Metadata-Version: 2.1
Name: ansys-dpf-core
Version: 0.3.5
Summary: DPF Python gRPC client
Home-page: https://github.com/pyansys/pydpf-core
Author: ANSYS
Author-email: ramdane.lagha@ansys.com
Maintainer-email: pyansys.maintainers@ansys.com
License: MIT
Description: # DPF - Ansys Data Processing Framework
        
        [![PyPI version](https://badge.fury.io/py/ansys-dpf-core.svg)](https://badge.fury.io/py/ansys-dpf-core)
        
        [![Build Status](https://dev.azure.com/pyansys/pyansys/_apis/build/status/pyansys.DPF-Core?branchName=master)](https://dev.azure.com/pyansys/pyansys/_build/latest?definitionId=2&branchName=master)
        
        
        The Data Processing Framework (DPF) is designed to provide numerical
        simulation users/engineers with a toolbox for accessing and
        transforming simulation data. DPF can access data from solver result
        files as well as several neutral formats (csv, hdf5, vtk,
        etc.). Various operators are available allowing the manipulation and
        the transformation of this data.
        
        DPF is a workflow-based framework which allows simple and/or complex
        evaluations by chaining operators. The data in DPF is defined based on
        physics agnostic mathematical quantities described in a
        self-sufficient entity called field. This allows DPF to be a modular
        and easy to use tool with a large range of capabilities. It's a
        product designed to handle large amount of data.
        
        The Python ``ansys.dpf.core`` module provides a Python interface to
        the powerful DPF framework enabling rapid post-processing of a variety
        of Ansys file formats and physics solutions without ever leaving a
        Python environment.  
        
        ## Documentation
        
        Visit the [DPF-Core Documentation](https://dpfdocs.pyansys.com) for a
        detailed description of the library, or see the [Examples
        Gallery](https://dpfdocs.pyansys.com/examples/index.html) for more
        detailed examples.
        
        ## Installation
        
        Install this repository with:
        
        ```
        pip install ansys-dpf-core 
        ```
        
        You can also clone and install this repository with:
        
        ```
        git clone https://github.com/pyansys/DPF-Core
        cd DPF-Core
        pip install . --user
        ```
        
        
        ## Running DPF
        
        See the example scripts in the examples folder for some basic example.  More will be added later.
        
        ### Brief Demo
        
        Provided you have ANSYS 2021R1 or higher installed, a DPF server will start
        automatically once you start using DPF.
        
        To open a result file and explore what's inside, do:
        
        ```py
        >>> from ansys.dpf import core as dpf
        >>> from ansys.dpf.core import examples
        >>> model = dpf.Model(examples.simple_bar)
        >>> print(model)
        
            DPF Model
            ------------------------------
            Static analysis
            Unit system: Metric (m, kg, N, s, V, A)
            Physics Type: Mecanic
            Available results:
                 -  displacement: Nodal Displacement
                 -  element_nodal_forces: ElementalNodal Element nodal Forces
                 -  elemental_volume: Elemental Volume
                 -  stiffness_matrix_energy: Elemental Energy-stiffness matrix
                 -  artificial_hourglass_energy: Elemental Hourglass Energy
                 -  thermal_dissipation_energy: Elemental thermal dissipation energy
                 -  kinetic_energy: Elemental Kinetic Energy
                 -  co_energy: Elemental co-energy
                 -  incremental_energy: Elemental incremental energy
                 -  structural_temperature: ElementalNodal Temperature
            ------------------------------
            DPF  Meshed Region: 
              3751 nodes 
              3000 elements 
              Unit: m 
              With solid (3D) elements
            ------------------------------
            DPF  Time/Freq Support: 
              Number of sets: 1 
            Cumulative     Time (s)       LoadStep       Substep         
            1              1.000000       1              1               
        
        
        ```
        
        Read a result with:
        
        ```py
        >>> result = model.results.displacement.eval()
        ```
        
        Then start connecting operators with:
        
        ```py
        >>> from ansys.dpf.core import operators as ops
        >>> norm = ops.math.norm(model.results.displacement())
        ```
        
        ### Starting the Service
        
        The `ansys.dpf.core` automatically starts a local instance of the DPF service in the
        background and connects to it.  If you need to connect to an existing
        remote or local DPF instance, use the ``connect_to_server`` function:
        
        ```py
        >>> from ansys.dpf import core as dpf
        >>> dpf.connect_to_server(ip='10.0.0.22', port=50054)
        ```
        
        Once connected, this connection will remain for the duration of the
        module until you exit python or connect to a different server.
        
             
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Requires-Python: >=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*
Description-Content-Type: text/markdown
Provides-Extra: plotting
Provides-Extra: reporting
