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:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAeAAAAFoCAYAAACPNyggAAAAAXNSR0IArs4c6QAADoVJREFUeF7t1cEJAAAIxDDdf2m3sJ+4wEEQuuMIECBAgACBd4F9XzRIgAABAgQIjAB7AgIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECAiwHyBAgAABAoGAAAfoJgkQIECAgAD7AQIECBAgEAgIcIBukgABAgQICLAfIECAAAECgYAAB+gmCRAgQICAAPsBAgQIECAQCAhwgG6SAAECBAgIsB8gQIAAAQKBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECByxcQFpoRMBzwAAAABJRU5ErkJggg==
de:animiere Setter _ Getter _ Delta _ über _ Sek. beschleunigt _ ca:modifica setter _ i getter _ amb delta _ en _ segons de forma _ pt:anima com modificador _ e inspector _ de _ em _ s de forma _ 501
de:Grad _ ca:graus de _ radians pt:_ radianos em graus 0.5
de:Fehler _ pt:assinala o erro _
de:gleite _ in _ Sek. beschleunigt: _ ca:llisca _ en _ segons de forma _ fr:glisser _ en _ sec. accélérer _ pt:desliza _ em _ s de forma _ 501linearlinear quadratic={ quadratic-in quadratic-out quadratic-in-out } cubic={ cubic-in cubic-out cubic-in-out } quart={ quart-in quart-out quart-in-out } sinusoidal={ sine-in sine-out sine-in-out } elastic
de:animiere _ um _ in _ Sek. beschleunigt: _ ca:modifica _ amb _ en _ segons de forma _ pt:anima _ de _ em _ s de forma _ x positionx position y position direction size ghost effect color effect saturation effect brightness effect fisheye effect whirl effect pixelate effect mosaic effect negative effect tempo volume balance501linearlinear quadratic={ quadratic-in quadratic-out quadratic-in-out } cubic={ cubic-in cubic-out cubic-in-out } quart={ quart-in quart-out quart-in-out } sinusoidal={ sine-in sine-out sine-in-out } elasticy positiondirectionsizetempovolumebalance1 12
de:Beschleunigung _ ca:de forma _ pt:a forma _ linearlinear quadratic={ quadratic-in quadratic-out quadratic-in-out } cubic={ cubic-in cubic-out cubic-in-out } quart={ quart-in quart-out quart-in-out } sinusoidal={ sine-in sine-out sine-in-out } elasticquadratic-inquadratic-outquadratic-in-outcubic-incubic-outcubic-in-outquart-inquart-outquart-in-outsine-insine-outsine-in-outelasticunknown easing function ""
de:für _ = _ bis _ _ in _ Sek. beschleunigt: _ _ ca:per _ = _ fins _ _ en _ segons de forma _ _ pt:para _ de _ a _ _ em _ s de forma _ _ 01001linearlinear quadratic={ quadratic-in quadratic-out quadratic-in-out } cubic={ cubic-in cubic-out cubic-in-out } quart={ quart-in quart-out quart-in-out } sinusoidal={ sine-in sine-out sine-in-out } elastic
de:Kostüm aus Text _ Größe _ pt:um traje com o texto _ de tamanho _ A72This block allows you to set the pen's color, transparency (on a scale from 0=opaque to 100=invisible), or size (in pixels). The color can be set in many ways, including RGB values, HSV values, HSL values, fair HSV or HSL (based on a modified spectrum that gives each spectral color equal space and promotes brown to a color), color number, crayon, or X11/W3C color name. See Appendix A in the Snap! Reference Manual for details.
