Normal dist block

.eslintignore

@@ -2,4 +2,5 @@ bin/
 node_modules/
 .cache/
 dist/
-static/scripts/jszip.js
+static/scripts/jszip.js
+static/scripts/gaussian.js

package.json

@@ -14,8 +14,8 @@
     "d3": "^7.8.5",
     "jquery": "^3.7.0",
     "js-beautify": "^1.14.9",
-    "prismjs": "^1.29.0",
-    "js-cookie": "^3.0.5"
+    "js-cookie": "^3.0.5",
+    "prismjs": "^1.29.0"
   },
   "devDependencies": {
     "babel-eslint": "^10.1.0",

static/blockDefinition/normalBlocks.js

@@ -522,6 +522,27 @@ export const blockDefinitions = [
     tooltip: "Mutate given individual bitwise using given probability.",
     helpUrl: "",
   },
+  {
+    type: "sample_normal_positive",
+    message0: "positive sample from normal distribution: mean %1, variance %2",
+    args0: [
+      {
+        type: "input_value",
+        name: "mean",
+        check: "Number",
+      },
+      {
+        type: "input_value",
+        name: "variance",
+        check: "Number",
+      },
+    ],
+    inputsInline: true,
+    output: "Number",
+    style: "indiv_blocks",
+    tooltip: "take positive sample from normal distribution with mean and variance as input",
+    helpUrl: "",
+  },
   {
     type: "ea_mutate_bit",
     message0: "mutate a random bit in %1 ",

static/scripts/gaussian.js

@@ -0,0 +1,202 @@
+/*
+Copied from https://github.com/errcw/gaussian/blob/master/LICENSE
+Copyright (c) 2023 Eric Woroshow
+
+Permission is hereby granted, free of charge, to any person obtaining a copy of
+this software and associated documentation files (the "Software"), to deal in
+the Software without restriction, including without limitation the rights to
+use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies
+of the Software, and to permit persons to whom the Software is furnished to do
+so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
+*/
+/**
+ * Box-Muller implementation
+ * https://en.wikipedia.org/wiki/Box%E2%80%93Muller_transform
+ */
+
+const PRECISION = 1e9;
+const _2PI = Math.PI * 2;
+
+/**
+ *
+ * @param {number} mean
+ * @param {number} std
+ * @param randFn - an optional function that returns a float between 0 (inclusive) and 1
+ * (exclusive).  Use this if you want to pass in a random number generator other than
+ * Math.random().
+ * @returns {number}
+ */
+function generateGaussian(mean, std, randFn = null) {
+  var u1;
+  var u2;
+  if (randFn) {
+    u1 = randFn();
+    u2 = randFn();
+  } else {
+    u1 = Math.random();
+    u2 = Math.random();
+  }
+
+  var z0 = Math.sqrt(-2.0 * Math.log(u1)) * Math.cos(_2PI * u2);
+  var z1 = Math.sqrt(-2.0 * Math.log(u1)) * Math.sin(_2PI * u2);
+
+  return z0 * std + mean;
+}
+// Complementary error function
+// From Numerical Recipes in C 2e p221
+var erfc = function (x) {
+  var z = Math.abs(x);
+  var t = 1 / (1 + z / 2);
+  var r =
+    t *
+    Math.exp(
+      -z * z -
+        1.26551223 +
+        t *
+          (1.00002368 +
+            t *
+              (0.37409196 +
+                t *
+                  (0.09678418 +
+                    t *
+                      (-0.18628806 +
+                        t *
+                          (0.27886807 +
+                            t *
+                              (-1.13520398 +
+                                t *
+                                  (1.48851587 +
+                                    t * (-0.82215223 + t * 0.17087277))))))))
+    );
+  return x >= 0 ? r : 2 - r;
+};
+
+// Inverse complementary error function
+// From Numerical Recipes 3e p265
+var ierfc = function (x) {
+  if (x >= 2) {
+    return -100;
+  }
+  if (x <= 0) {
+    return 100;
+  }
+
+  var xx = x < 1 ? x : 2 - x;
+  var t = Math.sqrt(-2 * Math.log(xx / 2));
+
+  var r =
+    -0.70711 *
+    ((2.30753 + t * 0.27061) / (1 + t * (0.99229 + t * 0.04481)) - t);
+
+  for (var j = 0; j < 2; j++) {
+    var err = erfc(r) - xx;
+    r += err / (1.12837916709551257 * Math.exp(-(r * r)) - r * err);
+  }
+
+  return x < 1 ? r : -r;
+};
+
+// Models the normal distribution
+var Gaussian = function (mean, variance) {
+  if (variance <= 0) {
+    throw new Error("Variance must be > 0 (but was " + variance + ")");
+  }
+  this.mean = mean;
+  this.variance = variance;
+  this.standardDeviation = Math.sqrt(variance);
+};
+
+// Probability density function
+Gaussian.prototype.pdf = function (x) {
+  var m = this.standardDeviation * Math.sqrt(2 * Math.PI);
+  var e = Math.exp(-Math.pow(x - this.mean, 2) / (2 * this.variance));
+  return e / m;
+};
+
+// Cumulative density function
+Gaussian.prototype.cdf = function (x) {
+  return 0.5 * erfc(-(x - this.mean) / (this.standardDeviation * Math.sqrt(2)));
+};
+
+// Percent point function
+Gaussian.prototype.ppf = function (x) {
+  return this.mean - this.standardDeviation * Math.sqrt(2) * ierfc(2 * x);
+};
+
+// Product distribution of this and d (scale for constant)
+Gaussian.prototype.mul = function (d) {
+  if (typeof d === "number") {
+    return this.scale(d);
+  }
+  var precision = 1 / this.variance;
+  var dprecision = 1 / d.variance;
+  return fromPrecisionMean(
+    precision + dprecision,
+    precision * this.mean + dprecision * d.mean
+  );
+};
+
+// Quotient distribution of this and d (scale for constant)
+Gaussian.prototype.div = function (d) {
+  if (typeof d === "number") {
+    return this.scale(1 / d);
+  }
+  var precision = 1 / this.variance;
+  var dprecision = 1 / d.variance;
+  return fromPrecisionMean(
+    precision - dprecision,
+    precision * this.mean - dprecision * d.mean
+  );
+};
+
+// Addition of this and d
+Gaussian.prototype.add = function (d) {
+  return gaussian(this.mean + d.mean, this.variance + d.variance);
+};
+
+// Subtraction of this and d
+Gaussian.prototype.sub = function (d) {
+  return gaussian(this.mean - d.mean, this.variance + d.variance);
+};
+
+// Scale this by constant c
+Gaussian.prototype.scale = function (c) {
+  return gaussian(this.mean * c, this.variance * c * c);
+};
+
+/**
+ * Generate [num] random samples
+ * @param {number} num
+ * @param randFn - an optional function that returns a float between 0 (inclusive) and 1
+ * (exclusive).  Use this if you want to pass in a random number generator other than
+ * Math.random().
+ * @returns {number[]}
+ */
+Gaussian.prototype.random = function (num, randFn = null) {
+  let mean = this.mean;
+  let std = this.standardDeviation;
+  return Array(num)
+    .fill(0)
+    .map(() => {
+      return generateGaussian(mean, std, randFn);
+    });
+};
+
+var gaussian = function (mean, variance) {
+  return new Gaussian(mean, variance);
+};
+
+var fromPrecisionMean = function (precision, precisionmean) {
+  return gaussian(precisionmean / precision, 1 / precision);
+};

