S2 Labs
  • Introduction
  • Getting Started
    • Quickstart
  • Command Line Options
    • isciml
    • isciml: generate-mesh tdem-loop
    • isciml: generate-models
      • inspect-mesh
      • initialize-mu-sigma
      • one-pipe
    • isciml: generate
    • isciml: train
    • isciml: inference
  • isciml tdem
  • Distributed computing
    • Overview
    • Data generation using Slurm
    • Multi-GPU Training
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  • Overview
  • Key Functionalities
  • Main Subcommands
  • Usage
  • Importance in Workflow
  1. Command Line Options

isciml: generate-models

Overview

The generate-models command group in isciml is designed for creating and manipulating the underlying physical models used in 3D non-invasive imaging problems. This group of commands allows users to set up the geometries and properties of the imaging scenarios they want to simulate or analyze.

Key Functionalities

  1. Model Creation: Generate various types of physical models, such as pipe configurations in different media.

  2. Property Initialization: Set initial values for physical properties like magnetic permeability (mu) and electrical conductivity (sigma) within the models.

  3. Mesh Manipulation: Create, modify, and inspect mesh files that represent the physical space of the imaging problem.

Main Subcommands

  1. initialize-mu-sigma: Initialize the mu (magnetic permeability) and sigma (electrical conductivity) values for different regions in a mesh file.

  2. inspect-mesh: Examine and report on the properties and structure of a given mesh file.

  3. one-pipe: Generate models with a single pipe configuration, allowing for customization of various geometric and physical parameters.

Usage

The general syntax for using commands in this group is:

singularity exec isciml.sif isciml generate-models [SUBCOMMAND] [OPTIONS]

Each subcommand has its own set of options for fine-tuning the model generation process.

Importance in Workflow

The generate-models command group is typically the first step in the isciml workflow. The models created here serve as the foundation for subsequent steps such as data generation, training, and inference. Accurate and flexible model generation is crucial for creating realistic simulations and achieving meaningful results in non-invasive imaging applications.

For detailed information on each subcommand and its options, users can refer to the specific documentation pages or use the --help option with each subcommand.

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Last updated 9 months ago