Repository: gaochq/IMU_Attitude_Estimator
Branch: master
Commit: 2ad6f4fe29da
Files: 20
Total size: 133.2 KB
Directory structure:
gitextract_hjgyys6b/
├── Allan_Analysis.py
├── CMakeLists.txt
├── DataSets.py
├── LICENSE
├── README.md
├── cmake_modules/
│ ├── FindEigen3.cmake
│ └── FindGlog.cmake
├── datasets/
│ └── readme.txt
├── demo/
│ └── Test.cpp
├── include/
│ ├── Convert.h
│ ├── EKF_Attitude.h
│ ├── ESKF_Attitude.h
│ ├── Mahony_Attitude.h
│ ├── TypeDefs.h
│ ├── matplotlibcpp.h
│ └── tic_toc.h
└── src/
├── Convert.cpp
├── EKF_Attitude.cpp
├── ESKF_Attitude.cpp
└── Mahony_Attitude.cpp
================================================
FILE CONTENTS
================================================
================================================
FILE: Allan_Analysis.py
================================================
import numpy as np
import matplotlib.pyplot as plt
import math
import numpy.matlib
from scipy.optimize import nnls
import scipy.io as sio
# data was sampled in 100hz
Pts_size = 100
fs = 100
data = np.loadtxt("./datasets/data.dat")
data = data[:,2:5]*3600
[N, M] = data.shape
n = np.arange(0, math.floor(math.log(N/2, 2))+1)
n = 2**n
maxN = n[n.size-1]
endLogInc = math.log(maxN, 10);
m = np.unique(np.ceil(np.logspace(0, endLogInc, Pts_size))).transpose()
t0 = 1.0/fs
T = m*t0
theta = np.zeros([N, M])
theta[:, 0] = data[:, 0].cumsum()/fs
theta[:, 1] = data[:, 1].cumsum()/fs
theta[:, 2] = data[:, 2].cumsum()/fs
sigma2 = np.zeros([T.size, M])
for i in range(0, m.size):
for k in range(0, int(N-2*m[i])):
sigma2[i,:] = sigma2[i,:] + (theta[int(k+2*m[i]), :] - 2*theta[int(k+m[i]), :] + theta[k, :])**2
print(i)
sigma2[i,:] = sigma2[i,:]/(2*T[i]**2*(N-2*m[i]))
sigma2 = np.load("sigma2.dat.npy")
T = np.load("T.dat.npy")
sigma = np.sqrt(sigma2)
print("hello")
plt.loglog(T, sigma2)
plt.show()
for j in range(0,2):
avar = sigma(j)
P = np.empty((T.size, 5))
P[:, 0] = 3 / T**2
P[:, 1] = 1 / T
P[:, 2] = 2 * np.log(2) / np.pi
P[:, 3] = T / 3
P[:, 4] = T**2 / 2
P /= avar[:, np.newaxis]
b = np.ones(T.size)
s = nnls(P, b)[0]
params = np.sqrt(s)
print(params)
================================================
FILE: CMakeLists.txt
================================================
cmake_minimum_required(VERSION 2.8)
project(IMU_Attitude_Estimator)
set(CMAKE_BUILD_TYPE Release)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11 -o3")
set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${PROJECT_SOURCE_DIR}/bin)
set(CMAKE_ARCHIVE_OUTPUT_DIRECTORY ${PROJECT_SOURCE_DIR}/lib)
list(APPEND CMAKE_MODULE_PATH ${PROJECT_SOURCE_DIR}/cmake_modules)
find_package(Eigen3 REQUIRED)
include_directories(EIGEN3_INCLUDE_DIR)
include_directories("/usr/include/eigen3")
find_package(Glog REQUIRED)
include_directories(${GLOG_INCLUDE_DIRS})
find_package(PythonLibs 2.7)
include_directories(${PYTHON_INCLUDE_DIRS})
include_directories(${PROJECT_SOURCE_DIR}/include)
add_library(${PROJECT_NAME} SHARED
src/Convert.cpp
src/EKF_Attitude.cpp
src/ESKF_Attitude.cpp
src/Mahony_Attitude.cpp)
target_link_libraries(${PROJECT_NAME}
${GLOG_LIBRARIES}
${EIGEN3_LIBS}
${PYTHON_LIBRARIES})
add_executable(Demo demo/Test.cpp)
target_link_libraries(Demo ${PROJECT_NAME})
================================================
FILE: DataSets.py
================================================
import numpy as np
import scipy.io as sio
load_fn = './datasets/NAV.mat'
load_Data = sio.loadmat(load_fn)
data = load_Data['NAV']
mea = data[:,8:17]
euler = data[:,29:32]
out = np.hstack((mea, euler))
np.savetxt("data.bin", out, fmt='%f')
print out.shape
print data
================================================
FILE: LICENSE
================================================
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If the Program specifies that a proxy can decide which future
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END OF TERMS AND CONDITIONS
How to Apply These Terms to Your New Programs
If you develop a new program, and you want it to be of the greatest
possible use to the public, the best way to achieve this is to make it
free software which everyone can redistribute and change under these terms.
To do so, attach the following notices to the program. It is safest
to attach them to the start of each source file to most effectively
state the exclusion of warranty; and each file should have at least
the "copyright" line and a pointer to where the full notice is found.
{one line to give the program's name and a brief idea of what it does.}
Copyright (C) {year} {fullname}
This program is free software: you can redistribute it and/or modify
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You should have received a copy of the GNU General Public License
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Also add information on how to contact you by electronic and paper mail.
If the program does terminal interaction, make it output a short
notice like this when it starts in an interactive mode:
IMU_Attitude_Estiamtor Copyright (C) 2018 gaochq
This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
This is free software, and you are welcome to redistribute it
under certain conditions; type `show c' for details.
The hypothetical commands `show w' and `show c' should show the appropriate
parts of the General Public License. Of course, your program's commands
might be different; for a GUI interface, you would use an "about box".
You should also get your employer (if you work as a programmer) or school,
if any, to sign a "copyright disclaimer" for the program, if necessary.
For more information on this, and how to apply and follow the GNU GPL, see
[http://www.gnu.org/licenses/].
The GNU General Public License does not permit incorporating your program
into proprietary programs. If your program is a subroutine library, you
may consider it more useful to permit linking proprietary applications with
the library. If this is what you want to do, use the GNU Lesser General
Public License instead of this License. But first, please read
[http://www.gnu.org/philosophy/why-not-lgpl.html].
================================================
FILE: README.md
================================================
# IMU_Attitude_Estimator
This project is aimed at estimating the attitude of Attitude Heading and Reference System(AHRS). And the project contains three popular attitude estimator algorithms.
- Mahony's algorithm
- Extend Kalman Filter(EKF)
- Error State Kalman Filter(ESKF)
```DataSets.py``` for converting estimator data.
```Allan_Analysis``` for Allan Variance analysis.
### Refrence
[1] [Mahony R, Hamel T, Pflimlin J M. Nonlinear complementary filters on the special orthogonal group[J]. IEEE Transactions on automatic control, 2008, 53(5): 1203-1218.](http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4608934)
[2] [Pixhawk state estimation](https://pixhawk.org/_media/firmware/apps/attitude_estimator_ekf/ekf_excerptmasterthesis.pdf)
[3] [Solà, Joan. Quaternion kinematics for the error-state Kalman filter[J]. 2017.](http://219.216.82.193/cache/4/03/www.iri.upc.edu/bbcd603c764cd75e76df0968d16bc022/kinematics.pdf)
[4] [Trawny N, Roumeliotis S I. Indirect Kalman Filter for 3D Attitude Estimation[J]. 2005.](http://pdfs.semanticscholar.org/2c8e/95bc331024105cbde6f6918cda8493f263c8.pdf)
### Dependencies
- Eigen3.2.0
- glog
```
sudo apt-get install libgoogle-glog-dev
```
- [matplotlib-cpp](https://github.com/lava/matplotlib-cpp)
### Simple Test
Simple comparision among three methods. And the params of Mahony filter can be further tuned.
<img src="Image/All_roll.png" width="50%" height="50%"><img src="Image/EKF-ESKF-Roll.png" width="50%" height="50%">
<img src="Image/EKF-ESKF-Pitch.png" width="50%" height="50%"><img src="Image/EKF-ESKF.png" width="50%" height="50%">
================================================
FILE: cmake_modules/FindEigen3.cmake
================================================
# - Try to find Eigen3 lib
#
# This module supports requiring a minimum version, e.g. you can do
# find_package(Eigen3 3.1.2)
# to require version 3.1.2 or newer of Eigen3.
#
# Once done this will define
#
# EIGEN3_FOUND - system has eigen lib with correct version
# EIGEN3_INCLUDE_DIR - the eigen include directory
# EIGEN3_VERSION - eigen version
# Copyright (c) 2006, 2007 Montel Laurent, <montel@kde.org>
# Copyright (c) 2008, 2009 Gael Guennebaud, <g.gael@free.fr>
# Copyright (c) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
# Redistribution and use is allowed according to the terms of the 2-clause BSD license.
if(NOT Eigen3_FIND_VERSION)
if(NOT Eigen3_FIND_VERSION_MAJOR)
set(Eigen3_FIND_VERSION_MAJOR 2)
endif(NOT Eigen3_FIND_VERSION_MAJOR)
if(NOT Eigen3_FIND_VERSION_MINOR)
set(Eigen3_FIND_VERSION_MINOR 91)
endif(NOT Eigen3_FIND_VERSION_MINOR)
if(NOT Eigen3_FIND_VERSION_PATCH)
set(Eigen3_FIND_VERSION_PATCH 0)
endif(NOT Eigen3_FIND_VERSION_PATCH)
set(Eigen3_FIND_VERSION "${Eigen3_FIND_VERSION_MAJOR}.${Eigen3_FIND_VERSION_MINOR}.${Eigen3_FIND_VERSION_PATCH}")
endif(NOT Eigen3_FIND_VERSION)
macro(_eigen3_check_version)
file(READ "${EIGEN3_INCLUDE_DIR}/Eigen/src/Core/util/Macros.h" _eigen3_version_header)
string(REGEX MATCH "define[ \t]+EIGEN_WORLD_VERSION[ \t]+([0-9]+)" _eigen3_world_version_match "${_eigen3_version_header}")
set(EIGEN3_WORLD_VERSION "${CMAKE_MATCH_1}")
string(REGEX MATCH "define[ \t]+EIGEN_MAJOR_VERSION[ \t]+([0-9]+)" _eigen3_major_version_match "${_eigen3_version_header}")
set(EIGEN3_MAJOR_VERSION "${CMAKE_MATCH_1}")
string(REGEX MATCH "define[ \t]+EIGEN_MINOR_VERSION[ \t]+([0-9]+)" _eigen3_minor_version_match "${_eigen3_version_header}")
set(EIGEN3_MINOR_VERSION "${CMAKE_MATCH_1}")
set(EIGEN3_VERSION ${EIGEN3_WORLD_VERSION}.${EIGEN3_MAJOR_VERSION}.${EIGEN3_MINOR_VERSION})
if(${EIGEN3_VERSION} VERSION_LESS ${Eigen3_FIND_VERSION})
set(EIGEN3_VERSION_OK FALSE)
else(${EIGEN3_VERSION} VERSION_LESS ${Eigen3_FIND_VERSION})
set(EIGEN3_VERSION_OK TRUE)
endif(${EIGEN3_VERSION} VERSION_LESS ${Eigen3_FIND_VERSION})
if(NOT EIGEN3_VERSION_OK)
message(STATUS "Eigen3 version ${EIGEN3_VERSION} found in ${EIGEN3_INCLUDE_DIR}, "
"but at least version ${Eigen3_FIND_VERSION} is required")
endif(NOT EIGEN3_VERSION_OK)
endmacro(_eigen3_check_version)
if (EIGEN3_INCLUDE_DIR)
# in cache already
_eigen3_check_version()
set(EIGEN3_FOUND ${EIGEN3_VERSION_OK})
else (EIGEN3_INCLUDE_DIR)
# specific additional paths for some OS
if (WIN32)
set(EIGEN_ADDITIONAL_SEARCH_PATHS ${EIGEN_ADDITIONAL_SEARCH_PATHS} "C:/Program Files/Eigen/include" "C:/Program Files (x86)/Eigen/include")
endif(WIN32)
find_path(EIGEN3_INCLUDE_DIR NAMES signature_of_eigen3_matrix_library
PATHS
${CMAKE_INSTALL_PREFIX}/include
${EIGEN_ADDITIONAL_SEARCH_PATHS}
${KDE4_INCLUDE_DIR}
PATH_SUFFIXES eigen3 eigen
)
if(EIGEN3_INCLUDE_DIR)
_eigen3_check_version()
endif(EIGEN3_INCLUDE_DIR)
include(FindPackageHandleStandardArgs)
find_package_handle_standard_args(Eigen3 DEFAULT_MSG EIGEN3_INCLUDE_DIR EIGEN3_VERSION_OK)
mark_as_advanced(EIGEN3_INCLUDE_DIR)
endif(EIGEN3_INCLUDE_DIR)
================================================
FILE: cmake_modules/FindGlog.cmake
================================================
# Ceres Solver - A fast non-linear least squares minimizer
# Copyright 2015 Google Inc. All rights reserved.
# http://ceres-solver.org/
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# * Redistributions of source code must retain the above copyright notice,
