data:image/png;base64,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 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 }colorcolor1001123Takes 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) This 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), or X11/W3C color name. See Appendix A in the Snap! Reference Manual for details.
size color fair hue transparency X11/W3C name (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 RGB hex } }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.sizehueHSLHSV✐ fair?falsesaturation (HSV)value (brightness)transparencyred✐ last set asRGB✐ fair?falsegreen✐ last set asRGB✐ fair?falseblue✐ last set asRGB✐ fair?falsefair huevalue100color3.6index1index-1scale1255fromto1newHSVHSL✐ fair?truefair huecolorColorcolor300index15scale15grayscale15255fromto12✐ last set ascolor✐ fair?falsesaturation (HSL)lightnessfair saturation (HSV)22✐ last set asHSV✐ fair?truefair value (brightness)33✐ last set asHSV✐ fair?truefair saturation (HSL)✐ last set asHSL2222✐ fair?truefair lightness✐ last set asHSL3333✐ fair?truefair HSL vectorfair HSV vectorHSL vectorHSV vectorRGB vectorRGB hex01566red1612green1634blue1656X11/W3C nameX11/W3C namevaluetruex11w3c44partial matches4matchhead matchesSUBSET throws here if it handles a unique match
1
HSVHSV100
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.
size crayon color fair hue transparency X11/W3C name (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 RGB hex } }huesaturation (HSV)value (brightness)transparencyRGB vectorredgreenblueRGB hexHSV vectorHSL vectorsaturation (HSL)lightnesscolorfair huenot setfair saturation (HSL)not setfair lightnessnot setfair HSL vectornot setfair saturation (HSV)2not setfair value (brightness)3not setfair HSV vectornot setcrayonnot setX11/W3C namenot setTakes a value from 0 to 15 and reports the corresponding hexadecimal digit. For internal use of the color library.
Changes 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.
size crayon color fair hue transparency (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 RGB hex } }crayonRGB hexI don't know how to handle
pt:lança o erro _
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 _ 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 _
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 _ Don't ask. Only for internal use by the SET PEN block.
true
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 _ ? Creates 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✐ last set asRGB✐ fair?false✐ raw HSV0100100
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You only need to complete ONE challenge to earn EPIC credit.