User Guide for the PSLab Remote-Access Framework

The remote-lab framework of the pocket science lab has been designed to enable user to access their devices remotely via the internet. The pslab-remote repository includes an API server built with Python-Flask and a webapp that uses EmberJS. This post is a guide for users who wish to test the framework. A series of blog posts have been previously written which have explored and elaborated various aspect of the remote-lab such as designing the API server, remote execution of function strings, automatic deployment on various domains etc. In this post, we shall explore how to execute function strings, execute example scripts, and write a script ourselves.

A live demo is hosted at . The API server is hosted at, and an API reference which is being developed can be accessed at . A screencast of the remote lab is also available

Create an account

Signing up at this point is very straightforward, and does not include any third party verification tools since the framework is under active development, and cannot be claimed to be ready for release yet.

Click on the sign-up button, and provide a username, email, and password. The e-mail will be used as the login-id, and needs to be unique.

Login to the remote lab

Use the email-id used for signing up, enter the password, and the app will redirect you to your new home-page, where you will be greeted with a similar screen.

Your home-page

On the home-page, you will find that the first section includes a text box for entering a function string, and an execute button. Here, you can enter any valid PSLab function such as `get_resistance()` , and click on the execute button in order to run the function on the PSLab device connected to the API server, and view the results. A detailed blog post on this process can be found here.

Since this is a new account, no saved scripts are present in the Your Scripts section. We will come to that shortly, but for now, there are some pre-written example scripts that will let you test them as well as view their source code in order to copy into your own collection, and modify them.

Click on the play icon next to `` in order to run the script. The eye icon to the right of the row enables you to view the source code, but this can also be done while the app is running. The multimeter app looks something like this, and you can click on the various buttons to try them out.

You may also click on the Source Code tab in order to view the source

Create and execute a small python script

We can now try to create a simple script of our own. Click on the `New Python Script` button in the top-bar to navigate to a page that will allow you to create and save your own scripts. We shall write a small 3-line code to print some sinusoidal coordinates, save it, and test it. Copy the following code for a sine wave with 30 points, and publish your script.

import numpy as np
print (x, np.sin(x))

Create a button widget and associate a callback to the get_voltage function

A small degree of object oriented capabilities have also been added, and the pslab-remote allows you to create button widgets and associate their targets with other widgets and labels.
The multimeter demo script uses this feature, and a single line of code suffices to demonstrate this feature.

button('Voltage on CH1 >',"get_voltage('CH1')","display_number")

You can copy the above line into a new script in order to try it out.

Associate a button’s callback to the capture routines, and set the target as a plot

The callback target for a button can be set to point to a plot. This is useful if the callback involves arrays such as those returned by the capture routines.

Example code to show a sine wave in a plot, and make button which will replace it with captured data from the oscilloscope:

import numpy as np
plt = plot(x, np.sin(x))
button('capture 1',"capture1('CH1',100,10)","update-plot",target=plt)
Figure: Demo animation from the plot_test example. Capture1 is connected to the plot shown.

Creating an Elementary Oscilloscope in PSLab’s Remote Framework

The last couple of blog posts explained how we could put together the versatility of ember components, the visual appeal of jqplot, the flexibility of Python Flask, and the simplicity of Python itself in order to make simple scripts for PSLab that would could be run on a server by a remote client anywhere on the web. We have also seen how callbacks could be assigned to widgets created in these scripts in order to make object oriented applications. In this blog post, we shall see how to assign a capture method to a button, and update a plot with the received data. It will also demonstrate how to use ember-lodash to perform array manipulations.

Specifying the return data type in the callback success routine

For a more instructive write-up on assigning callbacks, please refer to these posts .

Whenever the callback assigned to a button is a function that returns an array of elements, and the target for the resultant data is a plot, the stacking order of the returned array must be specified in order to change its shape to suit the plotting library. The default return data from a capture routine (oscilloscope) is made up of separate arrays for X coordinate and Y coordinate values. Since JQplot requires [X,Y] pairs , we must specify a stacking order of ‘xy’ so that the application knows that it must convert them to pairs (using lodash/zip)  before passing the result to the plot widget. Similarly, different stacking orders for capture2, and capture4 must also be defined.

