def create_geotiff(dt_aggregate, code='5min'):
pathhelper = utils.PathHelper(basedir=config.AGGREGATE_DIR,
code=code,
template='{code}_{timestamp}.h5')
rasterlayerkwargs = utils.rain_kwargs(
name='jet',
max_rain=2,
threshold=0.008,
)
aggregatepath = pathhelper.path(dt_aggregate)
tifpath_rd = os.path.join(config.IMG_DIR, 'geotiff', 'rd',
dt_aggregate.strftime('%Y-%m-%d-%H-%M.tiff'))
with h5py.File(aggregatepath, 'r') as h5:
array = h5['precipitation']
mask = np.equal(array, h5.attrs['fill_value'])
masked_array = np.ma.array(array, mask=mask)
# Create the rd tiff.
utils.makedir(os.path.dirname(tifpath_rd))
gridtools.RasterLayer(array=masked_array,
extent=h5.attrs['grid_extent'],
projection=h5.attrs['grid_projection'],
**rasterlayerkwargs).save(tifpath_rd, rgba=True)
logging.info('saved {}.'.format(os.path.basename(tifpath_rd)))
logging.debug('saved {}.'.format(tifpath_rd))
def create_geotiff(dt_aggregate, code='5min'):
pathhelper = utils.PathHelper(
basedir=config.AGGREGATE_DIR,
code=code,
template='{code}_{timestamp}.h5'
)
rasterlayerkwargs = utils.rain_kwargs(
name='jet', max_rain=2, threshold=0.008,
)
aggregatepath = pathhelper.path(dt_aggregate)
tifpath_rd = os.path.join(
config.IMG_DIR, 'geotiff', 'rd',
dt_aggregate.strftime('%Y-%m-%d-%H-%M.tiff')
)
with h5py.File(aggregatepath, 'r') as h5:
array = h5['precipitation']
mask = np.equal(array, h5.attrs['fill_value'])
masked_array = np.ma.array(array, mask=mask)
# Create the rd tiff.
utils.makedir(os.path.dirname(tifpath_rd))
gridtools.RasterLayer(array=masked_array,
extent=h5.attrs['grid_extent'],
projection=h5.attrs['grid_projection'],
**rasterlayerkwargs).save(tifpath_rd, rgba=True)
logging.info('saved {}.'.format(os.path.basename(tifpath_rd)))
logging.debug('saved {}.'.format(tifpath_rd))
def data_image(masked_array, max_rain=20, threshold=0.0):
""" """
basegrid = scans.BASEGRID
rasterlayerkwargs = utils.rain_kwargs(
name='jet', max_rain=max_rain, threshold=threshold,
)
return gridtools.RasterLayer(
array=masked_array,
extent=basegrid.extent,
projection=basegrid.projection,
**rasterlayerkwargs).image()
def data_image(masked_array, max_rain=20, threshold=0.0):
""" """
basegrid = scans.BASEGRID
rasterlayerkwargs = utils.rain_kwargs(
name='jet',
max_rain=max_rain,
threshold=threshold,
)
return gridtools.RasterLayer(array=masked_array,
extent=basegrid.extent,
projection=basegrid.projection,
**rasterlayerkwargs).image()
def _aggregate_radar(self, aggregatedatetime, method):
template = "aggregate.m{method}_%Y%m%d%H%M%S.{extension}"
path = os.path.join(
config.AGGREGATE_DIR, aggregatedatetime.strftime(template).format(method=method, extension="tif")
)
if os.path.exists(path):
logging.debug("We have this one in cache: {}".format(os.path.basename(path)))
return gdal.Open(path)
logging.info("doing {}".format(aggregatedatetime))
phkwargs = dict(basedir=config.COMPOSITE_DIR, template="{code}_{timestamp}.tif")
ph = utils.PathHelper(code=self.CODES[method], **phkwargs)
datetime_start = aggregatedatetime - datetime.timedelta(days=1)
datetime_stop = aggregatedatetime - datetime.timedelta(minutes=5)
text = "{}-{}".format(datetime_start.strftime("%Y%m%d%H%M"), datetime_stop.strftime("%Y%m%d%H%M"))
scandatetimes = utils.DateRange(text).iterdatetimes()
dataset = gdal.GetDriverByName(b"mem").CreateCopy(b"", gdal.Open(ph.path(datetime.datetime(2011, 1, 1))))
rain = np.ma.zeros(gridtools.BaseGrid(dataset).get_shape())
count = np.zeros(gridtools.BaseGrid(dataset).get_shape())
for scandatetime in scandatetimes:
logging.debug("adding {}".format(scandatetime))
composite = gdal.Open(ph.path(scandatetime))
if composite is None:
logging.warn("No composite found for method {} at {}".format(method, scandatetime))
continue
ma = gridtools.ds2ma(composite)
count += ~ma.mask # Where no mask, we count rain
rain += ma.filled(0)
rain /= 12 # Composite unit is mm/hr, but we add every 5 minutes.
