How to Read PIC Data-Sheet and Add a New Functionality to PSLab Firmware

Reading data-sheets is not a fun task. Going through tens of hundreds of pages with numerical, mathematical and scientific data is not fun reading. This blog post attempts to simplify reading the available data-sheets related to PIC24 micro-controller used in the PSLab device to help reader with implementing a new feature in PSLab firmware.

There are many features available in the PSLab device, such as; UART, SPI, I2C, ADC and Basic I/O reading. The “basic” implementation techniques do not vary much from one feature to other. That being stated this blog will carry out the basic implementation techniques one should follow and basic knowledge on PIC micro-controller programming to save himself from the trouble going through the 500+ pages in PIC data-sheets.

PIC Basics:

Before go into implementation there are few facts one should know about PIC programming.

– In the micro-controller values are saved in a memory block known as Registers. The values saved in these registers are volatile as they are all set to 0 regardless the value they were assigned when the power is off.

– Micro-controller configurations are made by setting values to these registers. Even turning on and off a whole feature like UART in PSLab device can be done using setting 0 to UARTEN register bit.

– When it comes to I/O ports, there are two different types of registers called TRIS and LAT/PORT. By setting 1 to TRIS ports will make the relevant pin an input pin. Setting it to 0 will make it an output pin. Easy way to remember this is think 1 as I in input and 0 as O in output. In UART implementation of PSLab, pin RP40 is set as an input pin to receive the data stream and pin RP39 is set as an output pin to send the data stream out. These settings are made using TRIS port settings. PORT registers save the value received by the relevant input pin attached to it.

The above figure extracted from mikroe learning materials, illustrates different stages an I/O pin can handle. As an extra point, ANSEL register makes the pin support digital signals or analog signals as per user requirements.

– In PIC, some registers such as PORT, TRIS and registers with similar functionalities are combined together. To access the value of each individual register can be done using dot notation. Assume the program requires to access the 8th register in TRISB register set. Note that the registers are indexed from zero. This implies that the 8th register will have the index 8 in the register sub-set. The following syntax is used to access the register;



The above points cover the basic knowledge one should have when developing firmware to PSLab device.

How to implement a feature like UART in PSLab firmware?

The first thing to know when implementing a new feature is that the developer needs to be familiar with the relevant hardware protocols. As an example, to implement UART; relevant protocol is RS232. If the feature is I2C; one should know about the I2C protocol.

Once the feature is familiar, next step is to refer the PIC data-sheet and resources on how to implement it in firmware. As for demonstrative purposes, this blog will continue with UART implementation.

Download the latest data-sheet from MicroChip official website and browse to the table of content. It consists of a set of features supported by the micro-controller implemented in the PSLab device. Find the entry related to the feature being implemented. In this case it will be Universal Asynchronous Receiver Transmitter (UART).

Each feature will contain a description following this format explaining what are the options it support and its constraints.

One must be aware of the fact that not every pin in the micro-controller can be used for any feature as he desires. The “PINOUT I/O DESCRIPTIONS” section in the data-sheet explains which pins are capable of the feature being implemented. According to these details, the pins should be initiated as Input/Output pins as well as Digital/Analog pins.

The next step is to refer to the control registers related to the feature. They are all mentioned in the data-sheet under the specific feature. There are some notations available in this section which resembles something like the following;

PDSEL<1:0>: Parity and Data Selection bits
11 = 9-bit data, no parity
10 = 8-bit data, odd parity
01 = 8-bit data, even parity
00 = 8-bit data, no parity


This represents a register with two bits. By setting either 11 or 10 or 01 or 00; different implementations can be achieved.

In PSLab firmware this is implemented as;

U1MODEbits.PDSEL = 0;


which implements UART feature with 8-bits stream having no parity bits for error correction.

In UART feature implemented in PSLab device, receiving bit stream is fetched by reading the register values in U1STAbits.URXDA and data is transmitted using U1TXREG. All these registers are mentioned in the control registers section in the feature.


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Performing Fourier Transforms in the PSLab Android App

Oscilloscope is one of the key features of PSLab. When periodic signals such as sine waves are read by the Oscilloscope, curve fitting functions are used to construct a curve that has the best fit to a series of data points. In PSLab, the sine curve fitting involves the Fourier Transforms. FFT (short for “Fast Fourier Transform”) is nothing more than a curve-fit of sines and cosines to some given data. In order to understand the implementation of Fourier Transforms in PSLab Android App let’s first have a look at the Fourier transform equations.

