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plot_functions.py
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"""Adapt plot functions with seaborn to get more beautiful plots."""
from __future__ import unicode_literals
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import logging
import os
import collections
import itertools
import numpy as np
import scipy.stats as ss
from distutils.spawn import find_executable
if find_executable('latex'):
HAS_LATEX = True
else:
HAS_LATEX = False
import matplotlib
if "DISPLAY" not in os.environ:
matplotlib.use("Agg")
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle, Arrow
import matplotlib.dates as mdates
from pandas import DataFrame
LINEWIDTH = 5
FONT_ENV = {
"lines.linewidth": LINEWIDTH,
"lines.markersize":20,
"ps.useafm": HAS_LATEX,
"pdf.use14corefonts" : HAS_LATEX,
"text.usetex": HAS_LATEX,
}
sns.set(font_scale=3.0, rc=FONT_ENV)
FIG_SIZE = (8, 7)
logging.basicConfig(level=logging.INFO)
COLOR_NAMES = ["cerulean", "light red", "seafoam", "dark orange",
"burgundy", "dark magenta", "midnight blue", "light violet",
"ocean blue", "bluish purple", "pinkish", "pale orange",
"aqua green", "pumpkin", "chocolate", "pine green"]
def start_plotting(fig_size, fig_pos, style="white", rc=None, despine=False):
with sns.axes_style(style, rc):
fig = plt.figure(figsize=fig_size)
if not fig_pos:
ax = fig.add_subplot(111)
else:
ax = fig.add_axes(fig_pos)
if despine:
sns.despine(left=True)
return fig, ax
def frange(x, y, step):
while x < y:
yield x
x += step
def end_plotting(fig, ax, title=None, xlabel=None,
ylabel=None, xlim=None, ylim=None, filename=None,
xticklabel=None, xlabel_rotation=None,
yticklabel=None, ylabel_rotation=None, label_text=None,
xtickgap=None):
'''A set of common operations after plotting.'''
if title:
ax.set_title(title)
if xlabel:
ax.set_xlabel(xlabel)
if xticklabel:
ax.set_xticks(xticklabel[0])
ax.set_xticklabels(xticklabel[1], rotation=xlabel_rotation)
elif xtickgap:
xticks = ax.get_xticks()
ax.set_xticks(list(frange(min(xticks), max(xticks) + 0.001, xtickgap)))
else:
ax.set_xticks(ax.get_xticks())
ax.set_xticklabels(ax.get_xticks())
if yticklabel:
ax.set_yticks(yticklabel[0])
ax.set_yticklabels(yticklabel[1], rotation=ylabel_rotation)
else:
ax.set_yticks(ax.get_yticks())
ax.set_yticklabels(ax.get_yticks())
if ylabel:
ax.set_ylabel(ylabel)
if xlim:
ax.set_xlim(xlim)
if ylim:
ax.set_ylim(ylim)
if label_text:
for x, y, t in label_text:
ax.text(x, y, t)
def savefig(fig, filename):
fig.savefig(filename)
plt.close()
def ax_plot_lines(ax, xs, ys, colors, shapes, linestyles,
errorbar=False, linewidth=LINEWIDTH):
lines = []
for (x, y, c, s, l) in zip(xs, ys, colors, shapes, linestyles):
if errorbar:
# y should be a list of lists in this case
mean = [np.mean(yl) for yl in y]
error = [ss.sem(yl) for yl in y]
l = ax.errorbar(x, mean, yerr=error, color=c,
marker=s, linestyle=l, ecolor=c)
else:
l, = ax.plot(x, y, color=c, marker=s, linestyle=l, linewidth=linewidth)
lines.append(l)
return lines
def plot_lines(xs, ys, title=None, xlabel=None,
ylabel=None, xlim=None, ylim=None,
colors=None, shapes=None, linestyles=None,
errorbar=False, legend=None, loc=0,
xticklabel=None, yticklabel=None,
xlabel_rotation=None, ylabel_rotation=None,
hlines=None, vlines=None, bbox_to_anchor=None,
fig_pos=None, fig_size=FIG_SIZE, label_text=None,
xdate=False, linewidth=LINEWIDTH, rc=None, despine=False,
ticksize=None, style="white", filename=None):
'''Plot lines for all pairs of xs and ys.
