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[diderot] Diff of /branches/tash/TODO
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# Diff of /branches/tash/TODO

trunk/TODO revision 1195, Thu May 12 03:07:35 2011 UTC branches/vis12/TODO revision 1685, Sun Jan 22 15:23:36 2012 UTC
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1    ***************************************************
2    ***************************************************
3    THIS TODO HAS BEEN MOVED TO THE DIDEROT WIKI:
4
5    http://diderot-wiki.cs.uchicago.edu/index.php/Todo
6
7    PLEASE USE THAT PAGE TO UPDATE PROBLEMS AND PROGRESS
8    ***************************************************
9    ***************************************************
10
11  NOTE: GLK's approximate ranking of 8 most important tagged with  NOTE: GLK's approximate ranking of 8 most important tagged with
12  [GLK:1], [GLK:2], ...  [GLK:1], [GLK:2], ...
13
# Line 5  Line 15
15  SHORT TERM ============= (*needed* for streamlines & tractography)  SHORT TERM ============= (*needed* for streamlines & tractography)
16  ========================  ========================
17
18  [GLK:3] Add sequence types (needed for evals & evecs)  [GLK:2] Add sequence types (needed for evals & evecs)
19      syntax      syntax
20          types: ty '{' INT '}'          types: ty '{' INT '}'
21          value construction: '{' e1 ',' … ',' en '}'          value construction: '{' e1 ',' … ',' en '}'
22          indexing: e '{' e '}'          indexing: e '{' e '}'
23
24  [GLK:4] evals & evecs for symmetric tensor[2,2] and  [GLK:3] evals & evecs for symmetric tensor[2,2] and
25  tensor[3,3] (requires sequences)  tensor[3,3] (requires sequences)
26
27  ability to emit/track/record variables into dynamically re-sized  ability to emit/track/record variables into dynamically re-sized
28  runtime buffer  runtime output buffer
29
30  tensor fields: convolution on general tensor images  [GLK:4] tensor fields from tensor images: Initially need at least
31    convolution on tensor[2,2] and tensor[3,3] (the same component-wise
32    convolution as for vectors).
33
34  ========================  ========================
35  SHORT-ISH TERM ========= (to make using Diderot less annoying to  SHORT-ISH TERM ========= (to make using Diderot less annoying to
36  ========================  program in, and slow to execute)  ========================  program in, and slow to execute)
37
value-numbering optimization [DONE, but needs more testing]

38  Allow ".ddro" file extensions in addition to ".diderot"  Allow ".ddro" file extensions in addition to ".diderot"
39
40  Be able to output values of type tensor[2,2] and tensor[3,3]  Be able to output values of type tensor[2,2] and tensor[3,3];
41  (currently only scalars & vectors)  (currently only scalars & vectors).  Want to add some regression tests
42    based on this and currently can't
43
44  [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
45
46  [GLK:2] Proper handling of stabilize method  Convolution on general tensor images (order > 2)
47
48  allow "*" to represent "modulate": per-component multiplication of  allow "*" to represent "modulate": per-component multiplication of
49  vectors, and vectors only (not tensors of order 2 or higher).  Once  vectors, and vectors only (not tensors of order 2 or higher).  Once
# Line 51  Line 53
53  implicit type promotion of integers to reals where reals are  implicit type promotion of integers to reals where reals are
54  required (e.g. not exponentiation "^")  required (e.g. not exponentiation "^")
55
56  [GLK:5] Save Diderot output to nrrd, instead of "mip.txt"  [Nick working on this] Save Diderot output to nrrd, instead of "mip.txt"
57    For grid of strands, save to similarly-shaped array    For grid of strands, save to similarly-shaped array
58    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
59    For ragged things (like tractography output), will need to save both    For ragged things (like tractography output), will need to save both
60      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
61      to index into complete list      to index into complete list
62
63  [GLK:6] Use of Teem's "hest" command-line 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
64  *always* "inside"; with various ways of mapping the known image values  *always* "inside"; with various ways of mapping the known image values
65  to non-existant index locations.  One possible syntax emphasizes that  to non-existant index locations.  One possible syntax emphasizes that
66  there is a index mapping function that logically precedes convolution:  there is a index mapping function that logically precedes convolution:
# Line 84  Line 83
83      rgb = real{3}      rgb = real{3}
84      rgba = real{4}      rgba = real{4}
85
86    Revisit how images are created within the language.
87    The "load" operator should probably go away, and its strange
88    that strings are there only as a way to refer to nrrd filenames
89
90  ==============================  ==============================
91  MEDIUM TERM ================== (*needed* for particles)  MEDIUM TERM ================== (*needed* for particles)
92  ==============================  ==============================
93
94  run-time birth of strands  [Lamont working on this] run-time birth of strands
95
96  "initially" supports lists  "initially" supports lists
97
98  "initially" supports lists of positions output from  "initially" supports lists of positions output from different
99  different initalization Diderot program  initalization Diderot program (or output from the same program;
100    e.g. using output of iso2d.diderot for one isovalue to seed the input
101  Communication between strands: they have to be able to learn each  to another invocation of the same program)
102  other's state (at the previous iteration).  Early version of this can
103  have the network of neighbors be completely static (for running one  [Lamont working on this] Communication between strands: they have to
104  strand/pixel image computations).  Later version with strands moving  be able to learn each other's state (at the previous iteration).
105  through the domain will require some spatial data structure to  Early version of this can have the network of neighbors be completely
106  optimize discovery of neighbors.  static (for running one strand/pixel image computations).  Later
107    version with strands moving through the domain will require some
108    spatial data structure to optimize discovery of neighbors.
109
110  ============================  ============================
111  MEDIUM-ISH TERM ============ (to make Diderot more useful/effective)  MEDIUM-ISH TERM ============ (to make Diderot more useful/effective)
112  ============================  ============================
113
114    [GLK:5] Want code-generation working for tensors of order three.
115    Order three matters for edge detection in scalar fields (to get
116    second derivatives of gradient magnitude), second derivatives
117    of vector fields (for some feature extraction), and first
118    derivatives of diffusion tensor fields.
119
120  Python/ctypes interface to run-time  Python/ctypes interface to run-time
121
122  support for Python interop and GUI  support for Python interop and GUI
# Line 113  Line 124
124  Allow integer exponentiation ("^2") to apply to square matrices,  Allow integer exponentiation ("^2") to apply to square matrices,
125  to represent repeated matrix multiplication  to represent repeated matrix multiplication
126
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.

