add align_to_ping_time function, and replace the other interp functions

echopype/calibrate/env_params.py

@@ -6,6 +6,7 @@
 
 from ..echodata import EchoData
 from ..utils import uwa
+from ..utils.align import align_to_ping_time
 from .cal_params import param2da
 
 ENV_PARAMS = (
@@ -68,9 +69,7 @@ def harmonize_env_param_time(
             return p.rename({"time1": "ping_time"})
 
         # Interpolate `p` to `ping_time`
-        return (
-            p.dropna(dim="time1").interp(time1=ping_time).ffill(dim="ping_time").drop_vars("time1")
-        )
+        return align_to_ping_time(p.dropna(dim="time1"), "time1", ping_time, method="linear")
     return p
 
 

echopype/consolidate/ek_depth_utils.py

@@ -2,6 +2,7 @@
 import xarray as xr
 from scipy.spatial.transform import Rotation as R
 
+from ..utils.align import align_to_ping_time
 from ..utils.log import _init_logger
 
 logger = _init_logger(__name__)
@@ -26,31 +27,6 @@ def _check_and_log_nans(
             )
 
 
-def _var_time2_to_ping_time(var_with_time2, ping_time_da):
-    """
-    If `time2` does not differ from `var`, we rename `time2` to 'ping_time',
-    else interpolate `transducer_depth`'s `time2` dimension to `ping_time`.
-
-    Useful for handling EK60 and EK80 platform data:
-
-    EK80 will have platform variables with time2 dimension that does not match
-    Beam group ping time values, while EK60 will have time2 dimension that
-    matches Beam group ping time values.
-    """
-    if not ping_time_da.equals(var_with_time2["time2"].rename({"time2": "ping_time"})):
-        var_with_ping_time = var_with_time2.interp(
-            {"time2": ping_time_da},
-            method="nearest",
-            # More details for `fill_value` and `extrapolate` can be found here:
-            # https://docs.scipy.org/doc/scipy/reference/generated/scipy.interpolate.interp1d.html # noqa
-            kwargs={"fill_value": "extrapolate"},
-        ).drop_vars("time2")
-    else:
-        var_with_ping_time = var_with_time2.rename({"time2": "ping_time"})
-
-    return var_with_ping_time
-
-
 def ek_use_platform_vertical_offsets(
     platform_ds: xr.Dataset,
     ping_time_da: xr.DataArray,
@@ -72,7 +48,7 @@ def ek_use_platform_vertical_offsets(
     # Compute z translation for transducer position vs water level
     transducer_depth = transducer_offset_z - (water_level + vertical_offset)
 
-    return _var_time2_to_ping_time(transducer_depth, ping_time_da)
+    return align_to_ping_time(transducer_depth, "time2", ping_time_da)
 
 
 def ek_use_platform_angles(platform_ds: xr.Dataset, ping_time_da: xr.DataArray) -> xr.DataArray:
@@ -95,7 +71,7 @@ def ek_use_platform_angles(platform_ds: xr.Dataset, ping_time_da: xr.DataArray)
         echo_range_scaling, dims="time2", coords={"time2": platform_ds["time2"]}
     )
 
-    return _var_time2_to_ping_time(echo_range_scaling, ping_time_da)
+    return align_to_ping_time(echo_range_scaling, "time2", ping_time_da)
 
 
 def ek_use_beam_angles(

echopype/consolidate/loc_utils.py

@@ -4,6 +4,7 @@
 import xarray as xr
 
 from ..echodata import EchoData
+from ..utils.align import align_to_ping_time
 from ..utils.log import _init_logger
 
 logger = _init_logger(__name__)
@@ -162,4 +163,4 @@ def sel_interp(
         )
     else:
         # Values may be nan if there are ping_time values outside the time_dim_name range
-        return position_var.interp(**{time_dim_name: ds["ping_time"]})
+        return align_to_ping_time(position_var, time_dim_name, ds["ping_time"], "linear")

echopype/tests/calibrate/test_env_params.py

@@ -30,6 +30,7 @@ def ek80_cal_path(test_path):
     return test_path["EK80_CAL"]
 
 
+@pytest.mark.unit
 def test_harmonize_env_param_time():
     # Scalar
     p = 10.05
@@ -67,16 +68,6 @@ def test_harmonize_env_param_time():
     assert (p_new.data == p.data).all()
 