Input:
xs: a list of x-value lists
ys: a list of y-value lists ([[1, 2, 3]], two layers),
or a list of y-value lists grouped by x ([[[1, 2, 3], [1, 3]]],
three layers),
in the second case, errorbar is computed using standard error
ys should be with the same length of xs
'''
fig, ax = start_plotting(fig_size, fig_pos, rc=rc, despine=despine,
style=style)
if not colors:
colors = sns.color_palette(n_colors=len(xs))
if not shapes:
shapes = ['o', 's', '^', 'd', '+', 'v', '*', 'x'] * (len(xs) // 8 + 1)
if not linestyles:
linestyles = ['-'] * len(xs)
if xdate:
xs = [[mdates.date2num(d) for d in l] for l in xs]
lines = ax_plot_lines(ax, xs, ys, colors, shapes, linestyles,
errorbar=errorbar, linewidth=linewidth)
if xdate:
# this works for years and month
# customize through xlabel and xticklabels
years = mdates.YearLocator() # every year
months = mdates.MonthLocator() # every month
yearsFmt = mdates.DateFormatter('%Y')
ax.xaxis.set_major_locator(years)
ax.xaxis.set_major_formatter(yearsFmt)
ax.xaxis.set_minor_locator(months)
fig.autofmt_xdate()
if hlines:
for y in hlines:
ax.axhline(y=y, linestyle='--', color='black')
if vlines:
for x in vlines:
ax.axvline(x=x, linestyle='--', color='black')
if legend:
ax.legend(lines, legend, loc=loc, bbox_to_anchor=bbox_to_anchor,
frameon=False)
if not xlim:
diff = np.max(xs) - np.min(xs)
xlim = (np.min(xs) - 0.02 * diff, np.max(xs) + 0.02 * diff)
end_plotting(fig, ax, title=title, xlabel=xlabel,
ylabel=ylabel, xlim=xlim, ylim=ylim,
xticklabel=xticklabel, yticklabel=yticklabel,
xlabel_rotation=xlabel_rotation,
ylabel_rotation=ylabel_rotation, label_text=label_text)
if ticksize is not None:
ax.tick_params(axis='both', which='major', labelsize=ticksize)
if filename:
savefig(fig, filename)
return fig
class SubsampleJointGrid(sns.JointGrid):
def plot_sub_joint(self, func, subsample, **kwargs):
"""Draw a bivariate plot of `x` and `y`.
Parameters
----------
func : plotting callable
This must take two 1d arrays of data as the first two
positional arguments, and it must plot on the "current" axes.
kwargs : key, value mappings
Keyword argument are passed to the plotting function.
Returns
-------
self : JointGrid instance
Returns `self`.
"""
if subsample > 0 and subsample < len(self.x):
indexes = np.random.choice(range(len(self.x)), subsample,
replace=False)
plot_x = np.array([self.x[i] for i in indexes])
plot_y = np.array([self.y[i] for i in indexes])
plt.sca(self.ax_joint)
func(plot_x, plot_y, **kwargs)
else:
plt.sca(self.ax_joint)
func(self.x, self.y, **kwargs)
return self
def joint_plot(x, y, xlabel=None,
ylabel=None, xlim=None, ylim=None,
loc="best", color='#0485d1',
size=8, markersize=50, kind="kde",
scatter_color="r"):
with sns.axes_style("darkgrid"):
if xlabel and ylabel:
g = SubsampleJointGrid(xlabel, ylabel,
data=DataFrame(data={xlabel: x, ylabel: y}),
space=0.1, ratio=2, size=size, xlim=xlim, ylim=ylim)
else:
g = SubsampleJointGrid(x, y, size=size,
space=0.1, ratio=2, xlim=xlim, ylim=ylim)
g.plot_joint(sns.kdeplot, shade=True, cmap="Blues")
g.plot_sub_joint(plt.scatter, 1000, s=20, c=scatter_color, alpha=0.3)
g.plot_marginals(sns.distplot, kde=False, rug=False)
g.annotate(ss.pearsonr, fontsize=25, template="{stat} = {val:.2g}\np = {p:.2g}")
g.ax_joint.set_yticklabels(g.ax_joint.get_yticks())
g.ax_joint.set_xticklabels(g.ax_joint.get_xticks())
return g
def plot_bar(value_lists, xlabel=None, fig_size=FIG_SIZE,
fig_pos=None, ylabel=None, xticklabel=None,
xlabel_rotation=None, width=-1, gap=1,
yticklabel=None, legend=None,
errorbar_list=None, color_list=sns.color_palette(n_colors=10),
ylim=None, ncol=1,
handlelength=None, loc=0, bbox_to_anchor=None,
handletextpad=None, columnspacing=None,
vlines=None, hlines=None, xlim=None,
hatches=None, filename=None):
fig, ax = start_plotting(fig_size, fig_pos)
N = len(value_lists[0])
if width < 0:
width = 0.75 * gap / len(value_lists)
ind = np.arange(N) * gap
rects = []
for i in range(len(value_lists)):
rect = ax.bar(ind, value_lists[i], width, color=color_list[i],
yerr=errorbar_list[i] if errorbar_list else None,
error_kw={"ecolor": "black"},
hatch=None if not hatches else hatches[i])
ind = ind + width
rects.append(rect)
xlim = (-width, max(ind) + width)
if hlines:
for y in hlines:
ax.axhline(y=y, linestyle='--', color='grey')
if vlines:
for x in vlines:
ax.axvline(x=x, linestyle='--', color='grey')
if legend:
ax.legend(rects, legend, loc=loc,
bbox_to_anchor=bbox_to_anchor,
ncol=ncol, handlelength=handlelength,
handletextpad=handletextpad,
columnspacing=columnspacing,
frameon=False)
end_plotting(fig, ax, xlabel=xlabel, ylabel=ylabel,
xticklabel=xticklabel,
xlabel_rotation=xlabel_rotation,
xlim=xlim,
yticklabel=yticklabel, ylim=ylim)
if filename:
savefig(fig, filename)
return fig