python图形绘制源代码(18页).doc

-python图形绘制源代码-第 18 页饼图import matplotlib.pyplot as plt# Pie chart, where the slices will be ordered and plotted counter-clockwise:labels = 'Frogs', 'Hogs', 'Dogs', 'Logs'sizes = 15, 30, 45, 10explode = (0, 0.1, 0, 0) # only "explode" the 2nd slice (i.e. 'Hogs')fig1, ax1 = plt.subplots()ax1.pie(sizes, explode=explode, labels=labels, autopct='%1.1f%', shadow=True, startangle=90)ax1.axis('equal') # Equal aspect ratio ensures that pie is drawn as a circle.plt.show()条形图1import numpy as npimport matplotlib.pyplot as pltfrom matplotlib.ticker import MaxNLocatorfrom collections import namedtuplen_groups = 5means_men = (20, 35, 30, 35, 27)std_men = (2, 3, 4, 1, 2)means_women = (25, 32, 34, 20, 25)std_women = (3, 5, 2, 3, 3)fig, ax = plt.subplots()index = np.arange(n_groups)error_config = 'ecolor': '0.3'rects1 = ax.bar(index, means_men, bar_width, alpha=opacity, color='b', yerr=std_men, error_kw=error_config, label='Men')rects2 = ax.bar(index + bar_width, means_women, bar_width, alpha=opacity, color='r', yerr=std_women, error_kw=error_config, label='Women')ax.set_xlabel('Group')ax.set_ylabel('Scores')ax.set_title('Scores by group and gender')ax.set_xticks(index + bar_width / 2)ax.set_xticklabels('A', 'B', 'C', 'D', 'E')ax.legend()fig.tight_layout()plt.show()表格图import numpy as npimport matplotlib.pyplot as pltdata = 66386, 174296, 75131, 577908, 32015, 58230, 381139, 78045, 99308, 160454, 89135, 80552, 152558, 497981, 603535, 78415, 81858, 150656, 193263, 69638, 139361, 331509, 343164, 781380, 52269columns = ('Freeze', 'Wind', 'Flood', 'Quake', 'Hail')rows = '%d year' % x for x in (100, 50, 20, 10, 5)values = np.arange(0, 2500, 500)value_increment = 1000# Get some pastel shades for the colorscolors = plt.cm.BuPu(np.linspace(0, 0.5, len(rows)n_rows = len(data)# Initialize the vertical-offset for the stacked bar chart.y_offset = np.zeros(len(columns)# Plot bars and create text labels for the tablecell_text = for row in range(n_rows): plt.bar(index, datarow, bar_width, bottom=y_offset, color=colorsrow) y_offset = y_offset + datarow cell_text.append('%1.1f' % (x / 1000.0) for x in y_offset)# Reverse colors and text labels to display the last value at the top.colors = colors:-1cell_text.reverse()# Add a table at the bottom of the axesthe_table = plt.table(cellText=cell_text, rowLabels=rows, rowColours=colors, colLabels=columns, loc='bottom')# Adjust layout to make room for the table:plt.subplots_adjust(left=0.2, bottom=0.2)plt.ylabel("Loss in $0's".format(value_increment)plt.yticks(values * value_increment, '%d' % val for val in values)plt.xticks()plt.title('Loss by Disaster')plt.show()散点图import numpy as npimport matplotlib.pyplot as pltimport matplotlib.cbook as cbook# Load a numpy record array from yahoo csv data with fields date, open, close,# volume, adj_close from the mpl-data/example directory. The record array# stores the date as an np.datetime64 with a day unit ('D') in the date column.with cbook.get_sample_data('goog.npz') as datafile: price_data = np.load(datafile)'price_data'.view(np.recarray)price_data = price_data-250: # get the most recent 250 trading daysdelta1 = np.diff(price_data.adj_close) / price_data.adj_close:-1# Marker