In [2]:

    

import pvl
from planet4 import io


    

In [4]:

    

labelfile = "/Users/klay6683/Dropbox/data/hirise/RDRCUMINDEX.LBL"


    

In [6]:

    

lbl = pvl.load(labelfile)


    

In [21]:

    

lblcols = [k for k in lbl['RDR_INDEX_TABLE'] if k[0] == 'COLUMN']


    

In [28]:

    

cols = [col[1]['NAME'] for col in lblcols]


    

In [29]:

    

len(cols)


    

    
Out[29]:





54

In [39]:

    

df = pd.read_csv("/Users/klay6683/Dropbox/data/hirise/RDRCUMINDEX.TAB", names=cols)


    

In [33]:

    

[col for col in cols if 'LATITUDE' in col]


    

    
Out[33]:





['SUB_SOLAR_LATITUDE',
 'SUB_SPACECRAFT_LATITUDE',
 'MINIMUM_LATITUDE',
 'MAXIMUM_LATITUDE',
 'PROJECTION_CENTER_LATITUDE',
 'CORNER1_LATITUDE',
 'CORNER2_LATITUDE',
 'CORNER3_LATITUDE',
 'CORNER4_LATITUDE']

In [42]:

    

df['median_lat'] = df.filter(regex="CORNER._LATITUDE").median(axis=1)


    

In [43]:

    

df['median_lon'] = df.filter(regex='CORNER._LONGITUDE').median(axis=1)


    

In [47]:

    

df.median_lon.dtype


    

    
Out[47]:





dtype('float64')

In [48]:

    

to_plot = df.loc[df.median_lat < -70]


    

In [49]:

    

to_plot.shape


    

    
Out[49]:





(6394, 56)

In [51]:

    

to_plot.SOLAR_LONGITUDE.describe()


    

    
Out[51]:





count    6394.000000
mean      268.098379
std        58.155847
min         0.083000
25%       223.653000
50%       277.064000
75%       315.264000
max       359.358000
Name: SOLAR_LONGITUDE, dtype: float64

In [10]:

    

%matplotlib inline


    

In [54]:

    

to_plot.plot(kind='scatter', x='median_lon', y='median_lat')


    

    
Out[54]:





<matplotlib.axes._subplots.AxesSubplot at 0x12750e208>






    

In [72]:

    

plt.hist2d(df.median_lon, df.median_lat, 
           bins=(range(0, 361, 15), range(-90, -74, 1)),
           cmap='viridis', cmin=1)
plt.colorbar()


    

    
Out[72]:





<matplotlib.colorbar.Colorbar at 0x117a35550>






    

In [ ]: