本文整理汇总了Python中matplotlib.pyplot.clabel方法的典型用法代码示例。如果您正苦于以下问题：Python pyplot.clabel方法的具体用法？Python pyplot.clabel怎么用？Python pyplot.clabel使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在模块matplotlib.pyplot的用法示例。

在下文中一共展示了pyplot.clabel方法的18个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于我们的系统推荐出更棒的Python代码示例。

示例1: visualizeFit

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# 需要导入模块: from matplotlib import pyplot [as 别名]

# 或者: from matplotlib.pyplot import clabel [as 别名]

def visualizeFit(X,mu,sigma2):

x = np.arange(0, 36, 0.5) # 0-36，步长0.5

y = np.arange(0, 36, 0.5)

X1,X2 = np.meshgrid(x,y) # 要画等高线，所以meshgird

Z = multivariateGaussian(np.hstack((X1.reshape(-1,1),X2.reshape(-1,1))), mu, sigma2) # 计算对应的高斯分布函数

Z = Z.reshape(X1.shape) # 调整形状

plt.plot(X[:,0],X[:,1],'bx')

if np.sum(np.isinf(Z).astype(float)) == 0: # 如果计算的为无穷，就不用画了

#plt.contourf(X1,X2,Z,10.**np.arange(-20, 0, 3),linewidth=.5)

CS = plt.contour(X1,X2,Z,10.**np.arange(-20, 0, 3),color='black',linewidth=.5) # 画等高线，Z的值在10.**np.arange(-20, 0, 3)

#plt.clabel(CS)

plt.show()

# 选择最优的epsilon，即：使F1Score最大

开发者ID:lawlite19，项目名称:MachineLearning_Python，代码行数:18，

示例2: test_collection

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# 需要导入模块: from matplotlib import pyplot [as 别名]

# 或者: from matplotlib.pyplot import clabel [as 别名]

def test_collection():

x, y = np.meshgrid(np.linspace(0, 10, 150), np.linspace(-5, 5, 100))

data = np.sin(x) + np.cos(y)

cs = plt.contour(data)

pe = [path_effects.PathPatchEffect(edgecolor='black', facecolor='none',

linewidth=12),

path_effects.Stroke(linewidth=5)]

for collection in cs.collections:

collection.set_path_effects(pe)

for text in plt.clabel(cs, colors='white'):

text.set_path_effects([path_effects.withStroke(foreground='k',

linewidth=3)])

text.set_bbox({'boxstyle': 'sawtooth', 'facecolor': 'none',

'edgecolor': 'blue'})

开发者ID:miloharper，项目名称:neural-network-animation，代码行数:18，

示例3: test_labels

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# 需要导入模块: from matplotlib import pyplot [as 别名]

# 或者: from matplotlib.pyplot import clabel [as 别名]

def test_labels():

# Adapted from pylab_examples example code: contour_demo.py

# see issues #2475, #2843, and #2818 for explanation

delta = 0.025

x = np.arange(-3.0, 3.0, delta)

y = np.arange(-2.0, 2.0, delta)

X, Y = np.meshgrid(x, y)

Z1 = mlab.bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)

Z2 = mlab.bivariate_normal(X, Y, 1.5, 0.5, 1, 1)

# difference of Gaussians

Z = 10.0 * (Z2 - Z1)

fig, ax = plt.subplots(1, 1)

CS = ax.contour(X, Y, Z)

disp_units = [(216, 177), (359, 290), (521, 406)]

data_units = [(-2, .5), (0, -1.5), (2.8, 1)]

CS.clabel()

for x, y in data_units:

CS.add_label_near(x, y, inline=True, transform=None)

for x, y in disp_units:

CS.add_label_near(x, y, inline=True, transform=False)

开发者ID:miloharper，项目名称:neural-network-animation，代码行数:26，

示例4: Pcolor

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# 需要导入模块: from matplotlib import pyplot [as 别名]

# 或者: from matplotlib.pyplot import clabel [as 别名]

def Pcolor(xs, ys, zs, pcolor=True, contour=False, **options):

"""Makes a pseudocolor plot.

xs:

ys:

zs:

pcolor: boolean, whether to make a pseudocolor plot

contour: boolean, whether to make a contour plot

options: keyword args passed to plt.pcolor and/or plt.contour

"""

_Underride(options, linewidth=3, cmap=matplotlib.cm.Blues)

X, Y = np.meshgrid(xs, ys)

