Units, Dimensions, Scale, and Normalization

Install and import#

bash

npm install fintech-algorithms

import { unitsDimensionsScaleAndNormalization } from "fintech-algorithms/financial-mathematics-statistics-and-data-foundations/mathematical-language-and-quantitative-reasoning/units-dimensions-scale-and-normalization";

Signature#

unitsDimensionsScaleAndNormalization(input)

Worked example#

verified This is the worked example published in the article, replayed by the test suite on every run. The output cannot drift.

Input#

input

{
  "values": [1, 2, 3, 4, 5],
  "startingCash": 1000,
  "inflows": 250,
  "outflows": 120,
  "slope": 2,
  "intercept": 1,
  "part": 25,
  "whole": 200,
  "elapsed": 5,
  "old": 4.5,
  "new": 4.75,
  "base": 16,
  "exponent": 0.5,
  "a": 2
}

Showing 14 of 28 fields.

Call#

unitsDimensionsScaleAndNormalization(input)

Returns#

object with 2 fields: normalized, sourceUnit

{
  "normalized": [0, 0.5, 1, 1.5, 2],
  "sourceUnit": "SAR millions"
}

Diagrams#

Calculation flow#

Units, Dimensions, Scale, and Normalization — four-part map

flowchart LR
    A["Name the input"] --> B["Apply: base amount = displayed amount × scale; per-unit amount = base amount / count"]
    B --> C["Check units and boundary"]
    C --> D["Explain the output"]

How it works#

This page states the contract — how to call it correctly. The article explains the concept: why it works, and where it breaks.

Read the article →

References#

The International System of Units (SI Brochure), 9th edition — Bureau International des Poids et Mesures
NIST/SEMATECH e-Handbook of Statistical Methods — NIST/SEMATECH
Author-derived and synthetic boundary