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numpy.min

Python. Called in 3 tutorials; each line below leads to its place in the tutorial.

ConceptPythonIntermediate

Rational approximation: why a resonance needs a ratio of polynomials

gap = np.array([np.min(np.abs(zeros_n - p)) for p in poles_n[doublet]])
print(f"largest distance to the exact poles: {max(np.min(np.abs(exact - p)) for p in poles):.1e}")

ToolPythonBeginner

Units with pint: catch the mistake that lost the Mars Climate Orbiter

print(f"coldest {np.min(T):~P}, warmest {np.max(T):~P}, mean {np.mean(T):.2f~P}")

ConceptPythonBeginner

Voronoi and Delaunay: the rainfall over a catchment from twelve gauges

d_view = np.min(np.hypot(xv[..., None] - gauges[:, 0], yv[..., None] - gauges[:, 1]), axis=-1)