Download Quantified Maximum Entropy MemSys5 Users` Manual

Chapter 11
Example of simple use
A self-documented “TOY” deconvolution simulation is supplied with copies of MemSys5. Schematically, it operates as follows, using the basic steps common to maximum entropy driving programs.
1. Call MEINIT to initialise the package.
2. Request user input (here METHOD, NRAND, AIM, RATE, UTOL and ICF width for flexible testing).
3. Initialise the storage area management. (“TOY” has 64-cell areas, broken into multiple blocks
for illustration.)
4. Call MEMTRQ to check that ICF/TRICF and OPUS/TROPUS are consistent (this step is optional).
5. Read the data into area h21i from the appropriate disc file, set up the default m (or m/(1 −m)
for Fermi–Dirac entropy) in DEF or h3i, and, for Gaussian likelihood, the accuracies [σ −1 ] in
ACC or h22i. The data are from a simulation in which a 64-cell visible-space distribution
is convolved with a square point-spread function of width five cells. Three files of data are
provided: gauss.dat in which Gaussian noise with standard deviation 10 units is added to
produce the dataset shown in Figure 11.1 (for METHOD(2) = 1), poiss.dat in which Poisson
noise is added (for METHOD(2) = 2), and fermi.dat in which the data are scaled suitably for
Fermi–Dirac entropy (METHOD(1) = 3).
6.
CALL MEMSET(METHOD,...)
MEMRUN=1
Repeat . . .
CALL MEM5(ST,MEMRUN,...)
MEMRUN=2
. . . until (ISTAT.EQ.0)
to set up the control variables for MEM5
to make MEM5 start a new run
to update w and maybe find Pr(D | α) and G
to make MEM5 continue the run
repeat until MEM5 has converged
7. Interrogate and/or output the results.
8.
9.
Repeat . . .
CALL MOVIE5(..)
. . . until (finish)
to obtain a sample from Pr(f | D)
repeat for as many samples as desired
Repeat . . .
Set mask
CALL MTRICF(..)
CALL MASK5(..)
. . . until (finish)
to define a linear feature of f
to generate hidden-space mask
to estimate the feature, with error bar
repeat for as many features as desired
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