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71

TL;DR: A package (Mathematica v10) can be found at the very bottom of this post. UPDATES 6: Tiny update: Import can now use the ".bvh" extension to determine the import type. The code that does this is ugly, but I don't see any other way at the moment. out = Import["C:\\Female1_C03_Run.bvh"] 5: Added error checking and registered the package ...


47

The idea behind this solution is to construct a superposition of Gaussian surfaces whose amplitude decay in time, and use DensityPlot to plot the trail: trail[fun_, {t_, tmin_, tmax_, dt_}, k_, lam_][xxx_, yyy_] := Module[{trange, xrange, yrange, twindow, trailf, sel, decayf}, decayf[x0_, y0_, t0_] := Exp[-k t0 - lam^2 (x0^2 + y0^2)]; twindow = 6/k; ...


40

Here is a simple approach to create a ghost trail: obj[{xfunc_, yfunc_}, rad_, lag_, npts_][x_] := MapThread[ {Opacity[#1, ColorData["SunsetColors", #1]], Disk[{xfunc@#2, yfunc@#2}, rad Exp[#1 - 1]]} &, Through[{Rescale, Identity}[Range[x - lag, x, lag/npts]]]] frames = Most@Table[Graphics[obj[{Sin[2 #] &, Sin[3 #] &}, 0.1, 1, 500][u], ...


37

Let me join. logo = Cases[ p7 /. triangulate /. moretriangles /. shrink /. shrink /. shrink /. colour3[] /. colour4["SunsetColors", 1, 28/34] , {c__, Polygon[pts__]}, \[Infinity]]; logo = SortBy[logo, First]; p = Evaluate[InterpolatingPolynomial[{ {0, {0, 0, 0, 0}}, {Pi, {Pi, 0, 0, 0, 0}}, {2 Pi, {2 Pi, 0, 0, 0}}},#]] &; pp[a_] := If[Abs[a - ...


36

After correcting the syntax errors in the original code, the actual question can be addressed: How to display the four variables x1[t]...y2[t] as an animation in a way that conveys their meaning? The basic idea is to use ListAnimate on a list of frames that I define below: Clear[phi1, phi2, t]; sol = First[ NDSolve[{2*phi1''[t] + phi2''[t]*Cos[phi1[t] - ...


35

Breathing with occluded borders, per Toad's request: Run the following command to get the Mathematica code NotebookPut@ImportString[Uncompress@FromCharacterCode@Flatten@ImageData[ Import@ "http://i.stack.imgur.com/VqjJ9.png","Byte"],"NB"]


35

My simple version using Image: size = 300; r = ListConvolve[DiskMatrix[#], RandomInteger[BernoulliDistribution[0.001], {5 size, size}], {1, 1}] & /@ {1.5, 2, 3}; Dynamic[Image[(r[[#]] = RotateRight[r[[#]], #]) & /@ {1, 2, 3}; Total[r[[All, ;; size]]]]] Update A slightly prettier version, same basic idea but now with flakes. flake := ...


34

A textbook-like animation turns = 10; aa = Table[Framed@ Show[ParametricPlot3D[ Piecewise[{{{1, x, 0}, x <= 0}, {{Cos[2 Pi turns x/r], x, Sin[2 Pi turns x/r]}, 0 < x <= r}, {{1, x, 0}, x > r}}], {x, -.5, r + .5}, PlotStyle -> {Gray, Specularity[Gray, 10]}, Lighting ...


32

As per the blog: Export["breathing.gif", Table[Graphics[ p7 /. triangulate /. moretriangles /. shrink /. shrink /. shrink /. colour3[] /. colour4["SunsetColors", 1, 28/34] /. curve /. bolicsn[(1 - Cos[2 \[Pi] t])/2], ImageSize -> 150], {t, 0, 1, 0.05}]]; Some good old fashioned colour cycling: Clear[f]; f[c_] /; c > 2 := c - 2; f[c_] ...


