Parsing HEC-RAS Compute Messages

Primary Sources (navigate to these for complete details):

HDF Class Reference: ras_commander/hdf/AGENTS.md - Class hierarchy, decorators
HdfResultsPlan Implementation: ras_commander/hdf/HdfResultsPlan.py - Compute message methods
Working Example: examples/400_1d_hdf_data_extraction.ipynb - Compute message extraction

This skill provides patterns for extracting and interpreting HEC-RAS computation output. For implementation details, see the primary sources above.

Quick Start

Check Plan Completion and Extract Messages

from ras_commander import init_ras_project, HdfResultsPlan

# Initialize project
init_ras_project("C:/Projects/MyModel", "6.6")

# Extract compute messages (handles HDF + .txt fallback automatically)
messages = HdfResultsPlan.get_compute_messages("01")

# Check if plan has results (runtime data exists only for completed plans)
runtime = HdfResultsPlan.get_runtime_data("01")
is_complete = runtime is not None

if is_complete:
    print(f"Plan completed in {runtime['Complete Process (hr)'].values[0]:.2f} hours")
else:
    print("Plan has not been executed or did not complete")

API Reference

HdfResultsPlan.get_compute_messages()

Purpose: Extract raw computation messages from HDF file

Signature:

@staticmethod
@log_call
@standardize_input(file_type='plan_hdf')
def get_compute_messages(hdf_path: Path) -> str

Parameters:

hdf_path: Plan HDF file path OR plan number string (e.g., "01")

Returns: String containing all computation messages, empty string if unavailable

Fallback Behavior:

First attempts: HDF path /Results/Summary/Compute Messages (text)
Fallback: .txt file via RasControl (for pre-6.x HEC-RAS)

Example:

messages = HdfResultsPlan.get_compute_messages("01")
print(len(messages))  # Character count

HdfResultsPlan.get_compute_messages_hdf_only()

Purpose: Extract compute messages WITHOUT RasControl/COM fallback

Use When: Automated workflows where COM locking is problematic

Fallback Order:

HDF /Results/Summary/Compute Messages (text)
{plan_file}.computeMsgs.txt (HEC-RAS 6.x+)
{plan_file}.comp_msgs.txt (HEC-RAS 5.x)

HdfResultsPlan.get_runtime_data()

Purpose: Extract detailed performance metrics for completed plans

Returns: DataFrame with columns:

Plan Name, File Name
Simulation Start Time, Simulation End Time
Simulation Duration (s), Simulation Time (hr)
Completing Geometry (hr), Preprocessing Geometry (hr)
Completing Event Conditions (hr), Unsteady Flow Computations (hr)
Complete Process (hr)
Unsteady Flow Speed (hr/hr), Complete Process Speed (hr/hr)

Returns None if: Plan not executed or did not complete

Common Error Patterns

Critical Errors (Plan Failed)

| Pattern | Meaning | Likely Cause | |---------|---------|--------------| | Unable to open geometry | Missing/corrupt geometry file | File path error, file locked | | Boundary condition not found | DSS path invalid | Wrong DSS pathname, missing file | | ERROR: HDF file cannot be opened | Output file issue | Permissions, disk full | | Unrecoverable error | Fatal execution error | Model configuration issue |

Stability Warnings (Plan May Succeed)

| Pattern | Meaning | Action | |---------|---------|--------| | Unsteady flow time step reduction | Stability issues | May need smaller time step | | Exceeded maximum iterations | Convergence problem | Check Manning's n, geometry | | Time step reduced below minimum | Critical instability | Review problem areas | | Solution did not converge | Numerical issues | Check boundary conditions |

Informational Messages

| Pattern | Meaning | |---------|---------| | Complete Process | Plan finished successfully | | Writing Results | Output phase started | | Completing Geometry | Preprocessing successful | | Completing Event Conditions | Boundary setup successful |

Message Parsing Pattern

Basic Severity Classification

def classify_message_severity(message_line: str) -> str:
    """Classify a compute message line by severity."""
    line_upper = message_line.upper()

    # CRITICAL - plan likely failed
    if any(x in line_upper for x in [
        'UNRECOVERABLE', 'FATAL', 'UNABLE TO OPEN',
        'CANNOT OPEN', 'ERROR:', 'FAILED'
    ]):
        return 'CRITICAL'

    # ERROR - significant issue
    if any(x in line_upper for x in [
        'ERROR', 'NOT FOUND', 'EXCEEDED MAXIMUM'
    ]):
        return 'ERROR'

    # WARNING - potential issue
    if any(x in line_upper for x in [
        'WARNING', 'TIME STEP REDUCTION', 'DID NOT CONVERGE',
        'INSTABILITY', 'REDUCED'
    ]):
        return 'WARNING'

    # INFO - normal operation
    return 'INFO'

Extract Structured Diagnostics

def parse_compute_messages(raw_messages: str) -> dict:
    """Parse raw compute messages into structured format."""
    lines = raw_messages.strip().split('\n')

    result = {
        'critical': [],
        'errors': [],
        'warnings': [],
        'info': [],
        'is_complete': False,
        'total_lines': len(lines)
    }

    for line in lines:
        line = line.strip()
        if not line:
            continue

        severity = classify_message_severity(line)

        if severity == 'CRITICAL':
            result['critical'].append(line)
        elif severity == 'ERROR':
            result['errors'].append(line)
        elif severity == 'WARNING':
            result['warnings'].append(line)
        else:
            result['info'].append(line)