Z = zs

x_formatter = matplotlib.ticker.ScalarFormatter(useOffset=False)

axes = plt.gca()

axes.xaxis.set_major_formatter(x_formatter)

if pcolor:

plt.pcolormesh(X, Y, Z, **options)

if contour:

cs = plt.contour(X, Y, Z, **options)

plt.clabel(cs, inline=1, fontsize=10)

开发者ID:Notabela，项目名称:Lie_to_me，代码行数:27，

示例5: test_contour_badlevel_fmt

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# 需要导入模块: from matplotlib import pyplot [as 别名]

# 或者: from matplotlib.pyplot import clabel [as 别名]

def test_contour_badlevel_fmt():

# test funny edge case from

# https://github.com/matplotlib/matplotlib/issues/9742

# User supplied fmt for each level as a dictionary, but

# MPL changed the level to the minimum data value because

# no contours possible.

# This would error out pre

# https://github.com/matplotlib/matplotlib/pull/9743

x = np.arange(9)

z = np.zeros((9, 9))

fig, ax = plt.subplots()

fmt = {1.: '%1.2f'}

with pytest.warns(UserWarning) as record:

cs = ax.contour(x, x, z, levels=[1.])

ax.clabel(cs, fmt=fmt)

assert len(record) == 1

开发者ID:holzschu，项目名称:python3_ios，代码行数:19，

示例6: Pcolor

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# 需要导入模块: from matplotlib import pyplot [as 别名]

# 或者: from matplotlib.pyplot import clabel [as 别名]

def Pcolor(xs, ys, zs, pcolor=True, contour=False, **options):

"""Makes a pseudocolor plot.

xs:

ys:

zs:

pcolor: boolean, whether to make a pseudocolor plot

contour: boolean, whether to make a contour plot

options: keyword args passed to pyplot.pcolor and/or pyplot.contour

"""

_Underride(options, linewidth=3, cmap=matplotlib.cm.Blues)

X, Y = np.meshgrid(xs, ys)

Z = zs

x_formatter = matplotlib.ticker.ScalarFormatter(useOffset=False)

axes = pyplot.gca()

axes.xaxis.set_major_formatter(x_formatter)

if pcolor:

pyplot.pcolormesh(X, Y, Z, **options)

if contour:

cs = pyplot.contour(X, Y, Z, **options)

pyplot.clabel(cs, inline=1, fontsize=10)

开发者ID:AllenDowney，项目名称:DataExploration，代码行数:27，

示例7: DrawContourAndMark

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# 需要导入模块: from matplotlib import pyplot [as 别名]

# 或者: from matplotlib.pyplot import clabel [as 别名]

def DrawContourAndMark(contour, x, y, z, level, clipborder, patch, m):

# 是否绘制等值线 ------ 等值线和标注是一体的

if contour.contour['visible']:

matplotlib.rcParams['contour.negative_linestyle'] = 'dashed'

if contour.contour['colorline']:

CS1 = m.contour(x, y, z, levels=level, linewidths=contour.contour['linewidth'])

else:

CS1 = m.contour(x,

y,

z,

levels=level,

linewidths=contour.contour['linewidth'],

colors=contour.contour['linecolor'])

# 是否绘制等值线标注

CS2 = None

if contour.contourlabel['visible']:

CS2 = plt.clabel(CS1,

inline=1,

fmt=contour.contourlabel['fmt'],

inline_spacing=contour.contourlabel['inlinespacing'],

fontsize=contour.contourlabel['fontsize'],

colors=contour.contourlabel['fontcolor'])

# 用区域边界裁切等值线图

if clipborder.path is not None and clipborder.using:

for collection in CS1.collections:

# collection.set_clip_on(True)

collection.set_clip_path(patch)

if CS2 is not None:

for text in CS2:

if not clipborder.path.contains_point(text.get_position()):

text.remove()

开发者ID:flashlxy，项目名称:PyMICAPS，代码行数:39，

示例8: test_patheffect2

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# 需要导入模块: from matplotlib import pyplot [as 别名]

# 或者: from matplotlib.pyplot import clabel [as 别名]

def test_patheffect2():

ax2 = plt.subplot(111)

arr = np.arange(25).reshape((5, 5))

ax2.imshow(arr)

cntr = ax2.contour(arr, colors="k")

plt.setp(cntr.collections,

path_effects=[path_effects.withStroke(linewidth=3,

foreground="w")])

clbls = ax2.clabel(cntr, fmt="%2.0f", use_clabeltext=True)

plt.setp(clbls,

path_effects=[path_effects.withStroke(linewidth=3,

foreground="w")])

开发者ID:miloharper，项目名称:neural-network-animation，代码行数:17，

示例9: test_contour_manual_labels

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# 需要导入模块: from matplotlib import pyplot [as 别名]

