Metadata-Version: 2.1
Name: csdmpy
Version: 0.3.3
Summary: A python module for the core scientific dataset model.
Home-page: https://github.com/DeepanshS/csdmpy/
Author: Deepansh Srivastava
Author-email: srivastava.89@osu.edu
License: BSD-3-Clause
Description: 
        # The csdmpy project
        
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        The _csdmpy_ package is a Python support for the core scientific
        dataset (CSD) model file exchange-format.
        The package is based on the core scientific dataset (CSD) model which is
        designed as a building block in the development of a more sophisticated
        portable scientific dataset file standard.
        The CSD model is capable of handling a wide variety of
        scientific datasets both within and across disciplinary fields.
        
        The main objective of this python package is to facilitate an easy import and
        export of the CSD model serialized JSON files for Python users. The
        package utilizes Numpy library and, therefore, offers the end users versatility
        to process or visualize the imported datasets with any third party package(s)
        compatible with Numpy.
        
        For further reading, refer to the [documentation](https://csdmpy.readthedocs.io/en/latest/).
        
        > **Download the examples files using in this package**
        >
        > [![](https://img.shields.io/badge/Download-CSDM%20sample%20files-blueviolet)](https://osu.box.com/s/bq10pc5jyd3mu67vqvhw4xmrqgsd0x8u)
        
        > **See example gallery**
        >
        > [![](https://img.shields.io/badge/View-Example%20Gallery-Purple?size=large)](https://csdmpy.readthedocs.io/en/latest/auto_examples/index.html)
        
        ## The core scientific dataset (CSD) model
        
        The core scientific dataset (CSD) model is a _light-weight_, _portable_,
        _versatile_, and _standalone_ data model capable of handling a variety of
        scientific datasets. The model only encapsulates
        data values and the minimum metadata, to accurately represent a _p_-component
        dependent variable,
        discretely sampled at _M_ unique points in a _d_-dimensional coordinate space.
        The model is not intended to encapsulate
        any information on how the data might be acquired, processed, or visualized.
        
        The data model is _versatile_ in allowing many use cases for most spectroscopy,
        diffraction, and imaging techniques. As
        such the model supports multi-component datasets associated with continuous
        physical quantities that are discretely sampled in a multi-dimensional space
        associated with other carefully controlled quantities, for e.g., a mass as a
        function of temperature, a current as a function of voltage and time, a signal
        voltage as a function of magnetic field gradient strength, a color image with
        a red, green, and blue (RGB) light intensity components as a function of two
        independent spatial dimensions, or the six components of the symmetric
        second-rank diffusion tensor MRI as a function of three independent spatial
        dimensions. Additionally, the model supports multiple dependent variables
        sharing the same _d_-dimensional coordinate space. For instance,
        the simultaneous measurement of current and voltage as a function of time.
        Another example would be the simultaneous acquisition of air temperature,
        pressure, wind velocity, and
        solar-flux as a function of Earth’s latitude and longitude coordinates. We
        refer to these dependent variables as _correlated-datasets_.
        
        The CSD model is independent of the hardware,
        operating system, application software, programming language, and the
        object-oriented file-serialization format utilized in serializing the CSD model
        to the file. Out of numerous file serialization formats, XML, JSON, property
        list, we adopt the data-exchange oriented JSON (JavaScript Object Notation)
        file-serialization format because it is _human-readable_, and _easily integrable_ with any number of programming languages
        and field related application-software.
        
        ## Installing _csdmpy_ package
        
        **Using PIP**:
        
        PIP is a package manager for Python packages and is included with
        python version 3.4 and higher.
        
            $ pip install csdmpy
        
        ## Citation
        
        Srivastava D.J., Vosegaard T., Massiot D., Grandinetti P.J. (2020) Core Scientific Dataset Model: A lightweight and portable model and file format for multi-dimensional scientific data. [PLOS ONE 15(1): e0225953.](https://doi.org/10.1371/journal.pone.0225953)
        
        ## Check out the media coverage.
        
        - [<img src="https://inc.cnrs.fr/sites/institut_inc/files/styles/top_left/public/image/cnrs_20180120_0025%20%281%29.jpg?itok=i3wlyGBq" height="64" width="64"> Des chimistes élaborent un nouveau format pour le partage de données scientifiques](https://inc.cnrs.fr/fr/cnrsinfo/des-chimistes-elaborent-un-nouveau-format-pour-le-partage-de-donnees-scientifiques)
        
        - [<img src="https://www.technology.org/texorgwp/wp-content/uploads/2020/01/1920_data-1536x1024.jpg" height="64" width="64"> Simplifying how scientists share data](https://www.technology.org/2020/01/03/simplifying-how-scientists-share-data/)
        
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: Operating System :: OS Independent
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Scientific/Engineering
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Provides-Extra: matplotlib
