sif_reader

Caution!!

sif_reader has renamed to sif_parser.
https://github.com/fujiisoup/sif_parser Use sif_parser instead.

Basic usage

A small package to read Andor Technology Multi-Channel files.

It provides the following methods,

sif_reader.np_open

Read '.sif' file and return as a np.ndarray for image and an OrderedDict for metadata.

>>> import sif_reader
>>> data, info = sif_reader.np_open('/path/to/file.sif')
>>> data
array([[[887.  , 881.25, 875.65, ..., 866.05, 870.  ],
        [905.6 , 872.7 , 900.7 , ..., 871.4 , 866.45],
        ...,
        [885.6 , 879.4 , 873.5 , ..., 883.6 , 877.  ],
        [879.4 , 873.  , 880.5 , ..., 881.  , 867.  ]]],
      dtype=float32)
>>> info
OrderedDict([('SifVersion', 65559),
             ('ExperimentTime', 1254330082),
             ('DetectorTemperature', -100.0),
             ...
            ])

If your calibration data is included in the file, this will be included as info['Calibration_data'] or info['Calibration_data_for_frame_1'].

sif_reader.xr_open('/path/to/file.sif'):

Read 'sif' file and return as a xr.DataArray. The metadata is stored in xr.DataArray.attrs. The calibration data and timestamps are stored as coordinates.

xarray is a very useful package to handle multi-dimensional arrays with metadata. See xarray project for the details.

>>> sif_reader.xr_open('testings/examples/image.sif')
<xarray.DataArray (Time: 1, height: 512, width: 512)>
array([[[887.  , 881.25, 875.65, ..., 866.05, 870.  ],
        [905.6 , 872.7 , 900.7 , ..., 871.4 , 866.45],
        [922.6 , 883.95, 899.  , ..., 864.6 , 864.8 ],
        ...,
        [880.65, 857.95, 883.55, ..., 866.  , 875.55],
        [885.6 , 879.4 , 873.5 , ..., 883.6 , 877.  ],
        [879.4 , 873.  , 880.5 , ..., 881.  , 867.  ]]],
      dtype=float32)
Coordinates:
  * Time     (Time) float64 0.0
Dimensions without coordinates: height, width
Attributes:
    SifVersion:            65559
    ExperimentTime:        1254330082
    DetectorTemperature:   -100.0
    ...

Utils

sif_reader.utils.extract_calibration

The Calibration_data entry of info contains coefficients of a cubic polynomial used to calculate the wavelengths of an image. To facilitate this sif_reader.utils contains the extract_calibration function, which returns the wavelength of each pixel.

data, info = sif_reader.np_open('path/to/file.sif')
wavelengths = sif_reader.utils.extract_calibration(info)

sif_reader.utils.parse

Used to parse a .sif file into a 2 column numpy array as wavelengths and counts.

import pandas as pd
import sif_reader


# parse the 'my_pl.sif' file
(data, info) = sif_reader.utils.parse('my_pl.sif')

# place data into a pandas Series
df = pd.Series(data[:, 1], index = data[:, 0])

CLI

Installs a command line interface (CLI) named sif_reader that can be used to convert .sif files to .csv.

Convert all .sif files in the current directory to .csv.

andor_sif

Convert all .sif files ending in pl in the current directly into a single .csv.

andor_sif --join *pl.sif

Use as a plugin for PIL

NOTE!! The current version does not work as a plugin, maybe due to updates in PIL. Contributions are very welcome. See the issue #7

We also provide a plugin for PIL,

from PIL import image
import sif_reader.plugin

I = Image.open('/path/to/file.sif')

Note that, however, it does not work for multiple-image files. Contribution is very welcome! The image mode is 'F', 32-bit floating-point greyscale.

History

This plugin is originally developed by soemraws based on Marcel Leutenegger's MATLAB script.

Current status

Andor has changed sif format for many times. Although I have tested this package with as many kinds of sif files as I have (the test suit is always checking the compatibility, as the badge above shows), it might be still incompatible with your particular sif file.

If your file cannot be read by this script, please raise an issue in github. If you send me your file, I can add your file into the test suit (I have a private repo in order to keep your sif file private).

Contribution is also very welcome.

License of original MATLAB script

Copyright (c) 2006, Marcel Leutenegger All rights reserved.

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

• Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
• Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution
• Neither the name of the Ecole Polytechnique Fédérale de Lausanne, Laboratoire d'Optique Biomédicale nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.