Merge pull request #15 from foretold-app/improvements/1102

Improvements/1102

src/components/DistBuilder.re

@@ -45,18 +45,20 @@ module FieldString = {
 
 module FieldNumber = {
   [@react.component]
-  let make = (~field, ~label) => {
+  let make = (~field, ~label, ~min=0) => {
     <Form.Field
       field
       render={({handleChange, error, value, validate}) =>
         <Antd.Form.Item label={label |> E.ste}>
           <Antd.InputNumber
             value
-            onChange={e => {
+            onChange=handleChange
-              e |> handleChange;
+            min
-              ();
-            }}
             onBlur={_ => validate()}
+            parser={str => {
+              let a = str |> Js.Float.fromString |> int_of_float;
+              a < min ? min : a;
+            }}
           />
         </Antd.Form.Item>
       }
@@ -66,19 +68,22 @@ module FieldNumber = {
 
 module FieldFloat = {
   [@react.component]
-  let make = (~field, ~label, ~className=Css.style([])) => {
+  let make =
+      (~field, ~label, ~className=Css.style([]), ~min=0., ~precision=2) => {
     <Form.Field
       field
       render={({handleChange, error, value, validate}) =>
         <Antd.Form.Item label={label |> E.ste}>
           <Antd.InputFloat
             value
-            onChange={e => {
+            precision
-              e |> handleChange;
+            onChange=handleChange
-              ();
-            }}
             onBlur={_ => validate()}
             className
+            parser={str => {
+              let a = str |> Js.Float.fromString;
+              Js.Float.isNaN(a) ? min : a;
+            }}
           />
         </Antd.Form.Item>
       }
@@ -440,16 +445,25 @@ let make = () => {
           </Row>
           <Row _type=`flex className=Styles.rows>
             <Col span=4>
-              <FieldNumber field=FormConfig.SampleCount label="Sample Count" />
+              <FieldNumber
+                field=FormConfig.SampleCount
+                label="Sample Count"
+                min=100
+              />
             </Col>
             <Col span=4>
               <FieldNumber
                 field=FormConfig.OutputXYPoints
                 label="Output XY-points"
+                min=100
               />
             </Col>
             <Col span=4>
-              <FieldNumber field=FormConfig.TruncateTo label="Truncate To" />
+              <FieldNumber
+                field=FormConfig.TruncateTo
+                label="Truncate To"
+                min=10
+              />
             </Col>
           </Row>
           <Antd.Button

src/components/DistBuilder2.re

@@ -34,11 +34,15 @@ module Styles = {
 module DemoDist = {
   [@react.component]
   let make = (~guesstimatorString: string) => {
-    let (ys, xs) = DistEditor.getPdfFromUserInput(guesstimatorString);
+    let (ys, xs, isEmpty) =
+      DistEditor.getPdfFromUserInput(guesstimatorString);
     let continuous: DistTypes.xyShape = {xs, ys};
     <Antd.Card title={"Distribution" |> E.ste}>
       <div className=Styles.spacer />
-      <DistributionPlot continuous />
+      {isEmpty
+         ? "Nothing to show. Try to change the distribution description."
+           |> E.ste
+         : <DistributionPlot continuous />}
     </Antd.Card>;
   };
 };

src/components/charts/DistributionPlot/distPlotD3.js

@@ -68,14 +68,18 @@ export class CdfChartD3 {
    * @returns {CdfChartD3}
    */
   data(data) {
+    const continuousXs = _.get(data, 'continuous.xs', []);
+    const continuousYs = _.get(data, 'continuous.ys', []);
+    const discreteXs = _.get(data, 'discrete.xs', []);
+    const discreteYs = _.get(data, 'discrete.ys', []);
     this.attrs.data = data;
-    this.attrs.data.continuous = data.continuous || {
+    this.attrs.data.continuous = {
-      xs: [],
+      xs: continuousXs,
-      ys: [],
+      ys: continuousYs,
     };
-    this.attrs.data.discrete = data.discrete || {
+    this.attrs.data.discrete = {
-      xs: [],
+      xs: discreteXs,
-      ys: [],
+      ys: discreteYs,
     };
     return this;
   }

src/components/editor/DistEditor.re

@@ -1,3 +1,3 @@
 [@bs.module "./main.js"]
-external getPdfFromUserInput: string => (array(float), array(float)) =
+external getPdfFromUserInput: string => (array(float), array(float), bool) =
   "get_pdf_from_user_input";

src/components/editor/distribution.js

@@ -1,11 +1,14 @@
-// This module defines an abstract BinnedDistribution class, which
-// should be implemented for each distribution. You need to decide
-// how to bin the distribution (use _adabin unless there's a nicer
-// way for your distr) and how to choose the distribution's support.
 const _math = require("mathjs");
 const math = _math.create(_math.all);
 const jStat = require("jstat");
 