# 或者: from matplotlib.pyplot import clabel [as 别名]

def test_contour_manual_labels():

x, y = np.meshgrid(np.arange(0, 10), np.arange(0, 10))

z = np.max(np.dstack([abs(x), abs(y)]), 2)

plt.figure(figsize=(6, 2))

cs = plt.contour(x, y, z)

pts = np.array([(1.5, 3.0), (1.5, 4.4), (1.5, 6.0)])

plt.clabel(cs, manual=pts)

开发者ID:miloharper，项目名称:neural-network-animation，代码行数:11，

示例10: Contour

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# 需要导入模块: from matplotlib import pyplot [as 别名]

# 或者: from matplotlib.pyplot import clabel [as 别名]

def Contour(obj, pcolor=False, contour=True, imshow=False, **options):

"""Makes a contour plot.

d: map from (x, y) to z, or object that provides GetDict

pcolor: boolean, whether to make a pseudocolor plot

contour: boolean, whether to make a contour plot

imshow: boolean, whether to use plt.imshow

options: keyword args passed to plt.pcolor and/or plt.contour

"""

try:

d = obj.GetDict()

except AttributeError:

d = obj

_Underride(options, linewidth=3, cmap=matplotlib.cm.Blues)

xs, ys = zip(*d.keys())

xs = sorted(set(xs))

ys = sorted(set(ys))

X, Y = np.meshgrid(xs, ys)

func = lambda x, y: d.get((x, y), 0)

func = np.vectorize(func)

Z = func(X, Y)

x_formatter = matplotlib.ticker.ScalarFormatter(useOffset=False)

axes = plt.gca()

axes.xaxis.set_major_formatter(x_formatter)

if pcolor:

plt.pcolormesh(X, Y, Z, **options)

if contour:

cs = plt.contour(X, Y, Z, **options)

plt.clabel(cs, inline=1, fontsize=10)

if imshow:

extent = xs[0], xs[-1], ys[0], ys[-1]

plt.imshow(Z, extent=extent, **options)

开发者ID:Notabela，项目名称:Lie_to_me，代码行数:39，

示例11: test_contour_manual_labels

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# 需要导入模块: from matplotlib import pyplot [as 别名]

# 或者: from matplotlib.pyplot import clabel [as 别名]

def test_contour_manual_labels():

x, y = np.meshgrid(np.arange(0, 10), np.arange(0, 10))

z = np.max(np.dstack([abs(x), abs(y)]), 2)

plt.figure(figsize=(6, 2), dpi=200)

cs = plt.contour(x, y, z)

pts = np.array([(1.5, 3.0), (1.5, 4.4), (1.5, 6.0)])

plt.clabel(cs, manual=pts)

开发者ID:holzschu，项目名称:python3_ios，代码行数:11，

示例12: test_contour_labels_size_color

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# 需要导入模块: from matplotlib import pyplot [as 别名]

# 或者: from matplotlib.pyplot import clabel [as 别名]

def test_contour_labels_size_color():

x, y = np.meshgrid(np.arange(0, 10), np.arange(0, 10))

z = np.max(np.dstack([abs(x), abs(y)]), 2)

plt.figure(figsize=(6, 2))

cs = plt.contour(x, y, z)

pts = np.array([(1.5, 3.0), (1.5, 4.4), (1.5, 6.0)])

plt.clabel(cs, manual=pts, fontsize='small', colors=('r', 'g'))

开发者ID:holzschu，项目名称:python3_ios，代码行数:11，

示例13: test_circular_contour_warning

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# 需要导入模块: from matplotlib import pyplot [as 别名]

# 或者: from matplotlib.pyplot import clabel [as 别名]

def test_circular_contour_warning():

# Check that almost circular contours don't throw a warning

with pytest.warns(None) as record:

x, y = np.meshgrid(np.linspace(-2, 2, 4), np.linspace(-2, 2, 4))

r = np.sqrt(x ** 2 + y ** 2)

plt.figure()

cs = plt.contour(x, y, r)

plt.clabel(cs)

assert len(record) == 0

开发者ID:holzschu，项目名称:python3_ios，代码行数:12，

示例14: visualize_function

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# 需要导入模块: from matplotlib import pyplot [as 别名]

