diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..d43030c --- /dev/null +++ b/.gitignore @@ -0,0 +1,19 @@ +#- Git configuration file + +#- .gitignore ~~ +# ~~ last updated 08 Oct 2012 + +#- Mercurial repository itself (if present) +.hg/ + +#- Vim swap files +*.swp + +#- OS generated files +.DS_Store* +ehthumbs.db +Icon\? +.localized +Thumbs.db + +#- vim:set syntax=gitconfig: diff --git a/23andme.html b/23andme.html new file mode 100644 index 0000000..6cd4766 --- /dev/null +++ b/23andme.html @@ -0,0 +1,10 @@ + + + + + + +Experimenting with 23andme + + + \ No newline at end of file diff --git a/23andme.js b/23andme.js new file mode 100644 index 0000000..5cdd0d5 --- /dev/null +++ b/23andme.js @@ -0,0 +1,33 @@ +//https://api.23andme.com/authorize/?redirect_uri=http://jmat.googlecode.com/git/23andme.html&response_type=code&client_id=09568fd79aa7911dad7727a024936f8d&scope=basic +// response directed to http://jmat.googlecode.com/git/23andme.html, alternative URL: +//https://dl-web.dropbox.com/get/http/jmat/23andme.html?w=bba1484b&code={borrow from above} +// +UAB={ // 23and me application document object model + code:null, + parms:{}, + search4parms:function(){ // gets parameters from call and pushes them to .parms + var parms = window.document.location.search.slice(1).split('&'); + parms.map(function(x){ + xx = x.split('='); + UAB.parms[xx[0]]=xx[1] + }) + + // + } +} + + + +// find out what is being provided and push it to parms +UAB.search4parms(); +if(!!UAB.parms.code){ + UAB.code=UAB.parms.code; + console.log('code = '+UAB.code); +} +else if (!!localStorage.getItem('code')){ // find out if there is one in the localstorage + UAB.code = localStorage.getItem('code'); + console.log('code = '+UAB.code); +} +else{ + throw('23andme access code not found :-(') +} \ No newline at end of file diff --git a/f.png b/f.png new file mode 100644 index 0000000..d730d99 Binary files /dev/null and b/f.png differ diff --git a/fminsearch.html b/fminsearch.html new file mode 100644 index 0000000..71f35ef --- /dev/null +++ b/fminsearch.html @@ -0,0 +1,23 @@ + + + + + + +
+

fminsearch

+

This page: http://jmat.googlecode.com/git/fminsearch.html, [source code]
+ In the browser's console you could, for example, :
+

    +
  1. x=[32,37,42,47,52,57,62,67,72,77,82,87,92];y=[0,34,59,77,99,114,121,133,146,159,165,173,170]; // some data
    2. +
  2. fun = function(x,P){return x.map(function(xi){return (1/(1/(P[0]*(xi-P[1]))+1/P[2]))})}; // some model
    3. +
  3. P=fminsearch(fun,[34.6,32,173],x,y); // the regression with some starting values
    4. +
+

+
+
+ + + \ No newline at end of file diff --git a/fminsearch.js b/fminsearch.js new file mode 100644 index 0000000..5ccff12 --- /dev/null +++ b/fminsearch.js @@ -0,0 +1,89 @@ +fminsearch=function(fun,Parm0,x,y,Opt){// fun = function(x,Parm) + // example + // + // x = [32,37,42,47,52,57,62,67,72,77,82,87,92];y=[749,1525,1947,2201,2380,2537,2671,2758,2803,2943,3007,2979,2992] + // fun = function(x,P){return x.map(function(xi){return (P[0]+1/(1/(P[1]*(xi-P[2]))+1/P[3]))})} + // Parms=jmat.fminsearch(fun,[100,30,10,5000],x,y) + // + // Another test: + // x=[32,37,42,47,52,57,62,67,72,77,82,87,92];y=[0,34,59,77,99,114,121,133,146,159,165,173,170]; + // + // Opt is an object will all other parameters, from the objective function (cost function), to the + // number of iterations, initial step vector and the display switch, for example + // Parms=fminsearch(fun,[100,30,10,5000],x,y,{maxIter:10000,display:false}) + + if(!Opt){Opt={}}; + if(!Opt.maxIter){Opt.maxIter=1000}; + if(!Opt.step){// initial