Creating an action that performs necessary array manipulations and plots the received data

It can be seen from the excerpt below, that if the onSuccess target for a callback is specified to be a plot in the actionDefinition object, then the stacking order is checked, and the returned data is modified accordingly

Relevant excerpt from controllers/user-home.js/runButtonAction

if (actionDefinition.success.type === 'update-plot') {
  if (actionDefinition.success.stacking === 'xy') {
    $.jqplot(, [zip(...resultValue)]).replot();
  } else if (actionDefinition.success.stacking === 'xyy') {
    $.jqplot(, [zip(...[resultValue[0], resultValue[1]]), zip(...[resultValue[0], resultValue[2]])]).replot();
  } else if (actionDefinition.success.stacking === 'xyyyy') {
    $.jqplot(, [zip(...[resultValue[0], resultValue[1]]), zip(...[resultValue[0], resultValue[2]]), zip(...[resultValue[0], resultValue[3]]), zip(...[resultValue[0], resultValue[4]])]).replot();
  } else {
    $.jqplot(, resultValue).replot();


With the above framework in place, we can add a plot with the line plt = plot(x, np.sin(x)) , and associate a button with a capture routine that will update its contents with a single line of code: button(‘capture1’,”capture1(‘CH1’,100,10)”,”update-plot”,target=plt)

Final Result

The following script created on the pslab-remote platform makes three buttons and plots, and sets the buttons to invoke capture1, capture2, and capture4 respectively when clicked.

import numpy as np
plt = plot(x, np.sin(x))
button('capture 1',"capture1('CH1',100,10)","update-plot",target=plt)

plt2 = plot(x, np.sin(x))
button('capture 2',"capture2(50,10)","update-plot",target=plt2,stacking='xyy')

plt3 = plot(x, np.sin(x))
button('capture 4',"capture4(50,10)","update-plot",target=plt3,stacking='xyyyy')















Including a Graph Component in the Remote Access Framework for PSLab

The remote-lab software of the pocket science lab enables users to access their devices remotely via the Internet. It includes an API server designed with Python Flask, and a web-app designed with EmberJS that allows users to access the API and carry out various tasks such as writing and executing Python scripts. In a series of blog posts, various aspects of this framework such as  remote execution of function strings, automatic deployment on various domains, creating and submitting python scripts which will be run on the remote server etc have already been explored.  This blog post deals with the inclusion of a graph component in the webapp that will be invoked when the user utilises the `plot` command in their scripts.

The JQPLOT library is being used for this purpose, and has been found to be quite lightweight and has a vast set of example code .

Task list for enabling the plotting feature
  • Add a plot method to the codeEvaluator module in the API server and allow access to it by adding it to the evalGlobals dictionary
  • Create an EmberJS component for handling plots
    • Create a named div in the template
    • Invoke the Jqplot initializer from the JS file and pass necessary arguments and data to the jqplot instance
  • Add a conditional statement to include the jqplot component whenever a plot subsection is present in the JSON object returned by the API server after executing a script
Adding a plot method to the API server

Thus far, in addition to the functions supported by the instance of PSLab, users had access to print, print_, and button functions. We shall now add a plot function.

def plot(self,x,y,**kwargs):


The X,Y datasets provided by the user are stacked in pairs because jqplot requires [x,y] pairs . not separate datasets.

We also need to add this to evalGlobals, so we shall modify the __init__ routine slightly:

Building an Ember component for handling plots

First, well need to install jqplot:   bower install –save jqplot

And this must be followed by including the following files using app.import statements in ember-cli-build.js

  • bower_components/jqplot/jquery.jqplot.min.js
  • bower_components/jqplot/plugins/jqplot.cursor.js
  • bower_components/jqplot/plugins/jqplot.highlighter.js
  • bower_components/jqplot/plugins/jqplot.pointLabels.js
  • bower_components/jqplot/jquery.jqplot.min.css

In addition to the jqplot js and css files, we have also included a couple of plugins we shall use later.

Now we need to set up a new component : ember g component jqplot-graph

Our component will accept an object as an input argument. This object will contain the various configuration options for the plot

Add the following line in templates/components/jqplot-graph.hbs:

style="solid gray 1px;" id="{{}}">

The JS file for this template must invoke the jqplot function in order to insert a complete plot into the previously defined <div> after it has been created. Therefore, the initialization routine must override the didInsertElement routine of the component.


import Ember from 'ember';

export default Ember.Component.extend({
  didInsertElement () {
        title: this.title,

        axes: {
          xaxis: {
            tickInterval: 1,
            rendererOptions: {
            minorTicks: 4
        highlighter: {
          show: true, 
          showLabel: true, 

          tooltipAxes: 'xy',
          sizeAdjust: 9.5 , tooltipLocation : 'ne'
        legend: {
          show: true,
          location: 'e',
          rendererOptions: {
            numberColumns: 1,
          show: true,


Our component is now ready to be used , and we must make the necessary changes to user-home.hbs in order to include the plot component if the output JSON of a script executed on the server contains it.

The following excerpt from the results modal shows how the plot component can be inserted

{{#each codeResults as |element|}}
	{{#if (eq element.type 'text')}}
	{{#if (eq element.type 'plot')}}
		{{jqplot-graph data=element}}

Most of the other components such as buttons and spans have been removed for clarity. Note that the element object is passed to the jqplot-graph component as an argument so that the component may configure itself accordingly.

In conclusion, the following screencast shows what we have created. A simple plot command creates a fancy plot in the output which includes data point highlighting, and can be easily configured to do a lot more. In the next blog post we shall explore how to use this plot to create a persistent application such as an oscilloscope.



