def transfer_physical_coords_from_imagestack_to_intensity_table(image_stack: ImageStack,
intensity_table: IntensityTable
) -> IntensityTable:
"""
Transfers physical coordinates from an Imagestack's coordinates xarray to an intensity table
1. Creates three new coords on the intensity table (xc, yc, zc)
2. For every spot:
- Get pixel x,y values
- Calculate the physical x,y values
- Assign those values to the coords arrays for this spot
"""
# Add three new coords to xarray (xc, yc, zc)
num_features = intensity_table.sizes[Features.AXIS]
intensity_table[Coordinates.X.value] = xr.DataArray(np.zeros(num_features, np.float32),
dims='features')
intensity_table[Coordinates.Y.value] = xr.DataArray(np.zeros(num_features, np.float32),
dims='features')
intensity_table[Coordinates.Z.value] = xr.DataArray(np.zeros(num_features, np.float32),
dims='features')
for ind, spot in intensity_table.groupby(Features.AXIS):
# Iterate through r, ch per spot
for ch, _round in np.ndindex(spot.data.shape):
# if non zero value set coords
if spot[ch][_round].data == 0:
continue
# get pixel coords of this tile
pixel_x = spot.coords[Axes.X].data
pixel_y = spot.coords[Axes.Y].data
pixel_z = spot.coords[Axes.ZPLANE].data
tile_indices = {
Axes.ROUND.value: _round,
Axes.CH.value: ch,
Axes.ZPLANE.value: pixel_z,
}
# Get corresponding physical coordinates
physical_coords = get_physical_coordinates_of_spot(
image_stack._coordinates,
tile_indices,
pixel_x,
pixel_y,
image_stack._tile_shape)
# Assign to coordinates arrays
intensity_table[Coordinates.X.value][ind] = physical_coords[0]
intensity_table[Coordinates.Y.value][ind] = physical_coords[1]
intensity_table[Coordinates.Z.value][ind] = physical_coords[2]
break
return intensity_table
def _calculate_mean_pixel_traces(
label_image: np.ndarray,
intensities: IntensityTable,
) -> IntensityTable:
"""
For all pixels that contribute to a connected component, calculate the mean value for
each (ch, round), producing an average "trace" of a feature across the imaging experiment
Parameters
----------
label_image : np.ndarray
An image where all pixels of a connected component share the same integer ID
intensities : IntensityTable
decoded intensities
Returns
-------
IntensityTable :
an IntensityTable where the number of features equals the number of connected components
and the intensities of each each feature is its mean trace.
"""
pixel_labels = label_image.reshape(-1)
intensities['spot_id'] = (Features.AXIS, pixel_labels)
mean_pixel_traces = intensities.groupby('spot_id').mean(Features.AXIS)
mean_distances = intensities[Features.DISTANCE].groupby('spot_id').mean(Features.AXIS)
mean_pixel_traces[Features.DISTANCE] = (
'spot_id',
np.ravel(mean_distances)
)
# the 0th pixel trace corresponds to background. If present, drop it.
try:
mean_pixel_traces = mean_pixel_traces.drop(0, dim='spot_id')
except KeyError:
pass
return mean_pixel_traces