static/scripts/modules/blocklyHandling.js

@@ -159,6 +159,10 @@ function runCode() {
     "importScripts(('" +
     self.location +
     "').replace(/([^/]*$)/, '')+'scripts/MessageHandler.js');\n";
+  imports +=
+    "importScripts(('" +
+    self.location +
+    "').replace(/([^/]*$)/, '')+'scripts/gaussian.js');\n";
   imports += "_thread_id = null;\n";
 
   // code = imports + "function windowalert(x) {self.postMessage({output:x})};\n" + messageHandler + dateSetup + code termination//logSetup + code + logSave + termination // TODO? we don't really need it other than for abort

static/scripts/normalBlockBehaviour.js

@@ -591,6 +591,27 @@ Blockly.JavaScript["ea_mutate_bit"] = function (block) {
   return [code, Blockly.JavaScript.ORDER_NONE];
 };
 
+Blockly.JavaScript["sample_normal_positive"] = function (block) {
+  let variableMean = Blockly.JavaScript.valueToCode(
+    block,
+    "mean",
+    Blockly.JavaScript.ORDER_ATOMIC,
+  );
+  let variableVariance = Blockly.JavaScript.valueToCode(
+    block,
+    "variance",
+    Blockly.JavaScript.ORDER_ATOMIC,
+  );
+
+  let code = `(function() {
+  const distribution = gaussian(${variableMean}, ${variableVariance});
+  let sample = 0;
+  while (sample <= 0) sample = Math.round(distribution.ppf(Math.random()));
+  return sample;
+})()`;
+  return [code, Blockly.JavaScript.ORDER_NONE];
+};
+
 Blockly.JavaScript["ea_debug_all"] = function () {
   var code = 'windowalert("genome_length: " + genome_length);\n';
   code += 'windowalert("lambda: " + _CE_BB);\n';

static/workspace.html

@@ -446,6 +446,7 @@ <h3>
       <block type="ea_mutate"></block>
       <block type="ea_mutate_prob"></block>
       <block type="ea_mutate_bit"></block>
+      <block type="sample_normal_positive"></block>
     </category>
 
     <category name="Fitness measure" colour="180">