In [1]:

    

import px4tools
import pandas
import pylab as pl
%matplotlib inline
pl.rcParams['figure.figsize'] = (15,5)


    

In [2]:

    

data = px4tools.process_data(
    pandas.read_csv('logs/15-10-01-09_31_04-jgoppert-accel-bias.csv'))


    

In [3]:

    

px4tools.find_lpe_gains(data[10:100])


    

    
Out[3]:





{'LPE_ACC_XY': 0.0030823535829648746,
 'LPE_ACC_Z': 0.033414201656182821,
 'LPE_BAR_Z': 0.58919875951217515,
 'LPE_GPS_VXY': 0.41561380597739034,
 'LPE_GPS_VZ': 0.38711289795608195,
 'LPE_GPS_XY': 1.7513615068311763,
 'LPE_GPS_Z': 2.7466845437010869,
 'LPE_LDR_Z': 0}

In [4]:

    

data.STAT_MainState.plot()


    

    
Out[4]:





<matplotlib.axes.AxesSubplot at 0x7fd53e3bb350>






    

In [5]:

    

px4tools.plot_position_loops(data)


    

In [9]:

    

px4tools.plot_velocity_loops(data)


    

In [10]:

    

px4tools.pos_analysis(data);


    

In [8]:

    

data.LPOS_VZ.plot()


    

    
Out[8]:





<matplotlib.axes.AxesSubplot at 0x7fd53e62c610>