Language/Application
Language/Sofware: C, Fortran, IDL, MATLAB, Python
Application type(s): Data Read/Write
Related project(s):
Description:
The library contains high-level read functions for HDF5 files in R and MATLAB.
Author(s): Aminata Ndiaye (CGTD)
Aug / 25 / 2014
Language/Sofware: Numpy, Python
Application type(s): Data Conversion, Data Read/Write
Related project(s):
Description:
This tool is a reading Python software for SSMI binary files consisting in some headers followed by records with the same pattern (Headers and record patterns are described in text files: ./conf/).
Datasets are returned as Numpy arrays and write in HDF4 file.
Author(s): Nicolas Henriot. Bruno Six (ICARE)
Feb / 27 / 2014
Language/Sofware: Numpy, Python
Application type(s): Data Conversion, Data Read/Write
Related project(s):
Description:
This tool is a reading Python software for SSMI binary files consisting in some headers followed by records with the same pattern (Headers and record patterns are described in text files: ./conf/).
Datasets are returned as Numpy arrays and write in HDF4 file.
Author(s): Nicolas Henriot. Bruno Six (ICARE)
Feb / 26 / 2014
Language/Sofware: C, Fortran, Fortran77, Fortran90, IDL, MATLAB, Python
Application type(s): Data Read/Write
Related project(s):
Description:
The library contains high-level read functions for HDF4 files in C, Fortran 77, Fortran 90, IDL, Python and MATLAB
Author(s): Bruno Six, Nicolas Pascal, Aminata Ndiaye (ICARE) ; Francois-Marie Breon (IPSL-LSCE)
Feb / 25 / 2014
Language/Sofware: Numpy, PIL, Python
Application type(s): Data Conversion, Visualization
Related project(s):
Description:
This application creates an image of a 2D HDF4 SDS. It supports different colormaps, min/max thresholding, scaling, fill value filtering…
Many output image formats are also supported.
Author(s): Nicolas Pascal (ICARE)
Jul / 25 / 2012
Language/Sofware: Numpy, Python
Application type(s): Data Read/Write
Related project(s):
Description:
This tool is a generic reading Python module for all binary files consisting in some headers followed by records with the same pattern.
Headers and record patterns are described in text files. Datasets are returned as Numpy arrays.
Author(s): Bruno SIX (ICARE)