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Title: (Re)-connecting foundational libraries with their communities: Successes, failures, and surprises in building the napari ...

Many scientific workflows rely on derivatives of complex models: Fisher forecasts, sensitivity analysis, gradient-based inference, ...

(Alex Zinovev) Moving computationally intensive scientific algorithms from desktop applications to cloud-based services presents ...

Speaker - Michael Zargham SciPy 2026 - www.scipy2026.scipy.org/ Graduate textbooks in applied mathematics are notoriously ...

A session featuring updates and roadmaps from maintainers of core Scientific Python libraries and tools.

A reproducible approach to scientific Python: Git, CI and remote execution with Jupyter notebooks Theodore Tucker Jupyter ...

Plotting is not decoration. Summary statistics lie by omission: four datasets can share the same means, the same variances, and ...

scipy.interpolate.make_interp_spline: modern 1-D splines Returns a callable BSpline. k=3 is cubic. Extrapolation is a choice.

scipy.integrate.quad: integrate a Python function Returns integral and error estimate. Singularities need points= or weight=.

NumPy gives you fast arrays. SciPy gives you algorithms — the industrial-strength numerical routines that working scientists and ...

scipy.optimize.minimize: find a minimum with a method you choose Pass fun, x0, method=. jac= helps. Check success before ...

scipy.linalg.solve: Ax=b with SciPy's solvers Prefer solve over inv. assume_a= when you know structure. scipy.linalg.solve — one ...

scipy.stats.ttest_ind: two-sample t-test without Excel equal_var=False is Welch. p-value is not effect size. scipy.stats.ttest_ind ...

scipy.linalg.lstsq: least squares when A is rectangular Under/over-determined systems. Residuals tell you fit quality.

scipy.special.expit: stable sigmoid Prefer expit over hand-rolled 1/(1+exp(-x)). logit is the inverse. scipy.special.expit — one API, ...

In 2004, Matthew Brett asked me a provocative question born of frustration with existing fMRI tools: "Why don't we rewrite them in ...

scipy.signal.butter: design a Butterworth filter Returns ba or sos. Prefer sos for stability. Wn is normalized to Nyquist unless fs=.

scipy.fft.fft: discrete Fourier transform Complex output. fftfreq labels bins. rfft for real input. scipy.fft.fft — one API, about 75 seconds.

scipy.io.loadmat: read MATLAB .mat into Python Returns a dict. squeeze_me and struct_as_record shape the pain.

scipy.spatial.ConvexHull: convex envelope of points vertices and simplices. Degenerate inputs raise QhullError. scipy.spatial.