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Nov
6
comment How to replicate v9's color conversion to LAB under v10
v9's lightness of 0.71 is far too light to be brown. Here's an independent implementation of RGB to Lab conversion, whose results are close to v10's (although slightly different because it uses a D65 white point).
Nov
5
comment How to make Distance transform invariant to scale
The number of white pixels is not directly proportional to the scale factor, it is proportional to the square of it. Try normalizing by the maximum distance instead.
Nov
4
comment Symbolic Expectation Operator
El_kingo has answered your question, but for future reference, there's a comprehensive Listing of Named Characters in the documentation.
Nov
4
comment Skip certain values in a sum
It's probably equivalent but I find this syntax more elegant: Sum[f[j] Boole[j != 10], {j, 0, J}]
Nov
3
comment How to enlarge the correlation coefficient of two vectors by matrix transform?
Is this question about mathematics or about the Mathematica computer algebra software?
Nov
3
comment How to intelligently use Binarize[] to find the surface concentration of an image?
Some denoising, using e.g. WienerFilter or TotalVariationFilter, will also help avoid the "shading in some black in the spots where there's nothing".
Nov
2
comment Using `N` gives strange result
@Michael, I think it's part of the answer. kguler's comment is the other, more interesting part.
Nov
2
comment Using `N` gives strange result
By the way, it's not the fault of N except insofar as it prevents Evaluate from doing anything (because Evaluate is no longer immediately under the :=). The real reason for the difference is that in g the integral is pre-evaluated while in f it is not.
Nov
2
comment Is there an easy way to use Matteo Niccoli's perceptual color maps for 2D plots in Mathematica?
@DumpsterDoofus, Jason: You could also look at Paul Tol's technote, where he gives several nice colour schemes along with their corresponding formulas. In particular, Fig. 8 shows a diverging colour scheme which is what you're looking for.
Nov
2
comment Is there an easy way to use Matteo Niccoli's perceptual color maps for 2D plots in Mathematica?
@kirma: Not sure what you mean; $l=0.295,c=0.476$ definitely leaves the RGB colour space. i.stack.imgur.com/jhuA8.png
Nov
1
comment Is there an easy way to use Matteo Niccoli's perceptual color maps for 2D plots in Mathematica?
@kirma: I think $l = 0.7206, c = 0.4286$ is the maximum chrominance at which all hues fit in RGB space.
Oct
31
comment How to keep computing Hilbert transforms until I find the right one
This question is far too vague to be answered reasonably. Please be more specific about what kinds of functions you want to consider and what sort of conditions you want them to satisfy.
Oct
31
comment Visualisation of intrinsic curvature
On the other hand, if all you want is a visualization made in Mathematica that interpolates between a torus and a flat surface, look no further.
Oct
31
comment Visualisation of intrinsic curvature
Unfortunately, the torus as drawn in your question does not have zero intrinsic curvature; the curvature is positive on the outside and negative on the inside. The "flat torus" is a mathematical object that has zero intrinsic curvature, but it cannot be embedded into three dimensions without distortion.
Oct
31
comment Exporting animated gifs; “AnimationRepetitions”->1 doesn't work
@Öskå: Deleting the question is worse! Behzad should post the solution as an answer instead.
Oct
31
comment Curve fitting of a list
Why not just analytically evaluate the integral? integral[x_] := Evaluate@Integrate[x^3/(Exp[x] - 1), x]; iop[zt_] := Evaluate[integral[35.5843/zt] - integral[25.967/zt]];
Oct
31
comment Curve fitting of a list
For any particular analytical form, you can use FindFit to find the parameters that best fit it to the data. But if you don't know what the analytical form should be in the first place, I don't think there is any functionality in Mathematica to help you discover it.
Oct
30
comment How can we plot the complex roots of an equation?
The roots of a random 150-degree polynomial with real coefficients would be symmetric about the real axis. I believe what you've plotted there is one root each of 150 random 150-degree polynomials. You could do something like expr = With[{coeffs = RandomInteger[{1, 10}, 150]}, Sum[coeffs[[k]] #^k, {k, 150}] &]; instead to get the correct plot.
Oct
30
revised DumpsterDoofus's captivating generative art
added link to post
Oct
30
comment Using FindFit to return a list of possible best fits
Can you elaborate of what sort of a "set of best fits" you're looking for? Right now it sounds like you're asking for the best fit and a bunch of worse fits, and I don't see why you would want that.