step is 1/100 of initial value (remember not to use zero in Parm0) + Opt.step=Parm0.map(function(p){return p/100}); + Opt.step=Opt.step.map(function(si){if(si==0){return 1}else{ return si}}); // convert null steps into 1's + }; + if(typeof(Opt.display)=='undefined'){Opt.display=true}; + if(!Opt.objFun){Opt.objFun=function(y,yp){return y.map(function(yi,i){return Math.pow((yi-yp[i]),2)}).reduce(function(a,b){return a+b})}} //SSD + + var cloneVector=function(V){return V.map(function(v){return v})}; + var ya,y0,yb,fP0,fP1; + var P0=cloneVector(Parm0),P1=cloneVector(Parm0); + var n = P0.length; + var step=Opt.step; + var funParm=function(P){return Opt.objFun(y,fun(x,P))}//function (of Parameters) to minimize + // silly multi-univariate screening + for(var i=0;i(Opt.maxIter-10)){console.log(i+1,funParm(P0),P0)}} + } + if (!!document.getElementById('plot')){ // if there is then use it + fminsearch.plot(x,y,fun(x,P0),P0); + } + return P0 +}; + +fminsearch.load=function(src){ // script loading + // example: fminsearch.load('http://localhost:8888/jmat/jmat.js') + var s = document.createElement('script'); + s.src = src; + document.head.appendChild(s); + s.parentElement.removeChild(s); +}; + +fminsearch.plot=function(x,y,yp,Parms,id){ // ploting results using + // defaults + var titulo='Model fitting'; + if(!!Parms){titulo='Model parameters: '+Parms}; + if(!id){var id='plot'} + // create Array in Google's format + var data = new google.visualization.DataTable(); + data.addColumn('number', 'X'); + data.addColumn('number', 'Observed'); + data.addColumn('number', 'Model fit'); + var n = x.length; + for (var i=0;i + +

Fun With Tables

+ + +
+
+ +
+
+ +
+ + + + + + + \ No newline at end of file diff --git a/funTable.js b/funTable.js new file mode 100644 index 0000000..5e3c39b --- /dev/null +++ b/funTable.js @@ -0,0 +1,50 @@ +console.log('fun with tables (funTable) loaded'); + +funTable={ + loadFiles:function(files,readAs,callback){ + // + if(!readAs){readAs='readAsDataURL'} // default is to read as dataURL + for(var i=0;i - - - - + + + + + + + + JMAT + diff --git a/jmat.js b/jmat.js index c47464f..84551c8 100644 --- a/jmat.js +++ b/jmat.js @@ -1,4 +1,1427 @@ -// jmat -// commit from cloud9 +//- JavaScript source code -console.log('jmat :-)') \ No newline at end of file +//- jmat.js ~~ +// +// This library's principal author is Jonas Almeida. I have re-written large +// chunks of it with the goal of allowing it to pass JSLint :-) +// +// ~~ SRW, 08 Oct 2012 + +(function () { + 'use strict'; + + // Pragmas + + /*jslint browser: true, devel: true, indent: 4, maxlen: 80 */ + + // Declarations + + var abs, array2mat, array2str, arrayfun, bin2dec, cat, catArray, cEl, + clone, clone2, cloneArray, cloneVector, colon, dimfun, ones, parse, + stringify, zeros; + + // Definitions + + abs = function (x) { + // absolute value + if (Array.isArray(x)) { + return x.map(function (xi) { + return jmat.abs(xi); + }); + } + return Math.abs(x); + }; + + array2mat = function (x) { + // to handle indexed arrays by converting them into two separate + // numerically indexed arrays + var i, j, y1, y2; + j = 0; + y1 = []; + y2 = []; + for (i in x) { + y1[j] = i; + y2[j] = x[i]; + j += 1; + } + return [y1, y2]; + }; + + array2str = function (x, sp) { + // convert array into a sp separated + if (!sp) { + sp = '\n'; + } + var i, y; + y = x[0]; + for (i = 1; i < x.length; i += 1) { + y += sp + x[i]; + } + return y; + }; + + arrayfun = function (x, fun, i) { + // apply function to each element of an array + if (Array.isArray(x)) { + return x.map(function (xi, i) { + return jmat.arrayfun(xi, fun, i); + }); + } + return fun(x, i); + }; + + bin2dec = function (x) { + var n = x.length; + return x.split('').map(function (xi, i) { + return xi * Math.pow(2, n - i - 1); + }).reduce(function (a, b) { + return a + b; + }); + }; + + cat = function (x, y) { + // cat will work for matrices and objects + x = stringify(x); + y = stringify(y); + return parse(x.slice(0, x.length - 1) + ',' + y.slice(1, y.length)); + }; + + catArray = function (A) { + // optimized for conCATenation of an array of numerically indexed arrays + // this function was developed to adress memory issues of dealing with + // large arrays, not performance + var Ai, Astr, i; + Ai = ''; + Astr = '['; + for (i = 0; i < A.length; i += 1) { + Ai = JSON.stringify(A[i]); + Astr += Ai.slice(1, Ai.length - 1) + ','; + } + return JSON.parse(Astr.slice(0, Astr.length - 1) + ']'); + }; + + cEl = function (x, id) { + x = document.createElement(x); + if (id) { + x.id = id; + } + return x; + }; + + clone = function (x) { + // clone object without functional elements + return JSON.parse(JSON.stringify(x)); + }; + + clone2 = function (x) { + // clone object that may have functional elements + return parse(stringify(x)); + }; + + cloneArray = function (A) { + if (Array.isArray(A)) { + return A.map(function (x) { + return jmat.cloneArray(x); + }); + } + return A; + }; + + cloneVector = function (V) { + // fastar than cloneArray if your array only has one dimension + return V.map(function (v) { + return v; + }); + }; + + colon = function (x) { + // equivalent to x(:) + var y = []; // to have it in the scope + arrayfun(x, function (x) { + y[y.length] = x; + }); + return y; + }; + + dimfun = function () { + // first argument is the function, subsequent arguments specify dimensions + // + // @Jonas: I rewrote this one to work with ES5 Strict Mode ... + // + var args, fun, i, x, x0, z; + args = Array.prototype.slice.call(arguments); + if (args.length === 0) { + args = [ + function () { + return 0; + } + ]; + } + fun = args[0]; + if (args.length > 1) { + x = []; + if ((typeof args[1]) !== 'number') { + for (i = 0; i < args[1].length; i += 1) { + x[i] = args[1][i]; + } + } else { + // note first argument is always fun + for (i = 1; i < args.length; i += 1) { + x[i - 1] = args[i]; + } + } + z = []; + if (x.length < 2) { + for (i = 0; i < x[0]; i += 1) { + z[i] = fun(i); // fun has access to array index + } + } else { + x0 = x[0]; + x = x.slice(1); + for (i = 0; i < x0; i += 1) { + z[i] = dimfun(fun, x); + } + } + } else { + z = fun(); + } + return z; + }; + + ones = function () { + return dimfun(function () { + return 1; + }, arguments); + }; + + parse = function (x) { + // x is a stringified Object + // + // @Jonas: This function probably won't work in ES5 Strict Mode, but it + // _might_ work if you use `JSON.parse` in the same way that you used + // `JSON.stringify` inside your own `stringify` function. + // + /*jslint evil: true */ + eval('var res = ' + x); + return res; + }; + + stringify = function (x) { + // extends JSON.stringify to work with both values and functions + var i, v, y; + y = (typeof x); + switch (y) { + case 'function': + y = x.toString(); + break; + case 'object': + if (Array.isArray(x)) { + y = '['; + for (i = 0; i < x.length; i += 1) { + y += stringify(x[i]) + ','; + } + y = y.slice(0, y.length - 1) + ']'; + } else { + y = '{'; + for (v in x) { + y += v + ':' + stringify(x[v]) + ','; + } + y = y.slice(0, y.length - 1) + '}'; + } + break; + case 'string': + y = JSON.stringify(x); + break; + case 'number': + y = JSON.stringify(x); + break; + default: + // (placeholder) + } + return y; + }; + + zeros = function () { + return dimfun(function () { + return 0; + }, arguments); + }; + + // Out-of-scope definitions + + window.jmat = { + abs: abs, + array2mat: array2mat, + array2str: array2str, + arrayfun: arrayfun, + bin2dec: bin2dec, + cat: cat, + catArray: catArray, + cEl: cEl, + + // ------------------------------------------------------------------------ + + class: function (x) { + if (!x.constructor) { + return null; + } + return x.constructor.name; + }, + + clone: clone, + clone2: clone2, + cloneArray: cloneArray, + cloneVector: cloneVector, + colon: colon, + + compress: function (uncompressed) { + // Source: http://rosettacode.org/wiki/LZW_compression#JavaScript + // this is new -- such that we are compressing JS objects, not strings + uncompressed = this.stringify(uncompressed); + // Build the dictionary. + var c, dictionary, dictSize, i, result, w, wc; + dictionary = {}; + dictSize = 256; + result = []; + w = ''; + // @Jonas: Should `256` in the following line be `dictSize`? + for (i = 0; i < 256; i += 1) { + dictionary[String.fromCharCode(i)] = i; + } + for (i = 0; i < uncompressed.length; i += 1) { + c = uncompressed.charAt(i); + wc = w + c; + if (dictionary[wc]) { + w = wc; + } else { + result.push(dictionary[w]); + // Add wc to the dictionary. + dictionary[wc] = dictSize++; + w = String(c); + } + } + // Output the code for w. + if (w !== "") { + result.push(dictionary[w]); + } + return result; + }, + +decompress: function (compressed) { + "use strict"; + // Build the dictionary. + var i, + dictionary = [], + w, + result, + k, + entry = "", + dictSize = 256; + for (i = 0; i < 256; i += 1) { + dictionary[i] = String.fromCharCode(i); + } + + w = String.fromCharCode(compressed[0]); + result = w; + for (i = 1; i < compressed.length; i += 1) { + k = compressed[i]; + if (dictionary[k]) { + entry = dictionary[k]; + } else { + if (k === dictSize) { + entry = w + w.charAt(0); + } else { + return null; + } + } + + result += entry; + + // Add w+entry[0] to the dictionary. + dictionary[dictSize++] = w + entry.charAt(0); + + w = entry; + } + return this.parse(result); + }, + +colormap:function(c){ + if(!c){c='default'} + switch(c){ + case 'default': + c=[[0,0,0.5625],[0,0,0.625],[0,0,0.6875],[0,0,0.75],[0,0,0.8125],[0,0,0.875],[0,0,0.9375],[0,0,1],[0,0.0625,1],[0,0.125,1],[0,0.1875,1],[0,0.25,1],[0,0.3125,1],[0,0.375,1],[0,0.4375,1],[0,0.5,1],[0,0.5625,1],[0,0.625,1],[0,0.6875,1],[0,0.75,1],[0,0.8125,1],[0,0.875,1],[0,0.9375,1],[0,1,1],[0.0625,1,0.9375],[0.125,1,0.875],[0.1875,1,0.8125],[0.25,1,0.75],[0.3125,1,0.6875],[0.375,1,0.625],[0.4375,1,0.5625],[0.5,1,0.5],[0.5625,1,0.4375],[0.625,1,0.375],[0.6875,1,0.3125],[0.75,1,0.25],[0.8125,1,0.1875],[0.875,1,0.125],[0.9375,1,0.0625],[1,1,0],[1,0.9375,0],[1,0.875,0],[1,0.8125,0],[1,0.75,0],[1,0.6875,0],[1,0.625,0],[1,0.5625,0],[1,0.5,0],[1,0.4375,0],[1,0.375,0],[1,0.3125,0],[1,0.25,0],[1,0.1875,0],[1,0.125,0],[1,0.0625,0],[1,0,0],[0.9375,0,0],[0.875,0,0],[0.8125,0,0],[0.75,0,0],[0.6875,0,0],[0.625,0,0],[0.5625,0,0],[0.5,0,0]]; + break; + default: + c = 'not found'; + } + return c +}, + +d3:{ + figure:function(id,type){ // create figure by appending d3's svg element to DOM element with specified id + if (typeof(id)==='undefined'){ + var fig = d3.select("body").append("div"); + fig.id = jmat.uid('fig'); + } + else{ + if(jmat.gId(id)!