color color number crayon fair hue ~1 size transparency X11/W3C name ~2 (3D color spaces)={ fair HSL={ fair hue fair saturation (HSL) fair lightness fair HSL vector } fair HSV={ fair hue fair saturation (HSV) fair value (brightness) fair HSV vector } HSL={ hue saturation (HSL) lightness HSL vector } HSV={ hue saturation (HSV) value (brightness) HSV vector } RGB (0-255)={ red green blue RGB(A) vector RGB(A) hex } }function () { // add/edit menus but don't forget to edit other slot manual menu options to match var color_number=[ "0 black=0", "14 white=14", "20 spectral red=20", "25 darkest red=25", "30 saddle brown=30", "35 darkest brown=35", "40 spectral orange=40", "45 darkest orange=45", "50 spectral yellow=50", "55 darkest yellow=55", "60 spectral green=60", "65 darkest green=65", "70 spectral cyan=70", "75 darkest cyan=75", "80 spectral blue=80", "85 darkest blue=85", "90 spectral violet=90", "95 magenta=95"]; var fair_hue=[ "0 red=0", "12.5 brown=12.5", "25 orange=25", "37.5 yellow=37.5", "50 green=50", "62.5 cyan=62.5", "75 blue=75", "87.5 violet=87.5"]; var crayon=[ "grays",[ "0 black #000000=0", "1 gray7 #121212=1", "2 gray14 #242424=2", "3 gray21 #363636=3", "4 gray28 #484848=4", "5 gray36 #5c5c5c=5", "6 gray43 #6d6d6d=6", "7 gray50 #7f7f7f=7", "8 gray57 #919191=8", "9 gray64 #a3a3a3=9", "10 gray71 #b5b5b5=10", "11 gray78 #c8c8c8=11", "12 gray85 #dadada=12", "13 gray92 #ececec=13", "14 white #ffffff=14"], "pinks",[ "15 deep pink #ff1493=15", "16 hot pink #ff69b4=16", "17 bright pink #ff007f=17", "18 raspberry #e30b5d=18", "19 amaranth #e52b50=19"], "reds",[ "20 red #ff0000=20", "21 burgundy #900020=21", "22 cherry #990000=22", "23 dark candy apple red #a40000=23", "24 sanguine #c00000=24", "25 maroon #800000=25", "26 crimson #c90016=26", "27 Lists #d94d11=27", "28 candy apple red #ff0800=28", "29 coquelicot #ff3800=29"], "browns",[ "30 saddle brown #8b4513=30", "31 chocolate #7b3f00=31", "32 kobicha #6b4423=32", "33 sepia #704214=33", "34 chestnut #954535=34", "35 dark brown #654321=35", "36 brown #964b00=36", "37 golden brown #996515=37", "38 cinnamon #b87333=38", "39 copper #d2691e=39"], "oranges",[ "40 orange #ff7f00=40", "41 Pantone orange #ff5800=41", "42 pumpkin #ff7518=42", "43 Variables #f3761d=43", "44 Spanish orange #e86100=44", "45 burnt orange #cc5500=45", "46 sinopia #cb410b=46", "47 ochre #cc7722=47", "48 carrot #ed9121=48", "49 tangerine #f28500=49"], "yellows",[ "50 yellow #ffff00=50", "51 Control #e6a822=51", "52 dark goldenrod #b8860b=52", "53 goldenrod #daa520=53", "54 saffron #f4c430=54", "55 sandstorm #ecd540=55", "56 mustard #ffdb58=56", "57 gold #ffd700=57", "58 egg yolk #fee33e=58", "59 rubber duck #fbe108=59"], "greens",[ "60 lime #00ff00=60", "61 apple green #8db600=61", "62 Operators #62c213=62", "63 forest green #228b22=63", "64 green #008000=64", "65 dark green #006400=65", "66 dark pastel green #03c03c=66", "67 emerald #50c878=67", "68 mint #3eb489=68", "69 Pen #00a178=69"], "cyans",[ "70 aqua (cyan) #00ffff=70", "71 dark cyan #008b8b=71", "72 cerulean #007ba7=72", "73 iceberg #71a6d2=73", "74 Sensing #0494dc=74", "75 teal #008080=75", "76 light sky blue #87cefa=76", "77 deep sky blue #00bfff=77", "78 dodger blue #1e90ff=78", "79 azure #007fff=79"], "blues",[ "80 blue #0000ff=80", "81 midnight blue #191970=81", "82 dark powder blue #003399=82", "83 cobalt #0047ab=83", "84 denim #1560bd=84", "85 navy blue #000080=85", "86 steel blue #4682b4=86", "87 Motion #4a6cd4=87", "88 cornflower #6495ed=88", "89 slate blue #6a5acd=89"], "purples",[ "90 violet #8000ff=90", "91 Looks #8f56e3=91", "92 grape #6f2da8=92", "93 indigo #4b0082=93", "94 x11 purple #a020f0=94", "95 magenta (fuchia) #ff00ff=95", "96 dark orchid #9932cc=96", "97 Sound #cf4ad9=97", "98 purple #7f007f=98", "99 dark magenta #8b008b=99"]]; function makeMenuHelper(items, output) { // in an array, walk through the items in pairs var i = 0; while (i < items.length) { var label = items[i]; var possiblyNested = items[i+1]; // if possiblyNested is array, it is a nest under label // if possiblyNested is string, it is just a sibling if (possiblyNested === undefined) { // label is actually the last element of