def create_layers(self):
data_range = RASTER_METEROLOGICAL_DATA_RANGE[self.map_class]
# get a list with geo codes and city names from available states
for geocode, city_name in get_cities().items():
raster_name = None
raster_date = None
# check the last raster file available by city
raster_dir_path = os.path.join(
RASTER_PATH,
'meteorological',
'city',
self.map_class,
str(geocode),
)
search_path = os.path.join(raster_dir_path, '*')
for raster_file_path in glob(search_path, recursive=True):
# filter by tiff format
if not raster_file_path[-3:] == 'tif':
continue
_raster_name = raster_file_path.split(os.sep)[-1]
_raster_date = datetime.strptime(_raster_name, '%Y%m%d.tif')
if raster_date is None or raster_date < _raster_date:
raster_name = _raster_name
raster_date = _raster_date
# skip if no file found
if raster_name is None:
continue
# layer configuration definition
layer_name = city_name.upper().replace(' ', '_')
layer_title = city_name.title()
vmin, vmax = data_range
layer_conf = {
# general information
'map_class': self.map_class,
'geocode': geocode,
'name': layer_name,
'rgb': '#FF9900',
'title': layer_title,
'date_time': str(datetime.now()),
# projection and data range
'wms_srs': self.map_config['wms_srs'],
'crs_proj': self.map_config['crs_proj'],
'vmin': vmin,
'vmax': vmax,
# path
'file_name': '%s.map' % geocode,
'data_name': '%s.tif' % raster_date.strftime('%Y%m%d'),
'dir_path': os.path.join(
self.path['local_mapfile_dir'], 'layers', self.map_class
),
}
self.create_layer(layer_conf)
def test_get_cities(self):
"""
:return:
"""
cities = dbdata.get_cities()
assert cities[3304557] == 'Rio de Janeiro'
def create_layers(self):
data_range = RASTER_METEROLOGICAL_DATA_RANGE[self.map_class]
# get a list with geo codes and city names from available states
for geocode, city_name in get_cities().items():
raster_name = None
raster_date = None
# check the last raster file available by city
raster_dir_path = os.path.join(
RASTER_PATH, 'meteorological', 'city', self.map_class,
str(geocode),
)
search_path = os.path.join(
raster_dir_path, '*'
)
for raster_file_path in glob(search_path, recursive=True):
# filter by tiff format
if not raster_file_path[-3:] == 'tif':
continue
_raster_name = raster_file_path.split(os.sep)[-1]
_raster_date = datetime.strptime(_raster_name, '%Y%m%d.tif')
if raster_date is None or raster_date < _raster_date:
raster_name = _raster_name
raster_date = _raster_date
# skip if no file found
if raster_name is None:
continue
# layer configuration definition
layer_name = city_name.upper().replace(' ', '_')
layer_title = city_name.title()
vmin, vmax = data_range
layer_conf = {
# general information
'map_class': self.map_class,
'geocode': geocode,
'name': layer_name,
'rgb': '#FF9900',
'title': layer_title,
'date_time': str(datetime.now()),
# projection and data range
'wms_srs': self.map_config['wms_srs'],
'crs_proj': self.map_config['crs_proj'],
'vmin': vmin,
'vmax': vmax,
# path
'file_name': '%s.map' % geocode,
'data_name': '%s.tif' % raster_date.strftime('%Y%m%d'),
'dir_path': os.path.join(
self.path['local_mapfile_dir'],
'layers', self.map_class
)
}
self.create_layer(layer_conf)
def generate_raster_cities(
raster_class: str,
date_start: datetime=None
):
"""
Create raster images by city using as mask a shapefile and background
a raster file of the whole country.
Each city can have raster file for datetime regards the datetime from
the original file (whole country).
:param raster_class:
:param date_start:
:return:
"""
path_search = os.path.join(
RASTER_PATH,
'meteorological', 'country', raster_class, '*'
)
cities = get_cities().items()
n_processes = mp.cpu_count()
for raster_input_file_path in glob(path_search, recursive=True):
raster_name = raster_input_file_path.split(os.sep)[-1]
# filter by tiff format
if not raster_name[-3:] == 'tif':
continue
# filter by date
raster_date = get_date_from_file_name(raster_name)
if date_start is not None and raster_date < date_start:
continue
# processing
p = mp.Pool(n_processes)
p.map(
MeteorologicalRasterProcess(
raster_class, raster_date, raster_input_file_path
), cities
)
p.close()
p.join()
def generate_raster_cities(raster_class: str, date_start: datetime = None):
"""
Create raster images by city using as mask a shapefile and background
a raster file of the whole country.
Each city can have raster file for datetime regards the datetime from
the original file (whole country).
:param raster_class:
:param date_start:
:return:
"""
path_search = os.path.join(
RASTER_PATH, 'meteorological', 'country', raster_class, '*'
)
cities = get_cities().items()
n_processes = mp.cpu_count()
for raster_input_file_path in glob(path_search, recursive=True):
raster_name = raster_input_file_path.split(os.sep)[-1]
# filter by tiff format
if not raster_name[-3:] == 'tif':
continue
# filter by date
raster_date = get_date_from_file_name(raster_name)
if date_start is not None and raster_date < date_start:
continue
# processing
p = mp.Pool(n_processes)
p.map(
MeteorologicalRasterProcess(
raster_class, raster_date, raster_input_file_path
),
cities,
)
p.close()
p.join()