Python matplotlib.pylab 模块，rc() 实例源码
我们从Python开源项目中，提取了以下9个代码示例，用于说明如何使用matplotlib.pylab.rc()。
def plot_1d(dataset, nbins, data):
with sns.axes_style('white'):
plt.rc('font', weight='bold')
plt.rc('grid', lw=2)
plt.rc('lines', lw=3)
plt.figure(1)
plt.hist(data, bins=np.arange(nbins+1), color='blue')
plt.ylabel('Count', weight='bold', fontsize=24)
xticks = list(plt.gca().get_xticks())
while (nbins-1) / float(xticks[-1]) < 1.1:
xticks = xticks[:-1]
while xticks[0] < 0:
xticks = xticks[1:]
xticks.append(nbins-1)
xticks = list(sorted(xticks))
plt.gca().set_xticks(xticks)
plt.xlim([int(np.ceil(-0.05*nbins)),int(np.ceil(nbins*1.05))])
plt.legend(loc='upper right')
plt.savefig('plots/marginals-{0}.pdf'.format(dataset.replace('_','-')), bbox_inches='tight')
plt.clf()
plt.close()
def plot_2d(dataset, nbins, data, extra=None):
with sns.axes_style('white'):
plt.rc('font', weight='bold')
plt.rc('grid', lw=2)
plt.rc('lines', lw=2)
rows, cols = nbins
im = np.zeros(nbins)
for i in xrange(rows):
for j in xrange(cols):
im[i,j] = ((data[:,0] == i) & (data[:,1] == j)).sum()
plt.imshow(im, cmap='gray_r', interpolation='none')
if extra is not None:
dataset += extra
plt.savefig('plots/marginals-{0}.pdf'.format(dataset.replace('_','-')), bbox_inches='tight')
plt.clf()
plt.close()
def plot_1d(dataset, nbins):
data = np.loadtxt('experiments/uci/data/splits/{0}_all.csv'.format(dataset), skiprows=1, delimiter=',')[:,-1]
with sns.axes_style('white'):
plt.rc('font', weight='bold')
plt.rc('grid', lw=2)
plt.rc('lines', lw=3)
plt.figure(1)
plt.hist(data, bins=np.arange(nbins+1), color='blue')
plt.ylabel('Count', weight='bold', fontsize=24)
xticks = list(plt.gca().get_xticks())
while (nbins-1) / float(xticks[-1]) < 1.1:
xticks = xticks[:-1]
while xticks[0] < 0:
xticks = xticks[1:]
xticks.append(nbins-1)
xticks = list(sorted(xticks))
plt.gca().set_xticks(xticks)
plt.xlim([int(np.ceil(-0.05*nbins)),int(np.ceil(nbins*1.05))])
plt.legend(loc='upper right')
plt.savefig('plots/marginals-{0}.pdf'.format(dataset.replace('_','-')), bbox_inches='tight')
plt.clf()
plt.close()
def plot_2d(dataset, nbins, data=None, extra=None):
if data is None:
data = np.loadtxt('experiments/uci/data/splits/{0}_all.csv'.format(dataset), skiprows=1, delimiter=',')[:,-2:]
with sns.axes_style('white'):
plt.rc('font', weight='bold')
plt.rc('grid', lw=2)
plt.rc('lines', lw=2)
rows, cols = nbins
im = np.zeros(nbins)
for i in xrange(rows):
for j in xrange(cols):
im[i,j] = ((data[:,0] == i) & (data[:,1] == j)).sum()
plt.imshow(im, cmap='gray_r', interpolation='none')
if extra is not None:
dataset += extra
plt.savefig('plots/marginals-{0}.pdf'.format(dataset.replace('_','-')), bbox_inches='tight')
plt.clf()
plt.close()
def mpl_single_column(usetex=False):
"""
Set matplotlib to make pretty plots for publishing in 2-column
"""
plt.rcdefaults()
plt.rc('font', family='serif', size=12.0, style='normal')
plt.rc('figure', figsize=(4,3))
plt.rc('axes', titlesize=12, labelsize=10)
plt.rc('legend', fontsize=8, numpoints=1, scatterpoints=1)
plt.rc('xtick', labelsize='x-small')
plt.rc('ytick', labelsize='x-small')
plt.rc('text', usetex=usetex)
plt.rc('savefig', format='pdf', bbox='tight')
def mpl_span_columns(usetex=False):
"""
