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THIS TODO HAS BEEN MOVED TO THE DIDEROT WIKI: 
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http://diderotwiki.cs.uchicago.edu/index.php/Todo 
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PLEASE USE THAT PAGE TO UPDATE PROBLEMS AND PROGRESS 
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NOTE: GLK's approximate ranking of 8 most important tagged with 
NOTE: GLK's approximate ranking of 8 most important tagged with 
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[GLK:1], [GLK:2], ... 
[GLK:1], [GLK:2], ... 
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SHORT TERM ============= (*needed* for streamlines & tractography) 
SHORT TERM ============= (*needed* for streamlines & tractography) 
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======================== 
======================== 
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[GLK:3] Add sequence types (needed for evals & evecs) 
[GLK:2] Add sequence types (needed for evals & evecs) 
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syntax 
syntax 
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types: ty '{' INT '}' 
types: ty '{' INT '}' 
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value construction: '{' e1 ',' … ',' en '}' 
value construction: '{' e1 ',' … ',' en '}' 
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indexing: e '{' e '}' 
indexing: e '{' e '}' 
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[GLK:4] evals & evecs for symmetric tensor[2,2] and 
[GLK:3] evals & evecs for symmetric tensor[2,2] and 
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tensor[3,3] (requires sequences) 
tensor[3,3] (requires sequences) 
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ability to emit/track/record variables into dynamically resized 
ability to emit/track/record variables into dynamically resized 
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runtime buffer 
runtime output buffer 
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tensor fields: convolution on general tensor images 
[GLK:4] tensor fields from tensor images: Initially need at least 
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convolution on tensor[2,2] and tensor[3,3] (the same componentwise 
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convolution as for vectors). 
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======================== 
======================== 
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SHORTISH TERM ========= (to make using Diderot less annoying to 
SHORTISH TERM ========= (to make using Diderot less annoying to 
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======================== program in, and slow to execute) 
======================== program in, and slow to execute) 
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valuenumbering optimization [DONE, but needs more testing] 
Allow ".ddro" file extensions in addition to ".diderot" 
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Be able to output values of type tensor[2,2] and tensor[3,3]; 
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(currently only scalars & vectors). Want to add some regression tests 
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based on this and currently can't 
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[GLK:1] Add a clamp function, which takes three arguments; either 
[GLK:1] Proper handling of stabilize method 

three scalars: 


clamp(lo, hi, x) = max(lo, min(hi, x)) 


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 

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[GLK:2] Proper handling of stabilize method 
Convolution on general tensor images (order > 2) 
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allow "*" to represent "modulate": percomponent multiplication of 
allow "*" to represent "modulate": percomponent multiplication of 
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vectors, and vectors only (not tensors of order 2 or higher). Once 
vectors, and vectors only (not tensors of order 2 or higher). Once 
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implicit type promotion of integers to reals where reals are 
implicit type promotion of integers to reals where reals are 
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required (e.g. not exponentiation "^") 
required (e.g. not exponentiation "^") 
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[GLK:5] Save Diderot output to nrrd, instead of "mip.txt" 
[Nick working on this] Save Diderot output to nrrd, instead of "mip.txt" 
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For grid of strands, save to similarlyshaped array 
For grid of strands, save to similarlyshaped array 
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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 
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For ragged things (like tractography output), will need to save both 
For ragged things (like tractography output), will need to save both 
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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 
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to index into complete list 
to index into complete list 
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[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 

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*always* "inside"; with various ways of mapping the known image values 
*always* "inside"; with various ways of mapping the known image values 
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to nonexistant index locations. One possible syntax emphasizes that 
to nonexistant index locations. One possible syntax emphasizes that 
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there is a index mapping function that logically precedes convolution: 
there is a index mapping function that logically precedes convolution: 
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rgb = real{3} 
rgb = real{3} 
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rgba = real{4} 
rgba = real{4} 
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Revisit how images are created within the language. 
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The "load" operator should probably go away, and its strange 
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that strings are there only as a way to refer to nrrd filenames 
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============================== 
============================== 
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MEDIUM TERM ================== (*needed* for particles) 
MEDIUM TERM ================== (*needed* for particles) 
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============================== 
============================== 
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runtime birth of strands 
[Lamont working on this] runtime birth of strands 
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"initially" supports lists 
"initially" supports lists 
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"initially" supports lists of positions output from 
"initially" supports lists of positions output from different 
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different initalization Diderot program 
initalization Diderot program (or output from the same program; 
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e.g. using output of iso2d.diderot for one isovalue to seed the input 
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Communication between strands: they have to be able to learn each 
to another invocation of the same program) 
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other's state (at the previous iteration). Early version of this can 

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have the network of neighbors be completely static (for running one 
[Lamont working on this] Communication between strands: they have to 
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strand/pixel image computations). Later version with strands moving 
be able to learn each other's state (at the previous iteration). 
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through the domain will require some spatial data structure to 
Early version of this can have the network of neighbors be completely 
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optimize discovery of neighbors. 
static (for running one strand/pixel image computations). Later 
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version with strands moving through the domain will require some 
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spatial data structure to optimize discovery of neighbors. 
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============================ 
============================ 
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MEDIUMISH TERM ============ (to make Diderot more useful/effective) 
MEDIUMISH TERM ============ (to make Diderot more useful/effective) 
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============================ 
============================ 
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[GLK:5] Want codegeneration working for tensors of order three. 
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Order three matters for edge detection in scalar fields (to get 
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second derivatives of gradient magnitude), second derivatives 
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of vector fields (for some feature extraction), and first 
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derivatives of diffusion tensor fields. 
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Python/ctypes interface to runtime 
Python/ctypes interface to runtime 
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support for Python interop and GUI 
support for Python interop and GUI 
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Allow integer exponentiation ("^2") to apply to square matrices, 
Allow integer exponentiation ("^2") to apply to square matrices, 
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to represent repeated matrix multiplication 
to represent repeated matrix multiplication 
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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. 




