From 07508af8b7e4ea5ff3793301c42596000bdc66e0 Mon Sep 17 00:00:00 2001
From: Helen Macdonald <179985228+helenmacdonald@users.noreply.github.com>
Date: Fri, 3 Jan 2025 14:04:07 +1100
Subject: [PATCH 1/8] fixing ERA5 winds paths

---
 regional_mom6/regional_mom6.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/regional_mom6/regional_mom6.py b/regional_mom6/regional_mom6.py
index cc843959..ee940bd1 100644
--- a/regional_mom6/regional_mom6.py
+++ b/regional_mom6/regional_mom6.py
@@ -2720,7 +2720,8 @@ def setup_era5(self, era5_path):
                 i for i in range(self.date_range[0].year, self.date_range[1].year + 1)
             ]
             # construct a list of all paths for all years to use for open_mfdataset
-            paths_per_year = [Path(era5_path / fname / year) for year in years]
+  #          paths_per_year = [Path(era5_path / fname / year) for year in years]
+            paths_per_year = [Path(f"{era5_path}/{fname}/{year}/") for year in years]
             all_files = []
             for path in paths_per_year:
                 # Use glob to find all files that match the pattern

From 59a138ac855b11b82c04597f6d42c4835e97686b Mon Sep 17 00:00:00 2001
From: Helen Macdonald <helen.macdonald@anu.edu.au>
Date: Mon, 13 Jan 2025 16:15:44 +1100
Subject: [PATCH 2/8] Putting lat and lon in bathymetry.nc

---
 regional_mom6/regional_mom6.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/regional_mom6/regional_mom6.py b/regional_mom6/regional_mom6.py
index ee940bd1..fb78336a 100644
--- a/regional_mom6/regional_mom6.py
+++ b/regional_mom6/regional_mom6.py
@@ -1956,9 +1956,9 @@ def tidy_bathymetry(
         )
 
         ## Ensure correct encoding
-        bathymetry = xr.Dataset(
-            {"depth": (["ny", "nx"], bathymetry[vertical_coordinate_name].values)}
-        )
+#        bathymetry = xr.Dataset(
+#            {"depth": (["ny", "nx"], bathymetry[vertical_coordinate_name].values)}
+#        )
         bathymetry.attrs["depth"] = "meters"
         bathymetry.attrs["standard_name"] = "bathymetric depth at T-cell centers"
         bathymetry.attrs["coordinates"] = "zi"

From 2ec4b5dd9c22d61f0177ca1e93f8aa77b4ef233e Mon Sep 17 00:00:00 2001
From: Helen Macdonald <helen.macdonald@anu.edu.au>
Date: Tue, 14 Jan 2025 10:15:03 +1100
Subject: [PATCH 3/8] adding example notebook for BYO grid

---
 demos/BYO-domain.ipynb | 1264 ++++++++++++++++++++++++++++++++++++++++
 1 file changed, 1264 insertions(+)
 create mode 100644 demos/BYO-domain.ipynb

