 trunk/TODO 2011/05/08 21:20:52 1156
+++ trunk/TODO 2011/07/11 19:04:35 1446
@@ 1,110 +1,134 @@
NOTE: GLK's approximate ranking of 5 most important tagged with
+***************************************************
+***************************************************
+THIS TODO HAS BEEN MOVED TO THE DIDEROT WIKI:
+
+http://diderotwiki.cs.uchicago.edu/index.php/Todo
+
+PLEASE USE THAT PAGE TO UPDATE PROBLEMS AND PROGESS
+***************************************************
+***************************************************
+
+NOTE: GLK's approximate ranking of 8 most important tagged with
[GLK:1], [GLK:2], ...
========================
SHORT TERM ============= (*needed* for streamlines & tractography)
========================
[GLK:1] Add sequence types (needed for evals & evecs)
+[GLK:2] Add sequence types (needed for evals & evecs)
syntax
types: ty '{' INT '}'
value construction: '{' e1 ',' … ',' en '}'
indexing: e '{' e '}'
[GLK:1] evals & evecs for symmetric tensor[3,3] (requires sequences)
+
+[GLK:3] evals & evecs for symmetric tensor[2,2] and
+tensor[3,3] (requires sequences)
ability to emit/track/record variables into dynamically resized
runtime buffer
+runtime output buffer
tensor fields: convolution on general tensor images
+[GLK:4] tensor fields from tensor images: Initially need at least
+convolution on tensor[2,2] and tensor[3,3] (the same componentwise
+convolution as for vectors).
========================
SHORTISH TERM ========= (to make using Diderot less annoying/slow)
========================
+SHORTISH TERM ========= (to make using Diderot less annoying to
+======================== program in, and slow to execute)
+
+Allow ".ddro" file extensions in addition to ".diderot"
+
+Be able to output values of type tensor[2,2] and tensor[3,3];
+(currently only scalars & vectors). Want to add some regression tests
+based on this and currently can't
+
+[GLK:1] Proper handling of stabilize method
+
+Convolution on general tensor images (order > 2)
valuenumbering optimization
+allow "*" to represent "modulate": percomponent multiplication of
+vectors, and vectors only (not tensors of order 2 or higher). Once
+sequences are implemented this should be removed: the operation is not
+invariant WRT basis so it is not a legit vector computation.
proper handling of stabilize method
+implicit type promotion of integers to reals where reals are
+required (e.g. not exponentiation "^")
[GLK:2] Save Diderot output to nrrd, instead of "mip.txt"
+[Nick working on this] Save Diderot output to nrrd, instead of "mip.txt"
For grid of strands, save to similarlyshaped array
For list of strands, save to long 1D (or 2D for nonscalar output) list
For ragged things (like tractography output), will need to save both
complete list of values, as well as list of start indices and lengths
to index into complete list
[GLK:3] Use of Teem's "hest" commandline parser for getting
any input variables that are not defined in the source file

[GLK:4] ability to declare a field so that probe positions are
+[GLK:6] ability to declare a field so that probe positions are
*always* "inside"; with various ways of mapping the known image values
to nonexistant index locations. One possible syntax emphasizes that
there is a index mapping function that logically precedes convolution:
 F = bspln3 ⊛ (img clamp)
+ F = bspln3 ⊛ (img ◦ clamp)
F = bspln3 ⊛ (img ◦ repeat)
F = bspln3 ⊛ (img ◦ mirror)
where "◦" or "∘" is used to indicate function composition
Use ∇⊗ etc. syntax
 syntax [DONE]
 typechecking
 IL and codegen

Add a clamp function, which takes three arguments; either three scalars:
 clamp(x, minval, maxval) = max(minval, min(maxval, x))
or three vectors of the same size:
 clamp([x,y], minvec, maxvec) = [max(minvec[0], min(maxvec[0], x)),
 max(minvec[1], min(maxvec[1], y))]
This would be useful in many current Diderot programs.
One question: clamp(x, minval, maxval) is the argument order
used in OpenCL and other places, but clamp(minval, maxval, x)
would be more consistent with lerp(minout, maxout, x).