Enhancing the Functionality of User Submitted Scripts in the PSLab-remote framework

The remote-lab framework of the pocket science lab enables users to access their devices remotely via the internet. Its design involves an API server built with Python-Flask and a webapp that uses EmberJS. This post is the latest in a series of blog posts which have explored and elaborated various aspect of the remote-lab such as designing the API server and testing with Postman, remote execution of function strings, automatic deployment on various domains etc. It also supports creating and submitting python scripts which will be run on the remote server, and the console output relayed to the webapp.

In this post, we shall take a look at how we can extend the functionality by providing support for object oriented code in user submitted scripts.

Let’s take an example of a Python script where the user wishes to create a button which when clicked will read a voltage via the API server, and display the value to the remote user. Clearly, an interpreter that only provides the console output is not enough for this task. We need the interpreter to generate an app structure that also includes callbacks for widgets such as buttons, and JSON objects are an obvious choice for relaying such a structure to the webapp.

In a nutshell, we had earlier created an API method that could execute a python script and return a string output, and now we will modify this method to return a JSON encoded structure which will be parsed by the webapp in order to display an output.

Let’s elaborate this with an example :

print ('testing')
print ('testing some changes..... ')
print_('highlighted print statement')


JSON returned by the API [localhost:8000/runScriptById] , for the above script:

{"Date": "Tue, 01 Aug 2017 21:39:12 GMT", "Filename": "", "Id": 4,
 "result": [
  {"name": "print", "type": "span", "value": "('testing',)"},
  {"name": "print", "type": "span", "value": "('testing some changes..... ',)"},
  {"class": "row well", "name": "print", "type": "span", "value": "highlighted print statement"}
"status": true}
Screenshot of the EmberJS webapp showing the output rendered with the above JSON

Adding Support for Widgets

In the previous section, we laid the groundwork for a flexible platform. Instead of returning a string, the webapp accepts a JSON object and parses it. We shall now add support for a clickable button which can be associated with a valid PSLab function.

An elementary JS twiddle has been made by Niranjan Rajendran which will help newbies to understand how to render dynamic templates via JSON objects retrieved from APIs. The twiddle uses two API endpoints; one to retrieve the compiled JSON output, and another to act as a voltmeter method which returns a voltage value.

To understand how this works in pslab-remote, consider a one line script called

button('get voltage',"get_voltage('CH1')")

The objective is to create a button with the text ‘get voltage’ on it , and which when clicked will run the command ‘get_voltage(‘CH1’)’ on the API server, and display the result.

When this script is run on the API server, it returns a JSON object with the following structure:

{"Date": "Tue, 01 Aug 2017 21:39:12 GMT", "Filename": "", "Id": 4,
 "result": [  {"type":"button","name":"button-id0","label":"get_voltage","fetched_value":"","action":{"type":"POST","endpoint":"get_voltage('CH1')","success":{"datapoint":'result',"type":"display_number", "target":"button-id0-label"}}},
  {"name": "button-id0label", "type": "label", "value": ""},
"status": true}

The above JSON object is parsed by the webapp’s user-home template, and a corresponding button and label are generated. The following section of code from user-home.hbs renders the JSON object

{{#each codeResults as |element|}}
  {{#if (eq element.type 'label')}}
    <label  id="{{}}" class="{{element.class}}">{{element.value}}</label>
  {{#if (eq element.type 'button')}}
    <button id="{{}}" {{action 'runButtonAction' element.action}}>{{element.label}}</button>

An action was also associated with the the created button, and this is the “get_voltage(‘CH1’)” string which we had specified in our one line script.

For the concluding section, we shall see how this action is invoked when the button is clicked, and how the returned value is used to update the contents of the label that was generated as part of this button.

Action defined in controllers/user-home.js :

runButtonAction(actionDefinition) {
  if(actionDefinition.type === 'POST') {
      .then(response => {
        const resultValue = Ember.get(response, actionDefinition.success.datapoint);
        if (actionDefinition.success.type === 'display_number') {
           Ember.$('#' +;

The action string is passed to the evalFunctionString endpoint of the API, and the contents are mapped to the display label.

Screencast of the above process

PSLab Remote Lab: Automatically deploying the EmberJS WebApp and Flask API Server to different domains

The remote-lab software of the pocket science lab enables users to access their devices remotely via the internet. Its design involves an API server designed with Python Flask, and a web-app designed with EmberJS that allows users to access the API and carry out various tasks such as writing and executing Python scripts. For testing purposes, the repository needed to be setup to deploy both the backend as well as the webapp automatically when a build passes, and this blog post deals with how this can be achieved.