=null){var fig = d3.select('#'+id);} // if it exists + else {var fig = this.figure();fig[0][0].id = id} // otherwise create it + } + + if (typeof(type)==='string'){ + fig.attr('class',type); // possibilities: "chart", + } + this.gcf=fig; + return fig; + }, + +}, + +data2imData:function(data){ // the reverse of im2data, data is a matlabish set of 4 2d matrices, with the r, g, b and alpha values + var n=data.length, m=data[0].length; + //var imData = {width:m, height:n, data:[]}; + var imData = document.createElement('canvas').getContext('2d').createImageData(m,n); + for (var i=0;i=0;i=i-1){ + m=Math.pow(2,i); + if(x>=m){b=b+'1';x=x-m} + else{b=b+'0'} + }; + return b +}, + +disp:function(x){ // by default displays both in the console and in document.body + console.log(x); + document.body.innerHTML+='
'+x+''; +}, + +dotFun:function(A,B,fun){ // dot matrix function + 4; +}, + + dimfun: dimfun, + +edge:function(M){//find edge in bidimensional binary matrix such as what is produced by im2bw + var n = M.length, m = M[0].length; + var E=M.map(function(x,i){return x.map(function(y,j){ + if((i>0)&&(i0)&&(j0){ // extract this feature + var C=[1,0,0]; // always use yellow + //jmat.plot(cvTop,m[1][1],m[1][0],'s',{Color:[1,1,0],MarkerSize:30}); + var extractSeg = function(x,y,S){ // bw is passed in the scope of extractSegs + if(typeof(S)=='undefined'){var S=[]} // collect feature's positions + S[S.length]=[x,y];bw[x][y]=0; + // check which neighbors are >0 and take them out too + var xi,yi; + if(x>0){xi=x-1;yi=y;if(bw[xi][yi]>0){S=extractSeg(xi,yi,S)}} + if(x0){S=extractSeg(xi,yi,S)}} + if(y>0){xi=x;yi=y-1;if(bw[xi][yi]>0){S=extractSeg(xi,yi,S)}} + if(y0){S=extractSeg(xi,yi,S)}} + return S; + } + segFeatures[segFeatures.length]=extractSeg(m[1][0],m[1][1]);//extraction starts with coordiantes ofmaximum value + m = jmat.max2(bw); + } + return segFeatures.map(function(si){return jmat.transpose(si)}) +}, + + extractSegs2: function (bw) { + // This function was written by Sean Wilkinson as a variation on a theme + // of segmentation extraction from binary matrices. It returns a matrix + // whose elements' entries represent membership in a numbered partition. + // I have actually enclosed my entire "count_nuclei.js" here as a single + // function to be optimized and rewritten at some point in the future to + // take advantage of functionality that 'jmat' already provides :-) + var col, cols, isSpecial, neighborhood, partition, row, rows, + traced_image; + cols = bw[0].length; + isSpecial = function (pixel) { + // This function needs documentation. + return (pixel === 1); + }; + neighborhood = function (row, col) { + // This function needs documentation. + var ball, flag, i, temp; + ball = []; + temp = [ + [row + 1, col + 0], //- North + [row + 1, col + 1], //- North-East + [row + 0, col + 1], //- East + [row - 1, col + 1], //- South-East + [row - 1, col + 0], //- South + [row - 1, col - 1], //- South-West + [row + 0, col - 1], //- West + [row + 1, col - 1] //- North-West + ]; + for (i = 0; i < 8; i += 1) { + flag = ((0 <= temp[i][0]) && + (temp[i][0] < rows) && + (0 <= temp[i][1]) && + (temp[i][1] < cols)); + if (flag === true) { + ball.push(temp[i]); + } + } + ball.push(ball[0]); + return ball; + }; + partition = 0; + rows = bw.length; + // First, preallocate a two-dimensional array with null values ... + traced_image = new Array(rows); + for (row = 0; row < rows; row += 1) { + traced_image[row] = new Array(cols); + for (col = 0; col < cols; col += 1) { + traced_image[row][col] = null; + } + } + // Then, start hunting for "black" pixels ... + for (row = 0; row < rows; row += 1) { + for (col = 0; col < cols; col += 