+/**
+ * This module defines an abstract BinnedDistribution class, which
+ * should be implemented for each distribution. You need to decide
+ * how to bin the distribution (use _adabin unless there's a nicer
+ * way for your distr) and how to choose the distribution's support.
+ */
+
 math.import({
   normal: jStat.normal,
   beta: jStat.beta,
@@ -14,6 +17,9 @@ math.import({
 });
 
 class BaseDistributionBinned {
+  /**
+   * @param args
+   */
   constructor(args) {
     this._set_props();
     this.max_bin_size = 0.5;
@@ -30,11 +36,18 @@ class BaseDistributionBinned {
     [this.pdf_vals, this.divider_pts] = this.bin();
   }
 
+  /**
+   * this is hacky but class properties aren't always supported
+   * @private
+   */
   _set_props() {
-    // this is hacky but class properties aren't always supported
     throw new Error("NotImplementedError");
   }
 
+  /**
+   * @returns {(number[]|[*])[]}
+   * @private
+   */
   _adabin() {
     let point = this.start_point;
     let vals = [this.pdf_func(point)];
@@ -78,6 +91,10 @@ class BaseDistributionBinned {
     throw new Error("NotImplementedError");
   }
 
+  /**
+   * @param args
+   * @returns {(any|(function(*=): *))[]}
+   */
   get_params_and_pdf_func(args) {
     let args_str = args.toString() + ")";
     let substr = this.name + ".pdf(x, " + args_str;
@@ -95,11 +112,17 @@ class BaseDistributionBinned {
 }
 
 class NormalDistributionBinned extends BaseDistributionBinned {
+  /**
+   * @private
+   */
   _set_props() {
     this.name = "normal";
     this.param_names = ["mean", "std"];
   }
 
+  /**
+   * @returns {(number|*)[]}
+   */
   get_bounds() {
     return [
       this.params.mean - 4 * this.params.std,
@@ -107,22 +130,34 @@ class NormalDistributionBinned extends BaseDistributionBinned {
     ];
   }
 
+  /**
+   * @returns {[[*], [*]]}
+   */
   bin() {
     return this._adabin(this.params.std);
   }
 }
 
 class UniformDistributionBinned extends BaseDistributionBinned {
+  /**
+   * @private
+   */
   _set_props() {
     this.name = "uniform";
     this.param_names = ["start_point", "end_point"];
     this.num_bins = 200;
   }
 
+  /**
+   * @returns {*[]}
+   */
   get_bounds() {
     return [this.params.start_point, this.params.end_point];
   }
 
+  /**
+   * @returns {(*[])[]}
+   */
   bin() {
     let divider_pts = evenly_spaced_grid(
       this.params.start_point,
@@ -138,6 +173,9 @@ class UniformDistributionBinned extends BaseDistributionBinned {
 }
 
 class LogNormalDistributionBinned extends BaseDistributionBinned {
+  /**
+   * @private
+   */
   _set_props() {
     this.name = "lognormal";
     this.param_names = ["normal_mean", "normal_std"];
@@ -145,6 +183,12 @@ class LogNormalDistributionBinned extends BaseDistributionBinned {
     this.n_largest_bound_sample = 10;
   }
 
+  /**
+   * @param samples
+   * @param n
+   * @returns {any}
+   * @private
+   */
   _nth_largest(samples, n) {
     var largest_buffer = Array(n).fill(-Infinity);
     for (const sample of samples) {
@@ -159,6 +203,9 @@ class LogNormalDistributionBinned extends BaseDistributionBinned {
     return largest_buffer[n - 1];
   }
 
+  /**
+   * @returns {(*|any)[]}
+   */
   get_bounds() {
     let samples = Array(this.n_bounds_samples)
       .fill(0)
@@ -169,11 +216,20 @@ class LogNormalDistributionBinned extends BaseDistributionBinned {
     ];
   }
 
+  /**
+   * @returns {[[*], [*]]}
+   */
   bin() {
     return this._adabin();
   }
 }
 
