Metadata-Version: 2.1
Name: csdmpy
Version: 0.1.1
Summary: A python module for importing and exporting CSD model file-format.
Home-page: https://github.com/DeepanshS/csdmpy/archive/v0.1-beta.1.tar.gz
Author: Deepansh Srivastava
Author-email: srivastava.89@osu.edu
License: BSD-3-Clause
Description: 
        
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        The `csdmpy` package
        ====================
        
        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.
        
        Read the **`csdmpy documentation`** [here](https://csdmpy.readthedocs.io/en/latest/).
        
        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
        ===========================
        
        We recommend installing [anaconda](https://www.anaconda.com/distribution/)
        distribution for python version 3.6 or higher. The anaconda distribution
        ships with numerous packages and modules including Numpy, Scipy, and Matplotlib
        which are useful packages for handling scientific datasets.
        
        **Using PIP**:
        
        PIP is a package manager for Python packages and is included with
        python version 3.4 and higher.
        
            $ pip install csdmpy
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Requires-Python: >=3.6
Description-Content-Type: text/markdown