Level of differentiability in field type should be statement about how
much differentiation the program *needs*, rather than what the kernel
*provides*. The needed differentiability can be less than or equal to
the provided differentiability.
+Use ∇⊗ etc. syntax
+ syntax [DONE]
+ typechecking
+ IL and codegen
+
Add type aliases for color types
rgb = real{3}
rgba = real{4}
+Revisit how images are created within the language.
+The "load" operator should probably go away, and its strangs
+that strings are there only as a way to refer to nrrd filenames
+
==============================
MEDIUM TERM ================== (*needed* for particles)
==============================
runtime birth of strands
+[Lamont working on this] runtime birth of strands
"initially" supports lists
"initially" supports lists of positions output from
different initalization Diderot program

Communication between strands: they have to be able to learn each
other's state (at the previous iteration). Early version of this can
have the network of neighbors be completely static (for running one
strand/pixel image computations). Later version with strands moving
through the domain will require some spatial data structure to
optimize discovery of neighbors.
+"initially" supports lists of positions output from different
+initalization Diderot program (or output from the same program;
+e.g. using output of iso2d.diderot for one isovalue to seed the input
+to another invocation of the same program)
+
+[Lamont working on this] Communication between strands: they have to
+be able to learn each other's state (at the previous iteration).
+Early version of this can have the network of neighbors be completely
+static (for running one strand/pixel image computations). Later
+version with strands moving through the domain will require some
+spatial data structure to optimize discovery of neighbors.
============================
MEDIUMISH TERM ============ (to make Diderot more useful/effective)
============================
+[GLK:5] Want codegeneration working for tensors of order three.
+Order three matters for edge detection in scalar fields (to get
+second derivatives of gradient magnitude), second derivatives
+of vector fields (for some feature extraction), and first
+derivatives of diffusion tensor fields.
+
Python/ctypes interface to runtime
support for Python interop and GUI
Alow X *= Y, X /= Y, X += Y, X = Y to mean what they do in C,
provided that X*Y, X/Y, X+Y, XY are already supported.
Nearly every Diderot program would be simplified by this.
+Allow integer exponentiation ("^2") to apply to square matrices,
+to represent repeated matrix multiplication
Put small 1D and 2D fields, when reconstructed specifically by tent
and when differentiation is not needed, into faster texture buffers.
test/illustvr.diderot is good example of program that uses multiple
such 1D fields basically as lookuptablebased function evaluation
expand trace in mid to low translation

extend norm (exp) to all tensor types [DONE for vectors and matrices]
determinant ("det") for tensor[3,3]
@@ 128,7 +152,6 @@
tensor construction [DONE]
tensor indexing [DONE]
tensor slicing
 verify that hessians work correctly [DONE]
Better handling of variables that determines the scope of a variable
based on its actual use, instead of where the user defined it. So,
@@ 142,58 +165,95 @@
(but we should only duplicate over the liverange of the result of the
conditional.
[GLK:5] Want: nontrivial field expressions & functions:
+[GLK:7] Want: nontrivial field expressions & functions.
+scalar fields from scalar fields F and G:
+ field#0(2)[] X = (sin(F) + 1.0)/2;
+ field#0(2)[] X = F*G;
+scalar field of vector field magnitude:
image(2)[2] Vimg = load(...);
field#0(2)[] Vlen = Vimg ⊛ bspln3;
to get a scalar field of vector length, or
+field of normalized vectors (for LIC and vector field feature extraction)
+ field#2(2)[2] F = ...
+ field#0(2)[2] V = normalize(F);
+scalar field of gradient magnitude (for edge detection))
field#2(2)[] F = Fimg ⊛ bspln3;
field#0(2)[] Gmag = ∇F;
to get a scalar field of gradient magnitude, or
+scalar field of squared gradient magnitude (simpler to differentiate):
field#2(2)[] F = Fimg ⊛ bspln3;
field#0(2)[] Gmsq = ∇F•∇F;
to get a scalar field of squared gradient magnitude, which is simpler
to differentiate. However, there is value in having these, even if
the differentiation of them is not supported (hence the indication
of "field#0" for these above)