The first equation here is the Forward Fourier transform. It converts the function of time (t) into the function of frequency (ω).
The second equation is Inverse Fourier transform. It does the opposite to first equation ie. it converts the function of frequency (ω) into the function of time (t).

So, first I will answer what is transform?
It is the mapping between two different sets of domains. In this case, the information is changed from the time domain to frequency domain. The data in these domains look different but represent the same information. A transform will get you from one representation to another.

Fourier transforms converts between the time domain f(t) and the frequency domain F(ω).
Performing Fourier Transforms in Android
Let’s perform Forward Fourier transform. This means it converts the function of time (t) into the function of frequency (ω). We will use Apache Maths Commons to perform Fourier transforms. Since we have finite input data set we will calculate Discrete Fourier Transform (DFT).
The algorithm which is being used here is Fast Fourier Transform (FFT) which is the best algorithm to calculate Fourier transforms.

FastFourierTransformer fastFourierTransformer = 
      new FastFourierTransformer(DftNormalization.STANDARD);

Here we are creating an instance of FastFourierTransformer which passed STANDARD normalization convention to its constructor. Normalization other than STANDARD is UNITARY.
Complex complex[] = fastFourierTransformer.transform(input, TransformType.FORWARD);

Here, input array and TransformType. FORWARD is also passed to transform method. Input is an array of data representing time whereas TransformType. FORWARD defines the type of Fourier transform that should be performed ie. forward or inverse.

Complex complex[] = fastFourierTransformer.transform(input, TransformType.FORWARD);

The output will be an array of complex number. Each data point will be represented like the following graph in the complex plane.

Suppose the amplitude of the data point given in above graph is 1 and phase shift is 45°. So, solving this we will get 2/√2 as both real and imaginary components. Therefore, F (ω) would be 1/√2 + (1/√2) i.
Dealing with Complex numbers in Java
A complex number has both real and imaginary part. Using Apache Maths Commons we can use Complex to represent a complex number.

Complex number = new Complex(1,2);
1.0 + 2.0i

We can also get real and imaginary parts separately of Complex numbers.


The array of the Complex numbers can be implemented like the following

Complex[] number;
Complex c1 = new Complex(1, 2);
Complex c2 = new Complex(3, 4);
number = new Complex[]{c1, c2};

[(1.0, 2.0), (3.0, 4.0)]
(3.0, 4.0)


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Creating Sensor Libraries in PSLab

The I2C bus of the PSLab enables access to a whole range of sensors capable of measuring parameters ranging from light intensity, humidity, and temperature, to acceleration, passive infrared, and magnetism.

Support for each sensor in the communication library is implemented as a small Python library that depends in the I2C communication module for PSLab.

However, most sensors have capabilities that are not just limited to data readouts, but also enable various configuration options.

This blog post explains how a common format followed across the sensor libraries enables the graphical utilities such as data loggers and control panels to dynamically create widgets pertaining to the various configuration options.

The following variables and methods must be present in each sensor file in order to enable the graphical utilities to correctly function:

Name: A generic name for the sensor to be shown in menus and such. e.g. ‘Altimeter BMP180’

GetRaw(): A function that returns a list of values read from the sensor. The values may have been directly read from the sensor, or derived based on some parameters/equations.

For example, the BMP180 altitude sensor is actually a pressure and temperature sensor. The altitude value is derived from these two using an equation. Therefore, the getRaw function for the BMP180 returns a list of three values, viz, [temperature, pressure, altitude]

NUMPLOTS: A constant that stores the number of available dataPoints in the list returned by the getRaw function. This enables the graphical utilities to create required number of traces . In case of the BMP180, it is 3

PLOTNAMES: A list of text strings to be displayed in the plot legend . For the BMP180, the following list is defined : [‘Temperature’, ‘Pressure’, ‘Altitude’]

params: A dictionary that stores the function names for configuring various features of the sensor, and options that can be passed to the function. For example, for the BMP180 altimeter, and oversampling parameter is available, and can take values 0,1,2 and 3 . Therefore, params = {‘setOversampling’: [0, 1, 2, 3]}

The Sensor data Logger application uses this dictionary to auto-generate menus with the ‘key’ as the name , and corresponding ‘values’ as a submenu . When the user opens a menu and clicks on a ‘value’ , the ‘value’ is passed to a function whose name is the corresponding key , and which must be defined in the sensor’s class.