# this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions and the following disclaimer in the documentation
# and/or other materials provided with the distribution.
# * Neither the name of Google Inc. nor the names of its contributors may be
# used to endorse or promote products derived from this software without
# specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
# POSSIBILITY OF SUCH DAMAGE.
#
# Author: alexs.mac@gmail.com (Alex Stewart)
#
# FindGlog.cmake - Find Google glog logging library.
#
# This module defines the following variables:
#
# GLOG_FOUND: TRUE iff glog is found.
# GLOG_INCLUDE_DIRS: Include directories for glog.
# GLOG_LIBRARIES: Libraries required to link glog.
#
# The following variables control the behaviour of this module:
#
# GLOG_INCLUDE_DIR_HINTS: List of additional directories in which to
# search for glog includes, e.g: /timbuktu/include.
# GLOG_LIBRARY_DIR_HINTS: List of additional directories in which to
# search for glog libraries, e.g: /timbuktu/lib.
#
# The following variables are also defined by this module, but in line with
# CMake recommended FindPackage() module style should NOT be referenced directly
# by callers (use the plural variables detailed above instead). These variables
# do however affect the behaviour of the module via FIND_[PATH/LIBRARY]() which
# are NOT re-called (i.e. search for library is not repeated) if these variables
# are set with valid values _in the CMake cache_. This means that if these
# variables are set directly in the cache, either by the user in the CMake GUI,
# or by the user passing -DVAR=VALUE directives to CMake when called (which
# explicitly defines a cache variable), then they will be used verbatim,
# bypassing the HINTS variables and other hard-coded search locations.
#
# GLOG_INCLUDE_DIR: Include directory for glog, not including the
# include directory of any dependencies.
# GLOG_LIBRARY: glog library, not including the libraries of any
# dependencies.
# Reset CALLERS_CMAKE_FIND_LIBRARY_PREFIXES to its value when
# FindGlog was invoked.
macro(GLOG_RESET_FIND_LIBRARY_PREFIX)
if (MSVC)
set(CMAKE_FIND_LIBRARY_PREFIXES "${CALLERS_CMAKE_FIND_LIBRARY_PREFIXES}")
endif (MSVC)
endmacro(GLOG_RESET_FIND_LIBRARY_PREFIX)
# Called if we failed to find glog or any of it's required dependencies,
# unsets all public (designed to be used externally) variables and reports
# error message at priority depending upon [REQUIRED/QUIET/<NONE>] argument.
macro(GLOG_REPORT_NOT_FOUND REASON_MSG)
unset(GLOG_FOUND)
unset(GLOG_INCLUDE_DIRS)
unset(GLOG_LIBRARIES)
# Make results of search visible in the CMake GUI if glog has not
# been found so that user does not have to toggle to advanced view.
mark_as_advanced(CLEAR GLOG_INCLUDE_DIR
GLOG_LIBRARY)
glog_reset_find_library_prefix()
# Note <package>_FIND_[REQUIRED/QUIETLY] variables defined by FindPackage()
# use the camelcase library name, not uppercase.
if (Glog_FIND_QUIETLY)
message(STATUS "Failed to find glog - " ${REASON_MSG} ${ARGN})
elseif (Glog_FIND_REQUIRED)
message(FATAL_ERROR "Failed to find glog - " ${REASON_MSG} ${ARGN})
else()
# Neither QUIETLY nor REQUIRED, use no priority which emits a message
# but continues configuration and allows generation.
message("-- Failed to find glog - " ${REASON_MSG} ${ARGN})
endif ()
endmacro(GLOG_REPORT_NOT_FOUND)
# Handle possible presence of lib prefix for libraries on MSVC, see
# also GLOG_RESET_FIND_LIBRARY_PREFIX().
if (MSVC)
# Preserve the caller's original values for CMAKE_FIND_LIBRARY_PREFIXES
# s/t we can set it back before returning.
set(CALLERS_CMAKE_FIND_LIBRARY_PREFIXES "${CMAKE_FIND_LIBRARY_PREFIXES}")
# The empty string in this list is important, it represents the case when
# the libraries have no prefix (shared libraries / DLLs).
set(CMAKE_FIND_LIBRARY_PREFIXES "lib" "" "${CMAKE_FIND_LIBRARY_PREFIXES}")
endif (MSVC)
# Search user-installed locations first, so that we prefer user installs
# to system installs where both exist.
list(APPEND GLOG_CHECK_INCLUDE_DIRS
/usr/local/include
/usr/local/homebrew/include # Mac OS X
/opt/local/var/macports/software # Mac OS X.
/opt/local/include
/usr/include)
# Windows (for C:/Program Files prefix).
list(APPEND GLOG_CHECK_PATH_SUFFIXES
glog/include
glog/Include
Glog/include
Glog/Include)
list(APPEND GLOG_CHECK_LIBRARY_DIRS
/usr/local/lib
/usr/local/homebrew/lib # Mac OS X.
/opt/local/lib
/usr/lib)
# Windows (for C:/Program Files prefix).
list(APPEND GLOG_CHECK_LIBRARY_SUFFIXES
glog/lib
glog/Lib
Glog/lib
Glog/Lib)
# Search supplied hint directories first if supplied.
find_path(GLOG_INCLUDE_DIR
NAMES glog/logging.h
PATHS ${GLOG_INCLUDE_DIR_HINTS}
${GLOG_CHECK_INCLUDE_DIRS}
PATH_SUFFIXES ${GLOG_CHECK_PATH_SUFFIXES})
if (NOT GLOG_INCLUDE_DIR OR
NOT EXISTS ${GLOG_INCLUDE_DIR})
glog_report_not_found(
"Could not find glog include directory, set GLOG_INCLUDE_DIR "
"to directory containing glog/logging.h")
endif (NOT GLOG_INCLUDE_DIR OR
NOT EXISTS ${GLOG_INCLUDE_DIR})
find_library(GLOG_LIBRARY NAMES glog
PATHS ${GLOG_LIBRARY_DIR_HINTS}
${GLOG_CHECK_LIBRARY_DIRS}
PATH_SUFFIXES ${GLOG_CHECK_LIBRARY_SUFFIXES})
if (NOT GLOG_LIBRARY OR
NOT EXISTS ${GLOG_LIBRARY})
glog_report_not_found(
"Could not find glog library, set GLOG_LIBRARY "
"to full path to libglog.")
endif (NOT GLOG_LIBRARY OR
NOT EXISTS ${GLOG_LIBRARY})
# Mark internally as found, then verify. GLOG_REPORT_NOT_FOUND() unsets
# if called.
set(GLOG_FOUND TRUE)
# Glog does not seem to provide any record of the version in its
# source tree, thus cannot extract version.
# Catch case when caller has set GLOG_INCLUDE_DIR in the cache / GUI and
# thus FIND_[PATH/LIBRARY] are not called, but specified locations are
# invalid, otherwise we would report the library as found.
if (GLOG_INCLUDE_DIR AND
NOT EXISTS ${GLOG_INCLUDE_DIR}/glog/logging.h)
glog_report_not_found(
"Caller defined GLOG_INCLUDE_DIR:"
" ${GLOG_INCLUDE_DIR} does not contain glog/logging.h header.")
endif (GLOG_INCLUDE_DIR AND
NOT EXISTS ${GLOG_INCLUDE_DIR}/glog/logging.h)
# TODO: This regex for glog library is pretty primitive, we use lowercase
# for comparison to handle Windows using CamelCase library names, could
# this check be better?
string(TOLOWER "${GLOG_LIBRARY}" LOWERCASE_GLOG_LIBRARY)
if (GLOG_LIBRARY AND
NOT "${LOWERCASE_GLOG_LIBRARY}" MATCHES ".*glog[^/]*")
glog_report_not_found(
"Caller defined GLOG_LIBRARY: "
"${GLOG_LIBRARY} does not match glog.")
endif (GLOG_LIBRARY AND
NOT "${LOWERCASE_GLOG_LIBRARY}" MATCHES ".*glog[^/]*")
# Set standard CMake FindPackage variables if found.
if (GLOG_FOUND)
set(GLOG_INCLUDE_DIRS ${GLOG_INCLUDE_DIR})
set(GLOG_LIBRARIES ${GLOG_LIBRARY})
endif (GLOG_FOUND)
glog_reset_find_library_prefix()
# Handle REQUIRED / QUIET optional arguments.
include(FindPackageHandleStandardArgs)
find_package_handle_standard_args(Glog DEFAULT_MSG
GLOG_INCLUDE_DIRS GLOG_LIBRARIES)
# Only mark internal variables as advanced if we found glog, otherwise
# leave them visible in the standard GUI for the user to set manually.
if (GLOG_FOUND)
mark_as_advanced(FORCE GLOG_INCLUDE_DIR
GLOG_LIBRARY)
endif (GLOG_FOUND)
================================================
FILE: demo/Test.cpp
================================================
#include <iostream>
#include <vector>
#include "time.h"
#include <Eigen/Core>
#include <Eigen/Geometry>
#include "Convert.h"
#include "EKF_Attitude.h"
#include "Mahony_Attitude.h"
#include "ESKF_Attitude.h"
#include "matplotlibcpp.h"
using namespace std;
using namespace IMU;
namespace plt = matplotlibcpp;
int main(int argc, char **argv)
{
Eigen::MatrixXd data, measurements, groundtruth;
data =IMU::readFromfile("./datasets/NAV2_data.bin");
if(data.isZero())
return 0;
const int Rows = data.rows() - 1;
measurements = data.block(0, 0, Rows, 9);
groundtruth = data.block(0, 9, Rows, 3)*180/M_PI;
IMU::EKF_Attitude EKF_AHRS(true, 0.02);
IMU::Mahony_Attitude Mahony(Eigen::Vector2d(1.0, 0), 0.02);
Eigen::Matrix<double, 12, 1> ESKF_InitVec;
ESKF_InitVec << 1e-5*Eigen::Vector3d::Ones(), 1e-9*Eigen::Vector3d::Ones(),
1e-3*Eigen::Vector3d::Ones(), 1e-4*Eigen::Vector3d::Ones();
IMU::ESKF_Attitude ESKF_AHRS(ESKF_InitVec, 0.02);
unsigned int i = 0;
Eigen::MatrixXd Euler(measurements.rows(), 3), Euler1(measurements.rows(), 3), Euler2(measurements.rows(), 3);
std::vector<double> Index, Roll, Pitch, Yaw, Roll_gt, Pitch_gt, Yaw_gt;
std::vector<double> Roll1, Pitch1, Yaw1, Roll_gt1, Pitch_gt1, Yaw_gt1;
std::vector<double> Roll2, Pitch2, Yaw2, Roll_gt2, Pitch_gt2, Yaw_gt2;
TicToc tc;
do
{
Eigen::MatrixXd measure;
Eigen::Quaterniond quaternion;
Vector_3 Euler_single;
quaternion = EKF_AHRS.Run(measurements.row(i).transpose());
Euler.row(i) = Quaternion_to_Euler(quaternion).transpose();
quaternion = Mahony.Run(measurements.row(i).transpose());
Euler1.row(i) = Quaternion_to_Euler(quaternion).transpose();
quaternion = ESKF_AHRS.Run(measurements.row(i).transpose());
Euler2.row(i) = Quaternion_to_Euler(quaternion).transpose();
Index.push_back(i*1.0);
Roll.push_back(Euler.row(i)[0]);
Pitch.push_back(Euler.row(i)[1]);
Yaw.push_back(Euler.row(i)[2]);
Roll1.push_back(Euler1.row(i)[0]);
Pitch1.push_back(Euler1.row(i)[1]);
Yaw1.push_back(Euler1.row(i)[2]);
Roll2.push_back(Euler2.row(i)[0]);
Pitch2.push_back(Euler2.row(i)[1]);
Yaw2.push_back(Euler2.row(i)[2]);
Roll_gt.push_back(groundtruth.row(i)[0]);
Pitch_gt.push_back(groundtruth.row(i)[1]);
Yaw_gt.push_back(groundtruth.row(i)[2]);
i++;
} while (i<measurements.rows());
cout << tc.toc() << "ms" << endl;
writeTofile(Euler, "Euler.bin");
plt::named_plot("EKF", Index, Pitch, "b");
plt::named_plot("ESKF", Index, Pitch2, "g");
plt::named_plot("Groundtruth", Index, Pitch_gt, "r");
//plt::named_plot("aa", Index, Yaw, "b");
plt::xlim(0, 1000*20);
plt::title("Yaw-Comparision");
plt::legend();
plt::show();
return 0;
}
================================================
FILE: include/Convert.h
================================================
#ifndef CONVERT_H_
#define CONVERT_H_
#include <iostream>
#include <vector>
#include <fstream>
#include <string>
#include <Eigen/Core>
#include <Eigen/Geometry>
#include "TypeDefs.h"
#include "tic_toc.h"
using namespace std;
namespace IMU
{
void Vect_to_SkewMat(Vector_3 Vector, Matrix_3 &Matrix);
void Angular_to_Mat(Vector_3 Vector, Eigen::Matrix<double, 4, 4> &Matrix);
//void Rotation_to_Qaut(Matrix_3 rotation, Eigen::Quaterniond &quat);
Vector_4 Quaternion_to_Vect(Eigen::Quaterniond q);
Eigen::Quaterniond QuatMult(Eigen::Quaterniond q1, Eigen::Quaterniond q2);
Matrix_3 Quat_to_Matrix(Eigen::Quaterniond q);
// Eigen IO
Eigen::MatrixXd readFromfile(const string file);
bool writeTofile(Eigen::MatrixXd matrix, const string file);
// Eluer(Rotate vector) to rotation matrix
Matrix_3 Euler_to_RoatMat(Vector_3 Euler);
// Eluer(Rotate vector) to rotation matrix
Eigen::Quaterniond Euler_to_Quaternion(Vector_3 Euler);
// Quaternion to eulers
Vector_3 Quaternion_to_Euler(Eigen::Quaterniond q);
// Rotation matrix to eulers, the rotation order is X-Y-Z(roll,pitch and yaw)
Vector_3 Rotation_to_Euler(Matrix_3 Rotation);
// Rotation matrix to quaternion http://www.cs.ucr.edu/~vbz/resources/quatut.pdf
Eigen::Quaterniond Rotation_to_Quater(Matrix_3 Rotation);
// Indirect Kalman Filter for 3D Attitude Estimation (Roumeliotis)
Eigen::Quaterniond BuildUpdateQuat(Eigen::Vector3d DeltaTheta);
} //namesapce IMU
#endif
================================================
FILE: include/EKF_Attitude.h
================================================
#ifndef EKF_ATTITUDE_H_
#define EKF_ATTITUDE_H_
#include <iostream>
#include <vector>
#include <mutex>
#include <Eigen/Core>
#include <Eigen/Geometry>
#include "TypeDefs.h"
#ifdef _WIN32
#include "windows.h"
#else
#include <unistd.h>
#endif
using namespace std;
namespace IMU
{
class EKF_Attitude
{
public:
EKF_Attitude(bool approx_prediction, double dt);
// Modify the params of the filter
void Param_Change(Vector_12 Pro_Nosiecovr, Vector_9 Mea_Nosiecovr);
// Calculate the transition matrix A
// refer to formula 4.19a
void Cal_TransMatrix();
/* The priori prediction:
* Xk+1 = F(Xk,0)
* Pk+1 = A*Pk*A' + Qk
*/
void Prior_Predict();
// The posteriori correction
void Post_Correct();
// Calculate the Euler angular
void Cal_Quaternion();
// read the sensors
void Read_SensorData(Vector_9 measurement);
Eigen::Quaterniond Run(Vector_9 measurement);
void Release();
void RequestStop();
void RequestStart();
bool Stop();
bool isStopped();
private:
Vector_9 cur_measurement;
bool using_2ndOrder;