diff --git a/demos/BYO-domain.ipynb b/demos/BYO-domain.ipynb
new file mode 100644
index 00000000..58c827d9
--- /dev/null
+++ b/demos/BYO-domain.ipynb
@@ -0,0 +1,1264 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "TO DO\n",
+    "1)When switching to the tides_regridding branch this notebook will need to swap to the new tides command\n",
+    "2)Double check that tidal input files are being created in the correct directory\n",
+    "3)make file path generic"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Bring-your-own rotated and/or curvilinear domain \n",
+    "\n",
+    "This example is forced by GLORYS, ERA5 reanalysis datasets and TPXO tidal model\n",
+    "\n",
+    "**Note**: FRE-NC tools are required to be set up, as outlined in the [documentation](https://regional-mom6.readthedocs.io/en/latest/) of regional-mom6 package.\n",
+    "\n",
+    "For this example we need:\n",
+    "\n",
+    "- [GEBCO bathymetry](https://www.gebco.net/data_and_products/gridded_bathymetry_data/)\n",
+    "- [GLORYS ocean reanalysis data](https://data.marine.copernicus.eu/product/GLOBAL_MULTIYEAR_PHY_001_030/description), and\n",
+    "- [ERA5 surface forcing](https://www.ecmwf.int/en/forecasts/dataset/ecmwf-reanalysis-v5)\n",
+    "- [TPXO tidel model](https://www.tpxo.net/global)\n",
+    "\n",
+    "This example reads in the entire global extent of ERA5, GEBCO and TPXO; we don't need to worry about cutting it down to size.\n",
+    "This example requires you to bring your own mom-6 compatible model domain input netcdf file called hgrid.nc. This regional mom-6 toolbox can cope with regular, rotated and curvilinear model domains.  \n",
+    "\n",
+    "Note that this notebook includes some example plots and you will need matplotlib for the plots to work"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "    <div style=\"width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;\"> </div>\n",
+       "    <div style=\"margin-left: 48px;\">\n",
+       "        <h3 style=\"margin-bottom: 0px;\">Client</h3>\n",
+       "        <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Client-1edf1ea8-d1ff-11ef-b04d-000007c5fe80</p>\n",
+       "        <table style=\"width: 100%; text-align: left;\">\n",
+       "\n",
+       "        <tr>\n",
+       "        \n",
+       "            <td style=\"text-align: left;\"><strong>Connection method:</strong> Cluster object</td>\n",
+       "            <td style=\"text-align: left;\"><strong>Cluster type:</strong> distributed.LocalCluster</td>\n",
+       "        \n",
+       "        </tr>\n",
+       "\n",
+       "        \n",
+       "            <tr>\n",
+       "                <td style=\"text-align: left;\">\n",
+       "                    <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:8787/status\" target=\"_blank\">http://127.0.0.1:8787/status</a>\n",
+       "                </td>\n",
+       "                <td style=\"text-align: left;\"></td>\n",
+       "            </tr>\n",
+       "        \n",
+       "\n",
+       "        </table>\n",
+       "\n",
+       "        \n",
+       "\n",
+       "        \n",
+       "            <details>\n",
+       "            <summary style=\"margin-bottom: 20px;\"><h3 style=\"display: inline;\">Cluster Info</h3></summary>\n",
+       "            <div class=\"jp-RenderedHTMLCommon jp-RenderedHTML jp-mod-trusted jp-OutputArea-output\">\n",
+       "    <div style=\"width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;\">\n",
+       "    </div>\n",
+       "    <div style=\"margin-left: 48px;\">\n",
+       "        <h3 style=\"margin-bottom: 0px; margin-top: 0px;\">LocalCluster</h3>\n",
+       "        <p style=\"color: #9D9D9D; margin-bottom: 0px;\">06bc5943</p>\n",
+       "        <table style=\"width: 100%; text-align: left;\">\n",
+       "            <tr>\n",
+       "                <td style=\"text-align: left;\">\n",
+       "                    <strong>Dashboard:</strong> <a href=\"http://127.0.0.1:8787/status\" target=\"_blank\">http://127.0.0.1:8787/status</a>\n",
+       "                </td>\n",
+       "                <td style=\"text-align: left;\">\n",
+       "                    <strong>Workers:</strong> 7\n",
+       "                </td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                <td style=\"text-align: left;\">\n",
+       "                    <strong>Total threads:</strong> 7\n",
+       "                </td>\n",
+       "                <td style=\"text-align: left;\">\n",
+       "                    <strong>Total memory:</strong> 32.00 GiB\n",
+       "                </td>\n",
+       "            </tr>\n",
+       "            \n",
+       "            <tr>\n",
+       "    <td style=\"text-align: left;\"><strong>Status:</strong> running</td>\n",
+       "    <td style=\"text-align: left;\"><strong>Using processes:</strong> True</td>\n",
+       "</tr>\n",
+       "\n",
+       "            \n",
+       "        </table>\n",
+       "\n",
+       "        <details>\n",
+       "            <summary style=\"margin-bottom: 20px;\">\n",
+       "                <h3 style=\"display: inline;\">Scheduler Info</h3>\n",
+       "            </summary>\n",
+       "\n",
+       "            <div style=\"\">\n",
+       "    <div>\n",
+       "        <div style=\"width: 24px; height: 24px; background-color: #FFF7E5; border: 3px solid #FF6132; border-radius: 5px; position: absolute;\"> </div>\n",
+       "        <div style=\"margin-left: 48px;\">\n",
+       "            <h3 style=\"margin-bottom: 0px;\">Scheduler</h3>\n",
+       "            <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Scheduler-b98902c6-547b-4dac-94aa-28101a140d3c</p>\n",
+       "            <table style=\"width: 100%; text-align: left;\">\n",
+       "                <tr>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Comm:</strong> tcp://127.0.0.1:35579\n",
+       "                    </td>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Workers:</strong> 7\n",
+       "                    </td>\n",
+       "                </tr>\n",
+       "                <tr>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Dashboard:</strong> <a href=\"http://127.0.0.1:8787/status\" target=\"_blank\">http://127.0.0.1:8787/status</a>\n",
+       "                    </td>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Total threads:</strong> 7\n",
+       "                    </td>\n",
+       "                </tr>\n",
+       "                <tr>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Started:</strong> Just now\n",
+       "                    </td>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Total memory:</strong> 32.00 GiB\n",
+       "                    </td>\n",
+       "                </tr>\n",
+       "            </table>\n",
+       "        </div>\n",
+       "    </div>\n",
+       "\n",
+       "    <details style=\"margin-left: 48px;\">\n",
+       "        <summary style=\"margin-bottom: 20px;\">\n",
+       "            <h3 style=\"display: inline;\">Workers</h3>\n",
+       "        </summary>\n",
+       "\n",
+       "        \n",
+       "        <div style=\"margin-bottom: 20px;\">\n",
+       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
+       "            <div style=\"margin-left: 48px;\">\n",
+       "            <details>\n",
+       "                <summary>\n",
+       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 0</h4>\n",
+       "                </summary>\n",
+       "                <table style=\"width: 100%; text-align: left;\">\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Comm: </strong> tcp://127.0.0.1:45001\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Total threads: </strong> 1\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:44295/status\" target=\"_blank\">http://127.0.0.1:44295/status</a>\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Memory: </strong> 4.57 GiB\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Nanny: </strong> tcp://127.0.0.1:44103\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\"></td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
+       "                            <strong>Local directory: </strong> /jobfs/132253303.gadi-pbs/dask-scratch-space/worker-7l4otz4l\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                </table>\n",
+       "            </details>\n",
+       "            </div>\n",
+       "        </div>\n",
+       "        \n",
+       "        <div style=\"margin-bottom: 20px;\">\n",
+       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
+       "            <div style=\"margin-left: 48px;\">\n",
+       "            <details>\n",
+       "                <summary>\n",
+       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 1</h4>\n",
+       "                </summary>\n",
+       "                <table style=\"width: 100%; text-align: left;\">\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Comm: </strong> tcp://127.0.0.1:44011\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Total threads: </strong> 1\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:41055/status\" target=\"_blank\">http://127.0.0.1:41055/status</a>\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Memory: </strong> 4.57 GiB\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Nanny: </strong> tcp://127.0.0.1:44545\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\"></td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
+       "                            <strong>Local directory: </strong> /jobfs/132253303.gadi-pbs/dask-scratch-space/worker-hrjqe8np\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                </table>\n",
+       "            </details>\n",
+       "            </div>\n",
+       "        </div>\n",
+       "        \n",
+       "        <div style=\"margin-bottom: 20px;\">\n",
+       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
+       "            <div style=\"margin-left: 48px;\">\n",
+       "            <details>\n",
+       "                <summary>\n",
+       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 2</h4>\n",
+       "                </summary>\n",
+       "                <table style=\"width: 100%; text-align: left;\">\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Comm: </strong> tcp://127.0.0.1:33481\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Total threads: </strong> 1\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:43611/status\" target=\"_blank\">http://127.0.0.1:43611/status</a>\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Memory: </strong> 4.57 GiB\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Nanny: </strong> tcp://127.0.0.1:38207\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\"></td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
+       "                            <strong>Local directory: </strong> /jobfs/132253303.gadi-pbs/dask-scratch-space/worker-_v0grs05\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                </table>\n",
+       "            </details>\n",
+       "            </div>\n",
+       "        </div>\n",
+       "        \n",
+       "        <div style=\"margin-bottom: 20px;\">\n",
+       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
+       "            <div style=\"margin-left: 48px;\">\n",
+       "            <details>\n",
+       "                <summary>\n",
+       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 3</h4>\n",
+       "                </summary>\n",
+       "                <table style=\"width: 100%; text-align: left;\">\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Comm: </strong> tcp://127.0.0.1:38391\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Total threads: </strong> 1\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:43375/status\" target=\"_blank\">http://127.0.0.1:43375/status</a>\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Memory: </strong> 4.57 GiB\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Nanny: </strong> tcp://127.0.0.1:42323\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\"></td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
+       "                            <strong>Local directory: </strong> /jobfs/132253303.gadi-pbs/dask-scratch-space/worker-q8vviqis\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                </table>\n",
+       "            </details>\n",
+       "            </div>\n",
+       "        </div>\n",
+       "        \n",
+       "        <div style=\"margin-bottom: 20px;\">\n",
+       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
+       "            <div style=\"margin-left: 48px;\">\n",
+       "            <details>\n",
+       "                <summary>\n",
+       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 4</h4>\n",
+       "                </summary>\n",
+       "                <table style=\"width: 100%; text-align: left;\">\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Comm: </strong> tcp://127.0.0.1:45719\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Total threads: </strong> 1\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:36917/status\" target=\"_blank\">http://127.0.0.1:36917/status</a>\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Memory: </strong> 4.57 GiB\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Nanny: </strong> tcp://127.0.0.1:46155\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\"></td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
+       "                            <strong>Local directory: </strong> /jobfs/132253303.gadi-pbs/dask-scratch-space/worker-p19shwu2\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                </table>\n",
+       "            </details>\n",
+       "            </div>\n",
+       "        </div>\n",
+       "        \n",
+       "        <div style=\"margin-bottom: 20px;\">\n",
+       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
+       "            <div style=\"margin-left: 48px;\">\n",
+       "            <details>\n",
+       "                <summary>\n",
+       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 5</h4>\n",
+       "                </summary>\n",
+       "                <table style=\"width: 100%; text-align: left;\">\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Comm: </strong> tcp://127.0.0.1:35585\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Total threads: </strong> 1\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:33031/status\" target=\"_blank\">http://127.0.0.1:33031/status</a>\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Memory: </strong> 4.57 GiB\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Nanny: </strong> tcp://127.0.0.1:43339\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\"></td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
+       "                            <strong>Local directory: </strong> /jobfs/132253303.gadi-pbs/dask-scratch-space/worker-0flhszy7\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                </table>\n",
+       "            </details>\n",
+       "            </div>\n",
+       "        </div>\n",
+       "        \n",
+       "        <div style=\"margin-bottom: 20px;\">\n",
+       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
+       "            <div style=\"margin-left: 48px;\">\n",
+       "            <details>\n",
+       "                <summary>\n",
+       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 6</h4>\n",
+       "                </summary>\n",
+       "                <table style=\"width: 100%; text-align: left;\">\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Comm: </strong> tcp://127.0.0.1:39715\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Total threads: </strong> 1\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:41109/status\" target=\"_blank\">http://127.0.0.1:41109/status</a>\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Memory: </strong> 4.57 GiB\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Nanny: </strong> tcp://127.0.0.1:46827\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\"></td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
+       "                            <strong>Local directory: </strong> /jobfs/132253303.gadi-pbs/dask-scratch-space/worker-db6x7lpk\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                </table>\n",
+       "            </details>\n",
+       "            </div>\n",
+       "        </div>\n",
+       "        \n",
+       "\n",
+       "    </details>\n",
+       "</div>\n",
+       "\n",
+       "        </details>\n",
+       "    </div>\n",
+       "</div>\n",
+       "            </details>\n",
+       "        \n",
+       "\n",
+       "    </div>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "<Client: 'tcp://127.0.0.1:35579' processes=7 threads=7, memory=32.00 GiB>"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import regional_mom6 as rmom6\n",
+    "\n",
+    "import os\n",
+    "from pathlib import Path\n",
+    "from dask.distributed import Client\n",
+    "client = Client()\n",
+    "client"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Step 1: Choose our domain, define workspace paths\n",
+    "\n",
+    "To make sure that things are working I'd recommend starting with a small domain. If this runs ok, then change to the domain of your choice and hopefully it runs ok too! If not, check the [README](https://github.com/COSIMA/regional-mom6/blob/main/README.md) and [documentation](https://regional-mom6.readthedocs.io/) for troubleshooting tips.\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "expt_name = \"rotated-demo\"\n",
+    "\n",
+    "#latitude_extent = [16., 27]\n",
+    "#longitude_extent = [192, 209] #fill will nones and test these are optional so remove\n",
+    "\n",
+    "date_range = [\"2020-01-01 00:00:00\", \"2020-02-01 00:00:00\"]\n",
+    "\n",
+    "## Place where all your input files go \n",
+    "input_dir = Path(f\"/scratch/tm70/hm6113/regional_ncar/{expt_name}/\")\n",
+    "\n",
+    "## Directory where you'll run the experiment from\n",
+    "run_dir = Path(f\"/scratch/tm70/hm6113/regional_ncar/{expt_name}/\")\n",
+    "\n",
+    "## Directory where compiled FRE tools are located (needed for construction of mask tables)\n",
+    "toolpath_dir = Path(\"/g/data/tm70/hm6113/repo/FRE-NCtools\")\n",
+    "\n",
+    "## Path to where your raw ocean forcing files are stored\n",
+    "glorys_path = Path(f\"/g/data/tm70/hm6113/glorys/{expt_name}\" )\n",
+    "\n",
+    "#Directory where the ERA raw atmospheric output files are stored\n",
+    "era_path = Path(\"/g/data/rt52/era5/single-levels/reanalysis\")\n",
+    "\n",
+    "#Location of TPXO raw tidal file\n",
+    "tide_h_path = Path(\"/g/data/tm70/hm6113/tides/DATA/h_tpxo10.v2.nc\")\n",
+    "tide_u_path = Path(\"/g/data/tm70/hm6113/tides/DATA/u_tpxo10.v2.nc\")\n",
+    "\n",
+    "#location of the BYO hgrid file\n",
+    "byogrid_path = \"/scratch/tm70/hm6113/regional_ncar/rotated-demo/hgrid.nc\"\n",
+    "\n",
+    "#location to where your bathymetry data is stored\n",
+    "bathy_path = Path(\"/scratch/tm70/hm6113/GEBCO_2024.nc\")\n",
+    "\n",
+    "## if directories don't exist, create them\n",
+    "for path in (run_dir, glorys_path, input_dir):\n",
+    "    os.makedirs(str(path), exist_ok=True)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'/scratch/tm70/hm6113/regional_ncar/rotated-demo5/hgrid.nc'"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "##Copy hgrid.nc into the experinment folder\n",
+    "import shutil\n",
+    "shutil.copy2(byogrid_path,input_dir)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Step 2: Make experiment object\n",
+    "The `regional_mom6.experiment` contains the regional domain basics, and also generates the horizontal and vertical grids, `hgrid` and `vgrid` respectively, and sets up the directory structures. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "expt = rmom6.experiment(\n",
+    "    date_range = date_range,\n",
+    "    resolution = 0.5,\n",
+    "    number_vertical_layers = 75,\n",
+    "    layer_thickness_ratio = 100,\n",
+    "    depth = 4500,\n",
+    "    minimum_depth = 5,\n",
+    "    mom_run_dir = run_dir,\n",
+    "    mom_input_dir = input_dir,\n",
+    "    toolpath_dir = toolpath_dir,\n",
+    "    hgrid_type = 'from_file',\n",
+    "    boundaries = ['north','south','east','west']\n",
+    ")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can now access the horizontal and vertical grid of the regional configuration via `expt.hgrid` and `expt.vgrid` respectively.\n",
+    "\n",
+    "Plotting the vertical grid with `marker = '.'` lets you see the spacing. You can use `numpy.diff` to compute the vertical spacings, e.g.,\n",
+    "```python\n",
+    "import numpy as np\n",
+    "np.diff(expt.vgrid.zl).plot(marker = '.')\n",
+    "```\n",
+    "shows you the vertical spacing profile.\n",
+    "\n",
+    "### Modular workflow!\n",
+    "\n",
+    "After constructing your `expt` object, if you don't like the default `hgrid` and `vgrid` you can simply modify and then save them back into the `expt` object. However, you'll then also need to save them to disk again. For example:\n",
+    "\n",
+    "```python\n",
+    "new_hgrid = xr.open_dataset(input_dir + \"/hgrid.nc\")\n",
+    "```\n",
+    "Modify `new_hgrid`, ensuring that _all metadata_ is retained to keep MOM6 happy. Then, save your changes\n",
+    "\n",
+    "```python\n",
+    "expt.hgrid = new_hgrid\n",
+    "\n",
+    "expt.hgrid.to_netcdf(input_dir + \"/hgrid.nc\")\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Step 3: Prepare ocean forcing data\n",
+    "\n",
+    "We need to cut out our ocean forcing. The package expects an initial condition and one time-dependent segment per non-land boundary. Naming convention is `\"east_unprocessed\"` for segments and `\"ic_unprocessed\"` for the initial condition.\n",
+    "\n",
+    "In this notebook, we are forcing with the Copernicus Marine \"Glorys\" reanalysis dataset. There's a function in the `mom6-regional` package that generates a bash script to download the correct boundary forcing files for your experiment. First, you will need to create an account with Copernicus, and then call `copernicusmarine login` to set up your login details on your machine. Then you can run the `get_glorys_data.sh` bash script.\n",
+    "\n",
+    "This bash script uses the [Capernicus marine toolbox]( https://help.marine.copernicus.eu/en/articles/7970514-copernicus-marine-toolbox-installation) and users should install this before running the bash script.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "script `get_glorys_data.sh` has been created at /g/data/tm70/hm6113/glorys/rotated-demo5.\n",
+      " Run this script via bash to download the data from a terminal with internet access. \n",
+      "You will need to enter your Copernicus Marine username and password.\n",
+      "If you don't have an account, make one here:\n",
+      "https://data.marine.copernicus.eu/register\n"
+     ]
+    }
+   ],
+   "source": [
+    "expt.get_glorys_rectangular(\n",
+    "    raw_boundaries_path=glorys_path\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Step 4: Set up bathymetry\n",
+    "\n",
