Merge pull request #93 from vadmbertr/meth-naming

Rename cyclogeostrophic methods for consistency with the paper

Author: vadmbertr

README.md

@@ -3,7 +3,7 @@
 ![Python](https://img.shields.io/badge/dynamic/yaml?url=https://raw.githubusercontent.com/meom-group/jaxparrow/master/.github/workflows/python-package.yml&label=Python&query=$.jobs.build.strategy.matrix["python-version"])
 [![PyPi](https://img.shields.io/badge/dynamic/xml?url=https://pypi.org/rss/project/jaxparrow/releases.xml&label=PyPi&query=/rss/channel/item[1]/title)](https://pypi.org/project/jaxparrow/)
 ![Tests](https://github.com/meom-group/jaxparrow/actions/workflows/python-package.yml/badge.svg)
-[![Docs](https://github.com/meom-group/jaxparrow/actions/workflows/python-documentation.yml/badge.svg)](https://jaxparrow.readthedocs.io/)
+[![Docs](https://app.readthedocs.org/projects/jaxparrow/badge/)](https://jaxparrow.readthedocs.io/)
 [![DOI](https://zenodo.org/badge/702998298.svg)](https://zenodo.org/badge/latestdoi/702998298)
 
 `jaxparrow` implements a novel approach based on a minimization-based formulation to compute the inversion of the cyclogeostrophic balance.
@@ -21,7 +21,7 @@ A comprehensive documenation is available: [https://jaxparrow.readthedocs.io/en/
 pip install jaxparrow
 ```
 
-**<ins>However</ins>**, users with access to GPUs or TPUs should first install `JAX` separately in order to fully benefit from its high-performance computing capacities. 
+**<ins>However</ins>**, users with access to GPUs or TPUs should first install `JAX` separately in order to fully benefit from its high-performance computing capacities.
 See [JAX instructions](https://jax.readthedocs.io/en/latest/installation.html).
 By default, `jaxparrow` will install a CPU-only version of JAX if no other version is already present in the Python environment.
 

docs/examples/duacs.ipynb

@@ -268,7 +268,7 @@
    "id": "d89919cd",
    "metadata": {},
    "source": [
-    "Below we animate the cyclogeostrophic currents magnitude over the year 2019."
+    "Below we animate the cyclogeostrophic currents magnitude over the month of June 2019."
    ]
   },
   {
@@ -24016,7 +24016,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "jaxparrow",
    "language": "python",
    "name": "python3"
   },
@@ -24030,7 +24030,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.23"
+   "version": "3.11.14"
   },
   "tags": [
    "toggle-input"

docs/examples/gradient_wind.ipynb

@@ -56,7 +56,7 @@ def cyclogeostrophy(
         lat_t: Float[Array, "lat lon"],
         lon_t: Float[Array, "lat lon"],
         mask: Float[Array, "lat lon"] = None,
-        method: Literal["minimization", "fixed-point"] = "minimization",
+        method: Literal["minimization-based", "fixed-point"] = "minimization-based",
         n_it: int = None,
         optim: Union[optax.GradientTransformation, str] = "sgd",
         optim_kwargs: dict = None,
@@ -85,9 +85,9 @@ def cyclogeostrophy(
         Mask defining the marine area of the spatial domain; `1` or `True` stands for masked (i.e. land)
 
         If not provided, inferred from ``ssh_t`` `nan` values
-    method : Literal["minimization", "fixed-point"], optional
+    method : Literal["minimization-based", "fixed-point"], optional
         Estimation method to use.
-        If ``method="minimization"``, then use our minimization-based formulation.
+        If ``method="minimization-based"``, then use our minimization-based formulation.
         If ``method="fixed-point"``, then use the fixed-point approach [Penven et al. (2014)](https://doi.org/10.1002/2013JC009528).
 
         Defaults to `minimization`
@@ -164,10 +164,10 @@ def cyclogeostrophy(
     coriolis_factor_v = geometry.compute_coriolis_factor(lat_v)
 
     # Handle spurious and masked data
-    u_geos_u = sanitize.sanitize_data(u_geos_u, 0, is_land)
-    v_geos_v = sanitize.sanitize_data(v_geos_v, 0, is_land)
+    u_geos_u = sanitize.sanitize_data(u_geos_u, jnp.nan, is_land)
+    v_geos_v = sanitize.sanitize_data(v_geos_v, jnp.nan, is_land)
 
-    if method == "minimization":
+    if method == "minimization-based":
         if n_it is None:
             n_it = N_IT_MB
         if isinstance(optim, str):
@@ -179,13 +179,13 @@ def cyclogeostrophy(
                             "an optimizer.")
         res = _minimization_based(u_geos_u, v_geos_v, dx_u, dx_v, dy_u, dy_v, coriolis_factor_u, coriolis_factor_v, 
                                   is_land, n_it, optim)
-    elif method == "fixed_point":
+    elif method == "fixed-point":
         if n_it is None:
             n_it = N_IT_FP
         res = _fixed_point(u_geos_u, v_geos_v, dx_u, dx_v, dy_u, dy_v, coriolis_factor_u, coriolis_factor_v, is_land,
                            n_it, res_eps, use_res_filter, res_filter_size, return_losses)
     else:
-        raise ValueError("method should be one of [\"minimization\", \"fixed_point\"]")
+        raise ValueError("method should be one of [\"minimization-based\", \"fixed-point\"]")
 
     # Handle masked data
     u_cyclo_u, v_cyclo_v, losses = res