def get_result_buffers_refine():
return {
'intensity': BufferWrapper(kind="nav", dtype="float32"),
'zero': BufferWrapper(kind="nav", extra_shape=(2, ), dtype="float32"),
'a': BufferWrapper(kind="nav", extra_shape=(2, ), dtype="float32"),
'b': BufferWrapper(kind="nav", extra_shape=(2, ), dtype="float32"),
}
def test_aux_1(lt_ctx):
data = _mk_random(size=(16, 16, 16, 16), dtype="float32")
aux_data = BufferWrapper(kind="nav", dtype="float32", extra_shape=(2, ))
aux_data.set_buffer(_mk_random(size=(16, 16, 2), dtype="float32"))
dataset = MemoryDataSet(data=data,
tileshape=(7, 16, 16),
num_partitions=2,
sig_dims=2)
echo_udf = EchoUDF(aux=aux_data)
res = lt_ctx.run_udf(dataset=dataset, udf=echo_udf)
assert 'echo' in res
print(data.shape, res['echo'].data.shape)
assert np.allclose(res['echo'].raw_data, aux_data.raw_data)
def batch_buffer():
"""
Initializes BufferWrapper objects for sum of variances,
sum of frames, and the number of frames
Returns
-------
A dictionary that maps 'var', 'std', 'mean', 'num_frame', 'sum_frame' to
the corresponding BufferWrapper objects
"""
return {
'var': BufferWrapper(kind='sig', dtype='float32'),
'num_frame': BufferWrapper(kind='single', dtype='float32'),
'sum_frame': BufferWrapper(kind='sig', dtype='float32')
}
def aux_data(cls, data, kind, extra_shape=(), dtype="float32"):
"""
Use this method to create auxiliary data. Auxiliary data should
have a shape like `(dataset.shape.nav, extra_shape)` and on access,
an appropriate view will be created. For example, if you access
aux data in `process_frame`, you will get the auxiliary data for
the current frame you are processing.
Example
-------
We create a UDF to demonstrate the behavior:
>>> class MyUDF(UDF):
... def get_result_buffers(self):
... # Result buffer for debug output
... return {'aux_dump': self.buffer(kind='nav', dtype='object')}
...
... def process_frame(self, frame):
... # Extract value of aux data for demonstration
... self.results.aux_dump[:] = str(self.params.aux_data[:])
...
>>> # for each frame, provide three values from a sequential series:
>>> aux1 = MyUDF.aux_data(
... data=np.arange(np.prod(dataset.shape.nav) * 3, dtype=np.float32),
... kind="nav", extra_shape=(3,), dtype="float32"
... )
>>> udf = MyUDF(aux_data=aux1)
>>> res = ctx.run_udf(dataset=dataset, udf=udf)
process_frame for frame (0, 7) received a view of aux_data with values [21., 22., 23.]:
>>> res['aux_dump'].data[0, 7]
'[21. 22. 23.]'
"""
buf = BufferWrapper(kind, extra_shape, dtype)
buf.set_buffer(data)
return buf
def get_result_buffers_pass_2(num_disks):
"""
we 'declare' what kind of result buffers we need, without concrete shapes
concrete shapes come later, either for partition or whole dataset
"""
return {
'centers':
BufferWrapper(kind="nav", extra_shape=(num_disks, 2), dtype="u2"),
'refineds':
BufferWrapper(kind="nav", extra_shape=(num_disks, 2), dtype="float32"),
'peak_values':
BufferWrapper(
kind="nav",
extra_shape=(num_disks, ),
dtype="float32",
),
'peak_elevations':
BufferWrapper(
kind="nav",
extra_shape=(num_disks, ),
dtype="float32",
),
}
def get_result_buffers_refine(num_disks):
return {
'centers':
BufferWrapper(kind="nav", extra_shape=(num_disks, 2), dtype="u2"),
'refineds':
BufferWrapper(kind="nav", extra_shape=(num_disks, 2), dtype="float32"),
'peak_values':
BufferWrapper(kind="nav", extra_shape=(num_disks, ), dtype="float32"),
'peak_elevations':
BufferWrapper(kind="nav", extra_shape=(num_disks, ), dtype="float32"),
'zero':
BufferWrapper(kind="nav", extra_shape=(2, ), dtype="float32"),
'a':
BufferWrapper(kind="nav", extra_shape=(2, ), dtype="float32"),
'b':
BufferWrapper(kind="nav", extra_shape=(2, ), dtype="float32"),
'selector':
BufferWrapper(kind="nav", extra_shape=(num_disks, ), dtype="bool"),
}
def buffer(self, kind, extra_shape=(), dtype="float32", where=None):
'''
Use this method to create :class:`~ libertem.common.buffers.BufferWrapper` objects
in :meth:`get_result_buffers`.
'''
return BufferWrapper(kind, extra_shape, dtype, where)
def get_result_buffers(self):
return {
'pixelsum': BufferWrapper(
kind="nav", dtype="float32"
)
}
def logsum_buffer():
return {
'logsum': BufferWrapper(kind='sig', dtype='float32'),
}
def counter_buffers():
return {'counter': BufferWrapper(kind="single", dtype="uint32")}
def make_result_buffers():
return {'std': BufferWrapper(kind="nav", dtype="float32")}
def test_buffer_extra_shape_1():
buffer = BufferWrapper(kind='nav', extra_shape=(2, 3))
assert buffer._extra_shape == (2, 3)
def make_result_buffers():
return {
'intensity': BufferWrapper(kind="nav", dtype="float32"),
}
def make_result_buffers():
return {'fou': BufferWrapper(kind="nav", dtype="complex64")}
def my_buffers():
return {
'pixelsum': BufferWrapper(
kind="nav", dtype="float32"
)
}
def test_buffer_extra_shape_2():
shape_obj = Shape(shape=(12, 13, 14, 15), sig_dims=2)
buffer = BufferWrapper(kind='nav', extra_shape=shape_obj)
assert buffer._extra_shape == (12, 13, 14, 15)
def buffer(self, kind, extra_shape=(), dtype="float32"):
return BufferWrapper(kind, extra_shape, dtype)
def make_result_buffers():
return {
'x2': BufferWrapper(kind="sig", dtype="float64"),
'x': BufferWrapper(kind="sig", dtype="float64"),
}