the list var hasEquals = label.split("="); if (hasEquals.length == 2) { output[hasEquals[0]] = hasEquals[1]; i += 1; } else if (hasEquals.length == 3) { output[hasEquals[0]+"\u00A0"+"="+"\u00A0"+hasEquals[2]] = hasEquals[0]+"\u00A0"+"="+"\u00A0"+hasEquals[2]; i += 1; } else { output[label] = label; i += 1; } } else if (typeof possiblyNested == "string") { var hasEquals = label.split("="); if (hasEquals.length == 2) { output[hasEquals[0]] = hasEquals[1]; i += 1; } else if (hasEquals.length == 3) { output[hasEquals[0]+"\u00A0"+"="+"\u00A0"+hasEquals[2]] = hasEquals[0]+"\u00A0"+"="+"\u00A0"+hasEquals[2]; i += 1; } else { output[label] = label; i += 1; } } else if (Array.isArray(possiblyNested)) { var nestingOutput = {}; makeMenuHelper(possiblyNested, nestingOutput); output[label] = nestingOutput; i += 2 } else { throw new Error("Bad value at index " + i); } } } var ide = world.children[0]; var menuVarName = this.parent.blockSpec; try { menuVarName = this.parent.cachedInputs[0].children[0].text; } catch(err) { menuPoss = this.parent.children; menuPoss = menuPoss.filter(function (e) { return (e instanceof InputSlotMorph)}); menuVarName = menuPoss[0].children[0].text; } menuVarName = menuVarName.replace(" ","_"); try { var menu = eval(menuVarName); var output = {}; makeMenuHelper(menu, output); return output; } catch(err) { } }Note to myself: When the user sets a fair dimension, say fair HSL, variable HSL contains the corresponding "unfair" values, and "raw HSL" contains the numbers the user actually gave. It has to be this way because in the case of HSV, there is no "HSV" variable; rather, we use the pen's actual remembered-by-Javascript color's HSV coordinates. So our HSL variable has to be analogous to that. In both cases "raw" means the numbers the user gave us.
1
HSV✐ raw HSL100HSV100
The identity function reports its input.
This block reports the pen size, color, or transparency, in all the same ways that the SET PEN block allows you to set those pen properties. (It will also report the current crayon number, if the pen color was most recently set with SET PEN TO CRAYON.) See Appendix A of the Snap! Reference Manual for details.
color color number crayon fair hue ~1 size transparency X11/W3C name ~2 (3D color spaces)={ fair HSL={ fair hue fair saturation (HSL) fair lightness fair HSL vector } fair HSV={ fair hue fair saturation (HSV) fair value (brightness) fair HSV vector } HSL={ hue saturation (HSL) lightness HSL vector } HSV={ hue saturation (HSV) value (brightness) HSV vector } RGB (0-255)={ red green blue RGB vector RGBA vector RGB(A) hex } }huesaturation (HSV)value (brightness)transparencyRGB vectorRGBA vectorredgreenblueRGB(A) hex1616HSV vectorHSL vectorsaturation (HSL)lightnesscolor numbercolorfair huenot setfair saturation (HSL)not setfair lightnessnot setfair HSL vectornot setfair saturation (HSV)2not setfair value (brightness)3not setfair HSV vectornot setcrayonX11/W3C nameChanges any pen property by the specified amount. Some color scales can't be adjusted this way unless the color was first SET using that scale. Vectors (e.g., RGB color as a list of three numbers) can be incremented by a vector as the amount. X11/W3C names can't be incremented.
color number crayon fair hue ~1 size transparency ~2 (3D color spaces)={ fair HSL={ fair hue fair saturation (HSL) fair lightness fair HSL vector } fair HSV={ fair hue fair saturation (HSV) fair value (brightness) fair HSV vector } HSL={ hue saturation (HSL) lightness HSL vector } HSV={ hue saturation (HSV) value (brightness) HSV vector } RGB (0-255)={ red green blue RGB vector RGBA vector } }crayonRGB hexI don't know how to handle
pt:lança o erro _
de:fange _ _ ca:agafa _ _ es:atrapar _ _ fr:attrape _ _ pt:captura _ _ cont3
de:wirf _ ca:llança _ es:lanzar _ fr:lance _ pt:lança _ catchtag
de:ignoriere _ ca:ignora _ es:ignorar _ fr:ignore _ pt:ignora _
This block creates new variables on the selected scope: global (for all sprites), sprite (for this sprite only) or script (only for that blocks stack) with the names given (in 'names' list). If there is already a variable with that name in that scope, it does nothing: no errors and no overwrites.
