In [1]:

    

import os.path
import pandas as pd
import clb
import datetime as dt
import numpy as np
import matplotlib.pyplot as plt
import typhon.plots
import seaborn as sns
import pickle
from pyclamster.positioning import plot_results2d, plot_results3d

plt.style.use('typhon')


    

In [2]:

    

BASE_DIR = '/home/tfinn/Data/Ceilometer'
ceilo_first = clb.csv.read(os.path.join(BASE_DIR, 'LEX', 'CL_first.txt'))
ceilo_second = clb.csv.read(os.path.join(BASE_DIR, 'LEX', 'CL.txt'))
ceilo_first['DATETIME'] = np.array([dt.datetime.strptime('-'.join([D, ceilo_first['TIME'][k]]), '%d.%m.%Y-%H:%M') for k, D in enumerate(ceilo_first['DATE'])])
ceilo_second['DATETIME'] = np.array([dt.datetime.strptime('-'.join([D, ceilo_second['TIME'][k]]), '%d.%m.%Y-%H:%M') for k, D in enumerate(ceilo_second['DATE'])])
ceilo = pd.DataFrame(ceilo_first).set_index('DATETIME')
ceilo.index = ceilo.index-dt.timedelta(hours=1)
ceilo_plt = ceilo.ix[:, ['CL_SCHA', 'CL_SCHB']]


    

In [3]:

    

cam = pd.read_json('/home/tfinn/Projects/pyclamster/data/heights_201609010900_4h_300_new.json')
#cam = pd.read_json('/home/tfinn/Desktop/heights_long_600.json')
cam.index = cam.index-dt.timedelta(hours=1, seconds=20*60)
cam[cam>8000] = np.NaN
cam_min = cam.mean(axis=1)


    

In [4]:

    

ceilo_cam = pd.DataFrame()
ceilo_cam = ceilo_plt
ceilo_cam.ix[:, 'cloud camera'] = cam_min.rolling(20, 5).mean()
ceilo_cam.dropna(inplace=True)
ceilo_cam.corr()


    

    
Out[4]:






  

    

      

      
CL_SCHA
      
CL_SCHB
      
cloud camera
    
  
  

    

      
CL_SCHA
      
1.000000
      
-0.109669
      
-0.049586
    
    

      
CL_SCHB
      
-0.109669
      
1.000000
      
0.435534
    
    

      
cloud camera
      
-0.049586
      
0.435534
      
1.000000
    
  

In [ ]:

    




    

In [5]:

    

fig, ax = plt.subplots()
fig.suptitle('Ceilometer and cloud camera')
c = ceilo_cam['CL_SCHA'].plot(ax=ax, label='ceilo 1')
c = ceilo_cam['CL_SCHB'].plot(ax=ax, label='ceilo 2')
#for i in cam.columns:
#    s = ax.scatter(cam.index, cam[i], c='r')
s = ax.scatter(ceilo_cam.index, ceilo_cam['cloud camera'], c='r')
plt.legend()
ax.set_ylim(0,9000)
ax.set_xlabel('Time 30/08/2016 in UTC+1')
ax.set_ylabel('Height [m]')
plt.tight_layout()
#plt.savefig('/home/tfinn/Desktop/ceilo_30_.png')
fig, ax = plt.subplots()
g = sns.jointplot("CL_SCHA", "cloud camera", data=ceilo_cam, kind='reg',
                  xlim=(0, 8000), ylim=(0, 8000), color="r", size=8)
#plt.savefig('/home/tfinn/Desktop/scatter_30_.png')
plt.show()
plt.close('all')


    

    




/home/tfinn/anaconda3/lib/python3.5/site-packages/statsmodels/nonparametric/kdetools.py:20: VisibleDeprecationWarning: using a non-integer number instead of an integer will result in an error in the future
  y = X[:m/2+1] + np.r_[0,X[m/2+1:],0]*1j






    













    













    

In [6]:

    

xy = pickle.load(open('/home/tfinn/Projects/pyclamster/data/xy.pk', mode='rb'))


    

In [7]:

    

x=xy[sorted(xy.keys())[0]][0][1]
y=xy[sorted(xy.keys())[0]][0][0]


    

In [8]:

    

plot_results2d(x, y, z=cam.iloc[0,0])
plt.show()