def test_ingest_segmentation():
delete_layer()
storage, data = create_layer(size=(256,256,128,1), offset=(0,0,0), layer_type='segmentation')
cv = CloudVolume(storage.layer_path)
assert len(cv.scales) == 3
assert len(cv.available_mips) == 3
slice64 = np.s_[0:64, 0:64, 0:64]
cv.mip = 0
assert np.all(cv[slice64] == data[slice64])
assert len(cv.available_mips) == 3
assert np.array_equal(cv.mip_volume_size(0), [ 256, 256, 128 ])
assert np.array_equal(cv.mip_volume_size(1), [ 128, 128, 128 ])
assert np.array_equal(cv.mip_volume_size(2), [ 64, 64, 128 ])
slice64 = np.s_[0:64, 0:64, 0:64]
cv.mip = 0
assert np.all(cv[slice64] == data[slice64])
data_ds1 = downsample.downsample_segmentation(data, factor=[2, 2, 1, 1])
cv.mip = 1
assert np.all(cv[slice64] == data_ds1[slice64])
data_ds2 = downsample.downsample_segmentation(data_ds1, factor=[2, 2, 1, 1])
cv.mip = 2
assert np.all(cv[slice64] == data_ds2[slice64])
def test_downsample_w_missing():
delete_layer()
storage, data = create_layer(size=(512,512,128,1), offset=(3,7,11))
cv = CloudVolume(storage.layer_path)
assert len(cv.scales) == 4
assert len(cv.available_mips) == 4
delete_layer()
cv.commit_info()
try:
create_downsampling_tasks(MockTaskQueue(), storage.layer_path, mip=0, num_mips=3, fill_missing=False)
except EmptyVolumeException:
pass
create_downsampling_tasks(MockTaskQueue(), storage.layer_path, mip=0, num_mips=3, fill_missing=True)
cv.refresh_info()
assert len(cv.available_mips) == 4
assert np.array_equal(cv.mip_volume_size(0), [ 512, 512, 128 ])
assert np.array_equal(cv.mip_volume_size(1), [ 256, 256, 128 ])
assert np.array_equal(cv.mip_volume_size(2), [ 128, 128, 128 ])
assert np.array_equal(cv.mip_volume_size(3), [ 64, 64, 128 ])
assert np.all(cv.mip_voxel_offset(3) == (0,0,11))
cv.mip = 0
cv.fill_missing = True
assert np.count_nonzero(cv[3:67, 7:71, 11:75]) == 0
def test_downsample_with_offset():
delete_layer()
storage, data = create_layer(size=(512,512,128,1), offset=(3,7,11))
cv = CloudVolume(storage.layer_path)
assert len(cv.scales) == 4
assert len(cv.available_mips) == 4
cv.commit_info()
create_downsampling_tasks(MockTaskQueue(), storage.layer_path, mip=0, num_mips=3)
cv.refresh_info()
assert len(cv.available_mips) == 4
assert np.array_equal(cv.mip_volume_size(0), [ 512, 512, 128 ])
assert np.array_equal(cv.mip_volume_size(1), [ 256, 256, 128 ])
assert np.array_equal(cv.mip_volume_size(2), [ 128, 128, 128 ])
assert np.array_equal(cv.mip_volume_size(3), [ 64, 64, 128 ])
assert np.all(cv.mip_voxel_offset(3) == (0,0,11))
cv.mip = 0
assert np.all(cv[3:67, 7:71, 11:75] == data[0:64, 0:64, 0:64])
data_ds1 = downsample.downsample_with_averaging(data, factor=[2, 2, 1, 1])
cv.mip = 1
assert np.all(cv[1:33, 3:35, 11:75] == data_ds1[0:32, 0:32, 0:64])
data_ds2 = downsample.downsample_with_averaging(data_ds1, factor=[2, 2, 1, 1])
cv.mip = 2
assert np.all(cv[0:16, 1:17, 11:75] == data_ds2[0:16, 0:16, 0:64])
data_ds3 = downsample.downsample_with_averaging(data_ds2, factor=[2, 2, 1, 1])
cv.mip = 3
assert np.all(cv[0:8, 0:8, 11:75] == data_ds3[0:8,0:8,0:64])
def test_downsample_no_offset(compression_method):
delete_layer()
storage, data = create_layer(size=(1024, 1024, 128, 1), offset=(0, 0, 0))
cv = CloudVolume(storage.layer_path)
assert len(cv.scales) == 1
assert len(cv.available_mips) == 1
cv.commit_info()
tq = MockTaskQueue()
tasks = create_downsampling_tasks(storage.layer_path,
mip=0,
num_mips=4,
compress=compression_method)
tq.insert_all(tasks)
cv.refresh_info()
assert len(cv.available_mips) == 5
assert np.array_equal(cv.mip_volume_size(0), [1024, 1024, 128])
assert np.array_equal(cv.mip_volume_size(1), [512, 512, 128])
assert np.array_equal(cv.mip_volume_size(2), [256, 256, 128])
assert np.array_equal(cv.mip_volume_size(3), [128, 128, 128])
assert np.array_equal(cv.mip_volume_size(4), [64, 64, 128])
slice64 = np.s_[0:64, 0:64, 0:64]
cv.mip = 0
assert np.all(cv[slice64] == data[slice64])
data_ds1, = tinybrain.downsample_with_averaging(data, factor=[2, 2, 1, 1])
cv.mip = 1
assert np.all(cv[slice64] == data_ds1[slice64])
data_ds2, = tinybrain.downsample_with_averaging(data, factor=[4, 4, 1, 1])
cv.mip = 2
assert np.all(cv[slice64] == data_ds2[slice64])
data_ds3, = tinybrain.downsample_with_averaging(data, factor=[8, 8, 1, 1])
cv.mip = 3
assert np.all(cv[slice64] == data_ds3[slice64])
data_ds4, = tinybrain.downsample_with_averaging(data,
factor=[16, 16, 1, 1])
cv.mip = 4
assert np.all(cv[slice64] == data_ds4[slice64])
def test_downsample_no_offset():
delete_layer()
storage, data = create_layer(size=(1024,1024,128,1), offset=(0,0,0))
cv = CloudVolume(storage.layer_path)
assert len(cv.scales) == 5
assert len(cv.available_mips) == 5
cv.commit_info()
create_downsampling_tasks(MockTaskQueue(), storage.layer_path, mip=0, num_mips=4)
cv.refresh_info()
assert len(cv.available_mips) == 5
assert np.array_equal(cv.mip_volume_size(0), [ 1024, 1024, 128 ])
assert np.array_equal(cv.mip_volume_size(1), [ 512, 512, 128 ])
assert np.array_equal(cv.mip_volume_size(2), [ 256, 256, 128 ])
assert np.array_equal(cv.mip_volume_size(3), [ 128, 128, 128 ])
assert np.array_equal(cv.mip_volume_size(4), [ 64, 64, 128 ])
slice64 = np.s_[0:64, 0:64, 0:64]
cv.mip = 0
assert np.all(cv[slice64] == data[slice64])
data_ds1 = downsample.downsample_with_averaging(data, factor=[2, 2, 1, 1])
cv.mip = 1
assert np.all(cv[slice64] == data_ds1[slice64])
data_ds2 = downsample.downsample_with_averaging(data_ds1, factor=[2, 2, 1, 1])
cv.mip = 2
assert np.all(cv[slice64] == data_ds2[slice64])
data_ds3 = downsample.downsample_with_averaging(data_ds2, factor=[2, 2, 1, 1])
cv.mip = 3
assert np.all(cv[slice64] == data_ds3[slice64])
data_ds4 = downsample.downsample_with_averaging(data_ds3, factor=[2, 2, 1, 1])
cv.mip = 4
assert np.all(cv[slice64] == data_ds4[slice64])
def test_downsample_no_offset_2x2x2():
delete_layer()
cf, data = create_layer(size=(512,512,512,1), offset=(0,0,0))
cv = CloudVolume(cf.cloudpath)
assert len(cv.scales) == 1
assert len(cv.available_mips) == 1
cv.commit_info()
tq = MockTaskQueue()
tasks = create_downsampling_tasks(
cf.cloudpath, mip=0, num_mips=3,
compress=None, factor=(2,2,2)
)
tq.insert_all(tasks)
cv.refresh_info()
assert len(cv.available_mips) == 4
assert np.array_equal(cv.mip_volume_size(0), [ 512, 512, 512 ])
assert np.array_equal(cv.mip_volume_size(1), [ 256, 256, 256 ])
assert np.array_equal(cv.mip_volume_size(2), [ 128, 128, 128 ])
assert np.array_equal(cv.mip_volume_size(3), [ 64, 64, 64 ])
slice64 = np.s_[0:64, 0:64, 0:64]
cv.mip = 0
assert np.all(cv[slice64] == data[slice64])
data_ds1, = tinybrain.downsample_with_averaging(data, factor=[2, 2, 2, 1])
cv.mip = 1
assert np.all(cv[slice64] == data_ds1[slice64])
data_ds2, = tinybrain.downsample_with_averaging(data, factor=[4, 4, 4, 1])
cv.mip = 2
assert np.all(cv[slice64] == data_ds2[slice64])
data_ds3, = tinybrain.downsample_with_averaging(data, factor=[8, 8, 8, 1])
cv.mip = 3
assert np.all(cv[slice64] == data_ds3[slice64])
