Updated order in which the array is read. Should potentially increase…

… reading speed for larger wueries
lsawade · Jul 19, 2023 · 22bb742 · 22bb742
1 parent f0059a2
commit 22bb742
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Showing 2 changed files with 9 additions and 6 deletions.
diff --git a/src/gf3d/bin/gf3d_exec.py b/src/gf3d/bin/gf3d_exec.py
@@ -449,7 +449,6 @@ def plot_station_seismogram(subsetfilename, cmtsolutionfilename, network, statio
 
     # CMTSOLUTION
     cmt = CMTSOLUTION.read(cmtsolutionfilename)
-    print(cmt)
 
     # %%
     # Loading the subset database

diff --git a/src/gf3d/seismograms.py b/src/gf3d/seismograms.py
@@ -830,8 +830,8 @@ def get_elements(self, lat, lon, depth, dist_in_km=125.0, NGLL=5, threading: boo
                 # sort the globs, and after we retreive the array unsort it and
                 # reshape it
                 # For later I'll need to test this before I can implement it.
-                # sglob = np.argsort(self.nglob2sub)
-                # rsglob = np.argsort(sglob)
+                sglob = np.argsort(self.nglob2sub)
+                rsglob = np.argsort(sglob)
 
                 # Get new index array of length of the unique values
                 indeces = np.arange(len(self.nglob2sub))
@@ -951,9 +951,13 @@ def read_stuff(args):
                         # Get norm and displacement
                         norm = db[f'displacement/{comp}/norm'][()]
 
-                        # Get displacement
-                        self.displacement[_i, _j, :, :, :] = db[f'displacement/{comp}/array'][:, self.nglob2sub, :].astype(
-                            np.float32) * norm / factor
+                        # Get displacement getting the output in ascending order
+                        self.displacement[_i, _j, :, :, :] = \
+                            db[f'displacement/{comp}/array'][:, self.nglob2sub[sglob], :].astype(
+                            np.float32)[:, rsglob, :] * norm / factor
+
+                        #  displacementd[comp] = db[f'displacement/{comp}/array'][
+                        #         :, iglob[sglob], :].astype(np.float64)[:, rsglob, :].reshape(3, NGLLX, NGLLY, NGLLZ, NT) * norm_disp / factor
 
                 if threading:
                     with parallel_backend('threading', n_jobs=self.Ndb):