+/**
+ * @param start
+ * @param stop
+ * @param numel
+ * @returns {*[]}
+ */
 function evenly_spaced_grid(start, stop, numel) {
   return Array(numel)
     .fill(0)

src/components/editor/main.js

@@ -1,30 +1,57 @@
-// The main algorithmic work is done by functions in this module.
+const _math = require("mathjs");
-// It also contains the main function, taking the user's string
+const bst = require("binary-search-tree");
-// and returning pdf values and x's.
 
 const distrs = require("./distribution.js").distrs;
 const parse = require("./parse.js");
-const _math = require("mathjs");
 const math = _math.create(_math.all);
-const bst = require("binary-search-tree");
 
 const NUM_MC_SAMPLES = 300;
 const OUTPUT_GRID_NUMEL = 300;
 
+/**
+ * The main algorithmic work is done by functions in this module.
+ * It also contains the main function, taking the user's string
+ * and returning pdf values and x's.
+ */
+
+/**
+ * @param start
+ * @param stop
+ * @param numel
+ * @returns {*[]}
+ */
 function evenly_spaced_grid(start, stop, numel) {
   return Array(numel)
     .fill(0)
     .map((_, idx) => start + (idx / numel) * (stop - start));
 }
 
+/**
+ * Takes an array of strings like "normal(0, 1)" and
+ * returns the corresponding distribution objects
+ * @param substrings
+ * @returns {*}
+ */
 function get_distributions(substrings) {
-  // Takes an array of strings like "normal(0, 1)" and
-  // returns the corresponding distribution objects
   let names_and_args = substrings.map(parse.get_distr_name_and_args);
   let pdfs = names_and_args.map(x => new distrs[x[0]](x[1]));
   return pdfs;
 }
 
+/**
+ * update the binary search tree with bin points of
+ * deterministic_pdf transformed by tansform func
+ * (transfrom func can be a stocahstic func with parameters
+ * sampled from mc_distrs)
+ *
+ * @param transform_func
+ * @param deterministic_pdf
+ * @param mc_distrs
+ * @param track_idx
+ * @param num_mc_samples
+ * @param bst_pts_and_idxs
+ * @returns {(number)[]}
+ */
 function update_transformed_divider_points_bst(
   transform_func,
   deterministic_pdf,
@@ -33,10 +60,6 @@ function update_transformed_divider_points_bst(
   num_mc_samples,
   bst_pts_and_idxs
 ) {
-  // update the binary search tree with bin points of
-  // deterministic_pdf transformed by tansform func
-  // (transfrom func can be a stocahstic func with parameters
-  // sampled from mc_distrs)
   var transformed_pts = [];
   var pdf_inner_idxs = [];
   var factors = [];
@@ -97,10 +120,17 @@ function update_transformed_divider_points_bst(
   return [start_pt, end_pt];
 }
 
+/**
+ * Take the binary search tree with transformed bin points,
+ * and an array of pdf values associated with the bins,
+ * and return a pdf over an evenly spaced grid
+ *
+ * @param pdf_vals
+ * @param bst_pts_and_idxs
+ * @param output_grid
+ * @returns {[]}
+ */
 function get_final_pdf(pdf_vals, bst_pts_and_idxs, output_grid) {
-  // Take the binary search tree with transformed bin points,
-  // and an array of pdf values associated with the bins,
-  // and return a pdf over an evenly spaced grid
   var offset = output_grid[1] / 2 - output_grid[0] / 2;
   var active_intervals = new Map();
   var active_endpoints = new bst.AVLTree();
@@ -152,16 +182,25 @@ function get_final_pdf(pdf_vals, bst_pts_and_idxs, output_grid) {
   return final_pdf_vals;
 }
 
