xiaohongshu
xiaohongshu
hist
Use when working with the scikit-hep hist library in Python to create, fill, slice, and plot histograms (1D/2D/multi-axis), including UHI indexing, categorical axes, and mplhep plotting conventions.
Full skill instructions
Use this skill to build and manipulate hist.Hist objects, choose axis/storage types, fill with data and weights, and produce publication-style plots with mplhep styles, all based on matplotlib.
Hist.new plus axis builders (Reg, Var, StrCat) and finish with exactly one storage (Int64 or Weight)..fill(...) using axis names; note that .fill returns None.h.project("x") or h[{"x": 5j}]).hist.plot(...) or mplhep.hist2dplot(...); use plt.style.use(hep.style.ATLAS) for HEP-style plots.Reg for uniform bins and Var for variable-width bins.StrCat for categorical axes; set growth=True for auto-added categories.Int64 for unweighted counts, Weight for weighted fills.h.fill(x=..., y=..., weight=...)).h.view() and errors from np.sqrt(h.variances()).::2j for rebinning).h.project("axis_name") for 1D plots.hist.plot(histtype="fill") for 1D; use mplhep.hist2dplot for 2D.plt.subplots() without custom figsize unless explicitly requested.fig.savefig("name.png") and close with plt.close(fig).references/hist-hints.md for concrete code snippets and common patterns.references/hist-advanced.md for UHI indexing, plotting gotchas, and label/LaTeX guidance.references/lhc-hist-ranges.md for starting suggestions on histogram axis ranges and binning.xiaohongshu
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