Scientific-data (SciData)

This package serves as a tool box to prepare raw data for later plotting in matplotlib, largely smoothing the process from reading raw data to generating processed data then to plotting them. To dive deeper, please visit my personal website

Introduction to SciData.py

In this .py file, we define all the classes for structing raw data and pre-processing them. In many experiments, we take data for a changing parameter A (sweep A) at a fixed parameter B in one .dat file, and then change the parameter B and sweep A. All the data will be stored in a folder with files named by the specific parameter B. Then in this case, our defined class can turn all the data in the folder into an instance of this class. By adding methods to this class, we can pre-process the data (getdata(self)), do Hall fit if one dimension is the magnetic field (hallfit(self,fitrange)) and quick plot data (plotdata(self,label_value)). The functionality of parent class Datajungle can be extended by creating more child class.

Child class	parameter A	parameter B
Databs	magnetic field	gate-voltage
Datags	gate-voltage	magnetic field
Datafc	gate-voltage	gate-voltage
DataX	unknown	unknown

The first three are most useful when handling (quantum) Hall measurement. For general flexibility, we also provide a less-defined class DataX to handle many other types of data.

How to use this package to speed up your work flow

startnb.py is a script to import default setting of your jupyter notebook, especially importing all the packages, scripts and functions to be ready to use and also plotting setting under plt.rc.

%run [dir to SciData]/startnb.py

Add this line in your first cell of opened notebook to start your data processing.