Modules

MAN

Extend mathjs script with mathjx script
and various numerical methods.

This module documented in accordance with jsdoc.

MATHJX

Reduce a mathjx-script to a mathjs-script
using the following language model:

if TEST
    BLOCK
elseif TEST
    BLOCK
:
else
    BLOCK
end
switch TEST
    case TEST
        BLOCK
    :
    default TEST
        BLOCK
end
try
    BLOCK
catch
    BLOCK
end
for INDEX
    BLOCK
end
while TEST
    BLOCK
end
until TEST
    BLOCK
end
when EVENT
    BLOCK
end
def f=(x,y,...)
    BLOCK
end

Inline functions are also supported using fat-arrows:

(x,y,...) => {
    BLOCK
}

JIMP

MAN

This module documented in accordance with jsdoc.

Requires: module:enums, module:mathjx, module:kalman-filter, module:arima, module:crypto, module:mathjs, module:fft-js, module:nodehmm, module:node-svd, module:node-svm, module:mljs, module:jimp, module:jsbayes, module:recurrent-js, module:gamma, module:expectation-maximization, module:multivariate-normal, module:newton-raphson, module:random-seed, module:edmonds-blossom, module:simple-simplex, module:@tensorflow/tfjs, module:sdbscan, module:tsne-js
Author: ACMESDS

| Param | Type | Description |
| --- | --- | --- |
| pgm | String | MathJx script to process. |
| ctx | Object | Context to run script. |

Example ( <caption>Eval a js or mathjs script in a context ctx)
``js

var
ctx = $( "script", ctx, ctx => { // eval with callback
Trace("updated context", ctx);
} ),

ctx = "script".$( ctx ), // abbreviated

{ x, y, ... } = "script".$( ctx ) || {}; // with context x,y extractions
`
Example (Create a matrix)
`js

var
A = $( N, (n,A) => A[n] = ... ) , // define N-length vector
A = $( [M,N], (n,m,A) => A[m][n] = ... ) ; // define M x N matrrix
`
Example (Index a matrix)
`js

A.$( (n,A) => A[n] = ... ) // index vector with callback
A.$$( (n,m,A) => A[n][m] = ... ) // index matrix with callback
`
Example (Sample a matrix with optional callback cb(val))
`js

var
B = A.get( idx , cb),
B = A.get( "key, ...", cb ),
B = A.get( [idx, ...] , cb),
B = A.get( [key, ...] , cb ),
B = A.get( {rekey: { toKey: "fromKey", ... }, cb ),
B = A.get( {draw: N}, cb ),
B = A.get( {start:N, count:N}, cb ),
B = A.get( {KEY_starts: "with", ...}, cb ),
B = A.get( {KEY_ends: "with", ...}, cb )
`
Example (Import functions to $.somefn and to $( "somefn(...)" ))
`js

$( {
somefn: function (args) { ... },
:
:
} );
`
Example (Use the task sharder)
`js

$( {
keys: "i,j,k", // array indicies
i: [0,1,2,3], // domain of index i
j: [4,8], // domain of index j
k: [0], // domain of index k
qos: 0, // regulation time in ms if not zero
local: false, // enable to run task local, i.e. w/o workers and nodes
workers: 4, // limit number of workers (aka cores) per node
nodes: 3 // limit number of nodes (ala locales) in the cluster
},

// here, a simple task that returns a message
$ => "my result is " + (i + j*k) + " from " + $.worker + " on " + $.node,

// here, a simple callback that displays the task results
msg => console.log(msg)
);
`
Example (Aggregate and save events ev = {at: "KEY", ...} to ctx.Save_KEY)
`js

[ev, ...].save( ctx, evs => { // unsave events ... } );
"query".save( ctx, evs => { //unsave events ... } );
`
Example (Indexing methods)
`js

$( "mathjs script", ctx, ctx => { ... } )
$( "mathjs script", ctx )
$( "mathjs script" )
$( [M,N], (m,n,A) => { A[m][n] = ... } )
$( N, (n,A) => { A[n] = ... } )
$({ // import functions
f: (...) => { ... },
...
})
$({ // task sharding
keys: "i,j,...", // array indicies
i: [...], // domain of index i
j: [...], // domain of index j
k: [...], // domain of index k
qos: N, // regulation time in ms if not zero
local: false, // enable to run task local, i.e. w/o workers and nodes
workers: N, // limit number of workers (aka cores) per node
nodes: N // limit number of nodes (ala locales) in the cluster
},

