企业网站大全,江苏国龙翔建设公司网站,一个网站怎么赚钱,网站建设竞标书目录线状堆积图 PolygonPlot三维表面图 SurfacePlot散点图ScatterPlot柱形图 BarPlot三维直方图螺旋曲线图 LinePlotContourPlot轮廓图网状图 WireframePlot箭头图二维三维合并文本图Text三维多个子图线状堆积图 PolygonPlot
Axes3D.add_collection3d(col, zs0, zdir‘z’) …
目录线状堆积图 PolygonPlot三维表面图 SurfacePlot散点图ScatterPlot柱形图 BarPlot三维直方图螺旋曲线图 LinePlotContourPlot轮廓图网状图 WireframePlot箭头图二维三维合并文本图Text三维多个子图线状堆积图 PolygonPlot
Axes3D.add_collection3d(col, zs0, zdir‘z’) 这个函数可以将三维 collection对象或二维collection对象加入到一个图形中包括
PolyCollectionLineCollectionPatchCollection
import pandas as pd
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.collections import PolyCollection
import matplotlib.pyplot as plt
from matplotlib import colors as mcolors
import numpy as np
plt.rcParams[font.family] Microsoft YaHei # 字体设置
plt.rcParams[font.size] 10 # 字体大小设置fig plt.figure(figsize(30,20))
ax fig.gca(projection3d)def cc(arg):return mcolors.to_rgba(arg, alpha0.6)
def polygon_under_graph(xlist, ylist):Construct the vertex list which defines the polygon filling the space underthe (xlist, ylist) line graph. Assumes the xs are in ascending order.return [(xlist[0], 0.), *zip(xlist, ylist), (xlist[-1], 0.)]xs np.arange(0,137,1)verts []zs [0.0,1.0,2.0, 3.0,4.0]
for z in zs:for i in range(1,6): #读取数据ys df.iloc[:,i]verts.append(polygon_under_graph(xs,ys))poly PolyCollection(verts, facecolors[cc(r), cc(g), cc(b),cc(y),cc(r)])
poly.set_alpha(0.7) # 图形的透明度
ax.add_collection3d(poly, zszs, zdiry)names_1 [2022-10-18, 2022-10-19, 2022-10-20,2022-10-21,
2022-10-22, 2022-10-23]
plt.xticks(xs[::24], names_1)names [北京, 石家庄, 保定,唐山,廊坊]
plt.yticks(zs, names)ax.set_xlabel(时间)
ax.set_ylabel(城市)
ax.set_zlabel(AQI)
ax.set_xlim3d(0, 136)
ax.set_ylim3d(-1, 5)
ax.set_zlim3d(0, 130)
#plt.savefig(三维时间.png,bbox_inches tight,dpi500)
plt.show()三维表面图 SurfacePlot
Axes3D.plot_surface(X, Y, Z, *args, normNone, vminNone, vmaxNone, lightsourceNone, **kwargs)
这个函数算是比较常用的函数用于绘制三维表面图让人惊艳的是它的着色效果。
ArgumentDescriptionX, YZ坐标点rcount,ccount,rstride,cstride同上color定义surface patch的颜色,type:color-likecmap定义surface patch的颜色只不过是colorMap,type:colormapfacecolors指定单个patch的颜色, type:array-like of colorsnormcolormap的normalization type:Normalizeshade阴影效果type:booleanvmin, vmaxnormalization的边界**kwargs向下传递到Poly3DCollectionantialiased抗锯齿type:boolean
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from matplotlib import cmfrom matplotlib.ticker import LinearLocator, FormatStrFormatter
import numpy as npfig plt.figure(figsize(30,10))
ax fig.gca(projection3d)# Make data.
