def compute_true_positives(distance_matrix, thresh):
dist_mat = cle.push(distance_matrix)
count_matrix = dist_mat < thresh
...
detected = np.asarray(cle.maximum_y_projection(count_matrix))[0, 1:]
# [0, 1:] is necessary to get rid of the first column which corresponds to background
...
# ambiguous matches occur when one annotation corresponds to multiple detected spots
ambiguous_matches = len(detected[detected>1])
...
I think maximum_y_projection -> sum_y_projection otherwise we cannot detect ambiguous matches. (everything will be 0 or 1 using the maximum projection)
Who should be in the column position : detected or annotation ?
Considering that annotation is 16 points.
Considering that detected_spots is 31 points.
It will put the detection as columns of the matrix (it's shape will be (16, 31))
But for the F1 score quantification:
print(f'We are detecting {distance_matrix.shape[0]} cells when there are {distance_matrix.shape[1]}')
The detections are in row, not in columns.
Also in def compute_true_positives(distance_matrix, thresh): the y_projection suggest also that annotation should be in the columns.
If distance_matrix.T is used from the definition maybe the legend of this figure will need to change
Hello,
Thank you for your work. I have two questions concerning the 29_algorithm_validation/validate-spot-counting
Maximum or sum projection ?
I think
maximum_y_projection
->sum_y_projection
otherwise we cannot detect ambiguous matches. (everything will be 0 or 1 using the maximum projection)Who should be in the column position : detected or annotation ?
Considering that annotation is 16 points. Considering that detected_spots is 31 points.
When
distance_matrix
is defined:It will put the detection as columns of the matrix (it's shape will be (16, 31))
But for the F1 score quantification:
The detections are in row, not in columns. Also in
def compute_true_positives(distance_matrix, thresh):
the y_projection suggest also that annotation should be in the columns.If![image](https://user-images.githubusercontent.com/94049435/222455174-a99550c0-e5b1-4677-b22c-db281d167e41.png)
distance_matrix.T
is used from the definition maybe the legend of this figure will need to change