def command(sourcepath):
""" Do something spectacular. """
dataset = gdal.Open(sourcepath)
array = read_as_shared_array(dataset)
shared = rasters.array2dataset(array, crs=None, extent=None)
shared.SetProjection(dataset.GetProjection())
shared.SetGeoTransform(dataset.GetGeoTransform())
process = multiprocessing.Process(
target=func,
kwargs=dict(shared=shared),
)
process.start()
process.join()
print(shared.ReadAsArray()[0,0])
def get_data_for_polygon(self, wkb, crs, size):
"""
Return a numpy array for the data.
"""
# Quick out if polygon bounds match polygon
geometry = vectors.Geometry(wkb)
envelope = geometry.envelope
extent = geometry.extent
nodatavalue = self.info['nodatavalue']
datatype = self.info['datatype']
# Initialize resulting array to nodatavalue
dtype = gdal_array.flip_code(datatype)
array = np.ones(
(1, size[1], size[0]),
dtype=dtype,
) * dtype(nodatavalue)
# Create dataset and use it to retrieve data from the store
dataset = rasters.array2dataset(array=array, extent=extent, crs=crs)
self.warpinto(dataset)
dataset.FlushCache()
# Cut when necessary
if not envelope.Equals(wkb):
source = OGR_MEM_DRIVER.CreateDataSource('')
sr = projections.get_spatial_reference(crs)
layer = source.CreateLayer(b'', sr)
defn = layer.GetLayerDefn()
feature = ogr.Feature(defn)
feature.SetGeometry(wkb)
layer.CreateFeature(feature)
gdal.RasterizeLayer(dataset, (1,), layer,
burn_values=(nodatavalue,))
dataset.FlushCache()
return np.ma.masked_equal(array, nodatavalue, copy=False)