// here, a simple task that returns a message
$ => "my result is " + (i + j*k) + " from " + $.worker + " on " + $.node,

// here, a simple callback that displays the task results
msg => console.log(msg)
);
`
Example (Eval a mathjs script with optional callback and optional context)
`js

var
ctx = $( "mathjs script", ctx, ctx => {
x: 1,
y: 20, ...
} );
`
Example (Eval with extraction of context keys)
`js

const {x, y, ... } = $( "mathjs script", ctx ) || {};
`
Example (Import functions)
`js
$( {
somefn: function (args) { ... },
:
:
} );
`
Example (Use the task sharder)
`js
$( {
keys: "i,j,k", // array indicies
i: [0,1,2,3], // domain of index i
j: [4,8], // domain of index j
k: [0], // domain of index k
qos: 0, // regulation time in ms if not zero
local: false, // enable to run task local, i.e. w/o workers and nodes
workers: 4, // limit number of workers (aka cores) per node
nodes: 3 // limit number of nodes (ala locales) in the cluster
},

// here, a simple task that returns a message
$ => "my result is " + (i + j*k) + " from " + $.worker + " on " + $.node,

// here, a simple callback that displays the task results
msg => console.log(msg)
);
`


MATHJX

Example (js-reduction)
`js
\\ program
def f=(x,y)
f=x+y;
end

\\ reduces to
def($ctx[1])

\\ with resulting context
[ { test: 'f=(x,y)', code: 'f=x+y\n' } ]
`
Example (js-reduction)
`js
\\ program
for i
i1
i2
for j
j1; j2;
while u\u1\end
end
end
\\ reduces to
for($ctx[3])
\\ with resulting context
[
{ test: 'u', code: 'u1\n' },
{ test: 'j', code: 'j1; j2;\nwhile($ctx[1])' },
{ test: 'i', code: 'i1\ni2\nfor($ctx[2])' }
]
`
Example (js-reduction)
`js
\\ program
a1="this;is;a;test";
\\ reduces to
a1=$ctx[1];
\\ with resulting context
[ 'this;is;a;test' ]
`
Example (js-reduction)
`js
\\ program
somefn(1,2, \def f=(x,y)
print("x=%f and y=%f",x,y);
end
)
\\ and program
somefn(1,2, \(x,y) => {
print("x=%f and y=%f",x,y);
})
\\ reduces to
def($ctx[2]))
\\ with resulting context
[ 'x=%f and y=%f', { test: 'f=(x,y)', code: 'print($ctx[1],x,y);\n' } ]
`
Example (js-reduction)
`js
\\ program
def f=(x,y)
f=x+y;
end
disp(f(1,2));
\\ reduces to
def($ctx[1]);disp(f(1,2));
\\ with resulting context
[ { test: 'f=(x,y)', code: 'f=x+y;\n' } ]
`
Example (js-reduction)
`js
\\ program
def f=([a,b],{x,y})
f=x+y+a+b;
end
disp(f([4,5],{x:10,y:20}));
\\ reduces to
def($ctx[1]);disp(f([4,5],{x:10,y:20}));
\\ with resulting context
[ { test: 'f=([a,b],{x,y})', code: 'f=x+y+a+b;\n' } ]
``

