Algorithms & Physics

Scientific core: clustering, thermochemistry, and spectroscopy.

Clustering & PCA

class ensemble_analyzer._clustering.cluster_config.ClusteringConfig(n_clusters: int | None = None, include_H: bool = True, set_cluster_attribute: bool = True, min_k: int = 2, max_k: int = 30, random_state: int = 42)[source]

Configuration parameters for clustering operations.

include_H: bool = True

max_k: int = 30

min_k: int = 2

n_clusters: int | None = None

random_state: int = 42

set_cluster_attribute: bool = True

class ensemble_analyzer._clustering.cluster_config.PCAResult(scores: numpy.ndarray, clusters: numpy.ndarray, colors: List[str], numbers: List[int], energies: numpy.ndarray, explained_variance: numpy.ndarray, n_clusters: int | None = None, original_features: numpy.ndarray | None = None, components: numpy.ndarray | None = None)[source]

Container for PCA and Clustering analysis results.

clusters: numpy.ndarray

colors: List[str]

components: numpy.ndarray | None = None

energies: numpy.ndarray

explained_variance: numpy.ndarray

n_clusters: int | None = None

numbers: List[int]

original_features: numpy.ndarray | None = None

scores: numpy.ndarray

Thermochemistry (qRRHO)

Spectroscopy & Plotting

class ensemble_analyzer._spectral.graph_default.GraphDefault(graph_type: Literal['IR', 'VCD', 'UV', 'ECD'])[source]

Default spectral parameters (range, shift, FWHM, labels) for each graph type.

graph_type: Literal['IR', 'VCD', 'UV', 'ECD']