GOES-13 Downloader

This is a general example demonstrating how download and view GOES-13 data from DISSM/INPE using TATHU support.

/home/docs/checkouts/readthedocs.org/user_builds/tathu/conda/latest/lib/python3.11/site-packages/osgeo/osr.py:424: FutureWarning: Neither osr.UseExceptions() nor osr.DontUseExceptions() has been explicitly called. In GDAL 4.0, exceptions will be enabled by default.
  warnings.warn(

Download GOES-13 data (DISSM):   0%|          | 0/2 [00:00<?, ?files/s]
Download GOES-13 data (DISSM):  50%|█████     | 1/2 [00:01<00:01,  1.92s/files]
Download GOES-13 data (DISSM): 100%|██████████| 2/2 [00:03<00:00,  1.85s/files]
Download GOES-13 data (DISSM): 100%|██████████| 2/2 [00:03<00:00,  1.86s/files]
/home/docs/checkouts/readthedocs.org/user_builds/tathu/conda/latest/lib/python3.11/site-packages/cartopy/mpl/feature_artist.py:143: UserWarning: facecolor will have no effect as it has been defined as "never".
  warnings.warn('facecolor will have no effect as it has been '

import glob
from datetime import datetime

from osgeo import gdal

from tathu.constants import LAT_LONG_WGS84_BRAZIL_NORTH_EXTENT
from tathu.downloader.goes import DISSM
from tathu.progress import TqdmProgress
from tathu.satellite import goes13
from tathu.visualizer import MapView

### Setup Parameters ###

# Geographic area of regular grid
extent = LAT_LONG_WGS84_BRAZIL_NORTH_EXTENT

# Grid resolution (kilometers)
resolution = 4.0

# Data directory
dir = './goes13-dissm/'

# Download 08 April 2022, Channel 13, 00:xx UTC
start = end = datetime.strptime('20170408', '%Y%m%d')
hours = ['00']

# From DISSM (crop/remapped version - GOES-13)
DISSM.download('goes13', 'retangular_4km/ch4_bin',
    start, end, hours, dir,
    progress=TqdmProgress('Download GOES-13 data (DISSM)', 'files'))

# Search images
query = dir + '/**/*'

# Get files
files = sorted(glob.glob(query, recursive=True))

# Show first file
grid = goes13.sat2grid(files[0], extent, resolution, progress=gdal.TermProgress_nocb)

# Visualize result
m = MapView(extent)
m.plotImage(grid, cmap='Greys', vmin=180.0, vmax=320.0)
m.show()