kbomodels 2024.1.0

A Python package for Kabirian-based optinalysis (KBO) and other advanced estimations

Kabirian-Based Optinalysis Modesls

Kabirian-based optinalysis models (kbomodels) consist of a collection of mathematical and statistical techniques designed for analyzing datasets within the Kabirian-based optinalysis framework, along with other advanced methodologies. The estimation modules integrated within kbomodels include:

1a) kc_isoptinalysis : Performs Kabirian-based isomorphic optinalysis to calculate the Kabirian coefficient.

1b) doc_kc_isoptinalysis : Prints the documentation of the kc_isoptinalysis module.

2a) kc_autoptinalysis : Performs Kabirian-based automorphic optinalysis to calculate the Kabirian coefficient.

2b) doc_kc_autoptinalysis : Prints the documentation of the kc_autoptinalysis.

3a) pSimSymId : Translates the Kabirian coefficient of similarity, symmetry, or identity (kc) to probability of similarity, symmetry, or Sidentity (SimSymId).

3b) doc_pSimSymId : Prints the documentation of the pSimSymId.

4a) pDsimAsymUid : Translates probability of similarity, symmetry, or identity (pSimSymId) to probability of dissimilarity, asymmetry, or unidentity (pDsimAsymUid).

4b) doc_pDsimAsymUid : Prints the documentation of the pDsimAsymUid.

5a) kc_alt1 : Translates probability of similarity, symmetry, or identity (pSimSymId) to an ascending-alternative (A-alternative) Kabirian coefficient of similarity, symmetry, or identity (kc_alt1).

5b) doc_kc_alt1 : Prints the documentation of the kc_alt1.

6a) kc_alt2 : Translates probability of similarity, symmetry, or identity (pSimSymId) to a descending-alternative (D-alternative) Kabirian coefficient of similarity, symmetry, or identity (kc_alt2).

6b) doc_kc_alt2 : Prints the documentation of the kc_alt2.

7a) kc_alt : Translates Kabirian coefficient of similarity, symmetry, or identity (kc) to its inverse alternative Kabirian coefficient of similarity, symmetry, or identity (kc_alt).

7b) doc_kc_alt : Prints the documentation of the kc_alt.

8a) isomorphic_optinalysis : Performs Kabirian-based isomorphic optinalysis.

8b) doc_isomorphic_optinalysis : Prints the documentation of the isomorphic_optinalysis.

9a) automorphic_optinalysis : Performs Kabirian-based automorphic optinalysis.

9b) doc_automorphic_optinalysis : Prints the documentation of the automorphic_optinalysis.

10a) stat_SymAsymmetry : Estimates the statistical symmetry and asymmetry of a dataset using a customized, and optimized Kabirian-based automorphic optinalysis.

10b) doc_stat_SymAsymmetry : Prints the documentation of the stat_SymAsymmetry.

11a) bioseq_gpa : Perform pairwise sequence analysis of aligned biological sequences using a customized, and optimized Kabirian-based isomorphic optinalysis.

11b) doc_bioseq_gpa : Prints the documentation of the bioseq_gpa.

12a) stat_mirroring : Performs statistical dispersion estimations on a dataset using a parameterized, customized, and optimized Kabirian-based isomorphic optinalysis.

12b) doc_stat_mirroring : Prints the documentation of the stat_mirroring.

13a) famispacing : Estimates family spacing conformity and disconformity using a customized, and optimized Kabirian-based isomorphic optinalysis.

13b) doc_famispacing : Prints the documentation of the famispacing.

14a) smb_ordinalysis : Perform statistical mirroring-based ordinalysis (SM-based Ordinalysis), a methodology for assessing an individual's level of assessments on a defined ordinal scale by applying a customized and optimized statistical mirroring techniques.

14b) doc_smb_ordinalysis : Prints the documentation of the smb_ordinalysis.

Installation and Documentation

## Installation

# You can install this package via pip:

pip install kbomodels

## Print the documentation

# You can print the documentation for each module in the package by using the following command.

import kbomodels as kbo
# Examples:
kbo.doc_kc_autoptinalysis(),
kbo.doc_kc_isoptinalysis(), 
kbo.doc_bioseq_gpa(), 
kbo.doc_stat_mirroring(), 
kbo.doc_famispacing(), 
kbo.doc_smb_ordinalysis(), 
kbo.modules_list(), e.t.c.

# Note: The documentation includes the function definitions, input parameters, usage examples, and other relevant details for each module.