     # ping_time target requires actual interpolation
-    ping_time_target = xr.DataArray(
-        data=[1, 2],
-        coords={
-            "ping_time": np.array(
-                ["2017-06-20T01:00:15", "2017-06-20T01:00:30"], dtype="datetime64[ns]"
-            )
-        },
-        dims=["ping_time"],
-    )
-
     ping_time_target = xr.DataArray(
         data=[1],
         coords={

echopype/tests/consolidate/test_add_location.py

@@ -162,7 +162,11 @@ def _tests(ds_test, location_type, nmea_sentence=None):
                     position_var = ed["Platform"][ed_position]
                     if nmea_sentence:
                         position_var = position_var[ed["Platform"]["sentence_type"] == nmea_sentence]
-                    position_interp = position_var.interp(time1=ds_test["ping_time"])
+                    position_interp = position_var.interp(
+                        {"time1": ds_test["ping_time"]},
+                        method="nearest",
+                        kwargs={"fill_value": "extrapolate"},
+                    )
                     # interpolated values are identical
                     assert np.allclose(ds_test[ds_position].values, position_interp.values, equal_nan=True) # noqa
             elif location_type == "fixed-location":

echopype/tests/utils/test_align.py

@@ -0,0 +1,48 @@
+import xarray as xr
+import numpy as np
+import pytest
+
+import echopype as ep
+from echopype.utils.align import align_to_ping_time
+
+
+@pytest.mark.unit
+def test_align_to_ping_time():
+    """
+    Test aligning external pitch data to Echosounder ping time
+    """
+    # Open RAW and extract ping time
+    ping_time_da = ep.open_raw(
+        raw_file="echopype/test_data/azfp/rutgers_glider_external_nc/18011107.01A",
+        xml_path="echopype/test_data/azfp/rutgers_glider_external_nc/18011107.XML",
+        sonar_model="azfp"
+    )["Sonar/Beam_group1"]["ping_time"]
+
+    # Open external glider dataset
+    glider_ds = xr.open_dataset(
+        "echopype/test_data/azfp/rutgers_glider_external_nc/ru32-20180109T0531-profile-sci-delayed-subset.nc",
+        engine="netcdf4"
+    )
+
+    # Drop NaNs from pitch and align data array
+    aligned_da = align_to_ping_time(glider_ds["m_pitch"].dropna("time"), "time", ping_time_da)
+
+    # Extract earliest non-NaN time of the aligned dataset
+    earliest_non_nan_time_in_aligned_da = aligned_da.dropna("ping_time")["ping_time"].min()
+
+    # Grab all values past the earliest non-NaN time in the aligned DataArray
+    subset_aligned_da = aligned_da.where(aligned_da["ping_time"] >= earliest_non_nan_time_in_aligned_da, drop=True)
+
+    # Check that all values past the earliest non-NaN time in the aligned DataArray are non-NaN
+    assert np.all(~np.isnan(subset_aligned_da))
+
+    # Test if aligned_da matches interpolation
+    assert np.allclose(
+        aligned_da,
+        glider_ds["m_pitch"].dropna("time").interp(
+            {"time": ping_time_da},
+            method="nearest",
+            kwargs={"fill_value": "extrapolate"},
+        ),
+        equal_nan=True,
+    )

echopype/utils/align.py

@@ -0,0 +1,42 @@
+import xarray as xr
+
+
+def align_to_ping_time(
+    external_da: xr.DataArray,
+    external_time_name: str,
+    ping_time_da: xr.DataArray,
+    method: str = "nearest",
+) -> xr.DataArray:
+    """
+    Aligns an external DataArray to align time-wise with the Echosounder ping time DataArray.
+
+    A wrapper function for https://docs.xarray.dev/en/stable/generated/xarray.DataArray.interp.html.
+
+    Parameters
+    ----------
+    external_da : xr.DataArray
+        External Non-Echosounder data.
+    external_time_name : str, default 'nearest'
+        Time variable name of the External Non-Echosounder data.
+    ping_time_da : xr.DataArray
+        Echosounder ping time.
+
+    Returns
+    -------
+    aligned_da : xr.DataArray
+        External Non-Echosounder data that is now aligned with the Echosounder ping time.
+    """
+    # Interpolate only if ping time and external time are not equal
+    if not ping_time_da.equals(
+        external_da[external_time_name].rename({external_time_name: "ping_time"})
+    ):
+        aligned_da = external_da.interp(
+            {external_time_name: ping_time_da},
+            method=method,
+            # More details for `fill_value` and `extrapolate` can be found here:
+            # https://docs.scipy.org/doc/scipy/reference/generated/scipy.interpolate.interp1d.html # noqa
+            kwargs={"fill_value": "extrapolate"},
+        ).drop_vars(external_time_name)
+    else:
+        aligned_da = external_da.rename({external_time_name: "ping_time"})
+    return aligned_da