Want: ability to apply "normalize" to a field itself, e.g.
 field#0(2)[2] V = normalize(Vimg ⊛ ctmr);
so that V(x) = normalize((Vimg ⊛ ctmr)(x)).
Having this would simplify expression of standard LIC method, and
would also help express other vector field expressions that arise
in vector field feature exraction.
+There is value in having these, even if the differentiation of them is
+not supported (hence the indication of "field#0" for these above)
Permit fields composition, especially for warping images by a
smooth field of deformation vectors
+Introduce region types (syntax region(d), where d is the dimension of the
+region. One useful operator would be
+ dom : field#k(d)[s] > region(d)
+Then the inside test could be written as
+ pos ∈ dom(F)
+We could further extend this approach to allow geometric definitions of
+regions. It might also be useful to do inside tests in world space,
+instead of image space.
+
+co vs contra index distinction
+
+Permit field composition:
field#2(3)[3] warp = bspln3 ⊛ warpData;
field#2(3)[] F = bspln3 ⊛ img;
field#2(3)[] Fwarp = F ◦ warp;
So Fwarp(x) = F(warp(X)). Chain rule can be used for differentation
+So Fwarp(x) = F(warp(X)). Chain rule can be used for differentation.
+This will be instrumental for expressing nonrigid registration
+methods (but those will require covscontra index distinction)
Allow the convolution to be specified either as a single 1D kernel
(as we have it now):
field#2(3)[] F = bspln3 ⊛ img;
or, as a tensor product of kernels, one for each axis, e.g.
field#0(3)[] F = (bspln3 ⊗ bspln3 ⊗ tent) ⊛ img;
This is especially important for things like timevarying data, or
other multidimensional fields where one axis of the domain is very
different from the rest. What is very unclear is how, in such cases,
we should notate the gradient, when we only want to differentiate with
respect to some of the axes.

co vs contra index distinction
+This is especially important for things like timevarying fields
+and the use of scalespace in field visualization: one axis of the
+must be convolved with a different kernel during probing.
+What is very unclear is how, in such cases, we should notate the
+gradient, when we only want to differentiate with respect to some
+subset of the axes. One ambitious idea would be:
+ field#0(3)[] Ft = (bspln3 ⊗ bspln3 ⊗ tent) ⊛ img; // 2D timevarying field
+ field#0(2)[] F = lambda([x,y], Ft([x,y,42.0])) // restriction to time=42.0
+ vec2 grad = ∇F([x,y]); // 2D gradient
some indication of tensor symmetry
+representation of tensor symmetry
(have to identify the group of index permutations that are symmetries)
dot works on all tensors
outer works on all tensors
+Help for debugging Diderot programs: need to be able to uniquely
+identify strands, and for particular strands that are known to behave
+badly, do something like printf or other logging of their computations
+and updates.
+
+Permit writing dimensionally general code: Have some statement of the
+dimension of the world "W" (or have it be learned from one particular
+field of interest), and then able to write "vec" instead of
+"vec2/vec3", and perhaps "tensor[W,W]" instead of
+"tensor[2,2]/tensor[3,3]"
+
+Traits: all things things that have boilerplate code (especially
+volume rendering) should be expressed in terms of the unique
+computational core. Different kinds of streamline/tractography
+computation will be another example, as well as particle systems.
+
Einstein summation notation
"tensor comprehension" (like list comprehension)
+Fields coming from different sources of data:
+* triangular or tetrahedral meshes over 2D or 3D domains (of the
+ source produced by finiteelement codes; these will come with their
+ own specialized kinds of reconstruction kernels, called "basis
+ functions" in this context)
+* Large point clouds, with some radial basis function around each point,
+ which will be tuned by parameters of the point (at least one parameter
+ giving some notion of radius)
+
======================
BUGS =================
======================
@@ 203,3 +263,4 @@
// uncaught exception Size [size]
// raised at ctarget/ctarget.sml:47.1547.19
//field#4(3)[] F = img ⊛ bspln5;
+