aim2dat.fct.function_comparison¶

Module to analyze spectra.

Module Contents¶

Classes¶

class aim2dat.fct.function_comparison.FunctionAnalysis(**kwargs)[source]¶

Class to analyze and compare functions.

Overview

Properties¶

allowed_distance_methods

Return allowed distance methods.

Methods¶

calculate_correlation(label1, label2)	Calculate the pearson-correlation between the values of two functions.
calculate_discrete_fingerprint(label, grid)	Calculate a discretized fingerprint of a function (doi:10.1038/s41597-022-01754-z).
calculate_distance(label1, label2, method)	Calculate the distance between the values of two functions.
compare_areas(label1, label2)	Compare the enclosed areas of two functions.
compare_functions_by_discrete_fingerprint(label1, label2, grid)	Compare two functions based on a discretized fingerprint
import_data(data_label, x_values, y_values)	Import data into the internal memory.

property allowed_distance_methods : list¶

Return allowed distance methods.

calculate_correlation(label1: str, label2: str) → float[source]¶

Calculate the pearson-correlation between the values of two functions.

Parameters:¶

• label_1 (str) – Label of the first dataset.

• label_2 (str) – Label of the second dataset.

Returns:¶

float – The correlation.

calculate_discrete_fingerprint(label: str, grid: aim2dat.fct.discretization.DiscretizedGrid) → numpy.array[source]¶

Calculate a discretized fingerprint of a function (doi:10.1038/s41597-022-01754-z).

Parameters:¶

• label (str) – Label of the dataset.

• grid (DiscretizedGrid) – The grid to discretize the function.

Returns:¶

np.array – Discretized fingerprint.

calculate_distance(label1: str, label2: str, method: str = 'euclidian') → float[source]¶

Calculate the distance between the values of two functions.

Parameters:¶

• label1 (str) – Label of the first dataset.

• label2 (str) – Label of the second dataset.

• method (str) – The metric to calculate the distance. Defaults to “euclidian”.

Returns:¶

float – Abs. error

compare_areas(label1: str, label2: str) → float[source]¶

Compare the enclosed areas of two functions.

Parameters:¶

• label1 (str) – Label of the first dataset.

• label2 (str) – Label of the second dataset.

Returns:¶

float – The ratio of the areas. (A1 / A2)

compare_functions_by_discrete_fingerprint(label1: str, label2: str, grid: aim2dat.fct.discretization.DiscretizedGrid) → float[source]¶

Compare two functions based on a discretized fingerprint (doi:10.1038/s41597-022-01754-z).

Parameters:¶

• label1 (str) – Label of the first dataset.

• label2 (str) – Label of the second dataset.

• grid (DiscretizedGrid) – The grid to discretize the function.

Returns:¶

float – Similarity.

import_data(data_label: str, x_values: numpy.array, y_values: numpy.array)[source]¶

Import data into the internal memory.

Parameters:¶

• data_label (str) – Label for the internal memory.

• x_values (np.array) – x-values of the function.

• y_values (np.array) – y-values of the function.