Python Axes3D.plot_surface方法代码示例

# 需要导入模块: from mpl_toolkits.mplot3d import Axes3D [as 别名]
# 或者: from mpl_toolkits.mplot3d.Axes3D import plot_surface [as 别名]
    def draw(self, axes: Axes3D):
        R = (self.orientation * (self.orientation_origin.get_inverse())).to_rot_matrix()

        xx = R[0, 0] * self.x + R[0, 1] * self.y + R[0, 2] * self.z
        yy = R[1, 0] * self.x + R[1, 1] * self.y + R[1, 2] * self.z
        zz = R[2, 0] * self.x + R[2, 1] * self.y + R[2, 2] * self.z

        axes.plot_surface(xx, yy, zz, rstride=4, cstride=4, color='b')
        return axes,

# 需要导入模块: from mpl_toolkits.mplot3d import Axes3D [as 别名]
# 或者: from mpl_toolkits.mplot3d.Axes3D import plot_surface [as 别名]
    def water(self, *argv):  # Dimension is unit type as V(olt) W(att), etc
#        http://matplotlib.org/examples/mplot3d/polys3d_demo.html
        Axes3D.plot_surface(self.signalx, self.signaly, self.signalz)  # till better funcion
        plt.xlabel('time [s]')  # Or Sample number
        plt.ylabel('Frequency [Hz]')  # Or Freq Bins number
        plt.zlabel('voltage [mV]')  # auto add unit here
        plt.title(' ')  # set title
        plt.grid(True)
        plt.show()

# 需要导入模块: from mpl_toolkits.mplot3d import Axes3D [as 别名]
# 或者: from mpl_toolkits.mplot3d.Axes3D import plot_surface [as 别名]
 def Spect(self):  #, dimension):  # Dimension is unit type as V(olt) W(att), etc
     Axes3D.plot_surface(self.signalx, self.signaly, self.signalz)
     if self.signalx.shape == self.signaly.shape == self.signalz.shape:
         pass
     elif self.signalx.shape == (len(self.signalx), ) or self.signaly.shape == (len(self.signaly), ):
     # Check for 1D array both
         if self.signalx.shape == (len(self.signalx), ) and self.signaly.shape == (len(self.signaly), ):
             self.signalx, self.signaly = np.meshgrid(self.signalx, self.signaly)
             nx, mx = np.shape(self.signalx)
             nz, mz = np.shape(self.signalz)
             if nx == nz and mx == mz:
                 pass
             elif nx == mz and mx == nz:
                 self.signalz = np.rot90(self.signalz, 1) 
                 # find out if it has to be 1 or 3
         elif self.signalx.shape == (len(self.signalx), ):
             pass
         elif self.signaly.shape == (len(self.signaly), ):
             pass
         if self.signalx.shape == self.signaly.shape != self.signalz.shape:
             nx, mx = np.shape(self.signalx)
             nz, mz = np.shape(self.signalz)
             if nx == nz and mx == mz:
                 pass
             elif nx == mz and mx == nz:
                 self.signalz = np.rot90(self.signalz, 1) 
                 # find out if it has to be 1 or 3
         elif self.signalx.shape == self.signalz.shape != self.signaly.shape:
             nx, mx = np.shape(self.signalx)
             ny, my = np.shape(self.signalz)
             if nx == ny and mx == my:
                 pass
             elif nx == my and mx == ny:
                 self.signaly = np.rot90(self.signaly, 1) 
                 # find out if it has to be 1 or 3
     elif self.signaly.shape == self.signalz.shape != self.signalx.shape:
         ny, my = np.shape(self.signaly)
         nx, mx = np.shape(self.signalx)
         if ny == nx and my == mx:
             pass
         elif ny == mx and my == nx:
             self.signalz = np.rot90(self.signalz, 1) 
             # find out if it has to be 1 or 3
     else:
         raise MeasError.DataError("No Valid data found in at least one of the axis")
     
     plt.xlabel('time [s]')  # Or Sample number
     plt.ylabel('Frequency [Hz]')  # Or Freq Bins number
     plt.zlabel('voltage [mV]')  # auto add unit here
     plt.title(' ')  # set title
     plt.grid(True)
     plt.show()

# 需要导入模块: from mpl_toolkits.mplot3d import Axes3D [as 别名]
# 或者: from mpl_toolkits.mplot3d.Axes3D import plot_surface [as 别名]
    def updatePlot(self, X, Y, Z, population=None):
        self.activePlot = (X,Y,Z)
        x, y = np.meshgrid(X,Y)

        if self.surface is not None:
            self.surface.remove()

        if self.scatter is not None:
            self.scatter.remove()

        # surface
        self.surface = Axes3D.plot_surface(
                self.axes,
                x, y, Z,
                rstride=1,
                cstride=1,
                cmap=cm.coolwarm,
                linewidth=0,
                antialiased=False,
                shade=False,
                alpha=0.5
        )

        # population
        if population is not None:
            self.activePopulation = population
            x, y, z = self.preparePopulationData(population)
            self.scatter = Axes3D.scatter(self.axes, x, y, z, c="r", marker="o")
            self.scatter.set_alpha(1.0)

        # Draw all
        self.canvas.draw()
        self.canvas.flush_events()

# 需要导入模块: from mpl_toolkits.mplot3d import Axes3D [as 别名]
# 或者: from mpl_toolkits.mplot3d.Axes3D import plot_surface [as 别名]
# -*- coding: utf-8 -*-
"""
Created on Sun Nov 22 20:56:55 2015

@author: jderoo
"""

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

#D is a vector from 0 to 3, 100 spaces in between
D = np.linspace(0,3,100)
#U is a vector from 0 to 3, 100 spaces in between
U = np.linspace(0,3,100)
#A is a blank matrix/list
A = []