1) { + if (traced_image[row][col] === null) { + if (isSpecial(bw[row][col])) { + partition += 1; + traced_image[row][col] = partition; + (function cover(ball) { + // This function needs documentation. + var col, i, row; + for (i = 0; i < ball.length; i += 1) { + row = ball[i][0]; + col = ball[i][1]; + if (traced_image[row][col] === null) { + if (isSpecial(bw[row][col])) { + traced_image[row][col] = partition; + cover(neighborhood(row, col)); + } else { + traced_image[row][col] = 0; + } + } + } + return; + }(neighborhood(row, col))); + } else { + traced_image[row][col] = 0; + } + } + } + } + return traced_image; + }, + + fieldnames: function (x) { + var f, i, y; + i = 0; + y = []; + for (f in x) { + y[i] = f; + i += 1; + } + return y; + }, + +find:function(x,patt,modifier){ // find wich elements of an array match a pattern + if(!modifier){modifier='gi'}// default is global and case insensitive + var y = []; + if(Array.isArray(patt)){patt='('+patt.join(')|(')+')'} // allows multiple patterns + patt = new RegExp(patt,modifier); + var M + for(var i in x){ + M=x[i].match(patt); + if(!!M){y.push(i)} + } + return y +}, + +fminsearch:function(fun,Parm0,x,y,Opt){// fun = function(x,Parm) + // example + // + // x = [32,37,42,47,52,57,62,67,72,77,82,87,92] + // y=[749,1525,1947,2201,2380,2537,2671,2758,2803,2943,3007,2979,2992] + // fun = function(x,P){return x.map(function(xi){return (P[0]+P[1]*(1-Math.exp(-P[2]*(xi-P[3]))))})} + // Parms=jmat.fminsearch(fun,[100,3000,1,30],x,y) + // + // Opt is an object will all other parameters, from the objective function (cost function), to the + // number of iterations, initial step vector and the display switch, for example + // Parms=jmat.fminsearch(fun,[100,3000,1,30],x,y,{maxIter:5000,display:false}) + + if(!Opt){Opt={}}; + if(!Opt.maxIter){Opt.maxIter=1000}; + if(!Opt.step){// initial step is 1/100 of initial value (remember not to use zero in Parm0) + Opt.step=Parm0.map(function(p){return p/100}); + Opt.step=Opt.step.map(function(si){if(si==0){return 1}else{ return si}}); // convert null steps into 1's + }; + if(typeof(Opt.display)=='undefined'){Opt.display=true}; + if(!Opt.objFun){Opt.objFun=function(y,yp){return jmat.sum(y.map(function(yi,i){return Math.pow((yi-yp[i]),2)}))}} + + var ya,y0,yb,fP0,fP1; + var P0=jmat.cloneVector(Parm0),P1=jmat.cloneVector(Parm0); + var n = P0.length; + var step=Opt.step; + var funParm=function(P){return Opt.objFun(y,fun(x,P))}//function (of Parameters) to minimize + // silly multi-univariate screening + for(var i=0;i(Opt.maxIter-10)){console.log(i+1,funParm(P0),P0)}} + } + return P0 +}, + + +get:function(key,callback,url){ // get content at url or key + if (!callback){callback=function(x){console.log(x)}} + if (!url){url=this.webrwUrl}; + var uid = this.uid(); + if(!this.get.jobs){this.get.jobs=[]} + this.get.jobs[uid]={'fun':callback}; + var url=url+'?get='+key+'&callback=jmat.get.jobs.'+uid+'.fun'; + var s=document.createElement('script'); + s.id = uid;s.src=url; + document.body.appendChild(s); + setTimeout('document.body.removeChild(document.getElementById("'+uid+'"));delete jmat.get.jobs.'