When the above are defined, menus and plots are automatically generated, and saves considerable time and effort for graphical utility development since no sensor specific code needs to be added on that front.

The following Params dictionary defined in the class of MPU6050 creates a menu as shown in the second image:

self.params = { 'powerUp':['Go'],

As shown in the image , when the user clicks on ‘8’ , MPU6050.setAccelRange(8) is executed.

Improving the flexibility of the auto-generated menus

The above approach is a little limited, since only a fixed set of values can be used for configuration options, and there may be cases where a flexible input is required.

This is the case with the Kalman filter option, where the user may want to provide the intensity of the filter as a decimal value. Therefore we shall implement a more flexible route for the params dictionary, and allow the value to certains keys to be objects other than lists.

Functions with user defined variable inputs are defined as Spinbox/QDoubleSpinBox.

KalmanFilter is defined in the following entry in Params:

‘KalmanFilter’:{‘dataType’:’double’,’min’:0,’max’:1000,’prefix’:’value: ‘}

Screenshot of the improved UI with MPU6050.

In this instance, the user can input a custom value, and the KalmanFilter function is called with the same.

Additional Reading:

[1]: Using sensors with PSLab Android

[2]: Analyzing sensor data with PSLab android
[3]: YouTube video to understand analysis of data from MPU6050 with Arduino –

Continue ReadingCreating Sensor Libraries in PSLab

Create a Distance Sensor using PSLab

PSLab device is a small lab which supports a ton of features. Among its many features, integrating a distance measuring sensor like HC SR04 sonar sensor into it is one of them. This blog post will bring out the basic concepts behind a sonar sensor available in the current market, how it measures distance and how it is implemented in the PSLab device.

A sonar sensor uses a sound wave with a very high frequency. These waves are called ultrasonic waves. They cannot be heard by the naked ear. Human ear can only hear frequencies from 20 Hz up to 20 kHz. Generally HC SR04 sensors use a wave with frequency as high as 40 kHz so this makes sense. The basic principal behind the sensor is the reflectance property of sound. Time is calculated from the transmission time up to the time receiving the reflected sound wave. Then using general moment equation S = ut; with the use of speed of sound, the distance can be measured.

The figure shows a HC SR04 ultrasound sensor. They are quiet famous in the electronic field; especially among hobbyists in making simple robots and DIY projects. They can be easily configured to measure distance from the sensor up to 400 cm with a measuring angle of 15 degrees. This angular measurement comes into action with the fact that sound travels through a medium in a spherical nature. This sensor will not give accurate measurements when used for scenarios like measuring distance to very thin objects as they reflect sound poorly or there will not be any reflectance at all.

There are four pins in the HC SR04 sonar sensor. Corner pins in the two sides are for powering up the Sonar sensor. The two pins named ECHO and TRIG pins are the important pins in this context. When the TRIG pin (Trigger for short) is excited with a set of 8 square pulses at a rate of 40 kHz, the ECHO pin will reach to logic HIGH state which is the supply voltage (+5 V). When the transmitted sound wave is reflected back to the sensor, this high state of the ECHO pin will shift to logic LOW state. If a timer is turned on when the ECHO pin goes to logic HIGH state, we can measure how long it was taken for the sound beam to return to the sensor by turning off the timer when the ECHO pin goes to logic LOW state.

Having described the general implementation of a sonar sensor; a similar implementation is available in PSLab device. As mentioned earlier, TRIG pin requires a triggering pulse of 8 set of square waves at 40 kHz. This is achieved in PSLab using SQR pulse generating pins. The time is measured from the transmitting point until the receiving point to evaluate the distance. The real distance to the obstacle in front of the sensor can be calculated using following steps;

  1. Measure total round trip time of the sound beam. Take it as t
  2. Calculate the time taken for the beam to travel from sensor to the obstacle. It will be t/2
  3. Use motion equation S = ut to calculate the actual distance taking u = speed of sound in air. Substituting the time value calculated in step 2 to t, S will produce the distance


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Communication by pySerial python module in PSLab

In the PSLab Desktop App we use Python for communication between the PC and PSLab device. The PSLab device is connected to PC via USB cable. The power for the hardware device is provided by the host through USB which in this case is a PC. We need well structured methods to establish communication between PC and PSLab device and this is where pySerial module comes in. We will discuss how to communicate efficiently from PC to a device like PSLab itself using pySerial module.

