def __init__(self, new_styles: dict, **kwargs):
from matplotlib import rcParams as params
self.save = params.copy()
self.params = params
self.new_styles = new_styles
self.kwargs = kwargs
self.kwargs.pop('new_styles', None)
def __init__(self, rc=None, fname=None):
self.rcdict = rc
self.fname = fname
self._rcparams = rcParams.copy()
if self.fname:
rc_file(self.fname)
if self.rcdict:
rcParams.update(self.rcdict)
def __init__(self, rc=None, fname=None):
self.rcdict = rc
self.fname = fname
self._rcparams = rcParams.copy()
if self.fname:
rc_file(self.fname)
if self.rcdict:
self.rcdict.update({"grid.alpha": 1.0})
rcParams.update(self.rcdict)
def ridge_plot(plots_dict, scores_df):
'''took the following from the seaborn documentation
https://seaborn.pydata.org/examples/kde_ridgeplot.html
and applied it to visualizing score distributions
'''
## backup of matplotlib parameters
## to reset at the bottom of this function
import matplotlib as mpl
params_backup = rcParams.copy()
ridge_df = scores_df[['label','score']].rename(
columns={'score':'Score'}
).assign(
**{'label': scores_df['label'].astype(str).map(plots_dict['label_map'])}
)
title='Score Distributions of {} vs. {}'\
.format(plots_dict['label_map']['1'],
plots_dict['label_map']['0'])
sns.set(style='white', rc={'axes.facecolor': (0, 0, 0, 0)})
# Create the data
pal = sns.cubehelix_palette(3, rot=-.25, light=.7)
g = sns.FacetGrid(
ridge_df, row='label', hue='label',
aspect=3, height=2.5, palette=['#35978f','#9970ab']
)
## first the curve, then a white line, then axis
g.map(sns.kdeplot, 'Score', clip_on=False, shade=True, alpha=1, lw=1.5, bw=.2)
g.map(sns.kdeplot, 'Score', clip_on=False, color='#f0f0f0', lw=2, bw=.2)
# add nice distribution label on the left
def label(x, color, label):
ax = plt.gca()
ax.text(-0.2, .2, label, fontweight='bold', color=color,
ha='left', va='center', transform=ax.transAxes)
g.map(label, 'Score')
g.fig.suptitle(title)
# add the overlap effect
g.fig.subplots_adjust(hspace=-.25)
# get rid of the facet labels
g.set_titles("")
g.set(yticks=[])
g.set(xlim=(0, 1))
g.despine(bottom=True, left=True)
g.savefig('{}/score_densities.png'.format(plots_dir))
plt.clf()
## reset matplotlib parameters
mpl.rcParams.update(params_backup)
def test_styles(self):
tmp = rcParams.copy()
plots.set_active_style(tab10)
g = plots.get_single_plotter()
self.assertEqual(g.settings.line_styles.name, 'tab10')
plots.set_active_style(planck)
g = plots.get_single_plotter()
self.assertTrue(g.settings.prob_y_ticks)
plots.set_active_style(tab10)
g = plots.get_single_plotter()
self.assertEqual(g.settings.line_styles.name, 'tab10')
plots.set_active_style()
g = plots.get_single_plotter()
self.assertFalse(g.settings.prob_y_ticks)
g = plots.get_single_plotter(style='tab10')
self.assertEqual(g.settings.line_styles.name, 'tab10')
plots.set_active_style('planck')
plots.set_active_style()
self.assertDictEqual(tmp, rcParams)
def test_styles(self):
from getdist.styles.tab10 import style_name as tab10
from getdist.styles.planck import style_name as planck
from matplotlib import rcParams
tmp = rcParams.copy()
plots.set_active_style(tab10)
g = plots.get_single_plotter()
self.assertEqual(g.settings.line_styles.name, 'tab10')
plots.set_active_style(planck)
g = plots.get_single_plotter()
self.assertTrue(g.settings.prob_y_ticks)
plots.set_active_style(tab10)
g = plots.get_single_plotter()
self.assertEqual(g.settings.line_styles.name, 'tab10')
plots.set_active_style()
g = plots.get_single_plotter()
self.assertFalse(g.settings.prob_y_ticks)
g = plots.get_single_plotter(style='tab10')
self.assertEqual(g.settings.line_styles.name, 'tab10')
plots.set_active_style('planck')
plots.set_active_style()
self.assertDictEqual(tmp, rcParams)
def loadstyle(style_name):
""" Load a custom style file, adding both rcParams and custom params.
