worstsurge -> potential height

Author: sdat2

CITATION.cff

@@ -4,8 +4,8 @@ authors:
   - family-names: Thomas
     given-names: Simon Donald Alistair
     orcid: https://orcid.org/0000-0001-7911-1659
-title: WorstSurge - Finding the potential height of tropical cyclone storm surges in a changing climate using Bayesian Optimization
-version: v0.0.3
+title: Finding the potential height of tropical cyclone storm surges in a changing climate using Bayesian Optimization
+version: v0.1.1
 doi: 10.5281/zenodo.15073504
 url: "https://github.com/sdat2/worstsurge"
-date-released: 2025-04-05
+date-released: 2025-09-15

README.md

@@ -1,4 +1,4 @@
-# WorstSurge: Finding the potential height of tropical cyclone storm surges in a changing climate using Bayesian optimization
+# Finding the potential height of tropical cyclone storm surges in a changing climate using Bayesian optimization
 [![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](https://opensource.org/licenses/MIT)[![Code Style](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)[![Python package](https://github.com/sdat2/worstsurge/actions/workflows/python-package.yml/badge.svg)](https://github.com/sdat2/worstsurge/actions/workflows/python-package.yml)[![Documentation Status](https://readthedocs.org/projects/worstsurge/badge/?version=latest)](https://worstsurge.readthedocs.io/en/latest/?badge=latest)[![Code DOI](https://zenodo.org/badge/718141777.svg)](https://doi.org/10.5281/zenodo.15073504)[![EarthArXiv Preprint](https://img.shields.io/badge/EarthArXiv-doi:10.31223/X57T5R-blue?style=flat)](https://doi.org/10.31223/X57T5R)
 
 EarthArxiv preprint now available <https://doi.org/10.31223/X57T5R>!
@@ -92,11 +92,11 @@ If you use this code, please cite the following paper:
 And cite the code as:
 
 ```bibtex
-@software{worstsurge_code,
+@software{potential_height_code,
   author = {Thomas, Simon D. A.},
   doi = {10.5281/zenodo.15073504},
   month = {Sep},
-  title = {{WorstSurge - Finding the potential height of tropical cyclone storm surges in a changing climate using Bayesian Optimization}},
+  title = {{Finding the potential height of tropical cyclone storm surges in a changing climate using Bayesian Optimization}},
   url = {https://github.com/sdat2/worstsurge},
   version = {v0.1.1},
   year = {2025}

setup.py

@@ -37,7 +37,7 @@
 
 
 setup(
-    name="worstsurge",
+    name="PotentialHeight",
     description="A set of tools to calculate the potential height of tropical cyclone storm surges",
     version="0.1.1",
     author_email="sdat2@cam.ac.uk",

w22/ps_runs.py

@@ -78,18 +78,21 @@ def get_regional_processed_data(place="new_orleans") -> xr.Dataset:
 
 
 @timeit
-def trimmed_cmip6_example(
+def spatial_example(
     pressure_assumption="isothermal",
     trial=1,
     pi_version=2,
     recalculate_pi: bool = True,
     place="new_orleans",
 ) -> None:
-    """Run potential size calculations on CMIP6 data to get Gulf of Mexico data.
+    """Run potential size calculations on CMIP6 data to get a region.
 
     Args:
-        pressure_assumption (str, optional): pressure assumption. Defaults to "isopycnal".
+        pressure_assumption (str, optional): pressure assumption. Defaults to "isothermal".
         trial (int, optional): trial number. Defaults to 1.
+        pi_version (int, optional): pi_version of the pi calculation. Defaults to 2.
+        recalculate_pi (bool, optional): whether to recalculate pi. Defaults to True.
+        place (str, optional): place to get data for. Defaults to "new_orleans
     """
     # print("input cmip6 data", xr.open_dataset(EX_DATA_PATH))
     # select roughly gulf of mexico
@@ -107,6 +110,7 @@ def trimmed_cmip6_example(
         print("ds_list", ds_list)
         ds = xr.merge(ds_list)
         ds = convert(ds)
+        print("converted ds", ds)
         ds_pi = calculate_pi(
             ds,
             dim="p",
@@ -146,8 +150,9 @@ def trimmed_cmip6_example(
             "place must be one of new_orleans, galverston, miami, shanghai, hong_kong, hanoi"
         )
     print("trimmed input data", in_ds)
-    rh = qtp2rh(in_ds["q"], in_ds["t"], in_ds["msl"])
-    in_ds["rh"] = rh
+    if "rh" not in in_ds:
+        rh = qtp2rh(in_ds["q"], in_ds["t"], in_ds["msl"])
+        in_ds["rh"] = rh
     in_ds = in_ds[["sst", "msl", "vmax", "t0", "rh", "otl"]]
 
     if pi_version == 2:
@@ -546,7 +551,7 @@ def ps_for_place(
         if "ERA5" in models:
             point_era5_timeseries(place=place, pressure_assumption=pressure_assumption)
         if "CESM2" in models:
-            trimmed_cmip6_example(
+            spatial_example(
                 pressure_assumption=pressure_assumption,
                 trial=1,
                 pi_version=4,
@@ -556,4 +561,17 @@ def ps_for_place(
     from tcpips.dask_utils import dask_cluster_wrapper
 
     # dask_cluster_wrapper(ps_for_place, "new_orleans")
-    dask_cluster_wrapper(ps_for_place, "hong_kong")
+    # dask_cluster_wrapper(ps_for_place, "hong_kong")
+    dask_cluster_wrapper(
+        spatial_example,
+        place="new_orleans",
+        pressure_assumption="isothermal",
+        trial=1,
+        pi_version=4,
+    )
+    # spatial_example(
+    #     pressure_assumption="isothermal",
+    #     trial=1,
+    #     pi_version=4,
+    #     place="hong_kong",
+    # )