading helped me become a a user of ReactiveUI. I went down another path. Actually, I went down several other paths. Maybe its just me I observe that most developers want content that explains how to get something done. If your objective is to do X, then do the following steps. The most popular books and articles tend to follow this pattern. Questions of this form are the ones that do well on StackOverflow. But this is almost never what I want. I much prefer content that explains how things work. Once I understand that, I can figure out the steps myself. When I am developing software, I always, ALWAYS do better when I understand what is going on under hood, when I can see through the leaky abstractions. And as I mentioned, I am apparently in the very small minority on this. If 90 of the world disagrees with me, does that put me in the top 10. Or does it mean my approach is somehow defective Modesty aside, my history contains enough successes to allow me some confidence in believing that my approach is better. I also observe that my approach is just a different spelling for the old adage, Give a man a fish and you feed him for a day. Teach a man to fish and he eats for a lifetime. If you tell a software developer what to type and where to click, you can help them complete todays task. But if you instead teach them how things work, they will be able to apply that understanding on other days too. Hmmm. Im talking myself into this. I dont know why most people prefer shallow recipes, but I really do think deep understanding is better. Still, I like to stay open-minded about things. Ive got a lot of failures too. The truth is that my approach has tradeoffs. The need to understand everything tends to slow me down during the early stages. I usually gain some of that back in the fourth quarter of the game, where deeper understanding is often helpful in diagnosing tricky problems. But again, in the decision making around software development, absolutes are rare. Ill admit that sometimes a simple set of steps without depth are exactly what is needed. Maybe the ReactiveUI docs are just bad I dont know. Kan være. Ive read the docs plenty. They dont seem bad to me. I also see nothing there that makes me want to defend them as the best docs ever. Suppose that I regret not choosing ReactiveUI sooner. Further suppose that I wanted to blame somebody else for my choices. I guess I could find something to complain about. But I also dont tend to find that criticizing somebody elses work is helpful. And remember, I started this journey sitting in front of an audience, listening to Paul Betts, and feeling dumb. To be clear, in that kind of context, I like feeling dumb. Its an opporunity to learn. So why did I not choose ReactiveUI sooner I guess I dont really know. But Im pretty sure that nothing has made me appreciate ReactiveUI more than the suffering that comes from not using it. And that remark isnt very helpful, is it Id like to try and do better. Lets see. Son, its just basic statistics. If youre going to always drive 15 MPH over the speed limit, you will eventually get caught. Suppose you roll the dice 20 times in a row without getting a 12. You still might get a 12 on the next roll, right Oh, wait, wrong topic. Let me try again. Why is ReactiveUI awesome In some software development situations, like mobile apps, if you take a step back and look at the forest instead of the trees, you will see that most of your code is reacting to something that changed. There are lots of tools you can use to approach this kind of app. You can use C events and callbacks and switch statements and delegates and lambdas and observables and notifications and bindings and more. For simple apps, none of these approaches are much better than any other. But as your app gets more complicated, some approaches cope more gracefully than others. Most cars drive pretty smooth at 30 MPH. But at 75 MPH, some vehicles are still giving a smooth ride, while others are shaking. Lets try a conceptual example or two. Suppose you have a button, and you want something to happen when the user presses that button. This is pretty simple. All reasonable solutions to this problem are about the same. On the other hand, lets say you have a list of items. The items in that list come from a SQL query. That query has 4 inputs, each of which comes from a UI control. Every time one of those controls changes its value, the query needs to be re-run and the list needs to be updated. A couple of those controls need to be disabled under certain circumstances. These UI elements have a complicated relationship. We still have plenty of choices in how to express that relationship in code, but this situation is complicated enough that we start to see differences between those approaches. Some of the ones that worked out really well in the simple case seem kinda tedious for this case. If my driveway has half an inch of snow, all methods of clearing it are about the same. But if my driveway has 15 inches of snow, a shovel is decidedly inferior to a tractor. Why do I like ReactiveUI Because I have found that it copes gracefully as the situation gets more complicated. Why is this Much of the credit goes to the reactive foundation on which ReactiveUI is built. Reactive Extensions. Rx. IObservable. These building blocks are particularly adept at expressing the relationship between a group of things that are changing. ReactiveUI adds another layer (or two) on top of these things to make that expressiveness more convenient when implementing user interfaces. To be honest, I fudged a little bit when I said that all solutions are roughly equivalent when the problem is simple. Thats not quite true. For simple situations, Id have to admit that ReactiveUI might be a little worse. There is a learning curve. If I am writing a grocery list, I could use a word processor, but a pencil and paper is actually simpler. But if I am writing a novel, the word processor is the clear winner. Im claiming that the effort to learn Rx and ReactiveUI is worth the trouble. My claim is based on this