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Merge pull request #616 from borglab/fix/misc 

Miscellaneous fixes
release/4.3a0
Varun Agrawal 2020-11-30 15:31:48 -05:00 committed by GitHub
parent 2d22258ed1 7eea8cd8ba
commit 92757a10f0
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GPG Key ID: 4AEE18F83AFDEB23
3 changed files with 14 additions and 12 deletions
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2
examples/ImuFactorsExample.cpp
View File

@ -125,7 +125,7 @@ int main(int argc, char* argv[]) {
output_filename = var_map["output_filename"].as<string>();
use_isam = var_map["use_isam"].as<bool>();
ISAM2* isam2;
ISAM2* isam2 = 0;
if (use_isam) {
printf("Using ISAM2\n");
ISAM2Params parameters;

2
gtsam/CMakeLists.txt
View File

@ -199,7 +199,7 @@ if(WIN32)
else()
if("${CMAKE_BUILD_TYPE}" STREQUAL "Release")
# Suppress all warnings from 3rd party sources.
set_source_files_properties(${3rdparty_srcs} PROPERTIES COMPILE_FLAGS "-w")
set_source_files_properties(${3rdparty_srcs} PROPERTIES COMPILE_FLAGS "-w -Wno-everything")
else()
set_source_files_properties(${3rdparty_srcs} PROPERTIES COMPILE_FLAGS "-Wno-error")
endif()

22
python/gtsam/utils/plot.py
View File

@ -36,18 +36,15 @@ def set_axes_equal(fignum):
ax.set_zlim3d([origin[2] - radius, origin[2] + radius])
def ellipsoid(xc, yc, zc, rx, ry, rz, n):
def ellipsoid(rx, ry, rz, n):
"""
Numpy equivalent of Matlab's ellipsoid function.
Args:
xc (double): Center of ellipsoid in X-axis.
yc (double): Center of ellipsoid in Y-axis.
zc (double): Center of ellipsoid in Z-axis.
rx (double): Radius of ellipsoid in X-axis.
ry (double): Radius of ellipsoid in Y-axis.
rz (double): Radius of ellipsoid in Z-axis.
n (int): The granularity of the ellipsoid plotted.
n (int): The granularity of the ellipsoid plotted.
Returns:
tuple[numpy.ndarray]: The points in the x, y and z axes to use for the surface plot.
@ -72,7 +69,8 @@ def plot_covariance_ellipse_3d(axes, origin, P, scale=1, n=8, alpha=0.5):
Args:
axes (matplotlib.axes.Axes): Matplotlib axes.
origin (gtsam.Point3): The origin in the world frame.
P (numpy.ndarray): The marginal covariance matrix of the 3D point which will be represented as an ellipse.
P (numpy.ndarray): The marginal covariance matrix of the 3D point
which will be represented as an ellipse.
scale (float): Scaling factor of the radii of the covariance ellipse.
n (int): Defines the granularity of the ellipse. Higher values indicate finer ellipses.
alpha (float): Transparency value for the plotted surface in the range [0, 1].
@ -85,7 +83,7 @@ def plot_covariance_ellipse_3d(axes, origin, P, scale=1, n=8, alpha=0.5):
rx, ry, rz = radii
# generate data for "unrotated" ellipsoid
xc, yc, zc = ellipsoid(0, 0, 0, rx, ry, rz, n)
xc, yc, zc = ellipsoid(rx, ry, rz, n)
# rotate data with orientation matrix U and center c
data = np.kron(U[:, 0:1], xc) + np.kron(U[:, 1:2], yc) + \
@ -106,7 +104,8 @@ def plot_pose2_on_axes(axes, pose, axis_length=0.1, covariance=None):
axes (matplotlib.axes.Axes): Matplotlib axes.
pose (gtsam.Pose2): The pose to be plotted.
axis_length (float): The length of the camera axes.
covariance (numpy.ndarray): Marginal covariance matrix to plot the uncertainty of the estimation.
covariance (numpy.ndarray): Marginal covariance matrix to plot
the uncertainty of the estimation.
"""
# get rotation and translation (center)
gRp = pose.rotation().matrix() # rotation from pose to global
@ -146,7 +145,8 @@ def plot_pose2(fignum, pose, axis_length=0.1, covariance=None,
fignum (int): Integer representing the figure number to use for plotting.
pose (gtsam.Pose2): The pose to be plotted.
axis_length (float): The length of the camera axes.
covariance (numpy.ndarray): Marginal covariance matrix to plot the uncertainty of the estimation.
covariance (numpy.ndarray): Marginal covariance matrix to plot
the uncertainty of the estimation.
axis_labels (iterable[string]): List of axis labels to set.
"""
# get figure object
@ -215,7 +215,8 @@ def plot_3d_points(fignum, values, linespec="g*", marginals=None,
fignum (int): Integer representing the figure number to use for plotting.
values (gtsam.Values): Values dictionary consisting of points to be plotted.
linespec (string): String representing formatting options for Matplotlib.
marginals (numpy.ndarray): Marginal covariance matrix to plot the uncertainty of the estimation.
marginals (numpy.ndarray): Marginal covariance matrix to plot the
uncertainty of the estimation.
title (string): The title of the plot.
axis_labels (iterable[string]): List of axis labels to set.
"""
@ -238,6 +239,7 @@ def plot_3d_points(fignum, values, linespec="g*", marginals=None,
continue
# I guess it's not a Point3
fig = plt.figure(fignum)
fig.suptitle(title)
fig.canvas.set_window_title(title.lower())