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 create_png(products, **kwargs):
"""
Create image for products.
This is a kind of sandbox version.
"""
utils.makedir(config.IMG_DIR)
# Load some images
img_shape = shape_image()
img_blue = plain_image(color=(0, 0, 127))
img_shape_filled = shape_image_filled()
# Get dutch time label
tz_amsterdam = pytz.timezone('Europe/Amsterdam')
tz_utc = pytz.timezone('UTC')
# Loop products
for product in products:
utc = tz_utc.localize(product.datetime)
amsterdam = utc.astimezone(tz_amsterdam)
label = amsterdam.strftime('%Y-%m-%d %H:%M')
label_from_kwargs = kwargs.get('label', '')
if label_from_kwargs:
label += ' ' + label_from_kwargs
offset = 0.1, 0.9
# Get data image
try:
with product.get() as h5:
array = h5['precipitation'][...] / h5.attrs['composite_count']
mask = np.equal(array, h5.attrs['fill_value'])
img_radars = radars_image(h5=h5, label=label, offset=offset)
except IOError:
logging.debug('Does not exist: {}'.format(product.path))
continue
masked_array = np.ma.array(array, mask=mask)
img_rain = data_image(masked_array, max_rain=2, threshold=0.008)
timestamp = utils.datetime2timestamp(product.datetime)
filename = '{}{}.{}'.format(
timestamp,
kwargs.get('postfix', ''),
kwargs.get('format', 'png'),
)
# Merge and save
path = os.path.join(config.IMG_DIR, filename)
utils.merge([
img_radars,
img_rain,
img_shape,
img_shape_filled,
img_blue,
]).save(path)
logging.info('saved {}.'.format(os.path.basename(path)))
logging.debug('saved {}.'.format(path))
def create_png_for_animated_gif(products, **kwargs):
"""
Create image for products.
This is the tweaked version that creates the pngs for use in the
animated gif.
"""
utils.makedir(config.IMG_DIR)
# Load some images
img_mapbox = mapbox_image()
img_osm = osm_image()
img_shape = shape_image()
img_blue = plain_image(color=(0, 0, 127))
img_shape_filled = shape_image_filled()
# Get dutch time label
tz_amsterdam = pytz.timezone('Europe/Amsterdam')
tz_utc = pytz.timezone('UTC')
# Loop products
for product in products:
utc = tz_utc.localize(product.datetime)
amsterdam = utc.astimezone(tz_amsterdam)
#label = amsterdam.strftime('%Y-%m-%d %H:%M')
label = amsterdam.strftime('%H:%M')
offset = 0.25, 0.82
# Get data image
with product.get() as h5:
array = h5['precipitation'][...] / h5.attrs['composite_count']
mask = np.equal(array, h5.attrs['fill_value'])
img_radars = radars_image(h5=h5, label=label, offset=offset)
masked_array = np.ma.array(array, mask=mask)
img_rain = data_image(masked_array, max_rain=2, threshold=0.008)
timestamp = utils.datetime2timestamp(product.datetime)
filename = '{}{}.{}'.format(
timestamp,
kwargs.get('postfix', ''),
kwargs.get('format', 'png'),
)
# Merge and save
path = os.path.join(config.IMG_DIR, filename)
utils.merge([
img_radars,
img_rain,
img_mapbox,
img_shape,
img_shape_filled,
img_blue,
]).save(path)
logging.info('saved {}.'.format(os.path.basename(path)))
logging.debug('saved {}.'.format(path))
def create_png(products, **kwargs):
"""
Create image for products.
This is a kind of sandbox version.
"""
utils.makedir(config.IMG_DIR)
# Load some images
img_shape = shape_image()
img_blue = plain_image(color=(0, 0, 127))
img_shape_filled = shape_image_filled()
# Get dutch time label
tz_amsterdam = pytz.timezone('Europe/Amsterdam')
tz_utc = pytz.timezone('UTC')
# Loop products
for product in products:
utc = tz_utc.localize(product.datetime)
amsterdam = utc.astimezone(tz_amsterdam)
label = amsterdam.strftime('%Y-%m-%d %H:%M')
label_from_kwargs = kwargs.get('label', '')
if label_from_kwargs:
label += ' ' + label_from_kwargs
offset = 0.1, 0.9
# Get data image
try:
with product.get() as h5:
array = h5['precipitation'][...] / h5.attrs['composite_count']
mask = np.equal(array, h5.attrs['fill_value'])
img_radars = radars_image(h5=h5, label=label, offset=offset)
except IOError:
logging.debug('Does not exist: {}'.format(product.path))
continue
masked_array = np.ma.array(array, mask=mask)
img_rain = data_image(masked_array, max_rain=2, threshold=0.008)
timestamp = utils.datetime2timestamp(product.datetime)
filename = '{}{}.{}'.format(
timestamp, kwargs.get('postfix', ''), kwargs.get('format', 'png'),
)
# Merge and save
path = os.path.join(config.IMG_DIR, filename)
utils.merge([
img_radars,
img_rain,
img_shape,
img_shape_filled,
img_blue,
]).save(path)
logging.info('saved {}.'.format(os.path.basename(path)))
logging.debug('saved {}.'.format(path))
def create_png_for_animated_gif(products, **kwargs):
"""
Create image for products.