Writing a proper parser for these settings is in the Matplotlib backlog,
so let's keep calm and avoid inventing their wheel.
"""
style = {}
style_file = os.path.join(HERE, '..', 'rc', style_name)
try:
# Check rc directory for built in styles first
rc_file(style_file)
except FileNotFoundError:
# Check current working dir or path
style_file = style_name
try:
rc_file(style_file)
except FileNotFoundError as err:
raise StyleNotFoundError(f"No such style file found: {err}")
style = rcParams.copy()
# The style files may also contain an extra section with typography
# for titles and captions (these can only be separately styled in code,
# as of Matplotlib 2.2)
# This is a hack, but it's nice to have all styling in one file
# The extra styling is prefixed with `#!`
with open(style_file, 'r') as file_:
doc = file_.readlines()
rc_params_newsworthy = "\n".join(
[d[2:] for d in doc if d.startswith("#!")])
rc_params_newsworthy = yaml.safe_load(rc_params_newsworthy)
###
# Typography
###
style["title_font"] = [
x.strip() for x in rc_params_newsworthy["title_font"].split(",")
]
# define as pt or reltive ("smaller")
style["subtitle.fontsize"] = rc_params_newsworthy.get(
"subtitle.fontsize", None)
# make annotation same font size as ticks by default
tick_font_size = style.get('xtick.labelsize', "smaller")
style["annotation.fontsize"] = rc_params_newsworthy.get(
"annotation.fontsize", tick_font_size)
style["note.fontsize"] = rc_params_newsworthy.get("note.fontsize",
"smaller")
style["caption.fontsize"] = rc_params_newsworthy.get(
"caption.fontsize", "smaller")
color = rc_params_newsworthy.get("neutral_color",
rcParams["figure.edgecolor"])
black_color = rc_params_newsworthy.get("black_color", BLACK)
dark_gray_color = rc_params_newsworthy.get("dark_gray_color", DARK_GRAY)
light_gray_color = rc_params_newsworthy.get("light_gray_color", LIGHT_GRAY)
strong_color = rc_params_newsworthy.get("strong_color", color)
positive_color = rc_params_newsworthy.get("positive_color", POSITIVE)
negative_color = rc_params_newsworthy.get("negative_color", NEGATIVE)
warm_color = rc_params_newsworthy.get("warm_color", WARM)
cold_color = rc_params_newsworthy.get("cold_color", COLD)
fill_between_color = rc_params_newsworthy.get("fill_between_color",
FILL_BETWEEN)
fill_between_alpha = rc_params_newsworthy.get("fill_between_alpha", 0.5)
style["black_color"] = to_rgba("#" + str(black_color), 1)
style["dark_gray_color"] = to_rgba("#" + str(dark_gray_color), 1)
style["light_gray_color"] = to_rgba("#" + str(light_gray_color), 1)
style["neutral_color"] = to_rgba("#" + str(color), 1)
style["strong_color"] = to_rgba("#" + str(strong_color), 1)
style["positive_color"] = to_rgba("#" + positive_color, 1)
style["negative_color"] = to_rgba("#" + negative_color, 1)
style["warm_color"] = to_rgba("#" + warm_color, 1)
style["cold_color"] = to_rgba("#" + cold_color, 1)
style["fill_between_color"] = to_rgba("#" + str(fill_between_color), 1)
style["fill_between_alpha"] = float(fill_between_alpha)
if "qualitative_colors" in rc_params_newsworthy:
style["qualitative_colors"] = [
to_rgba("#" + c.strip(), 1)
for c in rc_params_newsworthy["qualitative_colors"].split(",")
]
else:
style["qualitative_colors"] = [
to_rgba("#" + c, 1) for c in QUALITATIVE
]
if "logo" in rc_params_newsworthy:
style["logo"] = rc_params_newsworthy["logo"]
return style
def __init__(self, rc=None):
self.rcdict = rc
self._rcparams = rcParams.copy()
if self.rcdict:
rcParams.update(self.rcdict)
def Film(instance, solution, name, parameters):
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import warnings
import matplotlib.cbook
warnings.filterwarnings("ignore", category=matplotlib.cbook.mplDeprecation)