Deploying the API server

The Heroku PaaS was chosen due to its ease of use with a wide range of server software, and support for postgresql databases. It can be configured to automatically deploy branches from github repositories, and conditions such as passing of a linked CI can also be included. The following screenshot shows the Heroku configuration page of an app called pslab-test1. Most of the configuration actions can be carried out offline via the Heroku-Cli


In the above page, the pslab-test1 has been set to deploy automatically from the master branch of . The wait for CI to pass before deploy has been disabled since a CI has not been setup on the repository.

Files required for Heroku to deploy automatically

Once the Heroku PaaS has copied the latest commit made to the linked repository, it searches the base directory for a configuration file called runtime.txt which contains details about the language of the app and the version of the compiler/interpretor to use, and a Procfile which contains the command to launch the app once it is ready. Since the PSLab’s API server is written in Python, we also have a requirements.txt which is a list of dependencies to be installed before launching the application.


web: gunicorn app:app –log-file –




flask >= 0.10.1

But wait, our app cannot run yet, because it requires a postgresql database, and we did not do anything to set up one. The following steps will set up a postgres database using the heroku-cli usable from your command prompt.

  • Point Heroku-cli to our app
    $ heroku git:remote -a pslab-test1
  • Create a postgres database under the hobby-dev plan available for free users.
    $ heroku addons:create heroku-postgresql:hobby-dev

    Creating heroku-postgresql:hobby-dev on ⬢ pslab-test1… free
    Database has been created and is available
    ! This database is empty. If upgrading, you can transfer
    ! data from another database with pg:copy
    Created postgresql-slippery-81404 as HEROKU_POSTGRESQL_CHARCOAL_URL
    Use heroku addons:docs heroku-postgresql to view documentation

  • The previous step created a database along with an environment variable HEROKU_POSTGRESQL_CHARCOAL_URL . As a shorthand, we can also refer to it simply as CHARCOAL .
  • In order to make it our primary database, it must be promoted

    $ heroku pg:promote HEROKU_POSTGRESQL_CHARCOAL_URL
    The database will now be available via the environment variable DATABASE_URL

  • Further documentation on creating and modifying postgres databases on Heroku can be found in the articles section .

At this point, if the app is in good shape, Heroku will automatically deploy its contents to We can test it using a developer tool such as Postman, or make our own webapp to use it.

Deploying the EmberJS WebApp

Since we are using the free plan on Heroku which only allows one dyno, our EmberJS webapp which shares the repository cannot be deployed on the same heroku server. Therefore, we must look for other domains where the frontend can be deployed. allows easy deployment of Ember apps, and we shall set up our CI’s configuration file .travis.yml to do this for us when a pull request is made, and the build passes

This excerpt from .travis.yml only shows parts relevant to deployment on

– pushd frontend
– bash
– popd

Once the build has passed, the after_success hook executes a script called which is located in the directory of the webapp.

Contents of

#!/usr/bin/env bash
if [ “$TRAVIS_PULL_REQUEST” == “false” ]; then
echo “Not a PR. Skipping surge deployment”
exit 0

ember build –environment=’production’


npm i -g surge

# Details of a dummy account. So can be added to vcs.
export SURGE_LOGIN=j********[email protected]
export SURGE_TOKEN=4********************************f
export DEPLOY_DOMAIN=https://${REPO_NAME}
surge –project ./dist –domain $DEPLOY_DOMAIN;

The variables SURGE_LOGIN and SURGE_TOKEN must be specified, otherwise Surge will open a login prompt, and since there is no way to feed details into a prompt in a Travis build, it will timeout and fail. The surge token can be obtained with a simple `surge login` followed by `surge token` on your system’s terminal.

Final Application

A user’s homepage on the webapp deployed at . The EmberJS app has been configured to send all AJAX requests to the API server located at .


Designing A Remote Laboratory With PSLab: execution of function strings

In the previous blog post, we introduced the concept of a ‘remote laboratory’, which would enable users to access the various features of the PSLab via the internet. Many aspects of the project were worked upon, which also involved creation of a web-app using EmberJS that enables users to create accounts , sign in, and prepare Python programs to be sent to the server for execution. A backend APi server based on Python-flask was also developed to handle these tasks, and maintain a postgresql database using sqlalchemy .

The following screencast shows the basic look and feel of the proposed remote lab running in a web browser.

This blog post will deal with implementing a way for the remote user to submit a simple function string, such as get_voltage(‘CH1’), and retrieve the results from the server.