This is the tweaked version that creates the pngs for use in the
animated gif.
"""
utils.makedir(config.IMG_DIR)
# Load some images
img_mapbox = mapbox_image()
img_osm = osm_image()
img_shape = shape_image()
img_blue = plain_image(color=(0, 0, 127))
img_shape_filled = shape_image_filled()
# Get dutch time label
tz_amsterdam = pytz.timezone('Europe/Amsterdam')
tz_utc = pytz.timezone('UTC')
# Loop products
for product in products:
utc = tz_utc.localize(product.datetime)
amsterdam = utc.astimezone(tz_amsterdam)
#label = amsterdam.strftime('%Y-%m-%d %H:%M')
label = amsterdam.strftime('%H:%M')
offset = 0.25, 0.82
# Get data image
with product.get() as h5:
array = h5['precipitation'][...] / h5.attrs['composite_count']
mask = np.equal(array, h5.attrs['fill_value'])
img_radars = radars_image(h5=h5, label=label, offset=offset)
masked_array = np.ma.array(array, mask=mask)
img_rain = data_image(masked_array, max_rain=2, threshold=0.008)
timestamp = utils.datetime2timestamp(product.datetime)
filename = '{}{}.{}'.format(
timestamp, kwargs.get('postfix', ''), kwargs.get('format', 'png'),
)
# Merge and save
path = os.path.join(config.IMG_DIR, filename)
utils.merge([
img_radars,
img_rain,
img_mapbox,
img_shape,
img_shape_filled,
img_blue,
]).save(path)
logging.info('saved {}.'.format(os.path.basename(path)))
logging.debug('saved {}.'.format(path))
def __init__(self, datetime, max_age=86400):
"""
Set datetime and empty connection dictionary. Max age is in
seconds, measured from datetime.
"""
utils.makedir(config.SOURCE_DIR)
self.datetime = datetime
self.max_age = max_age
self.connections = {}
# Check what is already there.
self.arrived = []
def __init__(self, datetime, max_age=86400):
"""
Set datetime and empty connection dictionary. Max age is in
seconds, measured from datetime.
"""
utils.makedir(config.SOURCE_DIR)
self.datetime = datetime
self.max_age = max_age
self.connections = {}
# Check what is already there.
self.arrived = []
def create_tif(products, image_dir=None, **kwargs):
""" Save a tif with metadata """
if image_dir:
target_dir = image_dir
else:
target_dir = config.IMG_DIR
utils.makedir(target_dir)
# Loop products
for product in products:
# Get data
try:
with h5py.File(product.path, 'r') as h5:
data = np.ma.masked_equal(h5['precipitation'],
h5.attrs['fill_value'])
attrs = dict(h5.attrs)
except IOError:
logging.info('Not found: {}, skipping.'.format(product))
continue
# make a dataset
raster_layer = gridtools.RasterLayer(
array=data,
extent=attrs['grid_extent'],
projection=attrs['grid_projection'],
)
mem = raster_layer.create_dataset(datatype=6)
mem.SetProjection(PROJECTION_RD_WKT)
band = mem.GetRasterBand(1)
band.WriteArray(data.filled(band.GetNoDataValue()))
for k, v in attrs.items():
if hasattr(v, 'tolist'):
v = json.dumps(v.tolist())
band.SetMetadataItem(str(k), str(v))
timestamp = utils.datetime2timestamp(product.datetime)
filename = '{}{}.{}'.format(
timestamp,
kwargs.get('postfix', ''),
kwargs.get('format', 'png'),
)
path = os.path.join(target_dir, filename)
driver = gdal.GetDriverByName(b'gtiff')
driver.CreateCopy(path, mem)
logging.info('saved {}.'.format(os.path.basename(path)))
logging.debug('saved {}.'.format(path))
def create_tif(products, image_dir=None, **kwargs):
""" Save a tif with metadata """
if image_dir:
target_dir = image_dir
else:
target_dir = config.IMG_DIR
utils.makedir(target_dir)
# Loop products
for product in products:
# Get data
try:
with h5py.File(product.path, 'r') as h5:
