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  • aPriori Documentation
  • Related Projects
    • BLASTNet Bearable Large Accessible Scientific Training Network-of-Datasets
    • PyCSP A collection of tools based on Computational Singular Perturbation for the analysis of chemically reacting systems.
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Project Home

  • 👋 Welcome

Getting started

  • What is aPriori
  • Installation
  • Quickstart
  • Article preprint

Fundamentals and usage

  • Tutorial 1: Scalar class basic usage
  • Tutorial 2: Filtering numpy arrays
  • Tutorial 3: Read a DNS dataset
  • Tutorial 4: Data visualization
  • Tutorial 5: Cut DNS field
  • Tutorial 6: Favre filtering for variable density flows
  • Tutorial 7: Data-driven turbulent combustion modeling
  • Tutorial 8: Computational Singular Perturbation (CSP) analysis

API Guide

  • API Guide
    • aPriori.DNS
      • aPriori.DNS.Field
      • aPriori.DNS.Scalar
      • aPriori.DNS.Mesh
      • aPriori.DNS.add_variable
      • aPriori.DNS.compute_cell_volumes
      • aPriori.DNS.delete_existing_files
      • aPriori.DNS.delete_file
      • aPriori.DNS.download
      • aPriori.DNS.downsample
      • aPriori.DNS.process_file
      • aPriori.DNS.check_mesh_files
      • aPriori.DNS.build_meshgrid
      • aPriori.DNS.filter_gauss
      • aPriori.DNS.filter_box
      • aPriori.DNS.filter_3D
      • aPriori.DNS.save_file
      • aPriori.DNS.generate_mask
      • aPriori.DNS.check_same_shape
      • aPriori.DNS.check_input_string
      • aPriori.DNS.plot_power_spectrum
      • aPriori.DNS.process_chunk_LFR
      • aPriori.DNS.process_chunk_PSR
      • aPriori.DNS.section_and_average
      • aPriori.DNS.read_variable_in_chunks
      • aPriori.DNS.process_species_in_chunks
      • aPriori.DNS.x_midplane
      • aPriori.DNS.y_midplane
      • aPriori.DNS.z_midplane
    • aPriori.NN
      • aPriori.NN.TrainingBuilder
      • aPriori.NN.VectorScaler
      • aPriori.NN.is_json_file
    • aPriori.derivatives
      • aPriori.derivatives.set_gradients_order
      • aPriori.derivatives.print_gradients_order
      • aPriori.derivatives.gradient_x
      • aPriori.derivatives.gradient_y
      • aPriori.derivatives.gradient_z
      • aPriori.derivatives.laplacian
    • aPriori.plot_utilities
      • aPriori.plot_utilities.parity_plot
      • aPriori.plot_utilities.contour_plot
      • aPriori.plot_utilities.cond_mean_plot
      • aPriori.plot_utilities.scatter
      • aPriori.plot_utilities.plot_multifield
      • aPriori.plot_utilities.bins
      • aPriori.plot_utilities.generate_colors
      • aPriori.plot_utilities.generate_markers
      • aPriori.plot_utilities.generate_lines
    • aPriori.Field
    • aPriori.Scalar
    • aPriori.Mesh
    • aPriori.add_variable
    • aPriori.delete_file
    • aPriori.download
    • aPriori.process_file
    • aPriori.filter_gauss
    • aPriori.filter_box
    • aPriori.filter_3D
    • aPriori.save_file
    • aPriori.gradient_x
    • aPriori.gradient_y
    • aPriori.gradient_z
    • aPriori.contour_plot
    • aPriori.parity_plot
    • aPriori.cond_mean_plot
    • aPriori.scatter

Conference presentations

  • Machine Learning for Fluids, Paris 2024
  • CYPHER Meeting, Naples 2025
  • Machine Learning for Fluids, Amsterdam 2026

Extras

  • aPriori License
  • How to cite
  • Bibliography
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Getting started¶

Getting started

  • What is aPriori
  • Installation
  • Quickstart

Copyright © 2026, Lorenzo Piu, Heinz Pitsch, Alessandro Parente

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