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This commit is contained in:
Roman Galochkin 2020-02-27 14:32:05 +03:00
parent 1684d79d9b
commit 531df57242
6 changed files with 656 additions and 8 deletions
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5
package.json
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@ -55,7 +55,10 @@
"react-dom": "16.12.0",
"reason-react": ">=0.7.0",
"reschema": "1.3.0",
"tailwindcss": "1.2.0"
"tailwindcss": "1.2.0",
"binary-search-tree": "0.2.6",
"jstat": "1.9.2",
"mathjs": "6.6.0"
},
"alias": {
"react": "./node_modules/react",

181
src/components/editor/distribution.js Normal file
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// 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");
math.import({
normal: jStat.normal,
beta: jStat.beta,
lognormal: jStat.lognormal,
uniform: jStat.uniform
});
class BaseDistributionBinned {
constructor(args) {
this._set_props();
this.max_bin_size = 0.5;
this.min_bin_size = 0;
this.increment = 0.001;
this.desired_delta = 0.01;
this.start_bin_size = 0.01;
[this.params, this.pdf_func, this.sample] = this.get_params_and_pdf_func(
args
);
[this.start_point, this.end_point] = this.get_bounds();
[this.pdf_vals, this.divider_pts] = this.bin();
}
_set_props() {
// this is hacky but class properties aren't always supported
throw new Error("NotImplementedError");
}
_adabin() {
let point = this.start_point;
let vals = [this.pdf_func(point)];
let divider_pts = [point];
let support = this.end_point - this.start_point;
let bin_size = this.start_bin_size * support;
while (point < this.end_point) {
let val = this.pdf_func(point + bin_size);
if (Math.abs(val - vals[vals.length - 1]) > this.desired_delta) {
while (
(Math.abs(val - vals[vals.length - 1]) > this.desired_delta) &
(bin_size - this.increment * support > this.min_bin_size)
) {
bin_size -= this.increment;
val = this.pdf_func(point + bin_size);
}
} else if (Math.abs(val - vals[vals.length - 1]) < this.desired_delta) {
while (
(Math.abs(val - vals[vals.length - 1]) < this.desired_delta) &
(bin_size < this.max_bin_size)
) {
bin_size += this.increment;
val = this.pdf_func(point + bin_size);
}
}
point += bin_size;
vals.push(val);
divider_pts.push(point);
}
vals = vals.map((_, idx) => vals[idx] / 2 + vals[idx + 1] / 2);
vals = vals.slice(0, -1);
return [vals, divider_pts];
}
bin() {
throw new Error("NotImplementedError");
}
get_bounds() {
throw new Error("NotImplementedError");
}
get_params_and_pdf_func(args) {
let args_str = args.toString() + ")";
let substr = this.name + ".pdf(x, " + args_str;
let compiled = math.compile(substr);
function pdf_func(x) {
return compiled.evaluate({ x: x });
}
let mc_compiled = math.compile(this.name + ".sample(" + args_str);
let kv_pairs = this.param_names.map((val, idx) => [val, args[idx]]);
let params = Object.fromEntries(new Map(kv_pairs));
return [params, pdf_func, mc_compiled.evaluate];
}
}
class NormalDistributionBinned extends BaseDistributionBinned {
_set_props() {
this.name = "normal";
this.param_names = ["mean", "std"];
}
