scanning-squid-analysis

Analysis GUI for scanning SQUID microscopy datasets generated by the scanning-squid python package.

Requirements

• Anaconda 3

Installation

• Clone or download this repository.

Setup

Windows

• Edit the first line of create_env.bat, remove_env.bat, and start_gui.bat to read call <path\to\your\Anaconda3>\Scripts\activate.bat. For most users this is probably C:\Users\<your-user>\Anaconda3\Scripts\activate.bat.
  • If you don't know where to find this, open the Anaconda Prompt and run where python. You should see something like C:\Users\<your-user>\Anaconda3\python.exe (see here). Then update the first line of the above .bat scripts with call C:\Users\<your-user>\Anaconda3\Scripts\activate.bat.
• Double click creat_env.bat to create a conda env called scanning-squid-analysis with all of the required packages. You only have to do this once, when you first install the program. You can close this cmd window once it reads Press any key to continue....
• You can now start the data analysis GUI by double clicking start_gui.bat.

Mac

• Edit the second line of create_env.command and remove_env.command to read source <path/to/your>/anaconda3/bin/activate. For most users this is probably /anaconda3/bin/activate or ~/anaconda3/bin/activate.
• Edit the second line of start_gui.command to read source <path/to/your>/anaconda3/bin/activate scanning-squid-analysis.
• Open Terminal and navigate to this repository (cd <path/to/this/repo> or cd <space> and drag/drop this directory into the Terminal window).
• In Terminal, run chmod u+x create_env.command remove_env.command start_gui.command to give the terminal permission to run these files.
• Double click create_env.command to create a conda env called scanning-squid-analysis with all of the required packages. You only have to do this once, when you first install the program. You can close this Terminal window once it reads [Process completed].
• You can now start the data analysis GUI by double clicking start_gui.command.

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Usage

• Use the Select directory button, File -> Select directory..., or ctrl+O (Windows)/cmd+O (Mac) to select the data directory. This base directory (for example sample_data/data in this repo) should contain dated subdirectories, which in turn contain single datasets (e.g. sample_data/data/2018-09-14/#016_scan_13-07-41).
• Click a specific dataset in the DataSet Browser to load its data. The dataset metadata and instrument settings can be examined with the Measurement Metadata and Microscope Snapshot widgets.
• The arrays contained in the dataset can be visualized/lightly processed in the DataSet Plotter.
• The current matplotlib figure can be exported using Plot -> Export matplotlib... or ctrl+P (Windows)/cmd+P (Mac).
• The currently displayed data (including any rotations, background subtraction, cross-sections, etc.) can be exported using File -> Export current data... or ctrl+S (Windows)/cmd+S (Mac). The available export formats are:
  • MATLAB .mat file: Each array is saved to a struct with field names 'array' and 'unit'.
  • HDF5 .h5 file: Can be read by h5py, MATLAB, or viewed with HDF5 View.
  • Python pickle: A dictionary of arrays is written directly to a file in binary form and can be loaded using:

    import pickle
    with open('filename.pickle', 'rb') as f:
        arrays = pickle.load(f)

• The built-in IPython console has access to the following:
  • matplotlib.pyplot: plt
  • numpy: np
  • a dict of the current arrays in the form of pint Quantities: arrays. For example, arrays['MAG'].magnitude will be the MAG array, with units arrays['MAG'].units
  • the current qcodes.data.data_set.DataSet: dataset

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Notes

• If you wish to uninstall the program, double click remove_env.bat (Windows) or remove_env.command (Mac) to remove the scanning-squid-analysis conda env, then delete this repository.
• If you find bugs/have suggestions for new features, please use the GitHub Issues feature.
• Contact: logan.bvh@gmail.com.
• Logo by Tom Shahar.