5 
SHORT TERM ============= (*needed* for streamlines & tractography) 
SHORT TERM ============= (*needed* for streamlines & tractography) 
6 
======================== 
======================== 
7 


8 
[GLK:3] Add sequence types (needed for evals & evecs) 
[GLK:2] 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 


14 
[GLK:4] evals & evecs for symmetric tensor[2,2] and 
[GLK:3] evals & evecs for symmetric tensor[2,2] and 
15 
tensor[3,3] (requires sequences) 
tensor[3,3] (requires sequences) 
16 


17 
ability to emit/track/record variables into dynamically resized 
ability to emit/track/record variables into dynamically resized 
18 
runtime buffer 
runtime output buffer 
19 


20 
tensor fields: convolution on general tensor images 
[GLK:4] tensor fields from tensor images: Initially need at least 
21 

convolution on tensor[2,2] and tensor[3,3] (the same componentwise 
22 

convolution as for vectors). 
23 


24 
======================== 
======================== 
25 
SHORTISH TERM ========= (to make using Diderot less annoying to 
SHORTISH TERM ========= (to make using Diderot less annoying to 
26 
======================== program in, and slow to execute) 
======================== program in, and slow to execute) 
27 


28 
valuenumbering optimization 
Allow ".ddro" file extensions in addition to ".diderot" 
29 


30 
[GLK:1] Add a clamp function, which takes three arguments; either 
Be able to output values of type tensor[2,2] and tensor[3,3]; 
31 
three scalars: 
(currently only scalars & vectors). Want to add some regression tests 
32 
clamp(lo, hi, x) = max(lo, min(hi, x)) 
based on this and currently can't 

or three vectors of the same size: 


clamp(lo, hi, [x,y]) = [max(lo[0], min(hi[0], x)), 


max(lo[1], min(hi[1], y))] 


This would be useful in many current Diderot programs. 


One question: clamp(x, lo, hi) is the argument order used in OpenCL 


and other places, but clamp(lo, hi, x) is much more consistent with 


lerp(lo, hi, x), hence GLK's preference 

33 


34 
[GLK:2] Proper handling of stabilize method 
[GLK:1] Proper handling of stabilize method 
35 


36 

Convolution on general tensor images (order > 2) 
37 


38 
allow "*" to represent "modulate": percomponent multiplication of 
allow "*" to represent "modulate": percomponent multiplication of 
39 
vectors, and vectors only (not tensors of order 2 or higher). Once 
vectors, and vectors only (not tensors of order 2 or higher). Once 
43 
implicit type promotion of integers to reals where reals are 
implicit type promotion of integers to reals where reals are 
44 
required (e.g. not exponentiation "^") 
required (e.g. not exponentiation "^") 
45 


46 
[GLK:5] Save Diderot output to nrrd, instead of "mip.txt" 
[Nick working on this] Save Diderot output to nrrd, instead of "mip.txt" 
47 
For grid of strands, save to similarlyshaped array 
For grid of strands, save to similarlyshaped array 
48 
For list of strands, save to long 1D (or 2D for nonscalar output) list 
For list of strands, save to long 1D (or 2D for nonscalar output) list 
49 
For ragged things (like tractography output), will need to save both 
For ragged things (like tractography output), will need to save both 
50 
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 
51 
to index into complete list 
to index into complete list 
52 


53 
[GLK:6] Use of Teem's "hest" commandline parser for getting 
[GLK:6] ability to declare a field so that probe positions are 

any input variables that are not defined in the source file 





[GLK:7] ability to declare a field so that probe positions are 

54 
*always* "inside"; with various ways of mapping the known image values 
*always* "inside"; with various ways of mapping the known image values 
55 
to nonexistant index locations. One possible syntax emphasizes that 
to nonexistant index locations. One possible syntax emphasizes that 
56 
there is a index mapping function that logically precedes convolution: 
there is a index mapping function that logically precedes convolution: 
73 
rgb = real{3} 
rgb = real{3} 
74 
rgba = real{4} 
rgba = real{4} 
75 


76 

Revisit how images are created within the language. 
77 

The "load" operator should probably go away, and its strangs 
78 

that strings are there only as a way to refer to nrrd filenames 
79 


80 
============================== 
============================== 
81 
MEDIUM TERM ================== (*needed* for particles) 
MEDIUM TERM ================== (*needed* for particles) 
82 
============================== 
============================== 
83 