How to read and write data back to PSLab device?

pySerial is a python module which is used to communicate serially with microcontroller devices like Arduino, RaspBerry Pi, PSLab (Pocket Science Lab), etc. Serial data transfer is easier using this module, you just need to open a port and obtain serial object, which provides useful and powerful functionality. Users can send string (which is an array of bytes) or any other data type all data types can be expressed as byte string using struct module in python, read a specific number of bytes or read till some specific character like ‘\n’ is encountered. We are using this module to create custom read and write functions.

How to Install pySerial and obtain serial object for communication?

You can install pySerial using pip by following command

pip install pyserial

Once it’s installed we can now import it in our python script for use.

Obtain Serial Object

In Linux

>>> import serial
>>> ser = serial.Serial(‘/dev/ttyUSB0’)

In Windows

>>> ser = serial.Serial()
>>> ser.baudrate = 19200
>>> ser.port = ‘COM1’


>>> ser = serial.Serial(‘COM1’, 19200)

You can specify other properties like timeout, stopbits, etc to Serial constructor.

Complete list of parameters is available here. Now this “ser” is an object of Serial class that provides all the functionalities through its interface. In PSLab we obtain a serial object and implement custom methods to handle communication which isn’t directly provided by pySerial, for example if we need to implement a function to get the version of the PSLab device connected. Inside the version read function we need to send some bytes to the device in order to obtain the version string from device as a byte response.

What goes under the hood?

We send some sequence of bytes to PSLab device, every sequence of bytes corresponds to a unique function which is already written in device’s firmware. Device recognises the function and responses accordingly.

Let’s look at code to understand it better.

ser.write(struct.Struct(‘B’).pack(11))  #  Sends 11 as byte string
ser.write(struct.Struct(‘B’).pack(5))   #  Sends 5 as bytes string
x = ser.readline()                      #  Reads bytes until ‘\n’ is encountered   

To understand packing and unpacking using struct module, you can have a read at my other blog post Packing And Unpacking Data in JAVA in which I discussed packing and unpacking of data as byte strings and touched a bit on How it’s done in Python.  

You can specify how many bytes you want to read like shown in code below, which is showing and example for 100 bytes :

x =

After your communication is complete you can simply close the port by:


Based on these basic interface methods more complex functions can be written to handle your specific needs. More details one how to implement custom methods is available at python-communication-library of PSLab which uses pySerial for communication between Client and PSLab device.

An example of custom read function is suppose I want to write a function to read an int from the device. int is of 2 bytes as firmware is written in C, so we read 2 bytes from device and unpack them in client side i.e on PC. For more such custom functions refer of PSLab python communication library.

def getInt(self):
      reads two bytes from the serial port and
      returns an integer after combining them
      ss =  # reading 2 bytes from serial object
          if len(ss) == 2:
              return CP.ShortInt.unpack(ss)[0]  # unpacking bytes to make int
      except Exception as ex:
          self.raiseException(ex, “Communication Error , Function : get_Int”)


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Environment Monitoring with PSLab

In this post, we shall explore the working principle and output signals of particulate matter sensors, and explore how the PSLab can be used as a data acquisition device for these.

Working Principle

A commonly used technique employed by particulate matter sensors is to study the diffraction of light by dust particles, and estimate the concentration based on a parameter termed the ‘occupancy factor’. The following image illustrates how the most elementary particle sensors work using a photogate, and a small heating element to ensure continuous air flow by convection.

Occupancy Rate

Each time a dust particle of aerodynamic diameters 2.5um passes through the lit area, a phenomenon called Mie scattering which defines scattering of an electromagnetic plane wave by a homogenous sphere of diameter comparable to the wavelength of incident light, results in a photo-signal to be detected by the photosensor.  In more accurate dust sensors, a single wavelength source with a high quality factor such as a laser is used instead of LEDs which typically have broader spectra.

The signal output from the photosensor is in the form of intermittent digital pulses whenever a particle is detected. The occupancy ratio can be determined by measuring the sum total of time when a positive signal was output from the sensor to the total averaging time. The readings can be taken over a fairly long amount of time such as 30 seconds in order to get a more accurate representation of the occupancy ratio.

Using the Logic analyzer to capture and interpret signals

The PSLab has a built-in logic analyzer that can acquire data signals up to 67 seconds long at its highest sampling rate, and this period is more than sufficient to record and interpret a dataset from a dust sensor. An inexpensive dust sensor, DSM501A was chosen for the readings, and the following results were obtained

Dust sensor readings from an indoor, climate controlled environment. After the 100 second mark, the windows were opened to expose the sensor to the outdoor environment.

