incorrect spatial moments

[retogerber]

The calculation of the spatial moments is incorrect:

import nyxus
import numpy as np
outmask = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 0, 1, 1, 0, 0, 0], [0, 0, 0, 0, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 1, 0, 0], [0, 1, 1, 1, 1, 1, 1, 1, 1, 0], [0, 0, 1, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
outmask
>>> array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
>>>             [0, 0, 0, 0, 0, 0, 1, 0, 0, 0],
>>>             [0, 0, 0, 0, 0, 1, 1, 0, 0, 0],
>>>             [0, 0, 0, 0, 1, 1, 1, 1, 0, 0],
>>>             [0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
>>>             [0, 1, 1, 1, 1, 1, 1, 1, 1, 0],
>>>             [0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
>>>             [0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
>>>             [0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
>>>             [0, 0, 1, 1, 1, 1, 0, 0, 0, 0],
>>>             [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
nyx = nyxus.Nyxus(["AREA_PIXELS_COUNT","SPAT_MOMENT_00"])
nyx.featurize(outmask,outmask)[["AREA_PIXELS_COUNT","SPAT_MOMENT_00"]]
>>>    AREA_PIXELS_COUNT  SPAT_MOMENT_00
>>> 0               43.0             0.0

[friskluft]

Thanks for the bug report.
I am checking it

[friskluft]

Thanks for the bug report!
It is fixed and a new version (0.9.2) is just released.
The updated library produces meaningful features for you sample data:

>>> import nyxus
>>> import numpy as np
>>> outmask = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 0, 1, 1, 0, 0, 0], [0, 0, 0, 0, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 1, 0, 0], [0, 1, 1, 1, 1, 1, 1, 1, 1, 0], [0, 0, 1, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
>>> outmask
array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 1, 0, 0, 0],
       [0, 0, 0, 0, 0, 1, 1, 0, 0, 0],
       [0, 0, 0, 0, 1, 1, 1, 1, 0, 0],
       [0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
       [0, 1, 1, 1, 1, 1, 1, 1, 1, 0],
       [0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
       [0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
       [0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
       [0, 0, 1, 1, 1, 1, 0, 0, 0, 0],
       [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
>>> nyx = nyxus.Nyxus (["AREA_PIXELS_COUNT", "*SGEOMOMS*"])
>>> nyx.featurize(outmask,outmask)
  intensity_image     mask_image  ROI_label  AREA_PIXELS_COUNT  \
0      Intensity0  Segmentation0        1.0               43.0

   SPAT_MOMENT_00  SPAT_MOMENT_01  SPAT_MOMENT_02  SPAT_MOMENT_03  \
0            43.0           200.0          1116.0          6860.0

   SPAT_MOMENT_10  SPAT_MOMENT_11  SPAT_MOMENT_12  SPAT_MOMENT_13  \
0           154.0           678.0          3668.0         21996.0

   SPAT_MOMENT_20  SPAT_MOMENT_21  SPAT_MOMENT_22  SPAT_MOMENT_23  \
0           686.0          2924.0         15374.0         89750.0

   SPAT_MOMENT_30  CENTRAL_MOMENT_00  CENTRAL_MOMENT_01  CENTRAL_MOMENT_02  \
0          3394.0               43.0               28.0              204.0

   CENTRAL_MOMENT_03  CENTRAL_MOMENT_10  CENTRAL_MOMENT_11  CENTRAL_MOMENT_12  \
0              316.0               25.0              -22.0               96.0

   CENTRAL_MOMENT_13  CENTRAL_MOMENT_20  CENTRAL_MOMENT_21  CENTRAL_MOMENT_22  \
0             -280.0              149.0               60.0              546.0

   CENTRAL_MOMENT_23  CENTRAL_MOMENT_30  CENTRAL_MOMENT_31  CENTRAL_MOMENT_32  \
0              546.0              217.0              -28.0              630.0

   CENTRAL_MOMENT_33  NORM_SPAT_MOMENT_00  NORM_SPAT_MOMENT_01  \
0             -610.0                  1.0             0.709296

   NORM_SPAT_MOMENT_02  NORM_SPAT_MOMENT_03  NORM_SPAT_MOMENT_10  \
0             0.603569             0.565787             0.546158

   NORM_SPAT_MOMENT_11  NORM_SPAT_MOMENT_12  NORM_SPAT_MOMENT_13  \
0             0.366685             0.302523             0.276655
...

[retogerber]

Great, thanks!