data = np.ma.masked_equal(h5['precipitation'],
h5.attrs['fill_value'])
attrs = dict(h5.attrs)
except IOError:
logging.info('Not found: {}, skipping.'.format(product))
continue
# make a dataset
raster_layer = gridtools.RasterLayer(
array=data,
extent=attrs['grid_extent'],
projection=attrs['grid_projection'],
)
mem = raster_layer.create_dataset(datatype=6)
mem.SetProjection(PROJECTION_RD_WKT)
band = mem.GetRasterBand(1)
band.WriteArray(data.filled(band.GetNoDataValue()))
for k, v in attrs.items():
if hasattr(v, 'tolist'):
v = json.dumps(v.tolist())
band.SetMetadataItem(str(k), str(v))
timestamp = utils.datetime2timestamp(product.datetime)
filename = '{}{}.{}'.format(
timestamp, kwargs.get('postfix', ''), kwargs.get('format', 'png'),
)
path = os.path.join(target_dir, filename)
driver = gdal.GetDriverByName(b'gtiff')
driver.CreateCopy(path, mem)
logging.info('saved {}.'.format(os.path.basename(path)))
logging.debug('saved {}.'.format(path))
def get(self):
"""
Return a readonly hdf5 dataset for requested scans.
If the dataset is not available, it is created.
If it is available, but lacks some scan requested, it is appended.
"""
utils.makedir(os.path.dirname(self.path))
try:
# Improperly closed h5 files cannot be opened.
dataset = h5py.File(self.path, 'a')
except IOError:
dataset = h5py.File(self.path, 'w')
if len(dataset):
logging.debug(
'Multiscan file already has {}.'.format(', '.join(dataset))
)
else:
logging.debug('Starting with empty multiscan file.')
for scancode in self.scancodes:
scan = ScanSignature(
scandatetime=self.multiscandatetime, scancode=scancode,
).get_scan(self.grid)
if scan is None or scancode in dataset:
continue
if scan.is_readable():
self._add(dataset=dataset, scan=scan)
else:
# Remove it.
scanpath = scan.signature.get_scanpath()
try:
shutil.move(scanpath, config.RADAR_DIR)
logging.warn('Removed corrupt scanfile {}'.format(
os.path.basename(scanpath),
))
except (OSError, IOError):
pass # No permission.
dataset.close()
return h5py.File(self.path, 'r')
def get(self):
"""
Return a readonly hdf5 dataset for requested scans.
If the dataset is not available, it is created.
If it is available, but lacks some scan requested, it is appended.
"""
utils.makedir(os.path.dirname(self.path))
try:
# Improperly closed h5 files cannot be opened.
dataset = h5py.File(self.path, 'a')
except IOError:
dataset = h5py.File(self.path, 'w')
if len(dataset):
logging.debug('Multiscan file already has {}.'.format(
', '.join(dataset)))
else:
logging.debug('Starting with empty multiscan file.')
for scancode in self.scancodes:
scan = ScanSignature(
scandatetime=self.multiscandatetime,
scancode=scancode,
).get_scan(self.grid)
if scan is None or scancode in dataset:
continue
if scan.is_readable():
self._add(dataset=dataset, scan=scan)
else:
# Remove it.
scanpath = scan.signature.get_scanpath()
try:
shutil.move(scanpath, config.RADAR_DIR)
logging.warn('Removed corrupt scanfile {}'.format(
os.path.basename(scanpath), ))
except (OSError, IOError):
pass # No permission.
dataset.close()
return h5py.File(self.path, 'r')
def publish_local(self, cascade=False):
""" Publish to target dirs as configured in config. """
# Prepare dirs
logging.debug(
'Preparing {} dirs.'.format(len(config.COPY_TARGET_DIRS)),
)
for target_dir in config.COPY_TARGET_DIRS:
for path in [path
for d in config.PRODUCT_CODE.values()
for path in d.values()]:
utils.makedir(os.path.join(target_dir, path))
# Do the copying
logging.debug('Copying publications.')