pt:cria as variáveis _ _ ca:crea les _ variables _ es:crear las _ variables _ de:erstellen _ var _ globalglobal sprite scripteach itemvar ide = this.parentThatIsA(IDE_Morph); ide.flushBlocksCache('variables'); // b/c of inheritance ide.refreshPalette();This block reports "true" if there is a variable with this given name (input slot) in that context. It can be a global, sprite or script variable. Otherwise it reports "false".
pt:a variável _ existe ca:existeix la variable _ ? es:existe la variable _ ? de:existiert var _ ?
combines any number of colors, reporting the result of mixing them, either additively (like colored light beams) or subtractively (like paints). If the result is too bright (additive) or too dark (subtractive), try the "averaged" versions, which will make the brightness more like the brightnesses of the input colors.
additive (light) additive (averaged) subtractive (ideal) subtractive (averaged) simulated paint paint (sRGB corrected)waveformssum of weightscombined waveformweighted geometric mean of waveformssum of weightscombined waveformTback to RGBT5.47813E-05 0.000184722 0.000935514 0.003096265 0.009507714 0.017351596 0.022073595 0.016353161 0.002002407 -0.016177731 -0.033929391 -0.046158952 -0.06381706 -0.083911194 -0.091832385 -0.08258148 -0.052950086 -0.012727224 0.037413037 0.091701812 0.147964686 0.181542886 0.210684154 0.210058081 0.181312094 0.132064724 0.093723787 0.057159281 0.033469657 0.018235464 0.009298756 0.004023687 0.002068643 0.00109484 0.000454231 0.000255925-4.65552E-05 -0.000157894 -0.000806935 -0.002707449 -0.008477628 -0.016058258 -0.02200529 -0.020027434 -0.011137726 0.003784809 0.022138944 0.038965605 0.063361718 0.095981626 0.126280277 0.148575844 0.149044804 0.14239936 0.122084916 0.09544734 0.067421931 0.035691251 0.01313278 -0.002384996 -0.009409573 -0.009888983 -0.008379513 -0.005606153 -0.003444663 -0.001921041 -0.000995333 -0.000435322 -0.000224537 -0.000118838 -4.93038E-05 -2.77789E-050.00032594 0.001107914 0.005677477 0.01918448 0.060978641 0.121348231 0.184875618 0.208804428 0.197318551 0.147233899 0.091819086 0.046485543 0.022982618 0.00665036 -0.005816014 -0.012450334 -0.015524259 -0.016712927 -0.01570093 -0.013647887 -0.011317812 -0.008077223 -0.005863171 -0.003943485 -0.002490472 -0.001440876 -0.000852895 -0.000458929 -0.000248389 -0.000129773 -6.41985E-05 -2.71982E-05 -1.38913E-05 -7.35203E-06 -3.05024E-06 -1.71858E-06newsRGBRGB vector255addmax255RGB vector
pt:o texto multilinha _ Reports the part of the first string up to the first instance of the second string inside it. If the second string isn't found, reports the entire first string.
pt:o texto de _ antes de _ Reports the portion of the first input string starting after the first occurrence of the second string. If the second string isn't found in the first string, reports an empty string.
pt:o texto de _ depois de _ Reports the character position (starting from 1) of the beginning of the first input string inside the second input string. If it's not found, reports 0.
pt:a posição de _ em _ If input is TRUE, comparisons made by functions in the string library will be case-independent (so "FOO" = "foo"). This is the default. If input is FALSE, comparisons will be exact.
pt:altera comparações ignorando distinção minúsculas/maiúsculas para _ Reports the portion of the first input (string) starting at the position given by the second input (counting from 1, like LETTER n OF) and ending at the position given by the third input (also counting from 1). If the third input is empty, reports the portion from the first position to the end of the string. If a position number is negative, counts from the end backward, so -1 is the last character, -2 is the next to last, etc.
pt:o texto de _ entre as posições _ e _ , inclusive Reports True if the first input string contains the second input string, otherwise false. Comparison is case-independent by default; use USE CASE-INDEPENDENT COMPARISONS to change that.
pt:o texto de _ antes de _ Reports the input text with lower case letters instead of capital letters in the input. Uses the user's locale's rules for case conversion.
pt:em minúsculas _ This block reports a color. The color can be set in many ways, including RGB values, HSV values, HSL values, fair HSV or HSL (based on a modified spectrum that gives each spectral color equal space and promotes brown to a color), color number, crayon, or X11/W3C color name. See Appendix A in the Snap! Reference Manual for details.