def myround(x, base=5):
return int(base * round(float(x) / base))
class Update(object):
def __init__(self, ax, instance, solution, parameters):
self.parameters = parameters
self.ax = ax
self.instance = instance
self.solution = solution
self.X = np.array([loc.X for loc in instance.Locations],
dtype=float)
self.Y = np.array([loc.Y for loc in instance.Locations],
dtype=float)
self.depotLocId = 0
self.requestLocIds = np.array(
[r.customerLocID for r in instance.Requests]) - 1
self.techLocIds = np.array(
[t.locationID for t in self.instance.Technicians]) - 1
# https://stackoverflow.com/questions/22408237/named-colors-in-matplotlib
self.sizes = self.parameters.smallSize * np.ones(len(self.X))
self.sizes[self.techLocIds] = self.parameters.mediumSize
self.sizes[0] = self.parameters.largeSize
self.linewidths = 2 * np.ones(len(self.X))
self.colors = ['limegreen'] * len(self.sizes)
self.colors = [
'gold' if id in self.techLocIds else color
for id, color in enumerate(self.colors)
]
self.colors[0] = 'aquamarine'
self.edgecolors = ['tomato'] * len(self.sizes)
self.edgecolors[0] = 'darkcyan'
self.waitingFor = np.zeros(len(self.X))
em = self.parameters.extraMargin
self.ax.set_xlim(myround(min(self.X) - em),
myround(max(self.X) + em))
self.ax.set_ylim(myround(min(self.Y) - em),
myround(max(self.Y) + em))
self.maxTruckRoutes = 0
self.maxTechnicianRoutes = 0
if not solution is None:
self.maxTruckRoutes = max(
[len(day.TruckRoutes) for day in solution.Days])
self.maxTechnicianRoutes = max(
[len(day.TechnicianRoutes) for day in solution.Days])
self.artists = []
self.artists.append(
ax.text(0.05,
0.9,
'',
transform=ax.transAxes,
family='monospace',
zorder=4,
color='blue',
bbox=dict(facecolor='yellow', alpha=0.2)))
self.artists.append(ax.scatter(self.X, self.Y, zorder=3))
from matplotlib.collections import PatchCollection
if parameters.actionRadius:
from matplotlib.patches import Circle
lo = self.techLocIds
ar = [t.maxDayDistance / 2 for t in self.instance.Technicians]
order = reversed(np.argsort(ar))
circles = [
Circle((self.X[lo[i]], self.Y[lo[i]]), ar[i])
for i in order
]
self.artists.append(
ax.add_collection(PatchCollection(circles, zorder=0)))
else:
self.artists.append(
ax.add_collection(PatchCollection([], zorder=0)))
self.text = 0
self.points = 1
self.radius = 2
self.firstTruckRoute = len(self.artists)
for i in range(self.maxTruckRoutes):
self.artists.append(ax.plot([], [], linewidth=6, zorder=1)[0])
self.firstTechnicianRoute = len(self.artists)
for i in range(self.maxTechnicianRoutes):
self.artists.append(ax.plot([], [], linewidth=2, zorder=2)[0])
def frames(self):
import itertools
nofDays = self.instance.Days
if solution is None:
return [
f for f in itertools.product(
*[range(nofDays), range(1)])
]
else:
perDay = max(
[t.maxDayDistance for t in self.instance.Technicians] +
[self.instance.TruckMaxDistance])
step = myround(perDay / self.parameters.nofDaySteps)
return [
f for f in itertools.product(*[
range(nofDays),
range(0, myround(perDay + step), step)
])
]
def init(self):
self.artists[self.text].set_text('')
self.artists[self.points].set_sizes(self.sizes)
self.artists[self.points].set_color(self.colors)
self.artists[self.points].set_edgecolors(self.edgecolors)
self.artists[self.points].set_linewidths(self.linewidths)
self.artists[self.radius].set_facecolor((0, 1, 0, 0.08))
self.artists[self.radius].set_edgecolor((0, 0, 1, 0.5))
self.artists[self.radius].set_linestyle('--')
if not solution is None:
for i in range(
self.firstTruckRoute, self.firstTruckRoute +
self.maxTechnicianRoutes + self.maxTruckRoutes):
self.artists[i].set_data([], [])
return self.artists