for publication in self.publications(cascade=cascade):
proddict = config.PRODUCT_CODE[publication.timeframe]
for target_dir in config.COPY_TARGET_DIRS:
target_subdir = os.path.join(
target_dir,
proddict[publication.prodcode],
)
shutil.copy(publication.path, target_subdir)
logging.info('Local target dir copying complete.')
def create(self):
""" Return newly created threddsfile. """
utils.makedir(os.path.dirname(self.path))
h5 = h5py.File(self.path)
# East
east = scans.BASEGRID.get_grid()[0][0]
dataset = h5.create_dataset(
'east', east.shape, east.dtype,
compression='gzip', shuffle=True,
)
dataset[...] = east
# North
north = scans.BASEGRID.get_grid()[1][:, 0]
dataset = h5.create_dataset(
'north', north.shape, north.dtype,
compression='gzip', shuffle=True,
)
dataset[...] = north
# Time
time = h5.create_dataset(
'time', [self.timesteps], np.uint32,
compression='gzip', shuffle=True,
)
time.attrs['standard_name'] = b'time'
time.attrs['long_name'] = b'time'
time.attrs['calendar'] = b'gregorian'
time.attrs['units'] = self.datetime.strftime(
'seconds since %Y-%m-%d'
)
time[...] = self._time()
# Precipitation
shape = scans.BASEGRID.get_shape() + tuple([self.timesteps])
dataset = h5.create_dataset(
'precipitation', shape, np.float32, fillvalue=config.NODATAVALUE,
compression='gzip', shuffle=True, chunks=(20, 20, 24)
)
# Availability
dataset = h5.create_dataset(
'available', [self.timesteps], np.uint8, fillvalue=0,
compression='gzip', shuffle=True,
)
dataset[...] = 0
# Dimensions
h5['precipitation'].dims.create_scale(h5['north'])
h5['precipitation'].dims.create_scale(h5['east'])
h5['precipitation'].dims.create_scale(h5['time'])
h5['precipitation'].dims[0].attach_scale(h5['north'])
h5['precipitation'].dims[1].attach_scale(h5['east'])
h5['precipitation'].dims[2].attach_scale(h5['time'])
h5['available'].dims.create_scale(h5['time'])
h5['available'].dims[0].attach_scale(h5['time'])
logging.info(
'Created ThreddsFile {}'.format(os.path.basename(self.path)),
)
logging.debug(self.path)
return h5
def create(self):
""" Return newly created threddsfile. """
utils.makedir(os.path.dirname(self.path))
h5 = h5py.File(self.path)
# East
east = scans.BASEGRID.get_grid()[0][0]
dataset = h5.create_dataset(
'east',
east.shape,
east.dtype,
compression='gzip',
shuffle=True,
)
dataset[...] = east
# North
north = scans.BASEGRID.get_grid()[1][:, 0]
dataset = h5.create_dataset(
'north',
north.shape,
north.dtype,
compression='gzip',
shuffle=True,
)
dataset[...] = north
# Time
time = h5.create_dataset(
'time',
[self.timesteps],
np.uint32,
compression='gzip',
shuffle=True,
)
time.attrs['standard_name'] = b'time'
time.attrs['long_name'] = b'time'
time.attrs['calendar'] = b'gregorian'
time.attrs['units'] = self.datetime.strftime('seconds since %Y-%m-%d')
time[...] = self._time()
# Precipitation
shape = scans.BASEGRID.get_shape() + tuple([self.timesteps])
dataset = h5.create_dataset('precipitation',
shape,
np.float32,
fillvalue=config.NODATAVALUE,
compression='gzip',
shuffle=True,
chunks=(20, 20, 24))
# Availability
dataset = h5.create_dataset(
'available',
[self.timesteps],
np.uint8,
fillvalue=0,
compression='gzip',
shuffle=True,
)
dataset[...] = 0
# Dimensions
h5['precipitation'].dims.create_scale(h5['north'])
h5['precipitation'].dims.create_scale(h5['east'])
h5['precipitation'].dims.create_scale(h5['time'])
h5['precipitation'].dims[0].attach_scale(h5['north'])
h5['precipitation'].dims[1].attach_scale(h5['east'])
h5['precipitation'].dims[2].attach_scale(h5['time'])
h5['available'].dims.create_scale(h5['time'])
h5['available'].dims[0].attach_scale(h5['time'])
logging.info(
'Created ThreddsFile {}'.format(os.path.basename(self.path)), )
logging.debug(self.path)
return h5