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 –