metrics.py File Reference

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Namespaces
namespace	evaluator
namespace	evaluator.metrics

Functions
float	evaluator.metrics.get_average_difference (np.array output, np.array expected)
	Computes the average difference between an output output and the expected values.
int	evaluator.metrics.get_false_positives (np.ndarray output, np.ndarray expected, float threshold)
	Computes the number of false positives in the output compared to the expected values.
float	evaluator.metrics.get_mean_squared_difference (np.ndarray output, np.ndarray expected)
	Computes the mean squared difference between an output output and the expected values.
float	evaluator.metrics.compute_distance (np.array cone1, np.array cone2)
	Compute the Euclidean distance between two cones.
np.array	evaluator.metrics.build_adjacency_matrix (np.array cones)
int	evaluator.metrics.get_duplicates (np.array output, float threshold)
float	evaluator.metrics.get_inter_cones_distance (np.array perception_output)
	Computes the average distance between pairs of perceived cones using Minimum Spanning Tree Prim's algorithm.
np.ndarray	evaluator.metrics.compute_closest_distances (np.ndarray arr1, np.ndarray arr2)
	Computes the distance between each element in arr2 and the closest element in arr1.
float	evaluator.metrics.get_average_error (np.array values)
	Computes the average of a list of values.
float	evaluator.metrics.get_mean_squared_error (np.array values)
	Computes the mean squared value of a list of values.
float	evaluator.metrics.get_root_mean_squared_error (np.array values)
	Computes the root mean squared error of a list of values.