X np.arange(-5, 5, 0.25)
Y np.arange(-5, 5, 0.25)
X, Y np.meshgrid(X, Y)
R np.sqrt(X**2 Y**2)
Z np.sin(R)# Plot the surface.
surf ax.plot_surface(X, Y, Z, cmapcm.coolwarm,linewidth0, antialiasedFalse)# Customize the z axis.
ax.set_zlim(-1.01, 1.01)
ax.zaxis.set_major_locator(LinearLocator(10))
ax.zaxis.set_major_formatter(FormatStrFormatter(%.02f))# Add a color bar which maps values to colors.
fig.colorbar(surf, shrink0.5, aspect5)plt.show()散点图ScatterPlot
Axes3D.scatter(xs, ys, zs0, zdir‘z’, s20, cNone, depthshadeTrue, *args, **kwargs)
返回Patch3DCollection,
其他参数向下传递给plot函数
ArgumentDescriptionxs, ysx,y坐标点zsz 坐标可以是一个标量或一个x*y维矩阵默认是0.zdir当绘制二维图像时的z轴方向ssize,即散点大小c颜色映射其取值可以是非常多类型有时间专门写一篇讲解depthshade是否渲染景深或则就说阴影吧默认是True.
from mpl_toolkits.mplot3d import Axes3Dimport matplotlib.pyplot as plt
import numpy as np# Fixing random state for reproducibility
np.random.seed(19680801)def randrange(n, vmin, vmax):Helper function to make an array of random numbers having shape (n, )with each number distributed Uniform(vmin, vmax).return (vmax - vmin)*np.random.rand(n) vminfig plt.figure(figsize(20,10))
ax fig.add_subplot(111, projection3d)n 100# For each set of style and range settings, plot n random points in the box
# defined by x in [23, 32], y in [0, 100], z in [zlow, zhigh].
for c, m, zlow, zhigh in [(r, o, -50, -25), (b, ^, -30, -5)]:xs randrange(n, 23, 32)ys randrange(n, 0, 100)zs randrange(n, zlow, zhigh)ax.scatter(xs, ys, zs, cc, markerm)ax.set_xlabel(X Label)
ax.set_ylabel(Y Label)
ax.set_zlabel(Z Label)plt.show()柱形图 BarPlot
Axes3D.bar(left, height, zs0, zdir‘z’, *args, **kwargs)
其他参数向下传递给bar函数返回Patch3DCollection对象
ArgumentDescriptionleft条形图水平坐标height条形的高度zsZ方向zdir同上
from mpl_toolkits.mplot3d import Axes3D # noqa: F401 unused importimport matplotlib.pyplot as plt
import numpy as np# Fixing random state for reproducibility
np.random.seed(19680801)fig plt.figure(figsize(10,20))
ax fig.add_subplot(111, projection3d)colors [r, g, b, y]
yticks [3, 2, 1, 0]
for c, k in zip(colors, yticks):# Generate the random data for the yk layer.xs np.arange(20)ys np.random.rand(20)# You can provide either a single color or an array with the same length as# xs and ys. To demonstrate this, we color the first bar of each set cyan.cs [c] * len(xs)# Plot the bar graph given by xs and ys on the plane yk with 80% opacity.ax.bar(xs, ys, zsk, zdiry, colorcs, alpha0.8)ax.set_xlabel(X)
ax.set_ylabel(Y)
ax.set_zlabel(Z)# On the y axis lets only label the discrete values that we have data for.
ax.set_yticks(yticks)plt.show() 三维直方图
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as npfig plt.figure()
ax fig.add_subplot(111, projection3d)
x, y np.random.rand(2, 100) * 4
hist, xedges, yedges np.histogram2d(x, y, bins4, range[[0, 4], [0, 4]])# Construct arrays for the anchor positions of the 16 bars.
