image_thumbnail_sgskip
图像缩略图您可以使用matplotlib从现有图像生成缩略图。matplotlib本身支持输入端的PNG文件，如果安装了PIL，则透明地支持其他图像类型。 123456789101112131415161718192021222324# build thumbnails of all images in a directoryimport sysimport osimport globimport matplotlib.image as imageif len(sys.argv) != 2: print('Usage: python %s IMAGEDIR' % __file__) raise SystemExitindir = sys.argv[1]if not os.path.isdir(indir): print('Could not find input directory "%s"' % indir) raise SystemExitoutdir = 'thumbs'...
keyword_plotting
用关键字绘图在某些情况下，您可以使用允许您使用字符串访问特定变量的格式的数据。 例如，使用 numpy.recarray 或pandas.DataFrame。 Matplotlib允许您使用data关键字参数提供此类对象。如果提供，则可以生成具有与这些变量对应的字符串的图。 1234567891011121314import numpy as npimport matplotlib.pyplot as pltnp.random.seed(19680801)data = {'a': np.arange(50), 'c': np.random.randint(0, 50, 50), 'd': np.random.randn(50)}data['b'] = data['a'] + 10 * np.random.randn(50)data['d'] = np.abs(data['d']) * 100f...
load_converter
负载转换器 输出： 1loading /home/tcaswell/mc3/envs/dd37/lib/python3.7/site-packages/matplotlib/mpl-data/sample_data/msft.csv 12345678910111213141516import numpy as npimport matplotlib.pyplot as pltimport matplotlib.cbook as cbookfrom matplotlib.dates import bytespdate2numdatafile = cbook.get_sample_data('msft.csv', asfileobj=False)print('loading', datafile)dates, closes = np.loadtxt(datafile, delimiter=',', converters={0: bytespdate2num(&#...
logos2
Matplotlib标志显示一些matplotlib徽标。 感谢Tony Yu tsyu80@gmail.com的标志设计 1234567891011121314151617181920212223242526272829303132333435363738394041424344454647484950515253545556575859606162636465666768697071727374757677import numpy as npimport matplotlib as mplimport matplotlib.pyplot as pltimport matplotlib.cm as cmmpl.rcParams['xtick.labelsize'] = 10mpl.rcParams['ytick.labelsize'] = 12mpl.rcParams['axes.edgecolor'] = 'gray'axalpha = 0.05figcolor = 'white&#x...
multiprocess_sgskip
多进程演示使用多处理在一个过程中生成数据并在另一个过程中绘图。 由Robert Cimrman撰写 12345678import multiprocessing as mpimport timeimport matplotlib.pyplot as pltimport numpy as np# Fixing random state for reproducibilitynp.random.seed(19680801) 进程类此类绘制从管道接收的数据。 1234567891011121314151617181920212223242526272829303132class ProcessPlotter(object): def __init__(self): self.x = [] self.y = [] def terminate(self): plt.close('all') def call_back(self): while self.pipe.poll(): ...
multipage_pdf
多页PDF这是一个创建包含多个页面的pdf文件，以及向pdf文件添加元数据和注释的演示。 如果要使用LaTeX使用多页pdf文件，则需要使用 matplotlib.backends.backend_pgf 导入PdfPages。 但是这个版本不支持 attach_note。 1234567891011121314151617181920212223242526272829303132333435363738394041import datetimeimport numpy as npfrom matplotlib.backends.backend_pdf import PdfPagesimport matplotlib.pyplot as plt# Create the PdfPages object to which we will save the pages:# The with statement makes sure that the PdfPages object is closed properly at# the end of the block, even if...
patheffect_demo
修补效果演示 1234567891011121314151617181920212223242526272829303132333435363738394041import matplotlib.pyplot as pltimport matplotlib.patheffects as PathEffectsimport numpy as npif 1: plt.figure(1, figsize=(8, 3)) ax1 = plt.subplot(131) ax1.imshow([[1, 2], [2, 3]]) txt = ax1.annotate("test", (1., 1.), (0., 0), arrowprops=dict(arrowstyle="->", connectionstyle="angle3", lw=2), ...
plotfile_demo
Plotfile演示使用plotfile直接从文件绘制数据的示例。 12345678910111213141516171819202122232425262728293031323334353637import matplotlib.pyplot as pltimport matplotlib.cbook as cbookfname = cbook.get_sample_data('msft.csv', asfileobj=False)fname2 = cbook.get_sample_data('data_x_x2_x3.csv', asfileobj=False)# test 1; use intsplt.plotfile(fname, (0, 5, 6))# test 2; use namesplt.plotfile(fname, ('date', 'volume', 'adj_close'))# test 3; use semilogy for volumeplt.plot...
print_stdout_sgskip
打印标准输出将PNG打印到标准输出。 用法：python print_stdout.py > somefile.png 1234567import sysimport matplotlibmatplotlib.use('Agg')import matplotlib.pyplot as pltplt.plot([1, 2, 3])plt.savefig(sys.stdout.buffer) 下载这个示例 下载python源码: print_stdout_sgskip.py 下载Jupyter notebook: print_stdout_sgskip.ipynb
rasterization_demo
光栅化演示 1234567891011121314151617181920212223242526272829303132333435363738394041424344454647484950import numpy as npimport matplotlib.pyplot as pltd = np.arange(100).reshape(10, 10)x, y = np.meshgrid(np.arange(11), np.arange(11))theta = 0.25*np.pixx = x*np.cos(theta) - y*np.sin(theta)yy = x*np.sin(theta) + y*np.cos(theta)fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2)ax1.set_aspect(1)ax1.pcolormesh(xx, yy, d)ax1.set_title("No Rasterization")ax2.set_aspect(1)ax2.set_title("Ras...