rain.mask = np.less(count, 1)
dataset.GetRasterBand(1).WriteArray(rain.filled(config.NODATAVALUE))
gdal.GetDriverByName(b"GTiff").CreateCopy(path, dataset, 0, ["COMPRESS=DEFLATE"])
gridtools.RasterLayer(dataset, **utils.rain_kwargs(name="jet")).save(path.replace(".tif", ".png"))
# Adding the counts as tif
count_dataset = gdal.GetDriverByName(b"gtiff").Create(
path.replace(".tif", "_count.tif"), dataset.RasterXSize, dataset.RasterYSize, 1, gdalconst.GDT_UInt16
)
count_dataset.GetRasterBand(1).WriteArray(count)
return dataset
def _aggregate_radar(self, aggregatedatetime, method):
template = 'aggregate.m{method}_%Y%m%d%H%M%S.{extension}'
path = os.path.join(
config.AGGREGATE_DIR,
aggregatedatetime.strftime(template).format(
method=method,
extension='tif',
),
)
if os.path.exists(path):
logging.debug('We have this one in cache: {}'.format(
os.path.basename(path), ))
return gdal.Open(path)
logging.info('doing {}'.format(aggregatedatetime))
phkwargs = dict(
basedir=config.COMPOSITE_DIR,
template='{code}_{timestamp}.tif',
)
ph = utils.PathHelper(code=self.CODES[method], **phkwargs)
datetime_start = aggregatedatetime - datetime.timedelta(days=1)
datetime_stop = aggregatedatetime - datetime.timedelta(minutes=5)
text = '{}-{}'.format(
datetime_start.strftime('%Y%m%d%H%M'),
datetime_stop.strftime('%Y%m%d%H%M'),
)
scandatetimes = utils.DateRange(text).iterdatetimes()
dataset = gdal.GetDriverByName(b'mem').CreateCopy(
b'',
gdal.Open(ph.path(datetime.datetime(2011, 1, 1), )),
)
rain = np.ma.zeros(gridtools.BaseGrid(dataset).get_shape())
count = np.zeros(gridtools.BaseGrid(dataset).get_shape())
for scandatetime in scandatetimes:
logging.debug('adding {}'.format(scandatetime))
composite = gdal.Open(ph.path(scandatetime))
if composite is None:
logging.warn('No composite found for method {} at {}'.format(
method,
scandatetime,
))
continue
ma = gridtools.ds2ma(composite)
count += ~ma.mask # Where no mask, we count rain
rain += ma.filled(0)
rain /= 12 # Composite unit is mm/hr, but we add every 5 minutes.
rain.mask = np.less(count, 1)
dataset.GetRasterBand(1).WriteArray(rain.filled(config.NODATAVALUE))
gdal.GetDriverByName(b'GTiff').CreateCopy(path, dataset, 0,
['COMPRESS=DEFLATE'])
gridtools.RasterLayer(dataset, **utils.rain_kwargs(name='jet')).save(
path.replace('.tif', '.png'), )
# Adding the counts as tif
count_dataset = gdal.GetDriverByName(b'gtiff').Create(
path.replace('.tif', '_count.tif'),
dataset.RasterXSize,
dataset.RasterYSize,
1,
gdalconst.GDT_UInt16,
)
count_dataset.GetRasterBand(1).WriteArray(count)
return dataset