color color number crayon fair hue X11/W3C name ~ fair HSL=fair HSL vector fair HSV=fair HSV vector HSL=HSL vector HSV=HSV vector RGB (0-255)=RGB vector RGB hexfunction () { // add/edit menus but don't forget to edit 2nd slot manual menu options as well to match var color_number=[ "0 black=0", "14 white=14", "20 spectral red=20", "25 darkest red=25", "30 saddle brown=30", "35 darkest brown=35", "40 spectral orange=40", "45 darkest orange=45", "50 spectral yellow=50", "55 darkest yellow=55", "60 spectral green=60", "65 darkest green=65", "70 spectral cyan=70", "75 darkest cyan=75", "80 spectral blue=80", "85 darkest blue=85", "90 spectral violet=90", "95 magenta=95"]; var fair_hue=[ "0 red=0", "12.5 brown=12.5", "25 orange=25", "37.5 yellow=37.5", "50 green=50", "62.5 cyan=62.5", "75 blue=75", "87.5 violet=87.5"]; var crayon=[ "grays",[ "0 black #000000=0", "1 gray7 #121212=1", "2 gray14 #242424=2", "3 gray21 #363636=3", "4 gray28 #484848=4", "5 gray36 #5c5c5c=5", "6 gray43 #6d6d6d=6", "7 gray50 #7f7f7f=7", "8 gray57 #919191=8", "9 gray64 #a3a3a3=9", "10 gray71 #b5b5b5=10", "11 gray78 #c8c8c8=11", "12 gray85 #dadada=12", "13 gray92 #ececec=13", "14 white #ffffff=14"], "pinks",[ "15 deep pink #ff1493=15", "16 hot pink #ff69b4=16", "17 bright pink #ff007f=17", "18 raspberry #e30b5d=18", "19 amaranth #e52b50=19"], "reds",[ "20 red #ff0000=20", "21 burgundy #900020=21", "22 cherry #990000=22", "23 dark candy apple red #a40000=23", "24 sanguine #c00000=24", "25 maroon #800000=25", "26 crimson #c90016=26", "27 Lists #d94d11=27", "28 candy apple red #ff0800=28", "29 coquelicot #ff3800=29"], "browns",[ "30 saddle brown #8b4513=30", "31 chocolate #7b3f00=31", "32 kobicha #6b4423=32", "33 sepia #704214=33", "34 chestnut #954535=34", "35 dark brown #654321=35", "36 brown #964b00=36", "37 golden brown #996515=37", "38 cinnamon #b87333=38", "39 copper #d2691e=39"], "oranges",[ "40 orange #ff7f00=40", "41 Pantone orange #ff5800=41", "42 pumpkin #ff7518=42", "43 Variables #f3761d=43", "44 Spanish orange #e86100=44", "45 burnt orange #cc5500=45", "46 sinopia #cb410b=46", "47 ochre #cc7722=47", "48 carrot #ed9121=48", "49 tangerine #f28500=49"], "yellows",[ "50 yellow #ffff00=50", "51 Control #e6a822=51", "52 dark goldenrod #b8860b=52", "53 goldenrod #daa520=53", "54 saffron #f4c430=54", "55 sandstorm #ecd540=55", "56 mustard #ffdb58=56", "57 gold #ffd700=57", "58 egg yolk #fee33e=58", "59 rubber duck #fbe108=59"], "greens",[ "60 lime #00ff00=60", "61 apple green #8db600=61", "62 Operators #62c213=62", "63 forest green #228b22=63", "64 green #008000=64", "65 dark green #006400=65", "66 dark pastel green #03c03c=66", "67 emerald #50c878=67", "68 mint #3eb489=68", "69 Pen #00a178=69"], "cyans",[ "70 aqua (cyan) #00ffff=70", "71 dark cyan #008b8b=71", "72 cerulean #007ba7=72", "73 iceberg #71a6d2=73", "74 Sensing #0494dc=74", "75 teal #008080=75", "76 light sky blue #87cefa=76", "77 deep sky blue #00bfff=77", "78 dodger blue #1e90ff=78", "79 azure #007fff=79"], "blues",[ "80 blue #0000ff=80", "81 midnight blue #191970=81", "82 dark powder blue #003399=82", "83 cobalt #0047ab=83", "84 denim #1560bd=84", "85 navy blue #000080=85", "86 steel blue #4682b4=86", "87 Motion #4a6cd4=87", "88 cornflower #6495ed=88", "89 slate blue #6a5acd=89"], "purples",[ "90 violet #8000ff=90", "91 Looks #8f56e3=91", "92 grape #6f2da8=92", "93 indigo #4b0082=93", "94 x11 purple #a020f0=94", "95 magenta (fuchia) #ff00ff=95", "96 dark orchid #9932cc=96", "97 Sound #cf4ad9=97", "98 purple #7f007f=98", "99 dark magenta #8b008b=99"]]; function makeMenuHelper(items, output) { // in an