Eigen::Matrix<double, 12, 12> Q_noise;
Eigen::Matrix<double, 9, 9> R_noise;
double deltaT;
Eigen::Matrix<double, 12, 12> Alin;
// Xk+1, the state vector of posteriori correction
vector< Vector_12 > state_X_pro;
// Xk, the state vector of priori prediction
Vector_12 state_X_par;
// Pk+1
vector< Eigen::Matrix<double, 12, 12> > CovrMatrix_P_pro;
// Pk
Eigen::Matrix<double, 12, 12> CovrMatrix_P_par;
vector< Eigen::Quaterniond > quaternion;
bool mbStopped;
bool mbStopRequested;
std::mutex mMutexStop;
};
} //namespace IMU
#endif
================================================
FILE: include/ESKF_Attitude.h
================================================
#ifndef ESKF_ATTITUDE_H
#define ESKF_ATTITUDE_H
#include <iostream>
#include <vector>
#include <mutex>
#include <map>
#include <Eigen/Core>
#include <Eigen/Geometry>
#include "TypeDefs.h"
#ifdef _WIN32
#include "windows.h"
#else
#include "unistd.h"
#endif
using namespace std;
namespace IMU
{
class ESKF_Attitude
{
public:
ESKF_Attitude(Vector_12 Covar_Mat, double dt);
// Initialize the true state of the estimator
// including the nomial state and the error state,
// and the covariances matrices
void Init_Estimator();
// change the parametres of the estimator
void Param_Change(Vector_12 Covar_Mat);
// Predict the nomial and error state
void NominaState_Predict();
void ErrorState_Predict();
// Update the filter parametres
void Update_Filter();
// Uptate the nominal state
void Update_NomianState();
// Reset the error state
void Reset_ErrorState();
// read the sensors data and normalize the accelerometer and magnetometer
void Read_SensorData(Vector_9 measurement);
Eigen::Quaterniond Run(Vector_9 measurement);
void Release();
void RequestStop();
void RequestStart();
bool Stop();
bool isStopped();
private:
// the Gaussian noise for the covariances matrices Q and R
Vector_3 DetAng_noise;
Vector_3 DetAngVel_noise;
Vector_3 Acc_noise;
Vector_3 Mag_noise;
Eigen::Matrix<double, 6, 6> CovarMat_Q;
Eigen::Matrix<double, 6, 6> CovarMat_R;
struct IMU_State
{
public:
//! normal state
Eigen::Quaterniond Nominal_quat; //! quaterion state
Vector_3 Nominal_AngVel; //! Gyro bias state
//! Error state
Vector_3 Error_theta;
Vector_3 Error_AngVel;
Eigen::Matrix<double, 6, 6> Error_Convar;
// calculate the observe matrix and the correction residual
Eigen::Matrix<double, 6, 6> Cal_ObserveMat(Vector_9 measurenment, Vector_6 &residual);
};
vector< IMU_State > State_Vector;
vector< Eigen::Quaterniond > quaternion;
// sample time
double deltaT;
// Current and last time measurement (gyro;acc;mag)
Vector_9 Cur_Measurement;
Vector_9 Last_Measurement;
bool mbStopped;
bool mbStopRequested;
std::mutex mMutexStop;
};
}
#endif
================================================
FILE: include/Mahony_Attitude.h
================================================
#ifndef MAHONY_AHRS_H_
#define MAHONY_AHRS_H_
#include <iostream>
#include <vector>
#include <mutex>
#include <Eigen/Core>
#include <Eigen/Geometry>
#include "TypeDefs.h"
#ifdef _WIN32
#include "windows.h"
#else
#include <unistd.h>
#endif
using namespace std;
namespace IMU
{
class Mahony_Attitude
{
public:
Mahony_Attitude(Vector_2 PI, double dt);
void Params_Change(Vector_2 PI, double dt);
void Mahony_Estimate();
void Read_SensorData(Vector_9 measurement);
Eigen::Quaterniond Run(Vector_9 measurement);
void Release();
void RequestStop();
void RequestStart();
bool Stop();
bool isStopped();
private:
Vector_9 cur_measurement;
double Kp, Ki;
double deltaT;
Vector_3 Integ_angular;
vector< Eigen::Quaterniond > quaternion;
bool mbStopped;
bool mbStopRequested;
std::mutex mMutexStop;
};
} //namesapce IMU
#endif
================================================
FILE: include/TypeDefs.h
================================================
#ifndef TYPEDEFS_H_
#define TYPEDEFS_H_
#include <iostream>
#include <Eigen/Core>
//#pragma once
namespace IMU
{
typedef Eigen::Matrix<double, 2, 1> Vector_2;
typedef Eigen::Matrix<double, 3, 1> Vector_3;
typedef Eigen::Matrix<double, 4, 1> Vector_4;
typedef Eigen::Matrix<double, 6, 1> Vector_6;
typedef Eigen::Matrix<double, 7, 1> Vector_7;
typedef Eigen::Matrix<double, 9, 1> Vector_9;
typedef Eigen::Matrix<double, 12, 1> Vector_12;
typedef Eigen::Matrix3d Matrix_3;
const Matrix_3 Zeros_Matrix3 = Matrix_3::Zero(3, 3);
const Matrix_3 Ones_Matrix3 = Matrix_3::Ones(3, 3);
const Matrix_3 Identity_Matrix3 = Matrix_3::Identity(3, 3);
} // namespace IMU
#endif
================================================
FILE: include/matplotlibcpp.h
================================================
#pragma once
#include <vector>
#include <map>
#include <numeric>
#include <algorithm>
#include <stdexcept>
#include <iostream>
#include <stdint.h> // <cstdint> requires c++11 support
#if __cplusplus > 199711L || _MSC_VER > 1800
# include <functional>
#endif
#include <Python.h>
#ifndef WITHOUT_NUMPY
# define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION
# include <numpy/arrayobject.h>
#endif // WITHOUT_NUMPY
#if PY_MAJOR_VERSION >= 3
# define PyString_FromString PyUnicode_FromString
#endif
namespace matplotlibcpp {
namespace detail {
static std::string s_backend;
struct _interpreter {
PyObject *s_python_function_show;
PyObject *s_python_function_close;
PyObject *s_python_function_draw;
PyObject *s_python_function_pause;
PyObject *s_python_function_save;
PyObject *s_python_function_figure;
PyObject *s_python_function_plot;
PyObject *s_python_function_semilogx;
PyObject *s_python_function_semilogy;
PyObject *s_python_function_loglog;
PyObject *s_python_function_fill_between;
PyObject *s_python_function_hist;
PyObject *s_python_function_subplot;
PyObject *s_python_function_legend;
PyObject *s_python_function_xlim;
PyObject *s_python_function_ion;
PyObject *s_python_function_ylim;
PyObject *s_python_function_title;
PyObject *s_python_function_axis;
PyObject *s_python_function_xlabel;
PyObject *s_python_function_ylabel;
PyObject *s_python_function_grid;
PyObject *s_python_function_clf;
PyObject *s_python_function_errorbar;
PyObject *s_python_function_annotate;
PyObject *s_python_function_tight_layout;
PyObject *s_python_empty_tuple;
PyObject *s_python_function_stem;
PyObject *s_python_function_xkcd;
/* For now, _interpreter is implemented as a singleton since its currently not possible to have
multiple independent embedded python interpreters without patching the python source code
or starting a separate process for each.
http://bytes.com/topic/python/answers/793370-multiple-independent-python-interpreters-c-c-program
*/
static _interpreter& get() {
static _interpreter ctx;
return ctx;
}
private:
#ifndef WITHOUT_NUMPY
# if PY_MAJOR_VERSION >= 3
void *import_numpy() {
import_array(); // initialize C-API
return NULL;
}
# else
void import_numpy() {
import_array(); // initialize C-API
}
# endif
#endif
_interpreter() {
// optional but recommended
#if PY_MAJOR_VERSION >= 3
wchar_t name[] = L"plotting";
#else
char name[] = "plotting";
#endif
Py_SetProgramName(name);
Py_Initialize();
#ifndef WITHOUT_NUMPY
import_numpy(); // initialize numpy C-API
#endif
PyObject* matplotlibname = PyString_FromString("matplotlib");
PyObject* pyplotname = PyString_FromString("matplotlib.pyplot");
PyObject* pylabname = PyString_FromString("pylab");
if (!pyplotname || !pylabname || !matplotlibname) {
throw std::runtime_error("couldnt create string");
}
PyObject* matplotlib = PyImport_Import(matplotlibname);
Py_DECREF(matplotlibname);
if (!matplotlib) { throw std::runtime_error("Error loading module matplotlib!"); }
// matplotlib.use() must be called *before* pylab, matplotlib.pyplot,
// or matplotlib.backends is imported for the first time
if (!s_backend.empty()) {
PyObject_CallMethod(matplotlib, const_cast<char*>("use"), const_cast<char*>("s"), s_backend.c_str());
}
PyObject* pymod = PyImport_Import(pyplotname);
Py_DECREF(pyplotname);
if (!pymod) { throw std::runtime_error("Error loading module matplotlib.pyplot!"); }
PyObject* pylabmod = PyImport_Import(pylabname);
Py_DECREF(pylabname);
if (!pylabmod) { throw std::runtime_error("Error loading module pylab!"); }
s_python_function_show = PyObject_GetAttrString(pymod, "show");
s_python_function_close = PyObject_GetAttrString(pymod, "close");
s_python_function_draw = PyObject_GetAttrString(pymod, "draw");
s_python_function_pause = PyObject_GetAttrString(pymod, "pause");
s_python_function_figure = PyObject_GetAttrString(pymod, "figure");
s_python_function_plot = PyObject_GetAttrString(pymod, "plot");
s_python_function_semilogx = PyObject_GetAttrString(pymod, "semilogx");
s_python_function_semilogy = PyObject_GetAttrString(pymod, "semilogy");
s_python_function_loglog = PyObject_GetAttrString(pymod, "loglog");
s_python_function_fill_between = PyObject_GetAttrString(pymod, "fill_between");
s_python_function_hist = PyObject_GetAttrString(pymod,"hist");
s_python_function_subplot = PyObject_GetAttrString(pymod, "subplot");
s_python_function_legend = PyObject_GetAttrString(pymod, "legend");
s_python_function_ylim = PyObject_GetAttrString(pymod, "ylim");
s_python_function_title = PyObject_GetAttrString(pymod, "title");
s_python_function_axis = PyObject_GetAttrString(pymod, "axis");
s_python_function_xlabel = PyObject_GetAttrString(pymod, "xlabel");
s_python_function_ylabel = PyObject_GetAttrString(pymod, "ylabel");
s_python_function_grid = PyObject_GetAttrString(pymod, "grid");
s_python_function_xlim = PyObject_GetAttrString(pymod, "xlim");
s_python_function_ion = PyObject_GetAttrString(pymod, "ion");
s_python_function_save = PyObject_GetAttrString(pylabmod, "savefig");
s_python_function_annotate = PyObject_GetAttrString(pymod,"annotate");
s_python_function_clf = PyObject_GetAttrString(pymod, "clf");
s_python_function_errorbar = PyObject_GetAttrString(pymod, "errorbar");
s_python_function_tight_layout = PyObject_GetAttrString(pymod, "tight_layout");
s_python_function_stem = PyObject_GetAttrString(pymod, "stem");
s_python_function_xkcd = PyObject_GetAttrString(pymod, "xkcd");
if( !s_python_function_show
|| !s_python_function_close
|| !s_python_function_draw
|| !s_python_function_pause
|| !s_python_function_figure
|| !s_python_function_plot
|| !s_python_function_semilogx
|| !s_python_function_semilogy
|| !s_python_function_loglog
|| !s_python_function_fill_between
|| !s_python_function_subplot
|| !s_python_function_legend
|| !s_python_function_ylim
|| !s_python_function_title
|| !s_python_function_axis
|| !s_python_function_xlabel
|| !s_python_function_ylabel
|| !s_python_function_grid
|| !s_python_function_xlim
|| !s_python_function_ion
|| !s_python_function_save
|| !s_python_function_clf
|| !s_python_function_annotate
|| !s_python_function_errorbar
|| !s_python_function_errorbar
|| !s_python_function_tight_layout
|| !s_python_function_stem
|| !s_python_function_xkcd
) { throw std::runtime_error("Couldn't find required function!"); }
if ( !PyFunction_Check(s_python_function_show)
|| !PyFunction_Check(s_python_function_close)
|| !PyFunction_Check(s_python_function_draw)
|| !PyFunction_Check(s_python_function_pause)
|| !PyFunction_Check(s_python_function_figure)
|| !PyFunction_Check(s_python_function_plot)
|| !PyFunction_Check(s_python_function_semilogx)
|| !PyFunction_Check(s_python_function_semilogy)
|| !PyFunction_Check(s_python_function_loglog)
|| !PyFunction_Check(s_python_function_fill_between)
|| !PyFunction_Check(s_python_function_subplot)
|| !PyFunction_Check(s_python_function_legend)
|| !PyFunction_Check(s_python_function_annotate)
|| !PyFunction_Check(s_python_function_ylim)
|| !PyFunction_Check(s_python_function_title)
|| !PyFunction_Check(s_python_function_axis)
|| !PyFunction_Check(s_python_function_xlabel)
|| !PyFunction_Check(s_python_function_ylabel)
|| !PyFunction_Check(s_python_function_grid)
|| !PyFunction_Check(s_python_function_xlim)
|| !PyFunction_Check(s_python_function_ion)
|| !PyFunction_Check(s_python_function_save)
|| !PyFunction_Check(s_python_function_clf)
|| !PyFunction_Check(s_python_function_tight_layout)
|| !PyFunction_Check(s_python_function_errorbar)
|| !PyFunction_Check(s_python_function_stem)
|| !PyFunction_Check(s_python_function_xkcd)
) { throw std::runtime_error("Python object is unexpectedly not a PyFunction."); }
s_python_empty_tuple = PyTuple_New(0);
}
~_interpreter() {
Py_Finalize();
}
};
} // end namespace detail
// must be called before the first regular call to matplotlib to have any effect
inline void backend(const std::string& name)
{
detail::s_backend = name;
}