get_bounds() {
return [
this.params.mean - 4 * this.params.std,
this.params.mean + 4 * this.params.std
];
}
bin() {
return this._adabin(this.params.std);
}
}
class UniformDistributionBinned extends BaseDistributionBinned {
_set_props() {
this.name = "uniform";
this.param_names = ["start_point", "end_point"];
this.num_bins = 200;
}
get_bounds() {
return [this.params.start_point, this.params.end_point];
}
bin() {
let divider_pts = evenly_spaced_grid(
this.params.start_point,
this.params.end_point,
this.num_bins
);
let vals = divider_pts.map(x =>
this.pdf_func(this.params.start_point / 2 + this.params.end_point / 2)
);
vals = vals.slice(0, -1);
return [vals, divider_pts];
}
}
class LogNormalDistributionBinned extends BaseDistributionBinned {
_set_props() {
this.name = "lognormal";
this.param_names = ["normal_mean", "normal_std"];
this.n_bounds_samples = 1000;
this.n_largest_bound_sample = 10;
}
_nth_largest(samples, n) {
var largest_buffer = Array(n).fill(-Infinity);
for (const sample of samples) {
if (sample > largest_buffer[n - 1]) {
var i = n;
while ((i > 0) & (sample > largest_buffer[i - 1])) {
i -= 1;
}
largest_buffer[i] = sample;
}
}
return largest_buffer[n - 1];
}
get_bounds() {
let samples = Array(this.n_bounds_samples)
.fill(0)
.map(() => this.sample());
return [
math.min(samples),
this._nth_largest(samples, this.n_largest_bound_sample)
];
}
bin() {
return this._adabin();
}
}
function evenly_spaced_grid(start, stop, numel) {
return Array(numel)
.fill(0)
.map((_, idx) => start + (idx / numel) * (stop - start));
}
const distrs = {
normal: NormalDistributionBinned,
lognormal: LogNormalDistributionBinned,
uniform: UniformDistributionBinned
};
exports.distrs = distrs;

31
src/components/editor/index.js Normal file
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@ -0,0 +1,31 @@
import "./styles.css";
const embed = require("vega-embed").embed;
const get_pdf_from_user_input = require("./main.js").get_pdf_from_user_input;
let [y, x] = get_pdf_from_user_input("normal(1, 1) / normal(10, 1)");
let pdf = x.map((val, idx) => ({ x: val, pdf: y[idx] }));
let spec = {
data: {
values: pdf
},
mark: { type: "area", line: true },
encoding: {
x: { field: "x", type: "quantitative" },
y: {
field: "pdf",
type: "quantitative",
scale: { domain: [0, 3 * Math.max(...y)] }
}
},
width: 500
};
embed("#viz", spec);
console.log(y.reduce((a, b) => a + b));
document.getElementById("app").innerHTML = `
<div id="viz"></div>
`;

278
src/components/editor/main.js Normal file
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@ -0,0 +1,278 @@
// 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.
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;
function evenly_spaced_grid(start, stop, numel) {
return Array(numel)
.fill(0)
.map((_, idx) => start + (idx / numel) * (stop - start));
}
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;
}
function update_transformed_divider_points_bst(
transform_func,
deterministic_pdf,
mc_distrs,
track_idx,
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 = [];
var start_pt = Infinity;
