feat:node-modules

node_modules/mathjs/lib/cjs/expression/embeddedDocs/function/statistics/corr.js

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+"use strict";
+
+Object.defineProperty(exports, "__esModule", {
+  value: true
+});
+exports.corrDocs = void 0;
+const corrDocs = exports.corrDocs = {
+  name: 'corr',
+  category: 'Statistics',
+  syntax: ['corr(A,B)'],
+  description: 'Compute the correlation coefficient of a two list with values, For matrices, the matrix correlation coefficient is calculated.',
+  examples: ['corr([2, 4, 6, 8],[1, 2, 3, 6])', 'corr(matrix([[1, 2.2, 3, 4.8, 5], [1, 2, 3, 4, 5]]), matrix([[4, 5.3, 6.6, 7, 8], [1, 2, 3, 4, 5]]))'],
+  seealso: ['max', 'mean', 'min', 'median', 'min', 'prod', 'std', 'sum']
+};

node_modules/mathjs/lib/cjs/expression/embeddedDocs/function/statistics/cumsum.js

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+"use strict";
+
+Object.defineProperty(exports, "__esModule", {
+  value: true
+});
+exports.cumSumDocs = void 0;
+const cumSumDocs = exports.cumSumDocs = {
+  name: 'cumsum',
+  category: 'Statistics',
+  syntax: ['cumsum(a, b, c, ...)', 'cumsum(A)'],
+  description: 'Compute the cumulative sum of all values.',
+  examples: ['cumsum(2, 3, 4, 1)', 'cumsum([2, 3, 4, 1])', 'cumsum([1, 2; 3, 4])', 'cumsum([1, 2; 3, 4], 1)', 'cumsum([1, 2; 3, 4], 2)'],
+  seealso: ['max', 'mean', 'median', 'min', 'prod', 'std', 'sum', 'variance']
+};

node_modules/mathjs/lib/cjs/expression/embeddedDocs/function/statistics/mad.js

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+"use strict";
+
+Object.defineProperty(exports, "__esModule", {
+  value: true
+});
+exports.madDocs = void 0;
+const madDocs = exports.madDocs = {
+  name: 'mad',
+  category: 'Statistics',
+  syntax: ['mad(a, b, c, ...)', 'mad(A)'],
+  description: 'Compute the median absolute deviation of a matrix or a list with values. The median absolute deviation is defined as the median of the absolute deviations from the median.',
+  examples: ['mad(10, 20, 30)', 'mad([1, 2, 3])'],
+  seealso: ['mean', 'median', 'std', 'abs']
+};

node_modules/mathjs/lib/cjs/expression/embeddedDocs/function/statistics/max.js

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+"use strict";
+
+Object.defineProperty(exports, "__esModule", {
+  value: true
+});
+exports.maxDocs = void 0;
+const maxDocs = exports.maxDocs = {
+  name: 'max',
+  category: 'Statistics',
+  syntax: ['max(a, b, c, ...)', 'max(A)', 'max(A, dimension)'],
+  description: 'Compute the maximum value of a list of values.',
+  examples: ['max(2, 3, 4, 1)', 'max([2, 3, 4, 1])', 'max([2, 5; 4, 3])', 'max([2, 5; 4, 3], 1)', 'max([2, 5; 4, 3], 2)', 'max(2.7, 7.1, -4.5, 2.0, 4.1)', 'min(2.7, 7.1, -4.5, 2.0, 4.1)'],
+  seealso: ['mean', 'median', 'min', 'prod', 'std', 'sum', 'variance']
+};

node_modules/mathjs/lib/cjs/expression/embeddedDocs/function/statistics/mean.js

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+"use strict";
+
+Object.defineProperty(exports, "__esModule", {
+  value: true
+});
+exports.meanDocs = void 0;
+const meanDocs = exports.meanDocs = {
+  name: 'mean',
+  category: 'Statistics',
+  syntax: ['mean(a, b, c, ...)', 'mean(A)', 'mean(A, dimension)'],
+  description: 'Compute the arithmetic mean of a list of values.',
+  examples: ['mean(2, 3, 4, 1)', 'mean([2, 3, 4, 1])', 'mean([2, 5; 4, 3])', 'mean([2, 5; 4, 3], 1)', 'mean([2, 5; 4, 3], 2)', 'mean([1.0, 2.7, 3.2, 4.0])'],
+  seealso: ['max', 'median', 'min', 'prod', 'std', 'sum', 'variance']
+};

node_modules/mathjs/lib/cjs/expression/embeddedDocs/function/statistics/median.js