inline bool annotate(std::string annotation, double x, double y)
{
PyObject * xy = PyTuple_New(2);
PyObject * str = PyString_FromString(annotation.c_str());
PyTuple_SetItem(xy,0,PyFloat_FromDouble(x));
PyTuple_SetItem(xy,1,PyFloat_FromDouble(y));
PyObject* kwargs = PyDict_New();
PyDict_SetItemString(kwargs, "xy", xy);
PyObject* args = PyTuple_New(1);
PyTuple_SetItem(args, 0, str);
PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_annotate, args, kwargs);
Py_DECREF(args);
Py_DECREF(kwargs);
if(res) Py_DECREF(res);
return res;
}
#ifndef WITHOUT_NUMPY
// Type selector for numpy array conversion
template <typename T> struct select_npy_type { const static NPY_TYPES type = NPY_NOTYPE; }; //Default
template <> struct select_npy_type<double> { const static NPY_TYPES type = NPY_DOUBLE; };
template <> struct select_npy_type<float> { const static NPY_TYPES type = NPY_FLOAT; };
template <> struct select_npy_type<bool> { const static NPY_TYPES type = NPY_BOOL; };
template <> struct select_npy_type<int8_t> { const static NPY_TYPES type = NPY_INT8; };
template <> struct select_npy_type<int16_t> { const static NPY_TYPES type = NPY_SHORT; };
template <> struct select_npy_type<int32_t> { const static NPY_TYPES type = NPY_INT; };
template <> struct select_npy_type<int64_t> { const static NPY_TYPES type = NPY_INT64; };
template <> struct select_npy_type<uint8_t> { const static NPY_TYPES type = NPY_UINT8; };
template <> struct select_npy_type<uint16_t> { const static NPY_TYPES type = NPY_USHORT; };
template <> struct select_npy_type<uint32_t> { const static NPY_TYPES type = NPY_ULONG; };
template <> struct select_npy_type<uint64_t> { const static NPY_TYPES type = NPY_UINT64; };
template<typename Numeric>
PyObject* get_array(const std::vector<Numeric>& v)
{
detail::_interpreter::get(); //interpreter needs to be initialized for the numpy commands to work
NPY_TYPES type = select_npy_type<Numeric>::type;
if (type == NPY_NOTYPE)
{
std::vector<double> vd(v.size());
npy_intp vsize = v.size();
std::copy(v.begin(),v.end(),vd.begin());
PyObject* varray = PyArray_SimpleNewFromData(1, &vsize, NPY_DOUBLE, (void*)(vd.data()));
return varray;
}
npy_intp vsize = v.size();
PyObject* varray = PyArray_SimpleNewFromData(1, &vsize, type, (void*)(v.data()));
return varray;
}
#else // fallback if we don't have numpy: copy every element of the given vector
template<typename Numeric>
PyObject* get_array(const std::vector<Numeric>& v)
{
PyObject* list = PyList_New(v.size());
for(size_t i = 0; i < v.size(); ++i) {
PyList_SetItem(list, i, PyFloat_FromDouble(v.at(i)));
}
return list;
}
#endif // WITHOUT_NUMPY
template<typename Numeric>
bool plot(const std::vector<Numeric> &x, const std::vector<Numeric> &y, const std::map<std::string, std::string>& keywords)
{
assert(x.size() == y.size());
// using numpy arrays
PyObject* xarray = get_array(x);
PyObject* yarray = get_array(y);
// construct positional args
PyObject* args = PyTuple_New(2);
PyTuple_SetItem(args, 0, xarray);
PyTuple_SetItem(args, 1, yarray);
// construct keyword args
PyObject* kwargs = PyDict_New();
for(std::map<std::string, std::string>::const_iterator it = keywords.begin(); it != keywords.end(); ++it)
{
PyDict_SetItemString(kwargs, it->first.c_str(), PyString_FromString(it->second.c_str()));
}
PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_plot, args, kwargs);
Py_DECREF(args);
Py_DECREF(kwargs);
if(res) Py_DECREF(res);
return res;
}
template<typename Numeric>
bool stem(const std::vector<Numeric> &x, const std::vector<Numeric> &y, const std::map<std::string, std::string>& keywords)
{
assert(x.size() == y.size());
// using numpy arrays
PyObject* xarray = get_array(x);
PyObject* yarray = get_array(y);
// construct positional args
PyObject* args = PyTuple_New(2);
PyTuple_SetItem(args, 0, xarray);
PyTuple_SetItem(args, 1, yarray);
// construct keyword args
PyObject* kwargs = PyDict_New();
for (std::map<std::string, std::string>::const_iterator it =
keywords.begin(); it != keywords.end(); ++it) {
PyDict_SetItemString(kwargs, it->first.c_str(),
PyString_FromString(it->second.c_str()));
}
PyObject* res = PyObject_Call(
detail::_interpreter::get().s_python_function_stem, args, kwargs);
Py_DECREF(args);
Py_DECREF(kwargs);
if (res)
Py_DECREF(res);
return res;
}
template< typename Numeric >
bool fill_between(const std::vector<Numeric>& x, const std::vector<Numeric>& y1, const std::vector<Numeric>& y2, const std::map<std::string, std::string>& keywords)
{
assert(x.size() == y1.size());
assert(x.size() == y2.size());
// using numpy arrays
PyObject* xarray = get_array(x);
PyObject* y1array = get_array(y1);
PyObject* y2array = get_array(y2);
// construct positional args
PyObject* args = PyTuple_New(3);
PyTuple_SetItem(args, 0, xarray);
PyTuple_SetItem(args, 1, y1array);
PyTuple_SetItem(args, 2, y2array);
// construct keyword args
PyObject* kwargs = PyDict_New();
for(std::map<std::string, std::string>::const_iterator it = keywords.begin(); it != keywords.end(); ++it)
{
PyDict_SetItemString(kwargs, it->first.c_str(), PyUnicode_FromString(it->second.c_str()));
}
PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_fill_between, args, kwargs);
Py_DECREF(args);
Py_DECREF(kwargs);
if(res) Py_DECREF(res);
return res;
}
template< typename Numeric>
bool hist(const std::vector<Numeric>& y, long bins=10,std::string color="b", double alpha=1.0)
{
PyObject* yarray = get_array(y);
PyObject* kwargs = PyDict_New();
PyDict_SetItemString(kwargs, "bins", PyLong_FromLong(bins));
PyDict_SetItemString(kwargs, "color", PyString_FromString(color.c_str()));
PyDict_SetItemString(kwargs, "alpha", PyFloat_FromDouble(alpha));
PyObject* plot_args = PyTuple_New(1);
PyTuple_SetItem(plot_args, 0, yarray);
PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_hist, plot_args, kwargs);
Py_DECREF(plot_args);
Py_DECREF(kwargs);
if(res) Py_DECREF(res);
return res;
}
template< typename Numeric>
bool named_hist(std::string label,const std::vector<Numeric>& y, long bins=10, std::string color="b", double alpha=1.0)
{
PyObject* yarray = get_array(y);
PyObject* kwargs = PyDict_New();
PyDict_SetItemString(kwargs, "label", PyString_FromString(label.c_str()));
PyDict_SetItemString(kwargs, "bins", PyLong_FromLong(bins));
PyDict_SetItemString(kwargs, "color", PyString_FromString(color.c_str()));
PyDict_SetItemString(kwargs, "alpha", PyFloat_FromDouble(alpha));
PyObject* plot_args = PyTuple_New(1);
PyTuple_SetItem(plot_args, 0, yarray);
PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_hist, plot_args, kwargs);
Py_DECREF(plot_args);
Py_DECREF(kwargs);
if(res) Py_DECREF(res);
return res;
}
template<typename NumericX, typename NumericY>
bool plot(const std::vector<NumericX>& x, const std::vector<NumericY>& y, const std::string& s = "")
{
assert(x.size() == y.size());
PyObject* xarray = get_array(x);
PyObject* yarray = get_array(y);
PyObject* pystring = PyString_FromString(s.c_str());
PyObject* plot_args = PyTuple_New(3);
PyTuple_SetItem(plot_args, 0, xarray);
PyTuple_SetItem(plot_args, 1, yarray);
PyTuple_SetItem(plot_args, 2, pystring);
PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_plot, plot_args);
Py_DECREF(plot_args);
if(res) Py_DECREF(res);
return res;
}
template<typename NumericX, typename NumericY>
bool stem(const std::vector<NumericX>& x, const std::vector<NumericY>& y, const std::string& s = "")
{
assert(x.size() == y.size());
PyObject* xarray = get_array(x);
PyObject* yarray = get_array(y);
PyObject* pystring = PyString_FromString(s.c_str());
PyObject* plot_args = PyTuple_New(3);
PyTuple_SetItem(plot_args, 0, xarray);
PyTuple_SetItem(plot_args, 1, yarray);
PyTuple_SetItem(plot_args, 2, pystring);
PyObject* res = PyObject_CallObject(
detail::_interpreter::get().s_python_function_stem, plot_args);
Py_DECREF(plot_args);
if (res)
Py_DECREF(res);
return res;
}
template<typename NumericX, typename NumericY>
bool semilogx(const std::vector<NumericX>& x, const std::vector<NumericY>& y, const std::string& s = "")
{
assert(x.size() == y.size());
PyObject* xarray = get_array(x);
PyObject* yarray = get_array(y);
PyObject* pystring = PyString_FromString(s.c_str());
PyObject* plot_args = PyTuple_New(3);
PyTuple_SetItem(plot_args, 0, xarray);
PyTuple_SetItem(plot_args, 1, yarray);
PyTuple_SetItem(plot_args, 2, pystring);
PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_semilogx, plot_args);
Py_DECREF(plot_args);
if(res) Py_DECREF(res);
return res;
}
template<typename NumericX, typename NumericY>
bool semilogy(const std::vector<NumericX>& x, const std::vector<NumericY>& y, const std::string& s = "")
{
assert(x.size() == y.size());
PyObject* xarray = get_array(x);
PyObject* yarray = get_array(y);
PyObject* pystring = PyString_FromString(s.c_str());
PyObject* plot_args = PyTuple_New(3);
PyTuple_SetItem(plot_args, 0, xarray);
PyTuple_SetItem(plot_args, 1, yarray);
PyTuple_SetItem(plot_args, 2, pystring);
PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_semilogy, plot_args);
Py_DECREF(plot_args);
if(res) Py_DECREF(res);
return res;
}
template<typename NumericX, typename NumericY>
bool loglog(const std::vector<NumericX>& x, const std::vector<NumericY>& y, const std::string& s = "")
{
assert(x.size() == y.size());
PyObject* xarray = get_array(x);
PyObject* yarray = get_array(y);
PyObject* pystring = PyString_FromString(s.c_str());
PyObject* plot_args = PyTuple_New(3);
PyTuple_SetItem(plot_args, 0, xarray);
PyTuple_SetItem(plot_args, 1, yarray);
PyTuple_SetItem(plot_args, 2, pystring);
PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_loglog, plot_args);
Py_DECREF(plot_args);
if(res) Py_DECREF(res);
return res;
}
template<typename NumericX, typename NumericY>
bool errorbar(const std::vector<NumericX> &x, const std::vector<NumericY> &y, const std::vector<NumericX> &yerr, const std::string &s = "")
{
assert(x.size() == y.size());
PyObject* xarray = get_array(x);
PyObject* yarray = get_array(y);
PyObject* yerrarray = get_array(yerr);
PyObject *kwargs = PyDict_New();
PyDict_SetItemString(kwargs, "yerr", yerrarray);
PyObject *pystring = PyString_FromString(s.c_str());
PyObject *plot_args = PyTuple_New(2);
PyTuple_SetItem(plot_args, 0, xarray);
PyTuple_SetItem(plot_args, 1, yarray);
PyObject *res = PyObject_Call(detail::_interpreter::get().s_python_function_errorbar, plot_args, kwargs);
Py_DECREF(kwargs);
Py_DECREF(plot_args);
if (res)
Py_DECREF(res);
else
throw std::runtime_error("Call to errorbar() failed.");
return res;
}
template<typename Numeric>
bool named_plot(const std::string& name, const std::vector<Numeric>& y, const std::string& format = "")
{
PyObject* kwargs = PyDict_New();
PyDict_SetItemString(kwargs, "label", PyString_FromString(name.c_str()));
PyObject* yarray = get_array(y);
PyObject* pystring = PyString_FromString(format.c_str());
PyObject* plot_args = PyTuple_New(2);
PyTuple_SetItem(plot_args, 0, yarray);
PyTuple_SetItem(plot_args, 1, pystring);
PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_plot, plot_args, kwargs);
Py_DECREF(kwargs);
Py_DECREF(plot_args);
if (res) Py_DECREF(res);
return res;
}
template<typename Numeric>
bool named_plot(const std::string& name, const std::vector<Numeric>& x, const std::vector<Numeric>& y, const std::string& format = "")
{
PyObject* kwargs = PyDict_New();
PyDict_SetItemString(kwargs, "label", PyString_FromString(name.c_str()));
PyObject* xarray = get_array(x);
PyObject* yarray = get_array(y);
PyObject* pystring = PyString_FromString(format.c_str());
PyObject* plot_args = PyTuple_New(3);
PyTuple_SetItem(plot_args, 0, xarray);
PyTuple_SetItem(plot_args, 1, yarray);
PyTuple_SetItem(plot_args, 2, pystring);
PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_plot, plot_args, kwargs);
Py_DECREF(kwargs);
Py_DECREF(plot_args);
if (res) Py_DECREF(res);
return res;
}
template<typename Numeric>
bool named_semilogx(const std::string& name, const std::vector<Numeric>& x, const std::vector<Numeric>& y, const std::string& format = "")
{
PyObject* kwargs = PyDict_New();
PyDict_SetItemString(kwargs, "label", PyString_FromString(name.c_str()));
PyObject* xarray = get_array(x);
PyObject* yarray = get_array(y);
PyObject* pystring = PyString_FromString(format.c_str());
PyObject* plot_args = PyTuple_New(3);
PyTuple_SetItem(plot_args, 0, xarray);
PyTuple_SetItem(plot_args, 1, yarray);
PyTuple_SetItem(plot_args, 2, pystring);
PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_semilogx, plot_args, kwargs);
Py_DECREF(kwargs);
Py_DECREF(plot_args);
if (res) Py_DECREF(res);
