Add documentation for types: scalars, lists, and NumPy arrays

[PiotrPich2024]

Added documentation about passed types and how they are converted into C variables.
Added warning inside documentation about passing wrong precision floating-point types numbers.

This pull request introduces documentation improvements and dependency updates to the project. The main focus is on enhancing the Python API documentation for data types and clarifying input/output handling, as well as updating project dependencies.

Documentation improvements:

• Added a comprehensive new document (docs/python/types.md) detailing the accepted Python/NumPy data types for pyamtrack functions, including scalar and array-like inputs, broadcasting, output types, error handling, and practical recommendations. This will help users understand how to interact with the Python API and avoid common pitfalls.
• Updated the README.md to fix the link to the documentation site, ensuring it uses the correct URL format.
• Added a clarifying note in the README.md about the local server and file watching when running the documentation site.

Dependency updates:

• Added the baseline-browser-mapping package to package.json dependencies, which may be required for improved browser compatibility or build tooling.

[grzanka]

see comments

[grzanka]

see comments

[Copilot]

Pull request overview

This PR updates the libamtrack documentation site to better describe Python↔C type conversions for the pyamtrack wrapper, and fixes the top-level README link to the hosted docs site.

Changes:

• Fix README link to use the canonical https://libamtrack.github.io URL.
• Add a new docs/python/types.md page documenting Python input/output conversions (scalars, lists, NumPy arrays) for fully ported functions.

Reviewed changes

Copilot reviewed 2 out of 2 changed files in this pull request and generated 6 comments.

File	Description
README.md	Fixes documentation site link to include the https:// scheme.
docs/python/types.md	Adds a type conversion reference page for key pyamtrack functions/modules.

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[Copilot]

Pull request overview

Copilot reviewed 2 out of 2 changed files in this pull request and generated 7 comments.

[Copilot]

Pull request overview

Copilot reviewed 2 out of 2 changed files in this pull request and generated 12 comments.

Comments suppressed due to low confidence (4)

docs/python/types.md:29

• Grammar and wording issues in the array-like notes: “tuple and set is” should be plural, the inline “NOT IMPLEMENTED YET” is distracting, and “0-d python lists” isn’t a meaningful concept (lists are 1-D). Consider clarifying this as “empty Python lists” and “0‑D NumPy arrays”.

**Note:** `tuple` and `set` is not treated as array-like and will usually raise a `TypeError`. `NOT IMPLEMENTED YET`

**Note:** `0-d numpy.ndarray` and `0-d python lists` are treated as arrays-like type not scalars

docs/python/types.md:104

• This list example both uses the undocumented E_MeV keyword and claims the output is a numpy.ndarray. Elsewhere in this docs set (e.g. docs/python/API/stopping/electron_range.md and docs/python/API/converters.md) list inputs are documented as returning Python lists. Please align this example with the established API docs to avoid confusing users.

E_MeV = [50.0, 100.0, 150.0]
range_m = pyamtrack.stopping.electron_range(E_MeV = E_MeV)
# E_MeV -> [50.0, 100.0, 150.0] MeV
# range_m -> numpy.ndarray([0.2537, 0.4245, 0.5689])  (shape (3,), dtype float64)
# range_m[i] corresponds to E_MeV[i], same order preserved

docs/python/types.md:207

• This example again uses E_MeV= / material_id= / model_id= and describes a np.ndarray output for a list input. That contradicts the existing API docs in this repo, which document list inputs as returning Python lists (e.g. docs/python/API/stopping/electron_range.md, docs/python/API/converters.md). Please align the example and expected return type with the established documentation.

E_MeV = [50.0, 100.0]
range_m = pyamtrack.stopping.electron_range(E_MeV = E_MeV, material_id = 1, model_id = 7)
# material_id=1 and model_id=7 stay scalar -> broadcast to match E_MeV's length
# range_m -> np.ndarray([0.2537, 0.4245])  (shape=(2,), dtype=float64)

**docs/python/types.md:232**
* After switching the example to list inputs, the return type in this comment should be a Python list (as documented elsewhere in this repo for list inputs), not `np.ndarray`.

range_m -> np.ndarray([0.2537, 0.4245, 0.5689])

</details>

[grzanka]

@copilot resolve the merge conflicts in this pull request

[Copilot]

@copilot resolve the merge conflicts in this pull request

Resolved the merge conflicts in ec5ddc2. The only conflict was in yarn.lock — resolved by taking the newer package versions from main (which contained the security dependency bumps for brace-expansion, follow-redirects, etc.).