+    "Similarly to ocean forcing, we point the experiment's `setup_bathymetry` method at the location of the file of choice and also provide the variable names. We don't need to preprocess the bathymetry since it is simply a two-dimensional field and is easier to deal with. Afterwards you can inspect `expt.bathymetry` to have a look at the regional domain.\n",
+    "\n",
+    "After running this cell, your input directory will contain other bathymetry-related things like the ocean mosaic and mask table too. The mask table defaults to a 10x10 layout and can be modified later."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Begin regridding bathymetry...\n",
+      "\n",
+      "Original bathymetry size: 9.96 Mb\n",
+      "Regridded size: 0.06 Mb\n",
+      "Automatic regridding may fail if your domain is too big! If this process hangs or crashes,open a terminal with appropriate computational and resources try calling ESMF directly in the input directory /scratch/tm70/hm6113/regional_ncar/rotated-demo5 via\n",
+      "\n",
+      "`mpirun -np NUMBER_OF_CPUS ESMF_Regrid -s bathymetry_original.nc -d bathymetry_unfinished.nc -m bilinear --src_var depth --dst_var depth --netcdf4 --src_regional --dst_regional`\n",
+      "\n",
+      "For details see https://xesmf.readthedocs.io/en/latest/large_problems_on_HPC.html\n",
+      "\n",
+      "Afterwards, run the 'expt.tidy_bathymetry' method to skip the expensive interpolation step, and finishing metadata, encoding and cleanup.\n",
+      "\n",
+      "\n",
+      "\n",
+      "Regridding successful! Now calling `tidy_bathymetry` method for some finishing touches...\n",
+      "Tidy bathymetry: Reading in regridded bathymetry to fix up metadata...done. Filling in inland lakes and channels... done.\n",
+      "setup bathymetry has finished successfully.\n"
+     ]
+    }
+   ],
+   "source": [
+    "expt.setup_bathymetry(\n",
+    "    bathymetry_path=bathy_path,\n",
+    "    longitude_coordinate_name=\"lon\",\n",
+    "    latitude_coordinate_name=\"lat\",\n",
+    "    vertical_coordinate_name=\"elevation\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Check out your domain: \n",
+    "Calling expt.bathymetry returns an xarray dataset, which can be plotted as usual. If you haven't yet run setup_bathymetry, calling expt.bathymetry will return None and prompt you to do so!\n",
+    "\n",
+    "We do 2 different plots, the first is in x and y coordinates and will look rectangular. The second is in lat and lon coordinates and will show the shape of the curvilinear/rotated domain."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "tags": [
+     "nbval-ignore-output",
+     "nbval-skip"
+    ]
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x15009ed04f50>"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#In x/y coords\n",
+    "expt.bathymetry.depth.plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "tags": [
+     "nbval-ignore-output",
+     "nbval-skip"
+    ]
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x15009ea86fd0>"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#In lat/lon coords\n",
+    "import xarray as xr\n",
+    "bathy = xr.open_dataset(run_dir / \"bathymetry.nc\")\n",
+    "bathy.depth.plot(x=\"lon\",y=\"lat\")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "##  Step 5: Handle the ocean forcing - where the magic happens\n",
+    "\n",
+    "This cuts out and interpolates the initial condition as well as all boundaries (unless you don't pass it boundaries).\n",
+    "\n",
+    "The dictionary maps the MOM6 variable names to what they're called in your ocean input file. Notice how for GLORYS, the horizontal dimensions are `latitude` and `longitude`, vs `xh`, `yh`, `xq`, `yq` for MOM6. This is because for an 'A' grid type tracers share the grid with velocities so there's no difference.\n",
+    "\n",
+    "If one of your segments is land, you can delete its string from the 'boundaries' list. You'll need to update MOM_input to reflect this though so it knows how many segments to look for, and their orientations."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "INITIAL CONDITIONS\n",
+      "Regridding Velocities... Done.\n",
+      "Regridding Tracers... Done.\n",
+      "Regridding Free surface... Done.\n",
+      "Saving outputs... done setting up initial condition.\n",
+      "Processing north boundary...Done.\n",
+      "Processing south boundary...Done.\n",
+      "Processing east boundary...Done.\n",
+      "Processing west boundary...Done.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Define a mapping from the GLORYS variables and dimensions to the MOM6 ones\n",
+    "ocean_varnames = {\"time\": \"time\",\n",
+    "                  \"yh\": \"latitude\",\n",
+    "                  \"xh\": \"longitude\",\n",
+    "                  \"zl\": \"depth\",\n",
+    "                  \"eta\": \"zos\",\n",
+    "                  \"u\": \"uo\",\n",
+    "                  \"v\": \"vo\",\n",
+    "                  \"tracers\": {\"salt\": \"so\", \"temp\": \"thetao\"}\n",
+    "                  }\n",
+    "\n",
+    "# Set up the initial condition\n",
+    "expt.setup_initial_condition(\n",
+    "    glorys_path / \"ic_unprocessed.nc\", # directory where the unprocessed initial condition is stored, as defined earlier\n",
+    "    ocean_varnames,\n",
+    "    arakawa_grid=\"A\"\n",
+    "    )    \n",
+    "\n",
+    "# Set up the four boundary conditions. Remember that in the glorys_path, we have four boundary files names north_unprocessed.nc etc. \n",
+    "expt.setup_ocean_state_boundaries(\n",
+    "        glorys_path,\n",
+    "        ocean_varnames,\n",
+    "        arakawa_grid = \"A\"\n",
+    "        )\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Check out your initial condition data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'lon/lat coords')"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1600x400 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "## Preview the initial temperature at the surface in x/y and lat/lon coordinates\n",
+    "from matplotlib import pyplot as plt\n",
+    "##Creating a new temperature array with lat and lon coords\n",
+    "templatlon = expt.init_tracers.temp.assign_coords(lon=bathy.lon,lat=bathy.lat)\n",
+    "\n",
+    "#plotting\n",
+    "fig, axes = plt.subplots(ncols=2, figsize=(16,4))\n",
+    "templatlon.isel(zl=0).plot(ax=axes[0])\n",
+    "templatlon.isel(zl=0).plot(x=\"lon\",y=\"lat\",ax=axes[1])\n",
+    "axes[0].set_title(\"x/y coords\")\n",
+    "axes[1].set_title(\"lon/lat coords\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x15009ca36390>"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "## u boundary forcing for segment 1 (south)\n",
+    "expt.segment_001.u_segment_001.isel(time = 5).plot()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Step 6: Create Tidal forcing\n",
+    "You may need to change \"tpxo10.v2.nc\" to reflect your version"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#THIS ONE WORKS FOR MAIN\n",
+    "#NOTE \"rectangle\" is the only option\n",
+    "#expt.setup_boundary_tides(\n",
+    "#        Path(\"/g/data/tm70/hm6113/tides/DATA\"),\"tpxo10.v2.nc\",\n",
+    "#        tidal_constituents=[\"M2\"],\n",
+    "#        boundary_type=\"rectangle\"\n",
+    "#)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Processing north boundary...2025-01-10 14:36:52,454 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
+      "2025-01-10 14:36:52,458 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
+      "2025-01-10 14:37:13,744 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:37:13,747 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:37:13,756 - regional_mom6.regridding.add_or_update_time_dim - INFO - Adding time dimension\n",
+      "2025-01-10 14:37:13,760 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
+      "2025-01-10 14:37:13,762 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to zamp_segment_001\n",
+      "2025-01-10 14:37:13,765 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to zphase_segment_001\n",
+      "2025-01-10 14:37:13,767 - regional_mom6.regridding.mask_dataset - WARNING - All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
+      "2025-01-10 14:37:13,768 - regional_mom6.regridding.generate_encoding - INFO - Generating encoding dictionary\n",
+      "2025-01-10 14:37:13,861 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
+      "2025-01-10 14:37:35,116 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
+      "2025-01-10 14:37:56,654 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:37:56,655 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:37:56,657 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:37:56,659 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:37:56,675 - regional_mom6.regridding.add_or_update_time_dim - INFO - Adding time dimension\n",
+      "2025-01-10 14:37:56,680 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:37:56,684 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
+      "2025-01-10 14:37:56,687 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to uamp_segment_001\n",
+      "2025-01-10 14:37:56,688 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to vamp_segment_001\n",
+      "2025-01-10 14:37:56,690 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to uphase_segment_001\n",
+      "2025-01-10 14:37:56,692 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to vphase_segment_001\n",
+      "2025-01-10 14:37:56,694 - regional_mom6.regridding.mask_dataset - WARNING - All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
+      "2025-01-10 14:37:56,695 - regional_mom6.regridding.generate_encoding - INFO - Generating encoding dictionary\n",
+      "Done\n",
+      "Processing south boundary...2025-01-10 14:37:56,755 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
+      "2025-01-10 14:37:56,757 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
+      "2025-01-10 14:38:17,931 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:38:17,934 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:38:17,939 - regional_mom6.regridding.add_or_update_time_dim - INFO - Adding time dimension\n",
+      "2025-01-10 14:38:17,944 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
+      "2025-01-10 14:38:17,946 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to zamp_segment_002\n",
+      "2025-01-10 14:38:17,948 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to zphase_segment_002\n",
+      "2025-01-10 14:38:17,950 - regional_mom6.regridding.mask_dataset - WARNING - All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
+      "2025-01-10 14:38:17,952 - regional_mom6.regridding.generate_encoding - INFO - Generating encoding dictionary\n",
+      "2025-01-10 14:38:17,982 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
+      "2025-01-10 14:38:39,684 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
+      "2025-01-10 14:39:01,135 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:39:01,136 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:39:01,137 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:39:01,139 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:39:01,152 - regional_mom6.regridding.add_or_update_time_dim - INFO - Adding time dimension\n",
+      "2025-01-10 14:39:01,155 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:39:01,159 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
+      "2025-01-10 14:39:01,161 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to uamp_segment_002\n",
+      "2025-01-10 14:39:01,163 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to vamp_segment_002\n",
+      "2025-01-10 14:39:01,165 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to uphase_segment_002\n",
+      "2025-01-10 14:39:01,167 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to vphase_segment_002\n",
+      "2025-01-10 14:39:01,168 - regional_mom6.regridding.mask_dataset - WARNING - All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
+      "2025-01-10 14:39:01,170 - regional_mom6.regridding.generate_encoding - INFO - Generating encoding dictionary\n",
+      "Done\n",
+      "Processing east boundary...2025-01-10 14:39:01,241 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
+      "2025-01-10 14:39:01,243 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
+      "2025-01-10 14:39:22,804 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:39:22,806 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:39:22,811 - regional_mom6.regridding.add_or_update_time_dim - INFO - Adding time dimension\n",
+      "2025-01-10 14:39:22,815 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
+      "2025-01-10 14:39:22,817 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to zamp_segment_003\n",
+      "2025-01-10 14:39:22,820 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to zphase_segment_003\n",
+      "2025-01-10 14:39:22,822 - regional_mom6.regridding.mask_dataset - WARNING - All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
+      "2025-01-10 14:39:22,823 - regional_mom6.regridding.generate_encoding - INFO - Generating encoding dictionary\n",
+      "2025-01-10 14:39:22,850 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
+      "2025-01-10 14:39:43,725 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
+      "2025-01-10 14:40:04,730 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:40:04,733 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:40:04,738 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:40:04,740 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:40:04,756 - regional_mom6.regridding.add_or_update_time_dim - INFO - Adding time dimension\n",
+      "2025-01-10 14:40:04,760 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:40:04,765 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
+      "2025-01-10 14:40:04,768 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to uamp_segment_003\n",
+      "2025-01-10 14:40:04,770 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to vamp_segment_003\n",
+      "2025-01-10 14:40:04,772 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to uphase_segment_003\n",
+      "2025-01-10 14:40:04,775 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to vphase_segment_003\n",
+      "2025-01-10 14:40:04,776 - regional_mom6.regridding.mask_dataset - WARNING - All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
+      "2025-01-10 14:40:04,778 - regional_mom6.regridding.generate_encoding - INFO - Generating encoding dictionary\n",
+      "Done\n",
+      "Processing west boundary...2025-01-10 14:40:04,815 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
+      "2025-01-10 14:40:04,817 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
+      "2025-01-10 14:40:25,799 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:40:25,801 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:40:25,806 - regional_mom6.regridding.add_or_update_time_dim - INFO - Adding time dimension\n",
+      "2025-01-10 14:40:25,810 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
+      "2025-01-10 14:40:25,813 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to zamp_segment_004\n",
+      "2025-01-10 14:40:25,816 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to zphase_segment_004\n",
+      "2025-01-10 14:40:25,818 - regional_mom6.regridding.mask_dataset - WARNING - All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
+      "2025-01-10 14:40:25,820 - regional_mom6.regridding.generate_encoding - INFO - Generating encoding dictionary\n",
+      "2025-01-10 14:40:25,850 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
+      "2025-01-10 14:40:47,150 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
+      "2025-01-10 14:41:07,908 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:41:07,910 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:41:07,911 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:41:07,912 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:41:07,923 - regional_mom6.regridding.add_or_update_time_dim - INFO - Adding time dimension\n",
+      "2025-01-10 14:41:07,928 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:41:07,932 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
+      "2025-01-10 14:41:07,934 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to uamp_segment_004\n",
+      "2025-01-10 14:41:07,936 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to vamp_segment_004\n",
+      "2025-01-10 14:41:07,937 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to uphase_segment_004\n",
+      "2025-01-10 14:41:07,938 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to vphase_segment_004\n",
+      "2025-01-10 14:41:07,941 - regional_mom6.regridding.mask_dataset - WARNING - All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
+      "2025-01-10 14:41:07,943 - regional_mom6.regridding.generate_encoding - INFO - Generating encoding dictionary\n",
+      "Done\n"
+     ]
+    }
+   ],
+   "source": [
+    "#THIS ONE WORKS FOR tides_regridding_branch\n",
+    "##NOTE THAT THE FILES ARE PLACED in forcing folder but input files seek them from the higher level directory.\n",
+    "expt.setup_boundary_tides(\n",
+    "        tide_h_path,\n",
+    "        tide_u_path,\n",
+    "        tidal_constituents=[\"M2\"],\n",
+    "        boundary_type=\"rectangle\"\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Step 7: Run the FRE tools\n",
+    "\n",
+    "This is just a wrapper for the FRE tools needed to make the mosaics and masks for the experiment. The only thing you need to tell it is the processor layout. In this case we're saying that we want a 10 by 10 grid of 100 processors. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Running GFDL's FRE Tools. The following information is all printed by the FRE tools themselves\n",
+      "i=0, yb1=58.1331888751, yb2=58.3479205820, dy= 0.2147317068\n",
+      "NOTE from make_solo_mosaic: there are 0 contacts (align-contact)\n",
+      "congratulation: You have successfully run make_solo_mosaic\n",
+      "OUTPUT FROM MAKE SOLO MOSAIC:\n",
+      "\n",
+      "CompletedProcess(args='/g/data/tm70/hm6113/repo/FRE-NCtools/make_solo_mosaic/make_solo_mosaic --num_tiles 1 --dir . --mosaic_name ocean_mosaic --tile_file hgrid.nc', returncode=0)\n",
+      "cp ./hgrid.nc hgrid.nc \n",
+      "\n",
+      "NOTE from make_coupler_mosaic: the ocean land/sea mask will be determined by field depth from file bathymetry.nc\n",
+      "mosaic_file is grid_spec.nc\n",
+      "\n",
+      "***** Congratulation! You have successfully run make_quick_mosaic\n",
+      "OUTPUT FROM QUICK MOSAIC:\n",
+      "\n",
+      "CompletedProcess(args='/g/data/tm70/hm6113/repo/FRE-NCtools/make_quick_mosaic/make_quick_mosaic --input_mosaic ocean_mosaic.nc --mosaic_name grid_spec --ocean_topog bathymetry.nc', returncode=0)\n",
+      "\n",
+      " ===>NOTE from check_mask: when layout is specified, min_pe and max_pe is set to layout(1)*layout(2)=100\n",
+      "\n",
+      " ===>NOTE from check_mask: Below is the list of command line arguments.\n",
+      "\n",
+      "grid_file = ocean_mosaic.nc\n",
+      "model = ocean\n",
+      "topog_file = bathymetry.nc\n",
+      "min_pe = 100\n",
+      "max_pe = 100\n",
+      "layout = 10, 10\n",
+      "halo = 4\n",
+      "sea_level = 0\n",
+      "show_valid_only is not set\n",
+      "nobc = 0\n",
+      "\n",
+      " ===>NOTE from check_mask: End of command line arguments.\n",
+      "\n",
+      " ===>NOTE from check_mask: the grid file is version 2 (solo mosaic grid) grid which contains field gridfiles\n",
+      "\n",
+      "==>NOTE from get_boundary_type: x_boundary_type is solid_walls\n",
+      "\n",
+      "==>NOTE from get_boundary_type: y_boundary_type is solid_walls\n",
+      "\n",
+      "==>NOTE from check_mask: Checking for possible masking:\n",
+      "==>NOTE from check_mask: Assume 4 halo rows\n",
+      "==>NOTE from check_mask: Total domain size is 49, 49\n",
+      "\n",
+      "***** Congratulation! You have successfully run check_mask\n",
+      "OUTPUT FROM CHECK MASK:\n",
+      "\n",
+      " CompletedProcess(args='/g/data/tm70/hm6113/repo/FRE-NCtools/check_mask/check_mask --grid_file ocean_mosaic.nc --ocean_topog bathymetry.nc --layout 10,10 --halo 4', returncode=0)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "cp: './ocean_mosaic.nc' and 'ocean_mosaic.nc' are the same file\n",
+      "cp: './hgrid.nc' and 'hgrid.nc' are the same file\n"
+     ]
+    }
+   ],
+   "source": [
+    "expt.run_FRE_tools(layout=(10, 10)) ##the tiling/no processors"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Step 8: Set up ERA5 forcing:\n",
+    "\n",
+    "Here we assume the ERA5 dataset is stored somewhere on the system we are working on. \n",
+    "\n",
+    "Below is a table showing ERA5 characteristics and what needs to be done to sort it out.\n",
+    "\n",
+    "**Required ERA5 data**:\n",
+    "\n",
+    "Name | ERA5 filename | ERA5 variable name | Units\n",
+    "---|---|---|---\n",
+    "Surface Pressure | sp | sp | Pa \n",
+    "Surface Temperature | 2t | t2m | K \n",
+    "Meridional Wind | 10v | v10 | m/s \n",
+    "Zonal Wind | 10u | u10 | m/s \n",
+    "Specific Humidity | - | - | kg/kg, calculated from dewpoint temperature\n",
+    "Dewpoint Temperature | 2d | d2m | K\n",
+    "\n",
+    "\n",
+    "We calculate specific humidity $q$ from dewpoint temperature $T_d$ and surface pressure $P$ via saturation vapour pressure $P_v$.\n",
+    "\n",
+    "$$P_v = 10^{8.07131 - \\frac{1730.63}{233.426 + T}} \\frac{101325}{760} \\; \\textrm{[Pascal]} $$\n",
+    "\n",
+    "$$q = 0.001 \\times 0.622  \\frac{P_v}{P}$$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "expt.setup_era5(era_path)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Step 8: Modify the default input directory to make a (hopefully) runnable configuration out of the box\n",
+    "\n",
+    "This step copies the default directory and modifies the `MOM_layout` files to match your experiment by inserting the right number of x, y points and CPU layout.\n",
+    "\n",
+    "To run MOM6 using the [payu infrastructure](https://github.com/payu-org/payu), provide the keyword argument `using_payu = True` to the `setup_run_directory` method and an example `config.yaml` file will be appear in the run directory. The `config.yaml` file needs to be modified manually to add the locations of executables, etc."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Could not find premade run directories at  /scratch/tm70/hm6113/code/rm6_helen_dev/regional-mom6/regional_mom6/demos/premade_run_directories\n",
+      "Perhaps the package was imported directly rather than installed with conda. Checking if this is the case... \n",
+      "Found run files. Continuing...\n",
+      "No mask table found, but the cpu layout has been set to (10, 10) This suggests the domain is mostly water, so there are no `non compute` cells that are entirely land. If this doesn't seem right, ensure you've already run the `FRE_tools` method which sets up the cpu mask table. Keep an eye on any errors that might print whilethe FRE tools (which run C++ in the background) are running.\n",
+      "Number of CPUs required:  100\n",
+      "Deleting indexed OBC keys from MOM_input_dict in case we have a different number of segments\n"
+     ]
+    }
+   ],
+   "source": [
+    "expt.setup_run_directory(surface_forcing = \"era5\",using_payu = True, with_tides = True) "
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

