data:image/png;base64,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

This block turns on (show) the watcher view on stage (if it was not already activated) of the variable with the given name (slot input). It can only access to the closest variable scope (if there different variables with the same name in different scopes) following the order 'script' -> 'sprite' -> 'global'. No errors if that variable does not exist.

ca:mostra la variable _ es:mostrar variable _ pt:mostra a variável _ de:zeige var _ §_getVarNamesDict

This block sets the given value (last input) to the variable named with the name givent (var input). It looks for that variable following the scope order 'script' -> 'sprite' -> 'global' (the first match it finds). If that variable does not exist (in any scope) an error happens, stopping their script. You can check it before using the "does var (name) exists?" block.

ca:assigna a _ el valor _ es:asignar a _ el valor _ pt:altera _ para _ de:setze var _ auf _ §_getVarNamesDict

Sets the global instrument used for playing notes.

PianoPiano Brass={ French Horn Trumpet Tuba } Strings={ Banjo Bass, Acoustic Bass, Electric (Finger) Cello Guitar, Acoustic Guitar, Electric Harp Koto Sitar Violin } Woodwinds={ Bassoon Clarinet Flute Oboe Saxophone Shakuhachi } Drums={ Cabasa Snare Drum Bass Drum Closed Hi-Hat Open Hi-Hat Mid Tom High Tom Crash Cymbal } Other={ Accordion Marimba Organ Vibraphone }

Sets the global volume to the selected percentage.

Sets the default volume of the selected instrument to the specified percentage.

Plays the selected note for the specified musical duration. This block waits for the selected note to finish playing before moving to the next block. Notes may be entered as Scientific Pitch Notation (eg. C4) or as MIDI numbers. Note durations may be entered as duration names (eg. half, quarter, etc...) or as numerical values (eg. .5, .25, etc...)

C3 D3 E3 F3 G3 A3 B3 C4 D4 E4 F4 G4 A4 B4 Sharps={ C#3 D#3 E#3 F#3 G#3 A#3 B#3 C#4 D#4 E#4 F#4 G#4 A#4 B#4 } Flats={ Cb3 Db3 Eb3 Fb3 Gb3 Ab3 Bb3 Cb4 Db4 Eb4 Fb4 Gb4 Ab4 Bb4 }Whole Half Quarter Eighth Sixteenth Thirtysecond Dotted Notes={ Dotted Half Dotted Quarter Dotted Eighth Dotted Sixteenth } Triplet Notes={ Half Triplet Quarter Triplet Eighth Triplet Sixteenth Triplet }

Plays the selected note for the specified musical duration. Notes may be entered as Scientific Pitch Notation (eg. C4) or as MIDI numbers. Note durations may be entered as duration names (eg. half, quarter, etc...) or as numerical values (eg. .5, .25, etc...)

Plays a list of notes simultaneously for the specified musical duration. Chords must be entered as a list. Durations may be entered as duration names (eg. half, quarter, etc...) or as numerical values (eg. .5, .25, etc...)

Whole Half Quarter Eighth Sixteenth Thirtysecond Dotted Notes={ Dotted Half Dotted Quarter Dotted Eighth Dotted Sixteenth } Triplet Notes={ Half Triplet Quarter Triplet Eighth Triplet Sixteenth Triplet }

Waits for the selected musical duration. Durations may be entered as duration names (eg. half, quarter, etc...) or as numerical values (eg. .5, .25, etc...)

Each note duration is assigned a numerical value, with a whole note equalling "1". Dotted Notes are equal to the named note plus half of the named note's duration. Triplet notes are equal in duration to two of the named notes divided by three. Multiplying the numerical value of a note duration by 4*(60 / tempo) adjusts the note durations to match the current tempo.

QuarterWhole Half Quarter Eighth Sixteenth Thirtysecond Dotted Notes={ Dotted Half Dotted Quarter Dotted Eighth Dotted Sixteenth } Triplet Notes={ Half Triplet Quarter Triplet Eighth Triplet Sixteenth Triplet }

Reports all notes in a specified scale using the provided note and octave number as the starting note of the scale. To add additional scales to the "Types" script variable, create a list with the name of the scale as the first item and the steps between each note of the scale as the second item.

ChromaticChromatic Major MinorC40 1 2 3 4 5 6 7

Reports "#" or "b" of the input scientific pitch notation contains either.

Reports the note in a specific position within a major or minor musical scale. (e.g., The third note in a C Major scale starting in the fourth octave is E4.)