+/**
+ * Entrypoint. Pass user input strings to this function,
+ * get the corresponding pdf values and input points back.
+ * If the pdf requires monte carlo (it contains a between-distr function)
+ * we first determing which distr to have deterministic
+ * and which to sample from. This is decided based on which
+ * choice gives the least variance.
+ *
+ * @param user_input_string
+ * @returns {([]|*[])[]}
+ */
 function get_pdf_from_user_input(user_input_string) {
-  // Entrypoint. Pass user input strings to this function,
+  try{
-  // get the corresponding pdf values and input points back.
-  // If the pdf requires monte carlo (it contains a between-distr function)
-  // we first determing which distr to have deterministic
-  // and whih to sample from. This is decided based on which
-  // choice gives the least variance.
     let parsed = parse.parse_initial_string(user_input_string);
     let mm_args = parse.separate_mm_args(parsed.mm_args_string);
+
     const is_mm = mm_args.distrs.length > 0;
+    if (!parsed.outer_string) return [[], [], true];
+
     let tree = new bst.AVLTree();
     let possible_start_pts = [];
     let possible_end_pts = [];
@@ -170,6 +209,7 @@ function get_pdf_from_user_input(user_input_string) {
     let weights_sum = weights.reduce((a, b) => a + b);
     weights = weights.map(x => x / weights_sum);
     let n_iters = is_mm ? mm_args.distrs.length : 1;
+
     for (let i = 0; i < n_iters; ++i) {
       let distr_string = is_mm ? mm_args.distrs[i] : parsed.outer_string;
       var [deterministic_pdf, mc_distrs] = choose_pdf_func(distr_string);
@@ -186,13 +226,22 @@ function get_pdf_from_user_input(user_input_string) {
       possible_end_pts.push(end_pt);
       all_vals.push(deterministic_pdf.pdf_vals.map(x => x * weights[i]));
     }
+
     start_pt = Math.min(...possible_start_pts);
     end_pt = Math.max(...possible_end_pts);
+
     let output_grid = evenly_spaced_grid(start_pt, end_pt, OUTPUT_GRID_NUMEL);
     let final_pdf_vals = get_final_pdf(all_vals, tree, output_grid);
-  return [final_pdf_vals, output_grid];
+    return [final_pdf_vals, output_grid, false];
+  } catch (e) {
+    return [[], [], true];
+  }
 }
 
+/**
+ * @param vals
+ * @returns {number}
+ */
 function variance(vals) {
   var vari = 0;
   for (let i = 0; i < vals[0].length; ++i) {
@@ -209,14 +258,24 @@ function variance(vals) {
   return vari;
 }
 
+/**
+ * @param array
+ * @param idx
+ * @returns {*[]}
+ */
 function pluck_from_array(array, idx) {
   return [array[idx], array.slice(0, idx).concat(array.slice(idx + 1))];
 }
 
+/**
+ * If distr_string requires MC, try all possible
+ * choices for the deterministic distribution,
+ * and pick the one with the least variance.
+ *
+ * @param distr_string
+ * @returns {(*|*[])[]|*[]}
+ */
 function choose_pdf_func(distr_string) {
-  // If distr_string requires MC, try all possible
-  // choices for the deterministic distribution,
-  // and pick the one with the least variance.
   var variances = [];
   let transform_func = get_grid_transform(distr_string);
   let substrings = parse.get_distr_substrings(distr_string);
@@ -259,6 +318,10 @@ function choose_pdf_func(distr_string) {
   return [pdfs[best_idx], mc_distrs];
 }
 
+/**
+ * @param distr_string
+ * @returns {function(*): *}
+ */
 function get_grid_transform(distr_string) {
   let substrings = parse.get_distr_substrings(distr_string);
   let arg_strings = [];

src/components/editor/parse.js

@@ -1,7 +1,8 @@
-// Functions for parsing/processing user input strings are here
 const _math = require("mathjs");
 const math = _math.create(_math.all);
 
+// Functions for parsing/processing user input strings are here
+
 const DISTR_REGEXS = [
   /beta\(/g,
   /(log)?normal\(/g,
@@ -10,6 +11,11 @@ const DISTR_REGEXS = [
   /uniform\(/g
 ];
 
+/**
+ *
+ * @param user_input_string
+ * @returns {{mm_args_string: string, outer_string: string}}
+ */
 function parse_initial_string(user_input_string) {
   let outer_output_string = "";
   let mm_args_string = "";
@@ -42,6 +48,10 @@ function parse_initial_string(user_input_string) {
   };
 }
 
+/**
+ * @param mm_args_string
+ * @returns {{distrs: [], weights: string}}
+ */
 function separate_mm_args(mm_args_string) {
   if (mm_args_string.endsWith(",")) {
     mm_args_string = mm_args_string.slice(0, -1);
@@ -68,6 +78,10 @@ function separate_mm_args(mm_args_string) {
   };
 }
 
+/**
+ * @param distr_string
+ * @returns {[]}
+ */
 function get_distr_substrings(distr_string) {
   let substrings = [];
   for (let regex of DISTR_REGEXS) {
@@ -92,6 +106,10 @@ function get_distr_substrings(distr_string) {
   return substrings;
 }
 
+/**
+ * @param substr
+ * @returns {(string|*)[]}
+ */
 function get_distr_name_and_args(substr) {
   let distr_name = "";
   let args_str = "";