# Note: np.meshgrid gives arrays in (ny, nx) so we use F to flatten xpos,
# ypos in column-major order. For numpy 1.7, we could instead call meshgrid
# with indexingij.
xpos, ypos np.meshgrid(xedges[:-1] 0.25, yedges[:-1] 0.25)
xpos xpos.flatten(F)
ypos ypos.flatten(F)
zpos np.zeros_like(xpos)# Construct arrays with the dimensions for the 16 bars.
dx 0.5 * np.ones_like(zpos)
dy dx.copy()
dz hist.flatten()ax.bar3d(xpos, ypos, zpos, dx, dy, dz, colorb, zsortaverage)plt.show()螺旋曲线图 LinePlot
Axes3D.plot(xs, ys, *args, zdir‘z’, **kwargs)
其他参数向下传递给plot函数
ArgumentDescriptionxs, ysx、y 坐标zsz 坐标可以是一个标量或一个x*y维矩阵zdir当绘制二维图像时的z轴方向
from mpl_toolkits.mplot3d import Axes3Dimport numpy as np
import matplotlib.pyplot as pltplt.rcParams[legend.fontsize] 10
fig plt.figure(figsize(10,20))
ax fig.gca(projection3d) # get current axes# Prepare arrays x, y, z
theta np.linspace(-4 * np.pi, 4 * np.pi, 100)
z np.linspace(-2, 2, 100)
r z**2 1
x r * np.sin(theta)
y r * np.cos(theta)ax.plot(x, y, z, labelparametric curve)
ax.legend() plt.show()ContourPlot
Axes3D.contour(X, Y, Z, *args, extend3dFalse, stride5, zdir‘z’, offsetNone, **kwargs)
ArgumentDescriptionX, Y,ZData values as numpy.arraysextend3d是否延申到3d空间 (default: False)*strideextend3d的采样步长zdir同上offset绘制轮廓线在zdir垂直的水平面上的投影
from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
from matplotlib import cmfig plt.figure(figsize(30,10))
ax fig.gca(projection3d)
X, Y, Z axes3d.get_test_data(0.05)# Plot contour curves
cset ax.contour(X, Y, Z, cmapcm.coolwarm)ax.clabel(cset, fontsize9, inline1) # function to label a contourplt.show() 轮廓图 from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
from matplotlib import cmfig plt.figure()
ax fig.gca(projection3d)
X, Y, Z axes3d.get_test_data(0.05)
cset ax.contour(X, Y, Z, zdirz, offset-100, cmapcm.coolwarm)
cset ax.contour(X, Y, Z, zdirx, offset-40, cmapcm.coolwarm)
cset ax.contour(X, Y, Z, zdiry, offset40, cmapcm.coolwarm)ax.set_xlabel(X)
ax.set_xlim(-40, 40)
ax.set_ylabel(Y)
ax.set_ylim(-40, 40)
ax.set_zlabel(Z)
ax.set_zlim(-100, 100)plt.show()网状图 WireframePlot
Axes3D.plot_wireframe(X, Y, Z, *args, **kwargs)
ArgumentDescriptionX, Y,Z坐标点rcount,ccount采样数越大采样越多默认50rstride,cstride采样步长越小采样越多**kwargs其他参数向下传入Line3DCollection
from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as pltfig plt.figure(figsize(30,10))
ax fig.add_subplot(111, projection3d)# Grab some test data.
X, Y, Z axes3d.get_test_data(0.05)# Plot a basic wireframe.
ax.plot_wireframe(X, Y, Z, rstride10, cstride10)plt.show()箭头图
Axes3D.quiver(*args, **kwargs)
ArgumentDescriptionX, Y, ZThe x, y and z coordinates of the arrow locations (default is tail of arrow; see pivot kwarg)U, V, WThe x, y and z components of the arrow vectors
from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
import numpy as npfig plt.figure()
ax fig.gca(projection3d)# Make the grid
x, y, z np.meshgrid(np.arange(-0.8, 1, 0.2),np.arange(-0.8, 1, 0.2),np.arange(-0.8, 1, 0.8))# Make the direction data for the arrows
u np.sin(np.pi * x) * np.cos(np.pi * y) * np.cos(np.pi * z)
v -np.cos(np.pi * x) * np.sin(np.pi * y) * np.cos(np.pi * z)
w (np.sqrt(2.0 / 3.0) * np.cos(np.pi * x) * np.cos(np.pi * y) *np.sin(np.pi * z))ax.quiver(x, y, z, u, v, w, length0.1, normalizeTrue)plt.show()二维三维合并
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
import matplotlib.pyplot as pltfig plt.figure()
ax fig.gca(projection3d)# Plot a sin curve using the x and y axes.
