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[diderot] Diff of /branches/vis12-cl/TODO
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Diff of /branches/vis12-cl/TODO

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revision 1156, Sun May 8 21:20:52 2011 UTC revision 1167, Tue May 10 13:32:53 2011 UTC
# Line 1  Line 1 
1  NOTE: GLK's approximate ranking of 5 most important tagged with  NOTE: GLK's approximate ranking of 8 most important tagged with
2  [GLK:1], [GLK:2], ...  [GLK:1], [GLK:2], ...
3    
4  ========================  ========================
5  SHORT TERM ============= (*needed* for streamlines & tractography)  SHORT TERM ============= (*needed* for streamlines & tractography)
6  ========================  ========================
7    
8  [GLK:1] Add sequence types (needed for evals & evecs)  [GLK:3] Add sequence types (needed for evals & evecs)
9      syntax      syntax
10          types: ty '{' INT '}'          types: ty '{' INT '}'
11          value construction: '{' e1 ',' … ',' en '}'          value construction: '{' e1 ',' … ',' en '}'
12          indexing: e '{' e '}'          indexing: e '{' e '}'
13  [GLK:1] evals & evecs for symmetric tensor[3,3] (requires sequences)  
14    [GLK:4] evals & evecs for symmetric tensor[2,2] and
15    tensor[3,3] (requires sequences)
16    
17  ability to emit/track/record variables into dynamically re-sized  ability to emit/track/record variables into dynamically re-sized
18  runtime buffer  runtime buffer
# Line 18  Line 20 
20  tensor fields: convolution on general tensor images  tensor fields: convolution on general tensor images
21    
22  ========================  ========================
23  SHORT-ISH TERM ========= (to make using Diderot less annoying/slow)  SHORT-ISH TERM ========= (to make using Diderot less annoying to
24  ========================  ========================  program in, and slow to execute)
25    
26    value-numbering optimization [DONE, but needs more testing]
27    
28    Allow ".ddro" file extensions in addition to ".diderot"
29    
30    Be able to output values of type tensor[2,2] and tensor[3,3]
31    (currently only scalars & vectors)
32    
33    [GLK:1] Add a clamp function, which takes three arguments; either
34    three scalars:
35      clamp(lo, hi, x)  = max(lo, min(hi, x))
36    or three vectors of the same size:
37      clamp(lo, hi, [x,y])  = [max(lo[0], min(hi[0], x)),
38                               max(lo[1], min(hi[1], y))]
39    This would be useful in many current Diderot programs.
40    One question: clamp(x, lo, hi) is the argument order used in OpenCL
41    and other places, but clamp(lo, hi, x) is much more consistent with
42    lerp(lo, hi, x), hence GLK's preference
43    
44    [GLK:2] Proper handling of stabilize method
45    
46  value-numbering optimization  allow "*" to represent "modulate": per-component multiplication of
47    vectors, and vectors only (not tensors of order 2 or higher).  Once
48    sequences are implemented this should be removed: the operation is not
49    invariant WRT basis so it is not a legit vector computation.
50    
51  proper handling of stabilize method  implicit type promotion of integers to reals where reals are
52    required (e.g. not exponentiation "^")
53    
54  [GLK:2] Save Diderot output to nrrd, instead of "mip.txt"  [GLK:5] Save Diderot output to nrrd, instead of "mip.txt"
55    For grid of strands, save to similarly-shaped array    For grid of strands, save to similarly-shaped array
56    For list of strands, save to long 1-D (or 2-D for non-scalar output) list    For list of strands, save to long 1-D (or 2-D for non-scalar output) list
57    For ragged things (like tractography output), will need to save both    For ragged things (like tractography output), will need to save both
58      complete list of values, as well as list of start indices and lengths      complete list of values, as well as list of start indices and lengths
59      to index into complete list      to index into complete list
60    
61  [GLK:3] Use of Teem's "hest" command-line parser for getting  [GLK:6] Use of Teem's "hest" command-line parser for getting
62  any input variables that are not defined in the source file  any input variables that are not defined in the source file
63    
64  [GLK:4] ability to declare a field so that probe positions are  [GLK:7] ability to declare a field so that probe positions are
65  *always* "inside"; with various ways of mapping the known image values  *always* "inside"; with various ways of mapping the known image values
66  to non-existant index locations.  One possible syntax emphasizes that  to non-existant index locations.  One possible syntax emphasizes that
67  there is a index mapping function that logically precedes convolution:  there is a index mapping function that logically precedes convolution:
68    F = bspln3 ⊛ (img  clamp)    F = bspln3 ⊛ (img ◦ clamp)
69    F = bspln3 ⊛ (img ◦ repeat)    F = bspln3 ⊛ (img ◦ repeat)
70    F = bspln3 ⊛ (img ◦ mirror)    F = bspln3 ⊛ (img ◦ mirror)
71  where "◦" or "∘" is used to indicate function composition  where "◦" or "∘" is used to indicate function composition
72    
 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).  
   