return res;
}
template<typename Numeric>
bool named_semilogy(const std::string& name, const std::vector<Numeric>& x, const std::vector<Numeric>& y, const std::string& format = "")
{
PyObject* kwargs = PyDict_New();
PyDict_SetItemString(kwargs, "label", PyString_FromString(name.c_str()));
PyObject* xarray = get_array(x);
PyObject* yarray = get_array(y);
PyObject* pystring = PyString_FromString(format.c_str());
PyObject* plot_args = PyTuple_New(3);
PyTuple_SetItem(plot_args, 0, xarray);
PyTuple_SetItem(plot_args, 1, yarray);
PyTuple_SetItem(plot_args, 2, pystring);
PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_semilogy, plot_args, kwargs);
Py_DECREF(kwargs);
Py_DECREF(plot_args);
if (res) Py_DECREF(res);
return res;
}
template<typename Numeric>
bool named_loglog(const std::string& name, const std::vector<Numeric>& x, const std::vector<Numeric>& y, const std::string& format = "")
{
PyObject* kwargs = PyDict_New();
PyDict_SetItemString(kwargs, "label", PyString_FromString(name.c_str()));
PyObject* xarray = get_array(x);
PyObject* yarray = get_array(y);
PyObject* pystring = PyString_FromString(format.c_str());
PyObject* plot_args = PyTuple_New(3);
PyTuple_SetItem(plot_args, 0, xarray);
PyTuple_SetItem(plot_args, 1, yarray);
PyTuple_SetItem(plot_args, 2, pystring);
PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_loglog, plot_args, kwargs);
Py_DECREF(kwargs);
Py_DECREF(plot_args);
if (res) Py_DECREF(res);
return res;
}
template<typename Numeric>
bool plot(const std::vector<Numeric>& y, const std::string& format = "")
{
std::vector<Numeric> x(y.size());
for(size_t i=0; i<x.size(); ++i) x.at(i) = i;
return plot(x,y,format);
}
template<typename Numeric>
bool stem(const std::vector<Numeric>& y, const std::string& format = "")
{
std::vector<Numeric> x(y.size());
for (size_t i = 0; i < x.size(); ++i) x.at(i) = i;
return stem(x, y, format);
}
inline void figure()
{
PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_figure, detail::_interpreter::get().s_python_empty_tuple);
if(!res) throw std::runtime_error("Call to figure() failed.");
Py_DECREF(res);
}
inline void legend()
{
PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_legend, detail::_interpreter::get().s_python_empty_tuple);
if(!res) throw std::runtime_error("Call to legend() failed.");
Py_DECREF(res);
}
template<typename Numeric>
void ylim(Numeric left, Numeric right)
{
PyObject* list = PyList_New(2);
PyList_SetItem(list, 0, PyFloat_FromDouble(left));
PyList_SetItem(list, 1, PyFloat_FromDouble(right));
PyObject* args = PyTuple_New(1);
PyTuple_SetItem(args, 0, list);
PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_ylim, args);
if(!res) throw std::runtime_error("Call to ylim() failed.");
Py_DECREF(args);
Py_DECREF(res);
}
template<typename Numeric>
void xlim(Numeric left, Numeric right)
{
PyObject* list = PyList_New(2);
PyList_SetItem(list, 0, PyFloat_FromDouble(left));
PyList_SetItem(list, 1, PyFloat_FromDouble(right));
PyObject* args = PyTuple_New(1);
PyTuple_SetItem(args, 0, list);
PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_xlim, args);
if(!res) throw std::runtime_error("Call to xlim() failed.");
Py_DECREF(args);
Py_DECREF(res);
}
inline double* xlim()
{
PyObject* args = PyTuple_New(0);
PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_xlim, args);
PyObject* left = PyTuple_GetItem(res,0);
PyObject* right = PyTuple_GetItem(res,1);
double* arr = new double[2];
arr[0] = PyFloat_AsDouble(left);
arr[1] = PyFloat_AsDouble(right);
if(!res) throw std::runtime_error("Call to xlim() failed.");
Py_DECREF(res);
return arr;
}
inline double* ylim()
{
PyObject* args = PyTuple_New(0);
PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_ylim, args);
PyObject* left = PyTuple_GetItem(res,0);
PyObject* right = PyTuple_GetItem(res,1);
double* arr = new double[2];
arr[0] = PyFloat_AsDouble(left);
arr[1] = PyFloat_AsDouble(right);
if(!res) throw std::runtime_error("Call to ylim() failed.");
Py_DECREF(res);
return arr;
}
inline void subplot(long nrows, long ncols, long plot_number)
{
// construct positional args
PyObject* args = PyTuple_New(3);
PyTuple_SetItem(args, 0, PyFloat_FromDouble(nrows));
PyTuple_SetItem(args, 1, PyFloat_FromDouble(ncols));
PyTuple_SetItem(args, 2, PyFloat_FromDouble(plot_number));
PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_subplot, args);
if(!res) throw std::runtime_error("Call to subplot() failed.");
Py_DECREF(args);
Py_DECREF(res);
}
inline void title(const std::string &titlestr)
{
PyObject* pytitlestr = PyString_FromString(titlestr.c_str());
PyObject* args = PyTuple_New(1);
PyTuple_SetItem(args, 0, pytitlestr);
PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_title, args);
if(!res) throw std::runtime_error("Call to title() failed.");
Py_DECREF(args);
Py_DECREF(res);
}
inline void axis(const std::string &axisstr)
{
PyObject* str = PyString_FromString(axisstr.c_str());
PyObject* args = PyTuple_New(1);
PyTuple_SetItem(args, 0, str);
PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_axis, args);
if(!res) throw std::runtime_error("Call to title() failed.");
Py_DECREF(args);
Py_DECREF(res);
}
inline void xlabel(const std::string &str)
{
PyObject* pystr = PyString_FromString(str.c_str());
PyObject* args = PyTuple_New(1);
PyTuple_SetItem(args, 0, pystr);
PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_xlabel, args);
if(!res) throw std::runtime_error("Call to xlabel() failed.");
Py_DECREF(args);
Py_DECREF(res);
}
inline void ylabel(const std::string &str)
{
PyObject* pystr = PyString_FromString(str.c_str());
PyObject* args = PyTuple_New(1);
PyTuple_SetItem(args, 0, pystr);
PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_ylabel, args);
if(!res) throw std::runtime_error("Call to ylabel() failed.");
Py_DECREF(args);
Py_DECREF(res);
}
inline void grid(bool flag)
{
PyObject* pyflag = flag ? Py_True : Py_False;
Py_INCREF(pyflag);
PyObject* args = PyTuple_New(1);
PyTuple_SetItem(args, 0, pyflag);
PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_grid, args);
if(!res) throw std::runtime_error("Call to grid() failed.");
Py_DECREF(args);
Py_DECREF(res);
}
inline void show(const bool block = true)
{
PyObject* res;
if(block)
{
res = PyObject_CallObject(
detail::_interpreter::get().s_python_function_show,
detail::_interpreter::get().s_python_empty_tuple);
}
else
{
PyObject *kwargs = PyDict_New();
PyDict_SetItemString(kwargs, "block", Py_False);
res = PyObject_Call( detail::_interpreter::get().s_python_function_show, detail::_interpreter::get().s_python_empty_tuple, kwargs);
Py_DECREF(kwargs);
}
if (!res) throw std::runtime_error("Call to show() failed.");
Py_DECREF(res);
}
inline void close()
{
PyObject* res = PyObject_CallObject(
detail::_interpreter::get().s_python_function_close,
detail::_interpreter::get().s_python_empty_tuple);
if (!res) throw std::runtime_error("Call to close() failed.");
Py_DECREF(res);
}
inline void xkcd() {
PyObject* res;
PyObject *kwargs = PyDict_New();
res = PyObject_Call(detail::_interpreter::get().s_python_function_xkcd,
detail::_interpreter::get().s_python_empty_tuple, kwargs);
Py_DECREF(kwargs);
if (!res)
throw std::runtime_error("Call to show() failed.");
Py_DECREF(res);
}
inline void draw()
{
PyObject* res = PyObject_CallObject(
detail::_interpreter::get().s_python_function_draw,
detail::_interpreter::get().s_python_empty_tuple);
if (!res) throw std::runtime_error("Call to draw() failed.");
Py_DECREF(res);
}
template<typename Numeric>
inline void pause(Numeric interval)
{
PyObject* args = PyTuple_New(1);
PyTuple_SetItem(args, 0, PyFloat_FromDouble(interval));
PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_pause, args);
if(!res) throw std::runtime_error("Call to pause() failed.");
Py_DECREF(args);
Py_DECREF(res);
}
inline void save(const std::string& filename)
{
PyObject* pyfilename = PyString_FromString(filename.c_str());
PyObject* args = PyTuple_New(1);
PyTuple_SetItem(args, 0, pyfilename);
PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_save, args);
if (!res) throw std::runtime_error("Call to save() failed.");
Py_DECREF(args);
Py_DECREF(res);
}
inline void clf() {
PyObject *res = PyObject_CallObject(
detail::_interpreter::get().s_python_function_clf,
detail::_interpreter::get().s_python_empty_tuple);
if (!res) throw std::runtime_error("Call to clf() failed.");
Py_DECREF(res);
}
inline void ion() {
PyObject *res = PyObject_CallObject(
detail::_interpreter::get().s_python_function_ion,
detail::_interpreter::get().s_python_empty_tuple);
if (!res) throw std::runtime_error("Call to ion() failed.");
Py_DECREF(res);
}
// Actually, is there any reason not to call this automatically for every plot?
inline void tight_layout() {
PyObject *res = PyObject_CallObject(
detail::_interpreter::get().s_python_function_tight_layout,
detail::_interpreter::get().s_python_empty_tuple);
if (!res) throw std::runtime_error("Call to tight_layout() failed.");
Py_DECREF(res);
}
#if __cplusplus > 199711L || _MSC_VER > 1800
// C++11-exclusive content starts here (variadic plot() and initializer list support)
namespace detail {
template<typename T>
using is_function = typename std::is_function<std::remove_pointer<std::remove_reference<T>>>::type;
template<bool obj, typename T>
struct is_callable_impl;
template<typename T>
struct is_callable_impl<false, T>
{
typedef is_function<T> type;
}; // a non-object is callable iff it is a function
template<typename T>
struct is_callable_impl<true, T>
{
struct Fallback { void operator()(); };
struct Derived : T, Fallback { };
template<typename U, U> struct Check;
template<typename U>
static std::true_type test( ... ); // use a variadic function to make sure (1) it accepts everything and (2) its always the worst match
template<typename U>
static std::false_type test( Check<void(Fallback::*)(), &U::operator()>* );
public:
typedef decltype(test<Derived>(nullptr)) type;
typedef decltype(&Fallback::operator()) dtype;
static constexpr bool value = type::value;
}; // an object is callable iff it defines operator()
template<typename T>
struct is_callable
{
// dispatch to is_callable_impl<true, T> or is_callable_impl<false, T> depending on whether T is of class type or not
typedef typename is_callable_impl<std::is_class<T>::value, T>::type type;
};
template<typename IsYDataCallable>
struct plot_impl { };
template<>
struct plot_impl<std::false_type>
{
template<typename IterableX, typename IterableY>
bool operator()(const IterableX& x, const IterableY& y, const std::string& format)
{
// 2-phase lookup for distance, begin, end
using std::distance;
using std::begin;
using std::end;
auto xs = distance(begin(x), end(x));
auto ys = distance(begin(y), end(y));
assert(xs == ys && "x and y data must have the same number of elements!");
PyObject* xlist = PyList_New(xs);
PyObject* ylist = PyList_New(ys);
PyObject* pystring = PyString_FromString(format.c_str());
auto itx = begin(x), ity = begin(y);
for(size_t i = 0; i < xs; ++i) {
PyList_SetItem(xlist, i, PyFloat_FromDouble(*itx++));
PyList_SetItem(ylist, i, PyFloat_FromDouble(*ity++));
}
PyObject* plot_args = PyTuple_New(3);
PyTuple_SetItem(plot_args, 0, xlist);
PyTuple_SetItem(plot_args, 1, ylist);
PyTuple_SetItem(plot_args, 2, pystring);
PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_plot, plot_args);
Py_DECREF(plot_args);
if(res) Py_DECREF(res);
return res;
}
};
template<>
struct plot_impl<std::true_type>
{
template<typename Iterable, typename Callable>
bool operator()(const Iterable& ticks, const Callable& f, const std::string& format)
{
if(begin(ticks) == end(ticks)) return true;
// We could use additional meta-programming to deduce the correct element type of y,
// but all values have to be convertible to double anyways
std::vector<double> y;
for(auto x : ticks) y.push_back(f(x));
return plot_impl<std::false_type>()(ticks,y,format);
}
};
} // end namespace detail
// recursion stop for the above
template<typename... Args>
bool plot() { return true; }
template<typename A, typename B, typename... Args>
bool plot(const A& a, const B& b, const std::string& format, Args... args)
{
return detail::plot_impl<typename detail::is_callable<B>::type>()(a,b,format) && plot(args...);
}
/*
* This group of plot() functions is needed to support initializer lists, i.e. calling
* plot( {1,2,3,4} )
*/
inline bool plot(const std::vector<double>& x, const std::vector<double>& y, const std::string& format = "")
{
return plot<double,double>(x,y,format);
}