notion that ReactiveUI shines as complexity increases, but also on my belief that most people underestimate the complexity of their app. If you disagreed with me above when I said that most of your code is reacting to something that changed, you might be underestimating the complexity of your app. It is in fact very common to start implementing under the assumption that something will not change and then later realize that you need notifications or events. Or an observable. Would the paragraphs above have changed my course earlier I dont know. Probably not. I didnt start this believing that I could write the best ReactiveUI advocacy ever. Looking at it now, I cant believe I wrote it with no code in it. The canonical ReactiveUI evangelism pamphlet has gotta have WhenAnyValue() in it somewhere. I just think its interesting that despite my best efforts, I was unable to really understand the benefits of ReactiveUI until I tried using its alternatives. My current project is late. If I had chosen ReactiveUI earlier, maybe it would be, er, less late There are questions here worth asking. But am I 100 certain that it is always better to spare yourself the learning experience of using less effective approaches No. Can I credibly claim that everyone should choose ReactiveUI in every situation Certainly not. Maybe all I can say is that I am currently having a great experience with ReactiveUI. Maybe that means the rest of this blog post is useless. But you should have known that when you saw the cheesy title. Recently, Sven Slootweg (joepie91) published a blog entry entitled Why you should never, ever, ever use MongoDB. It starts out with the words MongoDB is evil and proceeds to give a list of negative statements about same. I am not here to respond to each of his statements. He labels them as facts, and some (or perhaps all) of them surely are. In fact, for now, lets assume that everything he wrote is correct. My point here is not to say that the author is wrong. Rather, my point here is that this kind of blog entry tells me very little about MongoDB while it tells me a great deal about the emotions of the person who wrote it. Like I said, it may be true that every WTF the author listed is correct. It is also true that some software has more WTFs than others. Im not a MongoDB expert, but Ive been digging into it quite a bit, and I could certainly make my own list of its WTFs. And I would also admit that my own exploration of Couchbase has yielded fewer of those moments. Therefore, every single person on the planet who chooses MongoDB instead of Couchbase is making a terrible mistake, right Let me briefly shift to a similar situation where I personally have a lot more knowledge: Microsoft SQL Server vs PostgreSQL. For me, it is hard to study SQL Server without several WTF moments. And while PostgreSQL is not perfect, I have found that a careful study there tends to produce more admiration than WTFs. So, after I discovered that (for example) SQL Server has no support for deferred foreign keys, why didnt I write a blog entry entitled Why you should never, ever, ever use SQL Server Because I calmed down and looked at the bigger picture. I think I could make an entirely correct list of negative things about SQL Server that is several pages long. And I suppose if I wanted to do that, and if I were really angry while I was writing it, I would include only the facts that support my feelings, omitting anything positive. For example, my rant blog entry would have no reason to acknowledge that SQL Server is the mostly widely used relational database server in the world. These kinds of facts merely distract people from my point. But what would happen if I stopped writing my rant and spent some time thinking about the fact I just omitted I just convinced myself that this piece of software is truly horrible, and yet, millions of people are using it every day. How do I explain this If I tried to make a complete list of theories that might fit the facts, todays blog entry would get too long. Suffice it to say this: Some of those theories might support an anti-Microsoft rant (for example, maybe Microsots field sales team is really good at swindling people), but Im NOT going to be able to prove that every single person who chose SQL Server has made a horrible mistake. There is no way I can credibly claim that PostgreSQL is the better choice for every single company simply because I admire it. Even though I think (for example) that SQL Server handles NULL and UNIQUE in a broken way, there is some very large group of people for whom SQL Server is a valid and smart choice. So why would I write a blog entry that essentially claims that all SQL Server users are stupid when that simply cannot be true I wouldnt. Unless I was really angry. MongoDB is undisputably the top NoSQL vendor. It is used by thousands of companies who serve millions of users every day. Like all young software serving a large user base, it has bugs and flaws, some of which are WTF-worthy. But it is steadily getting better. Any discussion of its technical deficiences which does not address these things is mostly just somebody venting emotion. Memory safety I have written a lot of C code over the years. More than once while in the middle of a project, I have stopped to explore ways of getting the compiler to catch my memory leaks. I tried the Clang static analyzer and Frama-C and Splint and others. It just seemed like there should be a way, even if I had to annotate function signatures with information about who owns a pointer. So perhaps you can imagine my joy when I first read about Rust. Even more cool, Rust has taken this set of ideas so much further than the simple feature I tried to envision. Rust doesnt just detect leaks, it also: frees everything for you, like a garbage collector, but its not. prevents access to something that has been freed. prevents modifying an iterator while it is being used. prevents all memory corruption bugs. automatically disposes other kinds of resources, not just allocated memory. prevents two threads from having