x np.linspace(0, 1, 100)
y np.sin(x * 2 * np.pi) / 2 0.5
ax.plot(x, y, zs0, zdirz, labelcurve in (x,y))# Plot scatterplot data (20 2D points per colour) on the x and z axes.
colors (r, g, b, k)
x np.random.sample(20 * len(colors))
y np.random.sample(20 * len(colors))
labels np.random.randint(3, size80)# By using zdiry, the y value of these points is fixed to the zs value 0
# and the (x,y) points are plotted on the x and z axes.
ax.scatter(x, y, zs0, zdiry, clabels, labelpoints in (x,z))# Make legend, set axes limits and labels
ax.legend()
ax.set_xlim(0, 1)
ax.set_ylim(0, 1)
ax.set_zlim(0, 1)
ax.set_xlabel(X)
ax.set_ylabel(Y)
ax.set_zlabel(Z)# Customize the view angle so its easier to see that the scatter points lie
# on the plane y0
ax.view_init(elev20., azim-35)plt.show() 文本图Text
Axes3D.text(x, y, z, s, zdirNone, **kwargs)
text的内容其实也很繁杂需要用一篇内容去探讨在三维中很重要的一点是要学会二维、三维文字的添加。
from mpl_toolkits.mplot3d import Axes3D # noqa: F401 unused importimport matplotlib.pyplot as pltfig plt.figure()
ax fig.gca(projection3d)# Demo 1: zdir
zdirs (None, x, y, z, (1, 1, 0), (1, 1, 1))
xs (1, 4, 4, 9, 4, 1)
ys (2, 5, 8, 10, 1, 2)
zs (10, 3, 8, 9, 1, 8)for zdir, x, y, z in zip(zdirs, xs, ys, zs):label (%d, %d, %d), dir%s % (x, y, z, zdir)ax.text(x, y, z, label, zdir)# Demo 2: color
ax.text(9, 0, 0, red, colorred)# Demo 3: text2D
# Placement 0, 0 would be the bottom left, 1, 1 would be the top right.
ax.text2D(0.05, 0.95, 2D Text, transformax.transAxes)# Tweaking display region and labels
ax.set_xlim(0, 10)
ax.set_ylim(0, 10)
ax.set_zlim(0, 10)
ax.set_xlabel(X axis)
ax.set_ylabel(Y axis)
ax.set_zlabel(Z axis)plt.show() 三维多个子图
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d.axes3d import Axes3D, get_test_data
from matplotlib import cm
import numpy as np# set up a figure twice as wide as it is tall
# fig plt.figure(figsizeplt.figaspect(0.5))
fig plt.figure(figsize(20,10))#
# First subplot
#
# set up the axes for the first plot
ax fig.add_subplot(1, 2, 1, projection3d)# plot a 3D surface like in the example mplot3d/surface3d_demo
X np.arange(-5, 5, 0.25)
Y np.arange(-5, 5, 0.25)
X, Y np.meshgrid(X, Y)
R np.sqrt(X ** 2 Y ** 2)
Z np.sin(R)
surf ax.plot_surface(X, Y, Z, rstride1, cstride1, cmapcm.coolwarm,linewidth0, antialiasedFalse)
ax.set_zlim(-1.01, 1.01)
fig.colorbar(surf, shrink0.5, aspect10)#
# Second subplot
#
# set up the axes for the second plot
ax fig.add_subplot(1, 2, 2, projection3d)# plot a 3D wireframe like in the example mplot3d/wire3d_demo
X, Y, Z get_test_data(0.05)
ax.plot_wireframe(X, Y, Z, rstride10, cstride10)plt.show()
