diff --git a/index.js b/index.js
index 97b03a2..f1abd61 100644
--- a/index.js
+++ b/index.js
@@ -2,19 +2,14 @@
 var gsl = require('./build/default/gsl');
 
 module.exports = {
+	Random: gsl.Random,
 	random: {
 		get: gsl.rngGet,
-		Get: gsl.RngGet,
 		min: gsl.rngMin,
 		max: gsl.rngMax,
 		uniform: gsl.rngUniform,
-		Uniform: gsl.RngUniform,
 		gaussian: gsl.ranGaussian,
-		Gaussian: gsl.RanGaussian,
 		gaussianZiggurat: gsl.ranGaussianZiggurat,
-		GaussianZiggurat: gsl.RanGaussianZiggurat,
-		gaussianRatioMethod: gsl.ranGaussianRatioMethod,
-		GaussianRatioMethod: gsl.RanGaussianRatioMethod
+		gaussianRatioMethod: gsl.ranGaussianRatioMethod
 	}
 };
-
diff --git a/readme.md b/readme.md
index fdf722d..010ed18 100644
--- a/readme.md
+++ b/readme.md
@@ -29,82 +29,70 @@ Via git (or downloaded tarball):
 Random API
 ----------
 
-Seed arguments are always optional and must be provided as unsigned integers. 
+The library takes two forms, functions and iterator objects. Both respect the same names with different conventions. For exemple, obtaining an uniform random name can be done as `random.get()` as well as `(new Random).get()`. If you wished to provide a seed, then you'll respectivelly call `random.get(seed)` and `(new Random(seed)).get()`
+
+Using an iterator objects make sense when performance is in consideration, specially when using seeds.
+
+Seeds are always optional and must be provided as unsigned integers. Deviations, used by gaussian functions, are float and default to 3.
+
+-	*Random([seed])*
+	Construct a new iterator, seel below for available random methods.
 
 ### [Sampling](http://www.gnu.org/software/gsl/manual/html_node/Sampling-from-a-random-number-generator.html)
 
 -	*random.get([seed])*
+	*Random.get()*
 	Returns a random integer. The minimum and maximum values depend on the algorithm used, but all integers in the range [min,max] are equally likely. The values of min and max can determined using the auxiliary functions `random.min()` and `random.max()`.
-		
--	*random.Get([seed])*
-	Creates an iterator. Take an optional seed argument as an unsigned int. Random number are obtained by calling `next`.
-	*random.Get.next()*
-	Same as `random.get` but called from a `random.Get` instance.  
 	
 -	*random.min()*
+	*Random.min()*
 	Returns the smallest value that `random.get()` can return
 	
 -	*random.max()*
+	*Random.max()*
 	Returns the largest value that `random.get()` can return
-
+	
 -	*random.uniform([seed])*
+	*Random.uniform([])*
 	Returns a double precision floating point number uniformly distributed in the range [0,1). The range includes 0.0 but excludes 1.0.
-		
--	*random.Uniform([seed])*
-	Creates an iterator. Take an optional seed argument as an unsigned int. Random number are obtained by calling `next`.
-	*random.Uniform.next()*
-	Same as `random.uniform` but called from a `random.Uniform` instance.  
 
 ### [Gaussian](http://www.gnu.org/software/gsl/manual/html_node/The-Gaussian-Distribution.html)
 
 -	*random.gaussian([seed], [deviation])*
+	*Random.gaussian([deviation])*
 	Returns a Gaussian random float with mean zero. Standart deviation is a float and default to 3.
-		
--	*random.Gaussian([seed])*
-	Creates an iterator. Take an optional seed argument as an unsigned int. Random number are obtained by calling `next` with an optional deviation.
-	Also, the `seed` property is accessible.
-	*random.Gaussian.next([deviation])*
-	Same as `random.gaussian` but called from a `random.Gaussian` instance. 
-	*random.Gaussian.seed*
-	Returns the seed used by the iterator.
 	
 -	*random.gaussianZiggurat([seed], [deviation])*
+	*Random.gaussianZiggurat([deviation])*
 	Same as `random.gaussian` but using the alternative Marsaglia-Tsang ziggurat method.
-		
--	*random.GaussianZiggurat([seed])*
-	Same as `random.Gaussian` but using the alternative Marsaglia-Tsang ziggurat method.
 	
 -	*random.gaussianRatioMethod([seed], [deviation])*
+	*Random.gaussianRatioMethod([deviation])*
 	Same as `random.gaussian` but using the alternative Kinderman-Monahan-Leva ratio method.
-		
--	*random.GaussianRatioMethod([seed])*
-	Same as `random.Gaussian` but using the alternative Kinderman-Monahan-Leva ratio method.
 