There are three parts to this:
  • Creating a dictionary of the functions available in the sciencelab instance. The user will only be allowed access to these functions remotely, and we may protect some functions as the initialization and destruction routines by blocking them from the remote user
  • Creating an API method to receive a form containing the function string, execute the corresponding function from the dictionary, and reply with JSON data
  • Testing the API using the postman chrome extension
Creating a dictionary of functions :

The function dictionary maps function names against references to the actual functions from an instance of PSL.sciencelab . A simple dictionary containing just the get_voltage function can be generated in the following way:

from PSL import sciencelab
functionList = {'get_voltage':I.get_voltage}

This dictionary is then used with the eval method in order to evaluate a function string:

result = eval('get_voltage('CH1')',functionList)
print (result)

A more efficient way to create this list is to use the inspect module, and automatically extract all the available methods into a dictionary

functionList = {}
for a in dir(I):
	attr = getattr(I, a)
	if inspect.ismethod(attr) and a!='__init__':
		functionList[a] = attr

In the above, we have made a dictionary of all the methods except __init__

This approach can also be easily extrapolated to automatically generate a dictionary for inline documentation strings which can then be passed on to the web app.

Creating an API method to execute submitted function strings

We create an API method that accepts a form containing the function string and option that specifies if the returned value is to be formatted as a string or JSON data. A special case arises for numpy arrays which cannot be directly converted to JSON, and the toList function must first be used for them.

def evalFunctionString():
    if session.get('user'):
            _user = session.get('user')[1]
            _fn = request.form['function']
            _stringify = request.form.get('stringify',False)
            res = eval(_fn,functionList)
        except Exception as e:
            res = str(e)
        #dump string if requested. Otherwise json array
        if _stringify:
            return json.dumps({'status':True,'result':str(res),'stringified':True})
            #Try to simply convert the results to json
                return json.dumps({'status':True,'result':res,'stringified':False})
            # If that didn't work, it's due to the result containing numpy arrays.
            except Exception as e:
                #try to convert the numpy arrays to json using the .toList() function
                    return json.dumps({'status':True,'result':np.array(res).tolist(),'stringified':False})
                #And if nothing works, return the string
                except Exception as e:
                    print( 'string return',str(e))
                    return json.dumps({'status':True,'result':str(res),'stringified':True})
        return json.dumps({'status':False,'result':'unauthorized access','message':'Unauthorized access'})
Testing the API using Postman

The postman chrome extension allows users to submit forms to API servers, and view the raw results. It supports various encodings, and is quite handy for testing purposes.Before executing these via the evalFunctionString method, user credentials must first be submitted to the validateLogin method for authentication purposes.

Here are screenshots of the test results from a ‘get_voltage(‘CH1’)’ and ‘capture1(‘CH1’,20,1)’ function executed remotely via postman.


Our next steps will be to implement the dialog box in the frontend that will allow users to quickly type in function strings, and fetch the resultant data



Designing a Remote Laboratory with PSLab using Python Flask Framework

In the introductory post about remote laboratories, a general set of tools to create a framework and handle its various aspects was also introduced. In this blog post, we will explore the implementation of several aspects of the backend app designed with python-flask, and the frontend based on EmberJS. A clear separation of the frontend and backend facilitates minimal disruption of either sections due to the other.

Implementing API methods in Python-Flask

In the Flask web server, page requests are handled via ‘routes’ , which are essentially URLs linked to a python function. Routes are also capable of handling payloads such as POST data, and various return types are also supported.

We shall use an example to demonstrate how a Sign-Up request sent from the sign-up form in the remote lab frontend for PSLab is handled.

def signUp():
	"""Sign Up for Virtual Lab

	POST: Submit sign-up parameters. The following must be present:
	 inputName : The name of your account. does not need to be unique
	 inputEmail : e-mail ID used for login . must be unique.
	 inputPassword: password .
	Returns HTTP 404 when data does not exist.
	# read the posted values from the UI
	_name = request.form['inputName']
	_email = request.form['inputEmail']
	_password = request.form['inputPassword']

	# validate the received values
	if _name and _email and _password:
		_hashed_password = generate_password_hash(_password)
		newUser = User(_email, _name,_hashed_password)
			return json.dumps({'status':True,'message':'User %s created successfully. e-mail:%s !'%(_name,_email)})
		except Exception as exc:
			reason = str(exc)
			return json.dumps({'status':False,'message':str(reason)})


In this example, the first line indicates that all URL requests made to <domain:port>/signUp will be handled by the function signUp . During development, we host the server on localhost, and use the default PORT number 8000, so sign-up forms must be submitted to .

For deployment on a globally accessible server, a machine with a static IP, and a DNS record must be used. An example for such a deployment would be the heroku subdomain where pslab-remote is automatically deployed ;

A closer look at the above example will tell you that POST data can be accessed via the request.form dictionary, and that the sign-up routine requires inputName,inputEmail, and inputPassword. A password hash is generated before writing the parameters to the database.

Testing API methods using the Postman chrome extension

The route described in the above example requires form data to be submitted along with the URL, and we will use a rather handy developer tool called Postman to help us do this. In the frontend apps , AJAX methods are usually employed to do such tasks as well as handle the response from the server.


The above screenshot shows Postman being used to submit form data to /signUp on our API server running at localhost:8000 . The fields inputName, inputDescription, and inputPassword are also posted along with it.