#for loop that ranges i from 0 to 100 steps of 1
for i in range(0,100,1):
    #for loop that ranges j from 0 to 100 steps of 1
    for j in range(0,100,1):
#The base equation we were given in the homework
      r = ((3*D[i]*(U[j])^.7)/(1 + D[i]^.95 + U[j])^.3)
 #in cell location i,j place the calced value of r     
      A[i,j] = r
#3D plot D, U, and the now filled matrix A
Axes3D.plot_surface(D,U,A)

# 需要导入模块: from mpl_toolkits.mplot3d import Axes3D [as 别名]
# 或者: from mpl_toolkits.mplot3d.Axes3D import plot_surface [as 别名]

#.........这里部分代码省略.........
    # -------------------------------------------------
    if (Nd_step>=1 and Ng_step==0):
        figure(1)
        plot(Vd_bias, Ie[0,:], 'o-')
        grid(True)
        xlabel('$V_{DS}$ [V]')
        ylabel('$I_{DS} [\mu A/\mu m]$')
        title('$I_{DS}$ vs. $V_{DS}$')
        savefig('ID_VD.png')

        #temmm = [Vd_bias, Ie[0,:]]
        #np.savetxt('ID_VD.dat', temmm, fmt='%e', delimiter=';')
        temmm = Vd_bias
        Ie2 = Ie.transpose()
        fid = open('ID_{VD}.dat','w')
        ind = 0
        for item1 in temmm:
            fid.write("%e " % item1)
            for item2 in Ie2[ind,:]:
                fid.write("%e " % item2)
            fid.write('\n')
            ind += 1
        fid.close()
    #if plot_Iv==1 end

    #***************************************************************************************
    # Ec(X,Y)
    # -------------------------------------------
    if plot_Ec3d == 1:
        figure(6)
        [X, Y] = np.meshgrid(XI, YI)
        Z = trMEc
        ax = gca(projection = '3d')
        surf = ax.plot_surface(X, Y, Z, rstride=3, cstride=3, cmap=cm.coolwarm, linewidth=0.5, antialiased = True)

        #surf(XI,YI,trMEc)
        #shading interp commented out to reduce size of the .ps file
        title('3D Conduction band edge potential profile')
        ax.set_xlabel('X [nm]')
        ax.set_ylabel('Y [nm]')
        ax.set_zlabel('Ec [eV]')
        ax.view_init(elev=60, azim=50)
        ax.dist=8
        savefig('Ec_X_Y.png')

        XII = (0, XI)
        tem1 = (YI, trMEc)
        tem2 = (XII, tem1)
        #np.savetxt('Ec_X_Y.dat', tem2, fmt='%e', delimiter=';')
        #f1 = open('Ec_X_Y','w')
        #writer = csv.writer(f1, delimiter = ',')
        #writer.writerows(tem2)



   #*******************************************************************************************
    if (plot_Ecsub==1 and max_subband>=1):
        figure(8)
        for iii in np.arange(0,max_subband):
            plot(XI, E_sub[0, Ng_step, Nd_step, :, iii],'r-')
            hold(True)
            grid(True)
            if (t_vall==3):
                plot(XI, E_sub[1, Ng_step, Nd_step, :,iii],'k-')
                plot(XI, E_sub[2, Ng_step, Nd_step, :,iii],'-')

# 需要导入模块: from mpl_toolkits.mplot3d import Axes3D [as 别名]
# 或者: from mpl_toolkits.mplot3d.Axes3D import plot_surface [as 别名]
# -*- coding: utf-8 -*-
"""
Created on Mon Jun 27 20:10:40 2016

@author: Bhuti
"""
import pandas as pd
pd.set_option('display.max_row', 1000)
pd.set_option('display.max_columns', 50)

got = pd.read_csv ('/Users/Bhuti/Desktop/war_of_the_five_kings_dataset-master/5kings_battles_v1.csv')
got = pd.DataFrame(got)
# print(got['attacker_size'])
print(got['defender_king'].value_counts())
got['defender_king'].value_counts().plot(kind='bar')

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
x = got['year']
y = got['battle_number']
z = got['attacker_size']
# Axes3D.plot_surface('defender_1','battle_number','attacker_outcome')
Axes3D.plot_surface(x,y,z)

# 需要导入模块: from mpl_toolkits.mplot3d import Axes3D [as 别名]
# 或者: from mpl_toolkits.mplot3d.Axes3D import plot_surface [as 别名]
theta0_vals = np.linspace(-10, 10, 100)
theta1_vals = np.linspace(-1, 4, 100)

# initialize J_vals to a matrix of 0's
J_vals = np.zeros((len(theta0_vals),len(theta1_vals)))

# Fill out J_Vals 
# Note: There is probably a more efficient way to do this that uses
#	broadcasting instead of the nested for loops
for i in range(len(theta0_vals)):
    for j in range(len(theta1_vals)):
        t = np.array([theta0_vals[i],theta1_vals[j]])
        J_vals[i][j] = computeCost(X,y,t)


# Surface plot using J_Vals
fig = plt.figure()
ax = plt.subplot(111,projection='3d')
Axes3D.plot_surface(ax,theta0_vals,theta1_vals,J_vals,cmap=cm.coolwarm)
plt.show()

# Contour plot
# TO DO: Currently does not work as expected. Need to find a way to mimic
#	 the logspace option in matlab
fig = plt.figure()
ax = plt.subplot(111)
plt.contour(theta0_vals,theta1_vals,J_vals) 


# vim: tabstop=8 expandtab shiftwidth=4 softtabstop=4