Set matplotlib to make pretty plots for publishing a full-page figure
"""
plt.rcdefaults()
plt.rc('font', family='serif', size=12.0, style='normal')
plt.rc('figure', figsize=(7, 5.25))
plt.rc('axes', titlesize=12, labelsize=10)
plt.rc('legend', fontsize=8, numpoints=1, scatterpoints=1)
plt.rc('xtick', labelsize='x-small')
plt.rc('ytick', labelsize='x-small')
plt.rc('text', usetex=usetex)
plt.rc('savefig', format='pdf', bbox='tight')
def mpl_slides(usetex=False):
"""
Set matplotlibrc to make pretty slides
"""
plt.rcdefaults()
plt.rc('font', family='serif', size=24)
# The default PowerPoint page setup
plt.rc('figure', figsize=(7,5.5))
plt.rc('axes', titlesize=24, labelsize=20, linewidth=3)
plt.rc('legend', fontsize=18, numpoints=1, scatterpoints=1)
plt.rc('xtick', labelsize='small')
plt.rc('ytick', labelsize='small')
plt.rc('text', usetex=usetex)
plt.rc('lines', linewidth=5)
plt.rc('savefig', format='pdf', bbox='tight')
def mpl_thumbnails(usetex=False):
"""
Make png thumbnails
"""
plt.rcdefaults()
plt.rc('font', family='serif')
plt.rc('xtick', labelsize='x-small')
plt.rc('ytick', labelsize='x-small')
plt.rc('text', usetex=usetex)
plt.rc('savefig', format='pdf', bbox='tight')
plt.rc('savefig', format='png', bbox='tight')
plt.rc('figure', figsize=(4,3))
def plot_graphs(df, trending_daily, day_from, day_to, limit, country_code, folder_out=None):
days = pd.DatetimeIndex(start=day_from, end=day_to, freq='D')
for day in days:
fig = plt.figure()
ax = fig.add_subplot(111)
plt.rc('lines', linewidth=2)
data = trending_daily.get_group(str(day.date()))
places, clusters = top_trending(data, limit)
for cluster in clusters:
places.add(max_from_cluster(cluster, data))
ax.set_prop_cycle(plt.cycler('color', ['r', 'b', 'yellow'] + [plt.cm.Accent(i) for i in np.linspace(0, 1, limit-3)]
) + plt.cycler('linestyle', ['-', '-', '-', '-', '-', '--', '--', '--', '--', '--']))
frame = export(places, clusters, data)
frame.sort_values('trending_rank', ascending=False, inplace=True)
for i in range(len(frame)):
item = frame.index[i]
lat, lon, country = item
result_items = ReverseGeoCode().get_address_attributes(lat, lon, 10, 'city', 'country_code')
if 'city' not in result_items.keys():
mark = "%s (%s)" % (manipulate_display_name(result_items['display_name']),
result_items['country_code'].upper() if 'country_code' in result_items.keys() else country)
else:
if check_eng(result_items['city']):
mark = "%s (%s)" % (result_items['city'], result_items['country_code'].upper())
else:
mark = "%.2f %.2f (%s)" % (lat, lon, result_items['country_code'].upper())
gp = df.loc[item].plot(ax=ax, x='date', y='count', label=mark)
ax.tick_params(axis='both', which='major', labelsize=10)
ax.set_yscale("log", nonposy='clip')
plt.xlabel('Date', fontsize='small', verticalalignment='baseline', horizontalalignment='right')
plt.ylabel('Total number of views (log)', fontsize='small', verticalalignment='center', horizontalalignment='center', labelpad=6)
gp.legend(loc='best', fontsize='xx-small', ncol=2)
gp.set_title('Top 10 OSM trending places on ' + str(day.date()), {'fontsize': 'large', 'verticalalignment': 'bottom'})
plt.tight_layout()
db = TrendingDb()
db.update_table_img(plt, str(day.date()), region=country_code)
plt.close()