ras-commander: Skill for Claude Code

Atlas 14 Spatial Variance Analysis

Invoke this skill to assess precipitation spatial variability in HEC-RAS models

Primary Sources (Read These First)

Canonical Contract:

• ras_commander/precip/AGENTS.md
  • Method selection for Atlas 14 grid and variance workflows
  • Critical precipitation rules and validation expectations
  • Reference notebooks for working examples

API Reference:

• ras_commander/precip/Atlas14Grid.py (404 lines)

  • get_pfe_from_project() - Main entry point for HEC-RAS integration
  • get_pfe_for_bounds() - Direct bounding box query
  • get_point_pfe() - Single point lookup

• ras_commander/precip/Atlas14Variance.py (322 lines)

  • analyze() - Full variance analysis
  • analyze_quick() - Rapid assessment (100-yr, 24-hr)
  • is_uniform_rainfall_appropriate() - Decision support
  • generate_report() - Export with plots

Working Example:

• examples/725_atlas14_spatial_variance.ipynb
  • Direct bounds queries
  • Point lookups
  • HEC-RAS project integration
  • Visualization

Quick Reference:

• .claude/rules/hec-ras/precipitation.md

---

Quick Reference

Typical Workflow (3 Steps)

from ras_commander.precip import Atlas14Variance

# Step 1: Quick check for representative event
stats = Atlas14Variance.analyze_quick("MyProject.g01.hdf")

# Step 2: Interpret results
if stats['range_pct'] > 10:
    # High variance - run full analysis
    results = Atlas14Variance.analyze(
        geom_hdf="MyProject.g01.hdf",
        durations=[6, 12, 24],
        return_periods=[10, 25, 50, 100]
    )

    # Step 3: Generate report
    Atlas14Variance.generate_report(
        results,
        output_dir="Atlas14_Report",
        project_name="My Project"
    )
else:
    # Low variance - uniform rainfall OK
    print("✓ Uniform rainfall appropriate")

Direct Grid Access

from ras_commander.precip import Atlas14Grid

# Get PFE for project extent
pfe = Atlas14Grid.get_pfe_from_project(
    geom_hdf="MyProject.g01.hdf",
    extent_source="2d_flow_area",  # or "project_extent"
    durations=[6, 12, 24],
    return_periods=[10, 50, 100],
    buffer_percent=10.0
)

# Access data
print(f"Grid size: {pfe['lat'].shape[0]} x {pfe['lon'].shape[0]}")
print(f"100-yr 24-hr max: {pfe['pfe_24hr'][:,:,5].max():.2f} inches")