Python package to read Andor sif file.
Project description
sif_parser
A small package to read Andor Technology Multi-Channel files.
This package was renamed from sif_reader.
Install
This package can be installed via pip
pip install sif_parser
or if you have git
installed in your system, you can also do
pip install git+https://www.github.com/fujiisoup/sif_parser
Basic usage
It provides the following methods,
sif_parser.np_open
Read '.sif' file and return as a np.ndarray
for image and an OrderedDict
for metadata.
>>> import sif_parser
>>> data, info = sif_parser.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_parser.xr_open('/path/to/file.sif')
:
This method is only included if the
xarray
project is installed.
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_parser.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_parser.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_parser.utils
contains the extract_calibration
function, which returns the wavelength of each pixel.
data, info = sif_parser.np_open('path/to/file.sif')
wavelengths = sif_parser.utils.extract_calibration(info)
sif_parser.utils.parse
Used to parse a .sif file into a 2 column numpy array as wavelengths and counts.
import pandas as pd
import sif_parser
# parse the 'my_pl.sif' file
(data, info) = sif_parser.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_parser
that can be used to
convert .sif files to .csv.
Convert all .sif files in the current directory to .csv.
sif_parser
Convert all .sif files ending in pl
in the current directly into a single .csv.
sif_parser --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_parser.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.
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