scientific-computing

Original：🇺🇸 English

Translated

Use when "scientific computing", "astronomy", "astropy", "bioinformatics", "biopython", "symbolic math", "sympy", "statistics", "statsmodels", "scientific Python"

2installs

Sourceeyadsibai/ltk

Added on2026-02-14

NPX Install

npx skill4agent add eyadsibai/ltk scientific-computing

SKILL.md Content

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Scientific Computing

Domain-specific Python libraries for scientific applications.

Libraries

Library	Domain	Purpose
AstroPy	Astronomy	Coordinates, units, FITS files
BioPython	Bioinformatics	Sequences, BLAST, PDB
SymPy	Mathematics	Symbolic computation
Statsmodels	Statistics	Statistical modeling, tests

AstroPy

Astronomy and astrophysics computations.

Key capabilities:

Units: Physical unit handling with automatic conversion
Coordinates: Celestial coordinate systems (ICRS, galactic, etc.)
Time: Astronomical time scales (UTC, TAI, Julian dates)
FITS: Read/write FITS astronomical data format

Key concept: Unit-aware calculations prevent errors from unit mismatches.

BioPython

Bioinformatics - sequences, structures, databases.

Key capabilities:

Sequences: DNA/RNA/protein manipulation, translation, complement
File parsing: FASTA, GenBank, PDB formats
BLAST: Local and remote sequence alignment
NCBI Entrez: Database access (nucleotide, protein, taxonomy)

Key concept:

SeqIO

for reading any sequence format,

Seq

for sequence operations.

SymPy

Symbolic mathematics - algebra, calculus, equation solving.

Key capabilities:

Algebra: Solve equations, simplify, expand, factor
Calculus: Derivatives, integrals, limits, series
Linear algebra: Matrix operations, eigenvalues
Printing: LaTeX output for documentation

Key concept: Work with symbols, not numbers. Get exact answers, not approximations.

Statsmodels

Statistical modeling with R-like formula interface.

Key capabilities:

Regression: OLS, logistic, generalized linear models
Time series: ARIMA, VAR, state space models
Statistical tests: t-tests, ANOVA, diagnostics
Formula API: R-style formulas (
```
y ~ x1 + x2
```
)

Key concept:

model.summary()

gives comprehensive statistical output like R.

Decision Guide

Domain	Library
Astronomy/astrophysics	AstroPy
Biology/genetics	BioPython
Symbolic math	SymPy
Statistical analysis	Statsmodels
Numerical computing	NumPy, SciPy
Data manipulation	Pandas

Resources

AstroPy: https://docs.astropy.org
BioPython: https://biopython.org/docs/
SymPy: https://docs.sympy.org
Statsmodels: https://www.statsmodels.org

Scientific Computing

Domain-specific Python libraries for scientific applications.

Libraries

Library	Domain	Purpose
AstroPy	Astronomy	Coordinates, units, FITS files
BioPython	Bioinformatics	Sequences, BLAST, PDB
SymPy	Mathematics	Symbolic computation
Statsmodels	Statistics	Statistical modeling, tests

AstroPy

Astronomy and astrophysics computations.

Key capabilities:

Units: Physical unit handling with automatic conversion
Coordinates: Celestial coordinate systems (ICRS, galactic, etc.)
Time: Astronomical time scales (UTC, TAI, Julian dates)
FITS: Read/write FITS astronomical data format

Key concept: Unit-aware calculations prevent errors from unit mismatches.

BioPython

Bioinformatics - sequences, structures, databases.

Key capabilities:

Sequences: DNA/RNA/protein manipulation, translation, complement
File parsing: FASTA, GenBank, PDB formats
BLAST: Local and remote sequence alignment
NCBI Entrez: Database access (nucleotide, protein, taxonomy)

Key concept:

SeqIO

for reading any sequence format,

Seq

for sequence operations.

SymPy

Symbolic mathematics - algebra, calculus, equation solving.

Key capabilities:

Algebra: Solve equations, simplify, expand, factor
Calculus: Derivatives, integrals, limits, series
Linear algebra: Matrix operations, eigenvalues
Printing: LaTeX output for documentation

Key concept: Work with symbols, not numbers. Get exact answers, not approximations.

Statsmodels

Statistical modeling with R-like formula interface.

Key capabilities:

Regression: OLS, logistic, generalized linear models
Time series: ARIMA, VAR, state space models
Statistical tests: t-tests, ANOVA, diagnostics
Formula API: R-style formulas (
```
y ~ x1 + x2
```
)

Key concept:

model.summary()

gives comprehensive statistical output like R.

Decision Guide

Domain	Library
Astronomy/astrophysics	AstroPy
Biology/genetics	BioPython
Symbolic math	SymPy
Statistical analysis	Statsmodels
Numerical computing	NumPy, SciPy
Data manipulation	Pandas

Resources

AstroPy: https://docs.astropy.org
BioPython: https://biopython.org/docs/
SymPy: https://docs.sympy.org
Statsmodels: https://www.statsmodels.org

scientific-computing

NPX Install

Tags

SKILL.md Content

Scientific Computing

Libraries

AstroPy

BioPython

SymPy

Statsmodels

Decision Guide

Resources

scientific-computing

NPX Install

Tags

SKILL.md Content

Scientific Computing

Libraries

AstroPy

BioPython

SymPy

Statsmodels

Decision Guide

Resources