Skip to content

results_cluster.py

Constants

Name Value
ALGORITHMS ['K-Means', 'Hierarchical', 'DBSCAN', 'Spectral...
METRICS ['Silhouette', 'Calinski-Harabasz', 'Davies-Bou...
METRIC_KEYS {'Silhouette': ('Silhouette Score', 'silhouette...
SCALING_OPTIONS ['StandardScaler', 'MinMaxScaler', 'None']
DIM_REDUCTION_OPTIONS ['None', 'PCA', 't-SNE']
DATA_TYPE_OPTIONS ['Counts', 'Element Mass (fg)', 'Particle Mass ...
DATA_KEY_MAP {'Counts': 'elements', 'Element Mass (fg)': 'el...
CLUSTER_COLORS ['#2563EB', '#DC2626', '#16A34A', '#D97706', '#...
ALGO_LINE_STYLES {'K-Means': dict(color='#2563EB', ls='-', marke...

Classes

ClusteringSettingsDialog (extends QDialog)

Full settings dialog opened from right-click → Configure.

Method Signature Description
__init__ (self, config, parent = None) Args:
_build_ui (self)
collect (self) → dict Returns:

ClusteringDisplayDialog (extends QDialog)

Main clustering dialog with toolbar, tabs, and right-click menus.

Method Signature Description
__init__ (self, node, parent_window = None) Args:
_is_multi (self) Returns:
_build_ui (self)
_make_btn (self, text, color, slot) Args:
_build_eval_tab (self)
_build_cluster_tab (self)
_build_char_tab (self)
_ctx_menu (self, pos, tab) Args:
_make_popout_btn (self, slot) Args:
_pop_out_figure (self, tab: str) Redraw the requested figure into a standalone resizable window.
_edit_figure (self, tab: str) Open a lightweight per-figure settings dialog.
_redraw_figure (self, tab: str) Args:
_cl_drag_press (self, event) Args:
_cl_drag_motion (self, event) Args:
_cl_drag_release (self, _event) Args:
_set (self, key, value) Args:
_build_overview_tab (self)
_build_dendrogram_tab (self)
_build_3d_tab (self)
_set_3d_view (self, elev, azim) Snap all 3D axes to a preset view angle.
_draw_3d (self)
_draw_3d_into (self, target_fig) Args:
_draw_dendrogram (self)
_draw_dendrogram_into (self, target_fig) Args:
_draw_overview (self) Heatmap (elements × clusters) + cluster size bar chart.
_draw_overview_into (self, target_fig) Draw the overview content into an arbitrary Figure (used for pop-out).
_on_eval_pick (self, event) Click a point on an evaluation curve to set K directly.
_on_cluster_hover (self, event) Show a floating tooltip with element values when hovering scatter points.
_draw_radar (self, algo) Spider/radar chart: detection frequency per element per cluster.
_open_settings (self)
_on_node_changed (self)
_get_elements (self) Returns:
_prepare_data (self, elements) Prepare data matrix — identical logic to original.
_run_algo (self, name, k, data) Args:
_run_evaluation (self)
_determine_optimal_k (self) Robust optimal-K selection via per-metric voting:
_elbow_k (k_vals: list, scores: list) → int Kneedle algorithm: find the K at the elbow of a monotone curve.
_update_optimal_label (self)
_refresh_eval_plot (self)
_run_clustering (self)
_characterise (self, elements, data) Generate cluster characterisation with real element-% composition labels.
_populate_char_combos (self, elements) Args:
_refresh_char (self)
_export_results (self)

ClusteringPlotNode (extends QObject)

Clustering analysis node with matplotlib figures.

Method Signature Description
__init__ (self, parent_window = None) Args:
set_position (self, pos) Args:
configure (self, parent_window) Args:
process_data (self, input_data) Args:

Functions

_style_ax

def _style_ax(ax, cfg, xlabel = '', ylabel = '', title = '')

Apply consistent styling to a matplotlib axes.

Args:

  • ax (Any): The ax.
  • cfg (Any): The cfg.
  • xlabel (Any): The xlabel.
  • ylabel (Any): The ylabel.
  • title (Any): Window or dialog title.

_draw_evaluation

def _draw_evaluation(fig, eval_results, cfg, optimal_k = None, view_algo = 'All Algorithms')

Draw evaluation metric curves on a matplotlib Figure.

Args:

  • fig (Any): The fig.
  • eval_results (Any): The eval results.
  • cfg (Any): The cfg.
  • optimal_k (Any): The optimal k.
  • view_algo (Any): The view algo.

_draw_clustering

def _draw_clustering(fig, clustering_results, data_matrix, characterisation, cfg)

Draw cluster scatter plots on a matplotlib Figure.

Args:

  • fig (Any): The fig.
  • clustering_results (Any): The clustering results.
  • data_matrix (Any): The data matrix.
  • characterisation (Any): The characterisation.
  • cfg (Any): The cfg.

_draw_characterisation

def _draw_characterisation(fig, algo_name, element, characterisation, cfg)

Draw cluster characterisation bar chart on a matplotlib Figure.

Args:

  • fig (Any): The fig.
  • algo_name (Any): The algo name.
  • element (Any): The element.
  • characterisation (Any): The characterisation.
  • cfg (Any): The cfg.