var end_pt = -Infinity;
let use_mc = mc_distrs.length > 0;
var num_outer_iters = use_mc ? num_mc_samples : 1;
for (let sample_idx = 0; sample_idx < num_outer_iters; ++sample_idx) {
var this_transformed_pts = deterministic_pdf.divider_pts;
if (use_mc) {
let samples = mc_distrs.map(x => x.sample());
this_transformed_pts = this_transformed_pts.map(x =>
transform_func([x].concat(samples))
);
} else {
this_transformed_pts = this_transformed_pts.map(x => transform_func([x]));
}
var this_transformed_pts_paired = [];
for (let tp_idx = 0; tp_idx < this_transformed_pts.length - 1; tp_idx++) {
let sorted = [
this_transformed_pts[tp_idx],
this_transformed_pts[tp_idx + 1]
].sort((a, b) => a - b);
if (sorted[0] < start_pt) {
start_pt = sorted[0];
}
if (sorted[1] > end_pt) {
end_pt = sorted[1];
}
this_transformed_pts_paired.push(sorted);
}
transformed_pts = transformed_pts.concat(this_transformed_pts_paired);
pdf_inner_idxs = pdf_inner_idxs.concat([
...Array(this_transformed_pts_paired.length).keys()
]);
var this_factors = [];
for (let idx = 0; idx < this_transformed_pts_paired.length; idx++) {
this_factors.push(
(deterministic_pdf.divider_pts[idx + 1] -
deterministic_pdf.divider_pts[idx]) /
(this_transformed_pts_paired[idx][1] -
this_transformed_pts_paired[idx][0])
);
}
factors = factors.concat(this_factors);
}
for (let i = 0; i < transformed_pts.length; ++i) {
bst_pts_and_idxs.insert(transformed_pts[i][0], {
start: transformed_pts[i][0],
end: transformed_pts[i][1],
idx: [track_idx, pdf_inner_idxs[i]],
factor: factors[i] / num_outer_iters
});
}
return [start_pt, end_pt];
}
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();
var final_pdf_vals = [];
for (
let out_grid_idx = 0;
out_grid_idx < output_grid.length;
++out_grid_idx
) {
let startpoints_within_bin = bst_pts_and_idxs.betweenBounds({
$gte: output_grid[out_grid_idx] - offset,
$lt: output_grid[out_grid_idx] + offset
});
for (let interval of startpoints_within_bin) {
active_intervals.set(interval.idx, [
interval.start,
interval.end,
interval.factor
]);
active_endpoints.insert(interval.end, interval.idx);
}
var contrib = 0;
for (let [pdf_idx, bounds_and_ratio] of active_intervals.entries()) {
let overlap_start = Math.max(
output_grid[out_grid_idx] - offset,
bounds_and_ratio[0]
);
let overlap_end = Math.min(
output_grid[out_grid_idx] + offset,
bounds_and_ratio[1]
);
let interval_size = bounds_and_ratio[1] - bounds_and_ratio[0];
let contrib_frac =
interval_size === 0
? 0
: (overlap_end - overlap_start) * bounds_and_ratio[2];
let t = contrib_frac * pdf_vals[pdf_idx[0]][pdf_idx[1]];
contrib += t;
}
final_pdf_vals.push(contrib);
let endpoints_within_bin = active_endpoints.betweenBounds({
$gte: output_grid[out_grid_idx] - offset,
$lt: output_grid[out_grid_idx] + offset
});
for (let interval_idx of endpoints_within_bin) {
active_intervals.delete(interval_idx);
}
}
return final_pdf_vals;
}
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.
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;
let tree = new bst.AVLTree();
let possible_start_pts = [];