* MATHJX
* ~saveKeys
* ~scripts
* .conf
* .pca
* .roc
* .snr
* .p0
* .pw
* .wk
* .trigger()
* ~def()
* ~for()
* ~while()
* ~if()
* ~try()
* ~switch()
* ~when()
* ~until()
* ~isNull()
* ~eye()
* ~toMatrix()
* ~toList()
* ~isDefined()
* ~rank()
* ~size()
* ~len()
* ~disp()
* ~print()
* ~plot()
* ~resnet()
* ~ols(use, x, y, solve, cb)
* ~train()
* ~predict(cls, use, x, y, solve, cb)
* ~qda_train()
* ~qda_predict()
* ~beta_train()
* ~beta_predict()
* ~rnn_train()
* ~rnn_predict()
* ~ann_train()
* ~ann_predict()
* ~dnn_train()
* ~dnn_predict()
* ~dhs_train()
* ~dhs_predict()
* ~lda_train()
* ~lda_predict()
* ~ror_train()
* ~ror_predict()
* ~dtr_train()
* ~dtr_predict()
* ~raf_train()
* ~raf_predict()
* ~nab_train()
* ~nab_predict()
* ~som_train()
* ~som_predict()
* ~ols_train()
* ~ols_predict()
* ~svm_train()
* ~svm_predict()
* ~lrm_train()
* ~lrm_predict()
* ~knn_train()
* ~knn_predict()
* ~pls_train()
* ~pls_predict()
* ~rp()
* ~mcmc()
* ~triggerProfile()
* ~coherenceIntervals()
* ~arrivalRates()
* ~estGauss()
* [~oga([Array], [Array], [Function])](#module_MATHJX..oga)
* ~getEv(d, keys)
* ~putEv()
* ~stateSize()
* ~BIC()
* ~draw()
* ~cum()
* ~crf()
* ~propEv()
* ~CMI()
* ~indicate()
* ~boost(cycle, sql, solve, trace, hypo)
* ~svd()
* ~evd()
* ~rng()
* ~rand()
* ~randRot()
* ~proj()
* ~orthoNorm()
* ~any()
* ~all()
* ~MaxFlowMinCut()
* ~ranreg()
* ~degrees()
* ~degree()
* ~nodes()
* ~spectrum()
* ~isoperi()
* ~edges()
* ~clone()
* ~graph()
* ~union()
* ~empty()
* ~ranregs()
* ~xcorr()
* ~dht()
* ~dft()
* ~pwrem()
* ~pwrec()
* ~wkpsd()
* ~psd()
* ~evpsd()
* ~udev()
* ~expdev()
* ~cumsum()
* ~conf()
* ~tolAtConf()
* ~tolsAtConf()
* ~loggamma()
* ~beta()
* ~cumbeta()
* ~sinc()
* ~rect()
* ~tri()
* ~negexp()
* ~lorenzian()
* ~zeta()
* ~infer()
* ~mle()
* ~mvn()
* ~lfa()
* ~lma()
* ~rnn()

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* ~scripts
* .conf
* .pca
* .roc
* .snr
* .p0
* .pw
* .wk
* .trigger()

#### scripts.conf
Kind: static property of scripts

#### scripts.pca
Kind: static property of scripts

#### scripts.roc
Kind: static property of scripts

#### scripts.snr
Kind: static property of scripts

#### scripts.p0
Kind: static property of scripts

#### scripts.pw
Kind: static property of scripts

#### scripts.wk
Kind: static property of scripts

#### scripts.trigger()
Kind: static method of scripts

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The y labels (<0 indicates unlabelled) are used by supervised regressors
(like OLS, logit, etc) to estimate their fitting parameters, as well as by
unsupervised regressors (like qda, som, etc) to remap their unordered solutions
into a consistant order (by computing a confusion matrix against the supplied and
the predicted labels).

Kind: inner method of MATHJX

| Param | Type | Description |
| --- | --- | --- |
| use | String | regression method |
| x | Array | sampled feature vectors |
| y | Array | labels of samples vectors (or null) |
| solve | Object | regression options |
| cb | function | callback(cls) |

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Kind: inner method of MATHJX

| Param | Type | Description |
| --- | --- | --- |
| cls | Object | classifier hash |
| use | String | regression method |
| x | Array | sampled feature vectors |
| y | Array | labels of samples vectors (or null) |
| solve | Object | regression options |
| cb | function | callback(ctx) |

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Kind: inner method of MATHJX

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x = normalized time interval of recovered trigger
h = recovered trigger function at normalized times x
modH = Fourier modulous of recovered trigger at frequencies f
argH = Fourier argument of recovered trigger at frequencies f
f = spectral frequencies

via the callback cb(stats) given a solve request:

evs = events list
refLambda = ref mean arrival rate (for debugging)
alpha = assumed detector gain
N = profile sample times = max coherence intervals
model = correlation model name
Tc = coherence time of arrival process
T = observation time

Kind: inner method of MATHJX

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| Param | Description |
| --- | --- |
| [Array] | x word list |
| [Array] | y word list |
| [Function] | s Distance function(gap marker, word) |

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Kind: inner method of MATHJX

| Param | Type | Description |
| --- | --- | --- |
| d | Array | data |
| keys | Array | keys into data |

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The hypothesis callback hypo(x,keys) will
return tested hypo if keys specified
return learned hypo keys if x specified
save hypo keys to boost stash if neither specified

Kind: inner method of MATHJX

| Param | Type | Description |
| --- | --- | --- |
| cycle | Number | number being boosted >=1 |
| sql | Object | connector |
| solve | Object | boosting options and stashes: alpha, eps, h, samples, mixes, thresh |
| trace | function | callback(msg) to handel messages |
| hypo | Funtion | callback(x,keys) |

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JIMP

* JIMP
* ~$
* ~help
* ~save()
* ~sym()
* ~XX()

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