A short averaging time has resulted in large fluctuations in the readings, and therefore it is important to maintain longer averaging times for stable measurements.

Recording data with a python script instead of the app

The output of the dust sensor must be connected to ID1 of the PSLab, and both devices must share a common ground which is a prerequisite for exchange of DC signals. All that is required is to start the logic analyzer in single channel mode, wait for a specified averging time, and interpret the acquired data

from PSL import sciencelab   #import the required library
import time
import numpy as np
I = sciencelab.connect()           #Create the instance
I.start_one_channel_LA(channel='ID1',channel_mode=1,trigger_mode=0)  #record all level changes
time.sleep(30)   #Wait for 30 seconds while the PSLab gathers data from the dust sensor
a,_,_,_,e =I.get_LA_initial_states()      #read the status of the logic analyzer
raw_data =I.fetch_long_data_from_LA(a,1)  #fetch number of samples available in chan #1
stamps =I.dchans[0].timestamps    #Obtain a copy of the timestamps
if len(stamps)>2:   #If more than two timestamps are available (At least one dust particle was detected
		if not self.I.dchans[0].initial_state:   #Ensure the starting position of timestamps
			stamps = stamps[1:] - stamps[0]   # is in the LOW state
	diff = np.diff(stamps)   #create an array of individual time gaps between successive level changes

	lows = diff[::2]      #Array of time durations when a particle was not present
	highs = diff[1::2]    #Array of time durations when a particle was present
	low_occupancy = 100*sum(lows)/stamps[-1] #Occupancy ratio
print (low_occupancy) # datasheets of individual dust sensors also provide a mathematical
                      #equation to interpret the occupancy ratio as concentration of
				#particulate matter

Further Reading, and application notes:

[1] LED based  dust Sensor application note

Continue ReadingEnvironment Monitoring with PSLab

Analyzing Sensor Data on PSLab

PSLab Android App and Desktop app have the functionality of reading data from the sensors. The raw sensor data received is in the form of a long string and needs to parsed to understand what the data actually conveys.

The sensor data is unique in terms of volume of data sent, the units of measurement of the data etc., however none of this is reflected in the raw data. The blog describes how the sensor data received by the Android/Desktop app is parsed, interpreted and finally presented to the user for viewing.

The image below displays the raw data sent by the sensors


Fig: Raw Sensor data displayed below the Get Raw button

  • In order to understand the data sent from the sensor, we need to understand what the sensor does.
    • For example, HMC5883L is a 3-axis magnetometer and it returns the value of the magnetic field in the x, y & z axes in the order of nanoTeslas.
    • Similarly, the DAC of PSLab – MCP4728 can also be used like other sensors, it returns the values of channels in millivolts.
    • The sensor MPU6050 being 3-axes accelerometer & gyroscope which returns the values of acceleration & angular momentum of the x, y & z axes in their SI units respectively.
  • Each sensor has a sensitivity value. The sensitivity of the sensor can be modified to adjust the accuracy of the data received. For PSLab, the data returned is a float number with each data point having 4 bytes of memory with the highest sensitivity. Although sensitivity is not a reliable indicator of the accuracy of the data. Each value received has a lot of trailing values after the decimal and it is evident that no sensor can possibly achieve accuracy that high, so the data after 2-3 decimal places is garbage and not taken into consideration.
  • Some sensors are configurable up to a great extent like MPU6050 where limits can also be set on the range of data, volume of data sent etc. whereas some are not configurable and are just meant for sending the data at regular intervals.
  • In order to parse the above data, if the sensor returns a single value, then the data is ready to be used. However, in most cases like above where the sensors return multiple values, the data stream can be divided into equal parts since each value occupies equal space and each value can be stored in different variables.
  • The stored data has to be presented to the user in a better understandable format where it is clear that what each value represents. For example, in case of the 3 axes sensors, the data of each axis must be distinctly represented to the user.

Shown below are the mock-ups of the sensor UIs in which each value has been distinctly represented.


Fig: Mock-ups for the sensor UIs (a) – HMC5883L (b) – MPU6050

Each UI has a card to display those values. These values are updated in real time and there are additional options to plot the data received in real time and in some cases also configure the sensor. In addition to that there are features for data logging where the data is recorded for a given time interval specified by the user and on completion of recording, calculations like the mean, standard deviation etc. are presented to the user.

