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Updated comments to reflect standard deviations instead of variances …
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…in the discussions regarding the values for k.
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magicbycalvin committed Jan 28, 2022
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Showing 1 changed file with 6 additions and 6 deletions.
12 changes: 6 additions & 6 deletions python/gtsam/utils/plot.py
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Expand Up @@ -76,8 +76,8 @@ def plot_covariance_ellipse_3d(axes,
Based on Maybeck Vol 1, page 366
For the 3D case:
k = 3.527 corresponds to 1 std, 68.26% of all probability
k = 14.157 corresponds to 3 std, 99.74% of all probability
k = 1.878 corresponds to 1 std, 68.26% of all probability
k = 3.763 corresponds to 3 std, 99.74% of all probability
We choose k = 5 which corresponds to 99.99846% of all probability in 3D
Expand Down Expand Up @@ -123,8 +123,8 @@ def plot_point2_on_axes(axes,
Based on Stochastic Models, Estimation, and Control Vol 1 by Maybeck,
page 366
For the 2D case:
k = 2.296 corresponds to 1 std, 68.26% of all probability
k = 11.820 corresponds to 3 std, 99.74% of all probability
k = 1.515 corresponds to 1 std, 68.26% of all probability
k = 3.438 corresponds to 3 std, 99.74% of all probability
We choose k = 5 which corresponds to 99.99963% of all probability for 2D.
Expand Down Expand Up @@ -193,8 +193,8 @@ def plot_pose2_on_axes(axes,
Based on Stochastic Models, Estimation, and Control Vol 1 by Maybeck,
page 366
For the 2D case:
k = 2.296 corresponds to 1 std, 68.26% of all probability
k = 11.820 corresponds to 3 std, 99.74% of all probability
k = 1.515 corresponds to 1 std, 68.26% of all probability
k = 3.438 corresponds to 3 std, 99.74% of all probability
We choose k = 5 which corresponds to 99.99963% of all probability for 2D.
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