Proper rounding of the x/y values (#305)

Use numpy.round instead of casting to int. See issue #297
pySTEPS · Aug 30, 2022 · 8c378d9 · 8c378d9
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commit 8c378d9
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Showing 2 changed files with 4 additions and 4 deletions.
diff --git a/pysteps/feature/tstorm.py b/pysteps/feature/tstorm.py
@@ -247,8 +247,8 @@ def get_profile(areas, binary, ref, loc_max, time, minref):
         maxref = np.nanmax(ref[cells_id.y[n], cells_id.x[n]])
         contours = skime.find_contours(cell_unique, 0.8)
         cells_id.cont.iloc[n] = contours
-        cells_id.cen_x.iloc[n] = int(np.nanmean(cells_id.x[n]))  # int(x[0])
-        cells_id.cen_y.iloc[n] = int(np.nanmean(cells_id.y[n]))  # int(y[0])
+        cells_id.cen_x.iloc[n] = np.round(np.nanmean(cells_id.x[n])).astype(int)
+        cells_id.cen_y.iloc[n] = np.round(np.nanmean(cells_id.y[n])).astype(int)
         cells_id.max_ref.iloc[n] = maxref
         cells_id.area.iloc[n] = len(cells_id.x.iloc[n])
         labels[cells == cell_labels[n]] = ID

diff --git a/pysteps/tracking/tdating.py b/pysteps/tracking/tdating.py
@@ -243,8 +243,8 @@ def advect(cells_id, labels, V1):
     for ID, cell in cells_id.iterrows():
         if cell.ID == 0 or np.isnan(cell.ID):
             continue
-        ad_x = int(np.nanmean(V1[0, cell.y, cell.x]))
-        ad_y = int(np.nanmean(V1[1, cell.y, cell.x]))
+        ad_x = np.round(np.nanmean(V1[0, cell.y, cell.x])).astype(int)
+        ad_y = np.round(np.nanmean(V1[1, cell.y, cell.x])).astype(int)
         new_x = cell.x + ad_x
         new_y = cell.y + ad_y
         new_x[new_x > labels.shape[1] - 1] = labels.shape[1] - 1