84 
runtime birth of strands 
[Lamont working on this] runtime birth of strands 
85 


86 
"initially" supports lists 
"initially" supports lists 
87 


88 
"initially" supports lists of positions output from 
"initially" supports lists of positions output from different 
89 
different initalization Diderot program 
initalization Diderot program (or output from the same program; 
90 

e.g. using output of iso2d.diderot for one isovalue to seed the input 
91 
Communication between strands: they have to be able to learn each 
to another invocation of the same program) 
92 
other's state (at the previous iteration). Early version of this can 

93 
have the network of neighbors be completely static (for running one 
[Lamont working on this] Communication between strands: they have to 
94 
strand/pixel image computations). Later version with strands moving 
be able to learn each other's state (at the previous iteration). 
95 
through the domain will require some spatial data structure to 
Early version of this can have the network of neighbors be completely 
96 
optimize discovery of neighbors. 
static (for running one strand/pixel image computations). Later 
97 

version with strands moving through the domain will require some 
98 

spatial data structure to optimize discovery of neighbors. 
99 


100 
============================ 
============================ 
101 
MEDIUMISH TERM ============ (to make Diderot more useful/effective) 
MEDIUMISH TERM ============ (to make Diderot more useful/effective) 
102 
============================ 
============================ 
103 


104 

[GLK:5] Want codegeneration working for tensors of order three. 
105 

Order three matters for edge detection in scalar fields (to get 
106 

second derivatives of gradient magnitude), second derivatives 
107 

of vector fields (for some feature extraction), and first 
108 

derivatives of diffusion tensor fields. 
109 


110 
Python/ctypes interface to runtime 
Python/ctypes interface to runtime 
111 


112 
support for Python interop and GUI 
support for Python interop and GUI 
114 
Allow integer exponentiation ("^2") to apply to square matrices, 
Allow integer exponentiation ("^2") to apply to square matrices, 
115 
to represent repeated matrix multiplication 
to represent repeated matrix multiplication 
116 



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. 




117 
Put small 1D and 2D fields, when reconstructed specifically by tent 
Put small 1D and 2D fields, when reconstructed specifically by tent 
118 
and when differentiation is not needed, into faster texture buffers. 
and when differentiation is not needed, into faster texture buffers. 
119 
test/illustvr.diderot is good example of program that uses multiple 
test/illustvr.diderot is good example of program that uses multiple 
120 
such 1D fields basically as lookuptablebased function evaluation 
such 1D fields basically as lookuptablebased function evaluation 
121 



expand trace in mid to low translation 




122 
extend norm (exp) to all tensor types [DONE for vectors and matrices] 
extend norm (exp) to all tensor types [DONE for vectors and matrices] 
123 


124 
determinant ("det") for tensor[3,3] 
determinant ("det") for tensor[3,3] 
142 
tensor construction [DONE] 
tensor construction [DONE] 
143 
tensor indexing [DONE] 
tensor indexing [DONE] 
144 
tensor slicing 
tensor slicing 

verify that hessians work correctly [DONE] 

145 


146 
Better handling of variables that determines the scope of a variable 
Better handling of variables that determines the scope of a variable 
147 
based on its actual use, instead of where the user defined it. So, 
based on its actual use, instead of where the user defined it. So, 
155 
(but we should only duplicate over the liverange of the result of the 
(but we should only duplicate over the liverange of the result of the 
156 
conditional. 
conditional. 
157 


158 
[GLK:8] Want: nontrivial field expressions & functions. 
[GLK:7] Want: nontrivial field expressions & functions. 
159 
scalar fields from scalar fields F and G: 
scalar fields from scalar fields F and G: 
160 
field#0(2)[] X = (sin(F) + 1.0)/2; 
field#0(2)[] X = (sin(F) + 1.0)/2; 
161 
field#0(2)[] X = F*G; 
field#0(2)[] X = F*G; 
174 
There is value in having these, even if the differentiation of them is 
There is value in having these, even if the differentiation of them is 
175 
not supported (hence the indication of "field#0" for these above) 
not supported (hence the indication of "field#0" for these above) 
176 