size in units of points2volume = (15 * price_data.volume:-2 / price_data.volume0)*2close = 0.003 * price_data.close:-2 / 0.003 * price_data.open:-2fig, ax = plt.subplots()ax.scatter(delta1:-1, delta11:, c=close, s=volume, alpha=0.5)ax.set_xlabel(r'$Delta_i$', fontsize=15)ax.set_ylabel(r'$Delta_i+1$', fontsize=15)ax.set_title('Volume and percent change')ax.grid(True)fig.tight_layout()plt.show()平滑图import numpy as npimport matplotlib.pyplot as pltfrom matplotlib.widgets import Slider, Button, RadioButtonsfig, ax = plt.subplots()plt.subplots_adjust(left=0.25, bottom=0.25)t = np.arange(0.0, 1.0, 0.001)a0 = 5f0 = 3s = a0*np.sin(2*np.pi*f0*t)l, = plt.plot(t, s, lw=2, color='red')plt.axis(0, 1, -10, 10)axcolor = 'lightgoldenrodyellow'axfreq = plt.axes(0.25, 0.1, 0.65, 0.03, facecolor=axcolor)axamp = plt.axes(0.25, 0.15, 0.65, 0.03, facecolor=axcolor)sfreq = Slider(axfreq, 'Freq', 0.1, 30.0, valinit=f0, valstep=delta_f)samp = Slider(axamp, 'Amp', 0.1, 10.0, valinit=a0)def update(val): l.set_ydata(amp*np.sin(2*np.pi*freq*t) fig.canvas.draw_idle()sfreq.on_changed(update)samp.on_changed(update)resetax = plt.axes(0.8, 0.025, 0.1, 0.04)button = Button(resetax, 'Reset', color=axcolor, hovercolor='0.975')def reset(event): sfreq.reset() samp.reset()button.on_clicked(reset)rax = plt.axes(0.025, 0.5, 0.15, 0.15, facecolor=axcolor)radio = RadioButtons(rax, ('red', 'blue', 'green'), active=0)def colorfunc(label): l.set_color(label) fig.canvas.draw_idle()radio.on_clicked(colorfunc)plt.show()数据打钩标签图import datetimeimport numpy as npimport matplotlib.pyplot as pltimport matplotlib.dates as mdatesimport matplotlib.cbook as cbookyears = mdates.YearLocator() # every yearmonths = mdates.MonthLocator() # every monthyearsFmt = mdates.DateFormatter('%Y')# Load a numpy record array from yahoo csv data with fields date, open, close,# volume, adj_close from the mpl-data/example directory. The record array# stores the date as an np.datetime64 with a day unit ('D') in the date column.with cbook.get_sample_data('goog.npz') as datafile: r = np.load(datafile)'price_data'.view(np.recarray)fig, ax = plt.subplots()ax.plot(r.date, r.adj_close)# format the ticksax.xaxis.set_major_locator(years)ax.xaxis.set_major_formatter(yearsFmt)ax.xaxis.set_minor_locator(months)# round to nearest years.datemin = np.datetime64(r.date0, 'Y')datemax = np.datetime64(r.date-1, 'Y') + np.timedelta64(1, 'Y')ax.set_xlim(datemin, datemax)# format the coords message boxdef price(x): return '$%1.2f' % xax.format_xdata = mdates.DateFormatter('%Y-%m-%d')ax.format_ydata = priceax.grid(True)# rotates and right aligns the x labels, and moves the bottom of the# axes up to make room for themfig.autofmt_xdate()plt.show()使用预定义标签的图例import numpy as npimport matplotlib.pyplot as plt# Make some fake data.a = b = np.arange(0, 3, .02)c = np.exp(a)d = c:-1# Create plots with pre-defined labels.fig, ax = plt.subplots()ax.plot(a, c, 'k-', label='Model length')ax.plot(a, d, 'k:', label='Data length')ax.plot(a, c + d, 'k', label='Total message length')legend = ax.legend(loc='upper center', shadow=True, fontsize='x-large')# Put a nicer background color on the