In the bottom section, one can see that the server returned a positive status variable, as well as a descriptive message.

Submitting the sign up form via an Ember controller.
  • Setting up a template
    We first need to set up a template that we shall call sign-up.hbs , and add the following form to it. This form contains the details essential for signing up , and its submit action is linked to an action called `signMeUp` . This action will be defined in the controller which we shall explore shortly

<form class="form-signin" {{action "signMeUp" on="submit"}} >
        <label for="inputName" class="sr-only">Your Name</label>
        {{input value=inputName type="text" name="inputName" id="inputName" class="form-control" placeholder="name" required=true autofocus=true}}
        <label for="inputEmail" class="sr-only">Email address</label>
        {{input value=inputEmail type="email" name="inputEmail" id="inputEmail" class="form-control" placeholder="Email address" required=true autofocus=true}}
        <label for="inputPassword" class="sr-only">Password</label>
        {{input value=inputPassword type="password" name="inputPassword" id="inputPassword" class="form-control" placeholder="Password" required=true autofocus=true}}
        <button class="btn btn-lg btn-primary btn-block" type="submit">Sign Up</button>


  • Defining the controller
    The controller contains the actions and variables that the template links to. In this case, we require an action called signMeUp. The success, failure, and error handlers are hidden for clarity.

import Ember from 'ember';
export default Ember.Controller.extend({
    signMeUp() {
        var request = Ember.$.post("/signUp",
        request.then(this.success.bind(this), this.failure.bind(this),

The signMeUp action submits the contents of the form to the signUp route on the API server, and the results are handled by functions called success, failure, or error depending on the type of response from the backend server.



Calibrating the PSLab’s Analog Features for Maximum Accuracy

The hardware design of the PSLab aims to achieve the maximum possible performance from a very conservative bill of materials. There are several analog components such as Op-amps, voltage dividers, and level-shifters involved in input signal processing that have inherent offsets and slopes that must be corrected in order get the best results. Similarly, some analog output signals from the PSLab are also modified by buffers, amplifiers, and level shifting circuits.

One way to improve the initial accuracy is to choose high performance analog components that are factory calibrated , and do not require any additional correction to achieve error margins that are less than the least count of the PSLab’s measurement capabilities. However, such components such as laser trimmed resistor pairs, and low-offset Op-Amps are quite expensive, and we must instead use software based correction methods to achieve similar performance from affordable parts.

Identifying a suitable calibrator for analog signals

In order to calibrate a device, we must first own a similar device whose measurements we can trust, and which has a finer resolution that the PSLab itself. Calibration is a one-time task that will quantify and store the gain and offset errors, and these errors are not expected to behave very differently unless a significant change in temperature, or mechanical stress is experienced.

Such a device may be as expensive as 24-bit, research-grade multimeters which generally cost upwards of $500 , or can be inexpensive analog to digital convertors that might require some expertise to extract data from them, but can still be used for calibration.

Fortunately, we have been able to identify a cheaply available device that puts the calibration process within the reach and capabilities of the end user. The ADS1115 16-bit ADC is a 4-channel, 0-3.3V ADC that can be interfaced via I2C. Typical initial accuracy of the internal voltage reference 0.01% and data rates higher than 500SPS are possible. It is cost effective, and is available in convenient module formats that can be directly plugged into the PSLab itself. It can be purchased through various vendors ( A , B , C )

Therefore, it appears to be most suited to calibrate individual PSLab devices.

Basic requirements for the calibration process

The process to calibrate the analog inputs and outputs involves looping them externally , and monitoring the actual values via the external calibrator.

We’re killing two birds with one stone by calibrating inputs and outputs in tandem, and it makes for a faster calibration process. The complete calibration process for  Digital to Analog converter outputs has enough complexity to warrant a separate blog post.

Let’s take an example; PV1 ( an analog output that can be set between -5V and +5V) can be connected to CH1 (An analog input which can read voltage values between -16 and +16 Volts) with a small segment of wire, and various voltage values can be set on PV1, and read back by CH1 . At the same time, the external calibration utility will also monitor this voltage, and store the error in PV1 (Set Voltage – Actual Voltage) as well as the error in CH1 ( Read Voltage – Actual Voltage ) .

In a similar manner , PV2 can be connected to CH2, and the second channel of the ADS1115 calibrator can be used to monitor the real value, and so on .

Deviations of various analog input channels and their different voltage ranges from the actual values. As is evident from the graph, errors can be as much as 40mV in a full scale range of +/-16,000mV . But since these errors are quite repeatable, we can apply a calibration polynomial to correct these.


Integral Non-linearity of the ADC

In addition to the overall slope and offset, you have probably observed in the previous image, a sawtooth pattern with an amplitude as small as the least count of the analog inputs superimposed on them. This error arises from the integral non-linearity (INL) of the analog to digital convertor of the PIC, and affects all analog inputs uniformly. While in principle we can ignore this for all practical purposes, in order to further improve the analog accuracy, we can also store this INL error of the ADC, and apply this correction to any channel after its slope and offset has been corrected.