73  Level of differentiability in field type should be statement about how  Level of differentiability in field type should be statement about how
74  much differentiation the program *needs*, rather than what the kernel  much differentiation the program *needs*, rather than what the kernel
75  *provides*.  The needed differentiability can be less than or equal to  *provides*.  The needed differentiability can be less than or equal to
76  the provided differentiability.  the provided differentiability.
77    
78    Use ∇⊗ etc. syntax
79        syntax [DONE]
80        typechecking
81        IL and codegen
82    
83  Add type aliases for color types  Add type aliases for color types
84      rgb = real{3}      rgb = real{3}
85      rgba = real{4}      rgba = real{4}
# Line 94  Line 110 
110    
111  support for Python interop and GUI  support for Python interop and GUI
112    
113    Allow integer exponentiation ("^2") to apply to square matrices,
114    to represent repeated matrix multiplication
115    
116  Alow X *= Y, X /= Y, X += Y, X -= Y to mean what they do in C,  Alow X *= Y, X /= Y, X += Y, X -= Y to mean what they do in C,
117  provided that X*Y, X/Y, X+Y, X-Y are already supported.  provided that X*Y, X/Y, X+Y, X-Y are already supported.
118  Nearly every Diderot program would be simplified by this.  Nearly every Diderot program would be simplified by this.
# Line 142  Line 161 
161  (but we should only duplicate over the live-range of the result of the  (but we should only duplicate over the live-range of the result of the
162  conditional.  conditional.
163    
164  [GLK:5] Want: non-trivial field expressions & functions:  [GLK:8] Want: non-trivial field expressions & functions.
165    scalar fields from scalar fields F and G:
166      field#0(2)[] X = (sin(F) + 1.0)/2;
167      field#0(2)[] X = F*G;
168    scalar field of vector field magnitude:
169    image(2)[2] Vimg = load(...);    image(2)[2] Vimg = load(...);
170    field#0(2)[] Vlen = |Vimg ⊛ bspln3|;    field#0(2)[] Vlen = |Vimg ⊛ bspln3|;
171  to get a scalar field of vector length, or  field of normalized vectors (for LIC and vector field feature extraction)
172      field#2(2)[2] F = ...
173      field#0(2)[2] V = normalize(F);
174    scalar field of gradient magnitude (for edge detection))
175    field#2(2)[] F = Fimg ⊛ bspln3;    field#2(2)[] F = Fimg ⊛ bspln3;
176    field#0(2)[] Gmag = |∇F|;    field#0(2)[] Gmag = |∇F|;
177  to get a scalar field of gradient magnitude, or  scalar field of squared gradient magnitude (simpler to differentiate):
178    field#2(2)[] F = Fimg ⊛ bspln3;    field#2(2)[] F = Fimg ⊛ bspln3;
179    field#0(2)[] Gmsq = ∇F•∇F;    field#0(2)[] Gmsq = ∇F•∇F;
180  to get a scalar field of squared gradient magnitude, which is simpler  There is value in having these, even if the differentiation of them is
181  to differentiate.  However, there is value in having these, even if  not supported (hence the indication of "field#0" for these above)
182  the differentiation of them is not supported (hence the indication  
183  of "field#0" for these above)  co- vs contra- index distinction
   
 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.  
184    
185  Permit fields composition, especially for warping images by a  Permit field composition:
 smooth field of deformation vectors  
186    field#2(3)[3] warp = bspln3 ⊛ warpData;    field#2(3)[3] warp = bspln3 ⊛ warpData;
187    field#2(3)[] F = bspln3 ⊛ img;    field#2(3)[] F = bspln3 ⊛ img;
188    field#2(3)[] Fwarp = F ◦ warp;    field#2(3)[] Fwarp = F ◦ warp;
189  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.
190    This will be instrumental for expressing non-rigid registration
191    methods (but those will require co-vs-contra index distinction)
192    
193  Allow the convolution to be specified either as a single 1D kernel  Allow the convolution to be specified either as a single 1D kernel
194  (as we have it now):  (as we have it now):
# Line 177  Line 197 
197    field#0(3)[] F = (bspln3 ⊗ bspln3 ⊗ tent) ⊛ img;    field#0(3)[] F = (bspln3 ⊗ bspln3 ⊗ tent) ⊛ img;
198  This is especially important for things like time-varying data, or  This is especially important for things like time-varying data, or
199  other multi-dimensional fields where one axis of the domain is very  other multi-dimensional fields where one axis of the domain is very
200  different from the rest.  What is very unclear is how, in such cases,  different from the rest, and hence must be treated separately when
201    it comes to convolution.  What is very unclear is how, in such cases,
202  we should notate the gradient, when we only want to differentiate with  we should notate the gradient, when we only want to differentiate with
203  respect to some of the axes.  respect to some subset of the axes.  One ambitious idea would be:
204      field#0(3)[] Ft = (bspln3 ⊗ bspln3 ⊗ tent) ⊛ img; // 2D time-varying field
205  co- vs contra- index distinction    field#0(2)[] F = lambda([x,y], Ft([x,y,42.0]))    // restriction to time=42.0
206      vec2 grad = ∇F([x,y]);                            // 2D gradient
207    
208  some indication of tensor symmetry  representation of tensor symmetry
209  (have to identify the group of index permutations that are symmetries)  (have to identify the group of index permutations that are symmetries)
210    
211  dot works on all tensors  dot works on all tensors

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