AgentSkillsCN

hecras_compute_rascontrol

Executes HEC-RAS plans using RasControl class via HECRASController COM interface for legacy HEC-RAS versions (3.x-5.x). Handles COM lifecycle management, session tracking, orphan cleanup, steady/unsteady result extraction, and watchdog protection for Jupyter notebooks. Use when automating legacy HEC-RAS, extracting results from older versions, comparing across HEC-RAS versions, or needing COM-based automation that RasCmdr cannot provide. Triggers: RasControl, HECRASController, COM, legacy, HEC-RAS 4, HEC-RAS 5, win32com, steady results, unsteady results, version comparison, COM interface, legacy automation, 3.x, 4.x, 5.x, orphan cleanup, watchdog, session tracking.

SKILL.md
--- frontmatter
name: hecras_compute_rascontrol
description: |
  Executes HEC-RAS plans using RasControl class via HECRASController COM interface
  for legacy HEC-RAS versions (3.x-5.x). Handles COM lifecycle management, session
  tracking, orphan cleanup, steady/unsteady result extraction, and watchdog
  protection for Jupyter notebooks. Use when automating legacy HEC-RAS, extracting
  results from older versions, comparing across HEC-RAS versions, or needing
  COM-based automation that RasCmdr cannot provide.
  Triggers: RasControl, HECRASController, COM, legacy, HEC-RAS 4, HEC-RAS 5,
  win32com, steady results, unsteady results, version comparison, COM interface,
  legacy automation, 3.x, 4.x, 5.x, orphan cleanup, watchdog, session tracking.

Executing HEC-RAS Plans via RasControl (COM Interface)

Use RasControl to automate HEC-RAS versions 3.x-5.x via the HECRASController COM interface. For HEC-RAS 6.x+, use RasCmdr instead.

Primary Sources

1. RasControl Implementation

Location: ras_commander/RasControl.py

Read these key sections:

  • Lines 438-527: RasControl class with version mapping and output variable codes
  • Lines 543-742: COM lifecycle management (_com_open_close())
  • Lines 746-884: run_plan() with smart skip and watchdog protection
  • Lines 936-1177: get_steady_results() - extract steady state profiles
  • Lines 1179-1458: get_unsteady_results() - extract time series with Max WS
  • Lines 1647-1909: Process management API (orphan cleanup)

2. Working Examples (Jupyter Notebooks)

  • examples/120_automating_ras_with_win32com.ipynb - Low-level win32com exploration
  • examples/121_legacy_hecrascontroller_and_rascontrol.ipynb - Complete RasControl workflows

3. Supporting Documentation

  • .claude/rules/hec-ras/execution.md - Execution mode comparison
  • ras_commander/CLAUDE.md - Library context and module organization

When to Use RasControl vs RasCmdr

ScenarioUse RasControlUse RasCmdr
HEC-RAS 3.x-5.xYesNo
HEC-RAS 6.x+No (use COM only if needed)Yes (preferred)
Need GUI interactionYes (COM opens GUI)No (headless)
Version comparisonYesYes
Production workflowsLimitedPreferred
Parallel executionNo (single-threaded)Yes

Quick Reference

Basic Workflow

python
from ras_commander import init_ras_project, RasControl

# Initialize project with version
init_ras_project(project_path, "5.0.6")  # Or "506", "4.1", "41", etc.

# Run plan (checks if current, skips if up-to-date)
success, msgs = RasControl.run_plan("02")

# Force recomputation
success, msgs = RasControl.run_plan("02", force_recompute=True)

# Extract steady state results
df_steady = RasControl.get_steady_results("02")

# Extract unsteady time series (includes Max WS row)
df_unsteady = RasControl.get_unsteady_results("01")

Version Format Support

RasControl accepts flexible version formats:

python
# All equivalent - HEC-RAS 4.1
init_ras_project(path, "4.1")
init_ras_project(path, "41")

