nclt2ros/extractor/read_sensor_data.py
def read_odometry_cov_100hz_csv(self, all_in_one=None):
        """reads the data in the odometry_cov_100hz csv file

        :param all_in_one: Boolean
        :return: ndarray: containing all data, if all_in_one is True
                 else
                 each column seperated as utimes and the upper diagonal of the covariance matrix (row major)
        """
        if self.sensor_data_flag:

            odom_cov = np.loadtxt(self.sensor_data_dir + '/%s/odometry_cov_100hz.csv' % self.date, delimiter=",")

            if all_in_one is True:

                return odom_cov

            else:

                utimes = odom_cov[:, 0]

                xx = odom_cov[:, 1]; xy = odom_cov[:, 2]; xz = odom_cov[:, 3]; xr = odom_cov[:, 4]; xp = odom_cov[:, 5]; xh = odom_cov[:, 6]
                yy = odom_cov[:, 7]; yz = odom_cov[:, 8]; yr = odom_cov[:, 9]; yp = odom_cov[:, 10]; yh = odom_cov[:, 11]
                zz = odom_cov[:, 12]; zr = odom_cov[:, 13]; zp = odom_cov[:, 14]; zh = odom_cov[:, 15]
                rr = odom_cov[:, 16]; rp = odom_cov[:, 17]; rh = odom_cov[:, 18]
                pp = odom_cov[:, 19]; ph = odom_cov[:, 20]
                hh = odom_cov[:, 21]

                return utimes, xx, xy, xz, xr, xp, xh, yy, yz, yr, yp, yh, zz, zr, zp, zh, rr, rp, rh, pp, ph, hh

        else:
            raise ValueError('no sensor_data directory available')
reads the data in the odometry_cov_100hz csv file

        :param all_in_one: Boolean
        :return: ndarray: containing all data, if all_in_one is True
                 else
                 each column seperated as utimes and the upper diagonal of the covariance matrix (row major)
        
reads the data in the odometry_cov_100hz csv file
reads the data in the odometry_cov_100hz csv file
def read_odometry_cov_100hz_csv(self, all_in_one=None):
        if self.sensor_data_flag:
            odom_cov = np.loadtxt(self.sensor_data_dir + '/%s/odometry_cov_100hz.csv' % self.date, delimiter=",")
            if all_in_one is True:
                return odom_cov
            else:
                utimes = odom_cov[:, 0]
                xx = odom_cov[:, 1]; xy = odom_cov[:, 2]; xz = odom_cov[:, 3]; xr = odom_cov[:, 4]; xp = odom_cov[:, 5]; xh = odom_cov[:, 6]
                yy = odom_cov[:, 7]; yz = odom_cov[:, 8]; yr = odom_cov[:, 9]; yp = odom_cov[:, 10]; yh = odom_cov[:, 11]
                zz = odom_cov[:, 12]; zr = odom_cov[:, 13]; zp = odom_cov[:, 14]; zh = odom_cov[:, 15]
                rr = odom_cov[:, 16]; rp = odom_cov[:, 17]; rh = odom_cov[:, 18]
                pp = odom_cov[:, 19]; ph = odom_cov[:, 20]
                hh = odom_cov[:, 21]
                return utimes, xx, xy, xz, xr, xp, xh, yy, yz, yr, yp, yh, zz, zr, zp, zh, rr, rp, rh, pp, ph, hh
        else:
            raise ValueError('no sensor_data directory available')
def read_odometry_cov_100hz_csv ( self , all_in_one = None ) : if self . sensor_data_flag : odom_cov = np . loadtxt ( self . sensor_data_dir + '/%s/odometry_cov_100hz.csv' % self . date , delimiter = "," ) if all_in_one is True : return odom_cov else : utimes = odom_cov [ : , 0 ] xx = odom_cov [ : , 1 ] ; xy = odom_cov [ : , 2 ] ; xz = odom_cov [ : , 3 ] ; xr = odom_cov [ : , 4 ] ; xp = odom_cov [ : , 5 ] ; xh = odom_cov [ : , 6 ] yy = odom_cov [ : , 7 ] ; yz = odom_cov [ : , 8 ] ; yr = odom_cov [ : , 9 ] ; yp = odom_cov [ : , 10 ] ; yh = odom_cov [ : , 11 ] zz = odom_cov [ : , 12 ] ; zr = odom_cov [ : , 13 ] ; zp = odom_cov [ : , 14 ] ; zh = odom_cov [ : , 15 ] rr = odom_cov [ : , 16 ] ; rp = odom_cov [ : , 17 ] ; rh = odom_cov [ : , 18 ] pp = odom_cov [ : , 19 ] ; ph = odom_cov [ : , 20 ] hh = odom_cov [ : , 21 ] return utimes , xx , xy , xz , xr , xp , xh , yy , yz , yr , yp , yh , zz , zr , zp , zh , rr , rp , rh , pp , ph , hh else : raise ValueError ( 'no sensor_data directory available' )
reads the data in the odometry_cov_100hz csv file
reads the data in the odometry_cov_100hz csv file
"""reads the data in the odometry_cov_100hz csv file

        :param all_in_one: Boolean
        :return: ndarray: containing all data, if all_in_one is True
                 else
                 each column seperated as utimes and the upper diagonal of the covariance matrix (row major)
        """
containing all data, if all_in_one is True
else
each column seperated as utimes and the upper diagonal of the covariance matrix (row major)
containing all data if all_in_one is True else each column seperated as utimes and the upper diagonal of the covariance matrix ( row major )
self
all_in_one
None