 Exemple
 
-	var random = require('gsl').random,
+	var gsl = require('gsl'),
 		seed = 50,
 		deviation = 0.5;
 	
-	console.log( random.gaussian() );
-	console.log( random.gaussian(seed) );
-	console.log( random.gaussian(seed,deviation) );
+	console.log( gsl.random.gaussian() );
+	console.log( gsl.random.gaussian(seed) );
+	console.log( gsl.random.gaussian(seed, deviation) );
 	
-	var it1 = new random.Gaussian();
-	console.log( it1.next() );
-	it1.seed;
+	var it1 = new gsl.Random();
+	console.log( it1.gaussian() );
 	
-	var it1 = new random.Gaussian(seed);
-	console.log( it1.next(deviation) );
-	console.log( it1.seed );
+	var it1 = new gsl.Random(seed);
+	console.log( it1.gaussian(deviation) );
 
 Running the tests
 -----------------
 
-Tests are executed with expresso. To install it, simple use `npm install expresso`.
+Tests are executed with expresso. To install it, simply issue `npm install expresso`.
 
 To run the tests
-	expresso test
+	expresso
 
 Contributors
 ------------
diff --git a/samples/gaussian.js b/samples/gaussian.js
index 64c0694..58b7ed4 100644
--- a/samples/gaussian.js
+++ b/samples/gaussian.js
@@ -1,16 +1,14 @@
 
-	var random = require('gsl').random,
+	var gsl = require('gsl'),
 		seed = 50,
 		deviation = 0.5;
+
+	console.log( gsl.random.gaussian() );
+	console.log( gsl.random.gaussian(seed) );
+	console.log( gsl.random.gaussian(seed, deviation) );
 	
-	console.log( random.gaussian() );
-	console.log( random.gaussian(seed) );
-	console.log( random.gaussian(seed,deviation) );
-	
-	var it1 = new random.Gaussian();
-	console.log( it1.next() );
-	it1.seed;
+	var it1 = new gsl.Random();
+	console.log( it1.gaussian() );
 	
-	var it1 = new random.Gaussian(seed);
-	console.log( it1.next(deviation) );
-	console.log( it1.seed );
\ No newline at end of file
+	var it1 = new gsl.Random(seed);
+	console.log( it1.gaussian(deviation) );
\ No newline at end of file
diff --git a/samples/gaussian_speed.js b/samples/gaussian_speed.js
index 4632c11..6c5a93b 100644
--- a/samples/gaussian_speed.js
+++ b/samples/gaussian_speed.js
@@ -54,10 +54,10 @@ var assert = require('assert'),
 	console.log('C++ fn',(new Date).getTime() - time);
 
 	var time = (new Date).getTime();
-	var random = new gsl.random.Gaussian(1978);
+	var random = new gsl.Random(1978);
 	for(var i=0;i<1000000;i++){
 		for(var j=0;j<2;j++){
-			random.next();
+			random.gaussian();
 		}
 	}
 	console.log('C++ it',(new Date).getTime() - time);
@@ -71,10 +71,10 @@ var assert = require('assert'),
 	console.log('C++ fn Ziggurat',(new Date).getTime() - time);
 
 	var time = (new Date).getTime();
-	var random = new gsl.random.GaussianZiggurat(1978);
+	var random = new gsl.Random(1978);
 	for(var i=0;i<1000000;i++){
 		for(var j=0;j<2;j++){
-			random.next();
+			random.gaussianZiggurat();
 		}
 	}
 	console.log('C++ it Ziggurat',(new Date).getTime() - time);
@@ -88,10 +88,10 @@ var assert = require('assert'),
 	console.log('C++ fn RatioMethod',(new Date).getTime() - time);
 
 	var time = (new Date).getTime();
-	var random = new gsl.random.GaussianRatioMethod(1978);
+	var random = new gsl.Random(1978);
 	for(var i=0;i<1000000;i++){
 		for(var j=0;j<2;j++){
-			random.next();
+			random.gaussianRatioMethod();
 		}
 	}
 	console.log('C++ it RatioMethod',(new Date).getTime() - time);
diff --git a/samples/random_speed.js b/samples/random_speed.js
index e941d5b..11b3a9e 100644
--- a/samples/random_speed.js
+++ b/samples/random_speed.js
@@ -39,10 +39,10 @@ var assert = require('assert'),
 	console.log('C++ get fn',(new Date).getTime() - time);
 