array, walk through the items in pairs var i = 0; while (i < items.length) { var label = items[i]; var possiblyNested = items[i+1]; // if possiblyNested is array, it is a nest under label // if possiblyNested is string, it is just a sibling if (possiblyNested === undefined) { // label is actually the last element of the list var hasEquals = label.split("="); if (hasEquals.length == 2) { output[hasEquals[0]] = hasEquals[1]; i += 1; } else if (hasEquals.length == 3) { output[hasEquals[0]+"\u00A0"+"="+"\u00A0"+hasEquals[2]] = hasEquals[0]+"\u00A0"+"="+"\u00A0"+hasEquals[2]; i += 1; } else { output[label] = label; i += 1; } } else if (typeof possiblyNested == "string") { var hasEquals = label.split("="); if (hasEquals.length == 2) { output[hasEquals[0]] = hasEquals[1]; i += 1; } else if (hasEquals.length == 3) { output[hasEquals[0]+"\u00A0"+"="+"\u00A0"+hasEquals[2]] = hasEquals[0]+"\u00A0"+"="+"\u00A0"+hasEquals[2]; i += 1; } else { output[label] = label; i += 1; } } else if (Array.isArray(possiblyNested)) { var nestingOutput = {}; makeMenuHelper(possiblyNested, nestingOutput); output[label] = nestingOutput; i += 2 } else { throw new Error("Bad value at index " + i); } } } var ide = world.children[0]; var menuVarName = this.parent.blockSpec; try { menuVarName = this.parent.cachedInputs[0].children[0].text; } catch(err) { menuPoss = this.parent.children; menuPoss = menuPoss.filter(function (e) { return (e instanceof InputSlotMorph)}); menuVarName = menuPoss[0].children[0].text; } menuVarName = menuVarName.replace(" ","_"); try { var menu = eval(menuVarName); var output = {}; makeMenuHelper(menu, output); return output; } catch(err) { } }color numbercolor300index15scale1515255fromto122crayon132X11/W3C nameRGB hexcolorRGB vectorHSV vectorHSL vectorfair HSV vectorindex-1scale1index1color100fair HSL vectorindex-1scale1index1color110050
nearest color number crayon number fair hue ~1 transparency X11/W3C name ~2 (3D color spaces)={ fair HSL={ fair hue fair saturation (HSL) fair lightness fair HSL vector } fair HSV={ fair hue fair saturation (HSV) fair value (brightness) fair HSV vector } HSL={ hue saturation (HSL) lightness HSL vector } HSV={ hue saturation (HSV) value (brightness) HSV vector } RGB (0-255)={ red green blue RGB vector RGBA vector RGB hex } }X11/W3C namenearest color numberrgbhslhsvrgbtransparencytransparencyRGB vectorRGBA vectorRGB hexredgreenbluehsvfalseHSV vectorhuesaturation (HSV)value (brightness)hsltrueHSL vectorsaturation (HSL)lightnessHSLlightnessfair lightness310030.9833.333333330.986.9444444516.944444451.96100fair lightnessfair saturation (HSL)210075.9493610075.949366.9444444516.944444451.96100fair saturation (HSL)fair HSL vectorfair lightness310030.9833.333333330.986.9444444516.944444458.823529100fair lightnessfair saturation (HSL)210075.9493610075.949366.9444444516.944444458.823529100fair saturation (HSL)fair HSL vectorfair hue11111111fair huefair saturation (HSL)fair lightnessfair HSL vectorbrownfair value (brightness)310054.5166.66666666754.516.9444444516.944444451.96100fair value (brightness)fair saturation (HSV)210086.3310086.336.9444444516.944444451.96100fair saturation (HSV)fair HSV vectorfair value (brightness)310054.5166.66666666754.516.9444444516.944444451.96100fair value (brightness)fair saturation (HSV)210086.3310086.336.9444444516.944444451.96100fair saturation (HSV)fair HSV vectorfair hue11111111fair huefair saturation (HSV)fair value (brightness)fair HSV vectorbrownfair somethingCan't get here -- please post project and screenshot to forum.This block reports the pen color (as a color, not as a list of numbers).