simultaneous access to something. That last bullet is worth repeating: With Rust, you never stare at your code trying to figure out if its thread safe or not. If it compiles, then its thread safe. Safety is Rusts killer feature, and it is very compelling. Mutability If you come to Rust hoping to find a great functional language, you will be disappointed. Rust does have a bunch of functional elements, but it is not really a functional language. Its not even a functional-first hybrid. Nonetheless, Rust has enough cool functional stuff available that it has been described as ML in C clothing. I did my Rust port of LSM as a line-by-line translation from the F version. This was not a particularly good approach. Functional programming is all about avoiding mutable things, typically by using recursion, monads, computation expressions, and immutable collections. In Rust, mutability should not be avoided, because its safe. If you are trying to use mutability in a way that would not be safe, your code will not compile. So if youre porting code from a more functional language, you can end up with code that isnt very Rusty. If you are a functional programming fan, you might be skeptical of Rust and its claims. Try to think of it like this: Rust agrees that mutability is a problem -- it is simply offering a different solution to that problem. Learning curve I dont know if Rust is the most difficult-to-learn programming language I have seen, but it is running in that race. Anybody remember back when Joel Spolsky used to talk about how difficult it is for some programmers to understand pointers. Rust is a whole new level above that. Compared to Rust, regular pointers are simplistic. With Rust, we dont just have pointers. We also have ownership, borrows, and lifetimes. As you learn Rust, you will reach a point where you think you are starting to understand things. And then you try to return a reference from a function, or store a reference in a struct. Suddenly you have lifetime ltagt annotations ltagt all ltagt over ltagt the ltagt place ltagt . And why did you put them there Because you understood something Heck no. You started sprinkling explicit lifetimes throughout your code because the compiler error messages told you to. Im not saying that Rust isnt worth the pain. I personally think Rust is rather brilliant. But a little expectation setting is appropriate here. Some programming languages are built for the purpose of making programming easier. (It is a valid goal to want to make software development accessible to a wider group of people.) Rust is not one of those languages. That said, the Rust team has invested significant effort in excellent documentation (see The Book ). And those compiler error messages really are good. Finally, let me observe that while some things are hard to learn because they are poorly designed, Rust is not one of those things. The deeper I get into this, the more impressed I am. And so far, every single time I thought the compiler was wrong, I was mistaken. I have found it helpful to try to make every battle with the borrow checker into a learning experience. I do not merely want to end up with the compiler accepting my code. I want to understand more than I did when I started. Error handling Rust does not have exceptions for error handling. Instead, error handling is done through the return values of functions. But Rust actually makes this far less tedious than it might sound. By convention (and throughout the Rust standard library), error handling is done by returning a generic enum type called ResultltT, Egt. This type can encapsulate either the successful result of the function or an error condition. On top of this, Rust has a clever macro called try. Because of this macro, if you read some Rust code, you might think it has exception handling. This function returns std::io::Resultltu64gt. When it calls the seek() method of the trait object it is given, it uses the try macro, which will cause an early return of the function if it fails. In practice, I like Rusts Result type very much. The From and Error traits make it easy to combine different kinds of ResultError values. The distinction between errors and panics seems very clean. I like having the compiler help me be certain that I am propagating errors everywhere I should be. (I dislike scanning library documentation to figure out if I called something that throws an exception I need to handle.) Nonetheless, when doing a line-by-line port of F to Rust, this was probably the most tedious issue. Lots of functions that returned () in F changed to return Result in Rust. Type inference Rust does type inference within functions, but it cannot or will not infer the types of function arguments or function return values. Very often I miss having the more complete form of type inference one gets in F. But I do remind myself of certain things: The Rust type system is far more complicated than that of F. Am I holding a Foo Or do I have a ampFoo (a reference to a Foo) Am I trying to transfer ownership of this value or not Being a bit more explicit can be helpful. F type inference has its weaknesses as well. Most notably, inference doesnt work at all with method calls. This gives the object-oriented features of F a very odd feel, as if they dont belong in the language, but it would be unthinkable for a CLR language not to have them. Rust has type inference for integer literals but F does not. The type inference capabilities of Rust may get smarter in the future. Rust iterators are basically like F seq (which is an alias for IEnumerable). They are really powerful and provide support for functional idioms like List. map. For example: This function takes a slice (a part of an array) of bytes (u8) and returns its representation as a hex string. Vec is a growable array iter() means something different than it does in F. Here, it is the function that returns an iterator for a slice map() is pretty similar to F. The argument above is Rusts syntax for a closure. collect() also means something different than it does in F. Here, it consumes