#!/usr/bin/env python
# coding: utf-8

# # Reading OLCI data from Sentinel 3 with Pytroll/Satpy

# This example shows how to read and resample Sentinel 3 OLCI level 1 data (as can be obtained on the scihub website).

# ## Find the files and create the scene object
# To find the files, we give the base directory containing the S3* directories, and filter by time to load just one segment.

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from datetime import datetime

from satpy import Scene, find_files_and_readers

files = find_files_and_readers(sensor='olci',
                               start_time=datetime(2018, 8, 29, 8, 26),
                               end_time=datetime(2018, 8, 29, 8, 27),
                               base_dir="/data/temp/Martin.Raspaud/s3",
                               reader='nc_olci_l1b')

scn = Scene(filenames=files)


# ## Creating and visualizing a color composite
# Here we generate a `true_color` composite and display it. It is in original data projection, no resampling has been performed yet.

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composite = 'true_color'

scn.load([composite])
scn.show(composite)


# ## Resampling the data
# We now resample the data to an area covering northern Europe in polar-stereographic projection. To define such an area, have a look at the pyresample documentation.
# The coastlines are added under the hood by pycoast, be sure to have it installed before running this example.

# In[5]:


newscn = scn.resample('euron1')
newscn.show(composite, {'coast_dir': '/home/a001673/data/shapes/', 'color': (255, 255, 0), 'resolution': 'i'})


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