11 2 3 4 5 6 7MajorMajor MinorC40 1 2 3 4 5 6 7

Reports the distance in steps between two notes in the selected scale. (e.g., In the C Major scale, there are two intervals between C4 and E4.) If one or more of the selected notes is not in the selected scale, the block reports nothing. Notes must be entered as scientific pitch notation (eg. C4).

C4G4MajorMajor MinorC

Chromatic Major Minor

Reports the notes comprising a major or minor chord, using the specified note and octave as the root note of the chord.

MajorMajor MinorC4

This block finds the notes in a specified chord along the selected scale. Roman numerals differentiate chord positions from octave numbers (e.g., the Roman numeral “I” reports the notes of the first chord in the sequence). Upper case Roman numerals represent major chords within the scale. Lower case Roman numerals represent minor chords within the scale.

MajorMajor MinorC40 1 2 3 4 5 6 7II ii iii IV V vi vii°Major145367Major236145Major72

Converts roman numerals to arabic numerals using an association table.

Reports the notes of a diminished chord, given the starting note and octave of the chord.

This block reports a chord and appends an additional note.

May be paired with a musical duration to insert a rest into a sequence of chords.

This block reports a series of beats that tell the drum when to play. Beats are represented as an “X,” which can be typed into the block. Beats can be added or subtracted using the arrows on the right of the block.

This block reports a drum pattern, assigns a drum to it, and sets the duration value of each item in the pattern. Different drums can be selected from the drop-down menu. Beat durations can be selected from the drop-down menu or entered directly.

Snare DrumBass Drum Snare Drum Crash Cymbal Cabasa Toms={ High Tom Mid Tom } Hi-Hats={ Closed Hi-hat Open Hi-hat }EighthQuarter Eighth Sixteenth11 2 3 4 8 12 16 24 LoopLoop

This block is used to group sequences of notes and chords into measures. Each note or chord in the measure is paired with a note duration. The pairs are entered into the block using a list.

This code block groups measures together. This can be helpful for separating groups of measures that repeat in various places throughout a song, like verses and choruses. This block works with both notes and chords. To add measures to a section, put the measures into a list.

This code block specifies the type of track to be played and assigns it an instrument. Both the track type and instrument are set using drop-down menus. This block accepts notes or chords paired with corresponding durations. This block also allows for the creation of note or chord loops that will repeat for the whole duration of the song. Both types of loops may be selected from the track drop-down menu. For a loop to play, it must have an accompanying track that is not a loop.

MelodyMelody Chords Loops={ Loop-Melody Loop-Chords }PianoPiano Brass={ French Horn Trumpet Tuba } Strings={ Banjo Bass, Acoustic Bass, Electric (Finger) Cello Guitar, Acoustic Guitar, Electric Guitar, Overdrive Harp Koto Sitar Violin } Woodwinds={ Bassoon Clarinet Flute Oboe Saxophone Shakuhachi } Drums={ Cabasa Snare Drum Bass Drum Closed Hi-Hat Open Hi-Hat Mid Tom High Tom Crash Cymbal } Other={ Accordion Marimba Music Box Organ Vibraphone }

This block is used to play multiple music tracks. In most cases, several tracks with musical instruments are played in parallel.

4/44/4 3/4 5/4 7/4 6/8 9/8 12/8

This block determines if the combined durations of notes or chords within a measure are correct. The combined duration of notes within a measure must equal the number of beats specified by the time signature. When reading time signatures, the bottom number determines which note gets counted as a beat, and the top number determines how many beats are in a measure. For example, in 4/4 time, quarter notes are counted as beats and there are four quarter notes in a measure. In 6/8 time, the eighth note counted as the beat, and there are six eighth notes in a measure. The Beats in Measure reports the discrepancy between the number of actual beats in a measure versus the required number of beats. If name durations are not entered correctly, the block reports nothing.

4/44/4 3/4 2/4 6/8 5/4 7/4 9/8 12/8Actual

of beats

The Note Duration Value block reports the numerical value of the input duration name. Inputing a list of duration names outputs a list of values.