 	var time = (new Date).getTime();
-	var random = new gsl.random.Get(1978);
+	var random = new gsl.Random(1978);
 	for(var i=0;i<1000000;i++){
 		for(var j=0;j<2;j++){
-			random.next();
+			random.get();
 		}
 	}
 	console.log('C++ get it',(new Date).getTime() - time);
@@ -56,10 +56,10 @@ var assert = require('assert'),
 	console.log('C++ uniform fn',(new Date).getTime() - time);
 
 	var time = (new Date).getTime();
-	var random = new gsl.random.Uniform(1978);
+	var random = new gsl.Random(1978);
 	for(var i=0;i<1000000;i++){
 		for(var j=0;j<2;j++){
-			random.next();
+			random.uniform();
 		}
 	}
 	console.log('C++ uniform it',(new Date).getTime() - time);
diff --git a/src/gaussian.cc b/src/gaussian.cc
index 11d3e6b..920b4df 100644
--- a/src/gaussian.cc
+++ b/src/gaussian.cc
@@ -30,56 +30,6 @@ Handle<Value> ranGaussian(const Arguments& args)
 	return Number::New(val);
 }
 
-class Gaussian: public ObjectWrap
-{
-private:
-	gsl_rng *_gsl_rng;
-public:
-	int seed;
-	static Persistent<FunctionTemplate> s_ct;
-	static void Init(Handle<Object> target)
-	{
-		HandleScope scope;
-		Local<FunctionTemplate> t = FunctionTemplate::New(New);
-		s_ct = Persistent<FunctionTemplate>::New(t);
-		s_ct->InstanceTemplate()->SetInternalFieldCount(1);
-		s_ct->SetClassName(String::NewSymbol("Gaussian"));
-		NODE_SET_PROTOTYPE_METHOD(s_ct, "next", Next);
-		target->Set(String::NewSymbol("RanGaussian"), s_ct->GetFunction());
-	}
-	~Gaussian()
-	{
-		gsl_rng_free(this->_gsl_rng);
-	}
-	static Handle<Value> New(const Arguments& args)
-	{
-		HandleScope scope;
-		Gaussian* g = new Gaussian();
-		g->Wrap(args.This());
-		g->_gsl_rng = gsl_rng_alloc (gsl_rng_default);
-		if(args.Length() == 1){
-			g->seed = args[0]->Uint32Value();
-		    gsl_rng_set(g->_gsl_rng, g->seed);
-		}
-		return args.This();
-	}
-
-	static Handle<Value> Next(const Arguments& args)
-	{
-		HandleScope scope;
-		Gaussian* g = ObjectWrap::Unwrap<Gaussian>(args.This());
-	    double deviation;
-		if(args.Length() == 0){
-			 deviation = 3;
-		}else{
-			 deviation = args[0]->NumberValue();
-		}
-		double val = gsl_ran_gaussian(g->_gsl_rng, deviation);
-		return scope.Close(Number::New(val));
-	}
-
-};
-
 Handle<Value> ranGaussianZiggurat(const Arguments& args)
 {
 	double deviation;
@@ -96,56 +46,6 @@ Handle<Value> ranGaussianZiggurat(const Arguments& args)
 	return Number::New(val);
 }
 
-class GaussianZiggurat: public ObjectWrap
-{
-private:
-	gsl_rng *_gsl_rng;
-public:
-	int seed;
-	static Persistent<FunctionTemplate> s_ct;
-	static void Init(Handle<Object> target)
-	{
-		HandleScope scope;
-		Local<FunctionTemplate> t = FunctionTemplate::New(New);
-		s_ct = Persistent<FunctionTemplate>::New(t);
-		s_ct->InstanceTemplate()->SetInternalFieldCount(1);
-		s_ct->SetClassName(String::NewSymbol("GaussianZiggurat"));
-		NODE_SET_PROTOTYPE_METHOD(s_ct, "next", Next);
-		target->Set(String::NewSymbol("RanGaussianZiggurat"), s_ct->GetFunction());
-	}
-	~GaussianZiggurat()
-	{
-		gsl_rng_free(this->_gsl_rng);
-	}
-	static Handle<Value> New(const Arguments& args)
-	{
-		HandleScope scope;
-		GaussianZiggurat* g = new GaussianZiggurat();
-		g->Wrap(args.This());
-		g->_gsl_rng = gsl_rng_alloc (gsl_rng_default);
-		if(args.Length() == 1){
-			g->seed = args[0]->Uint32Value();
-		    gsl_rng_set(g->_gsl_rng, g->seed);
-		}
-		return args.This();
-	}
-
-	static Handle<Value> Next(const Arguments& args)
-	{
-		HandleScope scope;
-		GaussianZiggurat* g = ObjectWrap::Unwrap<GaussianZiggurat>(args.This());
-	    double deviation;
-		if(args.Length() == 0){
-			 deviation = 3;
-		}else{
-			 deviation = args[0]->NumberValue();
-		}
-		double val = gsl_ran_gaussian_ziggurat(g->_gsl_rng, deviation);
-		return scope.Close(Number::New(val));
-	}
-
-};
-
 Handle<Value> ranGaussianRatioMethod(const Arguments& args)
 {
 	double deviation;
@@ -162,69 +62,13 @@ Handle<Value> ranGaussianRatioMethod(const Arguments& args)
 	return Number::New(val);
 }
 