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+"use strict";
+
+Object.defineProperty(exports, "__esModule", {
+  value: true
+});
+exports.medianDocs = void 0;
+const medianDocs = exports.medianDocs = {
+  name: 'median',
+  category: 'Statistics',
+  syntax: ['median(a, b, c, ...)', 'median(A)'],
+  description: 'Compute the median of all values. The values are sorted and the middle value is returned. In case of an even number of values, the average of the two middle values is returned.',
+  examples: ['median(5, 2, 7)', 'median([3, -1, 5, 7])'],
+  seealso: ['max', 'mean', 'min', 'prod', 'std', 'sum', 'variance', 'quantileSeq']
+};

node_modules/mathjs/lib/cjs/expression/embeddedDocs/function/statistics/min.js

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+"use strict";
+
+Object.defineProperty(exports, "__esModule", {
+  value: true
+});
+exports.minDocs = void 0;
+const minDocs = exports.minDocs = {
+  name: 'min',
+  category: 'Statistics',
+  syntax: ['min(a, b, c, ...)', 'min(A)', 'min(A, dimension)'],
+  description: 'Compute the minimum value of a list of values.',
+  examples: ['min(2, 3, 4, 1)', 'min([2, 3, 4, 1])', 'min([2, 5; 4, 3])', 'min([2, 5; 4, 3], 1)', 'min([2, 5; 4, 3], 2)', 'min(2.7, 7.1, -4.5, 2.0, 4.1)', 'max(2.7, 7.1, -4.5, 2.0, 4.1)'],
+  seealso: ['max', 'mean', 'median', 'prod', 'std', 'sum', 'variance']
+};

node_modules/mathjs/lib/cjs/expression/embeddedDocs/function/statistics/mode.js

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+"use strict";
+
+Object.defineProperty(exports, "__esModule", {
+  value: true
+});
+exports.modeDocs = void 0;
+const modeDocs = exports.modeDocs = {
+  name: 'mode',
+  category: 'Statistics',
+  syntax: ['mode(a, b, c, ...)', 'mode(A)', 'mode(A, a, b, B, c, ...)'],
+  description: 'Computes the mode of all values as an array. In case mode being more than one, multiple values are returned in an array.',
+  examples: ['mode(2, 1, 4, 3, 1)', 'mode([1, 2.7, 3.2, 4, 2.7])', 'mode(1, 4, 6, 1, 6)'],
+  seealso: ['max', 'mean', 'min', 'median', 'prod', 'std', 'sum', 'variance']
+};

node_modules/mathjs/lib/cjs/expression/embeddedDocs/function/statistics/prod.js

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+"use strict";
+
+Object.defineProperty(exports, "__esModule", {
+  value: true
+});
+exports.prodDocs = void 0;
+const prodDocs = exports.prodDocs = {
+  name: 'prod',
+  category: 'Statistics',
+  syntax: ['prod(a, b, c, ...)', 'prod(A)'],
+  description: 'Compute the product of all values.',
+  examples: ['prod(2, 3, 4)', 'prod([2, 3, 4])', 'prod([2, 5; 4, 3])'],
+  seealso: ['max', 'mean', 'min', 'median', 'min', 'std', 'sum', 'variance']
+};

node_modules/mathjs/lib/cjs/expression/embeddedDocs/function/statistics/quantileSeq.js