32

Who wanted the automagic? :) mmastar[as_, nn_: 1] := Graphics[ Scale[#, 1/max@#, {0, 0}] &[ Polygon[pt /@ as] /. triangulate /. moretriangles /. shrink /. shrink /. shrink /. colour3[] /. colour4[] /. curve /. bolicsn[nn]], AspectRatio -> Automatic, PlotRange -> 0.025]; da = 0.0001; max[zu_] := Cases[zu, {_?NumericQ, ...


30

My approach. The main distinguishing feature being the ridiculously clumsy and inefficient way of calculating the faces... v = Tuples[{-1, 1}, 4]; e = Select[Subsets[Range[Length[v]], {2}], Count[Subtract @@ v[[#]], 0] == 3 &]; f = Select[Union[Flatten[#]] & /@ Subsets[e, {4}], Length@# == 4 &]; f = f /. {a_, b_, c_, d_} :> {b, a, c, d}; ...


29

Note that ViewPoint is given in specially scaled coordinates which depend on amongst things the size of the bounding box. To get better control over the positioning of the camera you could use ViewVector instead, which is given in terms of the coordinates of the plot. You could for example do something like this: rotateMeHarder1[g_, vertical_, viewpoint0_, ...


29

Here you have a toy to start playing with: Edit preventing the animation running at different speeds in different machines by using Clock[] and DynamicWrapper[] (due credit to @jVincent) n = 500; (*number of managed particles*) x[i_][t_] := (vx0[i] (t - delay[i])) UnitStep[t - delay[i]]; y[i_][t_] := Module[{k}, If[(k = (-#^2 + vy0@i #) UnitStep@#) < ...


28

The first step is to rasterize the points, so let's just start there as an example: n = 512; g = Image[Map[Boole[# > 0.001] &, RandomReal[{0, 1}, {n, n}], {2}]] The trick is to exploit the distance image. Almost all the work is done here (and it's fast): i = DistanceTransform[g] // ImageAdjust // ImageData; We need a little more precomputation ...


27

Here is an example of how to create an animation from DensitPlot results. I have chosen a simple Gaussian function to plot, but its center depends on a parameter t. Now I create a table of plots for many different values of t, and then I take several different steps to create various kinds of movies from it. The parameter t and its step size is going to be ...


27

Load some images: size = {200, 200}; foot = ImageResize[Import[ "http://upload.wikimedia.org/wikipedia/commons/a/ab/Monty_python_foot.png" ], size]; spikey = ImageResize[Import[ "http://upload.wikimedia.org/wikipedia/en/b/bf/MathematicaSpikeyVersion8.png" ], size]; mse = ImageResize[Import[ "http://i.stack.imgur.com/yjrEY.png" ], size]; ...


26

n = 100; (*number of points*) s = RandomSample@Range@n; (*the initial set*) (*some aux functions*) head[{x_, xs___}] := Select[{xs}, # <= x &]; tail[{x_, xs___}] := Select[{xs}, # > x &]; (*qsort function modified for sowing the information needed*) qsort[{}] = {}; qsort[l : {x_, ___}] := Module[{lh, lt}, (Sow@{l, lh = head@l, x, lt = tail@l}; ...


26

Read comments to your post - many good links there. Additionally, are a few thoughts on the topic. 1) Avoid PPT, - use built-in Mathematica slideshow templates, they were recently updated and are beautiful. Advantage is - you preserve computations and native graphics (like rotations in 3D, etc.). You can read more in this post: Best way to give ...


26

Generally always check Demonstrations site for good code. I cannot not mention an excellent "classic" of planar three body problem by Stephen Wolfram and Michael Trott. Code is short and I verified it runs in the latest M10.1. I slightly changed variable labels so code parses better here, removed MaxRecursion -> ControlActive[3, 9] from plot option and ...