-class GaussianRatioMethod: public ObjectWrap
-{
-private:
-	gsl_rng *_gsl_rng;
-public:
-	int seed;
-	static Persistent<FunctionTemplate> s_ct;
-	static void Init(Handle<Object> target)
-	{
-		HandleScope scope;
-		Local<FunctionTemplate> t = FunctionTemplate::New(New);
-		s_ct = Persistent<FunctionTemplate>::New(t);
-		s_ct->InstanceTemplate()->SetInternalFieldCount(1);
-		s_ct->SetClassName(String::NewSymbol("GaussianRatioMethod"));
-		NODE_SET_PROTOTYPE_METHOD(s_ct, "next", Next);
-		target->Set(String::NewSymbol("RanGaussianRatioMethod"), s_ct->GetFunction());
-	}
-	~GaussianRatioMethod()
-	{
-		gsl_rng_free(this->_gsl_rng);
-	}
-	static Handle<Value> New(const Arguments& args)
-	{
-		HandleScope scope;
-		GaussianRatioMethod* g = new GaussianRatioMethod();
-		g->Wrap(args.This());
-		g->_gsl_rng = gsl_rng_alloc (gsl_rng_default);
-		if(args.Length() == 1){
-			g->seed = args[0]->Uint32Value();
-		    gsl_rng_set(g->_gsl_rng, g->seed);
-		}
-		return args.This();
-	}
-
-	static Handle<Value> Next(const Arguments& args)
-	{
-		HandleScope scope;
-		GaussianRatioMethod* g = ObjectWrap::Unwrap<GaussianRatioMethod>(args.This());
-	    double deviation;
-		if(args.Length() == 0){
-			 deviation = 3;
-		}else{
-			 deviation = args[0]->NumberValue();
-		}
-		double val = gsl_ran_gaussian_ratio_method(g->_gsl_rng, deviation);
-		return scope.Close(Number::New(val));
-	}
-
-};
-
-Persistent<FunctionTemplate> Gaussian::s_ct;
-Persistent<FunctionTemplate> GaussianZiggurat::s_ct;
-Persistent<FunctionTemplate> GaussianRatioMethod::s_ct;
 extern "C" {
 	static void gaussian_init(Handle<Object> target)
 	{
 		HandleScope scope;
 		target->Set(String::New("ranGaussian"), FunctionTemplate::New(ranGaussian)->GetFunction());
-	    Gaussian::Init(target);
 		target->Set(String::New("ranGaussianZiggurat"), FunctionTemplate::New(ranGaussianZiggurat)->GetFunction());
-		GaussianZiggurat::Init(target);
 		target->Set(String::New("ranGaussianRatioMethod"), FunctionTemplate::New(ranGaussianRatioMethod)->GetFunction());
-		GaussianRatioMethod::Init(target);
 	}
 }
 
diff --git a/src/gsl.cc b/src/gsl.cc
index b3ffe9e..98fceeb 100644
--- a/src/gsl.cc
+++ b/src/gsl.cc
@@ -16,6 +16,7 @@
 using namespace node;
 using namespace v8;
 
+Persistent<FunctionTemplate> Random::s_ct;
 extern "C" {
 	static void init (Handle<Object> target)
 	{
diff --git a/src/random.cc b/src/random.cc
index 45fc228..a80a97d 100644
--- a/src/random.cc
+++ b/src/random.cc
@@ -35,7 +35,16 @@ Handle<Value> rngMax(const Arguments& args)
 	return Int32::NewFromUnsigned(val);
 }
 