+uid+';',10000); // is the waiting still need ? script onload would be another possibility to delete it + return uid; +}, + + gId:function(x){ // x is the id of an existing DOM element + // return null if neither id nor class are found + // so constructs like !jmat.gId(someID) can be used + //var y=document.getElementById(x); + //if(!y){ + // var z=document.getElementsByClassName(x); + // if(z.length>0){return z} + // else{return y} + //} + //else{return y} + return document.getElementById(x) + }, + +im1to255:function(x){// converts {0-1} matrix into an im data matrix + 4 +}, + +imread:function(cv){ // reads image from context into matrix + // find out what type of input + if(typeof(cv)=='string'){ // cv is the id of a canvas element + cv=jmat.gId(cv) + } + var ct=cv.getContext('2d'), n=cv.width, m=cv.height; + var imData=ct.getImageData(0,0,n,m); // pixel values will be stored in imData.data + return this.imData2data(imData) +}, + +imhalve:function(dt0,PSmax){ // poor man's version of imresize, it halves an image size by averaging two rows/columns + var s = jmat.size(dt0); + if(!PSmax){PSmax = jmat.prod(s.slice(0,2))-1} // if maximum size not defined then just have it once + if(jmat.prod(s.slice(0,2))>PSmax){ + if(jmat.length(s)!==3){throw('this should be an image value matrix, size n x m x 4')} + if(s[2]!==4){throw('this should be an image value matrix, size n x m x 4')} + s = jmat.arrayfun(s,function(x){return Math.floor(x/2)}); // half size, with floored integers + s[2]=4; // rgba + var dt = jmat.zeros(s[0],s[1],s[2]); + dt=dt.map(function(x,i){ + return x.map(function(y,j){ + return y.map(function(z,k){ + return (dt0[i*2][j*2][k]+dt0[i*2+1][j*2+1][k]+dt0[i*2][j*2+1][k])/3; + }) + }) + }); + } + else{var dt = dt0}; + // if maximum pixel size was set and was exceeded keep halving + if(jmat.prod(jmat.size(dt).slice(0,2))>PSmax){dt = jmat.imhalve(dt,PSmax)} + return dt +}, + +imwrite:function(cv,im,dx,dy){ + if(!dy){dx=0;dy=0} // default location + if(typeof(cv)=='string'){cv=jmat.gId(cv)} //cv can also be the id of a canvas element + if(!im.data){im=jmat.data2imData(im)} // such that im can also be the matrix created by imread + var ct = cv.getContext('2d'); + ct.putImageData(im,dx,dy); + return ct; +}, + +image:function(cv,im,dx,dy){ // for consistency + return this.imwrite(cv,im,dx,dy); +}, + +imagesc:function(cv,dt,cm,fun,M){ // scales values to use full range of values. cv is the canvas, dt the data, and cm the colormap + if(!cm){cm=jmat.colormap()} + if(!fun){fun=function(){return 1}}; // opaque function + cm = jmat.transpose(cm); // to get one vector per channel + var n = cm[0].length-1; // should be 64-1=63 + var I = jmat.dimfun(function(i){return i/(n)},n+1); // 64 numbers evenly spaced between 0 and 1 + if(!M){M = jmat.max(jmat.max(dt))}; + if(typeof(fun)=='string'){eval('fun='+fun)} // allow eval fun with transparencies + dt = jmat.arrayfun(dt,function(x){return [jmat.interp1(I,cm[0],[x/M])[0],jmat.interp1(I,cm[1],[x/M])[0],jmat.interp1(I,cm[2],[x/M])[0],fun(x)]}); + dt = jmat.arrayfun(dt,function(x){return Math.round(255*x)}); + if(!!cv){jmat.imwrite(cv,dt)}; + return dt +}, + +imagebw:function(cv,dt,C0,C1){ // imagesc for binary matrices + if(!C0){C0=[0,0,0,0]} + if(!C1){C1=[255,255,255,255]} + var dt01 = jmat.arrayfun(dt,function(x){if(x==1){return C1}else{return C0}}) + if(!!cv){jmat.imwrite(cv,dt01)}; + return dt01; +}, + +imData2data:function(imData){ // imData is the data structure returned by canvas.getContext('2d').getImageData(0,0,n,m) + var m=imData.width, n=imData.height, data=[]; + for (var i=0;i=thr){return 1} + else{return 0} + } + ) +}, + +interp1:function(X,Y,XI){ // linear interpolation, remember X is supposed to be sorted + var n = X.length; + var YI = XI.map(function(XIi){ + var i=jmat.sum(X.map(function(Xi){if (Xi1){jmat.load(urls[0],function(){jmat.loadScripts(urls.slice(1))})} // recursion + else {jmat.load(urls[0],cb,er)} +}, + +loadFiles:function(files,readAs,callback){ + // //<-- example of button for