From ccf6bff2ca34267313446fde12c4ce7ff6e9aca7 Mon Sep 17 00:00:00 2001
From: Helen Macdonald <helen.macdonald@anu.edu.au>
Date: Tue, 14 Jan 2025 10:44:51 +1100
Subject: [PATCH 4/8] adding tides to the tasman example

---
 demos/reanalysis-forced.ipynb | 149 ++++++++++++++++++++++++++++++++--
 1 file changed, 141 insertions(+), 8 deletions(-)

diff --git a/demos/reanalysis-forced.ipynb b/demos/reanalysis-forced.ipynb
index a4d161f2..31c59db6 100644
--- a/demos/reanalysis-forced.ipynb
+++ b/demos/reanalysis-forced.ipynb
@@ -11,8 +11,9 @@
     "For this example we need:\n",
     "\n",
     "- [GEBCO bathymetry](https://www.gebco.net/data_and_products/gridded_bathymetry_data/)\n",
-    "- [GLORYS ocean reanalysis data](https://data.marine.copernicus.eu/product/GLOBAL_MULTIYEAR_PHY_001_030/description), and\n",
-    "- [ERA5 surface forcing](https://www.ecmwf.int/en/forecasts/dataset/ecmwf-reanalysis-v5)\n",
+    "- [GLORYS ocean reanalysis data](https://data.marine.copernicus.eu/product/GLOBAL_MULTIYEAR_PHY_001_030/description)\n",
+    "- [ERA5 surface forcing](https://www.ecmwf.int/en/forecasts/dataset/ecmwf-reanalysis-v5), and\n",
+    "- [TPXO tidel model](https://www.tpxo.net/global)\n",
     "\n",
     "This example reads in the entire global extent of ERA5 and GEBCO; we don't need to worry about cutting it down to size."
    ]
@@ -327,7 +328,139 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Step 6: Run the FRE tools\n",
+    "## Step 6: Create tidal forcing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Processing north boundary...2025-01-10 14:36:52,454 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
+      "2025-01-10 14:36:52,458 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
+      "2025-01-10 14:37:13,744 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:37:13,747 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:37:13,756 - regional_mom6.regridding.add_or_update_time_dim - INFO - Adding time dimension\n",
+      "2025-01-10 14:37:13,760 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
+      "2025-01-10 14:37:13,762 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to zamp_segment_001\n",
+      "2025-01-10 14:37:13,765 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to zphase_segment_001\n",
+      "2025-01-10 14:37:13,767 - regional_mom6.regridding.mask_dataset - WARNING - All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
+      "2025-01-10 14:37:13,768 - regional_mom6.regridding.generate_encoding - INFO - Generating encoding dictionary\n",
+      "2025-01-10 14:37:13,861 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
+      "2025-01-10 14:37:35,116 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
+      "2025-01-10 14:37:56,654 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:37:56,655 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:37:56,657 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:37:56,659 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:37:56,675 - regional_mom6.regridding.add_or_update_time_dim - INFO - Adding time dimension\n",
+      "2025-01-10 14:37:56,680 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:37:56,684 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
+      "2025-01-10 14:37:56,687 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to uamp_segment_001\n",
+      "2025-01-10 14:37:56,688 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to vamp_segment_001\n",
+      "2025-01-10 14:37:56,690 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to uphase_segment_001\n",
+      "2025-01-10 14:37:56,692 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to vphase_segment_001\n",
+      "2025-01-10 14:37:56,694 - regional_mom6.regridding.mask_dataset - WARNING - All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
+      "2025-01-10 14:37:56,695 - regional_mom6.regridding.generate_encoding - INFO - Generating encoding dictionary\n",
+      "Done\n",
+      "Processing south boundary...2025-01-10 14:37:56,755 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
+      "2025-01-10 14:37:56,757 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
+      "2025-01-10 14:38:17,931 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:38:17,934 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:38:17,939 - regional_mom6.regridding.add_or_update_time_dim - INFO - Adding time dimension\n",
+      "2025-01-10 14:38:17,944 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
+      "2025-01-10 14:38:17,946 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to zamp_segment_002\n",
+      "2025-01-10 14:38:17,948 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to zphase_segment_002\n",
+      "2025-01-10 14:38:17,950 - regional_mom6.regridding.mask_dataset - WARNING - All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
+      "2025-01-10 14:38:17,952 - regional_mom6.regridding.generate_encoding - INFO - Generating encoding dictionary\n",
+      "2025-01-10 14:38:17,982 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
+      "2025-01-10 14:38:39,684 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
+      "2025-01-10 14:39:01,135 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:39:01,136 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:39:01,137 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:39:01,139 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:39:01,152 - regional_mom6.regridding.add_or_update_time_dim - INFO - Adding time dimension\n",
+      "2025-01-10 14:39:01,155 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:39:01,159 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
+      "2025-01-10 14:39:01,161 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to uamp_segment_002\n",
+      "2025-01-10 14:39:01,163 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to vamp_segment_002\n",
+      "2025-01-10 14:39:01,165 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to uphase_segment_002\n",
+      "2025-01-10 14:39:01,167 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to vphase_segment_002\n",
+      "2025-01-10 14:39:01,168 - regional_mom6.regridding.mask_dataset - WARNING - All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
+      "2025-01-10 14:39:01,170 - regional_mom6.regridding.generate_encoding - INFO - Generating encoding dictionary\n",
+      "Done\n",
+      "Processing east boundary...2025-01-10 14:39:01,241 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
+      "2025-01-10 14:39:01,243 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
+      "2025-01-10 14:39:22,804 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:39:22,806 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:39:22,811 - regional_mom6.regridding.add_or_update_time_dim - INFO - Adding time dimension\n",
+      "2025-01-10 14:39:22,815 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
+      "2025-01-10 14:39:22,817 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to zamp_segment_003\n",
+      "2025-01-10 14:39:22,820 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to zphase_segment_003\n",
+      "2025-01-10 14:39:22,822 - regional_mom6.regridding.mask_dataset - WARNING - All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
+      "2025-01-10 14:39:22,823 - regional_mom6.regridding.generate_encoding - INFO - Generating encoding dictionary\n",
+      "2025-01-10 14:39:22,850 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
+      "2025-01-10 14:39:43,725 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
+      "2025-01-10 14:40:04,730 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:40:04,733 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:40:04,738 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:40:04,740 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:40:04,756 - regional_mom6.regridding.add_or_update_time_dim - INFO - Adding time dimension\n",
+      "2025-01-10 14:40:04,760 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:40:04,765 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
+      "2025-01-10 14:40:04,768 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to uamp_segment_003\n",
+      "2025-01-10 14:40:04,770 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to vamp_segment_003\n",
+      "2025-01-10 14:40:04,772 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to uphase_segment_003\n",
+      "2025-01-10 14:40:04,775 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to vphase_segment_003\n",
+      "2025-01-10 14:40:04,776 - regional_mom6.regridding.mask_dataset - WARNING - All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
+      "2025-01-10 14:40:04,778 - regional_mom6.regridding.generate_encoding - INFO - Generating encoding dictionary\n",
+      "Done\n",
+      "Processing west boundary...2025-01-10 14:40:04,815 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
+      "2025-01-10 14:40:04,817 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
+      "2025-01-10 14:40:25,799 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:40:25,801 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:40:25,806 - regional_mom6.regridding.add_or_update_time_dim - INFO - Adding time dimension\n",
+      "2025-01-10 14:40:25,810 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
+      "2025-01-10 14:40:25,813 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to zamp_segment_004\n",
+      "2025-01-10 14:40:25,816 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to zphase_segment_004\n",
+      "2025-01-10 14:40:25,818 - regional_mom6.regridding.mask_dataset - WARNING - All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
+      "2025-01-10 14:40:25,820 - regional_mom6.regridding.generate_encoding - INFO - Generating encoding dictionary\n",
+      "2025-01-10 14:40:25,850 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
+      "2025-01-10 14:40:47,150 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
+      "2025-01-10 14:41:07,908 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:41:07,910 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:41:07,911 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:41:07,912 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:41:07,923 - regional_mom6.regridding.add_or_update_time_dim - INFO - Adding time dimension\n",
+      "2025-01-10 14:41:07,928 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
+      "2025-01-10 14:41:07,932 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
+      "2025-01-10 14:41:07,934 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to uamp_segment_004\n",
+      "2025-01-10 14:41:07,936 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to vamp_segment_004\n",
+      "2025-01-10 14:41:07,937 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to uphase_segment_004\n",
+      "2025-01-10 14:41:07,938 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to vphase_segment_004\n",
+      "2025-01-10 14:41:07,941 - regional_mom6.regridding.mask_dataset - WARNING - All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
+      "2025-01-10 14:41:07,943 - regional_mom6.regridding.generate_encoding - INFO - Generating encoding dictionary\n",
+      "Done\n"
+     ]
+    }
+   ],
+   "source": [
+    "expt.setup_boundary_tides(\n",
+    "        tide_h_path,\n",
+    "        tide_u_path,\n",
+    "        tidal_constituents=[\"M2\"],\n",
+    "        boundary_type=\"rectangle\"\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Step 7: Run the FRE tools\n",
     "\n",
     "This is just a wrapper for the FRE tools needed to make the mosaics and masks for the experiment. The only thing you need to tell it is the processor layout. In this case we're saying that we want a 10 by 10 grid of 100 processors. "
    ]
@@ -345,7 +478,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Step 7: Set up ERA5 forcing:\n",
+    "## Step 8: Set up ERA5 forcing:\n",
     "\n",
     "Here we assume the ERA5 dataset is stored somewhere on the system we are working on. \n",
     "\n",
@@ -387,7 +520,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Step 8: Modify the default input directory to make a (hopefully) runnable configuration out of the box\n",
+    "## Step 9: Modify the default input directory to make a (hopefully) runnable configuration out of the box\n",
     "\n",
     "This step copies the default directory and modifies the `MOM_layout` files to match your experiment by inserting the right number of x, y points and CPU layout.\n",
     "\n",
@@ -407,7 +540,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Step 9: Run and Troubleshoot!\n",
+    "## Step 10: Run and Troubleshoot!\n",
     "\n",
     "To run the regional configuration first navigate to your run directory in terminal and use your favourite tool to run the experiment on your system. \n",
     "\n",
@@ -428,7 +561,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "crr_dev",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -442,7 +575,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.7"
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,

