Rob robianmcd

## gist:f70cee03cdb94dbfc1cd5dea2836c269
Equations

Equations are what really gives MSS it's power. You could be able to cover most of the basic things you want to do with MSS just using the presets but if you want to do something more advanced you'll need to learn to write some equations. This page provides a reference to the various operators, variables, constants, and functions available to you while creating an equation.

Operators

| Operator | Name | Description | Example | Result |
|:-------------|:---------|:----------------|:------------|:-----------|
| a + b | Addition | | 1 + 2 | 3 |
| a - b | Subtraction | | 3 - 1 | 2 |

## built-in-variables.md

      
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                robianmcd
                / built-in-variables.md
            
            
              Created
              July 25, 2017 21:41
            
          
Name
Description


x, input
These variables represent the input value from the an incoming message. The value taken from the incoming message is specified by the Input dropdown menu under the transformation graph. For example if the input message type is Note and the "velocity" is selected in the input dropdown then "x" or "input" will be the velocity of an incoming note. This value will be between 0 and 1.


d1, chan, channel
The first piece of data in an incoming message. For a MIDI message this will be the channel. You should use the "input" variable instead of this unless you need to use multiple types of input (e.g. velocity and channel). This value will be between 0 and 1.


d2, notenum, ccnum
The second piece of data in an incoming message. For a MIDI note message this will be the note number. You should use the "input" variable instead of this unless you need to use multiple types of input (e.g. velocity and note number). This value will be between 0 an


## model.py
import numpy
import pandas
from keras.models import Sequential
from keras.layers import Dense
from keras.wrappers.scikit_learn import KerasClassifier
from sklearn.model_selection import cross_val_score
from sklearn.preprocessing import LabelEncoder
from sklearn.model_selection import StratifiedKFold
from sklearn.preprocessing import StandardScaler
from sklearn.pipeline import Pipeline

## server.js
let express = require('express');
let app = express();
let path = require('path');

app.use(express.static(path.join(__dirname, '.')));

app.all('/*', function (req, res) {
    res.sendFile('index.html', {root: __dirname});
});

## server.js
/**
 * Module dependencies.
 */
var express = require('express');
var https = require('https');
var path = require('path');
var fs = require('fs');

var httpProxy = require('http-proxy');
//Solution for forwarding from http to https taken from

## index.html
<!DOCTYPE html>
<html>
<head lang="en">
    <meta charset="UTF-8">
    <title></title>
</head>
<body>
    <input id="myInput" type="checkbox"/>

    <script>

## license
var app = angular.module('myApp');
app.run(['$q', '$window', function($q, $window) {
	$window.Promise = function(executor) {
		return $q(executor);
	};

	$window.Promise.all = $q.all.bind($q);
	$window.Promise.reject = $q.reject.bind($q);
	$window.Promise.resolve = $q.when.bind($q);
	Equations

	Equations are what really gives MSS it's power. You could be able to cover most of the basic things you want to do with MSS just using the presets but if you want to do something more advanced you'll need to learn to write some equations. This page provides a reference to the various operators, variables, constants, and functions available to you while creating an equation.

	Operators

	\| Operator \| Name \| Description \| Example \| Result \|
	\|:-------------\|:---------\|:----------------\|:------------\|:-----------\|
	\| a + b \| Addition \| \| 1 + 2 \| 3 \|
	\| a - b \| Subtraction \| \| 3 - 1 \| 2 \|
Name	Description
x, input	These variables represent the input value from the an incoming message. The value taken from the incoming message is specified by the Input dropdown menu under the transformation graph. For example if the input message type is Note and the "velocity" is selected in the input dropdown then "x" or "input" will be the velocity of an incoming note. This value will be between 0 and 1.
d1, chan, channel	The first piece of data in an incoming message. For a MIDI message this will be the channel. You should use the "input" variable instead of this unless you need to use multiple types of input (e.g. velocity and channel). This value will be between 0 and 1.
d2, notenum, ccnum	The second piece of data in an incoming message. For a MIDI note message this will be the note number. You should use the "input" variable instead of this unless you need to use multiple types of input (e.g. velocity and note number). This value will be between 0 an
	import numpy
	import pandas
	from keras.models import Sequential
	from keras.layers import Dense
	from keras.wrappers.scikit_learn import KerasClassifier
	from sklearn.model_selection import cross_val_score
	from sklearn.preprocessing import LabelEncoder
	from sklearn.model_selection import StratifiedKFold
	from sklearn.preprocessing import StandardScaler
	from sklearn.pipeline import Pipeline
	let express = require('express');
	let app = express();
	let path = require('path');

	app.use(express.static(path.join(__dirname, '.')));

	app.all('/*', function (req, res) {
	res.sendFile('index.html', {root: __dirname});
	});
	/**
	* Module dependencies.
	*/
	var express = require('express');
	var https = require('https');
	var path = require('path');
	var fs = require('fs');

	var httpProxy = require('http-proxy');
	//Solution for forwarding from http to https taken from
	<!DOCTYPE html>
	<html>
	<head lang="en">
	<meta charset="UTF-8">
	<title></title>
	</head>
	<body>
	<input id="myInput" type="checkbox"/>

	<script>
	var app = angular.module('myApp');
	app.run(['$q', '$window', function($q, $window) {
	$window.Promise = function(executor) {
	return $q(executor);
	};

	$window.Promise.all = $q.all.bind($q);
	$window.Promise.reject = $q.reject.bind($q);
	$window.Promise.resolve = $q.when.bind($q);