177 

Introduce region types (syntax region(d), where d is the dimension of the 
178 

region. One useful operator would be 
179 

dom : field#k(d)[s] > region(d) 
180 

Then the inside test could be written as 
181 

pos ∈ dom(F) 
182 

We could further extend this approach to allow geometric definitions of 
183 

regions. It might also be useful to do inside tests in world space, 
184 

instead of image space. 
185 


186 
co vs contra index distinction 
co vs contra index distinction 
187 


188 
Permit field composition: 
Permit field composition: 
198 
field#2(3)[] F = bspln3 ⊛ img; 
field#2(3)[] F = bspln3 ⊛ img; 
199 
or, as a tensor product of kernels, one for each axis, e.g. 
or, as a tensor product of kernels, one for each axis, e.g. 
200 
field#0(3)[] F = (bspln3 ⊗ bspln3 ⊗ tent) ⊛ img; 
field#0(3)[] F = (bspln3 ⊗ bspln3 ⊗ tent) ⊛ img; 
201 
This is especially important for things like timevarying data, or 
This is especially important for things like timevarying fields 
202 
other multidimensional fields where one axis of the domain is very 
and the use of scalespace in field visualization: one axis of the 
203 
different from the rest, and hence must be treated separately when 
must be convolved with a different kernel during probing. 
204 
it comes to convolution. What is very unclear is how, in such cases, 
What is very unclear is how, in such cases, we should notate the 
205 
we should notate the gradient, when we only want to differentiate with 
gradient, when we only want to differentiate with respect to some 
206 
respect to some subset of the axes. One ambitious idea would be: 
subset of the axes. One ambitious idea would be: 
207 
field#0(3)[] Ft = (bspln3 ⊗ bspln3 ⊗ tent) ⊛ img; // 2D timevarying field 
field#0(3)[] Ft = (bspln3 ⊗ bspln3 ⊗ tent) ⊛ img; // 2D timevarying field 
208 
field#0(2)[] F = lambda([x,y], Ft([x,y,42.0])) // restriction to time=42.0 
field#0(2)[] F = lambda([x,y], Ft([x,y,42.0])) // restriction to time=42.0 
209 
vec2 grad = ∇F([x,y]); // 2D gradient 
vec2 grad = ∇F([x,y]); // 2D gradient 
215 


216 
outer works on all tensors 
outer works on all tensors 
217 


218 

Help for debugging Diderot programs: need to be able to uniquely 
219 

identify strands, and for particular strands that are known to behave 
220 

badly, do something like printf or other logging of their computations 
221 

and updates. 
222 


223 

Permit writing dimensionally general code: Have some statement of the 
224 

dimension of the world "W" (or have it be learned from one particular 
225 

field of interest), and then able to write "vec" instead of 
226 

"vec2/vec3", and perhaps "tensor[W,W]" instead of 
227 

"tensor[2,2]/tensor[3,3]" 
228 


229 

Traits: all things things that have boilerplate code (especially 
230 

volume rendering) should be expressed in terms of the unique 
231 

computational core. Different kinds of streamline/tractography 
232 

computation will be another example, as well as particle systems. 
233 


234 
Einstein summation notation 
Einstein summation notation 
235 


236 
"tensor comprehension" (like list comprehension) 
"tensor comprehension" (like list comprehension) 
237 


238 

Fields coming from different sources of data: 
239 

* triangular or tetrahedral meshes over 2D or 3D domains (of the 
240 

source produced by finiteelement codes; these will come with their 
241 

own specialized kinds of reconstruction kernels, called "basis 
242 

functions" in this context) 
243 

* Large point clouds, with some radial basis function around each point, 
244 

which will be tuned by parameters of the point (at least one parameter 
245 

giving some notion of radius) 
246 


247 
====================== 
====================== 
248 
BUGS ================= 
BUGS ================= 
249 
====================== 
====================== 
253 
// uncaught exception Size [size] 
// uncaught exception Size [size] 
254 
// raised at ctarget/ctarget.sml:47.1547.19 
// raised at ctarget/ctarget.sml:47.1547.19 
255 
//field#4(3)[] F = img ⊛ bspln5; 
//field#4(3)[] F = img ⊛ bspln5; 
256 

