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