https://github.com/ashirsch/spe2py

Loads Princeton Instruments LightField (SPE 3.0) files into a python environment.
https://github.com/ashirsch/spe2py

lightfield loader numpy optics princeton-instruments python

Last synced: about 2 months ago
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Loads Princeton Instruments LightField (SPE 3.0) files into a python environment.

• Host: GitHub
• URL: https://github.com/ashirsch/spe2py
• Owner: ashirsch
• Created: 2016-06-21T18:44:25.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2021-07-19T20:27:34.000Z (over 3 years ago)
• Last Synced: 2024-11-01T07:41:04.771Z (about 2 months ago)
• Topics: lightfield, loader, numpy, optics, princeton-instruments, python
• Language: Python
• Size: 6.26 MB
• Stars: 16
• Watchers: 1
• Forks: 12
• Open Issues: 6
• Metadata Files:
  • Readme: README.md

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README

        
# spe2py

spe2py is a module that imports a Princeton Instruments LightField (SPE 3.x) file into a python environment. 

### Basic Usage

##### Loading and accessing data

Use the `load()` function to load one or more SPE files at a time:

```python

>>> import spe2py as spe

>>> loaded_files = spe.load()

```

A file selection window will open to allow browsing for source files. The result is an individual SpeFile object, or, in the case where multiple files are loaded at once, a list of SpeFile objects.

Raw data from a file is stored in NumPy arrays and can be accessed directly by

```python

>>> frame_data = loaded_files.data[frame][regionOfInterest]  

>>> frame_data = loaded_files[n].data[frame][regionOfInterest]  # where multiple files are loaded

```

Alternatively one can load an individual file by passing `SpeFile()` the source path directly:

```python

file_object = spe.SpeFile(path)

# is equivalent to...

file_object = spe.load()  # and selecting the same file/path

```

##### Automatic imaging and plotting

To quickly view an individual frame, region-of-interest, or spectrum, use the `image()` or `specplot()` methods. For example,

```python

>>> loaded_file.image()  # images the first frame and region of interest

>>> loaded_file.image(f, r)  # images frame 'f' and region of interest 'r'

>>> loaded_file.specplot()  # plots the loaded spectrum

```

##### Accessing metadata

Upon loading, the metadata contained in the file's XML footer is automatically parsed and stored as an `untangle` object in the `footer` variable. Elements and attributes can be accessed by calling the different elements and subelements of footer, ending with the attribute as a string:

```python

>>> sensor_height = loaded_file.footer.SpeFormat.Calibrations.SensorInformation['height']

```

One can print the full element tree by calling the `xmltree()` method.

### Dependencies

  - NumPy - data storage and file reading

  - tkinter - file selection dialog

  - matplotlib - imaging and plotting

  - [untangle](https://github.com/stchris/untangle) - XML parsing

### Version

1.0.0a - initial upload

License

----

MIT