Additional Resources

  1. Analyzing sensor data using Arduino, similar to method for PSLab –
  2. YouTube video to understand analysis of data from MPU6050 in Arduino –
Continue ReadingAnalyzing Sensor Data on PSLab

Creating Multiple Device Compatible Layouts in PSLab Android

The developer’s goal is that PSLab Android App as an app should run smoothly on all the variety of Android devices out in the market. There are two aspects of it – the app should be able to support maximum number of Android versions possible which is related to the core software part and the other being the app should be able to generate the same user experience on all sizes of screens. This post focuses on the later.

There are a whole range of android devices available in the market right from 4 inch mobile phones to 12 inch tablets and the range in the screen sizes is quite large. So, the challenge in front of app designers is to make the app compatible with the maximum  number of devices without doing any specific tweaks related to a particular resolution range. Android has its mechanism of scaling the app as per the screen size and it does a good job almost all the time, however, still there are cases where android fails to scale up or scale down the app leading to distorted layout of the app.

This blog discusses some of the tricks that needs to be kept in mind while designing layouts that work independent of screen sizes.

Avoid using absolute dimensions

It is one of the most common things to keep in mind before starting any UI design. Use of absolute dimensions like px, inch etc. must be avoided every time as they are fixed in size and don’t scale up or scale down while screen sizes are changed. Instead relative dimensions like dp should be used which depend on the resolution and scale up or scale down. ( It’s a fair assumption that bigger screens will have better resolution compared to the smaller ones although exceptions do exist) .

Ensure the use of correct layout/View group

Since, android provides a variety of layouts like Linearlayout, Constrainedlayout, Relativelayout, Tablelayout and view groups like ScrollView, RecyclerView, ListView etc. it is often confusing to know which layout/viewgroup should be used. The following list gives a rough idea of when to use a particular layout or view group.

  • Linearlayout – Mostly used for simple designs when the elements are stacked in ordered horizontal/vertical fashion and it needs explicit declaration of orientation.
  • Relativelayout – Mostly used when the elements need to defined relative to the parent or the neighbouring elements. Since, the elements are relative, there is no need to define the orientation.
  • Constraintlayout – It has all the features of Relativelayout and in addition a feature of adding constraints to the child elements or neighbouring elements.
  • Tablelayout – Tablelayout is helpful to when all the views/widgets are arranged in an ordered fashion.

All the above layouts can be used interchangeably most of the times, however, certain cases make some more favourable than others like when than views/ widgets are not present in an organised manner, it is better to stick to Linearlayout or Relativelayout.

  • ListView – Used when the views/ widgets in a screen are repeated, so using a listview ensures that the volume of the code is reduced and all the repetitive views are identical in nature.
  • RecyclerView – More of an improved version of ListView. It is recommended to use this view over ListView. Additionally this view group supports features like swipe to refresh.
  • ScrollView – Used when the UI screen cannot fit within the given screen space. ScrollView supports one direct child layout. So, to implement a scrollview, all the views must be under a particular layout and then masked by scrollview.

Choosing the correct layout or view group would help to create a better UI.

Use of layout_weight

Ensuring the layout width assigned in XML file covers the entire width on the screen. For ensuring this, one possible solution is to use layout_weight instead of layout_width.

Example –



In order to use layout_weight, layout_width must be set to 0 else it would interfere with the width and as layout_width is a compulsory parameter it cannot be omitted. Layout weight can be any number and the space is allocated to each view in proportion to the weights assigned. Since it does not involve numerical dimensions, the distribution would be uniform for all types of screens. The result is clearly evident here. The same UI in different screen sizes is displayed below.


Fig: Screenshot taken on a 6” phone and on a 4” phone. Although the screen area of 4” phone is 44% that of the 6” phone, the UIs are identically the same.

Create different layout directories for different resolutions

  • Creating different layouts for different screen sizes ensures that the limitations of smaller screen sizes are taken care of and the advantages offered by bigger screen sizes are put to the best use.
  • The Android documentation here mentions the conventions to be followed while designing.
  • Although over the years, android has become better at auto-adjusting layouts for different screen sizes. However, if the no. of views and widgets are high, auto-adjusting does not work well as in case of PSLab and it is better to create different sets of layouts.
  • As evident from the picture of the 8” tablet, although the auto-adjusted layout is manageable, the layout looks stretched and does not utilize the entire screen space, so it a better UI can be made by creating a dedicated layout directory for bigger screens.

