def data(self,
data=None,
offset=None,
size=None,
shape=None,
as_memoryview=False):
"""
Read or writes pixel values for this band. Blocks of data can
be accessed by specifying the width, height and offset of the
desired block. The same specification can be used to update
parts of a raster by providing an array of values.
Allowed input data types are bytes, memoryview, list, tuple, and array.
"""
offset = offset or (0, 0)
size = size or (self.width - offset[0], self.height - offset[1])
shape = shape or size
if any(x <= 0 for x in size):
raise ValueError('Offset too big for this raster.')
if size[0] > self.width or size[1] > self.height:
raise ValueError('Size is larger than raster.')
# Create ctypes type array generator
ctypes_array = GDAL_TO_CTYPES[self.datatype()] * (shape[0] * shape[1])
if data is None:
# Set read mode
access_flag = 0
# Prepare empty ctypes array
data_array = ctypes_array()
else:
# Set write mode
access_flag = 1
# Instantiate ctypes array holding the input data
if isinstance(data, (bytes, memoryview)) or (numpy and isinstance(
data, numpy.ndarray)):
data_array = ctypes_array.from_buffer_copy(data)
else:
data_array = ctypes_array(*data)
# Access band
capi.band_io(self._ptr, access_flag, offset[0], offset[1], size[0],
size[1], byref(data_array), shape[0], shape[1],
self.datatype(), 0, 0)
# Return data as numpy array if possible, otherwise as list
if data is None:
if as_memoryview:
return memoryview(data_array)
elif numpy:
# reshape() needs a reshape parameter with the height first.
return numpy.frombuffer(data_array,
dtype=numpy.dtype(data_array)).reshape(
tuple(reversed(size)))
else:
return list(data_array)
else:
self._flush()
def data(self, data=None, offset=None, size=None, shape=None, as_memoryview=False):
"""
Reads or writes pixel values for this band. Blocks of data can
be accessed by specifying the width, height and offset of the
desired block. The same specification can be used to update
parts of a raster by providing an array of values.
Allowed input data types are bytes, memoryview, list, tuple, and array.
"""
if not offset:
offset = (0, 0)
if not size:
size = (self.width - offset[0], self.height - offset[1])
if not shape:
shape = size
if any(x <= 0 for x in size):
raise ValueError('Offset too big for this raster.')
if size[0] > self.width or size[1] > self.height:
raise ValueError('Size is larger than raster.')
# Create ctypes type array generator
ctypes_array = GDAL_TO_CTYPES[self.datatype()] * (shape[0] * shape[1])
if data is None:
# Set read mode
access_flag = 0
# Prepare empty ctypes array
data_array = ctypes_array()
else:
# Set write mode
access_flag = 1
# Instantiate ctypes array holding the input data
if isinstance(data, (bytes, memoryview)) or (numpy and isinstance(data, numpy.ndarray)):
data_array = ctypes_array.from_buffer_copy(data)
else:
data_array = ctypes_array(*data)
# Access band
capi.band_io(self._ptr, access_flag, offset[0], offset[1],
size[0], size[1], byref(data_array), shape[0],
shape[1], self.datatype(), 0, 0)
# Return data as numpy array if possible, otherwise as list
if data is None:
if as_memoryview:
return memoryview(data_array)
elif numpy:
# reshape() needs a reshape parameter with the height first.
return numpy.frombuffer(
data_array, dtype=numpy.dtype(data_array)
).reshape(tuple(reversed(size)))
else:
return list(data_array)
else:
self._flush()
# Set write mode
access_flag = 1
# Instantiate ctypes array holding the input data
<<<<<<< HEAD
if isinstance(data, (bytes, six.memoryview)) or (numpy and isinstance(data, numpy.ndarray)):
=======
if isinstance(data, (bytes, memoryview)) or (numpy and isinstance(data, numpy.ndarray)):
>>>>>>> 37c99181c9a6b95433d60f8c8ef9af5731096435
data_array = ctypes_array.from_buffer_copy(data)
else:
data_array = ctypes_array(*data)
# Access band
capi.band_io(self._ptr, access_flag, offset[0], offset[1],
size[0], size[1], byref(data_array), shape[0],
shape[1], self.datatype(), 0, 0)
# Return data as numpy array if possible, otherwise as list
if data is None:
if as_memoryview:
return memoryview(data_array)
elif numpy:
# reshape() needs a reshape parameter with the height first.
return numpy.frombuffer(
data_array, dtype=numpy.dtype(data_array)
).reshape(tuple(reversed(size)))
else:
return list(data_array)
else:
self._flush()
from ctypes import byref, c_int
