Diffusion

[edeno]

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[Copilot]

Pull Request Overview

This pull request refactors environment attribute names and method calls for improved consistency and clarity while adding a new helper function to calculate the random walk movement variance. Key changes include switching from fit_place_grid to fit, updating attribute names from distance_between_nodes_/track_graphDD to distance_between_bins/track_graph_nd_, and renaming DataFrame columns and parameters for clarity.

Reviewed Changes

Copilot reviewed 4 out of 4 changed files in this pull request and generated 1 comment.

File	Description
src/non_local_detector/models/base.py	Updated method call from fit_place_grid to fit to align with refactored API
src/non_local_detector/continuous_state_transitions.py	Replaced attribute names (distance_between_nodes_ to distance_between_bins and track_graphDD to track_graph_nd_) for consistency
src/non_local_detector/analysis/distance1D.py	Updated DataFrame column names and parameter renaming to reflect the new API

Comments suppressed due to low confidence (4)

src/non_local_detector/continuous_state_transitions.py:201

• Ensure the new attribute name 'track_graph_nd_' is used consistently and update any associated documentation or comments to avoid confusion with the old name.

self.environment.track_graph_nd_, distance="distance"

src/non_local_detector/analysis/distance1D.py:425

• [nitpick] The parameter renaming to 'track_graph_bin_centers_edges' improves clarity; ensure this naming is uniformly applied across all function definitions and calls.

track_graph_bin_centers_edges: nx.Graph,

src/non_local_detector/continuous_state_transitions.py:190

• Verify that 'distance_between_bins' is consistently used across the project as it replaces the previous 'distance_between_nodes_' property.

.pdf(self.environment.distance_between_bins.flat)

src/non_local_detector/analysis/distance1D.py:88

• Confirm that the new column names 'pos_x' and 'pos_y' are correct and consistently used in the codebase and documentation.

env.get_bin_center_dataframe().loc[:, ["pos_x", "pos_y"]].to_numpy()

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