import os
from pathlib import Path
from foamlib import FoamCase

# Clone and run a case
my_case = FoamCase(Path(os.environ["FOAM_TUTORIALS"]) / "incompressible/simpleFoam/pitzDaily").clone("myCase")
my_case.run()

# Access results
latest_time = my_case[-1]
pressure = latest_time["p"].internal_field
velocity = latest_time["U"].internal_field

print(f"Max pressure: {max(pressure)}")
print(f"Velocity at first cell: {velocity[0]}")

# Clean up
my_case.clean()

import os
from pathlib import Path
from foamlib import FoamCase

pitz_tutorial = FoamCase(Path(os.environ["FOAM_TUTORIALS"]) / "incompressible/simpleFoam/pitzDaily")
my_pitz = pitz_tutorial.clone("myPitz")

# Run the simulation
my_pitz.run()

# Access the latest time step
latest_time = my_pitz[-1]
p = latest_time["p"]
U = latest_time["U"]

print(f"Pressure field: {p.internal_field}")
print(f"Velocity field: {U.internal_field}")

# Clean the case
my_pitz.clean()

# Modify control settings
my_pitz.control_dict["writeInterval"] = 10
my_pitz.control_dict["endTime"] = 2000

# Make multiple file changes efficiently
with my_pitz.fv_schemes as f:
    f["gradSchemes"]["default"] = f["divSchemes"]["default"]
    f["snGradSchemes"]["default"] = "uncorrected"

import numpy as np
from foamlib import FoamFieldFile

# Read field data directly
U = FoamFieldFile("0/U")
print(f"Velocity field shape: {np.shape(U.internal_field)}")
print(f"Boundaries: {list(U.boundary_field)}")

from foamlib import AsyncFoamCase

case1 = AsyncFoamCase("path/to/case1")
case2 = AsyncFoamCase("path/to/case2")

await AsyncFoamCase.run_all([case1, case2])

import os
from pathlib import Path
from foamlib import AsyncSlurmFoamCase
from scipy.optimize import differential_evolution

# Set up base case for optimization
base = AsyncSlurmFoamCase(Path(os.environ["FOAM_TUTORIALS"]) / "incompressible/simpleFoam/pitzDaily")

async def objective_function(x):
    """Objective function for optimization."""
    async with base.clone() as case:
        # Set inlet velocity based on optimization parameters
        case[0]["U"].boundary_field["inlet"].value = [x[0], 0, 0]
        
        # Run with fallback to local execution if Slurm unavailable
        await case.run(fallback=True)
        
        # Return objective (minimize velocity magnitude at outlet)
        return abs(case[-1]["U"].internal_field[0][0])

# Run optimization with parallel jobs
result = differential_evolution(
    objective_function, 
    bounds=[(-1, 1)], 
    workers=AsyncSlurmFoamCase.map,  # Enables concurrent evaluations
    polish=False
)
print(f"Optimal inlet velocity: {result.x[0]}")

#!/usr/bin/env python3
"""Run the OpenFOAM case in this directory."""

from pathlib import Path
from foamlib import FoamCase

# Initialize case from this directory
case = FoamCase(Path(__file__).parent)

# Adjust simulation parameters
case.control_dict["endTime"] = 1000
case.control_dict["writeInterval"] = 100

# Run the simulation
print("Starting OpenFOAM simulation...")
case.run()
print("Simulation completed successfully!")