the iterator and puts all the mapped results into the Vec we asked for. connect() is basically a join of all the resulting strings. However, there are a few caveats. In Rust, you have a lot more flexibility about whether you are dealing with a Foo or a reference to a Foo, and most of the time, its the latter. Overall, this is just more work than it is in F, and using iterators feels like it magnifies that effect. Performance I havent done the sort of careful benchmarking that is necessary to say a lot about performance, so I will say only a little. I typically use one specific test for measuring performance changes. It writes 10 LSM segments and then merges them all into one, resulting in a data file. On that test, the Rust version is VERY roughly 5 times faster than the F version. The Rust and F versions end up producing exactly the same output file. The test is not all that fair to F. Writing an LSM database in F was always kind of a square-peground-hole endeavor. With Rust, the difference in compiling with or without the optimizer can be huge. For example, that test runs 15 times faster with compiler optimizations than it does without. With Rust, the LLVM optimizer cant really do its job very well if it cant do function inlining. Which it cant do across crates unless you use explicit inline attributes or turn on LTO. In F, there often seems to be a negative correlation between idiomatic-ness and performance. In other words, the more functional and idiomatic your code, the slower it will run. F could get a lot faster if it could take better advantage of the ability of the CLR to do value types. For example, in F, option and tuple always cause heap allocations. Integer overflow Integer overflow checking is one of my favorite features of Rust. In languages or environments without overflow checking, unsigned types are very difficult to use safely, so people generally use signed integers everywhere, even in cases where a negative value makes no sense. Rust doesnt suffer from this silliness. For example, the following code will panic: That said, I havent quite figured out how to get overflow checking to happen on casts. I want the following code (or something very much like it) to panic: Note that, by default, Rust turns off integer overflow checking in release builds, for performance reasons. Miscellany F is still probably the most productive and pleasant language I have ever used. But Rust is far better than C in this regard. IMO, the Read, Write, and Seek traits are a much better design than s Stream, which tries to encapsulate all three concepts. cargo test is a nice, easy-to-use testing framework that is built into Cargo. I like it. crates. io is like NuGet for Rust, and its integrated with Cargo. If cargo bench wants to always report timings in nanoseconds, I wish it would put in a separator every three digits. I actually like the fact that Rust is taking a stance on things like functionnamesinsnakecase and TypeNamesInCamelCase. even to the point of issuing compiler warnings for names that do not match the conventions. I dont agree 100 with their style choices, and thats my point. Being opinionated might help avoid a useless discussion about something that never really matters very much anyway. I miss printf-style format strings. Im not entirely sure I like the automatic dereferencing feature. I kinda wish the compiler wouldnt help me in this manner until I know what Im doing. Bottom line I am seriously impressed with Rust. Then again, I thought that Eric Banas Hulk movie was pretty good, so you might want to just ignore everything I say. In terms of maturity and ubiquity, C has no equal. Still, I believe Rust has the potential to become a compelling replacement for C in many situations. I look forward to using Rust more. Zumero for SQL Server (ZSS) is a solution for replication and sync between SQL Server and mobile devices. ZSS can be used to create offline-friendly mobile apps for iOS, Android, Windows Phone, PhoneGap, and Xamarin. Our 2.0 release is a major step forward in the maturity of the product. Compatibility with Azure SQL -- This release offers improved compatibility with Microsoft Azure SQL Database. Whether you prefer cloud or on-prem, ZSS 2.0 is a robust sync solution. Improved filtering -- In the 2.0 release, filters have become more powerful and easier to use. Arcane limitations of the 1.x filtering feature have been lifted. New capabilities include filtering by date, and filtering of incoming writes. Schema change detection -- The handling of schema changes is now friendlier to the use of other SQL tools. In 1.x, schema changes needed to be performed in the ZSS Manager application. In 2.0, we detect and handle most schema changes automatically, allowing you to integrate ZSS without changing the way you do things. Better UI for configuration -- The ZSS Manager application has been improved to include UI for configuration of multiple backend databases, as well as more fine-grained control of which columns in a table are published for sync. Increased Performance -- Perhaps most important of all, ZSS 2.0 is faster. In some situations, it is a LOT faster. Isnt New Microsoft awesome NET is going open source And cross-platform On Github. The news out of Redmond often seems like a mis-timed April fools joke. But its real. Dette skjer. Microsoft is apparently willing to do whatever it takes to get developers to love them again. How did this company change so much, so quickly A lot of folks are giving credit to CEO Satya Nadella. And there could be some truth to that. Maaaaaaybe. Another popular view: Two of the most visible people in this story are: Scott Hanselman (whose last name I cannot type without double-checking the spelling.) and Scott Gu (whose last name is Guenther. Or something like that. I can never remember anything after the first two letters.) I understand why people think maybe these two guys caused this revolution. They both seem to do a decent job I suppose. But the truth is that New Microsoft started when Microsoft hired Martin Woodward . Hva. Who the