In [1]:

    

import px4tools
import pandas
import pylab as pl
%matplotlib inline
pl.rcParams['figure.figsize'] = (15,5)
pl.rcParams['lines.linewidth'] = 3


    

In [2]:

    

data_inav = px4tools.project_lat_lon(px4tools.process_data(pandas.read_csv('logs/15-10-24-20_25_00.csv')))


    

In [3]:

    

data_lpe = px4tools.project_lat_lon(px4tools.process_data(pandas.read_csv('logs/15-10-24-20_46_53.csv')))


    

In [37]:

    

pl.figure(figsize=(10,10))
px4tools.pos_analysis(data_inav[70:95]);
pl.axis('equal')


    

    
Out[37]:





(-4.0, 8.0, -5.0, 25.0)






    

In [34]:

    

pl.figure(figsize=(10,10))
px4tools.pos_analysis(data_lpe[10:40]);
pl.axis('equal')


    

    
Out[34]:





(-6.0, 8.0, -5.0, 25.0)






    

In [9]:

    

px4tools.alt_analysis(data_lpe);


    

In [12]:

    

px4tools.alt_analysis(data_inav);


    

In [13]:

    

px4tools.plot_position_loops(data_inav)


    

In [14]:

    

px4tools.plot_position_loops(data_lpe)


    

In [38]:

    

data1 = data_lpe
data1.EST0_s6.plot(label='b_x')
data1.EST0_s7.plot(label='b_y')
data1.EST0_s8.plot(label='b_z')
pl.legend(loc='best', ncol=3)
pl.title('bias estimates')
pl.grid()


    

In [ ]: