def test_detect():
params = K2ISDataSet.detect_params(K2IS_TESTDATA_PATH,
InlineJobExecutor())["parameters"]
assert params == {
"path": K2IS_TESTDATA_PATH,
"nav_shape": (34, 35),
"sig_shape": (1860, 2048),
"sync_offset": 250
}
def test_k2is_dist(dist_ctx):
ds = K2ISDataSet(path=K2IS_TESTDATA_PATH)
import glob
print(dist_ctx.executor.run_function(lambda: os.listdir("/data/Capture52/")))
print(dist_ctx.executor.run_function(lambda: list(sorted(glob.glob("/data/Capture52/*")))))
ds = ds.initialize(dist_ctx.executor)
roi = np.zeros(ds.shape.nav, dtype=bool)
roi[0, 5] = 1
roi[0, 17] = 1
analysis = dist_ctx.create_sum_analysis(dataset=ds)
results = dist_ctx.run(analysis, roi=roi)
assert results[0].raw_data.shape == (1860, 2048)
def main(input_filename, output_filename, dtype):
ds = K2ISDataSet(path=input_filename)
ds.initialize()
out_ds = np.memmap(output_filename, dtype=dtype, mode="w+",
shape=tuple(ds.raw_shape))
num_parts = len(list(ds.get_partitions()))
for p_idx, p in enumerate(ds.get_partitions()):
for tile in p.get_tiles():
out_ds[tile.tile_slice.get()] = tile.data.astype(dtype)
print("partition %d/%d done" % (p_idx + 1, num_parts))
print("done")
def test_detect():
params = K2ISDataSet.detect_params(K2IS_TESTDATA_PATH)
assert params == {
"path": K2IS_TESTDATA_PATH,
}
def default_k2is():
ds = K2ISDataSet(path=K2IS_TESTDATA_PATH)
ds.initialize()
return ds
def test_detect():
params = K2ISDataSet.detect_params(K2IS_TESTDATA_PATH,
InlineJobExecutor())["parameters"]
assert params == {
"path": K2IS_TESTDATA_PATH,
}
def default_k2is():
ds = K2ISDataSet(path=K2IS_TESTDATA_PATH)
ds.initialize(InlineJobExecutor())
return ds