From 7f92ad6ebafaa22281651a0b13bb494201699c14 Mon Sep 17 00:00:00 2001
From: Helen Macdonald <helen.macdonald@anu.edu.au>
Date: Mon, 20 Jan 2025 16:01:23 +1100
Subject: [PATCH 5/8] updating notebooks to be compatable with latest code
 updates

---
 demos/BYO-domain.ipynb        | 821 ++++++++++++++++++++++++++--------
 demos/reanalysis-forced.ipynb |  13 +-
 2 files changed, 638 insertions(+), 196 deletions(-)

diff --git a/demos/BYO-domain.ipynb b/demos/BYO-domain.ipynb
index 58c827d9..d125439f 100644
--- a/demos/BYO-domain.ipynb
+++ b/demos/BYO-domain.ipynb
@@ -5,7 +5,6 @@
    "metadata": {},
    "source": [
     "TO DO\n",
-    "1)When switching to the tides_regridding branch this notebook will need to swap to the new tides command\n",
     "2)Double check that tidal input files are being created in the correct directory\n",
     "3)make file path generic"
    ]
@@ -45,7 +44,7 @@
        "    <div style=\"width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;\"> </div>\n",
        "    <div style=\"margin-left: 48px;\">\n",
        "        <h3 style=\"margin-bottom: 0px;\">Client</h3>\n",
-       "        <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Client-1edf1ea8-d1ff-11ef-b04d-000007c5fe80</p>\n",
+       "        <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Client-52810be8-d6e7-11ef-8fbc-000007d8fe80</p>\n",
        "        <table style=\"width: 100%; text-align: left;\">\n",
        "\n",
        "        <tr>\n",
@@ -58,7 +57,7 @@
        "        \n",
        "            <tr>\n",
        "                <td style=\"text-align: left;\">\n",
-       "                    <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:8787/status\" target=\"_blank\">http://127.0.0.1:8787/status</a>\n",
+       "                    <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:36165/status\" target=\"_blank\">http://127.0.0.1:36165/status</a>\n",
        "                </td>\n",
        "                <td style=\"text-align: left;\"></td>\n",
        "            </tr>\n",
@@ -76,11 +75,11 @@
        "    </div>\n",
        "    <div style=\"margin-left: 48px;\">\n",
        "        <h3 style=\"margin-bottom: 0px; margin-top: 0px;\">LocalCluster</h3>\n",
-       "        <p style=\"color: #9D9D9D; margin-bottom: 0px;\">06bc5943</p>\n",
+       "        <p style=\"color: #9D9D9D; margin-bottom: 0px;\">0933c645</p>\n",
        "        <table style=\"width: 100%; text-align: left;\">\n",
        "            <tr>\n",
        "                <td style=\"text-align: left;\">\n",
-       "                    <strong>Dashboard:</strong> <a href=\"http://127.0.0.1:8787/status\" target=\"_blank\">http://127.0.0.1:8787/status</a>\n",
+       "                    <strong>Dashboard:</strong> <a href=\"http://127.0.0.1:36165/status\" target=\"_blank\">http://127.0.0.1:36165/status</a>\n",
        "                </td>\n",
        "                <td style=\"text-align: left;\">\n",
        "                    <strong>Workers:</strong> 7\n",
@@ -113,11 +112,11 @@
        "        <div style=\"width: 24px; height: 24px; background-color: #FFF7E5; border: 3px solid #FF6132; border-radius: 5px; position: absolute;\"> </div>\n",
        "        <div style=\"margin-left: 48px;\">\n",
        "            <h3 style=\"margin-bottom: 0px;\">Scheduler</h3>\n",
-       "            <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Scheduler-b98902c6-547b-4dac-94aa-28101a140d3c</p>\n",
+       "            <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Scheduler-0c40ef8b-2843-4971-9fcc-cda50fc11433</p>\n",
        "            <table style=\"width: 100%; text-align: left;\">\n",
        "                <tr>\n",
        "                    <td style=\"text-align: left;\">\n",
-       "                        <strong>Comm:</strong> tcp://127.0.0.1:35579\n",
+       "                        <strong>Comm:</strong> tcp://127.0.0.1:44181\n",
        "                    </td>\n",
        "                    <td style=\"text-align: left;\">\n",
        "                        <strong>Workers:</strong> 7\n",
@@ -125,7 +124,7 @@
        "                </tr>\n",
        "                <tr>\n",
        "                    <td style=\"text-align: left;\">\n",
-       "                        <strong>Dashboard:</strong> <a href=\"http://127.0.0.1:8787/status\" target=\"_blank\">http://127.0.0.1:8787/status</a>\n",
+       "                        <strong>Dashboard:</strong> <a href=\"http://127.0.0.1:36165/status\" target=\"_blank\">http://127.0.0.1:36165/status</a>\n",
        "                    </td>\n",
        "                    <td style=\"text-align: left;\">\n",
        "                        <strong>Total threads:</strong> 7\n",
@@ -159,7 +158,7 @@
        "                <table style=\"width: 100%; text-align: left;\">\n",
        "                    <tr>\n",
        "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Comm: </strong> tcp://127.0.0.1:45001\n",
+       "                            <strong>Comm: </strong> tcp://127.0.0.1:39149\n",
        "                        </td>\n",
        "                        <td style=\"text-align: left;\">\n",
        "                            <strong>Total threads: </strong> 1\n",
@@ -167,7 +166,7 @@
        "                    </tr>\n",
        "                    <tr>\n",
        "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:44295/status\" target=\"_blank\">http://127.0.0.1:44295/status</a>\n",
+       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:42227/status\" target=\"_blank\">http://127.0.0.1:42227/status</a>\n",
        "                        </td>\n",
        "                        <td style=\"text-align: left;\">\n",
        "                            <strong>Memory: </strong> 4.57 GiB\n",
@@ -175,13 +174,13 @@
        "                    </tr>\n",
        "                    <tr>\n",
        "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Nanny: </strong> tcp://127.0.0.1:44103\n",
+       "                            <strong>Nanny: </strong> tcp://127.0.0.1:41021\n",
        "                        </td>\n",
        "                        <td style=\"text-align: left;\"></td>\n",
        "                    </tr>\n",
        "                    <tr>\n",
        "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
-       "                            <strong>Local directory: </strong> /jobfs/132253303.gadi-pbs/dask-scratch-space/worker-7l4otz4l\n",
+       "                            <strong>Local directory: </strong> /jobfs/132563736.gadi-pbs/dask-scratch-space/worker-rtapgw5w\n",
        "                        </td>\n",
        "                    </tr>\n",
        "\n",
@@ -204,7 +203,7 @@
        "                <table style=\"width: 100%; text-align: left;\">\n",
        "                    <tr>\n",
        "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Comm: </strong> tcp://127.0.0.1:44011\n",
+       "                            <strong>Comm: </strong> tcp://127.0.0.1:44915\n",
        "                        </td>\n",
        "                        <td style=\"text-align: left;\">\n",
        "                            <strong>Total threads: </strong> 1\n",
@@ -212,7 +211,7 @@
        "                    </tr>\n",
        "                    <tr>\n",
        "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:41055/status\" target=\"_blank\">http://127.0.0.1:41055/status</a>\n",
+       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:38931/status\" target=\"_blank\">http://127.0.0.1:38931/status</a>\n",
        "                        </td>\n",
        "                        <td style=\"text-align: left;\">\n",
        "                            <strong>Memory: </strong> 4.57 GiB\n",
@@ -220,13 +219,13 @@
        "                    </tr>\n",
        "                    <tr>\n",
        "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Nanny: </strong> tcp://127.0.0.1:44545\n",
+       "                            <strong>Nanny: </strong> tcp://127.0.0.1:33733\n",
        "                        </td>\n",
        "                        <td style=\"text-align: left;\"></td>\n",
        "                    </tr>\n",
        "                    <tr>\n",
        "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
-       "                            <strong>Local directory: </strong> /jobfs/132253303.gadi-pbs/dask-scratch-space/worker-hrjqe8np\n",
+       "                            <strong>Local directory: </strong> /jobfs/132563736.gadi-pbs/dask-scratch-space/worker-wfl_hdvk\n",
        "                        </td>\n",
        "                    </tr>\n",
        "\n",
@@ -249,7 +248,7 @@
        "                <table style=\"width: 100%; text-align: left;\">\n",
        "                    <tr>\n",
        "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Comm: </strong> tcp://127.0.0.1:33481\n",
+       "                            <strong>Comm: </strong> tcp://127.0.0.1:38925\n",
        "                        </td>\n",
        "                        <td style=\"text-align: left;\">\n",
        "                            <strong>Total threads: </strong> 1\n",
@@ -257,7 +256,7 @@
        "                    </tr>\n",
        "                    <tr>\n",
        "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:43611/status\" target=\"_blank\">http://127.0.0.1:43611/status</a>\n",
+       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:41215/status\" target=\"_blank\">http://127.0.0.1:41215/status</a>\n",
        "                        </td>\n",
        "                        <td style=\"text-align: left;\">\n",
        "                            <strong>Memory: </strong> 4.57 GiB\n",
@@ -265,13 +264,13 @@
        "                    </tr>\n",
        "                    <tr>\n",
        "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Nanny: </strong> tcp://127.0.0.1:38207\n",
+       "                            <strong>Nanny: </strong> tcp://127.0.0.1:41537\n",
        "                        </td>\n",
        "                        <td style=\"text-align: left;\"></td>\n",
        "                    </tr>\n",
        "                    <tr>\n",
        "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
-       "                            <strong>Local directory: </strong> /jobfs/132253303.gadi-pbs/dask-scratch-space/worker-_v0grs05\n",
+       "                            <strong>Local directory: </strong> /jobfs/132563736.gadi-pbs/dask-scratch-space/worker-kjudhd0l\n",
        "                        </td>\n",
        "                    </tr>\n",
        "\n",
@@ -294,7 +293,7 @@
        "                <table style=\"width: 100%; text-align: left;\">\n",
        "                    <tr>\n",
        "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Comm: </strong> tcp://127.0.0.1:38391\n",
+       "                            <strong>Comm: </strong> tcp://127.0.0.1:34667\n",
        "                        </td>\n",
        "                        <td style=\"text-align: left;\">\n",
        "                            <strong>Total threads: </strong> 1\n",
@@ -302,7 +301,7 @@
        "                    </tr>\n",
        "                    <tr>\n",
        "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:43375/status\" target=\"_blank\">http://127.0.0.1:43375/status</a>\n",
+       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:44237/status\" target=\"_blank\">http://127.0.0.1:44237/status</a>\n",
        "                        </td>\n",
        "                        <td style=\"text-align: left;\">\n",
        "                            <strong>Memory: </strong> 4.57 GiB\n",
@@ -310,13 +309,13 @@
        "                    </tr>\n",
        "                    <tr>\n",
        "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Nanny: </strong> tcp://127.0.0.1:42323\n",
+       "                            <strong>Nanny: </strong> tcp://127.0.0.1:43925\n",
        "                        </td>\n",
        "                        <td style=\"text-align: left;\"></td>\n",
        "                    </tr>\n",
        "                    <tr>\n",
        "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
-       "                            <strong>Local directory: </strong> /jobfs/132253303.gadi-pbs/dask-scratch-space/worker-q8vviqis\n",
+       "                            <strong>Local directory: </strong> /jobfs/132563736.gadi-pbs/dask-scratch-space/worker-vpxh59oz\n",
        "                        </td>\n",
        "                    </tr>\n",
        "\n",
@@ -339,7 +338,7 @@
        "                <table style=\"width: 100%; text-align: left;\">\n",
        "                    <tr>\n",
        "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Comm: </strong> tcp://127.0.0.1:45719\n",
+       "                            <strong>Comm: </strong> tcp://127.0.0.1:36523\n",
        "                        </td>\n",
        "                        <td style=\"text-align: left;\">\n",
        "                            <strong>Total threads: </strong> 1\n",
@@ -347,7 +346,7 @@
        "                    </tr>\n",
        "                    <tr>\n",
        "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:36917/status\" target=\"_blank\">http://127.0.0.1:36917/status</a>\n",
+       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:42299/status\" target=\"_blank\">http://127.0.0.1:42299/status</a>\n",
        "                        </td>\n",
        "                        <td style=\"text-align: left;\">\n",
        "                            <strong>Memory: </strong> 4.57 GiB\n",
@@ -355,13 +354,13 @@
        "                    </tr>\n",
        "                    <tr>\n",
        "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Nanny: </strong> tcp://127.0.0.1:46155\n",
+       "                            <strong>Nanny: </strong> tcp://127.0.0.1:46839\n",
        "                        </td>\n",
        "                        <td style=\"text-align: left;\"></td>\n",
        "                    </tr>\n",
        "                    <tr>\n",
        "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
-       "                            <strong>Local directory: </strong> /jobfs/132253303.gadi-pbs/dask-scratch-space/worker-p19shwu2\n",
+       "                            <strong>Local directory: </strong> /jobfs/132563736.gadi-pbs/dask-scratch-space/worker-bhjnq7mf\n",
        "                        </td>\n",
        "                    </tr>\n",
        "\n",
@@ -384,7 +383,7 @@
        "                <table style=\"width: 100%; text-align: left;\">\n",
        "                    <tr>\n",
        "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Comm: </strong> tcp://127.0.0.1:35585\n",
+       "                            <strong>Comm: </strong> tcp://127.0.0.1:34583\n",
        "                        </td>\n",
        "                        <td style=\"text-align: left;\">\n",
        "                            <strong>Total threads: </strong> 1\n",
@@ -392,7 +391,7 @@
        "                    </tr>\n",
        "                    <tr>\n",
        "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:33031/status\" target=\"_blank\">http://127.0.0.1:33031/status</a>\n",
+       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:39185/status\" target=\"_blank\">http://127.0.0.1:39185/status</a>\n",
        "                        </td>\n",
        "                        <td style=\"text-align: left;\">\n",
        "                            <strong>Memory: </strong> 4.57 GiB\n",
@@ -400,13 +399,13 @@
        "                    </tr>\n",
