def main():
bm = Benchmark(
datasets=[
Dataset(
factories=[
lambda n: make_quat_dataset(n, dtype=np.float16),
],
title='16bits',
extra_args=dict(
dtype=np.uint16
)
),
Dataset(
factories=[
lambda n: make_quat_dataset(n, dtype=np.float32),
],
title='32bits',
extra_args=dict(
dtype=np.uint32
)
),
Dataset(
factories=[
lambda n: make_quat_dataset(n, dtype=np.float64),
],
title='64bits',
extra_args=dict(
dtype=np.uint64
)
)
],
dataset_sizes=[2 ** n for n in range(25)],
kernels=[
Kernel(
stmt="quaternion.encode_quat_to_uint(DATASET, dtype=EXTRA_ARGS['dtype'], encoder=fp.encode_fp_to_std_snorm)",
setup='from fpq import quaternion\nfrom fpq import fp',
label='encode_quat_to_uint(std)'
),
Kernel(
stmt="quaternion.encode_quat_to_uint(DATASET, dtype=EXTRA_ARGS['dtype'], encoder=fp.encode_fp_to_ogl_snorm)",
setup='from fpq import quaternion\nfrom fpq import fp',
label='encode_quat_to_uint(ogl)'
),
],
xlabel='dataset sizes',
title='encode_quat_to_uint'
)
bm.run()
script_name, _ = os.path.splitext(os.path.basename(__file__))
bm.save_as_html(filepath=script_name + '.html')
def make_dataset(n, *, dtype):
dataset = make_quat_dataset(n, dtype=dtype)
max_abs_inds = fpq.utils.get_max_component_indices(np.absolute(dataset))
sign = np.sign(dataset[max_abs_inds])
rest_components = fpq.utils.remove_component(dataset, indices=max_abs_inds)
rest_components *= sign[..., None]
return rest_components.transpose()
def main():
dataset_size = 100000
src_dtype = np.float64
dst_dtype = np.uint64
dataset = make_quat_dataset(dataset_size, dtype=src_dtype)
mt.trace(
quaternion.encode_quat_to_uint,
target_args=dict(
q=dataset,
dtype=dst_dtype,
),
related_traces_output_mode=mt.RelatedTracesOutputMode.FOR_EACH_FILE,
include_patterns={'*/fpq/*'},
exclude_patterns=None
)
def make_dataset(n, *, src_dtype, dst_dtype, encoder):
dataset = make_quat_dataset(n, dtype=src_dtype)
return quaternion.encode_quat_to_uint(dataset,
dtype=dst_dtype,
encoder=encoder)