reading text files + if(!readAs){readAs='readAsDataURL'} // default is to read as dataURL + for(var i=0;i1){jmat.load} + if(V.length>0){ + if(V.length>1){jmat.loadVar(V[0],function(){jmat.loadVar(V.slice(1),cb,er,cbId)},er,cbId)} + else{ // V.length=1 + jmat.loadVar(V[0],jmat.loadVarCallBack[cbId],er); + } + } + } + else{ + switch(V){ + case 'Q': + url = 'https://qmachine.org/q.js';break; + case 'CoffeeScript': + url = 'https://raw.github.com/jashkenas/coffee-script/master/extras/coffee-script.js';break; + case 'jQuery': + url='jquery-1.8.2.min.js';break; + default : + throw('No library was found to assemble "'+V+'"'); + } + jmat.load(url,cb,er); + console.log('variable "'+V+'"'+' loaded from '+url); + } + //return true; +}, + +lookup:function(tbl,col_in,val_in,col_out){// lookup in table tbl, + // for value in column col_out where the column col_in has the value val_in + var val_out={};// return results as a table + // Find Columns + var col_in_i=this.find(tbl.columns,col_in); + if(col_in_i.length==0){throw('input column not found')} + // if output columns not specified use the same as the input columns + if(!col_out){col_out=col_in;var col_out_i=col_in_i} + else{var col_out_i=this.find(tbl.columns,col_out)} + // Find which rows have those values + var rows = this.transpose(tbl.rows) , r=[] , Ind=[]; + for(var c in col_in_i){ + r=this.find(rows[col_in_i[c]],val_in); + if(r.length>0){for (var i in r){Ind.push(r[i])}} + } + Ind = this.unique(Ind); + val_out.columns=col_out_i.map(function(i){return tbl.columns[i]}); + val_out.rows=this.zeros(Ind.length,col_out_i.length); + for(var i=0;ib){return a}else{return b}})}; + //return x.reduce(function(a,b){if(a>b){return a}else{return b}}) +}, + +max2:function(x){ // returns maximum value of array and its index, i.e. [max,i] + if(Array.isArray(x[0])){ // coded only up to 2 dimensions + var xx = jmat.transpose(x.map(function(xi){return jmat.max2(xi)})) + var y = jmat.max2(xx[0]); + return [y[0],[y[1],xx[1][y[1]]]]; + } + else{return x.map(function(xi,i){return [xi,i]}).reduce(function(a,b){if(a[0]>b[0]){return a}else{return b}})}; + //return x.map(function(xi,i){return [xi,i]}).reduce(function(a,b){if(a[0]>b[0]){return a}else{return b}}) +}, + +min:function(x){ //return maximum value of array + return x.reduce(function(a,b){if(a'} + else{if(y[j].error){ // if error + y[j].error=false; + //y[j]=jmat.qmachine.submit(y[j].more,fun,box,step); + console.log('Mapping error at #'+i+':',y[i]); + doneStr+='*'; // "*" indicates error + } + else{doneStr+='-'} // not done yet + } + } + //console.log('countMap:',jmat.sum(done)); + console.log('M'+i+'('+doneStr+')'); + if(jmat.sum(done)==n){clearInterval(t)}; + },step); + return y; + + }, + reduce:function(x,fun,box,step){ + if(!step){step=jmat.qmachine.step}; // control default step at jmat.qmachine.step + // check that the array is of Avar elements + if(x[0].constructor.name!=="AVar"){ + x=x.map(function(xi){return Q.avar({val:xi,box:box,done:true})}) + } + var n = x.length , doneStr = ''; + //x.map(function(xi){xi.reduceStarted=false;return false}); // prepare reduce parm + //var y = Q.avar({val:x , box:box , done:false}); // results wil be placed here + var r = x.map(function(xi){return {}}); // keep flags for reduction process here + var i = 0, toReduce=[], t = setInterval(function(){ // timer + i+=1; + toReduce=[]; // reset each time + for(var j=0;j'}; // being reduced as we speak + if(j==n-1){doneStr+=':'}; + + } + for(var j=r.length;j<(2*n-1);j++){doneStr+=' '}; 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