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README.md

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@@ -150,20 +150,21 @@ with my_pitz.fv_schemes as f:
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f["snGradSchemes"]["default"] = "uncorrected"
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```
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### ⏳ Run multiple cases in parallel
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Outside an [asyncio](https://docs.python.org/3/library/asyncio.html) context:
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### 🔢 Direct field file access without `FoamCase`
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```python
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from foamlib import AsyncFoamCase
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case1 = AsyncFoamCase("path/to/case1")
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case2 = AsyncFoamCase("path/to/case2")
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import numpy as np
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from foamlib import FoamFieldFile
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AsyncFoamCase.run_all_wait([case1, case2])
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# Read field data directly
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U = FoamFieldFile("0/U")
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print(f"Velocity field shape: {np.shape(U.internal_field)}")
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print(f"Boundaries: {list(U.boundary_field)}")
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```
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Within an asyncio context (e.g. in a [Jupyter](https://jupyter.org/) notebook):
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### ⏳ Run multiple cases in parallel
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In an `asyncio` context (e.g. [`asyncio`](https://docs.python.org/3/library/asyncio.html) REPL or [Jupyter](https://jupyter.org/) notebook):
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```python
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from foamlib import AsyncFoamCase
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await AsyncFoamCase.run_all([case1, case2])
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```
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### 🔢 Direct field file access
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```python
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import numpy as np
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from foamlib import FoamFieldFile
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# Read field data directly
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U = FoamFieldFile("0/U")
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print(f"Velocity field shape: {np.shape(U.internal_field)}")
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print(f"Boundaries: {list(U.boundary_field)}")
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```
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Note: outside of an `asyncio` context, you can use [`asyncio.run()`](https://docs.python.org/3/library/asyncio-runner.html#asyncio.run).
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### 🎯 Optimization with HPC clusters
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### 🎯 Full optimization run on a Slurm-based HPC cluster
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```python
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import os

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