The overall slope and offset are caused by the analog references and components, and can be corrected with a simple 3-degree polynomial. However, the sawtooth pattern is characteristics of the INL, and must be stored in a correction array with 4096 elements ( Each element represents the error of the corresponding ADC code of the 12-bit ADC )
The yellow trace represents the error in readings from the ADC after applying polynomial and table based correction. There appears to be a small offset that can be attributed to a change in ambient temperature , but can be neglected as it is in the order of 100uV


The following utilities and code are necessary for this process
  • An I2C communication library for ADS1115 must be present in order to acquire data from it via the PSLab
  • The library should be able to handle the following tasks
    • read single ended , and differential voltage values from any of the channels
    • Enable selection of voltage range and voltage reference
  • A graphical interface with the following features and algorithms will be required:
    • Vary the output voltages from PV1,2,3 in small, definite intervals
    • Store the errors in the analog outputs and inputs as a function of the actual voltage
    • Generate Cubic interpolation functions for each input and output channel
    • The Programmable Current Source can be calibrated using a measured Load resistor, and calibrated analog channel. Its interpolation function must also be stored.
    • Write all calibration constants into flash memory after assigning a timestamp
    • Store raw calibration data in a client-side folder
Testing of the analog inputs after applying calibration polynomials. It can be observed that the accuracy has been brought within a +/-5mV range for the wide input channels. For CH3, a +/-1mV accuracy is achieved.

Characteristization of Transistors Using PSLab

Transistors are one of the key building blocks of all electronics. They are fundamentally three-terminal semiconductor devices, with the terminals being labelled as the Emitter(E), Base(B), and Collector(C). These active components are found everywhere in electronics, and all of the complex processors that power everything from cellphones to aircraft employ millions of these devices in switching and amplification roles. In this blog post, we shall use the PSLab to explore some of the fundamental properties of transistors, and their various applications.

Transistor as an amplifier

In the schematic shown, we shall try to use an NPN transistor to amplify a small signal.

A small amplitude oscillation generated by W1 with the amplitude knob turned down to a very low level is used as the input. Since transistors do not handle bipolar signals, we have mixed a constant DC voltage generated PV3 to shift this small signal into the positive domain.

The fluctuating potential difference incident at the base of the transistor creates a corresponding current flow between the Base and Emitter.

By the fundamental property of transistors, this influences the path resistance between the Collector(C) and the Emitter(E) , and the resultant amplified voltage output can be monitored at the junction between the 1K resistor and the collector.

We have used CH1 to monitor the input voltage, and CH2 for the output

In a more applied scenario, we can implement the second schematic in order to create an audio amplifier. Instead of using W1 as the input signal, a speaker is used as a microphone. When a sound signal is incident on the speaker, its membrane oscillates, and as a result , the coil attached to it also does the same. Since this coil is placed in a magnetic field , its oscillations result in a change in the magnetic flux passing through, and this change causes a voltage(EMF) induced at its output. We then use our transistor amplifier to amplify this small EMF

Figure 2 : A Transistor being used to apply a gain of 81.5x to a small amplitude sine wave. The input waveform (green) is shown on a +/-500mV full scale and the output waveform is shown on a +/-8V scale in order to be able to view both. However, due to the difference in scales, the actual difference in amplitudes is 16 times more than what is visible.
Common Emitter Characteristics
Schematic Diagram

Any introductory course on transistors includes a diagram similar to the one shown , and a description about how for any base current, the collector current eventually saturates, and that this saturation level is proportional to the base current itself.

With the PSLab’s transistor CE characterization app, we can set up this experiment, and verify this for ourselves using an NPN transistor. The results shown were gathered using a 2N2222 transistor

In the schematic , the base current is determined by the voltage source PV2, and a high value series resistor of 200 KOhms . We use an analog input CH3 to monitor the voltage present at the Base of the transistor in order to calculate the total base current.

Base current = V/R = (PV2 – CH3) / 200e3

Now that we have set a particular base current, PV1 is used to sequentially increase the voltage across the collector and emitter of the transistor. A current limiting resistor of 1K Ohm is used, and CH1 is used to monitor the voltage drop across the transistor.

Collector current = V/R = (PV1 – CH1) / 1e3

Plotting the behaviour of the collector current with respect to the collector voltage gives us the familiar current voltage characteristics of a transistor.

Figure 3: Common emitter characteristics of an NPN transistor (2N2222) for various base currents

We can now alter the base current by changing PV2, and verify that the saturation current for the collector is indeed a function of it.



