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- """
- 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 class="table table-condensed">']
- if column_labels:
- table.append('<thead><tr>')
- if row_labels:
- table.append('<th></th>')
- table.extend(f'<th>{label}</th>' for label in column_labels)
- table.append('</tr></thead>')
- table.append('<tbody>\n')
- for row_label, (vals, *_) in zip_longest(row_labels, hists):
- table.append('<tr>')
- if row_label:
- table.append(f'<td><strong>{row_label}</strong></td>')
- table.extend(('<td>'+format.format(val)+'</td>') for val in vals)
- table.append('</tr>\n')
- table.append('</tbody></table>')
- return ''.join(table)
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