Merge pull request #15 from foretold-app/improvements/1102
Improvements/1102
This commit is contained in:
commit
7398877e55
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@ -45,18 +45,20 @@ module FieldString = {
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module FieldNumber = {
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[@react.component]
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let make = (~field, ~label) => {
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let make = (~field, ~label, ~min=0) => {
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<Form.Field
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field
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render={({handleChange, error, value, validate}) =>
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<Antd.Form.Item label={label |> E.ste}>
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<Antd.InputNumber
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value
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onChange={e => {
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e |> handleChange;
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();
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}}
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onChange=handleChange
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min
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onBlur={_ => validate()}
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parser={str => {
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let a = str |> Js.Float.fromString |> int_of_float;
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a < min ? min : a;
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}}
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/>
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</Antd.Form.Item>
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}
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@ -66,19 +68,22 @@ module FieldNumber = {
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module FieldFloat = {
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[@react.component]
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let make = (~field, ~label, ~className=Css.style([])) => {
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let make =
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(~field, ~label, ~className=Css.style([]), ~min=0., ~precision=2) => {
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<Form.Field
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field
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render={({handleChange, error, value, validate}) =>
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<Antd.Form.Item label={label |> E.ste}>
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<Antd.InputFloat
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value
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onChange={e => {
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e |> handleChange;
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();
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}}
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precision
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onChange=handleChange
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onBlur={_ => validate()}
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className
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parser={str => {
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let a = str |> Js.Float.fromString;
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Js.Float.isNaN(a) ? min : a;
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}}
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/>
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</Antd.Form.Item>
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}
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@ -440,16 +445,25 @@ let make = () => {
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</Row>
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<Row _type=`flex className=Styles.rows>
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<Col span=4>
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<FieldNumber field=FormConfig.SampleCount label="Sample Count" />
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<FieldNumber
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field=FormConfig.SampleCount
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label="Sample Count"
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min=100
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/>
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</Col>
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<Col span=4>
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<FieldNumber
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field=FormConfig.OutputXYPoints
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label="Output XY-points"
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min=100
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/>
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</Col>
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<Col span=4>
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<FieldNumber field=FormConfig.TruncateTo label="Truncate To" />
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<FieldNumber
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field=FormConfig.TruncateTo
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label="Truncate To"
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min=10
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/>
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</Col>
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</Row>
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<Antd.Button
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@ -34,11 +34,15 @@ module Styles = {
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module DemoDist = {
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[@react.component]
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let make = (~guesstimatorString: string) => {
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let (ys, xs) = DistEditor.getPdfFromUserInput(guesstimatorString);
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let (ys, xs, isEmpty) =
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DistEditor.getPdfFromUserInput(guesstimatorString);
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let continuous: DistTypes.xyShape = {xs, ys};
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<Antd.Card title={"Distribution" |> E.ste}>
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<div className=Styles.spacer />
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<DistributionPlot continuous />
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{isEmpty
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? "Nothing to show. Try to change the distribution description."
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|> E.ste
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: <DistributionPlot continuous />}
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</Antd.Card>;
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};
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};
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@ -68,14 +68,18 @@ export class CdfChartD3 {
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* @returns {CdfChartD3}
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*/
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data(data) {
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const continuousXs = _.get(data, 'continuous.xs', []);
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const continuousYs = _.get(data, 'continuous.ys', []);
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const discreteXs = _.get(data, 'discrete.xs', []);
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const discreteYs = _.get(data, 'discrete.ys', []);
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this.attrs.data = data;
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this.attrs.data.continuous = data.continuous || {
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xs: [],
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ys: [],
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this.attrs.data.continuous = {
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xs: continuousXs,
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ys: continuousYs,
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};
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this.attrs.data.discrete = data.discrete || {
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xs: [],
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ys: [],
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this.attrs.data.discrete = {
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xs: discreteXs,
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ys: discreteYs,
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};
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return this;
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}
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@ -1,3 +1,3 @@
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[@bs.module "./main.js"]
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external getPdfFromUserInput: string => (array(float), array(float)) =
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external getPdfFromUserInput: string => (array(float), array(float), bool) =
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"get_pdf_from_user_input";
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@ -1,11 +1,14 @@
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// This module defines an abstract BinnedDistribution class, which
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// should be implemented for each distribution. You need to decide
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// how to bin the distribution (use _adabin unless there's a nicer
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// way for your distr) and how to choose the distribution's support.
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const _math = require("mathjs");
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const math = _math.create(_math.all);
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const jStat = require("jstat");
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/**
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* This module defines an abstract BinnedDistribution class, which
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* should be implemented for each distribution. You need to decide
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* how to bin the distribution (use _adabin unless there's a nicer
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* way for your distr) and how to choose the distribution's support.