let possible_end_pts = [];
let all_vals = [];
let weights = is_mm ? math.compile(mm_args.weights).evaluate()._data : [1];
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);
var grid_transform = get_grid_transform(distr_string);
var [start_pt, end_pt] = update_transformed_divider_points_bst(
grid_transform,
deterministic_pdf,
mc_distrs,
i,
NUM_MC_SAMPLES,
tree
);
possible_start_pts.push(start_pt);
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];
}
function variance(vals) {
var vari = 0;
for (let i = 0; i < vals[0].length; ++i) {
let mean = 0;
let this_vari = 0;
for (let val of vals) {
mean += val[i] / vals.length;
}
for (let val of vals) {
this_vari += (val[i] - mean) ** 2;
}
vari += this_vari;
}
return vari;
}
function pluck_from_array(array, idx) {
return [array[idx], array.slice(0, idx).concat(array.slice(idx + 1))];
}
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);
var pdfs = get_distributions(substrings);
if (pdfs.length === 1) {
return [pdfs[0], []];
}
var start_pt = 0;
var end_pt = 0;
for (let i = 0; i < pdfs.length; ++i) {
var outputs = [];
for (let j = 0; j < 20; ++j) {
let tree = new bst.AVLTree();
let [deterministic_pdf, mc_distrs] = pluck_from_array(pdfs, i);
let [this_start_pt, this_end_pt] = update_transformed_divider_points_bst(
transform_func,
deterministic_pdf,
mc_distrs,
0,
10,
tree
);
[start_pt, end_pt] =
j === 0 ? [this_start_pt, this_end_pt] : [start_pt, end_pt];
var output_grid = evenly_spaced_grid(start_pt, end_pt, 100);
let final_pdf_vals = get_final_pdf(
[deterministic_pdf.pdf_vals],
tree,
output_grid
);
outputs.push(final_pdf_vals);
}
variances.push(variance(outputs));
}
let best_variance = Math.min(...variances);
let best_idx = variances
.map((val, idx) => [val, idx])
.filter(x => x[0] === best_variance)[0][1];
let mc_distrs = pdfs.slice(0, best_idx).concat(pdfs.slice(best_idx + 1));
return [pdfs[best_idx], mc_distrs];
}
function get_grid_transform(distr_string) {
let substrings = parse.get_distr_substrings(distr_string);
let arg_strings = [];
for (let i = 0; i < substrings.length; ++i) {
distr_string = distr_string.replace(substrings[i], "x_" + i.toString());
arg_strings.push("x_" + i.toString());
}
let compiled = math.compile(distr_string);
function grid_transform(x) {
let kv_pairs = arg_strings.map((val, idx) => [val, x[idx]]);
let args_obj = Object.fromEntries(new Map(kv_pairs));
return compiled.evaluate(args_obj);
}
return grid_transform;
}
exports.get_pdf_from_user_input = get_pdf_from_user_input;

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src/components/editor/parse.js Normal file
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@ -0,0 +1,119 @@
// Functions for parsing/processing user input strings are here
const _math = require("mathjs");
const math = _math.create(_math.all);
const DISTR_REGEXS = [
/beta\(/g,
/(log)?normal\(/g,
/multimodal\(/g,
/mm\(/g,
/uniform\(/g
];
function parse_initial_string(user_input_string) {
let outer_output_string = "";
let mm_args_string = "";
let idx = 0;
while (idx < user_input_string.length) {
