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Dedalus solves differential equations using spectral methods. It implements flexible algorithms to solve initial-value, boundary-value, and eigenvalue problems with broad ranges of custom equations and spectral domains. Its primary features include symbolic equation entry, multidimensional parallelization, implicit-explicit timestepping, and flexible analysis with HDF5. The code is written primarily in Python and features an easy-to-use interface. The numerical algorithm produces highly sparse systems for many equations which are efficiently solved using compiled libraries and MPI.
Eigentools is a set of tools for studying linear eigenvalue problems. The underlying eigenproblems are solved using Dedalus (ascl:1603.015), which provides a domain-specific language for partial differential equations. Eigentools extends Dedalus's EigenvalueProblem object and provides automatic rejection of unresolved eigenvalues, simple plotting of specified eigenmodes and of spectra, and computation of $\epsilon$-pseudospectra for any Differential-Algebraic Equations with user-specifiable norms. It includes tools to find critical parameters for linear stability analysis and is able to project eigenmode onto 2- or 3-D domain for visualization. It can also output projected eigenmodes as Dedalus-formatted HDF5 file to be used as initial conditions for Initial Value Problems, and provides simple plotting of drift ratios (both ordinal and nearest) to evaluate tolerance for eigenvalue rejection.