move iflag back.. may lower cov

noisepy · Feb 21, 2024 · 3e7033e · 3e7033e
1 parent 0bc4220
commit 3e7033e
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Showing 4 changed files with 6 additions and 6 deletions.
diff --git a/src/noisepy/old/S0B_to_ASDF_2019.py → ...oisepy/functions_2019/S0B_to_ASDF_2019.py b/src/noisepy/old/S0B_to_ASDF_2019.py → ...oisepy/functions_2019/S0B_to_ASDF_2019.py
diff --git a/src/noisepy/old/noise_module.py → src/noisepy/functions_2019/noise_module.py b/src/noisepy/old/noise_module.py → src/noisepy/functions_2019/noise_module.py
diff --git a/src/noisepy/seis/stack.py b/src/noisepy/seis/stack.py
@@ -225,15 +225,15 @@ def append_stacks(comp: str, tparameters: Dict[str, Any], stack_data: List[Tuple
             stack_results.append(Stack(comp, name, tparameters, data))
 
     # loop through cross-component for stacking
-    # iflag = 1
+    iflag = 1
     for icomp in range(nccomp):
         comp = enz_system[icomp]
         indx = np.where(cc_comp.lower() == comp.lower())[0]
         logger.debug(f"index to find the comp: {indx}")
 
         # jump if there are not enough data
         if len(indx) < 2:
-            # iflag = 0
+            iflag = 0
             continue
 
         # output stacked data
@@ -276,7 +276,7 @@ def append_stacks(comp: str, tparameters: Dict[str, Any], stack_data: List[Tuple
                 append_stacks(comp, tparameters, [(stack_name, cc_final[ii])])
 
     # do rotation if needed
-    if fft_params.rotation:
+    if fft_params.rotation and iflag:
         if np.all(bigstack == 0):
             return stack_results
         tparameters["station_source"] = src_sta.name

diff --git a/tests/test_noise_module.py b/tests/test_noise_module.py
@@ -13,7 +13,7 @@ def test_taper(data: np.ndarray):
     if data_taper.ndim == 1:
         assert np.isclose(data_taper[0], 0)
         assert np.isclose(data_taper[-1], 0)
-    elif data_taper.ndim == 2:
+    else:
         assert np.isclose(np.linalg.norm(data_taper[:, 0]), 0)
         assert np.isclose(np.linalg.norm(data_taper[:, -1]), 0)
 
@@ -23,7 +23,7 @@ def test_demean(data: np.ndarray):
     data_demean = demean(data)
     if data_demean.ndim == 1:
         assert np.isclose(np.mean(data_demean), 0)
-    elif data_demean.ndim == 2:
+    else:
         assert np.isclose(np.linalg.norm(np.mean(data_demean, axis=1)), 0)
 
 
@@ -32,7 +32,7 @@ def test_detrend(data: np.ndarray):
     data_detrend = detrend(data)
     if data_detrend.ndim == 1:
         npts = data_detrend.shape[0]
-    elif data_detrend.ndim == 2:
+    else:
         npts = data_detrend.shape[1]
 
     X = np.ones((npts, 2))