if (
user_input_string.substring(idx - 11, idx) === "multimodal(" ||
user_input_string.substring(idx - 3, idx) === "mm("
) {
let num_open_brackets = 1;
while (num_open_brackets > 0 && idx < user_input_string.length) {
mm_args_string += user_input_string[idx];
idx += 1;
if (user_input_string[idx] === ")") {
num_open_brackets -= 1;
} else if (user_input_string[idx] === "(") {
num_open_brackets += 1;
}
}
outer_output_string += ")";
idx += 1;
} else {
outer_output_string += user_input_string[idx];
idx += 1;
}
}
return {
outer_string: outer_output_string,
mm_args_string: mm_args_string
};
}
function separate_mm_args(mm_args_string) {
if (mm_args_string.endsWith(",")) {
mm_args_string = mm_args_string.slice(0, -1);
}
let args_array = [];
let num_open_brackets = 0;
let arg_substring = "";
for (let char of mm_args_string) {
if (num_open_brackets === 0 && char === ",") {
args_array.push(arg_substring.trim());
arg_substring = "";
} else {
if (char === ")" || char === "]") {
num_open_brackets -= 1;
} else if (char === "(" || char === "[") {
num_open_brackets += 1;
}
arg_substring += char;
}
}
return {
distrs: args_array,
weights: arg_substring.trim()
};
}
function get_distr_substrings(distr_string) {
let substrings = [];
for (let regex of DISTR_REGEXS) {
let matches = distr_string.matchAll(regex);
for (let match of matches) {
let idx = match.index + match[0].length;
let num_open_brackets = 1;
let distr_substring = "";
while (num_open_brackets !== 0 && idx < distr_string.length) {
distr_substring += distr_string[idx];
if (distr_string[idx] === "(") {
num_open_brackets += 1;
} else if (distr_string[idx] === ")") {
num_open_brackets -= 1;
}
idx += 1;
}
substrings.push((match[0] + distr_substring).trim());
}
}
return substrings;
}
function get_distr_name_and_args(substr) {
let distr_name = "";
let args_str = "";
let args_flag = false;
for (let char of substr) {
if (!args_flag && char !== "(") {
distr_name += char;
}
if (args_flag && char !== ")") {
args_str += char;
}
if (char === "(") {
args_str += "[";
args_flag = true;
}
}
args_str += "]";
let args = math.compile(args_str).evaluate()._data;
return [distr_name, args];
}
exports.get_distr_name_and_args = get_distr_name_and_args;
exports.get_distr_substrings = get_distr_substrings;
exports.separate_mm_args = separate_mm_args;
exports.parse_initial_string = parse_initial_string;

50
yarn.lock
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@ -2333,6 +2333,13 @@ binary-extensions@^2.0.0:
resolved "https://registry.yarnpkg.com/binary-extensions/-/binary-extensions-2.0.0.tgz#23c0df14f6a88077f5f986c0d167ec03c3d5537c"
integrity sha512-Phlt0plgpIIBOGTT/ehfFnbNlfsDEiqmzE2KRXoX1bLIlir4X/MR+zSyBEkL05ffWgnRSf/DXv+WrUAVr93/ow==
binary-search-tree@0.2.6:
version "0.2.6"
resolved "https://registry.yarnpkg.com/binary-search-tree/-/binary-search-tree-0.2.6.tgz#c6d29194e286827fcffe079010e6bf77def10ce3"
integrity sha1-xtKRlOKGgn/P/geQEOa/d97xDOM=
dependencies:
underscore "~1.4.4"
bindings@^1.5.0:
version "1.5.0"