        "                    <tr>\n",
        "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Nanny: </strong> tcp://127.0.0.1:43339\n",
+       "                            <strong>Nanny: </strong> tcp://127.0.0.1:44951\n",
        "                        </td>\n",
        "                        <td style=\"text-align: left;\"></td>\n",
        "                    </tr>\n",
        "                    <tr>\n",
        "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
-       "                            <strong>Local directory: </strong> /jobfs/132253303.gadi-pbs/dask-scratch-space/worker-0flhszy7\n",
+       "                            <strong>Local directory: </strong> /jobfs/132563736.gadi-pbs/dask-scratch-space/worker-zpzse13n\n",
        "                        </td>\n",
        "                    </tr>\n",
        "\n",
@@ -429,7 +428,7 @@
        "                <table style=\"width: 100%; text-align: left;\">\n",
        "                    <tr>\n",
        "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Comm: </strong> tcp://127.0.0.1:39715\n",
+       "                            <strong>Comm: </strong> tcp://127.0.0.1:37101\n",
        "                        </td>\n",
        "                        <td style=\"text-align: left;\">\n",
        "                            <strong>Total threads: </strong> 1\n",
@@ -437,7 +436,7 @@
        "                    </tr>\n",
        "                    <tr>\n",
        "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:41109/status\" target=\"_blank\">http://127.0.0.1:41109/status</a>\n",
+       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:34173/status\" target=\"_blank\">http://127.0.0.1:34173/status</a>\n",
        "                        </td>\n",
        "                        <td style=\"text-align: left;\">\n",
        "                            <strong>Memory: </strong> 4.57 GiB\n",
@@ -445,13 +444,13 @@
        "                    </tr>\n",
        "                    <tr>\n",
        "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Nanny: </strong> tcp://127.0.0.1:46827\n",
+       "                            <strong>Nanny: </strong> tcp://127.0.0.1:45001\n",
        "                        </td>\n",
        "                        <td style=\"text-align: left;\"></td>\n",
        "                    </tr>\n",
        "                    <tr>\n",
        "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
-       "                            <strong>Local directory: </strong> /jobfs/132253303.gadi-pbs/dask-scratch-space/worker-db6x7lpk\n",
+       "                            <strong>Local directory: </strong> /jobfs/132563736.gadi-pbs/dask-scratch-space/worker-_txsdv3w\n",
        "                        </td>\n",
        "                    </tr>\n",
        "\n",
@@ -478,7 +477,7 @@
        "</div>"
       ],
       "text/plain": [
-       "<Client: 'tcp://127.0.0.1:35579' processes=7 threads=7, memory=32.00 GiB>"
+       "<Client: 'tcp://127.0.0.1:44181' processes=7 threads=7, memory=32.00 GiB>"
       ]
      },
      "execution_count": 1,
@@ -512,7 +511,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "expt_name = \"rotated-demo\"\n",
+    "expt_name = \"rotated-demo5\"\n",
     "\n",
     "#latitude_extent = [16., 27]\n",
     "#longitude_extent = [192, 209] #fill will nones and test these are optional so remove\n",
@@ -651,16 +650,23 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "script `get_glorys_data.sh` has been created at /g/data/tm70/hm6113/glorys/rotated-demo5.\n",
-      " Run this script via bash to download the data from a terminal with internet access. \n",
-      "You will need to enter your Copernicus Marine username and password.\n",
-      "If you don't have an account, make one here:\n",
-      "https://data.marine.copernicus.eu/register\n"
+      "The script `get_glorys_data.sh` has been generated at:\n",
+      "  /g/data/tm70/hm6113/glorys/rotated-demo5.\n",
+      "To download the data, run this script using `bash` in a terminal with internet access.\n",
+      "\n",
+      "Important instructions:\n",
+      "1. You will need your Copernicus Marine username and password.\n",
+      "   If you do not have an account, you can create one here: \n",
+      "   https://data.marine.copernicus.eu/register\n",
+      "2. You will be prompted to enter your Copernicus Marine credentials multiple times: once for each dataset.\n",
+      "3. Depending on the dataset size, the download process may take significant time and resources.\n",
+      "4. Thus, on certain systems, you may need to run this script as a batch job.\n",
+      "\n"
      ]
     }
    ],
    "source": [
-    "expt.get_glorys_rectangular(\n",
+    "expt.get_glorys(\n",
     "    raw_boundaries_path=glorys_path\n",
     ")"
    ]
@@ -695,7 +701,7 @@
       "\n",
       "For details see https://xesmf.readthedocs.io/en/latest/large_problems_on_HPC.html\n",
       "\n",
-      "Afterwards, run the 'expt.tidy_bathymetry' method to skip the expensive interpolation step, and finishing metadata, encoding and cleanup.\n",
+      "Afterwards, we run the 'expt.tidy_bathymetry' method to skip the expensive interpolation step, and finishing metadata, encoding and cleanup.\n",
       "\n",
       "\n",
       "\n",
@@ -703,6 +709,442 @@
       "Tidy bathymetry: Reading in regridded bathymetry to fix up metadata...done. Filling in inland lakes and channels... done.\n",
       "setup bathymetry has finished successfully.\n"
      ]
+    },
+    {
+     "data": {
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+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
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+       "  --xr-background-color: var(--jp-layout-color0, white);\n",
+       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
+       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
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+       "\n",
+       "html[theme=dark],\n",
+       "body[data-theme=dark],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
+       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
+       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
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+       "  --xr-disabled-color: #515151;\n",
+       "  --xr-background-color: #111111;\n",
+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
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+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
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+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
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+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
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+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: '►';\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
+       "Dimensions:  (ny: 49, nx: 49)\n",
+       "Coordinates:\n",
+       "    lat      (ny, nx) float64 55.67 55.67 55.68 55.68 ... 58.31 58.32 58.32\n",
+       "    lon      (ny, nx) float64 -41.52 -41.43 -41.34 ... -37.72 -37.63 -37.53\n",
+       "Dimensions without coordinates: ny, nx\n",
+       "Data variables:\n",
+       "    depth    (ny, nx) float64 3.16e+03 3.271e+03 ... 3.192e+03 3.195e+03\n",
+       "Attributes:\n",
+       "    regrid_method:  bilinear\n",
+       "    depth:          meters\n",
+       "    standard_name:  bathymetric depth at T-cell centers\n",
+       "    coordinates:    zi</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-7fafad43-c9f1-4823-80b1-5f15193c4d1c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7fafad43-c9f1-4823-80b1-5f15193c4d1c' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>ny</span>: 49</li><li><span>nx</span>: 49</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-e0a4a8f9-199c-41da-8ab8-de47763b53ac' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e0a4a8f9-199c-41da-8ab8-de47763b53ac' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(ny, nx)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>55.67 55.67 55.68 ... 58.32 58.32</div><input id='attrs-c84a2b6d-a9af-40e2-bed2-fcb91af0ba0c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c84a2b6d-a9af-40e2-bed2-fcb91af0ba0c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-362289ac-bf3b-41fe-b9e9-88a1964a2064' class='xr-var-data-in' type='checkbox'><label for='data-362289ac-bf3b-41fe-b9e9-88a1964a2064' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>_FillValue :</span></dt><dd>1e+20</dd></dl></div><div class='xr-var-data'><pre>array([[55.6690997 , 55.67328048, 55.67743919, ..., 55.83789644,\n",
+       "        55.84101611, 55.84411171],\n",
+       "       [55.72089853, 55.72509551, 55.72927036, ..., 55.89036387,\n",
+       "        55.89349627, 55.89660452],\n",
+       "       [55.77265672, 55.77686994, 55.78106095, ..., 55.94279202,\n",
+       "        55.94593718, 55.94905812],\n",
+       "       ...,\n",
+       "       [58.0107782 , 58.01573698, 58.02067038, ..., 58.21178447,\n",
+       "        58.21552027, 58.21922829],\n",
+       "       [58.06077514, 58.0657516 , 58.0707026 , ..., 58.26251586,\n",
+       "        58.26626577, 58.26998782],\n",
+       "       [58.11073443, 58.1157286 , 58.12069724, ..., 58.31321112,\n",
+       "        58.31697517, 58.32071128]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(ny, nx)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-41.52 -41.43 ... -37.63 -37.53</div><input id='attrs-aecaa246-8ac7-4cd4-83d8-89a5e4375a4c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aecaa246-8ac7-4cd4-83d8-89a5e4375a4c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b6a83b4-1550-4b1f-afc6-fd533e8ea768' class='xr-var-data-in' type='checkbox'><label for='data-5b6a83b4-1550-4b1f-afc6-fd533e8ea768' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>_FillValue :</span></dt><dd>1e+20</dd></dl></div><div class='xr-var-data'><pre>array([[-41.52154418, -41.43233012, -41.34309817, ..., -37.40009819,\n",
+       "        -37.3101249 , -37.22013666],\n",
+       "       [-41.52922026, -41.43996836, -41.35069844, ..., -37.40590856,\n",
+       "        -37.31589203, -37.22586044],\n",
+       "       [-41.53693718, -41.44764726, -41.3583392 , ..., -37.4117512 ,\n",
+       "        -37.32169123, -37.23161609],\n",
+       "       ...,\n",
+       "       [-41.91968483, -41.82854577, -41.7373822 , ..., -37.70314762,\n",
+       "        -37.61096659, -37.51876501],\n",
+       "       [-41.92943237, -41.8382471 , -41.74703715, ..., -37.71060748,\n",
+       "        -37.61837324, -37.5261183 ],\n",
+       "       [-41.93922967, -41.84799799, -41.75674147, ..., -37.71810726,\n",
+       "        -37.62581957, -37.53351105]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1e4d5e64-f861-434d-818d-d9940041adbd' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1e4d5e64-f861-434d-818d-d9940041adbd' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>depth</span></div><div class='xr-var-dims'>(ny, nx)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.16e+03 3.271e+03 ... 3.195e+03</div><input id='attrs-1ec7dd58-c12c-47b3-a25f-c6611693fc32' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1ec7dd58-c12c-47b3-a25f-c6611693fc32' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cba4f3be-15f6-475d-8351-2f1afeec5722' class='xr-var-data-in' type='checkbox'><label for='data-cba4f3be-15f6-475d-8351-2f1afeec5722' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[3160.36657358, 3270.61654519, 3266.93203466, ..., 2597.47483393,\n",
+       "        2618.89837899, 2591.9801311 ],\n",
+       "       [3172.34092229, 3241.2481837 , 3233.95678481, ..., 2670.31937566,\n",
+       "        2651.44231632, 2687.01991238],\n",
+       "       [3226.00061779, 3200.45005269, 3265.77030518, ..., 2728.03887684,\n",
+       "        2616.99505535, 2771.49403649],\n",
+       "       ...,\n",
+       "       [3179.05082962, 3186.33035899, 3174.51301978, ..., 3194.        ,\n",
+       "        3197.57995344, 3190.77000804],\n",
+       "       [3162.4707476 , 3165.        , 3168.7553868 , ..., 3203.03091696,\n",
+       "        3199.33676776, 3200.73145629],\n",
+       "       [3154.05598178, 3145.57785207, 3144.59549248, ..., 3193.67066656,\n",
+       "        3192.4708743 , 3195.        ]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8c552900-a6f0-4b73-8cc5-cd5853f8cfb7' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-8c552900-a6f0-4b73-8cc5-cd5853f8cfb7' class='xr-section-summary'  title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-2c9a7535-1e8e-4f60-8767-7f0db47da100' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2c9a7535-1e8e-4f60-8767-7f0db47da100' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>regrid_method :</span></dt><dd>bilinear</dd><dt><span>depth :</span></dt><dd>meters</dd><dt><span>standard_name :</span></dt><dd>bathymetric depth at T-cell centers</dd><dt><span>coordinates :</span></dt><dd>zi</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset>\n",
+       "Dimensions:  (ny: 49, nx: 49)\n",
+       "Coordinates:\n",
+       "    lat      (ny, nx) float64 55.67 55.67 55.68 55.68 ... 58.31 58.32 58.32\n",
+       "    lon      (ny, nx) float64 -41.52 -41.43 -41.34 ... -37.72 -37.63 -37.53\n",
+       "Dimensions without coordinates: ny, nx\n",
+       "Data variables:\n",
+       "    depth    (ny, nx) float64 3.16e+03 3.271e+03 ... 3.192e+03 3.195e+03\n",
+       "Attributes:\n",
+       "    regrid_method:  bilinear\n",
+       "    depth:          meters\n",
+       "    standard_name:  bathymetric depth at T-cell centers\n",
+       "    coordinates:    zi"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
@@ -737,7 +1179,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.collections.QuadMesh at 0x15009ed04f50>"
+       "<matplotlib.collections.QuadMesh at 0x1500729805d0>"
       ]
      },
      "execution_count": 7,
@@ -773,7 +1215,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.collections.QuadMesh at 0x15009ea86fd0>"
+       "<matplotlib.collections.QuadMesh at 0x15006a8163d0>"
       ]
      },
      "execution_count": 8,
@@ -820,15 +1262,58 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "INITIAL CONDITIONS\n",
+      "Setting up Initial Conditions\n",
       "Regridding Velocities... Done.\n",
       "Regridding Tracers... Done.\n",
       "Regridding Free surface... Done.\n",
       "Saving outputs... done setting up initial condition.\n",
-      "Processing north boundary...Done.\n",
-      "Processing south boundary...Done.\n",
-      "Processing east boundary...Done.\n",
-      "Processing west boundary...Done.\n"
+      "Processing north boundary velocity & tracers..."
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
+      "All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Done.\n",
+      "Processing south boundary velocity & tracers..."
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Done.\n",
+      "Processing east boundary velocity & tracers..."
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Done.\n",
+      "Processing west boundary velocity & tracers...Done.\n"
      ]
     }
    ],
@@ -868,7 +1353,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -877,7 +1362,7 @@
        "Text(0.5, 1.0, 'lon/lat coords')"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -908,22 +1393,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.collections.QuadMesh at 0x15009ca36390>"
+       "<matplotlib.collections.QuadMesh at 0x15006a3ce310>"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -942,148 +1427,94 @@
    "metadata": {},
    "source": [
     "### Step 6: Create Tidal forcing\n",
