ViewTube

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

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

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

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

scipy.stats.bootstrap: confidence intervals without a formula Pass data and statistic. method= and confidence_level= matter.

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

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

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

scipy.signal.sosfiltfilt: zero-phase filter forward and back No phase distortion. Not for realtime. Pair with butter(sos).

scipy.signal.find_peaks: pick peaks with prominence height, distance, prominence beat a raw argmax loop.

scipy.spatial.distance.cdist: pairwise distances between two sets metric="euclidean" default. Don't reinvent broadcasting loops.

scipy.optimize.root: solve f(x)=0 in N dimensions method= hybr or lm. Need a residual vector. Check success. scipy.optimize.root ...

scipy.sparse.linalg.spsolve: solve sparse Ax=b Don't densify first. Format matters. Factorize once if A is fixed.

scipy.sparse.csr_matrix: store mostly-zeros without melting RAM CSR loves row slices and matvecs. Build with coo then convert.

scipy.ndimage.label: connected components in an array Structure defines neighbors. Returns labeled array and count.

scipy.ndimage.gaussian_filter: blur an array (images included) sigma per axis. mode= handles edges. Works on N-D, not only ...

When you write v + w in NumPy, or len(df) in pandas, you are using a secret that this episode makes yours: Python's operators are ...

[DESCRIPTION]: In Part 4.6, we upgrade Genome Toolkit from simple algorithm inputs and primitive return values to validated ...