-class RngGet: public ObjectWrap
+Handle<Value> rngUniform(const Arguments& args)
+{
+	if(args.Length() == 1){
+		gsl_rng_set (r_global, args[0]->Uint32Value());
+	}
+	double val = gsl_rng_uniform(r_global);
+	return Number::New(val);
+}
+
+class Random: public ObjectWrap
 {
 private:
 	gsl_rng *_gsl_rng;
@@ -48,92 +57,85 @@ class RngGet: public ObjectWrap
 		Local<FunctionTemplate> t = FunctionTemplate::New(New);
 		s_ct = Persistent<FunctionTemplate>::New(t);
 		s_ct->InstanceTemplate()->SetInternalFieldCount(1);
-		s_ct->SetClassName(String::NewSymbol("RngGet"));
-		NODE_SET_PROTOTYPE_METHOD(s_ct, "next", Next);
-		target->Set(String::NewSymbol("RngGet"), s_ct->GetFunction());
+		s_ct->SetClassName(String::NewSymbol("Random"));
+		NODE_SET_PROTOTYPE_METHOD(s_ct, "get", Get);
+		NODE_SET_PROTOTYPE_METHOD(s_ct, "uniform", Uniform);
+		NODE_SET_PROTOTYPE_METHOD(s_ct, "gaussian", Gaussian);
+		NODE_SET_PROTOTYPE_METHOD(s_ct, "gaussianZiggurat", GaussianZiggurat);
+		NODE_SET_PROTOTYPE_METHOD(s_ct, "gaussianRatioMethod", GaussianRatioMethod);
+		target->Set(String::NewSymbol("Random"), s_ct->GetFunction());
 	}
-	~RngGet()
+	~Random()
 	{
 		gsl_rng_free(this->_gsl_rng);
 	}
 	static Handle<Value> New(const Arguments& args)
 	{
 		HandleScope scope;
-		RngGet* g = new RngGet();
-		g->Wrap(args.This());
+		Random* g = new Random();
+		g->Wrap(args.Holder());
 		g->_gsl_rng = gsl_rng_alloc(gsl_rng_default);
 		if(args.Length() == 1){
 			g->seed = args[0]->Uint32Value();
 		    gsl_rng_set(g->_gsl_rng, g->seed);
 		}
-		return args.This();
+		return args.Holder();
 	}
-
-	static Handle<Value> Next(const Arguments& args)
+	static Handle<Value> Get(const Arguments& args)
 	{
 		HandleScope scope;
-		RngGet* g = ObjectWrap::Unwrap<RngGet>(args.This());
+		Random* g = ObjectWrap::Unwrap<Random>(args.Holder());
 		unsigned int val = gsl_rng_get(g->_gsl_rng);
 		return scope.Close(Int32::NewFromUnsigned(val));
 	}
-
-};
-
-Handle<Value> rngUniform(const Arguments& args)
-{
-	if(args.Length() == 1){
-		gsl_rng_set (r_global, args[0]->Uint32Value());
-	}
-	double val = gsl_rng_uniform(r_global);
-	return Number::New(val);
-}
-
-class RngUniform: public ObjectWrap
-{
-private:
-	gsl_rng *_gsl_rng;
-public:
-	int seed;
-	static Persistent<FunctionTemplate> s_ct;
-	static void Init(Handle<Object> target)
+	static Handle<Value> Uniform(const Arguments& args)
 	{
 		HandleScope scope;
-		Local<FunctionTemplate> t = FunctionTemplate::New(New);
-		s_ct = Persistent<FunctionTemplate>::New(t);
-		s_ct->InstanceTemplate()->SetInternalFieldCount(1);
-		s_ct->SetClassName(String::NewSymbol("RngUniform"));
-		NODE_SET_PROTOTYPE_METHOD(s_ct, "next", Next);
-		target->Set(String::NewSymbol("RngUniform"), s_ct->GetFunction());
+		Random* g = ObjectWrap::Unwrap<Random>(args.Holder());
+		double val = gsl_rng_uniform(g->_gsl_rng);
+		return scope.Close(Number::New(val));
 	}
-	~RngUniform()
+	static Handle<Value> Gaussian(const Arguments& args)
 	{
-		gsl_rng_free(this->_gsl_rng);
+		HandleScope scope;
+		Random* g = ObjectWrap::Unwrap<Random>(args.Holder());
+	    double deviation;
+		if(args.Length() == 0){
+			 deviation = 3;
+		}else{
+			 deviation = args[0]->NumberValue();
+		}
+		double val = gsl_ran_gaussian(g->_gsl_rng, deviation);
+		return scope.Close(Number::New(val));
 	}
-	static Handle<Value> New(const Arguments& args)
+	static Handle<Value> GaussianZiggurat(const Arguments& args)
 	{
 		HandleScope scope;
-		RngUniform* g = new RngUniform();
-		g->Wrap(args.This());
-		g->_gsl_rng = gsl_rng_alloc(gsl_rng_default);
-		if(args.Length() == 1){
-			g->seed = args[0]->Uint32Value();
-		    gsl_rng_set(g->_gsl_rng, g->seed);
+		Random* g = ObjectWrap::Unwrap<Random>(args.Holder());
+	    double deviation;
+		if(args.Length() == 0){
+			 deviation = 3;
+		}else{
+			 deviation = args[0]->NumberValue();
 		}
-		return args.This();
+		double val = gsl_ran_gaussian_ziggurat(g->_gsl_rng, deviation);
+		return scope.Close(Number::New(val));
 	}
-
-	static Handle<Value> Next(const Arguments& args)
+	static Handle<Value> GaussianRatioMethod(const Arguments& args)
 	{
 		HandleScope scope;
-		RngUniform* g = ObjectWrap::Unwrap<RngUniform>(args.This());
-		double val = gsl_rng_uniform(g->_gsl_rng);
+		Random* g = ObjectWrap::Unwrap<Random>(args.Holder());
+	    double deviation;
+		if(args.Length() == 0){
+			 deviation = 3;
+		}else{
+			 deviation = args[0]->NumberValue();
+		}
+		double val = gsl_ran_gaussian_ratio_method(g->_gsl_rng, deviation);
 		return scope.Close(Number::New(val));
 	}
-
 };
 
