autoemxsp.runners.analyze_sample module

Single-sample clustering and analysis of X-ray spectra.

This module loads configurations and acquired X-ray spectra for a single sample, performs clustering/statistical analysis, and prints results. It is suitable for both interactive use and integration into larger workflows.

Import this module in your own code and call the analyze_sample() function, passing the sample ID (and optional arguments) to perform analysis programmatically.

Workflow:

  • Loads sample configuration from Spectra_collection_info.json

  • Loads acquired spectral data from Data.csv

  • Performs clustering/statistical analysis

  • Prints summary results

Notes

  • Requires sample_ID (and optionally results_path if not using the default directory).

  • Designed to be robust and flexible for both batch and single-sample workflows.

Typical usage:

  • Edit the sample_ID and options in the script, or

  • Import and call analyze_sample() with your own arguments.

param sample_ID:

Sample identifier.

type sample_ID:

str

param results_path:

Directory where results are stored. If None, sets to default autoemxsp/Results

type results_path:

str, optional

param output_filename_suffix:

Suffix for output files.

type output_filename_suffix:

str, optional

param ref_formulae:

Reference formulae for clustering. If the first entry is “” or None, the rest are appended to the list loaded from Comp_analysis_configs.json; otherwise, the provided list replaces it.

type ref_formulae:

list of str, optional

param els_excluded_clust_plot:

Elements to exclude from cluster plot.

type els_excluded_clust_plot:

list of str, optional

param clustering_features:

Features to use for clustering.

type clustering_features:

list of str, optional

param k_finding_method:
Method for determining optimal number of clusters. Set to “forced” if a value of ‘k’ is specified manually.

Allowed methods are “silhouette”, “calinski_harabasz”, “elbow”.

type k_finding_method:

str, optional

param k_forced:

Forced number of clusters.

type k_forced:

int, optional

param max_analytical_error_percent:

Maximum analytical error allowed for clustering.

type max_analytical_error_percent:

float, optional

param quant_flags_accepted:

Accepted quantification flags.

type quant_flags_accepted:

list of int, optional

param plot_custom_plots:

Whether to use custom plots.

type plot_custom_plots:

bool, optional

param show_unused_compositions_cluster_plot:

Whether to show unused compositions in cluster plot.

type show_unused_compositions_cluster_plot:

bool, optional

param Created on Tue Jul 29 13:

type Created on Tue Jul 29 13:

18:16 2025

param @author:

type @author:

Andrea

autoemxsp.runners.analyze_sample.analyze_sample(sample_ID: str, results_path: str = None, output_filename_suffix: str = '', ref_formulae: List[str] | None = None, els_excluded_clust_plot: List[str] | None = None, clustering_features: List[str] | None = None, k_finding_method: str | None = None, k_forced: int | None = None, max_analytical_error_percent: float = 5, quant_flags_accepted: List[int] | None = None, plot_custom_plots: bool = False, show_unused_compositions_cluster_plot: bool = True) → None[source]

Run clustering and analysis for a single sample.

Parameters:

  • sample_ID (str) – Sample identifier.

  • results_path (str, optional) – Directory where results are loaded and stored. If None, defaults to autoemxsp/Results

  • output_filename_suffix (str, optional) – Suffix for output files.

  • ref_formulae (list of str, optional) – Reference formulae for clustering. If the first entry is “” or None, the rest are appended to the list loaded from Comp_analysis_configs.json; otherwise, the provided list replaces it.

  • els_excluded_clust_plot (list of str, optional) – Elements to exclude from cluster plot.

  • clustering_features (list of str, optional) – Features to use for clustering.

  • k_finding_method (str, optional) –

    Method for determining optimal number of clusters. Set to “forced” if a value of ‘k’ is specified manually.

    Allowed methods are “silhouette”, “calinski_harabasz”, “elbow”.

  • k_forced (int, optional) – Forced number of clusters.

  • max_analytical_error_percent (float, optional) – Maximum analytical error allowed for clustering.

  • quant_flags_accepted (list of int, optional) – Accepted quantification flags.

  • plot_custom_plots (bool, optional) – Whether to use custom plots.

  • show_unused_compositions_cluster_plot (bool, optional) – Whether to show unused compositions in cluster plot.

Returns:

comp_analyzer – The composition analysis object containing the results and methods for further analysis.

Return type:

EMXSp_Composition_Analyzer