C4C3 D3 E3 F3 G3 A3 B3 C4 D4 E4 F4 G4 A4 B4 Sharps={ C#3 D#3 E#3 F#3 G#3 A#3 B#3 C#4 D#4 E#4 F#4 G#4 A#4 B#4 } Flats={ Cb3 Db3 Eb3 Fb3 Gb3 Ab3 Bb3 Cb4 Db4 Eb4 Fb4 Gb4 Ab4 Bb4 }QuarterWhole Half Quarter Eighth Sixteenth Thirtysecond Dotted Whole Dotted Half Dotted Quarter Dotted Eighth Dotted Sixteenth Dotted Thirtysecond Whole Triplet Half Triplet Quarter Triplet Eighth Triplet Sixteenth Triplet Thirty Second Triplet

This block assigns a number, frequency, and amplitude to a tone.

11 2 3 4 50.5.1 .2 .3 .4 .5 .6 .7 .8 .9

This block turns the specified tone on or off. This block will play a sine wave.

11 2 3 4 5

This block turns off all the tones currently playing.

Passes through the signal from a MIDI controller, allowing the user to play the controller using the assigned instrument. The name of the MIDI controller must be input exactly as it appears on the user's computer.

MPK mini 3MPK mini 3 MPK mini play MPK Mini Mk II M-audio Keystation 49esPianoPiano Brass={ French Horn Trumpet Tuba } Strings={ Banjo Bass, Acoustic Bass, Electric (Finger) Cello Guitar, Acoustic Guitar, Electric Guitar, Overdrive Harp Koto Sitar Violin } Woodwinds={ Bassoon Clarinet Flute Oboe Saxophone Shakuhachi } Drums={ Cabasa Snare Drum Bass Drum Closed Hi-Hat Open Hi-Hat Mid Tom High Tom Crash Cymbal } Other={ Accordion Marimba Music Box Organ Vibraphone }

Reports the corresponding note (in scientific pitch notation) for the specified MIDI number, matching the use of sharps and flats to the input scientific pitch notation.

60§_pianoKeyboardMenuSharpsSharps Flats

Reports the midi number of the specified note. The note should be entered using scientific pitch notation (e.g., "C4").

Extracts the note name from the provided scientific pitch notation. (e.g., An input of "C4" produces an output of "C".)

Association list for note names and their corresponding MIDI numbers in the first octave. Used to convert note names to MIDI.

Extracts the octave number from the provided scientific pitch notation. (e.g., An input of "C4" produces an output of "4".)

de:fange _ _ ca:agafa _ _ es:atrapar _ _ fr:attrape _ _ pt:captura _ _ cont

This is a breakpoint block, to be used in debugging. The Boolean input specifies the condition under which the program should pause. (Use True for an unconditional breakpoint.) The intent is that the script should have SHOW VARIABLE blocks for the process's local variables. After the pause, this block automatically hides all temporary variables.

de:falls _ dann _ und pause $pause-1-255-220-0 ca:si _ fes _ i atura-ho tot $pause-1-255-220-0 es:si _ haz _ y páralo todo $pause-1-255-220-0 fr:si _ faire _ et mettre tout en pause $pause-1-255-220-0 pt:se _ , então _ e faz pausa em tudo $pause-1-255-220-0

Call f(f(f(...(f(x))))) n times where the three input slots are n, f, and x from left to right. The # variable can be used inside f to represent how many times f has been called.

pt:o resultado de _ invocações em cascata de _ com argumento inicial _ _ ca:en cascada _ vegades _ _ _

Call f(f(f(...(f(x))))) until condition is true, where the three input slots are condition, f, and x from left to right. The # variable can be used inside f or condition to indicate how many times f has been called.

pt:o resultado da invocação em cascata até que _ de _ com argumento inicial _ _ ca:en cascada fins _ _ _ _

Returns the function x↦f(g(x)) where f and g are the two inputs.

pt:a composição de _ com _ ca:composa _ _

Like the built-in REPEAT UNTIL block, except that the ending condition is not tested until the script has been run the first time. So the script is run at least once.

pt:repete _ até que _ $loop-0.7 ca:repeteix _ fins _

Run the script repeatedly, as long as the given condition is true. Runs the script at least once before testing the condition.

pt:repete _ enquanto _ $loop-0.7 ca:repeteix _ mentre _

Runs the script repeatedly, as long as the condition is true. Tests the condition before the first time the script is run. Like the built in REPEAT UNTIL except that in this block the condition must be true, not false.

pt:enquanto _ , repete _ $loop-0.7

Runs the script the specified number of times, like the built-in REPEAT block, but this one provides the # variable that can be used inside the script. Try REPEAT (200) MOVE (#) STEPS RIGHT 92 with the pen down.