-Persistent<FunctionTemplate> RngGet::s_ct;
-Persistent<FunctionTemplate> RngUniform::s_ct;
 extern "C" {
 	static void random_init(Handle<Object> target)
 	{
@@ -141,9 +143,8 @@ extern "C" {
 		target->Set(String::New("rngGet"), FunctionTemplate::New(rngGet)->GetFunction());
 		target->Set(String::New("rngMin"), FunctionTemplate::New(rngMin)->GetFunction());
 		target->Set(String::New("rngMax"), FunctionTemplate::New(rngMax)->GetFunction());
-		RngGet::Init(target);
 		target->Set(String::New("rngUniform"), FunctionTemplate::New(rngUniform)->GetFunction());
-		RngUniform::Init(target);
+		Random::Init(target);
 	}
 }
 
diff --git a/test/gaussian.js b/test/gaussian.js
index a2225f1..20e3211 100644
--- a/test/gaussian.js
+++ b/test/gaussian.js
@@ -14,28 +14,21 @@ module.exports = {
 		assert.eql(100, Object.keys(results).length);
 	},
 	'Test gaussian - function with seed': function(){
-		var results1 = {};
+		var results1 = {}, results2 = {};
 		for(var i=0;i<100;i++){
-			var random = gsl.random.gaussian(1978);
-			assert.ok( 'number', typeof random );
-			assert.ok( !isNaN(random) );
-			results1[ random ] = true;
+			results1[ gsl.random.gaussian(1978) ] = true;
 		}
-		var results2 = {};
 		for(var i=0;i<100;i++){
-			var random = gsl.random.gaussian(1978);
-			assert.ok( 'number', typeof random );
-			assert.ok( !isNaN(random) );
-			results2[ random ] = true;
+			results2[ gsl.random.gaussian(1978) ] = true;
 		}
 		assert.eql(1,Object.keys(results1).length);
 		assert.eql(results1,results2);
 	},
 	'Test gaussian - object': function(){
 		var results = {};
-		var obj = new gsl.random.Gaussian();
+		var obj = new gsl.Random();
 		for(var i=0;i<100;i++){
-			var random = obj.next();
+			var random = obj.gaussian();
 			assert.ok( 'number', typeof random );
 			assert.ok( !isNaN(random) );
 			results[ random ] = true;
@@ -43,15 +36,14 @@ module.exports = {
 		assert.eql(100, Object.keys(results).length);
 	},
 	'Test gaussian - object with seed': function(){
-		var results1 = {};
-		var obj1 = new gsl.random.Gaussian(1978);
+		var results1 = {}, results2 = {};
+		var obj1 = new gsl.Random(1978);
 		for(var i=0;i<100;i++){
-			results1[ obj1.next() ] = true;
+			results1[ obj1.gaussian() ] = true;
 		}
-		var results2 = {};
-		var obj2 = new gsl.random.Gaussian(1978);
+		var obj2 = new gsl.Random(1978);
 		for(var i=0;i<100;i++){
-			results2[ obj2.next() ] = true;
+			results2[ obj2.gaussian() ] = true;
 		}
 		assert.eql(100,Object.keys(results1).length);
 		assert.eql(results1,results2);
@@ -67,28 +59,21 @@ module.exports = {
 		assert.eql(100, Object.keys(results).length);
 	},
 	'Test gaussian ziggurat - function with seed': function(){
-		var results1 = {};
+		var results1 = {}, results2 = {};
 		for(var i=0;i<100;i++){
-			var random = gsl.random.gaussianZiggurat(1978);
-			assert.ok( 'number', typeof random );
-			assert.ok( !isNaN(random) );
-			results1[ random ] = true;
+			results1[ gsl.random.gaussianZiggurat(1978) ] = true;
 		}
-		var results2 = {};
 		for(var i=0;i<100;i++){
-			var random = gsl.random.gaussianZiggurat(1978);
-			assert.ok( 'number', typeof random );
-			assert.ok( !isNaN(random) );
-			results2[ random ] = true;
+			results2[ gsl.random.gaussianZiggurat(1978) ] = true;