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*/
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math.import({
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normal: jStat.normal,
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beta: jStat.beta,
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@ -14,6 +17,9 @@ math.import({
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});
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class BaseDistributionBinned {
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/**
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* @param args
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*/
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constructor(args) {
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this._set_props();
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this.max_bin_size = 0.5;
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@ -30,11 +36,18 @@ class BaseDistributionBinned {
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[this.pdf_vals, this.divider_pts] = this.bin();
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}
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/**
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* this is hacky but class properties aren't always supported
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* @private
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*/
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_set_props() {
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// this is hacky but class properties aren't always supported
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throw new Error("NotImplementedError");
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}
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/**
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* @returns {(number[]|[*])[]}
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* @private
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*/
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_adabin() {
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let point = this.start_point;
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let vals = [this.pdf_func(point)];
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@ -78,6 +91,10 @@ class BaseDistributionBinned {
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throw new Error("NotImplementedError");
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}
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/**
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* @param args
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* @returns {(any|(function(*=): *))[]}
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*/
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get_params_and_pdf_func(args) {
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let args_str = args.toString() + ")";
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let substr = this.name + ".pdf(x, " + args_str;
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@ -95,11 +112,17 @@ class BaseDistributionBinned {
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}
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class NormalDistributionBinned extends BaseDistributionBinned {
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/**
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* @private
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*/
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_set_props() {
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this.name = "normal";
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this.param_names = ["mean", "std"];
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}
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/**
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* @returns {(number|*)[]}
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*/
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get_bounds() {
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return [
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this.params.mean - 4 * this.params.std,
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@ -107,22 +130,34 @@ class NormalDistributionBinned extends BaseDistributionBinned {
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];
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}
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/**
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* @returns {[[*], [*]]}
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*/
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bin() {
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return this._adabin(this.params.std);
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}
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}
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class UniformDistributionBinned extends BaseDistributionBinned {
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/**
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* @private
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*/
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_set_props() {
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this.name = "uniform";
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this.param_names = ["start_point", "end_point"];
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this.num_bins = 200;
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}
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/**
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* @returns {*[]}
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*/
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get_bounds() {
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return [this.params.start_point, this.params.end_point];
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}
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/**
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* @returns {(*[])[]}
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*/
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bin() {
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let divider_pts = evenly_spaced_grid(
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this.params.start_point,
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@ -138,6 +173,9 @@ class UniformDistributionBinned extends BaseDistributionBinned {
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}
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class LogNormalDistributionBinned extends BaseDistributionBinned {
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/**
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* @private
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*/
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_set_props() {
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this.name = "lognormal";
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this.param_names = ["normal_mean", "normal_std"];
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@ -145,6 +183,12 @@ class LogNormalDistributionBinned extends BaseDistributionBinned {
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this.n_largest_bound_sample = 10;
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}
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/**
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* @param samples
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* @param n
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* @returns {any}
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* @private
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*/
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_nth_largest(samples, n) {
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var largest_buffer = Array(n).fill(-Infinity);
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for (const sample of samples) {
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@ -159,6 +203,9 @@ class LogNormalDistributionBinned extends BaseDistributionBinned {
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return largest_buffer[n - 1];
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}
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/**
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* @returns {(*|any)[]}
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*/
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get_bounds() {
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let samples = Array(this.n_bounds_samples)
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.fill(0)
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@ -169,11 +216,20 @@ class LogNormalDistributionBinned extends BaseDistributionBinned {
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];
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}
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/**
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* @returns {[[*], [*]]}
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*/
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bin() {
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return this._adabin();
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}
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}
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/**
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* @param start
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* @param stop
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* @param numel
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* @returns {*[]}
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*/
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function evenly_spaced_grid(start, stop, numel) {
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return Array(numel)
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.fill(0)
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@ -1,30 +1,57 @@
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// The main algorithmic work is done by functions in this module.
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// It also contains the main function, taking the user's string
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// and returning pdf values and x's.
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const _math = require("mathjs");
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const bst = require("binary-search-tree");
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const distrs = require("./distribution.js").distrs;
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const parse = require("./parse.js");
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const _math = require("mathjs");
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const math = _math.create(_math.all);
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const bst = require("binary-search-tree");
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const NUM_MC_SAMPLES = 300;
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const OUTPUT_GRID_NUMEL = 300;
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/**
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* The main algorithmic work is done by functions in this module.
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* It also contains the main function, taking the user's string
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* and returning pdf values and x's.
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*/
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/**
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* @param start
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* @param stop
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* @param numel
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* @returns {*[]}
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*/
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function evenly_spaced_grid(start, stop, numel) {
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return Array(numel)
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.fill(0)
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.map((_, idx) => start + (idx / numel) * (stop - start));
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}
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/**
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* Takes an array of strings like "normal(0, 1)" and
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* returns the corresponding distribution objects
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* @param substrings
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* @returns {*}
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*/
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function get_distributions(substrings) {
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// Takes an array of strings like "normal(0, 1)" and
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// returns the corresponding distribution objects
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let names_and_args = substrings.map(parse.get_distr_name_and_args);
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let pdfs = names_and_args.map(x => new distrs[x[0]](x[1]));
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return pdfs;
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}
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/**
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* update the binary search tree with bin points of
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* deterministic_pdf transformed by tansform func
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* (transfrom func can be a stocahstic func with parameters
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* sampled from mc_distrs)
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*
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* @param transform_func
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* @param deterministic_pdf
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* @param mc_distrs
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* @param track_idx
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* @param num_mc_samples
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* @param bst_pts_and_idxs
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* @returns {(number)[]}
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*/
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function update_transformed_divider_points_bst(
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transform_func,
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deterministic_pdf,
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@ -33,10 +60,6 @@ function update_transformed_divider_points_bst(
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num_mc_samples,
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bst_pts_and_idxs
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) {
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// update the binary search tree with bin points of
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// deterministic_pdf transformed by tansform func
|
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// (transfrom func can be a stocahstic func with parameters
|
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// sampled from mc_distrs)
|
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var transformed_pts = [];
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var pdf_inner_idxs = [];
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var factors = [];
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|
@ -97,10 +120,17 @@ function update_transformed_divider_points_bst(
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return [start_pt, end_pt];
|
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}
|
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|
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/**
|
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* Take the binary search tree with transformed bin points,
|
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* 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) {
|
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// Take the binary search tree with transformed bin points,
|
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// and an array of pdf values associated with the bins,
|
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// and return a pdf over an evenly spaced grid
|
||||
var offset = output_grid[1] / 2 - output_grid[0] / 2;
|
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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) {
|
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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,
|
||||
// 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.
|
||||
try{
|
||||
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 = [];
|
||||
|
|
|
@ -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 = "";
|
||||
|
|
Loading…
Reference in New Issue
Block a user