def RouteCoordinatesFromRequests(self, requests, includeDepot=True):
requests = np.array(requests) - 1
aux = self.requestLocIds[requests]
aux[requests < 0] = 0
if not includeDepot:
aux = aux[aux > 0]
return aux
def RouteCoordinatesFromRequestsUpToStep(self, requests, home, step):
def partial(X, Y, limit):
def distance(x, y):
from scipy.spatial import distance
import math
return int(math.ceil(distance.euclidean(x, y)))
points = [(x, y) for x, y in zip(X, Y)]
segments = np.append(
0,
[distance(p1, p2) for p1, p2 in zip(points, points[1:])])
cs = np.cumsum(segments, dtype=int)
idx, = np.where(cs <= limit)
if len(idx) < len(X):
last = idx[-1]
theta = (limit - cs[last]) * 1.0 / segments[last + 1]
if theta > 0:
X[last + 1] = X[last] + theta * (X[last + 1] - X[last])
Y[last + 1] = Y[last] + theta * (Y[last + 1] - Y[last])
idx = np.append(idx, last + 1)
X = X[idx]
Y = Y[idx]
return X, Y
route = self.RouteCoordinatesFromRequests(requests)
route = np.append(home, route)
route = np.append(route, home)
return partial(self.X[route], self.Y[route], step)
def __call__(self, day_and_step):
i, step = day_and_step
self.artists[self.text].set_text('{:>5d}@{:<3d}'.format(
step, i + 1))
active = list(
set([
r.customerLocID - 1 for r in instance.Requests
if r.fromDay <= i + 1 <= r.toDay
]))
import copy
sizes = copy.copy(self.sizes)
sizes[active] = self.parameters.largeSize
self.artists[self.points].set_sizes(sizes)
if not solution is None:
day = self.solution.Days[i]
if step == 0:
delivered = sum([truck.Route for truck in day.TruckRoutes],
[])
installed = sum([
technician.Route for technician in day.TechnicianRoutes
], [])
delivered = self.RouteCoordinatesFromRequests(
np.array(np.unique(delivered), dtype=int), False)
installed = self.RouteCoordinatesFromRequests(
np.array(np.unique(installed), dtype=int))
self.waitingFor[installed] = 0
self.waitingFor[self.waitingFor > 0] = self.waitingFor[
self.waitingFor > 0] + 1
self.waitingFor[delivered] = 1
widths = copy.copy(self.linewidths)
widths[self.waitingFor > 0] = 2 * (
self.waitingFor[self.waitingFor > 0] + 1)
self.artists[self.points].set_linewidths(widths)
for i in range(
self.firstTruckRoute, self.firstTruckRoute +
self.maxTechnicianRoutes + self.maxTruckRoutes):
self.artists[i].set_data([], [])
for i, truck in enumerate(day.TruckRoutes):
self.artists[self.firstTruckRoute + i].set_data(
self.RouteCoordinatesFromRequestsUpToStep(
truck.Route, 0, step))
for i, technician in enumerate(day.TechnicianRoutes):
person = self.instance.Technicians[technician.ID - 1]
self.artists[self.firstTechnicianRoute + i].set_data(
self.RouteCoordinatesFromRequestsUpToStep(
technician.Route, person.locationID - 1, step))
return self.artists
if parameters.xkcd:
from matplotlib import rcParams
saved_state = rcParams.copy()
plt.xkcd()
fig = plt.figure()
plt.axis('equal')
ax = plt.axes()
ud = Update(ax, instance, solution, parameters)
fig.set_size_inches(ud.parameters.inchH, ud.parameters.inchV)
ani = animation.FuncAnimation(fig,
ud,
frames=ud.frames(),
init_func=ud.init,
blit=True)
name = name.rsplit('.', 1)[0]
# install http://www.imagemagick.org/script/download.php#windows for ffmpeg and other writers.
if ud.parameters.mp4:
FFwriter = animation.FFMpegWriter(fps=ud.parameters.fps,
extra_args=['-vcodec', 'libx264'])
ani.save(name + '.mp4', writer=FFwriter)
if ud.parameters.html:
ani.save(name + ".htm", writer="html")
if ud.parameters.pdf:
from matplotlib.backends.backend_pdf import PdfPages
with PdfPages(name + '.pdf') as pdf:
ud.init()
for f in ud.frames():
ud(f)
plt.show()
pdf.savefig(fig)
plt.show()
plt.close()
if parameters.xkcd:
from matplotlib import rcParams
rcParams.update(saved_state)