pt:repete _ vezes _ _ $loop-0.7 ca:repeteix _ _ _

The primitive FOR block uses an implicit step of ±1 depending on which of the starting and ending values is larger. This version allows you to provide an explicit step value. If the sign of the step input is incompatible with the ordering of the starting and ending values, the script will not be run at all.

pt:para _ de _ com passo _ a _ _ $loop-0.7 ca:per _ = _ incrementant _ fins _ _ 1110

Provides LOOP as a function of one input that runs the body of the LET with A set to the function input, so the body can run itself recursively. See COPY block in Variables for an example of use.

pt:tendo _ o valor inicial _ , executa _ definido como _ ca:fes que _ sigui _ al _ _ new value

Reports a new list whose items are the same as in the input list, except that if two or more equal items appear in the input list, only the last one is kept in the result.

ca:elimina els duplicats de _

Reports a sorted version of the list in its first input slot, using the comparison function in the second input slot. For a list of numbers, using < as the comparison function will sort from low to high; using > will sort from high to low.

ca:ordena _ segons criteri _

The second input is an "association list," a list of two-item lists. Each of those smaller lists has a "key" as its first item and a "value" as its second. ASSOC reports the first key-value pair in the association list whose key matches the first input.

ca:associació _ _

This block carries out the given script for each item of the given list, like the primitive FOR EACH. What's different is that it provides the # variable, which will contain the item number in the list of each item in turn, 1 while processing item 1, and so on.

ca:_ per cada _ de _ _

Takes a (possibly deep) list as input, and reports a human-readable text form of the list (namely, Lisp notation). Will not work on circular lists.

ca:notació textual de _ (

)

SENTENCE is the main constructor for sentences, represented as lists of words. It takes zero or more inputs, each of which can be either a list or a text string. If a list, the input is assumed to be a list of words. If a text string, it is converted to a list of words using SENTENCE→LIST. Then all the lists of words are appended to form a new list of words. If the inputs are lists of lists rather than lists of words, SENTENCE, like APPEND, does only one level of flattening, reporting a list of all the items of all the input lists.

ca:frase _

ZIP takes any number of lists as inputs. The lists should all be the same length. ZIP reports a list of lists in which the first item is a list of all the first items, the second item is a list of all the second items, etc. Viewing the inputs as the rows of a matrix, ZIP reports its transpose.

Takes as input a function of N inputs and N lists. The function is called with item 1 of all the lists as its inputs, with item 2 of all the lists as its inputs, and so on. (The lists should all be the same length.)

ca:multi-mapeja _ sobre _

Takes a sentence in text string form and reports the sentence as a list of its words.

de:Satz $arrowRight Liste _ ca:frase $arrowRight llista _ es:frase $arrowRight lista _ fr:phrase $arrowRight liste _ pt:uma lista com as palavras da frase _

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), color number, crayon, or X11/W3C color name. See Appendix A in the Snap! Reference Manual for details.

ca:$brush fixa el _ del llapis a _ _ 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 } }§_ext_clr_numbersNote 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.

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.

ca:$brush _ del llapis 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) hex

HSV 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 name

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.

ca:$brush augmenta _ del llapis en _ 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 hex

I don't know how to handle

pt:lança o erro _

de:fange _ _ ca:agafa _ _ es:atrapar _ _ fr:attrape _ _ pt:captura _ _ cont

de:wirf _ ca:llança _ es:lanzar _ fr:lance _ pt:lança _ catchtag

de:ignoriere _ ca:ignora _ es:ignorar _ fr:ignore _ pt:ignora _

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.

ca:$brush barreja colors _ amb criteri _ additive (light) additive (averaged) subtractive (ideal) subtractive (averaged) simulated paint paint (sRGB corrected)waveforms

sum of weightscombined waveformweighted geometric mean of waveformssum of weightscombined waveform

Tback 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-06new

sRGB

RGB vector255

add

max255

RGB vector

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.

ca:$brush color amb _ _ _ 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 hex§_ext_clr_numberscolor numbercolor300index15scale15

15255fromto12

crayon

132

X11/W3C nameRGB hexcolorRGB vector

HSV vectorHSL vectorfair HSV vectorindex-1scale1index1color

100

fair HSL vectorindex-1scale1index1color

110050

ca:$brush _ del color _ 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 numberrgbhslhsvrgb

transparency

transparencyRGB vectorRGBA vectorRGB hexredgreenbluehsv

false

HSV vectorhuesaturation (HSV)value (brightness)hsl

true

HSL vectorsaturation (HSL)lightness

HSL

lightness

fair 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 something

Can'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).