heck is Martin Woodward Martins current position is Executive Director of the Foundation. Prior to that, he worked as a Program Manager on various developer tools. Nobody knows who Martin is. Either of the Scotts have 2 orders of magnitude more Twitter followers. But I think if you look closely at Martins five year career at Microsoft, you will see a pattern. Every time a piece of Old Microsoft got destroyed in favor of New Microsoft, Martin was nearby. Dont believe me Ask anybody in DevDiv how TFS ended up getting support for Git. Its all about Martin. So all the credit should go to Martin Woodward then You see, Martin joined Microsoft in late 2009 as part of their acquisition of Teamprise. And Teamprise was a division of SourceGear. I hired Martin Woodward (single-handedly, with no help or input from anybody else) in 2005. Four years later, when Microsoft acquired our Teamprise division (which I made happen, all by myself), Martin became a Microsoft employee. Bottom line: Are you excited about all of the fantastic news coming out of Build 2015 this week That stuff would never have happened if it were not for ME. Eric, how can we ever thank you So, now that you know that I am the one behind all the terrific things Microsoft is doing, Im sure you want to express your appreciation. But that wont be necessary. While I understand the sentiment, in lieu of expensive gifts and extravagant favors, I am asking my adoring fans to do two things: First, try not to forget all the little people at Microsoft who are directly involved in the implementation of change. People like Martin, or the Scotts, or Satya. Even though these folks are making a relatively minor contribution compared to my own, I would like them to be supported in their efforts. Be positive. Dont second-guess their motives. Lay aside any prejudices you might have from Old Microsoft. Believe. Second, get involved. Interact with New Microsoft as part of the community. Go to Github and grab the code. Report an issue. Send a pull request. Embellishments and revisionist history aside. Enjoy this Its a GREAT time to be a developer. A couple weeks ago I blogged about mobile sync for MongoDB. Updated Status of Elmo Embeddable Lite Mongo continues to move forward nicely: Progress on indexes: Compound and multikey indexes are supported. Sparse indexes are not done yet. Index key encoding is different from the KeyString stuff that Mongo itself does. For encoding numerics, I did an ugly-but-workable F port of the encoding used by SQLite4. Hint is supported, but is poorly tested so far. Explain is supported, partially, and only for version 3 of the wire protocol. More work to do there. The query planner (which has delusions of grandeur for even referring to itself by that term) isnt very smart. Indexes cannot yet be used for sorting. Indexes are currently never used to cover a query. When grabbing index bounds from the query, elemMatch is ignored. Because of this, and because of the way Mongo multikey indexes work, most index scans are bounded at only one end. The min and max query modifiers are supported. The query planner doesnt know how to deal with or at all. Progress on full-text search: This feature is working for some very basic cases. Phrase search is not implemented yet. Language is currently ignored. The matcher step for text is not implemented yet at all. Everything within the index bounds will get returned. The tokenizer is nothing more than string. split. No stemming. No stop words. Negations are not implemented yet. Weights are stored in the index entries, but textScore is not calculated yet. I also refactored to get better separation between the CRUD logic and the storage of bson blobs and indexes (making it easier to plug-in different storage layers). Questions about client-side APIs So, lets assume you are building a mobile app which communicates with your Mongo server in the cloud using a replicate and sync approach. In other words, your app is not doing its CRUD operations by making networkingREST calls back to the server. Instead, your app is working directly with a partial clone of the Mongo database that is right there on the mobile device. (And periodically, that partial clone is magically synchronized with the main database on the server.) What should the API for that embedded lite mongo look like Obviously, for each development environment, the form of the API should be designed to feel natural or native in that environment. This is the approach taken by Mongos own client drivers. In fact, as far as I can tell, these drivers dont even share much (or any) code. For example, the drivers for C and Java and Ruby are all different, and (unless Im mistaken) none of them are mere wrappers around something lower level like the C driver. Each one is built and maintained to provide the most pleasant experience to developers in a specific ecosystem. My knee-jerk reaction here is to say that mobile developers might want the exact same API as presented by their nearest driver. For example, if I am building a mobile app in C (using the Xamarin tools), there is a good chance my previous Mongo experience is also in C, so I am familiar with the C driver, so thats the API I want. Intuitive as this sounds, it may not be true. Continuing with the C example, that driver is quite large. Is its size appropriate for use on a mobile device Is it even compatible with iOS, which requires AOT compilation (FWIW, I tried compiling this driver as a PCL (Portable Class Library), and it didnt Just Work.) For Android, the same kinds of questions would need to be asked about the Mongo Java driver. And then there are Objective-C and Swift (the primary developer platform for iOS), for which there is no official Mongo driver. But there are a couple of them listed on the Community Supported Drivers page: docs. mongodb. orgecosystemdriverscommunity-supported-drivers . And we need to consider PhonegapCordova as well. Is the Node. js driver a starting point And in all of these cases, if we assume that the mobile API should be the same as the drivers API, how