inline bool plot(const std::vector<double>& y, const std::string& format = "") {
return plot<double>(y,format);
}
inline bool plot(const std::vector<double>& x, const std::vector<double>& y, const std::map<std::string, std::string>& keywords) {
return plot<double>(x,y,keywords);
}
#endif
} // end namespace matplotlibcpp
================================================
FILE: include/tic_toc.h
================================================
//
// Created by buyi on 18-1-28.
//
#ifndef IMU_ATTITUDE_ESTIMATOR_TIC_TOC_H_H
#define IMU_ATTITUDE_ESTIMATOR_TIC_TOC_H_H
#include <ctime>
#include <cstdlib>
#include <chrono>
namespace IMU
{
class TicToc
{
public:
TicToc()
{
tic();
}
void tic()
{
start = std::chrono::system_clock::now();
}
double toc() //ms
{
end = std::chrono::system_clock::now();
std::chrono::duration<double> elapsed_seconds = end - start;
return elapsed_seconds.count()*1000;
}
private:
std::chrono::time_point <std::chrono::system_clock> start, end;
};
} //namesapce IMU
#endif //IMU_ATTITUDE_ESTIMATOR_TIC_TOC_H_H
================================================
FILE: src/Convert.cpp
================================================
#include "Convert.h"
#include "TypeDefs.h"
#include <fstream>
namespace IMU
{
void Vect_to_SkewMat(Vector_3 Vector, Matrix_3 &Matrix)
{
Matrix << 0, -Vector(2), Vector(1),
Vector(2), 0, -Vector(0),
-Vector(1), Vector(0), 0;
}
void Angular_to_Mat(Vector_3 Vector, Eigen::Matrix<double, 4, 4> &Matrix)
{
Matrix << 0, -Vector(0), -Vector(1), -Vector(2),
Vector(0), 0, Vector(2), -Vector(1),
Vector(1), -Vector(2), 0, Vector(0),
Vector(2), Vector(1), -Vector(0), 0;
}
Vector_4 Quaternion_to_Vect(Eigen::Quaterniond q)
{
Vector_4 vector;
vector(0) = q.w();
vector.block<3, 1>(1, 0) = q.vec();
return vector;
}
Eigen::Quaterniond QuatMult(Eigen::Quaterniond q1, Eigen::Quaterniond q2)
{
Eigen::Quaterniond resultQ;
resultQ.setIdentity();
resultQ.w() = q1.w() * q2.w() - q1.vec().dot(q2.vec());
resultQ.vec() = q1.w() * q2.vec() + q2.w() * q1.vec() + q1.vec().cross(q2.vec());
return resultQ;
}
Matrix_3 Quat_to_Matrix(Eigen::Quaterniond q)
{
Matrix_3 matrix;
matrix << q.w()*q.w() + q.x()*q.x() - q.y()*q.y() - q.z()*q.z(), 2 * (q.x()*q.y() - q.w()*q.z()), 2 * (q.x()*q.z() + q.w()*q.y()),
2 * (q.x()*q.y() + q.w()*q.z()), q.w()*q.w() - q.x()*q.x() + q.y()*q.y() - q.z()*q.z(), 2 * (q.y()*q.z() - q.w()*q.x()),
2 * (q.x()*q.z() - q.w()*q.y()), 2 * (q.y()*q.z() + q.w()*q.x()), q.w()*q.w() - q.x()*q.x() - q.y()*q.y() + q.z()*q.z();
return matrix;
}
Eigen::MatrixXd readFromfile(const string file_name)
{
Eigen::MatrixXd matrix;
std::vector<double> entries;
ifstream data(file_name, ios::binary);
string lineOfData;
if (data.is_open())
{
int i = 0;
int cols = 0;
while (data.good())
{
int j = 0;
getline(data, lineOfData);
stringstream stream(lineOfData);
while (!stream.eof())
{
double a;
stream >> a;
entries.push_back(a);
j++;
}
cols = j;
i++;
}
matrix = Eigen::MatrixXd::Map(&entries[0], cols, i).transpose();
return matrix;
}
else
{
cout << "Unable to open file" << std::endl;
return Eigen::Vector3d::Zero();
}
}
bool writeTofile(Eigen::MatrixXd matrix, const string file_name)
{
std::ofstream file(file_name, ios::binary);
if (file.is_open())
{
file << matrix << '\n';
}
else
return false;
file.close();
return true;
}
Matrix_3 Euler_to_RoatMat(Vector_3 Euler)
{
Matrix_3 Rotate_Mat;
double theta;
Matrix_3 Skew_Euler;
theta = Euler.norm();
Euler.normalize();
Vect_to_SkewMat(Euler, Skew_Euler);
Rotate_Mat = Matrix_3::Identity() + sin(theta)*Skew_Euler + (1 - cos(theta))*Skew_Euler.transpose()*Skew_Euler;
return Rotate_Mat;
}
Eigen::Quaterniond Euler_to_Quaternion(Vector_3 Euler)
{
Eigen::Quaterniond quaternion;
/*
double theta = sqrt(Euler(0)*Euler(0) + Euler(1)*Euler(1) + Euler(2)*Euler(2));
Euler.normalize();
quaternion.w() = cos(0.5*theta);
quaternion.vec() = Euler*sin(0.5*theta);
*/
// using Eigen
/*
quaternion = Eigen::AngleAxisd(Euler(0), Eigen::Vector3d::UnitX())
* Eigen::AngleAxisd(Euler(1), Eigen::Vector3d::UnitY())
*Eigen::AngleAxisd(Euler(2), Eigen::Vector3d::UnitZ());
*/
double CosRoll = cos(Euler[0] * 0.5);
double SinRoll = sin(Euler[0] * 0.5);
double CosPitch = cos(Euler[1] * 0.5);
double SinPitch = sin(Euler[1] * 0.5);
double CosYaw = cos(Euler[2] * 0.5);
double SinYaw = sin(Euler[2] * 0.5);
double w = CosRoll*CosPitch*CosYaw + SinRoll*SinPitch*SinYaw;
double x = CosPitch*SinRoll*CosYaw - CosRoll*SinPitch*SinYaw;
double y = CosRoll*CosYaw*SinPitch + SinRoll*CosPitch*SinYaw;
double z = CosRoll*CosPitch*SinYaw - CosYaw*SinPitch*SinRoll;
quaternion = Eigen::Quaterniond(w, x, y, z);
return quaternion;
}
Vector_3 Quaternion_to_Euler(Eigen::Quaterniond q)
{
Vector_3 Euler;
// the normal way
Euler(0) = atan2(2 * (q.y()*q.z() + q.w()*q.x()), (q.w()*q.w() - q.x()*q.x() - q.y()*q.y() + q.z()*q.z()));
Euler(1) = asin(-2 * q.x()*q.z() + 2 * q.w()*q.y());
Euler(2) = atan2(2 * (q.x()*q.y() + q.w()*q.z()), (q.w()*q.w() + q.x()*q.x() - q.y()*q.y() - q.z()*q.z())) - 8.3*M_PI/180;
/*
// using the eigen
q.normalize();
Euler = q.toRotationMatrix().eulerAngles(0, 1, 2);
*/
return Euler*180/M_PI;
}
Vector_3 Rotation_to_Euler(Matrix_3 Rotation)
{
Vector_3 Euler;
Euler(0) = atan2(Rotation(1, 2), Rotation(2, 2));
Euler(1) = -asin(Rotation(0, 2));
Euler(2) = atan2(Rotation(0, 1), Rotation(0, 0));
return Euler;
}
Eigen::Quaterniond Rotation_to_Quater(Matrix_3 Rotation)
{
Eigen::Quaterniond quaternion;
Vector_4 quat_tmp;
double tr;
tr = Rotation.trace();
if (tr > 0.0)
{
double s = sqrtf(tr + 1.0);
quat_tmp(0) = s*0.5;
s = 0.5 / s;
quat_tmp(1) = (Rotation(2, 1) - Rotation(1, 2))*s;
quat_tmp(2) = (Rotation(0, 2) - Rotation(2, 0))*s;
quat_tmp(3) = (Rotation(1, 0) - Rotation(0, 1))*s;
}
else
{
int dcm_i = 0;
for (int i = 1; i < 3; i++)
{
if (Rotation(i, i) > Rotation(dcm_i, dcm_i))
dcm_i = i;
}
int dcm_j = (dcm_i + 1) % 3;
int dcm_k = (dcm_i + 2) % 3;
double s = sqrtf((Rotation(dcm_i, dcm_i) - Rotation(dcm_j, dcm_j) -
Rotation(dcm_k, dcm_k)) + 1.0f);
quat_tmp(dcm_i + 1) = s*0.5;
s = 0.5 / s;
quat_tmp(dcm_j + 1) = (Rotation(dcm_i, dcm_j) + Rotation(dcm_j, dcm_i)) * s;
quat_tmp[dcm_k + 1] = (Rotation(dcm_k, dcm_i) + Rotation(dcm_i, dcm_k)) * s;
quat_tmp[0] = (Rotation(dcm_k, dcm_j) - Rotation(dcm_j, dcm_k)) * s;
}
quaternion.w() = quat_tmp(0);
quaternion.vec() = quat_tmp.block<3, 1>(1, 0);
return quaternion;
}
Eigen::Quaterniond BuildUpdateQuat(Eigen::Vector3d DeltaTheta)
{
Eigen::Vector3d DeltaQuat = 0.5*DeltaTheta;
double checknorm = DeltaQuat.transpose()*DeltaQuat;
Eigen::Quaterniond UpdateQuat;
if (checknorm > 1)
{
UpdateQuat = Eigen::Quaterniond(1, DeltaQuat[0], DeltaQuat[1], DeltaQuat[2]);
UpdateQuat = UpdateQuat.coeffs()*sqrt(1 + checknorm);
}
else
UpdateQuat = Eigen::Quaterniond(sqrt(1 - checknorm), DeltaQuat[0], DeltaQuat[1], DeltaQuat[2]);
UpdateQuat.normalize();
return UpdateQuat;
}
} //IMU
================================================
FILE: src/EKF_Attitude.cpp
================================================
#include "EKF_Attitude.h"
#include "Convert.h"
using namespace std;
namespace IMU
{
EKF_Attitude::EKF_Attitude(bool approx_prediction, double dt):
mbStopped(false), mbStopRequested(false), deltaT(dt)
{
cout << "System initialization!" << endl;
/* Set the primary value of state vector and covariance matrix */
if (state_X_pro.size() == 0)
{
Vector_12 state_X_tmp;
/*
state_X_tmp << 0.0018, -0.0003, 0.0015,
0.0351, -0.0567, -0.0364,
0.0093, -0.0012, -0.9998,
0.0089, 0.4784, 0.8781;
*/
state_X_tmp << 0.0, -0.0, 0.0,
0.0, -0.0, -0.0,
0.0, -0.0, -0.9998,
0.0, 0.0, 1;
state_X_pro.push_back(state_X_tmp);
}
if (CovrMatrix_P_pro.size()==0)
{
// CovrMatrix_P_pro.push_back(Eigen::MatrixXd::Ones(12, 12) * 200);
Vector_3 V1(0, 0, 0.0001);
Vector_3 V2(0, 0.0001, -0.0001);
Matrix_3 M1, M2;
Vect_to_SkewMat(V1, M1);
Vect_to_SkewMat(V2, M2);
Eigen::Matrix<double, 12, 12> CovrMatrix_tmp;
CovrMatrix_tmp << 0.004*Identity_Matrix3, 0.056*Identity_Matrix3, Zeros_Matrix3, Zeros_Matrix3,
0.056*Identity_Matrix3, 0.2971*Identity_Matrix3, M1, M2,
Zeros_Matrix3, -M1, 2.9956*Identity_Matrix3, Zeros_Matrix3,
Zeros_Matrix3, -M2, Zeros_Matrix3, 0.7046*Identity_Matrix3;
CovrMatrix_P_pro.push_back(CovrMatrix_tmp);
}
using_2ndOrder = approx_prediction;
// set the process noise as the diagnoal of elements
Vector_12 Pro_Nosiecovr;
Vector_9 Mea_Nosiecovr;
Pro_Nosiecovr << 1e-4, 1e-4, 1e-4,
0.08, 0.08, 0.08,
0.009, 0.009, 0.009,
0.005, 0.005, 0.005;
Mea_Nosiecovr << 0.0008, 0.0008, 0.0008,
1000, 1000, 1000,
100, 100, 100;
Q_noise = Pro_Nosiecovr.asDiagonal();
R_noise = Mea_Nosiecovr.asDiagonal();
}
void EKF_Attitude::Param_Change(Vector_12 Pro_Nosiecovr, Vector_9 Mea_Nosiecovr)
{
if (isStopped())
{
Q_noise = Pro_Nosiecovr.asDiagonal();
R_noise = Mea_Nosiecovr.asDiagonal();
}
}
void EKF_Attitude::Cal_TransMatrix()
{
Matrix_3 r_acc, r_mag, w_angular, w_angular_T;
Vector_3 r_acc_v, r_mag_v, w_angular_v;
Vector_12 state_X_tmp;
state_X_tmp = state_X_pro.back();
w_angular_v = state_X_tmp.block<3, 1>(0, 0);
r_acc_v = state_X_tmp.block<3, 1>(6, 0);
r_mag_v = state_X_tmp.block<3, 1>(9, 0);
Vect_to_SkewMat(w_angular_v, w_angular_T);
w_angular = w_angular_T.transpose();
Vect_to_SkewMat(r_acc_v, r_acc);
Vect_to_SkewMat(r_mag_v, r_mag);
Alin << Zeros_Matrix3, Identity_Matrix3, Zeros_Matrix3, Zeros_Matrix3,
Zeros_Matrix3, Zeros_Matrix3, Zeros_Matrix3, Zeros_Matrix3,
r_acc, Zeros_Matrix3, w_angular, Zeros_Matrix3,
-r_mag, Zeros_Matrix3, Zeros_Matrix3, w_angular;
Alin = Eigen::MatrixXd::Identity(12, 12) + Alin*deltaT;
}
void EKF_Attitude::Prior_Predict()
{
Vector_12 state_X_tmp;
Vector_3 angular_vel, angular_acc, acc_state, mag_state;
Matrix_3 w_angular, w_angular_T;
state_X_tmp = state_X_pro.back();
angular_vel = state_X_tmp.block<3, 1>(0, 0);
angular_acc = state_X_tmp.block<3, 1>(3, 0);
Vect_to_SkewMat(angular_vel, w_angular_T);
w_angular = w_angular_T.transpose();
angular_vel = angular_vel + angular_acc*deltaT;
// calculate the non-liner system, and decide wto use the number of taylor expansion
if (using_2ndOrder)
{
Matrix_3 Temp_Mat = Identity_Matrix3 + w_angular*deltaT + deltaT*deltaT/2*w_angular*w_angular;
acc_state = state_X_tmp.block<3, 1>(6, 0);
acc_state = Temp_Mat*acc_state;
mag_state = state_X_tmp.block<3, 1>(9, 0);
mag_state = Temp_Mat*mag_state;
}
else
{
Matrix_3 Temp_Mat;
acc_state = state_X_tmp.block<3, 1>(6, 0);
Temp_Mat = Identity_Matrix3 + w_angular*deltaT;
acc_state = Temp_Mat*acc_state;
mag_state = state_X_tmp.block<3, 1>(9, 0);
mag_state = Temp_Mat*mag_state;
}
// refer to the 4.20 and 4.21 formula
Eigen::Matrix<double, 12, 12> CovrMatrix_tmp;
state_X_tmp << angular_vel, angular_acc, acc_state, mag_state;
state_X_pro.push_back(state_X_tmp);
CovrMatrix_tmp = CovrMatrix_P_pro.back();
CovrMatrix_tmp = Alin*CovrMatrix_tmp*Alin.transpose() + Q_noise;
CovrMatrix_P_pro.push_back(CovrMatrix_tmp);
}
void EKF_Attitude::Post_Correct()
{
Vector_12 state_X_tmp;
Eigen::Matrix<double, 12, 12> CovrMatrix_tmp;
state_X_tmp = state_X_pro.back();
state_X_pro.pop_back();
CovrMatrix_tmp = CovrMatrix_P_pro.back();
CovrMatrix_P_pro.pop_back();
// initialize the observe matrix H
Eigen::Matrix<double, 9, 12> Observe_Matrix;
Observe_Matrix << Identity_Matrix3, Zeros_Matrix3, Zeros_Matrix3, Zeros_Matrix3,
Zeros_Matrix3, Zeros_Matrix3, Identity_Matrix3, Zeros_Matrix3,
Zeros_Matrix3, Zeros_Matrix3, Zeros_Matrix3, Identity_Matrix3;
// calculate the Kalman gain
Eigen::Matrix<double, 9, 9> Kal_Matrix;
Eigen::Matrix<double, 12, 9> Kalman_gain;
Kal_Matrix = Observe_Matrix*CovrMatrix_tmp*Observe_Matrix.transpose() + R_noise;
Kalman_gain = CovrMatrix_tmp*Observe_Matrix.transpose()*Kal_Matrix.inverse();
// update the state vector
Vector_9 Mea_residual;
Mea_residual = cur_measurement - Observe_Matrix*state_X_tmp;
state_X_tmp = state_X_tmp + Kalman_gain*Mea_residual;
state_X_pro.push_back(state_X_tmp);
// update the covariance Matrix
CovrMatrix_tmp = (Eigen::MatrixXd::Identity(12, 12) - Kalman_gain*Observe_Matrix)*CovrMatrix_tmp;
CovrMatrix_P_pro.push_back(CovrMatrix_tmp);
}
void EKF_Attitude::Cal_Quaternion()
{
//if (quaternion.size() >= 358)
// cout << " " << endl;
// extract the true state of three sensors
Vector_3 acc_state, mag_state, angular_state;
Vector_12 state_X_tmp;
state_X_tmp = state_X_pro.back();
acc_state = state_X_tmp.block<3, 1>(6, 0);
mag_state = state_X_tmp.block<3, 1>(9, 0);
Vector_3 x_state, y_state, z_state;
acc_state.normalize();
mag_state.normalize();
z_state = -acc_state;
y_state = z_state.cross(mag_state);
y_state.normalize();
x_state = y_state.cross(z_state);