        # Check for completion marker
        if 'COMPLETE PROCESS' in line.upper():
            result['is_complete'] = True

    return result

Output Schema for Orchestrators

When reporting compute message analysis, use this structured format:

## Compute Messages Analysis

### Execution Status
- **Plan**: {plan_number}
- **HDF File**: {hdf_filename}
- **Completed**: Yes/No
- **Duration**: X.XX hours (if completed)

### Messages by Severity

**CRITICAL ({count})**:
- {critical message 1}
- {critical message 2}

**ERRORS ({count})**:
- {error message 1}

**WARNINGS ({count})**:
- {warning message 1}

**INFO ({count})**: {count} informational messages (omitted for brevity)

### Diagnostics
- {Actionable interpretation}
- {Recommended next steps}

### Performance (if completed)
- Simulation Time: X.X hours
- Compute Time: X.X hours
- Speed Ratio: X.X hr/hr

Complete Workflow Example

from ras_commander import init_ras_project, HdfResultsPlan
from pathlib import Path

def analyze_plan_execution(project_path: str, ras_version: str, plan_number: str):
    """Comprehensive compute message analysis for a plan."""

    # Initialize
    init_ras_project(project_path, ras_version)

    # Get compute messages
    messages = HdfResultsPlan.get_compute_messages(plan_number)

    # Get runtime data (None if not complete)
    runtime = HdfResultsPlan.get_runtime_data(plan_number)

    # Parse messages
    parsed = parse_compute_messages(messages)

    # Build report
    report = {
        'plan': plan_number,
        'completed': runtime is not None,
        'critical_count': len(parsed['critical']),
        'error_count': len(parsed['errors']),
        'warning_count': len(parsed['warnings']),
        'info_count': len(parsed['info']),
        'runtime_hours': None,
        'speed_ratio': None
    }

    if runtime is not None:
        report['runtime_hours'] = runtime['Complete Process (hr)'].values[0]
        report['speed_ratio'] = runtime['Complete Process Speed (hr/hr)'].values[0]

    # Print summary
    print(f"Plan {plan_number}: ", end='')
    if report['completed']:
        print(f"COMPLETE in {report['runtime_hours']:.2f}h ({report['speed_ratio']:.1f}x speed)")
    else:
        print("NOT COMPLETE")

    if parsed['critical']:
        print(f"  CRITICAL: {len(parsed['critical'])} issues")
        for msg in parsed['critical'][:3]:  # Show first 3
            print(f"    - {msg[:80]}...")

    if parsed['warnings']:
        print(f"  WARNINGS: {len(parsed['warnings'])} issues")

    return report

# Usage
report = analyze_plan_execution("C:/Projects/Muncie", "6.6", "01")

Integration with Results Analyst Agent

When delegating compute message analysis to the Results Analyst Agent:

Context to Provide:

Plan number and HDF path
Expected completion status
Any known issues or concerns

Expected Output:

Structured diagnostics following output schema
Severity classification of all messages
Actionable recommendations

Example Delegation:

Task(
    subagent_type="results-analyst",
    model="sonnet",
    prompt="""
    Analyze compute messages for plan 01.

    Context files:
    - agent_tasks/.agent/STATE.md

    Task: Extract compute messages from examples/Muncie.p01.hdf,
    classify by severity, and provide diagnostics.

    Write findings to: .claude/outputs/results-analyst/compute-analysis.md
    """
)

Common Issues

Empty Messages

Cause: Plan not executed yet, or HDF missing Results/Summary group

Solution: Check if plan has been executed:

runtime = HdfResultsPlan.get_runtime_data("01")
if runtime is None:
    print("Plan has not been executed - execute with RasCmdr.compute_plan('01')")

COM Locking in Automated Workflows

Cause: get_compute_messages() may invoke RasControl COM fallback

Solution: Use get_compute_messages_hdf_only() for automation:

# Safe for parallel/automated workflows
messages = HdfResultsPlan.get_compute_messages_hdf_only("01")

Partial Results

Cause: Plan crashed mid-execution

Symptoms:

get_runtime_data() returns None
get_compute_messages() shows partial output
HDF file exists but is incomplete

Diagnosis: Check for error patterns at end of messages

Primary Sources

For complete details, navigate to:

ras_commander/hdf/HdfResultsPlan.py (lines 717-914)
- get_compute_messages() implementation
- get_compute_messages_hdf_only() implementation
- HDF path /Results/Summary/Compute Messages (text)
ras_commander/hdf/HdfResultsPlan.py (lines 200-305)
- get_runtime_data() implementation
- Process time extraction
- Speed calculations
examples/400_1d_hdf_data_extraction.ipynb
- Working compute message extraction example
- Output formatting patterns
ras_commander/hdf/AGENTS.md
- HDF class organization
- Decorator patterns
- File type expectations

parsing-compute-messages