Overhaul access pattern [all tests ci] (#762)

* Update access patterns for convert api

* Update access pattern for 'Environment'

* Update access pattern for 'Platform'

* Update access pattern for 'Provenance'

* Update access pattern for 'Vendor_specific'

* Update access pattern for 'Sonar/Beam_group2'

* Update access pattern for 'Sonar/Beam_group1' and others

* Remove getattrs

* Update echopype/tests/echodata/test_echodata.py

Co-authored-by: Don Setiawan <landungs@uw.edu>

* Update echopype/tests/echodata/test_echodata_combine.py

Co-authored-by: Don Setiawan <landungs@uw.edu>

* Modify getitem to return None and remove try/except

* Add spec comment

* Update echopype/tests/echodata/test_echodata_combine.py

Co-authored-by: Wu-Jung Lee <leewujung@gmail.com>

Co-authored-by: Wu-Jung Lee <leewujung@gmail.com>

echopype/calibrate/api.py

@@ -104,9 +104,9 @@ def add_attrs(cal_type, ds):
     prov_dict["processing_function"] = f"calibrate.compute_{cal_type}"
     cal_ds = cal_ds.assign_attrs(prov_dict)
 
-    if "water_level" in echodata.platform.data_vars.keys():
+    if "water_level" in echodata["Platform"].data_vars.keys():
         # add water_level to the created xr.Dataset
-        cal_ds["water_level"] = echodata.platform.water_level
+        cal_ds["water_level"] = echodata["Platform"].water_level
 
     return cal_ds
 

echopype/calibrate/calibrate_azfp.py

@@ -34,13 +34,15 @@ def get_cal_params(self, cal_params):
         self.cal_params["equivalent_beam_angle"] = (
             cal_params["equivalent_beam_angle"]
             if "equivalent_beam_angle" in cal_params
-            else self.echodata.beam["equivalent_beam_angle"]
+            else self.echodata["Sonar/Beam_group1"]["equivalent_beam_angle"]
         )
 
         # Get params from the Vendor_specific group
         for p in ["EL", "DS", "TVR", "VTX", "Sv_offset"]:
             # substitute if None in user input
-            self.cal_params[p] = cal_params[p] if p in cal_params else self.echodata.vendor[p]
+            self.cal_params[p] = (
+                cal_params[p] if p in cal_params else self.echodata["Vendor_specific"][p]
+            )
 
     def get_env_params(self):
         """Get env params using user inputs or values from data file.
@@ -53,7 +55,7 @@ def get_env_params(self):
         self.env_params["temperature"] = (
             self.env_params["temperature"]
             if "temperature" in self.env_params
-            else self.echodata.environment["temperature"]
+            else self.echodata["Environment"]["temperature"]
         )
 
         # Salinity and pressure always come from user input
@@ -71,7 +73,7 @@ def get_env_params(self):
             formula_source="AZFP",
         )
         self.env_params["sound_absorption"] = uwa.calc_absorption(
-            frequency=self.echodata.beam["frequency_nominal"],
+            frequency=self.echodata["Sonar/Beam_group1"]["frequency_nominal"],
             temperature=self.env_params["temperature"],
             salinity=self.env_params["salinity"],
             pressure=self.env_params["pressure"],
@@ -108,10 +110,10 @@ def _cal_power(self, cal_type, **kwargs):
         # Compute derived params
 
         # Harmonize time coordinate between Beam_groupX data and env_params
-        # Use self.echodata.beam because complex sample is always in Beam_group1
+        # Use self.echodata["Sonar/Beam_group1"] because complex sample is always in Beam_group1
         for p in self.env_params.keys():
             self.env_params[p] = self.echodata._harmonize_env_param_time(
-                self.env_params[p], ping_time=self.echodata.beam.ping_time
+                self.env_params[p], ping_time=self.echodata["Sonar/Beam_group1"].ping_time
             )
 
         # TODO: take care of dividing by zero encountered in log10
@@ -122,7 +124,9 @@ def _cal_power(self, cal_type, **kwargs):
         # scaling factor (slope) in Fig.G-1, units Volts/dB], see p.84
         a = self.cal_params["DS"]
         EL = (
-            self.cal_params["EL"] - 2.5 / a + self.echodata.beam.backscatter_r / (26214 * a)
+            self.cal_params["EL"]
+            - 2.5 / a
+            + self.echodata["Sonar/Beam_group1"].backscatter_r / (26214 * a)
         )  # eq.(5)  # has beam dim due to backscatter_r
 
         if cal_type == "Sv":
@@ -136,7 +140,7 @@ def _cal_power(self, cal_type, **kwargs):
                 * np.log10(
                     0.5
                     * self.env_params["sound_speed"]
-                    * self.echodata.beam["transmit_duration_nominal"]
+                    * self.echodata["Sonar/Beam_group1"]["transmit_duration_nominal"]
                     * self.cal_params["equivalent_beam_angle"]
                 )
                 + self.cal_params["Sv_offset"]
@@ -155,7 +159,7 @@ def _cal_power(self, cal_type, **kwargs):
         out = out.merge(self.range_meter)
 
         # Add frequency_nominal to data set
-        out["frequency_nominal"] = self.echodata.beam["frequency_nominal"]
+        out["frequency_nominal"] = self.echodata["Sonar/Beam_group1"]["frequency_nominal"]
 
         # Add env and cal parameters
         out = self._add_params_to_output(out)