x_state.normalize();
// the rotation order is X-Y-Z,and
Matrix_3 Rotation_matrix;
Rotation_matrix << x_state, y_state, z_state;
Eigen::Quaterniond quat_temp(Rotation_matrix.transpose());
// Eigen::Quaterniond quat_temp = Rotation_to_Quater(Rotation_matrix.transpose());
Vector_3 Euler;
Euler = Quaternion_to_Euler(quat_temp);
// cout << Euler << endl;
quaternion.push_back(quat_temp);
}
void EKF_Attitude::Read_SensorData(Vector_9 measurement)
{
Vector_3 gyro_mea, acc_mea, mag_mea;
acc_mea = measurement.block<3, 1>(0, 0);
gyro_mea = measurement.block<3, 1>(3, 0);
mag_mea = measurement.block<3, 1>(6, 0);
acc_mea.normalize();
mag_mea.normalize();
cur_measurement.block<3, 1>(0, 0) = gyro_mea;
cur_measurement.block<3, 1>(3, 0) = acc_mea;
cur_measurement.block<3, 1>(6, 0) = mag_mea;
}
Eigen::Quaterniond EKF_Attitude::Run(Vector_9 measurement)
{
while (true)
{
Read_SensorData(measurement);
Cal_TransMatrix();
Prior_Predict();
Post_Correct();
Cal_Quaternion();
if (Stop())
{
while (isStopped())
{
#ifdef _WIN32
Sleep(3000);
#else
usleep(3000);
#endif
}
}
return quaternion.back();
}
}
void EKF_Attitude::RequestStop()
{
unique_lock<mutex> lock(mMutexStop);
mbStopRequested = true;
}
void EKF_Attitude::RequestStart()
{
unique_lock<mutex> lock(mMutexStop);
if (mbStopped)
{
mbStopped = false;
mbStopRequested = false;
}
}
bool EKF_Attitude::Stop()
{
unique_lock<mutex> lock(mMutexStop);
if (mbStopRequested)
{
mbStopped = true;
return true;
}
return false;
}
bool EKF_Attitude::isStopped()
{
unique_lock<mutex> lock(mMutexStop);
return mbStopped;
}
void EKF_Attitude::Release()
{
unique_lock<mutex> lock(mMutexStop);
mbStopped = false;
mbStopRequested = false;
state_X_pro.clear();
CovrMatrix_P_pro.clear();
quaternion.clear();
cout << "EKF attitude release " << endl;
}
}
================================================
FILE: src/ESKF_Attitude.cpp
================================================
#include <iostream>
#include "math.h"
#include "ESKF_Attitude.h"
#include "Convert.h"
using namespace std;
namespace IMU
{
ESKF_Attitude::ESKF_Attitude(Vector_12 Covar_Mat, double dt)
{
deltaT = dt;
DetAng_noise = Covar_Mat.block<3, 1>(0, 0);
DetAngVel_noise = Covar_Mat.block<3, 1>(3, 0);
Acc_noise = Covar_Mat.block<3, 1>(6, 0);
Mag_noise = Covar_Mat.block<3, 1>(9, 0);
CovarMat_Q = Eigen::Matrix<double, 6, 6>::Zero();
CovarMat_R = Eigen::Matrix<double, 6, 6>::Zero();
}
void ESKF_Attitude::Param_Change(Vector_12 Covar_Mat)
{
if (isStopped())
{
DetAng_noise = Covar_Mat.block<3, 1>(0, 0);
DetAngVel_noise = Covar_Mat.block<3, 1>(0, 0);
Acc_noise = Covar_Mat.block<3, 1>(0, 0);
Mag_noise = Covar_Mat.block<3, 1>(0, 0);
// Initialize the covariances matrices Q and R
CovarMat_Q.block<3, 3>(0, 0) = DetAng_noise.asDiagonal();
CovarMat_Q.block<3, 3>(3, 3) = DetAngVel_noise.asDiagonal();
CovarMat_R.block<3, 3>(0, 0) = Acc_noise.asDiagonal();
CovarMat_R.block<3, 3>(3, 3) = Mag_noise.asDiagonal();
}
}
void ESKF_Attitude::Init_Estimator()
{
// Initialize the covariances matrices Q and R
CovarMat_Q.block<3, 3>(0, 0) = DetAng_noise.asDiagonal();
CovarMat_Q.block<3, 3>(3, 3) = DetAngVel_noise.asDiagonal();
CovarMat_R.block<3, 3>(0, 0) = Acc_noise.asDiagonal();
CovarMat_R.block<3, 3>(3, 3) = Mag_noise.asDiagonal();
// Initialize the nominal state
//Vector_3 x_state, y_state, z_state;
//z_state = Cur_Measurement.block<3, 1>(3, 0);
//y_state = z_state.cross(Cur_Measurement.block<3, 1>(6, 0));
//x_state = y_state.cross(z_state);
Eigen::Vector3d Acc0, Gyro0, Mag0;
Gyro0 = Cur_Measurement.block<3, 1>(0, 0);
Acc0 = Cur_Measurement.block<3, 1>(3, 0);
Mag0 = Cur_Measurement.block<3, 1>(6, 0);
double Pitch0 = asin(Acc0[0]/Acc0.norm());
double Roll0 = atan2(-Acc0[1], -Acc0[2]);
double Yaw0 = atan2(-Mag0[1] * cos(Roll0) + Mag0[2] * sin(Roll0), Mag0[0] * cos(Pitch0) + Mag0[1] * sin(Pitch0)*sin(Roll0) + Mag0[2] * sin(Pitch0)*cos(Roll0)) - 8.3*3.14166 / 180;
Eigen::Quaterniond quat_temp = Euler_to_Quaternion(Eigen::Vector3d(Roll0, Pitch0, Yaw0));
quat_temp.normalize();
Vector_3 AngVel_temp = DetAngVel_noise;
IMU_State state;
state.Nominal_quat = quat_temp;
state.Nominal_AngVel = AngVel_temp;
// Initialize the error state
Vector_3 detla_theta, detla_angVel;
state.Error_theta = Vector_3::Zero();
state.Error_AngVel = Vector_3::Zero();
state.Error_Convar = Eigen::Matrix<double, 6, 6>::Zero();
state.Error_Convar.block<3, 3>(0, 0) = 1e-5*Eigen::Matrix<double, 3, 3>::Identity();
state.Error_Convar.block<3, 3>(3, 3) = 1e-7*Eigen::Matrix<double, 3, 3>::Identity();
State_Vector.push_back(state);
quaternion.push_back(quat_temp);
Last_Measurement = Cur_Measurement;
}
void ESKF_Attitude::NominaState_Predict()
{
Vector_3 delta_theta;
Eigen::Quaterniond quat_temp;
IMU_State Piror_State = State_Vector.back();
delta_theta = (0.5*(Cur_Measurement.block<3, 1>(0, 0) + Last_Measurement.block<3, 1>(0, 0)) - Piror_State.Nominal_AngVel)*deltaT;
quat_temp.w() = 1;
quat_temp.vec() = 0.5*delta_theta;
quat_temp = Piror_State.Nominal_quat*quat_temp;
quat_temp.normalize();
IMU_State Post_State;
Post_State.Nominal_quat = quat_temp;
Post_State.Nominal_AngVel = Piror_State.Nominal_AngVel;
State_Vector.push_back(Post_State);
}
void ESKF_Attitude::ErrorState_Predict()
{
IMU_State Post_State = State_Vector.back();
State_Vector.pop_back();
IMU_State Piror_State = State_Vector.back();
// calculate the transition matrix A
Eigen::Matrix<double, 6, 6> Trasition_A;
Vector_3 delta_theta;
delta_theta = (Last_Measurement.block<3, 1>(0, 0) - Piror_State.Nominal_AngVel)*deltaT;
Matrix_3 Rotation_Mat = Euler_to_RoatMat(delta_theta);
Trasition_A.block<3, 3>(0, 0) = Rotation_Mat.transpose();
Trasition_A.block<3, 3>(0, 3) = Matrix_3::Identity()*(-deltaT);
Trasition_A.block<3, 3>(3, 0) = Matrix_3::Zero();
Trasition_A.block<3, 3>(3, 3) = Matrix_3::Identity();
// priori prediction
Vector_6 Errstate_temp;
Errstate_temp.block<3, 1>(0, 0) = Piror_State.Error_theta;
Errstate_temp.block<3, 1>(3, 0) = Piror_State.Error_AngVel;
Errstate_temp = Trasition_A*Errstate_temp;
Post_State.Error_theta = Errstate_temp.block<3, 1>(0, 0);
Post_State.Error_AngVel = Errstate_temp.block<3, 1>(3, 0);
Eigen::Matrix<double, 6, 6> CovarMat_Qi = CovarMat_Q*deltaT;
Eigen::Matrix<double, 6, 6> NoiseMat_Fi = Eigen::Matrix<double, 6, 6>::Identity();
Post_State.Error_Convar = Trasition_A*Piror_State.Error_Convar*Trasition_A.transpose() +
NoiseMat_Fi*CovarMat_Qi*NoiseMat_Fi.transpose();
State_Vector.push_back(Post_State);
}
Eigen::Matrix<double, 6, 6> ESKF_Attitude::IMU_State::Cal_ObserveMat(Vector_9 measurenment, Vector_6 &residual)
{
Vector_3 True_AccMea, True_MagMre, Mea_Mag;
Eigen::Matrix<double, 4, 1> Mag_global;
Eigen::Quaterniond q = Nominal_quat;
Mea_Mag = measurenment.block<3, 1>(6, 0);
Eigen::Quaterniond Mag_quat(0.0, Mea_Mag(0), Mea_Mag(1), Mea_Mag(2));
Mag_quat = QuatMult(q, QuatMult(Mag_quat, q.conjugate()));
Mag_global << 0, sqrt(Mag_quat.x()*Mag_quat.x() + Mag_quat.y()*Mag_quat.y()),
0, Mag_quat.z();
// calculate the observe Matrix H
Eigen::Matrix<double, 3, 4> acc_H, mag_H;
acc_H << 2 * q.y(), -2 * q.z(), 2 * q.w(), -2 * q.x(),
-2 * q.x(), -2 * q.w(), -2 * q.z(), -2 * q.y(),
0, 4 * q.x(), 4 * q.y(), 0;
mag_H << -2 * Mag_global(3)*q.y(), 2 * Mag_global(3)*q.z(),
-4 * Mag_global(1)*q.y() - 2 * Mag_global(3)*q.w(), -4 * Mag_global(1)*q.z() + 2 * Mag_global(3)*q.x(),
-2 * Mag_global(1)*q.z() + 2 * Mag_global(3)*q.x(), 2 * Mag_global(1)*q.y() + 2 * Mag_global(3)*q.w(),
2 * Mag_global(1)*q.x() + 2 * Mag_global(3)*q.z(), -2 * Mag_global(1)*q.w() + 2 * Mag_global(3)*q.y(),
2 * Mag_global(1)*q.y(), 2 * Mag_global(1)*q.z() - 4 * Mag_global(3)*q.x(),
2 * Mag_global(1)*q.w() - 4 * Mag_global(3)*q.y(), 2 * Mag_global(1)*q.x();
Eigen::Matrix<double, 6, 7> Observe_Hx;
Observe_Hx.block<3, 4>(0, 0) = acc_H;
Observe_Hx.block<3, 4>(3, 0) = mag_H;
Observe_Hx.block<3, 3>(0, 4) = Matrix_3::Zero();
Observe_Hx.block<3, 3>(3, 4) = Matrix_3::Zero();
Eigen::Matrix<double, 7, 6> Observe_Xx;
Eigen::Matrix<double, 4, 3> Matrix_Q;
Matrix_Q << -q.x(), -q.y(), -q.z(),
q.w(), -q.z(), q.y(),
q.z(), q.w(), -q.x(),
-q.y(), q.x(), q.w();
Observe_Xx.block<4, 3>(0, 0) = 0.5*Matrix_Q;
Observe_Xx.block<4, 3>(0, 3) = Eigen::Matrix<double, 4, 3>::Zero();
Observe_Xx.block<3, 3>(4, 0) = Matrix_3::Zero();
Observe_Xx.block<3, 3>(4, 3) = Matrix_3::Identity();
Eigen::Matrix<double, 6, 6> Observe_Matrix;
Observe_Matrix = Observe_Hx*Observe_Xx;
// Calculate the true measurement
// the true accelerometer measurement
True_AccMea << -2 * (q.x()*q.z() - q.w()*q.y()),
-2 * (q.w()*q.x() + q.y()*q.z()),
-2 * (0.5 - q.x()*q.x() - q.y()*q.y());
// the true magnetometer measurement
True_MagMre << -(2 * Mag_global(1)*(0.5 - q.y()*q.y() - q.z()*q.z()) + 2 * Mag_global(3)*(q.x()*q.z() - q.w()*q.y())),
-(2 * Mag_global(1)*(q.x()*q.y() - q.w()*q.z()) + 2 * Mag_global(3)*(q.w()*q.x() + q.y()*q.z())),
-(2 * Mag_global(1)*(q.w()*q.y() + q.x()*q.z()) + 2 * Mag_global(3)*(0.5 - q.x()*q.x() - q.y()*q.y()));
// calculate the residual
residual.block<3, 1>(0, 0) = measurenment.block<3, 1>(3, 0) + True_AccMea;
residual.block<3, 1>(3, 0) = measurenment.block<3, 1>(6, 0) + True_MagMre;
return Observe_Matrix;
}
void ESKF_Attitude::Update_Filter()
{
Vector_6 Residual;
Eigen::Matrix<double, 6, 6> Observe_Matrix;
IMU_State Post_State = State_Vector.back();
State_Vector.pop_back();
// calculate the observe matrix and the correction residual
Observe_Matrix = Post_State.Cal_ObserveMat(Cur_Measurement, Residual);
//Calculate the kalman gain
Eigen::Matrix<double, 6, 6> Poste_Cov = Post_State.Error_Convar;
Eigen::Matrix<double, 6, 6> Kalman_Gain;
Kalman_Gain = Observe_Matrix*Poste_Cov*Observe_Matrix.transpose() + CovarMat_R;
Kalman_Gain = Poste_Cov*Observe_Matrix.transpose()*Kalman_Gain.inverse();
// update error state
Vector_6 Post_ErrState = Kalman_Gain*Residual;
Post_State.Error_theta = Post_ErrState.block<3, 1>(0, 0);
Post_State.Error_AngVel = Post_ErrState.block<3, 1>(3, 0);
Post_State.Error_Convar = Poste_Cov - Kalman_Gain*(Observe_Matrix*Poste_Cov*Observe_Matrix.transpose() +
CovarMat_R)*Kalman_Gain.transpose();
State_Vector.push_back(Post_State);
}
void ESKF_Attitude::Update_NomianState()
{
IMU_State Post_State = State_Vector.back();
State_Vector.pop_back();
Eigen::Quaterniond delta_q = BuildUpdateQuat(Post_State.Error_theta);
Post_State.Nominal_quat = Post_State.Nominal_quat*delta_q;
Post_State.Nominal_quat.normalize();
Post_State.Nominal_AngVel = Post_State.Nominal_AngVel + Post_State.Error_AngVel;
State_Vector.push_back(Post_State);
quaternion.push_back(Post_State.Nominal_quat);
}
void ESKF_Attitude::Reset_ErrorState()
{
IMU_State Post_State = State_Vector.back();
State_Vector.pop_back();
Eigen::Matrix<double, 6, 6> Matrix_G = Eigen::Matrix<double, 6, 6>::Identity();
//Matrix_3 Ang_Mat = Post_State.Error_theta.asDiagonal();
//Matrix_G.block<3, 3>(0, 0) = Matrix_3::Identity() - Ang_Mat;
Post_State.Error_theta = Vector_3::Zero();
Post_State.Error_AngVel = Vector_3::Zero();
Post_State.Error_Convar = Matrix_G*Post_State.Error_Convar*Matrix_G.transpose();
State_Vector.push_back(Post_State);
Last_Measurement = Cur_Measurement;
}
void ESKF_Attitude::Read_SensorData(Vector_9 measurement)
{
Vector_3 gyro_mea, acc_mea, mag_mea;
acc_mea = measurement.block<3, 1>(0, 0);
gyro_mea = measurement.block<3, 1>(3, 0);
mag_mea = measurement.block<3, 1>(6, 0);
acc_mea.normalize();
mag_mea.normalize();
Cur_Measurement.block<3, 1>(0, 0) = gyro_mea;
Cur_Measurement.block<3, 1>(3, 0) = acc_mea;
Cur_Measurement.block<3, 1>(6, 0) = mag_mea;
}
Eigen::Quaterniond ESKF_Attitude::Run(Vector_9 measurement)
{
while (true)
{
Read_SensorData(measurement);
if (State_Vector.size() == 0 || quaternion.size() == 0)
{
// Initialize the true state of the estimator
Init_Estimator();
}
else
{
// Predict the nomial and error state
NominaState_Predict();
ErrorState_Predict();
// Update the filter parametres
Update_Filter();
// Uptate the nominal state
Update_NomianState();
// Reset the error state
Reset_ErrorState();
}
if (Stop())
{
while (isStopped())
{
#ifdef _WIN32
Sleep(3);
#else
usleep(3000);
#endif
}
}
return quaternion.back();
}
}
void ESKF_Attitude::RequestStop()
{
unique_lock<mutex> lock(mMutexStop);
mbStopRequested = true;
}
void ESKF_Attitude::RequestStart()
{
unique_lock<mutex> lock(mMutexStop);
if (mbStopped)
{
mbStopped = false;
mbStopRequested = false;
}
}
bool ESKF_Attitude::Stop()
{
unique_lock<mutex> lock(mMutexStop);
if (mbStopRequested)
{
mbStopped = true;
return true;
}
return false;
}
bool ESKF_Attitude::isStopped()
