From 9cb15ca79df8a28231cb600b2898835ba1b22c25 Mon Sep 17 00:00:00 2001
From: Alexey Kiselev <kiselev@amazon.com>
Date: Sat, 30 Nov 2019 16:23:38 +0000
Subject: [PATCH] Readme refactored

---
 Readme.md                    | 44 +++++++++++++++++++++++++++++++++---
 core/methods/extremevalue.js |  2 +-
 2 files changed, 42 insertions(+), 4 deletions(-)

diff --git a/Readme.md b/Readme.md
index c975324..b8e597a 100644
--- a/Readme.md
+++ b/Readme.md
@@ -6,14 +6,44 @@ A JavaScript module for generating seeded random distributions and its statistic
 
 Implemented in pure JavaScript with no dependencies, designed to work in Node.js and fully asynchronous, tested *with 600+ tests*.
 
-[Supported distributions](./core/methods/)
+#### [Supported distributions](./core/methods/)
+
+| Name | Parameters | Usage |
+| --- | --- | --- |
+| Uniform distribution | `min` - any value, `max` - any value, `min` < `max` | `unirand.uniform(min, max).random()` |
+| Normal (Gaussian) distribution | `mu` - any value, `sigma` > 0 | `unirand.normal(mu, sigma).random()` |
+| Bates distribution | `n` - integer, `n` >= 1, `a` - any value, `b` - any value, `b` > `a` | `unirand.bates(n, a, b).random()` |
+| Bernoulli distribution | `p` - float number, 0 <= `p` <= 1 | `unirand.bernoulli(p).random()` |
+| Beta distribution | `alpha` - integer, `alpha` > 0, `beta` > integer, `beta` > 0 | `unirand.beta(alpha, beta).random()` |
+| BetaPrime distribution | `alpha` - integer, `alpha` > 0, `beta` > integer, `beta` > 0 | `unirand.betaprime(alpha, beta).random()` |
+| Binomial distribution | `n` - integer, `n` > 0, `p` - float number, 0 <= `p` <= 1  | `unirand.binomial(n, p).random()` |
+| Cauchy (Lorenz) distribution | `x` - any value, `gamma` > 0 | `unirand.cauchy(x, gamma).random()` |
+| Chi distribution | `k` - integer, `k` > 0 | `unirand.chi(k).random()` |
+| Chi Square distribution | `k` - integer, `k` > 0 | `unirand.chisquare(k).random()` |
+| Erlang distribution | `k` - integer, `k` > 0, `mu` - float value, `mu` > 0 | `unirand.erlang(k, mu).random()` |
+| Exponential distribution | `lambda` - float value, `lambda` > 0 | `unirand.exponential(lambda).random()` |
+| Extreme (Gumbel-type) Value distribution | `mu` - any value, `sigma` - float number, `sigma` > 0 | `unirand.extremevalue(mu, sigma).random()` |
+| Gamma distribution | `alpha` - float value, `alpha` > 0, `beta` - integer, `beta` > 0 | `unirand.gamma(alpha, beta).random()` |
+| Geometric distribution | `p` - float value, 0 <= `p` <= 1 | `unirand.geometric(p).random()` |
+| Irwin-Hall distribution | `n` - integer, `n` > 0 | `unirand.irwinhall(n).random()` |
+| Laplace distribution | `mu` - any value, `b` - float value, `b` > 0 | `unirand.laplace(mu, b).random()` |
+| Logistic distribution | `mu` - any value, `s` - float value, `s` > 0 | `unirand.logistic(mu, s).random()` |
+| Lognormal distribution | `mu` - any value, `sigma` - float value, `sigma` > 0 | `unirand.lognormal(mu, sigma).random()` |
+| Negative Binomial distribution | `r` - integer, `r` > 0, `p` - float value, 0 <= `p` <= 1 | `unirand.negativebinomial(r, p).random()` |
+| Pareto distribution | `xm` - float value, `xm` > 0, `alpha` - float value, `alpha` > 0 | `unirand.pareto(xm, alpha).random()` |
+| Poisson distribution | `lambda` - integer, `lambda` > 0 | `unirand.poisson(lambda).random()` |
+| Rayleigh distribution | `sigma` - float value, `sigma` > 0 | `unirand.rayleigh(sigma).random()` |
+| Student's t-distribution | `v` - integer, `v` > 0 | `unirand.student(v).random()` |
+| Triangular distribution | `a`, `b`, `c` - any number, `b` > `a`, `a` <= `c` <= `b` | `unirand.triangular(a, b, c).random()` |
+| Weibull distribution | `k` - float value, `k` > 0, `lambda` - float value, `lambda` > 0 | `unirand.weibull(k, lambda).random()` |
+| Zipf distribution | `alpha` - float value, `alpha` >= 0, `shape` - integer, `shape` > 1 | `unirand.zipf(alpha, shape).random()` |
 
 ## Installation and Usage
 
 Install the `unirand` module, using `npm install unirand`, then include the code with require. The `require` method returns an object with all of the module's methods attached to it.
 
 ```javascript
-const unirand = require('unirand')
+const unirand = require('unirand');
 ```
 
 ### PRNG
@@ -133,9 +163,17 @@ unirand.utils.erf(2); // returns error function with argument 2
 ### Hash
 Returns *hash* using murmur3 algorithm
 ```javascript
-unirand.hash('unirand');
+unirand.hash('unirand'); // string input
+// or
+unirand.hash(123456); // numerical input
 ```  
 
+Also supports different `seed values`. By default, `seed` value is zero.
+
+```javascript
+unirand.hash('unirand', 123);
+```
+
 ### Sample
 Generates **random sample** from array, string or object. This method will generate *k* random elements from array/string with *n* elements.
 ```javascript
diff --git a/core/methods/extremevalue.js b/core/methods/extremevalue.js
index 632c6ae..6184360 100644
--- a/core/methods/extremevalue.js
+++ b/core/methods/extremevalue.js
@@ -7,7 +7,7 @@
  * @param mu <number> - location, any value
  * @param sigma <number> - scale, sigma > 0
  * @returns Extreme Value distributed numbers
- * Created by Alexey S. Kiselev on 27.11.2017.
+ * Created by Alexey S. Kiselev
  */
 
 import type { MethodError, RandomArray } from '../types';