-    "You may need to change \"tpxo10.v2.nc\" to reflect your version"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 56,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "#THIS ONE WORKS FOR MAIN\n",
-    "#NOTE \"rectangle\" is the only option\n",
-    "#expt.setup_boundary_tides(\n",
-    "#        Path(\"/g/data/tm70/hm6113/tides/DATA\"),\"tpxo10.v2.nc\",\n",
-    "#        tidal_constituents=[\"M2\"],\n",
-    "#        boundary_type=\"rectangle\"\n",
-    "#)"
+    "For rectangluar domains (boundaries are aligned with lats and longs) you can use :\n",
+    "boundary_type=\"rectangular\"\n",
+    "\n",
+    "Note that this step can take a while (5 mins +). "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 57,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Processing north boundary...2025-01-10 14:36:52,454 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
-      "2025-01-10 14:36:52,458 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
-      "2025-01-10 14:37:13,744 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:37:13,747 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:37:13,756 - regional_mom6.regridding.add_or_update_time_dim - INFO - Adding time dimension\n",
-      "2025-01-10 14:37:13,760 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
-      "2025-01-10 14:37:13,762 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to zamp_segment_001\n",
-      "2025-01-10 14:37:13,765 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to zphase_segment_001\n",
-      "2025-01-10 14:37:13,767 - regional_mom6.regridding.mask_dataset - WARNING - All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
-      "2025-01-10 14:37:13,768 - regional_mom6.regridding.generate_encoding - INFO - Generating encoding dictionary\n",
-      "2025-01-10 14:37:13,861 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
-      "2025-01-10 14:37:35,116 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
-      "2025-01-10 14:37:56,654 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:37:56,655 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:37:56,657 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:37:56,659 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:37:56,675 - regional_mom6.regridding.add_or_update_time_dim - INFO - Adding time dimension\n",
-      "2025-01-10 14:37:56,680 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:37:56,684 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
-      "2025-01-10 14:37:56,687 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to uamp_segment_001\n",
-      "2025-01-10 14:37:56,688 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to vamp_segment_001\n",
-      "2025-01-10 14:37:56,690 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to uphase_segment_001\n",
-      "2025-01-10 14:37:56,692 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to vphase_segment_001\n",
-      "2025-01-10 14:37:56,694 - regional_mom6.regridding.mask_dataset - WARNING - All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
-      "2025-01-10 14:37:56,695 - regional_mom6.regridding.generate_encoding - INFO - Generating encoding dictionary\n",
+      "Processing north boundary..."
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
+      "All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
       "Done\n",
-      "Processing south boundary...2025-01-10 14:37:56,755 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
-      "2025-01-10 14:37:56,757 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
-      "2025-01-10 14:38:17,931 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:38:17,934 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:38:17,939 - regional_mom6.regridding.add_or_update_time_dim - INFO - Adding time dimension\n",
-      "2025-01-10 14:38:17,944 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
-      "2025-01-10 14:38:17,946 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to zamp_segment_002\n",
-      "2025-01-10 14:38:17,948 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to zphase_segment_002\n",
-      "2025-01-10 14:38:17,950 - regional_mom6.regridding.mask_dataset - WARNING - All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
-      "2025-01-10 14:38:17,952 - regional_mom6.regridding.generate_encoding - INFO - Generating encoding dictionary\n",
-      "2025-01-10 14:38:17,982 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
-      "2025-01-10 14:38:39,684 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
-      "2025-01-10 14:39:01,135 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:39:01,136 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:39:01,137 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:39:01,139 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:39:01,152 - regional_mom6.regridding.add_or_update_time_dim - INFO - Adding time dimension\n",
-      "2025-01-10 14:39:01,155 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:39:01,159 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
-      "2025-01-10 14:39:01,161 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to uamp_segment_002\n",
-      "2025-01-10 14:39:01,163 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to vamp_segment_002\n",
-      "2025-01-10 14:39:01,165 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to uphase_segment_002\n",
-      "2025-01-10 14:39:01,167 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to vphase_segment_002\n",
-      "2025-01-10 14:39:01,168 - regional_mom6.regridding.mask_dataset - WARNING - All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
-      "2025-01-10 14:39:01,170 - regional_mom6.regridding.generate_encoding - INFO - Generating encoding dictionary\n",
+      "Processing south boundary..."
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
+      "All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
       "Done\n",
-      "Processing east boundary...2025-01-10 14:39:01,241 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
-      "2025-01-10 14:39:01,243 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
-      "2025-01-10 14:39:22,804 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:39:22,806 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:39:22,811 - regional_mom6.regridding.add_or_update_time_dim - INFO - Adding time dimension\n",
-      "2025-01-10 14:39:22,815 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
-      "2025-01-10 14:39:22,817 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to zamp_segment_003\n",
-      "2025-01-10 14:39:22,820 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to zphase_segment_003\n",
-      "2025-01-10 14:39:22,822 - regional_mom6.regridding.mask_dataset - WARNING - All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
-      "2025-01-10 14:39:22,823 - regional_mom6.regridding.generate_encoding - INFO - Generating encoding dictionary\n",
-      "2025-01-10 14:39:22,850 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
-      "2025-01-10 14:39:43,725 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
-      "2025-01-10 14:40:04,730 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:40:04,733 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:40:04,738 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:40:04,740 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:40:04,756 - regional_mom6.regridding.add_or_update_time_dim - INFO - Adding time dimension\n",
-      "2025-01-10 14:40:04,760 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:40:04,765 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
-      "2025-01-10 14:40:04,768 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to uamp_segment_003\n",
-      "2025-01-10 14:40:04,770 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to vamp_segment_003\n",
-      "2025-01-10 14:40:04,772 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to uphase_segment_003\n",
-      "2025-01-10 14:40:04,775 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to vphase_segment_003\n",
-      "2025-01-10 14:40:04,776 - regional_mom6.regridding.mask_dataset - WARNING - All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
-      "2025-01-10 14:40:04,778 - regional_mom6.regridding.generate_encoding - INFO - Generating encoding dictionary\n",
+      "Processing east boundary..."
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
+      "All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
       "Done\n",
-      "Processing west boundary...2025-01-10 14:40:04,815 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
-      "2025-01-10 14:40:04,817 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
-      "2025-01-10 14:40:25,799 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:40:25,801 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:40:25,806 - regional_mom6.regridding.add_or_update_time_dim - INFO - Adding time dimension\n",
-      "2025-01-10 14:40:25,810 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
-      "2025-01-10 14:40:25,813 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to zamp_segment_004\n",
-      "2025-01-10 14:40:25,816 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to zphase_segment_004\n",
-      "2025-01-10 14:40:25,818 - regional_mom6.regridding.mask_dataset - WARNING - All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
-      "2025-01-10 14:40:25,820 - regional_mom6.regridding.generate_encoding - INFO - Generating encoding dictionary\n",
-      "2025-01-10 14:40:25,850 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
-      "2025-01-10 14:40:47,150 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
-      "2025-01-10 14:41:07,908 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:41:07,910 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:41:07,911 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:41:07,912 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:41:07,923 - regional_mom6.regridding.add_or_update_time_dim - INFO - Adding time dimension\n",
-      "2025-01-10 14:41:07,928 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:41:07,932 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
-      "2025-01-10 14:41:07,934 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to uamp_segment_004\n",
-      "2025-01-10 14:41:07,936 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to vamp_segment_004\n",
-      "2025-01-10 14:41:07,937 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to uphase_segment_004\n",
-      "2025-01-10 14:41:07,938 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to vphase_segment_004\n",
-      "2025-01-10 14:41:07,941 - regional_mom6.regridding.mask_dataset - WARNING - All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
-      "2025-01-10 14:41:07,943 - regional_mom6.regridding.generate_encoding - INFO - Generating encoding dictionary\n",
+      "Processing west boundary..."
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
+      "All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
       "Done\n"
      ]
     }
    ],
    "source": [
-    "#THIS ONE WORKS FOR tides_regridding_branch\n",
-    "##NOTE THAT THE FILES ARE PLACED in forcing folder but input files seek them from the higher level directory.\n",
     "expt.setup_boundary_tides(\n",
     "        tide_h_path,\n",
     "        tide_u_path,\n",
     "        tidal_constituents=[\"M2\"],\n",
-    "        boundary_type=\"rectangle\"\n",
+    "        boundary_type=\"curvilinear\"\n",
     ")"
    ]
   },
@@ -1111,7 +1542,21 @@
       "congratulation: You have successfully run make_solo_mosaic\n",
       "OUTPUT FROM MAKE SOLO MOSAIC:\n",
       "\n",
-      "CompletedProcess(args='/g/data/tm70/hm6113/repo/FRE-NCtools/make_solo_mosaic/make_solo_mosaic --num_tiles 1 --dir . --mosaic_name ocean_mosaic --tile_file hgrid.nc', returncode=0)\n",
+      "CompletedProcess(args='/g/data/tm70/hm6113/repo/FRE-NCtools/make_solo_mosaic/make_solo_mosaic --num_tiles 1 --dir . --mosaic_name ocean_mosaic --tile_file hgrid.nc', returncode=0)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "cp: './ocean_mosaic.nc' and 'ocean_mosaic.nc' are the same file\n",
+      "cp: './hgrid.nc' and 'hgrid.nc' are the same file\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
       "cp ./hgrid.nc hgrid.nc \n",
       "\n",
       "NOTE from make_coupler_mosaic: the ocean land/sea mask will be determined by field depth from file bathymetry.nc\n",
@@ -1154,14 +1599,6 @@
       "\n",
       " CompletedProcess(args='/g/data/tm70/hm6113/repo/FRE-NCtools/check_mask/check_mask --grid_file ocean_mosaic.nc --ocean_topog bathymetry.nc --layout 10,10 --halo 4', returncode=0)\n"
      ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "cp: './ocean_mosaic.nc' and 'ocean_mosaic.nc' are the same file\n",
-      "cp: './hgrid.nc' and 'hgrid.nc' are the same file\n"
-     ]
     }
    ],
    "source": [
@@ -1219,19 +1656,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Could not find premade run directories at  /scratch/tm70/hm6113/code/rm6_helen_dev/regional-mom6/regional_mom6/demos/premade_run_directories\n",
-      "Perhaps the package was imported directly rather than installed with conda. Checking if this is the case... \n",
-      "Found run files. Continuing...\n",
+      "Could not find premade run directories at  /scratch/tm70/hm6113/code/rm6_helen_update/regional-mom6/regional_mom6/demos/premade_run_directories\n",
+      "Perhaps the package was imported directly rather than installed with conda. Checking if this is the case... Found run files. Continuing...\n",
       "No mask table found, but the cpu layout has been set to (10, 10) This suggests the domain is mostly water, so there are no `non compute` cells that are entirely land. If this doesn't seem right, ensure you've already run the `FRE_tools` method which sets up the cpu mask table. Keep an eye on any errors that might print whilethe FRE tools (which run C++ in the background) are running.\n",
       "Number of CPUs required:  100\n",
-      "Deleting indexed OBC keys from MOM_input_dict in case we have a different number of segments\n"
+      "Deleting indexed OBC keys from MOM_input_dict in case we have a different number of segments\n",
+      "Changed OBC_TIDE_REF_DATE from 2020, 1, 1 to 2020, 01, 01in MOM_override!\n"
      ]
     }
    ],
diff --git a/demos/reanalysis-forced.ipynb b/demos/reanalysis-forced.ipynb
index eb2555ba..8a3b3deb 100644
--- a/demos/reanalysis-forced.ipynb
+++ b/demos/reanalysis-forced.ipynb
@@ -122,6 +122,11 @@
     "## Path to where your raw ocean forcing files are stored\n",
     "glorys_path = Path(\"PATH_TO_GLORYS_DATA\")\n",
     "\n",
+    "#Location of TPXO raw tidal file\n",
+    "#note that you will need to swap ## to the version number for each of the file names\n",
+    "tide_h_path = Path(\"PATH_TO_TPXO_H_FILE/h_tpxo##.nc\")\n",
+    "tide_u_path = Path(\"PATH_TO_TPXO_U_FILE/u_tpxo##.nc\")\n",
+    "\n",
     "## if directories don't exist, create them\n",
     "for path in (run_dir, glorys_path, input_dir):\n",
     "    os.makedirs(str(path), exist_ok=True)"
@@ -465,7 +470,7 @@
     "        tide_h_path,\n",
     "        tide_u_path,\n",
     "        tidal_constituents=[\"M2\"],\n",
-    "        boundary_type=\"rectangle\"\n",
+    "        boundary_type=\"rectangular\"\n",
     ")"
    ]
   },
@@ -546,7 +551,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "expt.setup_run_directory(surface_forcing = \"era5\")"
+    "expt.setup_run_directory(surface_forcing = \"era5\", with_tides = True)"
    ]
   },
   {
@@ -574,7 +579,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "CrocoDash",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -588,7 +593,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.8"
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,

