added_resample_mesh

[kzqureshi]

PR Type

Enhancement

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Description

• Added a new resample method to the Mesh class.

• Enables resampling of mesh with specified number of cells.

• Includes detailed documentation and examples for usage.

• Ensures boundaries remain unchanged during resampling.

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Changes walkthrough 📝

	Relevant files
Enhancement	mesh.py Add `resample` method to `Mesh` class                                        discretisedfield/mesh.py Introduced a new resample method to the Mesh class. Added detailed docstring with parameters, return type, and examples. Implemented functionality to adjust the number of cells while keeping boundaries fixed. Ensured compatibility with existing mesh attributes like region and bc. +63/-0

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[github-actions]

PR Reviewer Guide 🔍

Here are some key observations to aid the review process:

⏱️ Estimated effort to review: 2 🔵🔵⚪⚪⚪

🧪 No relevant tests

🔒 No security concerns identified

⚡ Recommended focus areas for review Possible Issue The resample method does not handle cases where the input n array has a different length than mesh.region.ndim. This could lead to unexpected behavior or errors. """ n = np.array(n, dtype=int) new_n = self.n.copy() for i in range(len(n)): new_n[i] = n[i] return self.__class__( region=self.region, n=new_n, bc=self.bc, subregions=self.subregions, ) Missing Validation The resample method does not validate whether the new n values are positive integers, which could result in invalid mesh configurations. """ n = np.array(n, dtype=int) new_n = self.n.copy() for i in range(len(n)): new_n[i] = n[i] return self.__class__( region=self.region, n=new_n, bc=self.bc, subregions=self.subregions, )

[github-actions]

PR Code Suggestions ✨

Explore these optional code suggestions:

Category	Suggestion	Score
Possible issue	Add validation to ensure the input array has the correct number of elements Validate that the input n has the correct number of elements matching mesh.region.ndim and raise a descriptive error if it does not, to prevent potential runtime errors. discretisedfield/mesh.py [2168-2171] n = np.array(n, dtype=int) +if len(n) != self.region.ndim: + raise ValueError(f"Input array 'n' must have {self.region.ndim} elements, but got {len(n)}.") new_n = self.n.copy() for i in range(len(n)): new_n[i] = n[i] Suggestion importance[1-10]: 9 Why: This suggestion adds an essential validation step to ensure the input array n matches the expected dimensionality of the mesh, preventing potential runtime errors and improving robustness.	9
	Add a check to ensure all elements of the input array are positive integers Ensure that the input n contains only positive integers to avoid invalid mesh configurations or unexpected behavior. discretisedfield/mesh.py [2168-2171] n = np.array(n, dtype=int) +if np.any(n <= 0): + raise ValueError("All elements of input array 'n' must be positive integers.") new_n = self.n.copy() for i in range(len(n)): new_n[i] = n[i] Suggestion importance[1-10]: 9 Why: This suggestion ensures that the input array n contains only positive integers, which is critical for maintaining valid mesh configurations and avoiding unexpected behavior.	9

[lang-m]

@fangohr @samjrholt, @swapneelap This MR introduces mesh.resample. We don't strictly need it as it is just calling mesh.__init__ with the new n. It might still be nice to have for consistency. What is your opinion?

[lang-m]

Suggested change

	``pmin`` and ``pmax`` stay unchanged. The values of the new cells are taken from
	the nearest old cell, no interpolation is performed.
	``pmin`` and ``pmax`` stay unchanged.

The mesh does not have any values. Therefore this sentence does not apply.

[lang-m]

Suggested change

	n = np.array(n, dtype=int)
	new_n = self.n.copy()
	for i in range(len(n)):
	new_n[i] = n[i]
	return self.__class__(
	region=self.region,
	n=new_n,
	return self.__class__(
	region=self.region,
	n=n,

None of this should be required.