Skip to content
CDS v2
cds2.linalg
Initializing search
Furox-Art/scientific-computing-system-2.0
CDS v2
Furox-Art/scientific-computing-system-2.0
Home
Getting started
Modules overview
Deprecated modules
Supply chain and provenance
npm launcher shim
Examples
Recipes
Research quality
Research quality
Validation & reproducibility
Research-readiness checklist
Reproducible case studies
NumPy/SciPy version-drift example
Benchmark methodology
Industrial computing
Benchmarks
Release process
API Reference
API Reference
cds2.linalg
cds2.linalg
Table of contents
linalg
cds2.stats
cds2.optimize
cds2.guided_fit
cds2.integrate
cds2.interpolate
cds2.signals
cds2.montecarlo
cds2.graph
cds2.ml
cds2.timeseries
cds2.viz
cds2.io
cds2.sparse
cds2.spectral
cds2.modeling
cds2.quantum
cds2.knowledge
cds2.scientific
cds2.hypothesis
cds2.nlp
cds2.infotheory
cds2.chaos
cds2.bayes
cds2.bayesopt
cds2.data_analysis
cds2.pde
cds2.sde
cds2.metaheuristics
cds2.geometry
cds2.rl
cds2.quality
cds2.design
cds2.wavelets
cds2.epidemiology
cds2.image
cds2.genetics
cds2.reliability
cds2.finance
cds2.text
cds2.game_theory
cds2.combinatorial
cds2.spatial
cds2.calculus
cds2.special
cds2.distributions
cds2.cli
Table of contents
linalg
cds2.linalg
Dense linear algebra on NumPy.
Dense linear algebra with typed dataclass results.
Back to top