# All equivalent - HEC-RAS 5.0.6
init_ras_project(path, "5.0.6")
init_ras_project(path, "506")

# All equivalent - HEC-RAS 6.6
init_ras_project(path, "6.6")
init_ras_project(path, "66")

Supported versions: 3.0-3.1.3, 4.0-4.1, 5.0-5.0.7, 6.0-6.7

Separating Max WS from Time Series

python
# Max WS contains computational maximums (critical for design!)
df_maxws = df_unsteady[df_unsteady['time_string'] == 'Max WS']
df_timeseries = df_unsteady[df_unsteady['datetime'].notna()]

# Plot time series with Max WS reference line
import matplotlib.pyplot as plt
xs_data = df_timeseries[df_timeseries['node_id'] == '10000']
plt.plot(xs_data['datetime'], xs_data['wsel'])
plt.axhline(df_maxws[df_maxws['node_id'] == '10000']['wsel'].iloc[0],
            color='r', linestyle='--', label='Max WS')

COM Lifecycle Management

Critical Pattern: Open-Operate-Close

RasControl handles COM lifecycle automatically via _com_open_close():

python
# Internal pattern (you don't call this directly)
# 1. Create COM object: win32com.client.Dispatch("RAS66.HECRASController")
# 2. Open project: com_rc.Project_Open(project_path)
# 3. Create session lock for crash recovery
# 4. Execute operation
# 5. Close HEC-RAS: com_rc.QuitRas()
# 6. Clean up session tracking

Why this matters:

  • COM objects MUST be released properly
  • Orphaned ras.exe processes consume resources
  • Session tracking enables recovery after crashes

Session Tracking Infrastructure

RasControl tracks all active COM sessions:

python
# List tracked processes
df = RasControl.list_processes()
print(df)  # Shows PID, tracked status, project, age

# List all ras.exe (including untracked)
df_all = RasControl.list_processes(show_all=True)

Orphan Detection and Cleanup

After crashes or Jupyter kernel restarts:

python
# Scan for orphaned processes
orphans = RasControl.scan_orphans()
if orphans:
    print(f"Found {len(orphans)} orphaned processes")

# Interactive cleanup (prompts for confirmation)
RasControl.cleanup_orphans()

# Automatic cleanup (no prompts)
count = RasControl.cleanup_orphans(interactive=False)

# Dry run (see what would be cleaned)
RasControl.cleanup_orphans(dry_run=True)

# Nuclear option - kill ALL ras.exe (requires "YES" confirmation)
RasControl.force_cleanup_all()

Watchdog Protection

For long-running operations in Jupyter:

python
# With watchdog (default) - survives kernel restarts
success, msgs = RasControl.run_plan("01", use_watchdog=True, max_runtime=3600)

# Without watchdog (not recommended in Jupyter)
success, msgs = RasControl.run_plan("01", use_watchdog=False)

Watchdog features:

  • Independent Python process monitors parent
  • Terminates ras.exe if Python crashes
  • Enforces max_runtime timeout
  • Responds to manual lock file deletion

Result Extraction

Steady State Results

python
df = RasControl.get_steady_results("02")

# DataFrame columns:
# - river, reach, node_id (location)
# - profile (profile name)
# - wsel (water surface elevation)
# - velocity, flow, froude, energy, max_depth, min_ch_el

Unsteady Results with Datetime

python
df = RasControl.get_unsteady_results("01")

# DataFrame columns:
# - river, reach, node_id (location)
# - time_index (1 = Max WS, 2+ = timesteps)
# - time_string ("Max WS" or "18FEB1999 0000")
# - datetime (datetime64[ns], NaT for Max WS)
# - wsel, velocity, flow, froude, energy, max_depth, min_ch_el

Computation Messages

python
# Read computation messages (tries .txt then HDF)
msgs = RasControl.get_comp_msgs("01")
print(msgs)

Common Patterns

Pattern: Version Comparison

python
from ras_commander import RasPlan

versions = [("5.0.6", "506"), ("6.3.1", "631"), ("6.6", "66")]
results = {}

for version_name, version_code in versions:
    # Clone plan for this version
    new_plan = RasPlan.clone_plan("01", new_shortid=f"v{version_code}")

    # Run with this version
    init_ras_project(project_path, version_name)
    RasControl.run_plan(new_plan, force_recompute=True)

