Diff of /trunk/TODO

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	revision 1441, Sun Jul 10 08:02:53 2011 UTC	revision 1442, Sun Jul 10 08:09:50 2011 UTC
#	Line 17	Line 17
17	ability to emit/track/record variables into dynamically re-sized	ability to emit/track/record variables into dynamically re-sized
18	runtime output buffer	runtime output buffer
19
20	tensor fields: convolution on general tensor images (order > 1)	[GLK:4] tensor fields from tensor images: Initially need at least
21		convolution on tensor[2,2] and tensor[3,3] (the same component-wise
22		convolution as for vectors).
23
24	========================	========================
25	SHORT-ISH TERM ========= (to make using Diderot less annoying to	SHORT-ISH TERM ========= (to make using Diderot less annoying to
#	Line 31	Line 33
33
34	[GLK:1] 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": per-component multiplication of	allow "*" to represent "modulate": per-component 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
40	sequences are implemented this should be removed: the operation is not	sequences are implemented this should be removed: the operation is not
#	Line 39	Line 43
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:4] 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 similarly-shaped array	For grid of strands, save to similarly-shaped array
48	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
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:5] ability to declare a field so that probe positions are	[GLK:6] 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 non-existant index locations.  One possible syntax emphasizes that	to non-existant 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:
#	Line 77	Line 81
81	MEDIUM TERM ================== (*needed* for particles)	MEDIUM TERM ================== (*needed* for particles)
82	==============================	==============================
83
84	run-time birth of strands	[Lamont working on this] run-time birth of strands
85
86	"initially" supports lists	"initially" supports lists
87
#	Line 86	Line 90
90	e.g. using output of iso2d.diderot for one isovalue to seed the input	e.g. using output of iso2d.diderot for one isovalue to seed the input
91	to another invocation of the same program)	to another invocation of the same program)
92
93	Communication between strands: they have to be able to learn each	[Lamont working on this] Communication between strands: they have to
94	other's state (at the previous iteration).  Early version of this can	be able to learn each other's state (at the previous iteration).
95	have the network of neighbors be completely static (for running one	Early version of this can have the network of neighbors be completely
96	strand/pixel image computations).  Later version with strands moving	static (for running one strand/pixel image computations).  Later
97	through the domain will require some spatial data structure to	version with strands moving through the domain will require some
98	optimize discovery of neighbors.	spatial data structure to optimize discovery of neighbors.
99
100	============================	============================
101	MEDIUM-ISH TERM ============ (to make Diderot more useful/effective)	MEDIUM-ISH TERM ============ (to make Diderot more useful/effective)
102	============================	============================
103
104		[GLK:5] Want code-generation 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 run-time	Python/ctypes interface to run-time
111
112	support for Python interop and GUI	support for Python interop and GUI
#	Line 128	Line 138
138	LONG TERM ==================== (make Diderot more interesting/attractive from	LONG TERM ==================== (make Diderot more interesting/attractive from
139	==============================  a research standpoint)	==============================  a research standpoint)
140
	[GLK:6] Want code-generation working for tensors of order three.
	Order three matters for edge detection in scalar fields (to get
	second derivatives of gradient magnitude), second derivatives
	of vector fields (for some feature extraction), and first
	derivatives of diffusion tensor fields.
141	IL support for higher-order tensor values (matrices, etc).	IL support for higher-order tensor values (matrices, etc).
142	tensor construction [DONE]	tensor construction [DONE]
143	tensor indexing [DONE]	tensor indexing [DONE]
#	Line 204	Line 208
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
210
	Tensors of order 3 (e.g. gradients of diffusion tensor fields, or
	hessians of vector fields) and order 4 (e.g. Hessians of diffusion
	tensor fields).
211	representation of tensor symmetry	representation of tensor symmetry
212	(have to identify the group of index permutations that are symmetries)	(have to identify the group of index permutations that are symmetries)
213

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