add pcp management

Makefile

@@ -51,7 +51,8 @@ reorder.v1.js: \
 	src/pca_order.js \
 	src/ca.js \
 	src/cuthill_mckee_order.js \
-	src/condition.js
+	src/condition.js \
+	src/pcp.js
 
 test: all
 	@npm test

examples/pcp/index.html

@@ -1,8 +1,12 @@
 <meta charset="UTF8">
 <script src="../../lib/d3.v3.js"></script>
 <script src="../../lib/d3.parcoords.js"></script>
+<script src="../../lib/science.v1.js"></script>
+<script src="../../lib/tiny-queue.js"></script>
+<script src="../../reorder.v1.js"></script>
 <link rel="stylesheet" type="text/css" href="../../lib/d3.parcoords.css">
 <div id="example" class="parcoords" style="width:360px;height:150px"></div>
+<div id="example2" class="parcoords" style="width:360px;height:150px"></div>
 
 <script>
 var data = [
@@ -11,11 +15,26 @@
   [2,-2,4,4,0.5,2],
   [3,-3,9,6,0.33,4],
   [4,-4,16,8,0.25,9]
-];
+],
+  dimensions = reorder.range(6),
+  axes = ['a', 'b', 'c', 'd', 'e', 'f'];
 
 var pc = d3.parcoords()("#example")
-  .data(data)
+  .data(reorder.array_to_dicts(data, axes))
   .render()
   .ticks(3)
   .createAxes();
+
+var pcp = reorder.pcp(data, axes),
+   ndata = pcp[0],
+   perm = pcp[1],
+   naxes = pcp[2];
+
+var pc2 = d3.parcoords()("#example2")
+  .data(reorder.array_to_dicts(ndata, naxes))
+  .render()
+  .ticks(3)
+  .dimensions(naxes)
+  .createAxes();
+
 </script>

reorder.v1.js

@@ -2689,4 +2689,84 @@ reorder.condition = function(matrix) {
     }
     return ret;
 };
+function array_to_dicts(data, axes) {
+    if (arguments.length < 2) 
+	axes = reorder.range(data[0].length);
+    var ret = [], row, dict, i, j;
+    for (i = 0; i < data.length; i++) {
+	row = data[i];
+	dict = {};
+	for (j = 0; j < row.length; j++) {
+	    dict[axes[j]] = row[j];
+	}
+	ret.push(dict);
+    }
+    return ret;
+}
+
+reorder.array_to_dicts = array_to_dicts;
+
+function dicts_to_array(dicts, keys) {
+    if (arguments.length < 2)
+	keys = Object.keys(dicts[0]);
+    var n = keys.length,
+	m = dicts.length,
+	array = Array(m), i, j, row;
+
+    for (i = 0; i < m; i++) {
+	row = Array(n);
+	array[i] = row;
+	for (j = 0; j < n; j++)
+	    row[j] = dicts[i][keys[j]];
+    }
+    return array;
+}
+
+reorder.dicts_to_array = dicts_to_array;
+
+function abs_matrix(x) {
+    return x.map(function(y) { return y.map(Math.abs); });
+}
+
+function pcp(data, axes) {
+    if (arguments.length < 2) 
+	axes = reorder.range(data[0].length);
+    var tdata = reorder.transpose(data),
+	pcor = reorder.correlation.pearsonMatrix(tdata),
+	abs_pcor = abs_matrix(pcor),
+	h1 = science.stats.hcluster()
+	    .linkage("complete")
+	    .distanceMatrix(abs_pcor)(tdata),
+	perm = reorder.optimal_leaf_order()
+	    .distanceMatrix(abs_pcor)(tdata),
+	naxes = reorder.permute(axes, perm);
+    tdata = reorder.permute(tdata, perm);
+
+    var i, c, sign = 1, signs = [], negs=0;
+
+    console.log('Permutation is '+perm);
+
+    for (i = 1; i < tdata.length; i++) {
+	c = pcor[perm[i-1]][perm[i]];
+	if (c < 0)
+	    sign = -sign;
+	if (sign < 0) {
+	    signs.push(-1);
+	    negs++;
+	}
+	else
+	    signs.push(1);
+    }
+    sign = (negs > (tdata.length-negs)) ? -1 : 1;
+    for (i = 0; i < (tdata.length-1); i++) {
+	if (signs[i]*sign < 0) {
+	    naxes[i] = '-'+naxes[i];
+	    tdata[i] = tdata[i].map(function(x) { return -x; });
+	}
+    }
+    var  ndata = reorder.transpose(tdata);
+    return [ndata, perm, naxes];
+}
+
+reorder.pcp = pcp;
 })(this);

