phenotastic 0.5.1

Using the Python API

from phenotastic import PhenoMesh, Pipeline, load_preset
import pyvista as pv

# Load a mesh
polydata = pv.read("my_mesh.vtk")
mesh = PhenoMesh(polydata)

# Process with the default pipeline
pipeline = load_preset()
result = pipeline.run(mesh)

# Access results
print(f"Mesh has {result.mesh.n_points} points")
print(f"Found {len(result.domains.unique())} domains")

Using the CLI

# Run with default pipeline
phenotastic run image.tif --output results/

# Run with custom config
phenotastic run image.tif --config my_pipeline.yaml

# Generate a config template
phenotastic init-config my_pipeline.yaml

# List available operations
phenotastic list-operations

# List available presets
phenotastic list-presets

# Validate configuration
phenotastic validate my_pipeline.yaml

# View a mesh interactively
phenotastic view mesh.vtk --scalars curvature

Example Configuration

steps:
  # Create mesh from contour
  - name: create_mesh
    params:
      step_size: 1

  # Smoothing
  - name: smooth
    params:
      iterations: 100
      relaxation_factor: 0.01

  # Remesh to regularize faces
  - name: remesh
    params:
      n_clusters: 10000

  # More smoothing
  - name: smooth
    params:
      iterations: 50

  # Domain segmentation
  - name: compute_curvature
    params:
      curvature_type: mean

  - name: segment_domains

  - name: merge_small
    params:
      threshold: 50

  - name: extract_domaindata

Default Pipeline

Phenotastic provides a default pipeline that includes the full workflow from 3D image to domain analysis. The default pipeline is automatically used when calling load_preset() without arguments or when running the CLI.

Image/Contour Operations

• contour: Generate binary contour from 3D image using morphological active contours

• create_mesh: Create mesh from contour using marching cubes

• create_cellular_mesh: Create mesh from segmented image (one mesh per cell)

Mesh Processing Operations

• smooth: Laplacian smoothing

• smooth_taubin: Taubin smoothing (less shrinkage than Laplacian)

• smooth_boundary: Smooth only boundary edges

• remesh: Regularize faces using ACVD algorithm

• decimate: Reduce mesh complexity by removing faces

• subdivide: Increase mesh resolution by subdividing faces

• repair_holes: Fill small holes in the mesh

• repair: Full mesh repair using MeshFix

• make_manifold: Remove non-manifold edges

• filter_curvature: Remove vertices outside curvature threshold range

• remove_normals: Remove vertices based on normal angle

• remove_bridges: Remove triangles where all vertices are on the boundary

• remove_tongues: Remove tongue-like artifacts

• extract_largest: Keep only the largest connected component

• clean: Remove degenerate cells

• triangulate: Convert all faces to triangles

• compute_normals: Compute surface normals

• flip_normals: Flip all surface normals

• correct_normal_orientation: Correct normal orientation relative to an axis

• rotate: Rotate mesh around an axis

• clip: Clip mesh with a plane

• erode: Erode mesh by removing boundary points

• ecft: ExtractLargest, Clean, FillHoles, Triangulate (combined operation)

Domain Operations

• compute_curvature: Compute mesh curvature (mean, gaussian, minimum, maximum)

• filter_scalars: Apply filter to curvature field (median, mean, minmax, maxmin)

• segment_domains: Create domains via steepest ascent on curvature field

• merge_angles: Merge domains within angular threshold from meristem

• merge_distance: Merge domains within spatial distance threshold

• merge_small: Merge small domains to their largest neighbor

• merge_engulfing: Merge domains mostly encircled by a neighbor

• merge_disconnected: Connect domains isolated from meristem

• merge_depth: Merge domains with similar depth values

• define_meristem: Identify the meristem domain

• extract_domaindata: Extract geometric measurements for each domain