    # Extract results
    results[version_name] = RasControl.get_unsteady_results(new_plan)

# Compare across versions
for version, df in results.items():
    max_wse = df[df['time_string'] == 'Max WS']['wsel'].max()
    print(f"v{version}: Max WSE = {max_wse:.2f} ft")

Pattern: Error Recovery

python
try:
    success, msgs = RasControl.run_plan("01")
except Exception as e:
    print(f"COM error: {e}")

    # Clean up any orphaned processes
    RasControl.cleanup_orphans(interactive=False)

    # Read computation messages for diagnosis
    comp_msgs = RasControl.get_comp_msgs("01")
    print(f"Computation messages:\n{comp_msgs}")

Pattern: Extract Before Running

python
# Check if results are current before running
success, msgs = RasControl.run_plan("01")

if "Results are current" in msgs[0]:
    print("Skipped - results already up-to-date")
else:
    print("Plan executed")

# Extract results (works whether run or skipped)
df = RasControl.get_unsteady_results("01")

Troubleshooting

COM Object Not Found

python
# Error: "COM object not found" or "Class not registered"

# Verify HEC-RAS COM registration
import win32com.client
try:
    rc = win32com.client.Dispatch("RAS66.HECRASController")
    print("COM registered correctly")
except Exception as e:
    print(f"COM issue: {e}")
    print("Solution: Reinstall HEC-RAS or run as Administrator")

HEC-RAS Freezes or Hangs

python
# Check for orphaned processes
RasControl.list_processes(show_all=True)

# Clean up orphans
RasControl.cleanup_orphans()

# If still stuck, nuclear option (kills ALL ras.exe)
RasControl.force_cleanup_all()

Results Extraction Fails

python
# If get_steady_results() or get_unsteady_results() fails:

# 1. Check if plan was executed
success, msgs = RasControl.run_plan("01", force_recompute=True)

# 2. Check computation messages
comp_msgs = RasControl.get_comp_msgs("01")
print(comp_msgs)

# 3. Look for "error" or "warning" in messages
if "error" in comp_msgs.lower():
    print("Computation had errors - fix model issues")

Version Mismatch

python
# Error: Version 'X.Y' not supported

# Check supported versions
print(RasControl.VERSION_MAP.keys())

# Use normalized format
init_ras_project(path, "5.0.6")  # Not "5.06" or "5.6"

Performance Considerations

COM is Single-Threaded

  • RasControl cannot run plans in parallel
  • Each operation opens/closes HEC-RAS GUI
  • For parallel execution, use RasCmdr with HEC-RAS 6.x+

GUI Overhead

  • COM interface opens HEC-RAS GUI (requires active desktop)
  • Slower than RasCmdr subprocess execution
  • Consider RDP session for headless servers

Memory Usage

  • Large unsteady simulations may consume significant RAM
  • Use max_times parameter to limit extraction:
    python
    df = RasControl.get_unsteady_results("01", max_times=20)
    

Migration Path: RasControl to RasCmdr

When upgrading to HEC-RAS 6.x+:

python
# Legacy (RasControl - HEC-RAS 5.x)
init_ras_project(path, "5.0.6")
RasControl.run_plan("01")
df = RasControl.get_steady_results("01")

# Modern (RasCmdr - HEC-RAS 6.x)
from ras_commander import RasCmdr
from ras_commander.hdf import HdfResultsPlan

init_ras_project(path, "6.6")
RasCmdr.compute_plan("01")
hdf = HdfResultsPlan(ras.plan_df.loc[0, 'HDF_Results_Path'])
wse = hdf.get_steady_wse()

Cross-References

Rules (follow these):

  • .claude/rules/hec-ras/execution.md -- General execution context

Agents (delegate when needed):

  • win32com-automation-expert -- Delegate for COM interface details and GUI automation

Skills (related workflows):

  • hecras_compute_plans -- Preferred: modern RasCmdr execution (HEC-RAS 6.x+)
  • hecras_extract_results -- Downstream: extract results after COM execution

Primary sources:

  • ras_commander/RasControl.py -- HECRASController wrapper
  • examples/120_automating_ras_with_win32com.ipynb -- COM automation tutorial
  • examples/121_legacy_hecrascontroller_and_rascontrol.ipynb -- RasControl patterns