127  Put small 1-D and 2-D fields, when reconstructed specifically by tent  Put small 1-D and 2-D fields, when reconstructed specifically by tent
128  and when differentiation is not needed, into faster texture buffers.  and when differentiation is not needed, into faster texture buffers.
129  test/illust-vr.diderot is good example of program that uses multiple  test/illust-vr.diderot is good example of program that uses multiple
130  such 1-D fields basically as lookup-table-based function evaluation  such 1-D fields basically as lookup-table-based function evaluation
131
expand trace in mid to low translation

132  extend norm (|exp|) to all tensor types [DONE for vectors and matrices]  extend norm (|exp|) to all tensor types [DONE for vectors and matrices]
133
134  determinant ("det") for tensor[3,3]  determinant ("det") for tensor[3,3]
# Line 147  Line 152
152      tensor construction [DONE]      tensor construction [DONE]
153      tensor indexing [DONE]      tensor indexing [DONE]
154      tensor slicing      tensor slicing
verify that hessians work correctly [DONE]
155
156  Better handling of variables that determines the scope of a variable  Better handling of variables that determines the scope of a variable
157  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,
# Line 161  Line 165
165  (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
166  conditional.  conditional.
167
168  [GLK:8] Want: non-trivial field expressions & functions.  [GLK:7] Want: non-trivial field expressions & functions.
169  scalar fields from scalar fields F and G:  scalar fields from scalar fields F and G:
170    field#0(2)[] X = (sin(F) + 1.0)/2;    field#0(2)[] X = (sin(F) + 1.0)/2;
171    field#0(2)[] X = F*G;    field#0(2)[] X = F*G;
# Line 204  Line 208
208    field#2(3)[] F = bspln3 ⊛ img;    field#2(3)[] F = bspln3 ⊛ img;
209  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.
210    field#0(3)[] F = (bspln3 ⊗ bspln3 ⊗ tent) ⊛ img;    field#0(3)[] F = (bspln3 ⊗ bspln3 ⊗ tent) ⊛ img;
211  This is especially important for things like time-varying data, or  This is especially important for things like time-varying fields
212  other multi-dimensional fields where one axis of the domain is very  and the use of scale-space in field visualization: one axis of the
213  different from the rest, and hence must be treated separately when  must be convolved with a different kernel during probing.
214  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
215  we should notate the gradient, when we only want to differentiate with  gradient, when we only want to differentiate with respect to some
216  respect to some subset of the axes.  One ambitious idea would be:  subset of the axes.  One ambitious idea would be:
217    field#0(3)[] Ft = (bspln3 ⊗ bspln3 ⊗ tent) ⊛ img; // 2D time-varying field    field#0(3)[] Ft = (bspln3 ⊗ bspln3 ⊗ tent) ⊛ img; // 2D time-varying field
218    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
# Line 221  Line 225
225
226  outer works on all tensors  outer works on all tensors
227
228    Help for debugging Diderot programs: need to be able to uniquely
229    identify strands, and for particular strands that are known to behave
230    badly, do something like printf or other logging of their computations
232
233    Permit writing dimensionally general code: Have some statement of the
234    dimension of the world "W" (or have it be learned from one particular
235    field of interest), and then able to write "vec" instead of
236    "vec2/vec3", and perhaps "tensor[W,W]" instead of
237    "tensor[2,2]/tensor[3,3]"
238
239    Traits: all things things that have boilerplate code (especially
240    volume rendering) should be expressed in terms of the unique
241    computational core.  Different kinds of streamline/tractography
242    computation will be another example, as well as particle systems.
243
244  Einstein summation notation  Einstein summation notation
245
246  "tensor comprehension" (like list comprehension)  "tensor comprehension" (like list comprehension)
247
248    Fields coming from different sources of data:
249    * triangular or tetrahedral meshes over 2D or 3D domains (of the
250      source produced by finite-element codes; these will come with their
251      own specialized kinds of reconstruction kernels, called "basis
252      functions" in this context)
253    * Large point clouds, with some radial basis function around each point,
254      which will be tuned by parameters of the point (at least one parameter
255      giving some notion of radius)
256
257  ======================  ======================
258  BUGS =================  BUGS =================
259  ======================  ======================
# Line 234  Line 263
263  //  uncaught exception Size [size]  //  uncaught exception Size [size]
264  //    raised at c-target/c-target.sml:47.15-47.19  //    raised at c-target/c-target.sml:47.15-47.19
265  //field#4(3)[] F = img ⊛ bspln5;  //field#4(3)[] F = img ⊛ bspln5;
266

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