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Put small 1D and 2D fields, when reconstructed specifically by tent 
Put small 1D and 2D fields, when reconstructed specifically by tent 
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and when differentiation is not needed, into faster texture buffers. 
and when differentiation is not needed, into faster texture buffers. 
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test/illustvr.diderot is good example of program that uses multiple 
test/illustvr.diderot is good example of program that uses multiple 
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such 1D fields basically as lookuptablebased function evaluation 
such 1D fields basically as lookuptablebased function evaluation 
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expand trace in mid to low translation 




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extend norm (exp) to all tensor types [DONE for vectors and matrices] 
extend norm (exp) to all tensor types [DONE for vectors and matrices] 
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determinant ("det") for tensor[3,3] 
determinant ("det") for tensor[3,3] 
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tensor construction [DONE] 
tensor construction [DONE] 
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tensor indexing [DONE] 
tensor indexing [DONE] 
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tensor slicing 
tensor slicing 

verify that hessians work correctly [DONE] 

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Better handling of variables that determines the scope of a variable 
Better handling of variables that determines the scope of a variable 
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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, 
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(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 
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conditional. 
conditional. 
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[GLK:8] Want: nontrivial field expressions & functions. 
[GLK:7] Want: nontrivial field expressions & functions. 
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scalar fields from scalar fields F and G: 
scalar fields from scalar fields F and G: 
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field#0(2)[] X = (sin(F) + 1.0)/2; 
field#0(2)[] X = (sin(F) + 1.0)/2; 
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field#0(2)[] X = F*G; 
field#0(2)[] X = F*G; 
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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 
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not supported (hence the indication of "field#0" for these above) 
not supported (hence the indication of "field#0" for these above) 
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Introduce region types (syntax region(d), where d is the dimension of the 
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region. One useful operator would be 
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dom : field#k(d)[s] > region(d) 
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Then the inside test could be written as 
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pos ∈ dom(F) 
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We could further extend this approach to allow geometric definitions of 
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regions. It might also be useful to do inside tests in world space, 
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instead of image space. 
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co vs contra index distinction 
co vs contra index distinction 
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Permit field composition: 
Permit field composition: 
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field#2(3)[] F = bspln3 ⊛ img; 
field#2(3)[] F = bspln3 ⊛ img; 
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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. 
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field#0(3)[] F = (bspln3 ⊗ bspln3 ⊗ tent) ⊛ img; 
field#0(3)[] F = (bspln3 ⊗ bspln3 ⊗ tent) ⊛ img; 
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This is especially important for things like timevarying data, or 
This is especially important for things like timevarying fields 
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other multidimensional fields where one axis of the domain is very 
and the use of scalespace in field visualization: one axis of the 
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different from the rest, and hence must be treated separately when 
must be convolved with a different kernel during probing. 
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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 
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we should notate the gradient, when we only want to differentiate with 
gradient, when we only want to differentiate with respect to some 
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respect to some subset of the axes. One ambitious idea would be: 
subset of the axes. One ambitious idea would be: 
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field#0(3)[] Ft = (bspln3 ⊗ bspln3 ⊗ tent) ⊛ img; // 2D timevarying field 
field#0(3)[] Ft = (bspln3 ⊗ bspln3 ⊗ tent) ⊛ img; // 2D timevarying field 
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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 
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vec2 grad = ∇F([x,y]); // 2D gradient 
vec2 grad = ∇F([x,y]); // 2D gradient 
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outer works on all tensors 
outer works on all tensors 
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Help for debugging Diderot programs: need to be able to uniquely 
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identify strands, and for particular strands that are known to behave 
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badly, do something like printf or other logging of their computations 
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and updates. 
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Permit writing dimensionally general code: Have some statement of the 
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dimension of the world "W" (or have it be learned from one particular 
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field of interest), and then able to write "vec" instead of 
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"vec2/vec3", and perhaps "tensor[W,W]" instead of 
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"tensor[2,2]/tensor[3,3]" 
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Traits: all things things that have boilerplate code (especially 
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volume rendering) should be expressed in terms of the unique 
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computational core. Different kinds of streamline/tractography 
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computation will be another example, as well as particle systems. 
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Einstein summation notation 
Einstein summation notation 
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"tensor comprehension" (like list comprehension) 
"tensor comprehension" (like list comprehension) 
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Fields coming from different sources of data: 
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* triangular or tetrahedral meshes over 2D or 3D domains (of the 
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source produced by finiteelement codes; these will come with their 
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own specialized kinds of reconstruction kernels, called "basis 
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functions" in this context) 
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* Large point clouds, with some radial basis function around each point, 
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which will be tuned by parameters of the point (at least one parameter 
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giving some notion of radius) 
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====================== 
====================== 
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BUGS ================= 
BUGS ================= 
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====================== 
====================== 
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// uncaught exception Size [size] 
// uncaught exception Size [size] 
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// raised at ctarget/ctarget.sml:47.1547.19 
// raised at ctarget/ctarget.sml:47.1547.19 
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//field#4(3)[] F = img ⊛ bspln5; 
//field#4(3)[] F = img ⊛ bspln5; 
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