resolved "https://registry.yarnpkg.com/bindings/-/bindings-1.5.0.tgz#10353c9e945334bc0511a6d90b38fbc7c9c504df"
@ -2889,7 +2896,7 @@ commander@2, commander@^2.11.0, commander@^2.18.0, commander@^2.19.0, commander@
resolved "https://registry.yarnpkg.com/commander/-/commander-2.20.3.tgz#fd485e84c03eb4881c20722ba48035e8531aeb33"
integrity sha512-GpVkmM8vF2vQUkj2LvZmD35JxeJOLCwJ9cUkugyk2nuhbv3+mJvpLYYt+0+USMxE+oj+ey/lJEnhZw75x/OMcQ==
complex.js@2.0.11:
complex.js@2.0.11, complex.js@^2.0.11:
version "2.0.11"
resolved "https://registry.yarnpkg.com/complex.js/-/complex.js-2.0.11.tgz#09a873fbf15ffd8c18c9c2201ccef425c32b8bf1"
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@ -3632,7 +3639,7 @@ decamelize@^1.2.0:
resolved "https://registry.yarnpkg.com/decamelize/-/decamelize-1.2.0.tgz#f6534d15148269b20352e7bee26f501f9a191290"
integrity sha1-9lNNFRSCabIDUue+4m9QH5oZEpA=
decimal.js@10.2.0:
decimal.js@10.2.0, decimal.js@^10.2.0:
version "10.2.0"
resolved "https://registry.yarnpkg.com/decimal.js/-/decimal.js-10.2.0.tgz#39466113a9e036111d02f82489b5fd6b0b5ed231"
integrity sha512-vDPw+rDgn3bZe1+F/pyEwb1oMG2XTlRVgAa6B4KccTEpYgF8w6eQllVbQcfIJnZyvzFtFpxnpGtx8dd7DJp/Rw==
@ -4043,7 +4050,7 @@ escape-html@~1.0.3:
resolved "https://registry.yarnpkg.com/escape-html/-/escape-html-1.0.3.tgz#0258eae4d3d0c0974de1c169188ef0051d1d1988"
integrity sha1-Aljq5NPQwJdN4cFpGI7wBR0dGYg=
escape-latex@1.2.0:
escape-latex@1.2.0, escape-latex@^1.2.0:
version "1.2.0"
resolved "https://registry.yarnpkg.com/escape-latex/-/escape-latex-1.2.0.tgz#07c03818cf7dac250cce517f4fda1b001ef2bca1"
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@ -4438,7 +4445,7 @@ form-data@~2.3.2:
combined-stream "^1.0.6"
mime-types "^2.1.12"
fraction.js@4.0.12:
fraction.js@4.0.12, fraction.js@^4.0.12:
version "4.0.12"
resolved "https://registry.yarnpkg.com/fraction.js/-/fraction.js-4.0.12.tgz#0526d47c65a5fb4854df78bc77f7bec708d7b8c3"
integrity sha512-8Z1K0VTG4hzYY7kA/1sj4/r1/RWLBD3xwReT/RCrUCbzPszjNQCCsy3ktkU/eaEqX3MYa4pY37a52eiBlPMlhA==
@ -5410,7 +5417,7 @@ iterall@^1.2.1, iterall@^1.2.2:
resolved "https://registry.yarnpkg.com/iterall/-/iterall-1.3.0.tgz#afcb08492e2915cbd8a0884eb93a8c94d0d72fea"
integrity sha512-QZ9qOMdF+QLHxy1QIpUHUU1D5pS2CG2P69LF6L6CPjPYA/XMOmKV3PZpawHoAjHNyB0swdVTRxdYT4tbBbxqwg==
javascript-natural-sort@0.7.1:
javascript-natural-sort@0.7.1, javascript-natural-sort@^0.7.1:
version "0.7.1"
resolved "https://registry.yarnpkg.com/javascript-natural-sort/-/javascript-natural-sort-0.7.1.tgz#f9e2303d4507f6d74355a73664d1440fb5a0ef59"
integrity sha1-+eIwPUUH9tdDVac2ZNFED7Wg71k=
@ -6320,6 +6327,11 @@ jstat@1.9.0:
resolved "https://registry.yarnpkg.com/jstat/-/jstat-1.9.0.tgz#96a625f5697566f6ba3b15832fb371f9451b8614"
integrity sha512-xSsSJ3qY4rS+u8+dAwRcJ0LQGxNdibdW6rSalNPZDbLYkW1C7b0/j79IxXtQjrweqMNI3asN7FCIPceNSIJr2g==
jstat@1.9.2:
version "1.9.2"
resolved "https://registry.yarnpkg.com/jstat/-/jstat-1.9.2.tgz#cd2d24df200fd3488861dc7868be01ff65a238cc"
integrity sha512-nc3uAadgrWWvJz6RyXUFN0lvTWEXYxMVIrm6ZVoOh4YPLvukLKYpqMofKIE2ReWkL7gFw6hEo6VWZjotYW2Bsw==
kind-of@^3.0.2, kind-of@^3.0.3, kind-of@^3.2.0:
version "3.2.2"
resolved "https://registry.yarnpkg.com/kind-of/-/kind-of-3.2.2.tgz#31ea21a734bab9bbb0f32466d893aea51e4a3c64"
@ -6559,6 +6571,20 @@ mathjs@5.10.3:
tiny-emitter "2.1.0"
typed-function "1.1.0"
mathjs@6.6.0:
version "6.6.0"
resolved "https://registry.yarnpkg.com/mathjs/-/mathjs-6.6.0.tgz#0d71c7cc6b50bd112e160b55703a395caf4db4b1"
integrity sha512-gYYc1+irFbwuwYUx6O8G2YauvbD1+tPBbq829PaxAiRWpPzPEE8pvwGgvdMuk6c3pqhm6Do/mN26vLiQP46H5A==
dependencies:
complex.js "^2.0.11"
decimal.js "^10.2.0"
escape-latex "^1.2.0"
fraction.js "^4.0.12"
javascript-natural-sort "^0.7.1"
seed-random "^2.2.0"
tiny-emitter "^2.1.0"
typed-function "^1.1.1"
md5.js@^1.3.4:
version "1.3.5"
resolved "https://registry.yarnpkg.com/md5.js/-/md5.js-1.3.5.tgz#b5d07b8e3216e3e27cd728d72f70d1e6a342005f"
@ -9235,7 +9261,7 @@ screenfull@^5.0.0:
resolved "https://registry.yarnpkg.com/screenfull/-/screenfull-5.0.2.tgz#b9acdcf1ec676a948674df5cd0ff66b902b0bed7"
integrity sha512-cCF2b+L/mnEiORLN5xSAz6H3t18i2oHh9BA8+CQlAh5DRw2+NFAGQJOSYbcGw8B2k04g/lVvFcfZ83b3ysH5UQ==
seed-random@2.2.0:
seed-random@2.2.0, seed-random@^2.2.0:
version "2.2.0"
resolved "https://registry.yarnpkg.com/seed-random/-/seed-random-2.2.0.tgz#2a9b19e250a817099231a5b99a4daf80b7fbed54"
integrity sha1-KpsZ4lCoFwmSMaW5mk2vgLf77VQ=
@ -9989,7 +10015,7 @@ timsort@^0.3.0:
resolved "https://registry.yarnpkg.com/timsort/-/timsort-0.3.0.tgz#405411a8e7e6339fe64db9a234de11dc31e02bd4"
integrity sha1-QFQRqOfmM5/mTbmiNN4R3DHgK9Q=
tiny-emitter@2.1.0:
tiny-emitter@2.1.0, tiny-emitter@^2.1.0:
version "2.1.0"
resolved "https://registry.yarnpkg.com/tiny-emitter/-/tiny-emitter-2.1.0.tgz#1d1a56edfc51c43e863cbb5382a72330e3555423"
integrity sha512-NB6Dk1A9xgQPMoGqC5CVXn123gWyte215ONT5Pp5a0yt4nlEoO1ZWeCwpncaekPHXO60i47ihFnZPiRPjRMq4Q==
@ -10176,6 +10202,11 @@ typed-function@1.1.0:
resolved "https://registry.yarnpkg.com/typed-function/-/typed-function-1.1.0.tgz#ea149706e0fb42aca1791c053a6d94ccd6c4fdcb"
integrity sha512-TuQzwiT4DDg19beHam3E66oRXhyqlyfgjHB/5fcvsRXbfmWPJfto9B4a0TBdTrQAPGlGmXh/k7iUI+WsObgORA==
typed-function@^1.1.1:
version "1.1.1"
resolved "https://registry.yarnpkg.com/typed-function/-/typed-function-1.1.1.tgz#a1316187ec3628c9e219b91ca96918660a10138e"
integrity sha512-RbN7MaTQBZLJYzDENHPA0nUmWT0Ex80KHItprrgbTPufYhIlTePvCXZxyQK7wgn19FW5bnuaBIKcBb5mRWjB1Q==
typedarray-to-buffer@^3.1.5:
version "3.1.5"
resolved "https://registry.yarnpkg.com/typedarray-to-buffer/-/typedarray-to-buffer-3.1.5.tgz#a97ee7a9ff42691b9f783ff1bc5112fe3fca9080"
@ -10208,6 +10239,11 @@ uncss@^0.17.2:
postcss-selector-parser "6.0.2"
request "^2.88.0"
underscore@~1.4.4:
version "1.4.4"
resolved "https://registry.yarnpkg.com/underscore/-/underscore-1.4.4.tgz#61a6a32010622afa07963bf325203cf12239d604"
integrity sha1-YaajIBBiKvoHljvzJSA88SI51gQ=
unicode-canonical-property-names-ecmascript@^1.0.4:
version "1.0.4"
resolved "https://registry.yarnpkg.com/unicode-canonical-property-names-ecmascript/-/unicode-canonical-property-names-ecmascript-1.0.4.tgz#2619800c4c825800efdd8343af7dd9933cbe2818"