NOTE: GLK's approximate ranking of 5 most important tagged with
[GLK:1], [GLK:2], ...
========================
SHORT TERM ============= (*needed* for streamlines & tractography)
========================
[GLK:1] 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)
ability to emit/track/record variables into dynamically re-sized
runtime buffer
tensor fields: convolution on general tensor images
========================
SHORT-ISH TERM ========= (to make using Diderot less annoying/slow)
========================
value-numbering optimization
proper handling of stabilize method
[GLK:2] Save Diderot output to nrrd, instead of "mip.txt"
For grid of strands, save to similarly-shaped array
For list of strands, save to long 1-D (or 2-D for non-scalar 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" command-line 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
*always* "inside"; with various ways of mapping the known image values
to non-existant index locations. One possible syntax emphasizes that
there is a index mapping function that logically precedes convolution:
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.
Add type aliases for color types
rgb = real{3}
rgba = real{4}
==============================
MEDIUM TERM ================== (*needed* for particles)
==============================
run-time 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.
============================
MEDIUM-ISH TERM ============ (to make Diderot more useful/effective)
============================
Python/ctypes interface to run-time
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, X-Y are already supported.
Nearly every Diderot program would be simplified by this.
Put small 1-D and 2-D fields, when reconstructed specifically by tent
and when differentiation is not needed, into faster texture buffers.
test/illust-vr.diderot is good example of program that uses multiple
such 1-D fields basically as lookup-table-based 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]
add ":" for tensor dot product (contracts out two indices
instead of one like •), valid for all pairs of tensors with
at least two indices
test/uninit.diderot:
documents need for better compiler error messages when output variables
are not initialized; the current messages are very cryptic
want: warnings when "D" (reserved for differentiation) is declared as
a variable name (get confusing error messages now)
==============================
LONG TERM ==================== (make Diderot more interesting/attractive from
============================== a research standpoint)
IL support for higher-order tensor values (matrices, etc).
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,
for example, we should lift strand-invariant variables to global
scope. Also prune out useless variables, which should include field
variables after the translation to mid-il.
test/vr-kcomp2.diderot: Add support for code like
(F1 if x else F2)@pos
This will require duplication of the continuation of the conditional
(but we should only duplicate over the live-range of the result of the
conditional.
[GLK:5] Want: non-trivial field expressions & functions:
image(2)[2] Vimg = load(...);
field#0(2)[] Vlen = |Vimg ⊛ bspln3|;
to get a scalar field of vector length, or
field#2(2)[] F = Fimg ⊛ bspln3;
field#0(2)[] Gmag = |∇F|;
to get a scalar field of gradient magnitude, or
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.
Permit fields composition, especially for warping images by a
smooth field of deformation vectors
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
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 time-varying data, or
other multi-dimensional 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
some indication of tensor symmetry
(have to identify the group of index permutations that are symmetries)
dot works on all tensors
outer works on all tensors
Einstein summation notation
"tensor comprehension" (like list comprehension)
======================
BUGS =================
======================
test/zslice2.diderot:
// HEY (bug) bspln5 leads to problems ...
// uncaught exception Size [size]
// raised at c-target/c-target.sml:47.15-47.19
//field#4(3)[] F = img ⊛ bspln5;