--- a/spot_detection_2d.py	Wed Jul 21 19:59:00 2021 +0000
+++ b/spot_detection_2d.py	Sat Feb 19 20:43:29 2022 +0000
@@ -13,7 +13,7 @@
 import numpy as np
 import pandas as pd
 from skimage.feature import peak_local_max
-from skimage.filters import gaussian
+from skimage.filters import gaussian, laplace
 
 
 def getbr(xy, img, nb, firstn):
@@ -27,7 +27,9 @@
     return br
 
 
-def spot_detection(fn_in, fn_out, frame_1st=1, frame_end=0, typ_br='smoothed', th=10, ssig=1, bd=10):
+def spot_detection(fn_in, fn_out, frame_1st=1, frame_end=0,
+                   typ_filter='Gauss', ssig=1, th=10,
+                   typ_br='smoothed', bd=10):
     ims_ori = imageio.mimread(fn_in, format='TIFF')
     ims_smd = np.zeros((len(ims_ori), ims_ori[0].shape[0], ims_ori[0].shape[1]), dtype='float64')
     if frame_end == 0 or frame_end > len(ims_ori):
@@ -40,6 +42,9 @@
     txyb_all = np.array([]).reshape(0, 4)
     for i in range(frame_1st - 1, frame_end):
         tmp = np.copy(ims_smd[i, :, :])
+        if typ_filter == 'LoG':
+            tmp = laplace(tmp)
+
         tmp[tmp < th * ims_smd_max / 100] = 0
         coords = peak_local_max(tmp, min_distance=1)
         idx_to_del = np.where((coords[:, 0] <= bd) | (coords[:, 0] >= tmp.shape[0] - bd) |
@@ -66,21 +71,18 @@
 
 
 if __name__ == "__main__":
-    parser = argparse.ArgumentParser(description="Spot detection based on local maxima")
+    parser = argparse.ArgumentParser(description="Spot detection")
     parser.add_argument("fn_in", help="Name of input image sequence (stack)")
     parser.add_argument("fn_out", help="Name of output file to save the coordinates and intensities of detected spots")
     parser.add_argument("frame_1st", type=int, help="Index for the starting frame to detect spots (1 for first frame of the stack)")
     parser.add_argument("frame_end", type=int, help="Index for the last frame to detect spots (0 for the last frame of the stack)")
+    parser.add_argument("filter", help="Detection filter")
+    parser.add_argument("ssig", type=float, help="Sigma of the Gaussian for noise suppression")
+    parser.add_argument("thres", type=float, help="Percentage of the global maximal for thresholding candidate spots")
     parser.add_argument("typ_intens", help="smoothed or robust (for measuring the intensities of spots)")
-    parser.add_argument("thres", type=float, help="Percentage of the global maximal intensity for thresholding candidate spots")
-    parser.add_argument("ssig", type=float, help="Sigma of the Gaussian filter for noise suppression")
     parser.add_argument("bndy", type=int, help="Number of pixels (Spots close to image boundaries will be ignored)")
     args = parser.parse_args()
-    spot_detection(args.fn_in,
-                   args.fn_out,
-                   frame_1st=args.frame_1st,
-                   frame_end=args.frame_end,
-                   typ_br=args.typ_intens,
-                   th=args.thres,
-                   ssig=args.ssig,
-                   bd=args.bndy)
+    spot_detection(args.fn_in, args.fn_out,
+                   frame_1st=args.frame_1st, frame_end=args.frame_end,
+                   typ_filter=args.filter, ssig=args.ssig, th=args.thres,
+                   typ_br=args.typ_intens, bd=args.bndy)

--- a/spot_detection_2d.xml	Wed Jul 21 19:59:00 2021 +0000
+++ b/spot_detection_2d.xml	Sat Feb 19 20:43:29 2022 +0000
@@ -1,21 +1,22 @@
-<tool id="ip_spot_detection_2d" name="Spot Detection" version="0.0.1" profile="20.05"> 
-    <description>based on local intensity maxima</description>
+<tool id="ip_spot_detection_2d" name="Spot Detection" version="0.0.2" profile="20.05"> 
+    <description>in a 2D image (sequence)</description>
     <requirements>
         <requirement type="package" version="2.9.0">imageio</requirement>
         <requirement type="package" version="1.20.2">numpy</requirement>
         <requirement type="package" version="1.2.4">pandas</requirement>
         <requirement type="package" version="0.18.1">scikit-image</requirement>
     </requirements>
-    <command>
+    <command detect_errors="aggressive">
     <![CDATA[
          python '$__tool_directory__/spot_detection_2d.py'
          '$fn_in'
          '$fn_out'
          '$frame_1st'
          '$frame_end'
-         '$typ_intens'
+         '$filter'
+         '$ssig'
          '$thres'
-         '$ssig'
+         '$typ_intens'
          '$bndy'
     ]]>
     </command>
@@ -23,13 +24,17 @@
         <param name="fn_in" type="data" format="tiff" label="Image sequence (stack)" />
         <param name="frame_1st" type="integer" value="1" label="Starting time point (1 for the first frame of the stack)" />
         <param name="frame_end" type="integer" value="0" label="Ending time point (0 for the last frame of the stack)" />
+        <param name="filter" type="select" label="Choose a detection filter">
+            <option value="Gauss" selected="True">Gaussian</option>
+            <option value="LoG">Laplacian-of-Gaussian, LoG (more accurate when spots have similar sizes)</option>
+        </param>
+        <param name="ssig" type="float" value="1.0" min="0.5" max="10" label="Sigma of the Gaussian (for noise suppression)" />
+        <param name="thres" type="float" value="10.0" min="0" max="100" label="Percentage of the global maximal as the threshold for candidate spots" />
         <param name="typ_intens" type="select" label="How to measure the intensities">
             <option value="smoothed" selected="True">Smoothed</option>
             <option value="robust">Robust</option>
         </param>
-        <param name="thres" type="float" value="10" label="Percentage of the global maximal intensity as the threshold for candidate spots" />
-        <param name="ssig" type="float" value="1" label="Sigma of the Gaussian filter for noise suppression" />
-        <param name="bndy" type="integer" value="10" label="Number of pixels (Spots within n-pixel image boundaries will be ignored)" />
+        <param name="bndy" type="integer" value="10" min="0" max="50" label="Width (in pixel) of image boundaries where spots will be ignored" />
     </inputs>
     <outputs>
         <data format="tabular" name="fn_out" />
@@ -39,9 +44,10 @@
             <param name="fn_in" value="test_img1.tif"/>
             <param name="frame_1st" value="1"/>
             <param name="frame_end" value="0"/>
-            <param name="typ_intens" value="smoothed"/>
+            <param name="filter" value="Gauss"/>
+            <param name="ssig" value="1"/>
             <param name="thres" value="10"/>
-            <param name="ssig" value="1"/>
+            <param name="typ_intens" value="smoothed"/>
             <param name="bndy" value="10"/>
             <output name="fn_out" value="spots_detected.tsv" ftype="tabular" />
         </test>
@@ -49,6 +55,8 @@
     <help>
     **What it does**
 
-    This tool detects spots and measures the intensities in a 2D image sequence based on local intensity maxima.
+    This tool detects spots and measures the intensities in a 2D image (sequence).
     </help>
+    <citations>
+    </citations>
 </tool>