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analysis-and-io

analysis-and-io

QuTiP visualization, phase-space analysis, tomography, file I/O, and reporting workflows.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentación de la Skill

GitHub

name: "analysis-and-io" description: "QuTiP visualization, phase-space analysis, tomography, file I/O, and reporting workflows." metadata: disco-role: operating disable-model-invocation: true license: BSD 3-Clause

Analysis and I/O

Use this subskill when the task is about turning QuTiP objects or solver results into plots, saved artifacts, process tomography, environment summaries, or citation output.

Read this subskill when the prompt mentions

  • Bloch, Bloch sphere plots, vectors, arcs, points, or qubit-state visualization
  • hinton, matrix_histogram, plot_wigner, plot_qfunc, plot_fock_distribution, plot_expectation_values
  • wigner, qfunc, spin Wigner functions, quasi-probability distributions, or harmonic-oscillator probability functions
  • qpt, process tomography, qpt_plot, or qpt_plot_combined
  • qsave, qload, file_data_store, file_data_read
  • about(), cite(), ipynbtools.version_table, or notebook/reporting helpers

What to decide first

  1. Is the user trying to visualize a state, an operator, a process, or solver result data?
  2. Does the environment have Matplotlib, and is a headless backend needed?
  3. Is the task about a saved QuTiP object (.qu) or plain numeric data?
  4. Does the task need a reusable artifact or only a quick diagnostic plot?

Core workflow

  • Set a non-interactive Matplotlib backend before plotting in headless runs.
  • Build or receive a valid Qobj first; plotting helpers do not fix object dimensions.
  • Pass explicit fig and ax objects when embedding plots into a larger script.
  • Use qsave / qload for QuTiP objects and file_data_store / file_data_read for raw numeric arrays.
  • Use about() for environment summaries and cite() for publication reminders.

Typical success signals

  • Plot helpers return a Matplotlib Figure and Axes or an animation object.
  • Saved Qobj objects round-trip through qsave and qload.
  • Basis labels have the same length as the plotted matrix axes.
  • about() reports the package and dependency versions from the active interpreter.

Boundaries

Use this subskill for analysis artifacts after a valid object or result exists. Do not use it as the main route for:

  • Building the Hamiltonian, state, or measurement operators; use core-objects first.
  • Choosing a solver or fixing time-dependent coefficient logic; use dynamics-and-solvers.
  • PIQS, HEOM, or bath-model construction; use specialized-open-systems before plotting or saving outputs.

Answer shape

When responding from this subskill, give:

  1. The correct plotting, phase-space, file I/O, or reporting API.
  2. The minimal object/result shape expected by that API.
  3. A headless-safe code snippet if figures are created.
  4. The artifact path, file suffix, or return-object type to expect.
  5. A cleanup step such as closing Matplotlib figures or using a temporary directory.

Validation hints

  • Use matplotlib.use('Agg') for non-interactive smoke checks.
  • Use qubit states for Bloch examples unless the prompt explicitly requires another representation.
  • Verify qsave / qload round trips in a scratch directory before relying on saved data.

Reference files

  • references/api-reference.md for plotting, phase-space, file I/O, and reporting entry points.
  • references/workflows.md for compact plotting and save/load recipes.
  • references/troubleshooting.md for Matplotlib, basis-label, Bloch-geometry, and .qu suffix issues.

Helper script

  • scripts/visual_io_smoke.py verifies Matplotlib plotting, Bloch rendering, Wigner calculation, and qsave/qload round-tripping.
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