should that be achieved Fork the driver code and rip out all the networking and replace it with calls to the embedded library Or should each mobile platform get a newly-designed API which is specifically for mobile use cases Believe it or not, some days I wonder: Suppose I got Elmo running as a server on an Android device, listening on localhost port 27017. Could an Android app talk to it with the Mongo Java driver unchanged Even if this would work, it would be more like a proof-of-concept than a production solution. Still, when looking for solutions to a problem, the mind goes places. So anyway, Ive got more questions than answers here, and I would welcome thoughts or opinions. Or email me: ericzumero Or Tweet: ericsink Or find me at MongoDB World in NYC at the beginning of June. Talks over the network to the sync server Pushes and pulls incremental changes to keep the mobile database synchronized For this blog entry, I want to talk mostly about the mobile database. In our Zumero for SQL Server solution, this role is played by SQLite. There are certainly differences between SQL Server and SQLite, but on the whole, SQLite does a pretty good job pretending to be SQL Server. What embedded database could play this role for Mongo This question has no clear answer, so weve been building a a lightweight Mongo-compatible database. Right now its just a prototype, but its development serves the purpose of helping us explore mobile sync for Mongo. Embeddable Lite Mongo Or Elmo, for short. Elmo is a database that is designed to be as Mongo-compatible as it can be within the constraints of mobile devices. In terms of the status of our efforts, let me begin with stuff that does NOT work: Sharding is an example of a Mongo feature that Elmo does not support and probably never will. Elmo also has no plans to support any feature which requires embedding a JavaScript engine, since that would violate Apples rules for the App Store. We do hope to support full text search (text, meta, etc), but this is not yet implemented. Similarly, we have not yet implemented any of the geo features, but we consider them to be within the scope of the project. Elmo does not support capped collections, and we are not yet sure if it should. Broadly speaking, except for the above, everything works. Mostly: All documents are stored in BSON Except for JS code, all BSON types are supported Comparison and sorting of BSON values (including different types) works All basic CRUD operations are implemented The update command supports all the update operators except isolated The update command supports upsert as well The findAndModify command includes full support for its various options Basic queries are fully functional, including query operators, projection, and sorting The matcher supports Mongos notion of query predicates matching any element of an array CRUD operations support resolution of paths into array subobjects, like x. y to Regex works, with support for the i, s, and m options The positional operator works in update and projection Cursors and batchSize are supported The aggregation pipeline is supported, including all expression elements and all stages (except geo) Support for indexes is being implemented, but they dont actually speed anything up yet. The dbref format is tolerated, but is not yet resolved. The explain feature is not implemented yet. For the purpose of storing BSON blobs, Elmo is currently using SQLite. Changing this later will be straightforward, as were basically just using SQLite as a key-value store, so the API between all of Elmos CRUD logic and the storage layer is not very wide. Notes on testing: Although mobile-focused Elmo does not need an actual server, it has one, simply so that we can run the jstests suite against it. The only test suite sections we have worked on are jstestscore and jstestsaggregation. Right now, Elmo can pass 311 of the test cases from jstests. We have never tried contacting Elmo with any client driver except the mongo shell. So this probably doesnt work yet. Elmos server only supports the new style protocol, including OPQUERY, OPGETMORE, OPKILLCURSORS, and OPREPLY. None of the old fire and forget messages are implemented. Where necessary to make a test case pass, Elmo tries to return the same error numbers as Mongo itself. All effort thus far has been focused on making Elmo functional, with no effort spent on performance. How Elmo should work: In general, our spec for Elmos behavior is the MongoDB documentation plus the jstests suite. In cases where the Mongo docs seem to differ from the actual behavior of Mongo, we try to make Elmo behave like Mongo does. In cases where the Mongo docs are silent, we often stick a proxy in front of the Mongo server and dump all the messages so we can see exactly what is going on. We occasionally consult the Mongo server source code for reference purposes, but no Mongo code has been copied into Elmo. Notes on the code: Elmo is written in F, which was chosen because its an insanely productive environment and we want to move quickly. But while F is a great language for this exploratory prototype, it may not be the right choice for production, simply because it would confine Elmo use cases to Xamarin, and Miguel s world domination plan is not quite complete yet. :-) The Elmo code is now available on GitHub at githubzumeroElmo. Currently the license is GPLv3, which makes it incompatible with production use on mobile platforms, which is okay for now, since Elmo isnt ready for production use anyway. Well revisit licensing issues later. Our purpose in this blog entry is to start conversations with others who may be interested in mobile sync solutions for Mongo. Feel free to post a question or comment or whatever as an issue on GitHub: githubzumeroElmoissues Or email me: ericzumero Or Tweet: ericsink If youre interested in a face-to-face conversation or a demo, well be at MongoDB World in NYC at the beginning of June. Back in November I wrote a blog entry about performance problems resulting from the design of the layout system in Xamarin. Forms. I