 		}
 		assert.eql(1,Object.keys(results1).length);
 		assert.eql(results1,results2);
 	},
 	'Test gaussian ziggurat - object': function(){
 		var results = {};
-		var obj = new gsl.random.GaussianZiggurat();
+		var obj = new gsl.Random();
 		for(var i=0;i<100;i++){
-			var random = obj.next();
+			var random = obj.gaussianZiggurat();
 			assert.ok( 'number', typeof random );
 			assert.ok( !isNaN(random) );
 			results[ random ] = true;
@@ -96,15 +81,14 @@ module.exports = {
 		assert.eql(100, Object.keys(results).length);
 	},
 	'Test gaussian ziggurat - object with seed': function(){
-		var results1 = {};
-		var obj1 = new gsl.random.GaussianZiggurat(1978);
+		var results1 = {}, results2 = {};
+		var obj1 = new gsl.Random(1978);
 		for(var i=0;i<100;i++){
-			results1[ obj1.next() ] = true;
+			results1[ obj1.gaussianZiggurat() ] = true;
 		}
-		var results2 = {};
-		var obj2 = new gsl.random.GaussianZiggurat(1978);
+		var obj2 = new gsl.Random(1978);
 		for(var i=0;i<100;i++){
-			results2[ obj2.next() ] = true;
+			results2[ obj2.gaussianZiggurat() ] = true;
 		}
 		assert.eql(100,Object.keys(results1).length);
 		assert.eql(results1,results2);
@@ -120,28 +104,21 @@ module.exports = {
 		assert.eql(100, Object.keys(results).length);
 	},
 	'Test gaussian ratio method - function with seed': function(){
-		var results1 = {};
+		var results1 = {}, results2 = {};
 		for(var i=0;i<100;i++){
-			var random = gsl.random.gaussianRatioMethod(1978);
-			assert.ok( 'number', typeof random );
-			assert.ok( !isNaN(random) );
-			results1[ random ] = true;
+			results1[ gsl.random.gaussianRatioMethod(1978) ] = true;
 		}
-		var results2 = {};
 		for(var i=0;i<100;i++){
-			var random = gsl.random.gaussianRatioMethod(1978);
-			assert.ok( 'number', typeof random );
-			assert.ok( !isNaN(random) );
-			results2[ random ] = true;
+			results2[ gsl.random.gaussianRatioMethod(1978) ] = true;
 		}
 		assert.eql(1,Object.keys(results1).length);
 		assert.eql(results1,results2);
 	},
 	'Test gaussian ratio method - object': function(){
 		var results = {};
-		var obj = new gsl.random.GaussianRatioMethod();
+		var obj = new gsl.Random();
 		for(var i=0;i<100;i++){
-			var random = obj.next();
+			var random = obj.gaussianRatioMethod();
 			assert.ok( 'number', typeof random );
 			assert.ok( !isNaN(random) );
 			results[ random ] = true;
@@ -149,15 +126,14 @@ module.exports = {
 		assert.eql(100, Object.keys(results).length);
 	},
 	'Test gaussian ratio method - object with seed': function(){
-		var results1 = {};
-		var obj1 = new gsl.random.GaussianRatioMethod(1978);
+		var results1 = {}, results2 = {};
+		var obj1 = new gsl.Random(1978);
 		for(var i=0;i<100;i++){
-			results1[ obj1.next() ] = true;
+			results1[ obj1.gaussianRatioMethod() ] = true;
 		}
-		var results2 = {};
-		var obj2 = new gsl.random.GaussianRatioMethod(1978);
+		var obj2 = new gsl.Random(1978);
 		for(var i=0;i<100;i++){
-			results2[ obj2.next() ] = true;
+			results2[ obj2.gaussianRatioMethod() ] = true;
 		}
 		assert.eql(100,Object.keys(results1).length);
 		assert.eql(results1,results2);
diff --git a/test/random.js b/test/random.js
index fe8aede..23943ee 100644
--- a/test/random.js
+++ b/test/random.js
@@ -26,14 +26,13 @@ module.exports = {
