Add ensemble model function arguments (#136)

* Add ensemble model function arguments

* Automatically update integration test validation results

* use kwargs

* Automatically update integration test validation results

---------

Co-authored-by: lars-fillmore <lars-fillmore@users.noreply.github.com>

Author: lars-fillmore

intertidal/elevation.py

@@ -795,6 +795,7 @@ def elevation(
     tide_model_dir="/var/share/tide_models",
     run_id=None,
     log=None,
+    **model_tides_kwargs,
 ):
     """
     Generates DEA Intertidal Elevation outputs using satellite imagery
@@ -859,6 +860,12 @@ def elevation(
         prefix log entries.
     log : logging.Logger, optional
         Logger object, by default None.
+    **model_tides_kwargs :
+        Optional parameters passed to the `eo_tides.model.model_tides`
+        function. Important parameters include `cutoff` (used to
+        extrapolate modelled tides away from the coast; defaults to
+        `np.inf`), `crop` (whether to crop tide model constituent files
+        on-the-fly to improve performance) etc.
 
     Returns
     -------
@@ -892,6 +899,7 @@ def elevation(
         data=satellite_ds,
         model=tide_model,
         directory=tide_model_dir,
+        **model_tides_kwargs,
     )
 
     # Set tide array pixels to nodata if the satellite data array pixels

tests/README.md

@@ -10,7 +10,7 @@ Integration tests
 
 This directory contains tests that are run to verify that DEA Intertidal code runs correctly. The ``test_intertidal.py`` file runs a small-scale full workflow analysis over an intertidal flat in the Gulf of Carpentaria using the DEA Intertidal [Command Line Interface (CLI) tools](../notebooks/Intertidal_CLI.ipynb), and compares these results against a LiDAR validation DEM to produce some simple accuracy metrics.
 
-The latest integration test completed at **2025-05-05 11:48**. Compared to the previous run, it had an:
+The latest integration test completed at **2025-06-23 15:23**. Compared to the previous run, it had an:
 - RMSE accuracy of **0.14 m ( :heavy_minus_sign: no change)**
 - MAE accuracy of **0.12 m ( :heavy_minus_sign: no change)**
 - Bias of **0.12 m ( :heavy_minus_sign: no change)**

tests/validation.csv

@@ -111,3 +111,5 @@ time,Correlation,RMSE,MAE,R-squared,Bias,Regression slope
 2025-05-02 06:32:51.594612+00:00,0.975,0.145,0.123,0.95,0.117,1.119
 2025-05-02 07:14:19.583638+00:00,0.975,0.145,0.123,0.95,0.117,1.119
 2025-05-05 01:48:26.455865+00:00,0.975,0.145,0.123,0.95,0.117,1.119
+2025-06-23 01:25:05.874000+00:00,0.975,0.145,0.123,0.95,0.117,1.119
+2025-06-23 05:23:05.398537+00:00,0.975,0.145,0.123,0.95,0.117,1.119