de:fange _ _ ca:agafa _ _ es:atrapar _ _ fr:attrape _ _ pt:captura _ _ cont
de:wirf _ _ ca:llança _ _ es:lanzar _ _ fr:lance _ _ pt:lança _ _ catchtagSets the pen color to one of 100 preselected colors, like a box of 100 crayons. The colors have names that are meant to be evocative. They are organized in families, more or less corresponding to spectral (rainbow) colors; the input slot has a two-level menu in which you can hover over a family name to see the colors of that family, each including a crayon number and an RGB value. See Appendix A of the Snap! Reference Manual for more details.
grays={ 0 black #000000=0 1 gray7 #121212=1 2 gray14 #242424=2 3 gray21 #363636=3 4 gray28 #484848=4 5 gray36 #5c5c5c=5 6 gray43 #6d6d6d=6 7 gray50 #7f7f7f=7 8 gray57 #919191=8 9 gray64 #a3a3a3=9 10 gray71 #b5b5b5=10 11 gray78 #c8c8c8=11 12 gray85 #dadada=12 13 gray92 #ececec=13 14 white #ffffff=14 } pinks={ 15 deep pink #ff1493=15 16 hot pink #ff69b4=16 17 bright pink #ff007f=17 18 raspberry #e30b5d=18 19 amaranth #e52b50=19 } reds={ 20 red #ff0000=20 21 burgundy #900020=21 22 cherry #990000=22 23 dark candy apple red #a40000=23 24 sanguine #c00000=24 25 maroon #800000=25 26 crimson #c90016=26 27 Lists #d94d11=27 28 candy apple red #ff0800=28 29 coquelicot #ff3800=29 } browns={ 30 saddle brown #8b4513=30 31 chocolate #7b3f00=31 32 kobicha #6b4423=32 33 sepia #704214=33 34 chestnut #954535=34 35 dark brown #654321=35 36 brown #964b00=36 37 golden brown #996515=37 38 cinnamon #b87333=38 39 copper #d2691e=39 } oranges={ 40 orange #ff7f00=40 41 Pantone orange #ff5800=41 42 pumpkin #ff7518=42 43 Variables #f3761d=43 44 Spanish orange #e86100=44 45 burnt orange #cc5500=45 46 sinopia #cb410b=46 47 ochre #cc7722=47 48 carrot #ed9121=48 49 tangerine #f28500=49 } yellows={ 50 yellow #ffff00=50 51 Control #e6a822=51 52 dark goldenrod #b8860b=52 53 goldenrod #daa520=53 54 saffron #f4c430=54 55 sandstorm #ecd540=55 56 mustard #ffdb58=56 57 gold #ffd700=57 58 egg yolk #fee33e=58 59 rubber duck #fbe108=59 } greens={ 60 lime #00ff00=60 61 apple green #8db600=61 62 Operators #62c213=62 63 forest green #228b22=63 64 green #008000=64 65 dark green #006400=65 66 dark pastel green #03c03c=66 67 emerald #50c878=67 68 mint #3eb489=68 69 Pen #00a178=69 } cyans={ 70 aqua (cyan) #00ffff=70 71 dark cyan #008b8b=71 72 cerulean #007ba7=72 73 iceberg #71a6d2=73 74 Sensing #0494dc=74 75 teal #008080=75 76 light sky blue #87cefa=76 77 deep sky blue #00bfff=77 78 dodger blue #1e90ff=78 79 azure #007fff=79 } blues={ 80 blue #0000ff=80 81 midnight blue #191970=81 82 dark powder blue #003399=82 83 cobalt #0047ab=83 84 denim #1560bd=84 85 navy blue #000080=85 86 steel blue #4682b4=86 87 Motion #4a6cd4=87 88 cornflower #6495ed=88 89 slate blue #6a5acd=89 } purples={ 90 violet #8000ff=90 91 Looks #8f56e3=91 92 grape #6f2da8=92 93 indigo #4b0082=93 94 x11 purple #a020f0=94 95 magenta (fuchia) #ff00ff=95 96 dark orchid #9932cc=96 97 Sound #cf4ad9=97 98 purple #7f007f=98 99 dark magenta #8b008b=99 }✐ last set ascrayon✐ fair?false1231Takes three inputs for red, green, and blue values, each between 0 and 255. 0,0,0 is black; 255,255,255 is white. 255,255,0 is yellow, and so on. The SET PEN block in this library lets you set individual red, green, or blue without changing the others, lets you provide a list of three RGB color components, and lets you provide a six-digit hexadecimal number, the form in which RGB color values are usually found online. See Appendix A of the Snap! Reference Manual for details.