am pleased to report that things took a big step forward with the recent release of version 1.3. Reviewing the problem In a nutshell, the Layout classes do too much. They contain functionality to make sure everything gets updated whenever something changes. In principle, this is good, since we obviously dont want stale stuff on the screen. But in practice, there are many cases where the built-in update code ends up being slower than necessary. For example, suppose Im going to add ten child views to a layout. With the built-in update code, a layout cycle will get triggered ten times, once for each child view I add. Worse, if Im trying to do any kind of subview recycling, the odds are high that I want to add a child view while I am processing a layout cycle. This will trigger a recursive layout cycle, resulting in the end of civilization as we know it. Instead, what I want is one layout cycle which happens after all ten child views have been added. The solution I proposed IMHO, the best design for this kind of problem is to have multiple layers: The Low-Level layer models child view relationships only. It provides a way for a View to be inside another View, but it doesnt give much more than that. In iOS terms, this is UIView. addSubView. The High-Level layer (which is built on the functionality provided by the layers below it) has Views which actively manage their child views. In iOS terms, an example of this would be UICollectionView. In the Middle, it would make sense to have a layer which provides things which are common to all (or nearly all) of the stuff in the High-Level layer, to avoid code duplication. Xamarin. Forms has the High-Level layer and the Middle layer, but it does not have the Low-Level layer. So I proposed creating it. I didnt get exactly what I wanted, but. The solution in Xamarin. Forms 1.3 In Xamarin. Forms 1.3, the Middle layer is still the lowest thing weve got. However, there are new capabilities which allow the Middle layer to pretend like it is a Low-Level layer. It still has a bunch of built-in update code, but now that code can be turned off. :-) The important new capabilities are: ShouldInvalidateOnChildAdded ShouldInvalidateOnChildRemoved OnChildMeasureInvalidated By returning false from my override of ShouldInvalidateOnChildAdded() and ShouldInvalidateOnChildRemoved(), I can have a Layout which doesnt do any automatic updates when I add or remove children. And by overriding OnChildMeasureInvalidated(), I can have a Layout which refuses to do real estate negotiations with its child views. How Im using this Because of this new stuff, an upcoming release of our DataGrid component will be even faster. Our panel layout class will look something like this: This Layout class is obviously very simplistic, but it merely scratches the surface of what becomes possible now that Xamarin. Forms has something that can imitate a Low-Level subview layer. Kudos and thanks to the Xamarin. Forms team Ouch. Eric, youre one of those anti-F people, arent you If you skim this blog entry too quickly or just read the title, you might think I am someone who does not like F. Nothing could be further from the truth. Over the last several months, I have become a big F fan. It has become my preferred language for personal projects. My current side project is a key-value store in F. I have learned a lot by writing it, and I am even starting to think it might end up becoming useful. :-) Mostly, I find coding in F to be extremely satisfying. I am writing this article not as an opponent of F, but rather, as someone who hopes that F will become a mainstream language. Eric, youre wrong. F is mainstream already. Of course it is. For some definition of mainstream. F is gaining traction really fast. People are using F for real stuff. The language is improving. Xamarin is supporting it. By nearly any measure, F is showing a lot of momentum over the last few years. If you are an F fan, there just isnt any bad news running around. But for this article, I am using a definition of mainstream, (which Ill explain below) which I believe F has not yet reached. If, when you arrive at the end of this article, you do not like my definition of mainstream, thats okay. Just take a copy of this article, and do a search and replace all instances of the word mainstream with purple. I have no desire to argue with you about what mainstream means, but if you want to argue about the meaning of purple, Ill be happy to. :-) Youre wrong again. My F evangelism IS working Of course it is. To a certain extent. But in marketing terminology, as far as I can tell, most F users today are early adopters. Very few are pragmatists. And F has not yet crossed the chasm. What is the chasm The term originates from a 1991 book by Geoffrey Moore. The main point of Moores book is that the classical marketing bell curve has a problem. Typically (and, prior to Moores book, always), that bell curve is drawn like this: The basic idea of this curve is that when a market adopts a new techology, it follows a pattern. The technology moves from left to right on the bell curve, becoming adopted by four groups in the following order: the early adopters (people who like trying new technologies) the pragmatists (people who only care about technology to get something done) the conservatives (pragmatists, but even more risk-averse) the laggards (people who actively avoid new things) Together, the pragmatists and conservatives are the definition of mainstream for the purpose of this article. Moores key observation is that moving from the early adopters to the pragmatists is very hard. Some technologies never make it. To illustrate this problem, Moore suggests drawing the bell curve differently, with a chasm between the early adopters and the pragmatists: His book explains why the chasm exists, why some technologies die at the bottom of the chasm, and how some technologies successfully cross the chasm. It is a marketing classic and highly recommended. For the purpose of this blog entry, the main thing you need to know is this: The chasm exists because