25

The following is a little involved, but it calculates the "minimum displacement" evolution by choosing the least total displacement alternatives from the permutations generated by the "AutomorphismGroup" of the graph: {n, edges, coords1, perms} = GraphData["PappusGraph", {"VertexCount", "EdgeList", ...


23

Try a simple way. Typical key frame animation is done by nothing more than n-degree interpolation (and n is usually 1), and they look quite reasonable. Here is how I would tackle (it is generic version, so individual points have its own colors). Define "start" and "final" positions: startPos = RandomReal[{-2, 2}, {4000, 2}]; normalRDN[μ_, σ_, No_] := ...


23

Embedded cdf with music version. code at the bottom For full period, change max t to 200, my gif is cut in half because for some reasons I couldn't upload whole. f[r_, t_] := Mod[-t (1 - r), 2. Pi]; dr = Pi /100. Animate[Graphics[{ Table[{ AbsolutePointSize[10 # + 2 + 2 Unitize@Clip[f[#, t] - 5.5, {0, 1}]], ...


22

Here's a spinning "3D version" of the logo Using the code from meta/blog to create the logo (assigned to the variable logo), continue with the following steps: side[o_] := Block[{z, pts = Partition[ Table[N[{Cos[t], Sin[t], z}], {t, Pi/14, 2 Pi, 2 Pi/7}], 2, 1, 1]}, Composition[Polygon, Flatten[#, 1] &] /@ Thread[{pts /. z -> o/2, Reverse ...


22

With a bit of blur, but still not the variable-width blur in the example. obj[{xfunc_, yfunc_}, rad_, lag_, npts_][x_] := With[{trail = Range[x - lag, x, lag/npts]}, {ColorData["SunsetColors"]@#1, Opacity@#1, Disk[{xfunc@#2, yfunc@#2}, rad]} & @@@ Transpose[{Rescale[trail], trail}]] frames = Most@ Table[ImageCompose[# ~Blur~ 4, ...


22

Here's my contribution. I know you asked for hints only, but I couldn't resist text = Style["This is some text on a Möbius strip", FontFamily -> "Helvetica", FontSize -> 35]; img = ImageData@Image[Rasterize[text, Background -> None, ImageSize -> 1000]]; Manipulate[ ParametricPlot3D[{4 Cos[a] + r Cos[a] Cos[a/2], 4 Sin[a] + r Sin[a] ...


21

I don't know if you can persuade Import to return the correct durations, but luckily the format of .gif files is pretty straight forward so it's not that hard to extract the correct durations manually from the raw data. In an animated gif the frame durations are stored in a so called Graphic Control Extension or GCE preceding each frame. A GCE starts with ...


21

A very rough interpretation, which I hope might at least give some ideas: (* Final image *) fin = (p7 /. triangulate /. moretriangles /. shrink /. shrink /. shrink /. colour3[] /. colour4["SunsetColors", 1, 28/34]); icycle[ j_, k_] := Table[Graphics[fin[[1 ;; i, j, k]], PlotRange -> 1], {i, 7}] kcycle[i_, j_] := ...


21

I happened to create some snowflakes and snow fall a couple weeks back, and its nice to have some place to share with others! First, we create some algorithmically generated snowflakes with some randomness using a kind of iterated function system based off the 6-pointed "star" shown below. H = Table[{Cos[n*Pi/3], Sin[n*Pi/3]}, {n, 0, 5, 1}]; ...


21

Edit V10! This is simple example what we can now do in real time! R = RegionUnion @@ Table[Disk[{Cos[i], Sin[i]}, .4], {i, 0, 2 Pi, Pi/6.}]; R2 = RegionBoundary@DiscretizeRegion@R; go[] := (While[r > .105, x += v; r = RegionDistance[R2, x]; Pause[.01]]; bounce[];) bounce[] := With[{normal = Normalize[x - RegionNearest[R2, x]]}, If[break, Abort[]]; ...


20

Yes, you can create a table of the plots at appropriate time intervals and then use ListAnimate[] on the table.



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