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+"use strict";
+
+Object.defineProperty(exports, "__esModule", {
+  value: true
+});
+exports.quantileSeqDocs = void 0;
+const quantileSeqDocs = exports.quantileSeqDocs = {
+  name: 'quantileSeq',
+  category: 'Statistics',
+  syntax: ['quantileSeq(A, prob[, sorted])', 'quantileSeq(A, [prob1, prob2, ...][, sorted])', 'quantileSeq(A, N[, sorted])'],
+  description: 'Compute the prob order quantile of a matrix or a list with values. The sequence is sorted and the middle value is returned. Supported types of sequence values are: Number, BigNumber, Unit Supported types of probability are: Number, BigNumber. \n\nIn case of a (multi dimensional) array or matrix, the prob order quantile of all elements will be calculated.',
+  examples: ['quantileSeq([3, -1, 5, 7], 0.5)', 'quantileSeq([3, -1, 5, 7], [1/3, 2/3])', 'quantileSeq([3, -1, 5, 7], 2)', 'quantileSeq([-1, 3, 5, 7], 0.5, true)'],
+  seealso: ['mean', 'median', 'min', 'max', 'prod', 'std', 'sum', 'variance']
+};

node_modules/mathjs/lib/cjs/expression/embeddedDocs/function/statistics/std.js

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+"use strict";
+
+Object.defineProperty(exports, "__esModule", {
+  value: true
+});
+exports.stdDocs = void 0;
+const stdDocs = exports.stdDocs = {
+  name: 'std',
+  category: 'Statistics',
+  syntax: ['std(a, b, c, ...)', 'std(A)', 'std(A, dimension)', 'std(A, normalization)', 'std(A, dimension, normalization)'],
+  description: 'Compute the standard deviation of all values, defined as std(A) = sqrt(variance(A)). Optional parameter normalization can be "unbiased" (default), "uncorrected", or "biased".',
+  examples: ['std(2, 4, 6)', 'std([2, 4, 6, 8])', 'std([2, 4, 6, 8], "uncorrected")', 'std([2, 4, 6, 8], "biased")', 'std([1, 2, 3; 4, 5, 6])'],
+  seealso: ['max', 'mean', 'min', 'median', 'prod', 'sum', 'variance']
+};

node_modules/mathjs/lib/cjs/expression/embeddedDocs/function/statistics/sum.js

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+"use strict";
+
+Object.defineProperty(exports, "__esModule", {
+  value: true
+});
+exports.sumDocs = void 0;
+const sumDocs = exports.sumDocs = {
+  name: 'sum',
+  category: 'Statistics',
+  syntax: ['sum(a, b, c, ...)', 'sum(A)', 'sum(A, dimension)'],
+  description: 'Compute the sum of all values.',
+  examples: ['sum(2, 3, 4, 1)', 'sum([2, 3, 4, 1])', 'sum([2, 5; 4, 3])'],
+  seealso: ['max', 'mean', 'median', 'min', 'prod', 'std', 'sum', 'variance']
+};

node_modules/mathjs/lib/cjs/expression/embeddedDocs/function/statistics/variance.js

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+"use strict";
+
+Object.defineProperty(exports, "__esModule", {
+  value: true
+});
+exports.varianceDocs = void 0;
+const varianceDocs = exports.varianceDocs = {
+  name: 'variance',
+  category: 'Statistics',
+  syntax: ['variance(a, b, c, ...)', 'variance(A)', 'variance(A, dimension)', 'variance(A, normalization)', 'variance(A, dimension, normalization)'],
+  description: 'Compute the variance of all values. Optional parameter normalization can be "unbiased" (default), "uncorrected", or "biased".',
+  examples: ['variance(2, 4, 6)', 'variance([2, 4, 6, 8])', 'variance([2, 4, 6, 8], "uncorrected")', 'variance([2, 4, 6, 8], "biased")', 'variance([1, 2, 3; 4, 5, 6])'],
+  seealso: ['max', 'mean', 'min', 'median', 'min', 'prod', 'std', 'sum']
+};