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User Guide

Welcome to the ORION user guide! This section provides comprehensive documentation for using ORION's command-line converter and programming APIs.

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Overview

ORION provides three ways to work with scientific data:

1. Command-line Converter

The fastest way to convert between formats without writing any code:

ORION --input-format tecplot --input-file data.dat \
      --output-format vtk --output-file output.vtk

Best for:

  • Quick one-off conversions
  • Batch processing with shell scripts
  • Integration into existing workflows

Learn more: Converter Guide

2. Fortran API

Native Fortran library for IO applications in external codes:

use Lib_ORION_data
use Lib_Tecplot

type(ORION_data) :: IOfield
integer :: E_IO

E_IO = tec_read_structured_multiblock(filename='data.dat', orion=IOfield)

Best for:

  • Integration with Fortran solvers
  • Direct memory management
  • All format support (Tecplot, VTK, PLOT3D)

Learn more: Fortran API Guide

3. Python API

Convenient Python interface for scripting and analysis:

from ORION import read_TEC

x, y, z, var, varnames = read_TEC('data.dat')

Limited IO

Python API may be used only for reading.

Best for:

  • Post-processing and analysis
  • Data visualization

Learn more: Python API Guide

Supported File Formats

ORION supports the following scientific data formats:

Format Description Fortran Python Command-line
Tecplot ASCII Text-based format ✅ Read/Write ✅ Read/Write ✅
Tecplot Binary Binary format ✅ Read/Write¹ ❌ ✅¹
VTK Visualization Toolkit format ✅ Read/Write ❌ ✅
PLOT3D NASA structured grid format ✅ Read/Write ❌ ✅

¹ Requires building with --use-tecio flag

Learn more: Supported Formats

Advanced Topics

Multi-Block Data

All ORION interfaces support multi-block structured grids:

  • Fortran: Iterate over blocks with array indexing
  • Python: Index into block dimension of NumPy arrays
  • Converter: Automatically handles multi-block files

Troubleshooting

Common Issues

"Format not supported"

  • Check that format is spelled correctly
  • Verify file extension matches format
  • For binary Tecplot, ensure TecIO is enabled

"Out of memory"

  • Use the converter for very large files
  • In Fortran, deallocate arrays after use
  • In Python, process data in chunks

More help: Each guide has a dedicated troubleshooting section.

Best Practices

For Efficient Workflows

  1. Use the right tool: Converter for conversions, APIs for processing
  2. Cache conversions: Don't reconvert the same file repeatedly
  3. Choose formats wisely: Binary formats are faster for large data
  4. Test with small data: Verify logic before running on large files

For Code Quality

  1. Check error codes: Always verify I/O operations succeeded
  2. Document your code: Explain why, not just what
  3. Add tests: Ensure your code works as expected
  4. Use version control: Track changes to your scripts

For Performance

  1. Minimize I/O: Read once, process multiple times
  2. Use binary formats: Faster than ASCII for large datasets
  3. Vectorize operations: Use array operations instead of loops (Python)

Additional Resources

Examples

  • Examples: Complete working examples in src/lib/test

External Resources

What's Next?

Ready to dive deeper? Here are your next steps:

  1. Learn the converter - Start with command-line conversion
  2. Explore Fortran API - High-performance programming
  3. Try Python API - Convenient scripting