pt:altera a cor da tua caneta para vermelho _ , verde _ e azul _ (0 a 255) 25500Takes three inputs for hue, saturation, and value ("brightness") values, each between 0 and 1. 0,0,0 is black; 0,0,1 is white. 0.15,1,1 is yellow, and so on. The SET PEN block in this library lets you set individual hue, saturation, or value without changing the others, lets you provide a list of three HSV color components, and lets you use the very much superior HSL (hue, saturation, lightness) color space. See Appendix A of the Snap! Reference Manual for details.
pt:altera a cor da caneta para matiz _ , saturação _ e brilho _ (0 a 1) 0.30.70.6Reports the current pen color as a list of three RGB values in the range 0-255. The PEN block in this library provides a large set of ways to examine the color. See Appendix A in the Snap! Reference Manual for details.
pt:a cor da caneta em RGB (vermelho, verde e azul; 0 a 255) Reports the current pen color as a list of three HSV values in the range 0-1. See Appendix A in the Snap! Reference Manual for details.
pt:a cor da caneta em HSV (matiz, saturação e brilho, 0 a 1) Takes a value from 0 to 15 and reports the corresponding hexadecimal digit. For internal use of the color library.
Don't ask. Only for internal use by the SET PEN block.
truetrueCreates a bunch of global variables. For internal use by Color library.
global✐ last set as✐ fair?✐ color scale✐ HSL✐ last crayon✐ last X11✐ raw HSL✐ raw HSV✐ X11✐ crayon colors✐ fair hue table✐ colors✐ brights✐ pivots✐ HSV brights✐ HSL brights✐ HSV colors✐ HSL colors✐ X11 catch✐ dimension names✐ dimension dispatch✐ last set asRGB✐ fair?false✐ raw HSV0100100✐ HSL010050✐ raw HSL010050
not a crayon
not an X11 color
11000hues1fair hues00hue101100021000✐ fair hue table10
11
1
smallest componentrgb255
smallest component2rgb255
2Red family8.7Brown/orange family17yellow501427.7522.334green52cyan67blue83.33333333purple9550505left of black
falsehue603.61001003.6100100
hue mod 100, other components cut off at [0, 100]
value100color3.6index1index-1scale1255fromto1newHSVHSL✐ fair?true
color300index15scale15grayscale15255fromto121✐ last set ascolor number✐ fair?true✐ raw HSL10050✐ raw HSV100100
015866161216341656✐ last set asRGB✐ fair?false1
44partial matchestrue4matchhead matchestrueSUBSET throws here if it handles a unique match1
44partial matchesfalse4matchhead matchesfalseSUBSET throws here if it handles a unique match2
015866161216341656
fair hue transparency ~2 (3D color spaces)={ fair HSL={ fair hue fair saturation (HSL) fair lightness } fair HSV={ fair hue fair saturation (HSV) fair value (brightness) } HSL={ hue saturation (HSL) lightness } HSV={ hue saturation (HSV) value (brightness) } RGB (0-255)={ red green blue } }255100We have to do this last test to rule out the vector options, which aren't numbers; their code makes three recursive calls and we catch range issues then.huesaturation (HSV)value (brightness)saturation (HSL)lightnesstransparencyredgreenbluefair huefair saturation (HSV)fair value (brightness)fair saturation (HSL)fair lightness
✐ last set asHSL33✐ fair?false1
✐ last set asRGB✐ fair?false
✐ last set asRGB✐ fair?false
✐ last set asRGB✐ fair?false
✐ last set asRGB✐ fair?false
0
4value0255131✐ last set asRGB✐ fair?false
✐ last set asHSL22✐ fair?false1
✐ last set asHSL✐ HSL11000100✐ raw HSL✐ fair?false1
✐ last set asHSV✐ fair?false✐ raw HSV1310031
100if USED TO BE fairHSL✐ fair?false1
✐ last set asHSL2222✐ fair?true1
✐ last set asHSL3333✐ fair?true1
2313
22✐ last set asHSV✐ fair?true1
33✐ last set asHSV✐ fair?true1
23131
pt:os dados JSON _ em formato de lista
pt:o valor com chave _ em _
pt:a resposta a _ de _ enviando _ e cabeçalhos _ GETGET POST PUT DELETEhttps://snap.berkeley.edu
pt:um par (chave: _ , valor: _ ) Reports a three-item list containing the latitude and longitude of the user, and the precision of the measurements. Works only if the user allows snap.berkeley.edu access to location data. Some browsers also require an HTTPS connection to Snap!.
pt:a localização actual do dispositivo
weekday17,
0100January,February,March,April,May,June,July,August,September,October,November,DecemberSunday,Monday,Tuesday,Wednesday,Thursday,Friday,Saturday