ca:✐ color de llapis actual

de:fange _ _ ca:agafa _ _ es:atrapar _ _ fr:attrape _ _ pt:captura _ _ cont

de:wirf _ _ ca:llança _ _ es:lanzar _ _ fr:lance _ _ pt:lança _ _ catchtag

Sets 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.

ca:✐ fixa el llapis de color _ _ 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?false

123

Takes 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) ca:fixa el llapis al color r: _ g: _ b: _ 25500

Takes 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) ca:fixa el llapis al color h: _ s: _ v: _ 0.30.70.6

Reports 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.

truetrue

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✐ 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

smallest componentrgb255

smallest component2rgb255

2Red family8.7Brown/orange family17yellow

501427.7522.3

34green52cyan67blue83.33333333purple9550505left of black

falsehue603.61001003.6100100

hue mod 100, other components cut off at [0, 100]

value100color3.6index1index-1scale1

255fromto1

newHSV

HSL✐ fair?true

color300index15scale15grayscale

15255fromto12

1✐ last set ascolor number✐ fair?true✐ raw HSL10050✐ raw HSV100100

015866

161216341656

✐ last set asRGB✐ fair?false1

partial matchestrue

matchhead matchestrue

SUBSET throws here if it handles a unique match1

partial matchesfalse

matchhead matchesfalse

SUBSET throws here if it handles a unique match

015866

161216341656

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?false

✐ last set asRGB✐ fair?false

4value

0255

131✐ last set asRGB✐ fair?false

✐ last set asHSL22

✐ fair?false

✐ last set asHSL✐ HSL1100

0100

✐ raw HSL

✐ fair?false

✐ last set asHSV✐ fair?false✐ raw HSV1310031

100if USED TO BE fairHSL✐ fair?false1

✐ last set asHSL2222✐ fair?true

✐ last set asHSL3333✐ fair?true

22✐ last set asHSV✐ fair?true

33✐ last set asHSV✐ fair?true

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 _

err_reset

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 script

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 _ ? err_reset

takes a snapshot with the webcam and reports it as a new costume, or zero if the user cancels

pt:$camera a imagem actual do vídeo

§_costumesMenu

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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 } elasticend time1000deltaXdeltaY

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

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-outelastic

unknown 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:sprich _ mit _ Aussprache _ und Höhe _ Geschwindigkeit _ pt:fala _ na língua _ _ com tom _ e velocidade _ ca:digues _ amb accent _ _ to _ i velocitat _ Hello, World!en-USالعربية=ar Български=bg বাংলা=bn Català=ca Català - Valencià=ca-VA Česky=cs Deutsch=de Dansk=dk Ελληνικά=el English-American=en-US English-British=en-GB Esperanto=eo Español=es Eesti=et Euskara=eu suomi=fi Français=fr Galego=gl Hrvatski=hr Magyar=hu Interlingua=ia Bahasa Indonesia=id Italiano=it 日本語=ja にほんご=ja-HIRA ಕನ್ನಡ=kn 한국어=ko Malayalam=ml Nederlands=nl Norsk=no Polski=pl Português=pt Português do Brasil=pt-BR Român=ro Русский=ru Slovenščina=si svenska=sv Tamil=ta Telagu=te Türkçe=tr Українська=ua 简体中文=zh-CN 繁體中文=zh-TW11

de:sprich _ mit _ Aussprache _ und Höhe _ Geschwindigkeit _ und warte pt:fala _ na língua _ _ com tom _ e velocidade _ , e espera ca:digues _ amb accent _ _ to _ velocitat _ i espera Hello, World!en-USالعربية=ar Български=bg বাংলা=bn Català=ca Català - Valencià=ca-VA Česky=cs Deutsch=de Dansk=dk Ελληνικά=el English-American=en-US English-British=en-GB Esperanto=eo Español=es Eesti=et Euskara=eu suomi=fi Français=fr Galego=gl Hrvatski=hr Magyar=hu Interlingua=ia Bahasa Indonesia=id Italiano=it 日本語=ja にほんご=ja-HIRA ಕನ್ನಡ=kn 한국어=ko Malayalam=ml Nederlands=nl Norsk=no Polski=pl Português=pt Português do Brasil=pt-BR Român=ro Русский=ru Slovenščina=si svenska=sv Tamil=ta Telagu=te Türkçe=tr Українська=ua 简体中文=zh-CN 繁體中文=zh-TW11

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