Additional resources


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Using Sensors with PSLab Android App

The PSLab Android App as of now supports quite a few sensors. Sensors are an essential part of many science experiments and therefore PSLab has a feature to support plug & play sensors. The list of sensors supported by PSLab can be found here.

  • AD7718 – 24-bit 10-channel Low voltage Low power Sigma Delta ADC
  • AD9833 – Low Power Programmable Waveform generator
  • ADS1115 – Low Power 16 bit ADC
  • BH1750 – Light Intensity sensor
  • BMP180 – Digital Pressure Sensor
  • HMC5883L – 3-axis digital magnetometer
  • MF522 – RFID Reader
  • MLX90614 – Infrared thermometer
  • MPU6050 – Accelerometer & gyroscope
  • MPU925x – Accelerometer & gyroscope
  • SHT21 – Humidity sensor
  • SSD1306 – Control for LED matrix
  • Sx1276 – Low Power Long range Transceiver
  • TSL2561 – Digital Luminosity Sensor

All the sensors except Sx1276 communicate using the I2C protocol whereas the Sx1276 uses the SPI protocol for communication. There is a dedicated set of ports on the PSLab board for the communication under the label I2C with the ports named 3.3V, GND, SCL & SDA.


Fig; PSLab board sketch

Any I2C sensor has ports named 3.3V/VCC, GND, SCL, SDA at least along with some other ports in some sensors. The connections are as follows:

  1. 3.3V on PSLab – 3.3V/VCC on sensor
  2. GND on PSLab – GND on sensor
  3. SCL on PSLab – SCL on sensor
  4. SDA on PSLab – SDA on sensor

The diagram here shows the connections

For using the sensors with the Android App, there is a dedicated I2C library written in communication in Java for the communication. Each sensor has its own specific set of functionalities and therefore has its own library file. However, all these sensors share some common features like each one of them has a getRaw method which fetches the raw sensor data. For getting the data from a sensor, the sensor is initially connected to the PSLab board.

The following piece of code is responsible for detecting any devices that are connected to the PSLab board through the I2C bus. Each sensor has it’s own unique address and can be identified using it. So, the AutoScan function returns the addresses of all the connected sensors and the sensors can be uniquely identified using those addresses.

public ArrayList<Integer> scan(Integer frequency) throws IOException {
	if (frequency == null) frequency = 100000;
	ArrayList<Integer> addresses = new ArrayList<>();
	for (int i = 0; i < 128; i++) {
		int x = start(i, 0);
		if ((x & 1) == 0) {
	return addresses;


As per the addresses fetched, the sensor library corresponding to that particular sensor can be imported and the getRaw method can be called. The getRaw method will return the raw sensor data. For example here is the getRaw method of ADS1115.

public int[] getRaw() throws IOException, InterruptedException {
	String chan = typeSelection.get(channel);
	if (channel.contains("UNI"))
		return new int[]{(int) readADCSingleEnded(Integer.parseInt(chan))};
	else if (channel.contains("DIF"))
		return new int[]{readADCDifferential(chan)};
	return new int[0];

Here the raw data is returned in the form of voltages in mV.

Similarly, the other sensors return some values like luminosity sensor TSL2561 returns values of luminosity in Lux, the accelerometer & gyroscope MPU6050 returns the angles of the 3-axes.

In order to initiate the process of getting raw data from the sensor in Sensor Activity, the object for the sensor is created and the method of getRaw is called. The following is the implementation for ADS1115. The rest of the sensors also have an implementation similar to this. There are try-catch statements in the code to handle some of the exceptions thrown during process of method calls.

ADS1115 ADS1115 = null;
try {
	ADS1115 = new ADS1115(i2c);
} catch (IOException | InterruptedException e) {

int[] dataADS1115 = null;
String datadispADS1115 = null;
try {
	if (ADS1115 != null) {
		dataADS1115 = ADS1115.getRaw();
} catch (IOException | InterruptedException e) {

if (dataADS1115 != null) {
	for(int i = 0; i < dataADS1115.length; i++)
		datadispADS1115 += String.valueOf(dataADS1115[i]);



Additional Resources

  1. Sensor implementation in PSLab Python repository –
  2. Using the sensors with Arduino in case you have worked with Arduino before – The basic connections are same as PSLab
Continue ReadingUsing Sensors with PSLab Android App

Creating Custom Components in the PSLab Android App

PSLab Android App supports a lot of features and each of these features need components & views for their implementation. A typical UI of PSLab is shown in the figure below. Considering the number of views & components used in the figure, implementation of each view & component separately would lead to a huge volume of repetitive and inefficient code. As it is evident that the EditText and two buttons beside it keep repeating a lot, it is wiser to create a single custom component consisting of an EditText and two buttons. This not only leads to efficient code but also results in a drastic reduction of the volume of code.