{
unique_lock<mutex> lock(mMutexStop);
return mbStopped;
}
void ESKF_Attitude::Release()
{
unique_lock<mutex> lock(mMutexStop);
mbStopped = false;
mbStopRequested = false;
State_Vector.clear();
quaternion.clear();
cout << "EKF attitude release " << endl;
}
}// namespace IMU
================================================
FILE: src/Mahony_Attitude.cpp
================================================
#include <iostream>
#include "Mahony_Attitude.h"
#include "Convert.h"
using namespace std;
namespace IMU
{
Mahony_Attitude::Mahony_Attitude(Vector_2 PI, double dt):
mbStopped(false), mbStopRequested(false)
{
Kp = PI(0);
Ki = PI(1);
deltaT = dt;
Integ_angular = Vector_3::Zero();
}
void Mahony_Attitude::Params_Change(Vector_2 PI, double dt)
{
if (isStopped())
{
Kp = PI(0);
Ki = PI(1);
deltaT = dt;
}
}
void Mahony_Attitude::Mahony_Estimate()
{
Vector_3 angular_vel, acc, mag;
angular_vel = cur_measurement.block<3, 1>(0, 0);
acc = cur_measurement.block<3, 1>(3, 0);
mag = cur_measurement.block<3, 1>(6, 0);
Eigen::Quaterniond quat_temp;
Vector_3 x_state, y_state, z_state;
Matrix_3 Rotation_matrix;
// if the quaternion is empty, the quaternion will be initialized by tha accelerometer and magnetometer
if (quaternion.empty())
{
z_state = acc;
y_state = z_state.cross(mag);
x_state = y_state.cross(z_state);
Rotation_matrix << x_state, y_state, z_state;
quat_temp = Rotation_matrix;
quaternion.push_back(quat_temp);
}
else
{
// get the error from the measurement from accelerometer and magnetometer
quat_temp = quaternion.back();
quat_temp.normalized();
Rotation_matrix = quat_temp.toRotationMatrix();
Vector_3 error_acc, error_mag, mag_ned, error_sum;
error_acc = Rotation_matrix.block<3, 1>(0, 2);
error_acc = acc.cross(error_acc);
mag_ned = Rotation_matrix.transpose()*mag;
error_mag << sqrt(mag_ned(0)*mag_ned(0) + mag_ned(1)*mag_ned(1)), 0, mag_ned(2);
error_mag = Rotation_matrix*error_mag;
error_mag = mag.cross(error_mag);
error_sum = error_acc + error_mag;
// get the modify value from the error
Vector_3 Integ_angular, Correct_angular;
Integ_angular = Integ_angular + Ki*deltaT*error_sum;
Correct_angular = angular_vel + Kp*error_sum + Integ_angular;
Eigen::Quaterniond Angular_quat;
Angular_quat.w() = 0.0;
Angular_quat.vec() = Correct_angular;
// update the quaternion refer to the correct angular
Eigen::Quaterniond quat_temp_new;
quat_temp_new = QuatMult(quat_temp, Angular_quat);
quat_temp_new.w() = quat_temp_new.w()*0.5*deltaT + quat_temp.w();
quat_temp_new.vec() = quat_temp_new.vec()*0.5*deltaT + quat_temp.vec();
quat_temp_new.normalize();
quaternion.push_back(quat_temp_new);
}
}
void Mahony_Attitude::Read_SensorData(Vector_9 measurement)
{
Vector_3 gyro_mea, acc_mea, mag_mea;
acc_mea = measurement.block<3, 1>(0, 0);
gyro_mea = measurement.block<3, 1>(3, 0);
mag_mea = measurement.block<3, 1>(6, 0);
acc_mea.normalize();
mag_mea.normalize();
cur_measurement.block<3, 1>(0, 0) = gyro_mea;
cur_measurement.block<3, 1>(3, 0) = acc_mea;
cur_measurement.block<3, 1>(6, 0) = mag_mea;
}
Eigen::Quaterniond Mahony_Attitude::Run(Vector_9 measurement)
{
while (true)
{
Read_SensorData(measurement);
Mahony_Estimate();
if (Stop())
{
while (isStopped())
{
#ifdef _WIN32
Sleep(3000);
#else
usleep(3000);
#endif
}
}
return quaternion.back();
}
}
void Mahony_Attitude::RequestStop()
{
unique_lock<mutex> lock(mMutexStop);
mbStopRequested = true;
}
void Mahony_Attitude::RequestStart()
{
unique_lock<mutex> lock(mMutexStop);
if (mbStopped)
{
mbStopped = false;
mbStopRequested = false;
}
}
bool Mahony_Attitude::Stop()
{
unique_lock<mutex> lock(mMutexStop);
if (mbStopRequested)
{
mbStopped = true;
return true;
}
return false;
}
bool Mahony_Attitude::isStopped()
{
unique_lock<mutex> lock(mMutexStop);
return mbStopped;
}
void Mahony_Attitude::Release()
{
unique_lock<mutex> lock(mMutexStop);
mbStopped = false;
mbStopRequested = false;
Integ_angular = Vector_3::Zero();
quaternion.clear();
cout << "Mahony attitude release " << endl;
}
}
gitextract_hjgyys6b/
├── Allan_Analysis.py
├── CMakeLists.txt
├── DataSets.py
├── LICENSE
├── README.md
├── cmake_modules/
│ ├── FindEigen3.cmake
│ └── FindGlog.cmake
├── datasets/
│ └── readme.txt
├── demo/
│ └── Test.cpp
├── include/
│ ├── Convert.h
│ ├── EKF_Attitude.h
│ ├── ESKF_Attitude.h
│ ├── Mahony_Attitude.h
│ ├── TypeDefs.h
│ ├── matplotlibcpp.h
│ └── tic_toc.h
└── src/
├── Convert.cpp
├── EKF_Attitude.cpp
├── ESKF_Attitude.cpp
└── Mahony_Attitude.cpp
SYMBOL INDEX (47 symbols across 12 files)
FILE: demo/Test.cpp
function main (line 20) | int main(int argc, char **argv)
FILE: include/Convert.h
function namespace (line 16) | namespace IMU
FILE: include/EKF_Attitude.h
function namespace (line 19) | namespace IMU
FILE: include/ESKF_Attitude.h
function namespace (line 22) | namespace IMU
FILE: include/Mahony_Attitude.h
function namespace (line 18) | namespace IMU
FILE: include/TypeDefs.h
function namespace (line 10) | namespace IMU
FILE: include/matplotlibcpp.h
function namespace (line 27) | namespace matplotlibcpp {
function figure (line 746) | inline void figure()
function legend (line 754) | inline void legend()
function subplot (line 832) | inline void subplot(long nrows, long ncols, long plot_number)
function title (line 847) | inline void title(const std::string &titlestr)
function axis (line 860) | inline void axis(const std::string &axisstr)
function xlabel (line 873) | inline void xlabel(const std::string &str)
function ylabel (line 886) | inline void ylabel(const std::string &str)
function grid (line 899) | inline void grid(bool flag)
function close (line 937) | inline void close()
function xkcd (line 948) | inline void xkcd() {
function draw (line 963) | inline void draw()
function save (line 987) | inline void save(const std::string& filename)
function clf (line 1001) | inline void clf() {
function ion (line 1011) | inline void ion() {
function tight_layout (line 1022) | inline void tight_layout() {
function namespace (line 1035) | namespace detail {
type Fallback (line 1052) | struct Fallback { void operator()(); }
type Derived (line 1053) | struct Derived
type dtype (line 1065) | typedef decltype(&Fallback::operator()) dtype;
type typename (line 1073) | typedef typename is_callable_impl<std::is_class<T>::value, T>::type type;
function false_type (line 1080) | struct plot_impl<std::false_type>
function true_type (line 1119) | struct plot_impl<std::true_type>
FILE: include/tic_toc.h
function namespace (line 12) | namespace IMU
FILE: src/Convert.cpp
type IMU (line 5) | namespace IMU
function Vect_to_SkewMat (line 8) | void Vect_to_SkewMat(Vector_3 Vector, Matrix_3 &Matrix)
function Angular_to_Mat (line 15) | void Angular_to_Mat(Vector_3 Vector, Eigen::Matrix<double, 4, 4> &Matrix)
function Vector_4 (line 23) | Vector_4 Quaternion_to_Vect(Eigen::Quaterniond q)
function QuatMult (line 32) | Eigen::Quaterniond QuatMult(Eigen::Quaterniond q1, Eigen::Quaterniond q2)
function Matrix_3 (line 43) | Matrix_3 Quat_to_Matrix(Eigen::Quaterniond q)
function readFromfile (line 53) | Eigen::MatrixXd readFromfile(const string file_name)
function writeTofile (line 92) | bool writeTofile(Eigen::MatrixXd matrix, const string file_name)
function Matrix_3 (line 105) | Matrix_3 Euler_to_RoatMat(Vector_3 Euler)
function Euler_to_Quaternion (line 120) | Eigen::Quaterniond Euler_to_Quaternion(Vector_3 Euler)
function Vector_3 (line 159) | Vector_3 Quaternion_to_Euler(Eigen::Quaterniond q)
function Vector_3 (line 180) | Vector_3 Rotation_to_Euler(Matrix_3 Rotation)
function Rotation_to_Quater (line 191) | Eigen::Quaterniond Rotation_to_Quater(Matrix_3 Rotation)
function BuildUpdateQuat (line 231) | Eigen::Quaterniond BuildUpdateQuat(Eigen::Vector3d DeltaTheta)
FILE: src/EKF_Attitude.cpp
type IMU (line 6) | namespace IMU
FILE: src/ESKF_Attitude.cpp
type IMU (line 9) | namespace IMU
FILE: src/Mahony_Attitude.cpp
type IMU (line 6) | namespace IMU
Condensed preview — 20 files, each showing path, character count, and a content snippet. Download the .json file or copy for the full structured content (144K chars).
[
{
"path": "Allan_Analysis.py",
"chars": 1329,
"preview": "import numpy as np\nimport matplotlib.pyplot as plt\nimport math\nimport numpy.matlib\nfrom scipy.optimize import nnls\nimpor"
},
{
"path": "CMakeLists.txt",
"chars": 1012,
"preview": "cmake_minimum_required(VERSION 2.8)\nproject(IMU_Attitude_Estimator)\n\nset(CMAKE_BUILD_TYPE Release)\nset(CMAKE_CXX_FLAGS \""
},
{
"path": "DataSets.py",
"chars": 271,
"preview": "import numpy as np\nimport scipy.io as sio\n\nload_fn = './datasets/NAV.mat'\nload_Data = sio.loadmat(load_fn)\ndata = load_D"
},
{
"path": "LICENSE",
"chars": 35121,
"preview": "GNU GENERAL PUBLIC LICENSE\n Version 3, 29 June 2007\n\n Copyright (C) 2007 Free Software Foundation,"
},
{
"path": "README.md",
"chars": 1602,
"preview": "# IMU_Attitude_Estimator\n\nThis project is aimed at estimating the attitude of Attitude Heading and Reference System(AHRS"
},
{
"path": "cmake_modules/FindEigen3.cmake",
"chars": 3379,
"preview": "# - Try to find Eigen3 lib\n#\n# This module supports requiring a minimum version, e.g. you can do\n# find_package(Eigen3"
},
{
"path": "cmake_modules/FindGlog.cmake",
"chars": 8915,
"preview": "# Ceres Solver - A fast non-linear least squares minimizer\n# Copyright 2015 Google Inc. All rights reserved.\n# http://ce"
},
{
"path": "demo/Test.cpp",
"chars": 2973,
"preview": "#include <iostream>\r\n#include <vector>\r\n#include \"time.h\"\r\n#include <Eigen/Core>\r\n#include <Eigen/Geometry>\r\n\r\n#include "
},
{
"path": "include/Convert.h",
"chars": 1479,
"preview": "#ifndef CONVERT_H_\r\n#define CONVERT_H_\r\n\r\n#include <iostream>\r\n#include <vector>\r\n#include <fstream>\r\n#include <string>\r"
},
{
"path": "include/EKF_Attitude.h",
"chars": 1800,
"preview": "#ifndef EKF_ATTITUDE_H_\r\n#define EKF_ATTITUDE_H_\r\n\r\n#include <iostream>\r\n#include <vector>\r\n#include <mutex>\r\n#include <"
},
{
"path": "include/ESKF_Attitude.h",
"chars": 2425,
"preview": "#ifndef ESKF_ATTITUDE_H\r\n#define ESKF_ATTITUDE_H\r\n\r\n#include <iostream>\r\n#include <vector>\r\n#include <mutex>\r\n#include <"
},
{
"path": "include/Mahony_Attitude.h",
"chars": 898,
"preview": "#ifndef MAHONY_AHRS_H_\r\n#define MAHONY_AHRS_H_\r\n\r\n#include <iostream>\r\n#include <vector>\r\n#include <mutex>\r\n#include <Ei"
},
{
"path": "include/TypeDefs.h",
"chars": 697,
"preview": "#ifndef TYPEDEFS_H_\r\n#define TYPEDEFS_H_\r\n\r\n\r\n#include <iostream>\r\n#include <Eigen/Core>\r\n\r\n//#pragma once\r\n\r\nnamespace "
},
{
"path": "include/matplotlibcpp.h",
"chars": 42145,
"preview": "#pragma once\n\n#include <vector>\n#include <map>\n#include <numeric>\n#include <algorithm>\n#include <stdexcept>\n#include <io"
},
{
"path": "include/tic_toc.h",
"chars": 688,
"preview": "//\n// Created by buyi on 18-1-28.\n//\n\n#ifndef IMU_ATTITUDE_ESTIMATOR_TIC_TOC_H_H\n#define IMU_ATTITUDE_ESTIMATOR_TIC_TOC_"
},
{
"path": "src/Convert.cpp",
"chars": 6909,
"preview": "#include \"Convert.h\"\r\n#include \"TypeDefs.h\"\r\n#include <fstream>\r\n\r\nnamespace IMU\r\n{\r\n\r\nvoid Vect_to_SkewMat(Vector_3 Vec"
},
{
"path": "src/EKF_Attitude.cpp",
"chars": 8047,
"preview": "#include \"EKF_Attitude.h\"\r\n#include \"Convert.h\"\r\n\r\nusing namespace std;\r\n\r\nnamespace IMU\r\n{\r\n\r\nEKF_Attitude::EKF_Attitud"
},
{
"path": "src/ESKF_Attitude.cpp",
"chars": 12645,
"preview": "#include <iostream>\r\n#include \"math.h\"\r\n#include \"ESKF_Attitude.h\"\r\n#include \"Convert.h\"\r\n\r\n\r\nusing namespace std;\r\n\r\nna"
},
{
"path": "src/Mahony_Attitude.cpp",
"chars": 4080,
"preview": "#include <iostream>\r\n#include \"Mahony_Attitude.h\"\r\n#include \"Convert.h\"\r\n\r\nusing namespace std;\r\nnamespace IMU\r\n{\r\n\tMaho"
}
]
// ... and 1 more files (download for full content)
About this extraction
This page contains the full source code of the gaochq/IMU_Attitude_Estimator GitHub repository, extracted and formatted as plain text for AI agents and large language models (LLMs). The extraction includes 20 files (133.2 KB), approximately 35.3k tokens, and a symbol index with 47 extracted functions, classes, methods, constants, and types. Use this with OpenClaw, Claude, ChatGPT, Cursor, Windsurf, or any other AI tool that accepts text input. You can copy the full output to your clipboard or download it as a .txt file.
Extracted by GitExtract — free GitHub repo to text converter for AI. Built by Nikandr Surkov.