Merged in feature/cython-plot2d-marginals (pull request #388)
wip - plotting covariances in 2d in cython examplesrelease/4.3a0
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20c4af4ec6
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@ -17,6 +17,9 @@ import numpy as np
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import gtsam
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import matplotlib.pyplot as plt
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import gtsam.utils.plot as gtsam_plot
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# Create noise models
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ODOMETRY_NOISE = gtsam.noiseModel_Diagonal.Sigmas(np.array([0.2, 0.2, 0.1]))
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PRIOR_NOISE = gtsam.noiseModel_Diagonal.Sigmas(np.array([0.3, 0.3, 0.1]))
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@ -50,3 +53,17 @@ params = gtsam.LevenbergMarquardtParams()
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optimizer = gtsam.LevenbergMarquardtOptimizer(graph, initial, params)
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result = optimizer.optimize()
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print("\nFinal Result:\n{}".format(result))
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# 5. Calculate and print marginal covariances for all variables
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marginals = gtsam.Marginals(graph, result)
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for i in range(1, 4):
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print("X{} covariance:\n{}\n".format(i, marginals.marginalCovariance(i)))
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fig = plt.figure(0)
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for i in range(1, 4):
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gtsam_plot.plot_pose2(0, result.atPose2(i), 0.5, marginals.marginalCovariance(i))
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plt.axis('equal')
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plt.show()
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@ -19,6 +19,9 @@ import numpy as np
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import gtsam
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import matplotlib.pyplot as plt
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import gtsam.utils.plot as gtsam_plot
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def vector3(x, y, z):
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"""Create 3d double numpy array."""
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@ -85,3 +88,10 @@ print("Final Result:\n{}".format(result))
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marginals = gtsam.Marginals(graph, result)
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for i in range(1, 6):
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print("X{} covariance:\n{}\n".format(i, marginals.marginalCovariance(i)))
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fig = plt.figure(0)
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for i in range(1, 6):
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gtsam_plot.plot_pose2(0, result.atPose2(i), 0.5, marginals.marginalCovariance(i))
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plt.axis('equal')
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plt.show()
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@ -2,9 +2,10 @@
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import numpy as np
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import matplotlib.pyplot as plt
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from matplotlib import patches
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def plot_pose2_on_axes(axes, pose, axis_length=0.1):
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def plot_pose2_on_axes(axes, pose, axis_length=0.1, covariance=None):
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"""Plot a 2D pose on given axis 'axes' with given 'axis_length'."""
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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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@ -20,13 +21,26 @@ def plot_pose2_on_axes(axes, pose, axis_length=0.1):
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line = np.append(origin[np.newaxis], y_axis[np.newaxis], axis=0)
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axes.plot(line[:, 0], line[:, 1], 'g-')
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if covariance is not None:
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pPp = covariance[0:2, 0:2]
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gPp = np.matmul(np.matmul(gRp, pPp), gRp.T)
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def plot_pose2(fignum, pose, axis_length=0.1):
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w, v = np.linalg.eig(gPp)
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# k = 2.296
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k = 5.0
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angle = np.arctan2(v[1, 0], v[0, 0])
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e1 = patches.Ellipse(origin, np.sqrt(w[0]*k), np.sqrt(w[1]*k),
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np.rad2deg(angle), fill=False)
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axes.add_patch(e1)
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def plot_pose2(fignum, pose, axis_length=0.1, covariance=None):
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"""Plot a 2D pose on given figure with given 'axis_length'."""
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# get figure object
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fig = plt.figure(fignum)
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axes = fig.gca()
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plot_pose2_on_axes(axes, pose, axis_length)
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plot_pose2_on_axes(axes, pose, axis_length, covariance)
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def plot_point3_on_axes(axes, point, linespec):
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