CALCULA, the scientific calculation notebook

CALCULA works like a sheet of paper: you write your calculations one under another, and the cells talk to each other. A cell defining m = 2.5 kg makes that symbol usable throughout the rest of the document; correcting its value recomputes everything that depends on it. That is the fundamental difference from a calculator: you do not start a calculation over, you correct a datum.

Units and uncertainties follow the calculation — 1.250 ± 0.002 m comes out with its uncertainty propagated. Data is imported from a CSV or a spreadsheet, a model is fitted to it, a differential equation is solved, and a cell runs real Python. A glossary of 2,500 formulas, 2,272 of them directly computable, stays readable and insertable while you compute, and every result says how it was obtained.

Every calculation — symbolic algebra, analysis, statistics, physics, chemistry, orbital mechanics — runs locally in your browser through a Python scientific engine (Pyodide: SymPy, NumPy, SciPy). No expression, no imported data and no result is ever sent to a server.

The fields covered

• Algebra & calculus — equations, systems, derivatives, integrals, limits, series, matrices.
• Trigonometry & geometry — the unit circle, identities, areas and volumes, vectors.
• Statistics & probability — mean, standard deviation, regression, distributions, tests.
• Physics — mechanics, energy, waves, electricity, thermodynamics, relativity.
• Chemistry — molarity, dilution, pH, equilibria, kinetics, thermochemistry.
• Orbital mechanics — Kepler's laws, the rocket equation, Hohmann transfers, vis-viva.
• Radiometric dating — decay, half-life, carbon-14, isotope pairs.
• Number theory — GCD, congruences, primes, modular arithmetic.
• Conversions & units — number bases, physical units, classical ciphers.

Each field has its guide: the essential formulas, a worked example with numbers, and how to type them in. Alongside these subject guides, nine feature guides explain how to use the notebook — the reactive page, units and uncertainties, data and fitting, the Python cell, the subject packs, export and offline use — each with an example to replay.