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()