Android has a feature which allows creating components. For almost all the cases, the pre-defined views in Android serve our purpose of creating the UIs. However, sometimes there is a need to create custom components to reduce code volume and improve quality. Custom components are used when a particular set of component needed by us is not present in the Android view collection or when a pattern of components is frequently repeated or when we need to reduce the code complexity.

The above set can be replaced by defining a custom component which includes an edittext and two buttons and then treating it like just any other component. To get started with creating a custom component, the steps are the following:

Create a layout for the custom component to be designed

<?xml version="1.0" encoding="utf-8"?>
<LinearLayout xmlns:android=""
   android:orientation="horizontal" android:layout_width="match_parent"

       android:background="@drawable/button_minus" />

       android:background="@drawable/control_edittext" />

       android:background="@drawable/button_plus" />

The layout file edittext_control.xml is created with three views and each one of them has been assigned an ID along with all the other relevant parameters.

Incorporate the newly created custom layout in the Activity/Fragment layout file


The custom layout can be added the activity/fragment layout just like any other view and can be assigned properties similarly.

Create the activity file for the custom layout

public class Edittextwidget extends LinearLayout{

   private EditText editText;
   private Button button1;
   private Button button2;
   private double leastCount;
   private double maxima;
   private double minima;

   public Edittextwidget(Context context, AttributeSet attrs, int defStyle) {
       super(context, attrs, defStyle);

   public Edittextwidget(Context context, AttributeSet attrs) {
       super(context, attrs);

   public Edittextwidget(Context context) {

  public void init(Context context, final double leastCount, final double minima, final double maxima) {
       View.inflate(context, R.layout.edittext_control, this);
       editText = (EditText) findViewById(;
       button1 = (Button) findViewById(;
       button2 = (Button) findViewById(;

       button1.setOnClickListener(new OnClickListener() {
           public void onClick(View v) {
               Double data = Double.valueOf(editText.getText().toString());
               data = data - leastCount;
               data = data > maxima ? maxima : data;
               data = data < minima ? minima : data;

       button2.setOnClickListener(new OnClickListener() {
           public void onClick(View v) {
               Double data = Double.valueOf(editText.getText().toString());
               data = data + leastCount;
               data = data > maxima ? maxima : data;
               data = data < minima ? minima : data;

   private void applyAttrs(AttributeSet attrs) {
       TypedArray a = getContext().obtainStyledAttributes(attrs, R.styleable.Edittextwidget);
       final int N = a.getIndexCount();
       for (int i = 0; i < N; ++i) {
           int attr = a.getIndex(i);
           switch (attr) {
               case R.styleable.Edittextwidget_leastcount:
                   this.leastCount = a.getFloat(attr, 1.0f);
               case R.styleable.Edittextwidget_maxima:
                   this.maxima = a.getFloat(attr, 1.0f);
               case R.styleable.Edittextwidget_minima:
                   this.minima = a.getFloat(attr, 1.0f);

In the activity file, the views of the custom layout are defined and functionalities are assigned to them. For example, here there are two buttons which work as increment/decrement buttons and an edittext which takes numeric input. The buttons are initiated just like the way they are done in other activity/fragment using OnClickListener.

Define the attributes for the custom layout

<declare-styleable name="Edittextwidget">
     <attr name="leastcount" format="float" />
     <attr name="maxima" format="float" />
     <attr name="minima" format="float" />

The attributes for the custom layout are defined in the attrs.xml file. Each attribute is assigned a name and a format which can be int, float, double, string etc.

Finally call the methods of the custom layout from the desired activity/fragment

Edittextwidget etwidgetControlAdvanced1 = (Edittextwidget)view.findViewById(;

etwidgetControlAdvanced1.init(getContext(), 1.0, 10.0, 5000.0);

The init method of is called while passing the relevant parameters like context, least count, maxima and minima.

Additional Resources on Custom Components

  1. Official Android Guide on Custom components –
  2. Simple example of creating a custom component to get started –
Continue ReadingCreating Custom Components in the PSLab Android App