legend.legend.get_frame().set_facecolor('#00FFCC')plt.show()数学公式编辑图from _future_ import print_functionimport matplotlib.pyplot as pltimport subprocessimport sysimport reimport gc# Selection of features following "Writing mathematical expressions" tutorialmathtext_titles = 0: "Header demo", 1: "Subscripts and superscripts", 2: "Fractions, binomials and stacked numbers", 3: "Radicals", 4: "Fonts", 5: "Accents", 6: "Greek, Hebrew", 7: "Delimiters, functions and Symbols"n_lines = len(mathtext_titles)# Randomly picked examplesmathext_demos = 0: r"$W3beta_delta_1 rho_1 sigma_2 = " r"U3beta_delta_1 rho_1 + frac18 pi 2 " r"intalpha_2_alpha_2 d alphaprime_2 leftfrac " r"U2beta_delta_1 rho_1 - alphaprime_2U1beta_" r"rho_1 sigma_2 U0beta_rho_1 sigma_2right$", 1: r"$alpha_i > beta_i, " r"alpha_i+1j = rm sin(2pi f_j t_i) e-5 t_i/tau, " r"ldots$", 2: r"$frac34, binom34, stackrel34, " r"left(frac5 - frac1x4right), ldots$", 3: r"$sqrt2, sqrt3x, ldots$", 4: r"$mathrmRoman , mathitItalic , mathttTypewriter " r"mathrmor mathcalCALLIGRAPHY$", 5: r"$acute a, bar a, breve a, dot a, ddot a, grave a, " r"hat a, tilde a, vec a, widehatxyz, widetildexyz, " r"ldots$", 6: r"$alpha, beta, chi, delta, lambda, mu, " r"Delta, Gamma, Omega, Phi, Pi, Upsilon, nabla, " r"aleph, beth, daleth, gimel, ldots$", 7: r"$coprod, int, oint, prod, sum, " r"log, sin, approx, oplus, star, varpropto, " r"infty, partial, Re, leftrightsquigarrow, ldots$"def doall(): # Colors used in mpl online documentation. mpl_blue_rvb = (191. / 255., 209. / 256., 212. / 255.) mpl_orange_rvb = (202. / 255., 121. / 256., 0. / 255.) mpl_grey_rvb = (51. / 255., 51. / 255., 51. / 255.) # Creating figure and axis. plt.figure(figsize=(6, 7) plt.axes(0.01, 0.01, 0.98, 0.90, facecolor="white", frameon=True) plt.gca().set_xlim(0., 1.) plt.gca().set_ylim(0., 1.) plt.gca().set_title("Matplotlib's math rendering engine", color=mpl_grey_rvb, fontsize=14, weight='bold') plt.gca().set_xticklabels("", visible=False) plt.gca().set_yticklabels("", visible=False) # Gap between lines in axes coords line_axesfrac = (1. / (n_lines) # Plotting header demonstration formula full_demo = mathext_demos0 plt.annotate(full_demo, xy=(0.5, 1. - 0.59 * line_axesfrac), xycoords='data', color=mpl_orange_rvb, ha='center', fontsize=20) # Plotting features demonstration formulae for i_line in range(1, n_lines): baseline = 1 - (i_line) * line_axesfrac baseline_next = baseline - line_axesfrac title = mathtext_titlesi_line + ":" fill_color = 'white', mpl_blue_rvbi_line % 2 plt.fill_between(0., 1., baseline, baseline, baseline_next, baseline_next, color=fill_color, alpha=0.5) plt.annotate(title, xy=(0.07, baseline - 0.3 * line_axesfrac), xycoords='data', color=mpl_grey_rvb, weight='bold') demo = mathext_demosi_line plt.annotate(demo, xy=(0.05, baseline - 0.75 * line_axesfrac), xycoords='data', color=mpl_grey_rvb, fontsize=16) for i in range(n_lines): s = mathext_demosi print(i, s) plt.show()if '-latex' in sys.argv: # Run: python mathtext_examples.py -latex # Need amsmath and amssymb packages. fd = open("mathtext_examples.ltx", "w") fd.write("documentclassarticlen") fd.write("usepackageamsmath, amssymbn") fd.write("begindocumentn") fd.write("beginenumeraten") for i in range(n_lines): s = mathext_demosi s = re.sub(r"(?