Set range entries with no backscatter data to NaN in output of echodata.compute_range()

echopype/echodata/echodata.py

@@ -339,16 +339,15 @@ def squeeze_non_scalar(n):
                     beam.range_bin - tvg_correction_factor
                 ) * sample_thickness  # [frequency x range_bin]
             elif waveform_mode == "BB":
+                beam = self.beam  # always use the Beam group
                 # TODO: bug: right now only first ping_time has non-nan range
-                shift = self.beam[
+                shift = beam[
                     "transmit_duration_nominal"
                 ]  # based on Lar Anderson's Matlab code
                 # TODO: once we allow putting in arbitrary sound_speed,
                 # change below to use linearly-interpolated values
                 range_meter = (
-                    (self.beam.range_bin * self.beam["sample_interval"] - shift)
-                    * sound_speed
-                    / 2
+                    (beam.range_bin * beam["sample_interval"] - shift) * sound_speed / 2
                 )
                 # TODO: Lar Anderson's code include a slicing by minRange with a default of 0.02 m,
                 #  need to ask why and see if necessary here
@@ -360,7 +359,18 @@ def squeeze_non_scalar(n):
             range_meter = range_meter.where(
                 range_meter > 0, 0
             )  # set negative ranges to 0
-            range_meter.name = "range"  # add name to facilitate xr.merge
+
+            # set entries with NaN backscatter data to NaN
+            if "quadrant" in beam["backscatter_r"].dims:
+                valid_idx = (
+                    ~beam["backscatter_r"].isel(quadrant=0).drop("quadrant").isnull()
+                )
+            else:
+                valid_idx = ~beam["backscatter_r"].isnull()
+            range_meter = range_meter.where(valid_idx)
+
+            # add name to facilitate xr.merge
+            range_meter.name = "range"
 
             return range_meter
 

echopype/preprocess/api.py

@@ -9,7 +9,10 @@
 
 def _check_range_uniqueness(ds):
     """Check if range changes across ping in a given frequency channel."""
-    return (ds["range"].isel(ping_time=0) == ds["range"]).all()
+    return (
+        ds["range"].isel(ping_time=0).dropna(dim="range_bin")
+        == ds["range"].dropna(dim="range_bin")
+    ).all()
 
 
 def compute_MVBS(ds_Sv, range_meter_bin=20, ping_time_bin="20S"):

echopype/test_data/README.md

@@ -18,6 +18,7 @@ Most of these files are stored on Git LFS but the ones that aren't (due to file
 
 ### EK60
 - DY1801_EK60-D20180211-T164025.raw: Standard test with constant ranges across ping times
+- Winter2017-D20170115-T150122.raw: Contains a change of recording length in the middle of the file
 - 2015843-D20151023-T190636.raw: Not used in tests but contains ranges are not constant across ping times
 - SH1701_consecutive_files_w_range_change: Not used in tests. [Folder](https://drive.google.com/drive/u/1/folders/1PaDtL-xnG5EK3N3P1kGlXa5ub16Yic0f) on shared drive that contains seqential files with ranges that are not constant across ping times.
 

echopype/tests/echodata/test_echodata.py

@@ -163,6 +163,29 @@ def compute_range_samples(request, test_path):
     )
 
 
+@pytest.fixture(
+    params=[
+        {
+            "path_model": "EK60",
+            "raw_path": "Winter2017-D20170115-T150122.raw",
+        },
+        {
+            "path_model": "EK80",
+            "raw_path": "D20170912-T234910.raw",
+        },
+    ],
+    ids=[
+        "ek60_winter2017",
+        "ek80_summer2017",
+    ],
+)
+def range_check_files(request, test_path):
+    return (
+        request.param["path_model"],
+        test_path[request.param["path_model"]].joinpath(request.param['raw_path'])
+    )
+
+
 @pytest.fixture(
     params=[
         {
@@ -308,6 +331,24 @@ def test_compute_range(compute_range_samples):
         assert isinstance(range, xr.DataArray)
 
 
+def test_nan_range_entries(range_check_files):
+    sonar_model, ek_file = range_check_files
+    echodata = echopype.open_raw(ek_file, sonar_model=sonar_model)
+    if sonar_model == "EK80":
+        ds_Sv = echopype.calibrate.compute_Sv(echodata, waveform_mode='BB', encode_mode='complex')
+        range_output = echodata.compute_range(env_params=[], ek_waveform_mode='BB')
+        nan_locs_backscatter_r = ~echodata.beam.backscatter_r.isel(quadrant=0).drop("quadrant").isnull()
+    else:
+        ds_Sv = echopype.calibrate.compute_Sv(echodata)
+        range_output = echodata.compute_range(env_params=[])
+        nan_locs_backscatter_r = ~echodata.beam.backscatter_r.isnull()
+
+    nan_locs_Sv_range = ~ds_Sv.range.isnull()
+    nan_locs_range = ~range_output.isnull()
+    assert xr.Dataset.equals(nan_locs_backscatter_r, nan_locs_range)
+    assert xr.Dataset.equals(nan_locs_backscatter_r, nan_locs_Sv_range)
+
+
 def test_update_platform(update_platform_samples):
     raw_file, extra_platform_data_file = update_platform_samples
     extra_platform_data_file_name = extra_platform_data_file.name