def _import_variable(c_variable):
# Import variable data.
data = _import_array(c_variable.data_type, c_variable.num_elements,
c_variable.data)
num_dimensions = c_variable.num_dimensions
if num_dimensions == 0:
variable = Variable(numpy.asscalar(data))
else:
data = data.reshape(
[c_variable.dimension[i] for i in range(num_dimensions)])
dimension = [
_get_py_dimension_type(c_variable.dimension_type[i])
for i in range(num_dimensions)
]
variable = Variable(data, dimension)
# Import variable attributes.
if c_variable.unit != _ffi.NULL:
variable.unit = _decode_string(_ffi.string(c_variable.unit))
if c_variable.data_type != _lib.harp_type_string:
variable.valid_min = _import_scalar(c_variable.data_type,
c_variable.valid_min)
variable.valid_max = _import_scalar(c_variable.data_type,
c_variable.valid_max)
if c_variable.description:
variable.description = _decode_string(
_ffi.string(c_variable.description))
return variable
def _import_product(c_product):
product = Product()
# Import product attributes.
if c_product.source_product:
product.source_product = _decode_string(_ffi.string(c_product.source_product))
if c_product.history:
product.history = _decode_string(_ffi.string(c_product.history))
# Import variables.
for i in range(c_product.num_variables):
c_variable_ptr = c_product.variable[i]
variable = _import_variable(c_variable_ptr[0])
setattr(product, _decode_string(_ffi.string(c_variable_ptr[0].name)), variable)
return product
def _import_product(c_product):
product = Product()
# Import product attributes.
if c_product.source_product:
product.source_product = _decode_string(
_ffi.string(c_product.source_product))
if c_product.history:
product.history = _decode_string(_ffi.string(c_product.history))
# Import variables.
for i in range(c_product.num_variables):
c_variable_ptr = c_product.variable[i]
variable = _import_variable(c_variable_ptr[0])
setattr(product, _decode_string(_ffi.string(c_variable_ptr[0].name)),
variable)
return product
def __init__(self, errno=None, strerror=None):
if errno is None:
errno = _lib.harp_errno
if strerror is None:
strerror = _decode_string(_ffi.string(_lib.harp_errno_to_string(errno)))
super(CLibraryError, self).__init__(errno, strerror)
self.errno = errno
self.strerror = strerror
def __init__(self, errno=None, strerror=None):
if errno is None:
errno = _lib.harp_errno
if strerror is None:
strerror = _decode_string(
_ffi.string(_lib.harp_errno_to_string(errno)))
super(CLibraryError, self).__init__(errno, strerror)
self.errno = errno
self.strerror = strerror
def _import_array(c_data_type, c_num_elements, c_data):
if c_data_type == _lib.harp_type_string:
data = numpy.empty((c_num_elements,), dtype=numpy.object)
for i in range(c_num_elements):
# NB. The _ffi.string() method returns a copy of the C string.
data[i] = _decode_string(_ffi.string(c_data.string_data[i]))
return data
# NB. The _ffi.buffer() method, as well as the numpy.frombuffer() method, provide a view on the C array; neither
# method incurs a copy.
c_data_buffer = _ffi.buffer(c_data.ptr, c_num_elements * _lib.harp_get_size_for_type(c_data_type))
return numpy.copy(numpy.frombuffer(c_data_buffer, dtype=_get_py_data_type(c_data_type)))
def _import_array(c_data_type, c_num_elements, c_data):
if c_data_type == _lib.harp_type_string:
data = numpy.empty((c_num_elements, ), dtype=numpy.object)
for i in range(c_num_elements):
# NB. The _ffi.string() method returns a copy of the C string.
data[i] = _decode_string(_ffi.string(c_data.string_data[i]))
return data
# NB. The _ffi.buffer() method, as well as the numpy.frombuffer() method, provide a view on the C array; neither
# method incurs a copy.
c_data_buffer = _ffi.buffer(
c_data.ptr, c_num_elements * _lib.harp_get_size_for_type(c_data_type))
return numpy.copy(
numpy.frombuffer(c_data_buffer, dtype=_get_py_data_type(c_data_type)))
def _import_variable(c_variable):
# Import variable data.
data = _import_array(c_variable.data_type, c_variable.num_elements, c_variable.data)
num_dimensions = c_variable.num_dimensions
if num_dimensions == 0:
variable = Variable(numpy.asscalar(data))
else:
data = data.reshape([c_variable.dimension[i] for i in range(num_dimensions)])
dimension = [_get_py_dimension_type(c_variable.dimension_type[i]) for i in range(num_dimensions)]
variable = Variable(data, dimension)
# Import variable attributes.
if c_variable.unit != _ffi.NULL:
variable.unit = _decode_string(_ffi.string(c_variable.unit))
if c_variable.data_type != _lib.harp_type_string:
variable.valid_min = _import_scalar(c_variable.data_type, c_variable.valid_min)
variable.valid_max = _import_scalar(c_variable.data_type, c_variable.valid_max)
if c_variable.description:
variable.description = _decode_string(_ffi.string(c_variable.description))
return variable
def version():
"""Return the version of the HARP C library."""
return _decode_string(_ffi.string(_lib.libharp_version))
def version():
"""Return the version of the HARP C library."""
return _decode_string(_ffi.string(_lib.libharp_version))