# 或者: from matplotlib.pyplot import clabel [as 别名]

def visualize_function(self, func, show_3d=True, show_3d_inv=True,

show_contour=True, num_levels=15, rng_x=(-5, 5),

rng_y=(-5, 5)):

import matplotlib.pyplot as plt

if self._dim == 1:

xs = np.linspace(rng_x[0], rng_x[1], 100)

plt.plot(xs, np.apply_along_axis(func, 0, xs[np.newaxis, :]))

elif self._dim == 2:

freq = 50

x = np.linspace(rng_x[0], rng_x[1], freq)

y = np.linspace(rng_y[0], rng_y[1], freq)

Xs, Ys = np.meshgrid(x, y)

xs = np.reshape(Xs, -1)

ys = np.reshape(Ys, -1)

zs = np.apply_along_axis(func, 0, np.vstack((xs, ys)))

if show_3d:

fig = plt.figure(figsize=(10, 10))

ax = fig.gca(projection='3d')

ax.plot_trisurf(xs, ys, zs, linewidth=0.2, antialiased=True)

plt.show()

if show_3d_inv:

fig = plt.figure(figsize=(10, 10))

ax = fig.gca(projection='3d')

ax.invert_zaxis()

ax.plot_trisurf(xs, ys, zs, linewidth=0.2, antialiased=True)

plt.show()

if show_contour:

fig = plt.figure(figsize=(10, 10))

cs = plt.contour(Xs, Ys, zs.reshape(freq, freq), num_levels)

plt.clabel(cs, inline=1, fontsize=10)

plt.show()

else:

raise ValueError("Only dim=1 or dim=2 are supported")

开发者ID:NVIDIA，项目名称:Milano，代码行数:36，

示例15: visualize_distribution

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# 需要导入模块: from matplotlib import pyplot [as 别名]

# 或者: from matplotlib.pyplot import clabel [as 别名]

def visualize_distribution(log_densities, ax = None):

if ax is None:

ax = plt.gca()

t = normalize_log_density(log_densities)

img = ax.imshow(t, cmap=plt.cm.viridis)

levels = levels=[0, 0.25, 0.5, 0.75, 1.0]

cs = ax.contour(t, levels=levels, colors='black')

#plt.clabel(cs)

return img, cs

开发者ID:matthias-k，项目名称:pysaliency，代码行数:12，

示例16: plot_stability

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# 需要导入模块: from matplotlib import pyplot [as 别名]

# 或者: from matplotlib.pyplot import clabel [as 别名]

def plot_stability(lambda_s, lambda_f, num_nodes, K, stab):

"""

Plotting routine of the stability domains

Args:

lambda_s (numpy.ndarray): lambda_slow

lambda_f (numpy.ndarray): lambda_fast

num_nodes (int): number of collocation nodes

K (int): number of iterations

stab (numpy.ndarray): stability numbers

"""

lam_s_max = np.amax(lambda_s.imag)

lam_f_max = np.amax(lambda_f.imag)

rcParams['figure.figsize'] = 1.5, 1.5

fs = 8

fig = plt.figure()

levels = np.array([0.25, 0.5, 0.75, 0.9, 1.1])

CS1 = plt.contour(lambda_s.imag, lambda_f.imag, np.absolute(stab), levels, colors='k', linestyles='dashed')

CS2 = plt.contour(lambda_s.imag, lambda_f.imag, np.absolute(stab), [1.0], colors='k')

# Set markers at points used in plot_stab_vs_k

plt.plot(4, 10, 'x', color='k', markersize=fs - 4)

plt.plot(1, 10, 'x', color='k', markersize=fs - 4)

plt.clabel(CS1, inline=True, fmt='%3.2f', fontsize=fs - 2)

manual_locations = [(1.5, 2.5)]

if K > 0: # for K=0 and no 1.0 isoline, this crashes Matplotlib for somer reason

plt.clabel(CS2, inline=True, fmt='%3.2f', fontsize=fs - 2, manual=manual_locations)

plt.gca().add_patch(Polygon([[0, 0], [lam_s_max, 0], [lam_s_max, lam_s_max]], visible=True, fill=True,

facecolor='.75', edgecolor='k', linewidth=1.0, zorder=11))

plt.gca().set_xticks(np.arange(0, int(lam_s_max) + 1))

plt.gca().set_yticks(np.arange(0, int(lam_f_max) + 2, 2))

plt.gca().tick_params(axis='both', which='both', labelsize=fs)

plt.xlim([0.0, lam_s_max])

plt.ylim([0.0, lam_f_max])

plt.xlabel('$\Delta t \lambda_{slow}$', fontsize=fs, labelpad=0.0)

plt.ylabel('$\Delta t \lambda_{fast}$', fontsize=fs, labelpad=0.0)

plt.title(r'$M=%1i$, $K=%1i$' % (num_nodes, K), fontsize=fs)

filename = 'data/stability-K' + str(K) + '-M' + str(num_nodes) + '.png'

fig.savefig(filename, bbox_inches='tight')