src/pcp.js

@@ -0,0 +1,80 @@
+function array_to_dicts(data, axes) {
+    if (arguments.length < 2) 
+	axes = reorder.range(data[0].length);
+    var ret = [], row, dict, i, j;
+    for (i = 0; i < data.length; i++) {
+	row = data[i];
+	dict = {};
+	for (j = 0; j < row.length; j++) {
+	    dict[axes[j]] = row[j];
+	}
+	ret.push(dict);
+    }
+    return ret;
+}
+
+reorder.array_to_dicts = array_to_dicts;
+
+function dicts_to_array(dicts, keys) {
+    if (arguments.length < 2)
+	keys = Object.keys(dicts[0]);
+    var n = keys.length,
+	m = dicts.length,
+	array = Array(m), i, j, row;
+
+    for (i = 0; i < m; i++) {
+	row = Array(n);
+	array[i] = row;
+	for (j = 0; j < n; j++)
+	    row[j] = dicts[i][keys[j]];
+    }
+    return array;
+}
+
+reorder.dicts_to_array = dicts_to_array;
+
+function abs_matrix(x) {
+    return x.map(function(y) { return y.map(Math.abs); });
+}
+
+function pcp(data, axes) {
+    if (arguments.length < 2) 
+	axes = reorder.range(data[0].length);
+    var tdata = reorder.transpose(data),
+	pcor = reorder.correlation.pearsonMatrix(tdata),
+	abs_pcor = abs_matrix(pcor),
+	h1 = science.stats.hcluster()
+	    .linkage("complete")
+	    .distanceMatrix(abs_pcor)(tdata),
+	perm = reorder.optimal_leaf_order()
+	    .distanceMatrix(abs_pcor)(tdata),
+	naxes = reorder.permute(axes, perm);
+    tdata = reorder.permute(tdata, perm);
+
+    var i, c, sign = 1, signs = [], negs=0;
+
+    console.log('Permutation is '+perm);
+
+    for (i = 1; i < tdata.length; i++) {
+	c = pcor[perm[i-1]][perm[i]];
+	if (c < 0)
+	    sign = -sign;
+	if (sign < 0) {
+	    signs.push(-1);
+	    negs++;
+	}
+	else
+	    signs.push(1);
+    }
+    sign = (negs > (tdata.length-negs)) ? -1 : 1;
+    for (i = 0; i < (tdata.length-1); i++) {
+	if (signs[i]*sign < 0) {
+	    naxes[i] = '-'+naxes[i];
+	    tdata[i] = tdata[i].map(function(x) { return -x; });
+	}
+    }
+    var  ndata = reorder.transpose(tdata);
+    return [ndata, perm, naxes];
+}
+
+reorder.pcp = pcp;

test/pcp-test.js

@@ -0,0 +1,23 @@
+require("science");
+require("../reorder.v1");
+
+var vows = require("vows"),
+    assert = require("assert");
+
+var suite = vows.describe("reorder.pcp");
+
+suite.addBatch({
+    "pcp": {
+	"simple": function() {
+	    var earray = [[0, 1, 2], [3, 4, 5]],
+		dicts = reorder.array_to_dicts(earray);
+	    assert.equal(dicts.length, earray.length);
+	    var array = reorder.dicts_to_array(dicts);
+	    assert.deepEqual(earray,array);
+	}
+    }
+});
+
+suite.export(module);
+
+