import pytesmo.io.sat.ascat as ascat
import pytesmo.time_series as ts

import os
import matplotlib.pyplot as plt

ascat_folder = os.path.join('R:\\','Datapool_processed','WARP','WARP5.5',
                                         'ASCAT_WARP5.5_R1.2','080_ssm','netcdf')
ascat_grid_folder = os.path.join('R:\\','Datapool_processed','WARP','ancillary','warp5_grid')
#init the ASCAT_SSM reader with the paths

ascat_SSM_reader = ascat.AscatH25_SSM(ascat_folder,ascat_grid_folder)

ascat_ts = ascat_SSM_reader.read_ssm(45,0)
#plot soil moisture
ascat_ts.data['sm'].plot()

<matplotlib.axes.AxesSubplot at 0x22ee3550>

#calculate anomaly based on moving +- 17 day window
anomaly = ts.anomaly.calc_anomaly(ascat_ts.data['sm'], window_size=35)
anomaly.plot()

<matplotlib.axes.AxesSubplot at 0x269109e8>

#calculate climatology
climatology = ts.anomaly.calc_climatology(ascat_ts.data['sm'])
climatology.plot()

<matplotlib.axes.AxesSubplot at 0x1bc54ef0>

#calculate anomaly based on climatology
anomaly_clim = ts.anomaly.calc_anomaly(ascat_ts.data['sm'], climatology=climatology)
anomaly_clim.plot()

<matplotlib.axes.AxesSubplot at 0x1bc76860>