99 lines
2.8 KiB
Python
99 lines
2.8 KiB
Python
"""
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GTSAM Copyright 2010-2019, Georgia Tech Research Corporation,
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Atlanta, Georgia 30332-0415
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All Rights Reserved
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See LICENSE for the license information
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Script to plot City10000 results.
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Can be used to plot results from both C++ and python scripts.
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Usage:
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```
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python plot_city10000.py Data/ISAM2_GT_city10000.txt --estimates ../build/examples/ISAM2_city10000.txt ../build/examples/Hybrid_City10000.txt
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```
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You can generate estimates by running
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- `make ISAM2_City10000.run` for the ISAM2 version
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- `make Hybrid_City10000.run` for the Hybrid Smoother version
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Author: Varun Agrawal
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"""
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import argparse
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import numpy as np
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from matplotlib import pyplot as plt
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def parse_args():
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"""Parse command line arguments"""
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parser = argparse.ArgumentParser()
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parser.add_argument("ground_truth", help="The ground truth data file.")
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parser.add_argument(
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"--estimates",
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nargs='+',
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help="File(s) with estimates (as .txt), can be more than one.")
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return parser.parse_args()
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def plot_estimates(gt,
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estimates,
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fignum: int,
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estimate_color=(0.1, 0.1, 0.9, 0.4),
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estimate_label="Hybrid Factor Graphs"):
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"""Plot the City10000 estimates against the ground truth.
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Args:
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gt (np.ndarray): The ground truth trajectory as xy values.
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estimates (np.ndarray): The estimates trajectory as xy values.
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fignum (int): The figure number for multiple plots.
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estimate_color (tuple, optional): The color to use for the graph of estimates.
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Defaults to (0.1, 0.1, 0.9, 0.4).
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estimate_label (str, optional): Label for the estimates, used in the legend.
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Defaults to "Hybrid Factor Graphs".
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"""
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fig = plt.figure(fignum)
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ax = fig.gca()
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ax.axis('equal')
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ax.axis((-65.0, 65.0, -75.0, 60.0))
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ax.plot(gt[:, 0],
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gt[:, 1],
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'--',
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linewidth=1,
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color=(0.1, 0.7, 0.1, 0.5),
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label="Ground Truth")
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ax.plot(estimates[:, 0],
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estimates[:, 1],
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'-',
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linewidth=1,
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color=estimate_color,
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label=estimate_label)
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ax.legend()
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def main():
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"""Main runner"""
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args = parse_args()
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gt = np.loadtxt(args.ground_truth, delimiter=" ")
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# Default colors and labels, assuming we have only 2 estimates
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colors = ((0.9, 0.1, 0.1, 0.4), (0.1, 0.1, 0.9, 0.4))
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labels = ("ISAM2", "Hybrid Factor Graphs")
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for i in range(len(args.estimates)):
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h_poses = np.loadtxt(args.estimates[i], delimiter=" ")
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gt = gt[:h_poses.shape[0]]
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plot_estimates(gt,
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h_poses,
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i + 1,
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estimate_color=colors[i],
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estimate_label=labels[i])
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plt.show()
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if __name__ == "__main__":
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main()
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