""" plotting.py The functions in this module are meant for plotting the histogram objects created via filval.histogram """ from collections import defaultdict from itertools import zip_longest 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 import (hist, hist2d, hist_bin_centers, hist_fit, hist_norm, hist_stats) __all__ = ['Plot', 'decl_plot', 'grid_plot', 'render_plots', 'generate_dashboard', 'hist_plot', 'hist_plot_stack', 'hist2d_plot', 'hists_to_table', 'simple_plot'] class Plot: def __init__(self, subplots, name, title=None, docs="N/A", arg_dicts=None): if type(subplots) is not list: subplots = [[subplots]] elif len(subplots) > 0 and type(subplots[0]) is not list: subplots = [subplots] 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 from html import escape pnames = list(signature(fn).parameters) pvals = list(args) + list(kwargs.values()) return {escape(str(k)): escape(str(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): txt = fn(*args, **kwargs) argdict = _fn_call_to_dict(fn, *args, **kwargs) docs = _process_docs(fn) if not txt: txt = '' txt = MD.convert(txt) return argdict, docs, txt return f def simple_plot(thx, *args, log=None, **kwargs): import ROOT if isinstance(thx, ROOT.TH2): def f(h): hist2d_plot(hist2d(h), *args, **kwargs) plt.xlabel(h.GetXaxis().GetTitle()) plt.ylabel(h.GetYaxis().GetTitle()) if log == 'x': plt.semilogx() elif log == 'y': plt.semilogy() elif log == 'xy': plt.loglog() return dict(), "", "" return Plot([[(f, (thx,), {})]], thx.GetName()) elif isinstance(thx, ROOT.TH1): def f(h): hist_plot(hist(h), *args, **kwargs) plt.xlabel(h.GetXaxis().GetTitle()) plt.ylabel(h.GetYaxis().GetTitle()) if log == 'x': plt.semilogx() elif log == 'y': plt.semilogy() elif log == 'xy': plt.loglog() return dict(), "", "" return Plot([[(f, (thx,), {})]], thx.GetName()) else: raise ValueError("must call simple_plot with a ROOT TH1 or TH2 object") def generate_dashboard(plots, title, output='dashboard.html', template='dashboard.j2', source=None, ana_source=None, config=None): from jinja2 import Environment, PackageLoader, select_autoescape from os.path import join, isdir from os import mkdir from urllib.parse import quote env = Environment( loader=PackageLoader('filval', 'templates'), autoescape=select_autoescape(['htm', 'html', 'xml']), ) env.globals.update({'quote': quote, 'enumerate': enumerate, 'zip': zip, }) def get_by_n(objects, n=2): objects = list(objects) while objects: yield objects[:n] objects = objects[n:] if source is not None: with open(source, 'r') as f: source = f.read() if not isdir('output'): mkdir('output') dashboard_path = join('output', output) with open(dashboard_path, 'w') as tempout: templ = env.get_template(template) tempout.write(templ.render( plots=get_by_n(plots, 3), title=title, source=source, ana_source=ana_source, config=config )) return dashboard_path 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_row_span(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_column_span(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) txts = 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] column_span = calc_column_span(subplots, i, j) row_span = calc_row_span(subplots, i, j) plt.subplot2grid((rows, cols), (i, j), colspan=column_span, rowspan=row_span) for plot in cell: if not isinstance(plot, tuple): plot_fn, args, kwargs = plot, (), {} elif len(plot) == 1: plot_fn, args, kwargs = plot[0], (), {} elif len(plot) == 2: plot_fn, args, kwargs = plot[0], plot[1], {} elif len(plot) == 3: plot_fn, args, kwargs = plot[0], plot[1], plot[2] else: raise ValueError('Plot tuple must be of format (func), ' f'or (func, tuple), or (func, tuple, dict). Got {plot}') this_args, this_docs, txt = plot_fn(*args, **kwargs) argdicts[(i, j)].append(this_args) docs[(i, j)].append(this_docs) txts[(i, j)].append(txt) return argdicts, docs, txts def render_plots(plots, exts=('png',), directory='output/figures/', 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.replace(' ', '_'), directory=directory, exts=exts, size=(scale * 10, scale * 10)): argdicts, docs, txts = grid_plot(plot.subplots) else: out = BytesIO() with lp.mem_figure(out, ext=exts[0], size=(scale * 10, scale * 10)): argdicts, docs, txts = grid_plot(plot.subplots) out.seek(0) plot.data = b64encode(out.read()).decode() plot.argdicts = argdicts plot.docs = docs plot.txts = txts 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, include_errors=False, fit=None, stats=False, **kwargs): """ Plots a 1D ROOT histogram object using matplotlib """ from inspect import signature values, errors, edges = h left, right = np.array(edges[:-1]), np.array(edges[1:]) x = np.array([left, right]).T.flatten() y = np.array([values, values]).T.flatten() title = kwargs.pop('title', '') plt.plot(x, y, *args, linewidth=1, **kwargs) if include_errors: plt.errorbar(hist_bin_centers(h), values, yerr=errors, color='k', marker=None, linestyle='None', barsabove=True, elinewidth=.7, capsize=1) 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) plt.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)) plt.text(0.60, 0.95, label_txt, va='top', transform=plt.gca().transAxes, fontsize='medium', family='monospace', usetex=False) if stats: _add_stats(h, title) def hist2d_plot(h, txt_format=None, colorbar=False, **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, **kwargs) if txt_format is not None: cmap = plt.get_cmap() min_, max_ = float(np.min(values)), float(np.max(values)) def get_intensity(val): cmap_idx = int((cmap.N-1) * (val - min_) / (max_-min_)) color = cmap.colors[cmap_idx] return color[0]*0.25 + color[1]*0.5 + color[2]*0.25 for idx_row in range(values.shape[0]): for idx_col in range(values.shape[1]): x_mid = (xs[idx_row, idx_col] + xs[idx_row, idx_col+1]) / 2 y_mid = (ys[idx_row, idx_col] + ys[idx_row+1, idx_col]) / 2 val = txt_format.format(values[idx_row, idx_col]) txt_color = 'w' if get_intensity(values[idx_row, idx_col]) < 0.5 else 'k' plt.text(x_mid, y_mid, val, verticalalignment='center', horizontalalignment='center', color=txt_color, fontsize=12) if colorbar: plt.colorbar() 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 def hists_to_table(hists, row_labels=(), column_labels=(), format="{:.2f}"): table = ['
') table.extend(f' | {label} | ' for label in column_labels) table.append('
---|---|
{row_label} | ') table.extend((''+format.format(val)+' | ') for val in vals) table.append('