#!/usr/bin/env python3 from collections import defaultdict from io import BytesIO from base64 import b64encode import numpy as np import matplotlib.pyplot as plt from markdown import Markdown import latexipy as lp from filval.histogram_utils import (hist, hist2d, hist_bin_centers, hist_fit, hist_normalize, hist_stats) __all__ = ['Plot', 'decl_plot', 'grid_plot', 'render_plots', 'hist_plot', 'hist_plot_stack', 'hist2d_plot'] class Plot: def __init__(self, subplots, name, title=None, docs="N/A", arg_dicts=None): self.subplots = subplots self.name = name self.title = title self.docs = docs self.arg_dicts = arg_dicts if arg_dicts is not None else {} MD = Markdown(extensions=['mdx_math'], extension_configs={'mdx_math': {'enable_dollar_delimiter': True}}) lp.latexify(params={'pgf.texsystem': 'pdflatex', 'text.usetex': True, 'font.family': 'serif', 'pgf.preamble': [], 'font.size': 15, 'axes.labelsize': 15, 'axes.titlesize': 13, 'legend.fontsize': 13, 'xtick.labelsize': 11, 'ytick.labelsize': 11, 'figure.dpi': 150, 'savefig.transparent': False, }, new_backend='TkAgg') def _fn_call_to_dict(fn, *args, **kwargs): from inspect import signature pnames = list(signature(fn).parameters) pvals = list(args) + list(kwargs.values()) return {k: v for k, v in zip(pnames, pvals)} def _process_docs(fn): from inspect import getdoc raw = getdoc(fn) if raw: return MD.convert(raw) else: return None def decl_plot(fn): from functools import wraps @wraps(fn) def f(*args, **kwargs): fn(*args, **kwargs) argdict = _fn_call_to_dict(fn, *args, **kwargs) docs = _process_docs(fn) return argdict, docs return f def _add_stats(hist, title=''): fmt = r'''\begin{{eqnarray*}} \sum{{x_i}} &=& {sum:5.3f} \\ \sum{{\Delta x_i \cdot x_i}} &=& {int:5.3G} \\ \mu &=& {mean:5.3G} \\ \sigma^2 &=& {var:5.3G} \\ \sigma &=& {std:5.3G} \end{{eqnarray*}}''' txt = fmt.format(**hist_stats(hist), title=title) txt = txt.replace('\n', ' ') plt.text(0.7, 0.9, txt, bbox={'facecolor': 'white', 'alpha': 0.7, 'boxstyle': 'square,pad=0.8'}, transform=plt.gca().transAxes, verticalalignment='top', horizontalalignment='left', size='small') if title: plt.text(0.72, 0.97, title, bbox={'facecolor': 'white', 'alpha': 0.8}, transform=plt.gca().transAxes, verticalalignment='top', horizontalalignment='left') def grid_plot(subplots): if any(len(row) != len(subplots[0]) for row in subplots): raise ValueError("make_plot requires a rectangular list-of-lists as " "input. Fill empty slots with None") def calc_rowspan(fig, row, col): span = 1 for r in range(row + 1, len(fig)): if fig[r][col] == "FU": span += 1 else: break return span def calc_colspan(fig, row, col): span = 1 for c in range(col + 1, len(fig[row])): if fig[row][c] == "FL": span += 1 else: break return span rows = len(subplots) cols = len(subplots[0]) argdicts = defaultdict(list) docs = defaultdict(list) for i in range(rows): for j in range(cols): cell = subplots[i][j] if cell in ("FL", "FU", None): continue if not isinstance(cell, list): cell = [cell] colspan = calc_colspan(subplots, i, j) rowspan = calc_rowspan(subplots, i, j) plt.subplot2grid((rows, cols), (i, j), colspan=colspan, rowspan=rowspan) for plot in cell: plot_fn, args, kwargs = plot this_args, this_docs = plot_fn(*args, **kwargs) argdicts[(i, j)].append(this_args) docs[(i, j)].append(this_docs) return argdicts, docs def render_plots(plots, exts=('png',), scale=1.0, to_disk=True): for plot in plots: print(f'Building plot {plot.name}') plot.data = None if to_disk: with lp.figure(plot.name, directory='output/figures', exts=exts, size=(scale * 10, scale * 10)): argdicts, docs = grid_plot(plot.subplots) else: out = BytesIO() with lp.mem_figure(out, ext=exts[0], size=(scale * 10, scale * 10)): argdicts, docs = grid_plot(plot.subplots) out.seek(0) plot.data = b64encode(out.read()).decode() plot.argdicts = argdicts plot.docs = docs def add_decorations(axes, luminosity, energy): cms_prelim = r'{\raggedright{}\textsf{\textbf{CMS}}\\ \emph{Preliminary}}' axes.text(0.01, 0.98, cms_prelim, horizontalalignment='left', verticalalignment='top', transform=axes.transAxes) lumi = "" energy_str = "" if luminosity is not None: lumi = r'${} \mathrm{{fb}}^{{-1}}$'.format(luminosity) if energy is not None: energy_str = r'({} TeV)'.format(energy) axes.text(1, 1, ' '.join([lumi, energy_str]), horizontalalignment='right', verticalalignment='bottom', transform=axes.transAxes) def hist_plot(h, *args, norm=None, include_errors=False, log=False, xlim=None, ylim=None, fit=None, grid=False, stats=True, **kwargs): """ Plots a 1D ROOT histogram object using matplotlib """ from inspect import signature if norm: h = hist_normalize(h, norm) values, errors, edges = h scale = 1. if norm is None else norm / np.sum(values) values = [val * scale for val in values] errors = [val * scale for val in errors] left, right = np.array(edges[:-1]), np.array(edges[1:]) x = np.array([left, right]).T.flatten() y = np.array([values, values]).T.flatten() ax = plt.gca() ax.set_xlabel(kwargs.pop('xlabel', '')) ax.set_ylabel(kwargs.pop('ylabel', '')) title = kwargs.pop('title', '') if xlim is not None: ax.set_xlim(xlim) if ylim is not None: ax.set_ylim(ylim) # elif not log: # axes.set_ylim((0, None)) ax.plot(x, y, *args, linewidth=1, **kwargs) if include_errors: ax.errorbar(hist_bin_centers(h), values, yerr=errors, color='k', marker=None, linestyle='None', barsabove=True, elinewidth=.7, capsize=1) if log: ax.set_yscale('log') if fit: f, p0 = fit popt, pcov = hist_fit(h, f, p0) fit_xs = np.linspace(x[0], x[-1], 100) fit_ys = f(fit_xs, *popt) ax.plot(fit_xs, fit_ys, '--g') arglabels = list(signature(f).parameters)[1:] label_txt = "\n".join('{:7s}={: 0.2G}'.format(label, value) for label, value in zip(arglabels, popt)) ax.text(0.60, 0.95, label_txt, va='top', transform=ax.transAxes, fontsize='medium', family='monospace', usetex=False) if stats: _add_stats(h, title) else: ax.set_title(title) ax.grid(grid, color='#E0E0E0') def hist2d_plot(h, **kwargs): """ Plots a 2D ROOT histogram object using matplotlib """ try: values, errors, xs, ys = h except (TypeError, ValueError): values, errors, xs, ys = hist2d(h) plt.xlabel(kwargs.pop('xlabel', '')) plt.ylabel(kwargs.pop('ylabel', '')) plt.title(kwargs.pop('title', '')) plt.pcolormesh(xs, ys, values, ) # axes.colorbar() TODO: Re-enable this def hist_plot_stack(hists: list, labels: list = None): """ Creates a stacked histogram in the current axes. :param hists: list of histogram :param labels: :return: """ if len(hists) == 0: return if len(set([len(hist[0]) for hist in hists])) != 1: raise ValueError("all histograms must have the same number of bins") if labels is None: labels = [None for _ in hists] if len(labels) != len(hists): raise ValueError("Label mismatch") bottoms = [0 for _ in hists[0][0]] for hist, label in zip(hists, labels): centers = [] widths = [] heights = [] for left, right, content in zip(hist[2][:-1], hist[2][1:], hist[0]): centers.append((right+left)/2) widths.append(right - left) heights.append(content) plt.bar(centers, heights, widths, bottoms, label=label) for i, content in enumerate(hist[0]): bottoms[i] += content