开发者ID:Parallel-in-Time，项目名称:pySDC，代码行数:42，

示例17: make_plot

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# 需要导入模块: from matplotlib import pyplot [as 别名]

# 或者: from matplotlib.pyplot import clabel [as 别名]

def make_plot(m, time, verif, forecast, fill=None, file_name=None):

fig = plt.figure()

fig.set_size_inches(9, 6)

gs1 = gs.GridSpec(2, 1)

gs1.update(wspace=0.04, hspace=0.04)

plot_fn = getattr(m, plot_type)

contours = np.arange(np.min(contour_range), np.max(contour_range), contour_step)

if fill is None:

fill = [None] * 2

def plot_panel(n, da, title, filler):

ax = plt.subplot(gs1[n])

lons, lats = np.meshgrid(da.lon, da.lat)

x, y = m(lons, lats)

m.drawcoastlines(color=(0.7, 0.7, 0.7))

m.drawparallels(np.arange(0., 91., 30.), color=(0.5, 0.5, 0.5))

m.drawmeridians(np.arange(0., 361., 60.), color=(0.5, 0.5, 0.5))

if filler is not None:

m.pcolormesh(x, y, filler.values, vmin=np.min(laplace_range), vmax=np.max(laplace_range),

cmap=laplace_colormap)

cs = plot_fn(x, y, da.values, contours, cmap=plot_colormap)

plt.clabel(cs, fmt='%1.0f')

ax.text(0.01, 0.01, title, horizontalalignment='left', verticalalignment='bottom', transform=ax.transAxes)

plot_panel(0, verif, 'Observed (%s)' % datetime.strftime(time, '%HZ %e %b %Y'), fill[0])

plot_panel(1, forecast, 'DLWP (%s)' % datetime.strftime(time, '%HZ %e %b %Y'), fill[1])

if file_name is not None:

plt.savefig(file_name, bbox_inches='tight', dpi=200)

plt.close()

开发者ID:jweyn，项目名称:DLWP，代码行数:34，

示例18: plot_contour_trajectory

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# 需要导入模块: from matplotlib import pyplot [as 别名]

# 或者: from matplotlib.pyplot import clabel [as 别名]

def plot_contour_trajectory(surf_file, dir_file, proj_file, surf_name='loss_vals',

vmin=0.1, vmax=10, vlevel=0.5, show=False):

"""2D contour + trajectory"""

assert exists(surf_file) and exists(proj_file) and exists(dir_file)

# plot contours

f = h5py.File(surf_file,'r')

x = np.array(f['xcoordinates'][:])

y = np.array(f['ycoordinates'][:])

X, Y = np.meshgrid(x, y)

if surf_name in f.keys():

Z = np.array(f[surf_name][:])

fig = plt.figure()

CS1 = plt.contour(X, Y, Z, levels=np.arange(vmin, vmax, vlevel))

CS2 = plt.contour(X, Y, Z, levels=np.logspace(1, 8, num=8))

# plot trajectories

pf = h5py.File(proj_file, 'r')

plt.plot(pf['proj_xcoord'], pf['proj_ycoord'], marker='.')

# plot red points when learning rate decays

# for e in [150, 225, 275]:

# plt.plot([pf['proj_xcoord'][e]], [pf['proj_ycoord'][e]], marker='.', color='r')

# add PCA notes

df = h5py.File(dir_file,'r')

ratio_x = df['explained_variance_ratio_'][0]

ratio_y = df['explained_variance_ratio_'][1]

plt.xlabel('1st PC: %.2f %%' % (ratio_x*100), fontsize='xx-large')

plt.ylabel('2nd PC: %.2f %%' % (ratio_y*100), fontsize='xx-large')

df.close()

plt.clabel(CS1, inline=1, fontsize=6)

plt.clabel(CS2, inline=1, fontsize=6)

fig.savefig(proj_file + '_' + surf_name + '_2dcontour_proj.pdf', dpi=300,

bbox_inches='tight', format='pdf')

pf.close()

if show: plt.show()

开发者ID:tomgoldstein，项目名称:loss-landscape，代码行数:41，

注：本文中的matplotlib.pyplot.clabel方法示例整理自Github/MSDocs等源码及文档管理平台，相关代码片段筛选自各路编程大神贡献的开源项目，源码版权归原作者所有，传播和使用请参考对应项目的License；未经允许，请勿转载。