<!)$", "$", s) fd.write("item %sn" % s) fd.write("endenumeraten") fd.write("enddocumentn") fd.close() subprocess.call("pdflatex", "mathtext_examples.ltx")else: doall()读取数学问题使用TEXfrom _future_ import unicode_literalsimport numpy as npimport matplotlibmatplotlib.rcParams'text.usetex' = Truematplotlib.rcParams'text.latex.unicode' = Trueimport matplotlib.pyplot as pltt = np.linspace(0.0, 1.0, 100)s = np.cos(4 * np.pi * t) + 2fig, ax = plt.subplots(figsize=(6, 4), tight_layout=True)ax.plot(t, s)ax.set_xlabel(r'textbftime (s)')ax.set_ylabel('textitVelocity (NDEGREE SIGN/sec)', fontsize=16)ax.set_title(r'TeX is Number $displaystylesum_n=1infty' r'frac-eipi2n$!', fontsize=16, color='r')plt.show()XKCD图import matplotlib.pyplot as pltimport numpy as npwith plt.xkcd(): # Based on "Stove Ownership" from XKCD by Randall Monroe fig = plt.figure() ax = fig.add_axes(0.1, 0.2, 0.8, 0.7) ax.spines'right'.set_color('none') ax.spines'top'.set_color('none') plt.xticks() plt.yticks() ax.set_ylim(-30, 10) data = np.ones(100) data70: -= np.arange(30) plt.annotate( 'THE DAY I REALIZEDnI COULD COOK BACONnWHENEVER I WANTED', xy=(70, 1), arrowprops=dict(arrowstyle='->'), xytext=(15, -10) plt.plot(data) plt.xlabel('time') plt.ylabel('my overall health') fig.text( 0.5, 0.05, '"Stove Ownership" from xkcd by Randall Monroe', ha='center')with plt.xkcd(): # Based on "The Data So Far" from XKCD by Randall Monroe fig = plt.figure() ax = fig.add_axes(0.1, 0.2, 0.8, 0.7) ax.bar(0, 1, 0, 100, 0.25) ax.spines'right'.set_color('none') ax.spines'top'.set_color('none') ax.xaxis.set_ticks_position('bottom') ax.set_xticks(0, 1) ax.set_xlim(-0.5, 1.5) ax.set_ylim(0, 110) ax.set_xticklabels('CONFIRMED BYnEXPERIMENT', 'REFUTED BYnEXPERIMENT') plt.yticks() plt.title("CLAIMS OF SUPERNATURAL POWERS") fig.text( 0.5, 0.05, '"The Data So Far" from xkcd by Randall Monroe', ha='center')plt.show()样本子图import matplotlib.pyplot as pltimport numpy as npnp.random.seed(19680801)data = np.random.randn(2, 100)fig, axs = plt.subplots(2, 2, figsize=(5, 5)axs0, 0.hist(data0)axs1, 0.scatter(data0, data1)axs0, 1.plot(data0, data1)axs1, 1.hist2d(data0, data1)plt.show()极图import numpy as npimport matplotlib.pyplot as pltr = np.arange(0, 2, 0.01)theta = 2 * np.pi * rax = plt.subplot(111, projection='polar')ax.plot(theta, r)ax.set_rmax(2)ax.set_rticks(0.5, 1, 1.5, 2) # Less radial ticksax.set_rlabel_position(-22.5) # Move radial labels away from plotted lineax.grid(True)ax.set_title("A line plot on a polar axis", va='bottom')plt.show()Log图import numpy as npimport matplotlib.pyplot as plt# Data for plottingt = np.arange(0.01, 20.0, 0.01)# Create figurefig, (ax1, ax2), (ax3, ax4) = plt.subplots(2, 2)# log y axisax1.semilogy(t, np.exp(-t / 5.0)ax1.set(title='semilogy')ax1.grid()# log x axisax2.semilogx(t, np.sin(2 * np.pi * t)ax2.set(title='semilogx')ax2.grid()# log x and y axisax3.loglog(t, 20 * np.exp(-t / 10.0), basex=2)ax3.set(title='loglog base 2 on x')ax3.grid()# With errorbars: clip non-positive values# Use new data for plottingx = 10.0*np.linspace(0.0, 2.0, 20)ax4.set_xscale("log", nonposx='clip')ax4.set_yscale("log", nonposy