60 lines
		
	
	
		
			2.0 KiB
		
	
	
	
		
			Python
		
	
	
			
		
		
	
	
			60 lines
		
	
	
		
			2.0 KiB
		
	
	
	
		
			Python
		
	
	
import numpy as np
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import matplotlib.pyplot as plt
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from mpl_toolkits.mplot3d import Axes3D as _Axes3D
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def plotPoint3(fignum, point, linespec):
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    fig = plt.figure(fignum)
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    ax = fig.gca(projection='3d')
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    ax.plot([point.x()], [point.y()], [point.z()], linespec)
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def plot3DPoints(fignum, values, linespec, marginals=None):
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    # PLOT3DPOINTS Plots the Point3's in a values, with optional covariances
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    #    Finds all the Point3 objects in the given Values object and plots them.
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    #  If a Marginals object is given, this function will also plot marginal
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    #  covariance ellipses for each point.
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    keys = values.keys()
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    # Plot points and covariance matrices
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    for key in keys:
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        try:
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            p = values.atPoint3(key);
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            # if haveMarginals
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            #     P = marginals.marginalCovariance(key);
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            #     gtsam.plotPoint3(p, linespec, P);
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            # else
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            plotPoint3(fignum, p, linespec);
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        except RuntimeError:
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            continue
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            # I guess it's not a Point3
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def plotPose3(fignum, pose, axisLength=0.1):
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    # get figure object
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    fig = plt.figure(fignum)
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    ax = fig.gca(projection='3d')
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    # get rotation and translation (center)
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    gRp = pose.rotation().matrix()  # rotation from pose to global
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    C = pose.translation().vector()
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    # draw the camera axes
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    xAxis = C + gRp[:, 0] * axisLength
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    L = np.append(C[np.newaxis], xAxis[np.newaxis], axis=0)
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    ax.plot(L[:, 0], L[:, 1], L[:, 2], 'r-')
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    yAxis = C + gRp[:, 1] * axisLength
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    L = np.append(C[np.newaxis], yAxis[np.newaxis], axis=0)
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    ax.plot(L[:, 0], L[:, 1], L[:, 2], 'g-')
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    zAxis = C + gRp[:, 2] * axisLength
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    L = np.append(C[np.newaxis], zAxis[np.newaxis], axis=0)
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    ax.plot(L[:, 0], L[:, 1], L[:, 2], 'b-')
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    # # plot the covariance
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    # if (nargin>2) && (~isempty(P))
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    #     pPp = P(4:6,4:6); % covariance matrix in pose coordinate frame    
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    #     gPp = gRp*pPp*gRp'; % convert the covariance matrix to global coordinate frame
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    #     gtsam.covarianceEllipse3D(C,gPp);  
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    # end
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