The Pocket Science Lab: Who Needs it, and Why

Science and technology share a symbiotic relationship. The degree of success of experimentation is largely dependent on the accuracy and flexibility of instrumentation tools at the disposal of the scientist, and the subsequent findings in fundamental sciences drive innovation in technology itself. In addition to this, knowledge must be free as in freedom. That is, all information towards constructing such tools and using them must be freely accessible for the next generation of citizen scientists. A common platform towards sharing results can also be considered in the path to building a better open knowledge network.

But before we get to scientists, we need to consider the talent pool in the student community that gave rise to successful scientists, and the potential talent pool that lost out on the opportunity to better contribute to society because of an inadequate support system. And this brings us to the Pocket Science Lab

How can PSLab help electronics engineers & students?

This device packs a variety of fundamental instruments into one handy package, with a Bill-of-materials that’s several orders of magnitude less than a distributed set of traditional instruments.

It does not claim to be as good as a Giga Samples Per second oscilloscope, or a 22-bit multimeter, but has the potential to offer a greater learning experience. Here’s how:

  • A fresh perspective to characterize the real world. The visualization tools that can be coded on an Android device/Desktop (3D surface plots, waterfall charts, thermal distributions etc ), are far more advanced than what one can expect from a reasonably priced oscilloscope. If the same needs to be achieved with an ordinary scope, a certain level of technical expertise is expected from the user who must interface the oscilloscope with a computer, and write their own acquisition & visualization app.
  • Reduce the entry barrier for advanced experiments.: All the tools are tightly integrated in a cost-effective package, and even the average undergrad student that has been instructed to walk on eggshells around a conventional scope, can now perform elaborate data acquisition tasks such as plotting the resonant frequency of a tuning fork as a function of the relative humidity/temperature. The companion app is being designed to offer varying levels of flexibility as demanded by the target audience.

  • Is there a doctor in the house? With the feature set available in the PSlab , most common electronic components can be easily studied , and will save hours while prototyping new designs.  Components such as resistors, capacitors, diodes, transistors, Op-amps, LEDs, buffers etc can be tested.

How can PSLab help science enthusiasts ?

Physicists, Chemists and biologists in the applied fields are mostly dependent on instrument vendors for their measurement gear. Lack of an electronic/technical background hinders their ability to improve the gear at their disposal, and this is why a gauss meter which is basically a magnetometer coupled with a crude display in an oversized box with an unnecessarily huge transformer can easily cost upwards of $150 . The PSLab does not ask the user to be an electronics/robotics expert , but helps them to get straight to the acquisition part. It takes care of the communication protocols, calibration requirements, and also handles visualization via attractive plots.

A physicist might not know what I2C is , but is more than qualified to interpret the data acquired from a physical sensor, and characterize its accuracy.

  • The magnetometer (HMC5883L) can be used to demonstrate the dependence of the axial magnetic field on distance from the center of a solenoid
  • The pressure,temperature sensor (BMP280) can be used to verify the gas laws, and verify thermodynamic phenomena against prevalent theories.

Similarly, a chemist can use an RGB sensor (TCS3200) to put the colour of a solution into numbers, and develop a colorimeter in the process. Colorimeters are quite handy for determining molality of coloured solutions., and commercial ones are rather expensive. What it also needs is a set of LEDs with known wavelengths, and most manufacturers offer proper characterisation information.

What does it mean for the hobbyist?

It is capable of greatly speeding up the troubleshooting process . It can also instantly characterize the expected data from various sensors so that the hobbyist can code accordingly. For example, ‘beyond what tilt threshold & velocity should my humanoid robot swing its arms forward in order to prevent a broken nose?’ . That’s not a question that can be easily answered by said hobbyist who is currently in the process of developing his/her own acquisition system.

How can we involve the community?

The PSLab features an experiment designer that speeds acquisition by providing spreadsheets, analytical tools, and visualisation options all in one place. An option for users to upload their new experiments/utilities to the cloud, and subject those to a peer-review process has been planned. Following which , these new experiments can be pumped back into the ecosystem which will find more uses for it, improve it, and so on.

For example , a user can combine the waveform generator with an analog multiplier IC, and develop a spectrum analyzer.

The case for self-reliance

The average undergraduate laboratory currently employs dedicated instruments for each experiment as prescribed by the curriculum. These instruments often only include the measurement tools essential to the experiment, and students merely repeat the procedure verbatim. That’s not experimentation, it’s rather just verification. PSLab offers a wide array of additional instruments that can be employed by the student to enhance the experiment with their own inputs.

For example, a commonly used diode IV curve-tracer kit usually has a couple of power supplies, a voltmeter, and an ammeter. But, if a student wishes to study the impact of temperature on the band gap, he will hard pressed for the additional tools, and software to combine the acquisition process. With the PSLab, however , he/she can pick from a variety of temperature sensors (LM35, BMP180, Si7021 .. ) depending on the requirement, and explore beyond the book. They are thus better prepared to enter research labs .

And in conclusion , this project has immense potential to help create the next generation of scientists, engineers and creators.