pragmatists generally adopt new techologies as a herd. They dont adopt a new technology until they see other pragmatists using it. This creates a chicken-and-egg problem. How does this herd thing work Pragmatists have an annual conference where they all agree to stay with their existing technologies. The actual vote is not formal, but consensus gets reached. A lot of this process happens in hallways and the dining hall: Are you considering Windows 8 or should we all just stay with Windows 7 and see what happens next Some of the process happens in the conference itself, where youll see session titles like, Why its safe for you to ignore mobile for another year. At PragmatiCon 2014, the ratified platform looked something like this: SQL is still the only safe choice. Keep an eye on your developers to make sure theyre not using Ruby. Exchange is still the best email solution. The cloud is okay for some things, but important data needs to stay in your own server room. Lets ignore BYOD and hope it goes away. Building a mobile app is still too expensive and too risky. So the pragmatists dont care about the ways that F is better This point is where the title of this blog entry comes from. If you are trying to explain the benefits of F to pragmatists, you are probably frustrated. It probably seems like theyre not listening to you. Thats because theyre not. Pragmatists dont make technology decisions on the basis of what is better. They prefer the safety of the herd. A pragmatist wants to be using the same technology as all the other pragmatists, even if everybody is somewhat unhappy with it. They will choose predictably disappointing over excellent and unproven every time. Maybe we just need to do a better job of explaining the benefits of F Wouldnt it be great if it were that simple But no. As an early adopter, there is nothing you can say to a pragmatist that will make a difference. They know that your opinion and experience are not to be trusted, because they do not share your values. So these pragmatists are just stupid then Not at all. Their decision-making process is quite rational. It is a natural consequence of being someone who uses technology to get something done rather than using technology for its own sake. Near the top of this blog entry, I said that I find coding in F to be extremely satisfying. That remark identifies me as an early adopter. It is something a pragmatist would never say. If any pragmatists accidentally stumbled across this blog entry, they stopped reading right there. Pragmatists dont care about the craft of software. They dont care about how cool something is. They care about cars and investments and law and soap and oil rigs and health care and construction and transportation and insurance. Technology is just a tool. BTW, if you find the word pragmatists to be too tedious to pronounce, you can just refer to these folks by their more commonly-used label: normal people. Fine. We dont need those pragmatists anyway, right Maybe not. Some things stay in the land of early adopters forever. But the area under the bell curve matters. It is roughly equivalent to revenue. Together, the pragmatists and conservatives represent almost all of the money in the market. If your situation allows you to be successful with a given technology even though it only gets used by early adopters, great. But many people are (directly or indirectly) placing bets (financial or otherwise) which will only pay off when their technology get used by the majority of the market. So this chicken-and-egg situation is hopeless then Sometimes a pragmatist can be convinced to break with the herd. The key is to find what Moore calls a pragmatist in pain. A pragmatist in pain is someone whose needs are not being well met by whatever technology is current popular among pragmatists. The current technology is not merely annoying them. It is failing them. A pragmatist in pain actually does care about how F is better, even though this goes against their nature. They really hate the idea of listening to some F nerd prattle on about immutability and type inference. But they have reached their last resort. Their pain has forced them to look for hope from somebody outside the herd. This is how a new product gets across the chasm. Find a pragmatist in pain. Do whatever-it-takes to make them happy with your product. Then go back and do it again. Repeat until you have enough customers that they can go to PragmatiCon without being shunned and ridiculed. Why will it be especially hard for F to cross the chasm Because C is really, really good. I love C, but I hold the opinion that F is better. I also understand that Fs awesomeness is basically irrelevant to the question of whether it will go mainstream or not. If the pragmatists are not in pain, they are not interested. C doesnt cause very much pain. Will the hybrid functional-first languages cross the chasm together Certainly it is true that F is part of a trend. The Java world has Scala. The AppleiOS world has Swift. It is not merely true that F is gaining momentum. It is also true that functional programming is gaining momentum. But in terms of going mainstream, these three languages will be related-but-separate. If Swift cross the chasm first (and it will), that will add a bit more momentum to F, simply because the two languages will be seen as comparables in different ecosystems. But F will have to cross the chasm on its own. Why will Swift go mainstream before F Yes, F has a seven year head start, but Swift will cross the chasm first. This has nothing to do with the relative merits of these two languages. As of January 2015, F is quite stable and trustworthy for most use cases, while Swift is mostly an unstable mess that isnt ready for prime time. This too is irrelevant. The simple fact is that C is kinda great and Objective-C is kinda dreadful. Swift will go mainstream first because you cant swing a 9-iron in the AppleiOS ecosystem without hitting a pragmatist in pain. Eric, youre wrong. I know some pragmatists who are using F. Really Great Please spread the word.