 		assert.eql(100, Object.keys(results).length);
 	},
 	'Test get - function with seed': function(){
-		var results1 = {};
+		var results1 = {}, results2 = {};
 		for(var i=0;i<100;i++){
 			var random = gsl.random.get(1978);
 			assert.ok( 'number', typeof random );
 			assert.ok( !isNaN(random) );
 			results1[ random ] = true;
 		}
-		var results2 = {};
 		for(var i=0;i<100;i++){
 			var random = gsl.random.get(1978);
 			assert.ok( 'number', typeof random );
@@ -45,9 +44,9 @@ module.exports = {
 	},
 	'Test get - object': function(){
 		var results = {};
-		var obj = new gsl.random.Get();
+		var obj = new gsl.Random();
 		for(var i=0;i<100;i++){
-			var random = obj.next();
+			var random = obj.get();
 			assert.ok( 'number', typeof random );
 			assert.ok( !isNaN(random) );
 			results[ random ] = true;
@@ -55,15 +54,14 @@ module.exports = {
 		assert.eql(100, Object.keys(results).length);
 	},
 	'Test get - object with seed': function(){
-		var results1 = {};
-		var obj1 = new gsl.random.Get(1978);
+		var results1 = {}, results2 = {};
+		var obj1 = new gsl.Random(1978);
 		for(var i=0;i<100;i++){
-			results1[ obj1.next() ] = true;
+			results1[ obj1.get() ] = true;
 		}
-		var results2 = {};
-		var obj2 = new gsl.random.Get(1978);
+		var obj2 = new gsl.Random(1978);
 		for(var i=0;i<100;i++){
-			results2[ obj2.next() ] = true;
+			results2[ obj2.get() ] = true;
 		}
 		assert.eql(100,Object.keys(results1).length);
 		assert.eql(results1,results2);
@@ -80,28 +78,21 @@ module.exports = {
 		assert.eql(100, Object.keys(results).length);
 	},
 	'Test uniform - function with seed': function(){
-		var results1 = {};
+		var results1 = {}, results2 = {};
 		for(var i=0;i<100;i++){
-			var random = gsl.random.uniform(1978);
-			assert.ok( 'number', typeof random );
-			assert.ok( !isNaN(random) );
-			results1[ random ] = true;
+			results1[ gsl.random.uniform(1978) ] = true;
 		}
-		var results2 = {};
 		for(var i=0;i<100;i++){
-			var random = gsl.random.uniform(1978);
-			assert.ok( 'number', typeof random );
-			assert.ok( !isNaN(random) );
-			results2[ random ] = true;
+			results2[ gsl.random.uniform(1978) ] = true;
 		}
 		assert.eql(1,Object.keys(results1).length);
 		assert.eql(results1,results2);
 	},
 	'Test uniform - object': function(){
 		var results = {};
-		var obj = new gsl.random.Uniform();
+		var obj = new gsl.Random();
 		for(var i=0;i<100;i++){
-			var random = obj.next();
+			var random = obj.uniform();
 			assert.ok( 'number', typeof random );
 			assert.ok( !isNaN(random) );
 			results[ random ] = true;
@@ -109,15 +100,14 @@ module.exports = {
 		assert.eql(100, Object.keys(results).length);
 	},
 	'Test uniform - object with seed': function(){
-		var results1 = {};
-		var obj1 = new gsl.random.Uniform(1978);
+		var results1 = {}, results2 = {};
+		var obj1 = new gsl.Random(1978);
 		for(var i=0;i<100;i++){
-			results1[ obj1.next() ] = true;
+			results1[ obj1.uniform() ] = true;
 		}
-		var results2 = {};
-		var obj2 = new gsl.random.Uniform(1978);
+		var obj2 = new gsl.Random(1978);
 		for(var i=0;i<100;i++){
-			results2[ obj2.next() ] = true;
+			results2[ obj2.uniform() ] = true;
 		}
 		assert.eql(100,Object.keys(results1).length);
 		assert.eql(results1,results2);