From 0c7c65de906a27b50be31b2e8c4839edb385d3a9 Mon Sep 17 00:00:00 2001
From: Helen Macdonald <helen.macdonald@anu.edu.au>
Date: Mon, 20 Jan 2025 16:21:17 +1100
Subject: [PATCH 6/8] changing the output directory of tidal .nc files to be
 consistent with path expected at run-time

---
 regional_mom6/regional_mom6.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/regional_mom6/regional_mom6.py b/regional_mom6/regional_mom6.py
index be58f410..0191fd79 100644
--- a/regional_mom6/regional_mom6.py
+++ b/regional_mom6/regional_mom6.py
@@ -3462,7 +3462,7 @@ def encode_tidal_files_and_output(self, ds, filename):
 
         ## Export Files ##
         ds.to_netcdf(
-            Path(self.outfolder / "forcing" / fname),
+            Path(self.outfolder  / fname),
             engine="netcdf4",
             encoding=encoding,
             unlimited_dims="time",

From 7f3e6335004389d347d70843d561ac6c4edadfde Mon Sep 17 00:00:00 2001
From: Helen Macdonald <helen.macdonald@anu.edu.au>
Date: Mon, 20 Jan 2025 16:32:34 +1100
Subject: [PATCH 7/8] cleaning up notebooks by making paths generic

---
 demos/BYO-domain.ipynb        | 1326 ++-------------------------------
 demos/reanalysis-forced.ipynb |  121 +--
 2 files changed, 49 insertions(+), 1398 deletions(-)

diff --git a/demos/BYO-domain.ipynb b/demos/BYO-domain.ipynb
index d125439f..aef92a4e 100644
--- a/demos/BYO-domain.ipynb
+++ b/demos/BYO-domain.ipynb
@@ -1,14 +1,5 @@
 {
  "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "TO DO\n",
-    "2)Double check that tidal input files are being created in the correct directory\n",
-    "3)make file path generic"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -34,457 +25,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "    <div style=\"width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;\"> </div>\n",
-       "    <div style=\"margin-left: 48px;\">\n",
-       "        <h3 style=\"margin-bottom: 0px;\">Client</h3>\n",
-       "        <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Client-52810be8-d6e7-11ef-8fbc-000007d8fe80</p>\n",
-       "        <table style=\"width: 100%; text-align: left;\">\n",
-       "\n",
-       "        <tr>\n",
-       "        \n",
-       "            <td style=\"text-align: left;\"><strong>Connection method:</strong> Cluster object</td>\n",
-       "            <td style=\"text-align: left;\"><strong>Cluster type:</strong> distributed.LocalCluster</td>\n",
-       "        \n",
-       "        </tr>\n",
-       "\n",
-       "        \n",
-       "            <tr>\n",
-       "                <td style=\"text-align: left;\">\n",
-       "                    <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:36165/status\" target=\"_blank\">http://127.0.0.1:36165/status</a>\n",
-       "                </td>\n",
-       "                <td style=\"text-align: left;\"></td>\n",
-       "            </tr>\n",
-       "        \n",
-       "\n",
-       "        </table>\n",
-       "\n",
-       "        \n",
-       "\n",
-       "        \n",
-       "            <details>\n",
-       "            <summary style=\"margin-bottom: 20px;\"><h3 style=\"display: inline;\">Cluster Info</h3></summary>\n",
-       "            <div class=\"jp-RenderedHTMLCommon jp-RenderedHTML jp-mod-trusted jp-OutputArea-output\">\n",
-       "    <div style=\"width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;\">\n",
-       "    </div>\n",
-       "    <div style=\"margin-left: 48px;\">\n",
-       "        <h3 style=\"margin-bottom: 0px; margin-top: 0px;\">LocalCluster</h3>\n",
-       "        <p style=\"color: #9D9D9D; margin-bottom: 0px;\">0933c645</p>\n",
-       "        <table style=\"width: 100%; text-align: left;\">\n",
-       "            <tr>\n",
-       "                <td style=\"text-align: left;\">\n",
-       "                    <strong>Dashboard:</strong> <a href=\"http://127.0.0.1:36165/status\" target=\"_blank\">http://127.0.0.1:36165/status</a>\n",
-       "                </td>\n",
-       "                <td style=\"text-align: left;\">\n",
-       "                    <strong>Workers:</strong> 7\n",
-       "                </td>\n",
-       "            </tr>\n",
-       "            <tr>\n",
-       "                <td style=\"text-align: left;\">\n",
-       "                    <strong>Total threads:</strong> 7\n",
-       "                </td>\n",
-       "                <td style=\"text-align: left;\">\n",
-       "                    <strong>Total memory:</strong> 32.00 GiB\n",
-       "                </td>\n",
-       "            </tr>\n",
-       "            \n",
-       "            <tr>\n",
-       "    <td style=\"text-align: left;\"><strong>Status:</strong> running</td>\n",
-       "    <td style=\"text-align: left;\"><strong>Using processes:</strong> True</td>\n",
-       "</tr>\n",
-       "\n",
-       "            \n",
-       "        </table>\n",
-       "\n",
-       "        <details>\n",
-       "            <summary style=\"margin-bottom: 20px;\">\n",
-       "                <h3 style=\"display: inline;\">Scheduler Info</h3>\n",
-       "            </summary>\n",
-       "\n",
-       "            <div style=\"\">\n",
-       "    <div>\n",
-       "        <div style=\"width: 24px; height: 24px; background-color: #FFF7E5; border: 3px solid #FF6132; border-radius: 5px; position: absolute;\"> </div>\n",
-       "        <div style=\"margin-left: 48px;\">\n",
-       "            <h3 style=\"margin-bottom: 0px;\">Scheduler</h3>\n",
-       "            <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Scheduler-0c40ef8b-2843-4971-9fcc-cda50fc11433</p>\n",
-       "            <table style=\"width: 100%; text-align: left;\">\n",
-       "                <tr>\n",
-       "                    <td style=\"text-align: left;\">\n",
-       "                        <strong>Comm:</strong> tcp://127.0.0.1:44181\n",
-       "                    </td>\n",
-       "                    <td style=\"text-align: left;\">\n",
-       "                        <strong>Workers:</strong> 7\n",
-       "                    </td>\n",
-       "                </tr>\n",
-       "                <tr>\n",
-       "                    <td style=\"text-align: left;\">\n",
-       "                        <strong>Dashboard:</strong> <a href=\"http://127.0.0.1:36165/status\" target=\"_blank\">http://127.0.0.1:36165/status</a>\n",
-       "                    </td>\n",
-       "                    <td style=\"text-align: left;\">\n",
-       "                        <strong>Total threads:</strong> 7\n",
-       "                    </td>\n",
-       "                </tr>\n",
-       "                <tr>\n",
-       "                    <td style=\"text-align: left;\">\n",
-       "                        <strong>Started:</strong> Just now\n",
-       "                    </td>\n",
-       "                    <td style=\"text-align: left;\">\n",
-       "                        <strong>Total memory:</strong> 32.00 GiB\n",
-       "                    </td>\n",
-       "                </tr>\n",
-       "            </table>\n",
-       "        </div>\n",
-       "    </div>\n",
-       "\n",
-       "    <details style=\"margin-left: 48px;\">\n",
-       "        <summary style=\"margin-bottom: 20px;\">\n",
-       "            <h3 style=\"display: inline;\">Workers</h3>\n",
-       "        </summary>\n",
-       "\n",
-       "        \n",
-       "        <div style=\"margin-bottom: 20px;\">\n",
-       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
-       "            <div style=\"margin-left: 48px;\">\n",
-       "            <details>\n",
-       "                <summary>\n",
-       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 0</h4>\n",
-       "                </summary>\n",
-       "                <table style=\"width: 100%; text-align: left;\">\n",
-       "                    <tr>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Comm: </strong> tcp://127.0.0.1:39149\n",
-       "                        </td>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Total threads: </strong> 1\n",
-       "                        </td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:42227/status\" target=\"_blank\">http://127.0.0.1:42227/status</a>\n",
-       "                        </td>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Memory: </strong> 4.57 GiB\n",
-       "                        </td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Nanny: </strong> tcp://127.0.0.1:41021\n",
-       "                        </td>\n",
-       "                        <td style=\"text-align: left;\"></td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
-       "                            <strong>Local directory: </strong> /jobfs/132563736.gadi-pbs/dask-scratch-space/worker-rtapgw5w\n",
-       "                        </td>\n",
-       "                    </tr>\n",
-       "\n",
-       "                    \n",
-       "\n",
-       "                    \n",
-       "\n",
-       "                </table>\n",
-       "            </details>\n",
-       "            </div>\n",
-       "        </div>\n",
-       "        \n",
-       "        <div style=\"margin-bottom: 20px;\">\n",
-       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
-       "            <div style=\"margin-left: 48px;\">\n",
-       "            <details>\n",
-       "                <summary>\n",
-       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 1</h4>\n",
-       "                </summary>\n",
-       "                <table style=\"width: 100%; text-align: left;\">\n",
-       "                    <tr>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Comm: </strong> tcp://127.0.0.1:44915\n",
-       "                        </td>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Total threads: </strong> 1\n",
-       "                        </td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:38931/status\" target=\"_blank\">http://127.0.0.1:38931/status</a>\n",
-       "                        </td>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Memory: </strong> 4.57 GiB\n",
-       "                        </td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Nanny: </strong> tcp://127.0.0.1:33733\n",
-       "                        </td>\n",
-       "                        <td style=\"text-align: left;\"></td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
-       "                            <strong>Local directory: </strong> /jobfs/132563736.gadi-pbs/dask-scratch-space/worker-wfl_hdvk\n",
-       "                        </td>\n",
-       "                    </tr>\n",
-       "\n",
-       "                    \n",
-       "\n",
-       "                    \n",
-       "\n",
-       "                </table>\n",
-       "            </details>\n",
-       "            </div>\n",
-       "        </div>\n",
-       "        \n",
-       "        <div style=\"margin-bottom: 20px;\">\n",
-       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
-       "            <div style=\"margin-left: 48px;\">\n",
-       "            <details>\n",
-       "                <summary>\n",
-       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 2</h4>\n",
-       "                </summary>\n",
-       "                <table style=\"width: 100%; text-align: left;\">\n",
-       "                    <tr>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Comm: </strong> tcp://127.0.0.1:38925\n",
-       "                        </td>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Total threads: </strong> 1\n",
-       "                        </td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:41215/status\" target=\"_blank\">http://127.0.0.1:41215/status</a>\n",
-       "                        </td>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Memory: </strong> 4.57 GiB\n",
-       "                        </td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Nanny: </strong> tcp://127.0.0.1:41537\n",
-       "                        </td>\n",
-       "                        <td style=\"text-align: left;\"></td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
-       "                            <strong>Local directory: </strong> /jobfs/132563736.gadi-pbs/dask-scratch-space/worker-kjudhd0l\n",
-       "                        </td>\n",
-       "                    </tr>\n",
-       "\n",
-       "                    \n",
-       "\n",
-       "                    \n",
-       "\n",
-       "                </table>\n",
-       "            </details>\n",
-       "            </div>\n",
-       "        </div>\n",
-       "        \n",
-       "        <div style=\"margin-bottom: 20px;\">\n",
-       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
-       "            <div style=\"margin-left: 48px;\">\n",
-       "            <details>\n",
-       "                <summary>\n",
-       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 3</h4>\n",
-       "                </summary>\n",
-       "                <table style=\"width: 100%; text-align: left;\">\n",
-       "                    <tr>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Comm: </strong> tcp://127.0.0.1:34667\n",
-       "                        </td>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Total threads: </strong> 1\n",
-       "                        </td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:44237/status\" target=\"_blank\">http://127.0.0.1:44237/status</a>\n",
-       "                        </td>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Memory: </strong> 4.57 GiB\n",
-       "                        </td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Nanny: </strong> tcp://127.0.0.1:43925\n",
-       "                        </td>\n",
-       "                        <td style=\"text-align: left;\"></td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
-       "                            <strong>Local directory: </strong> /jobfs/132563736.gadi-pbs/dask-scratch-space/worker-vpxh59oz\n",
-       "                        </td>\n",
-       "                    </tr>\n",
-       "\n",
-       "                    \n",
-       "\n",
-       "                    \n",
-       "\n",
-       "                </table>\n",
-       "            </details>\n",
-       "            </div>\n",
-       "        </div>\n",
-       "        \n",
-       "        <div style=\"margin-bottom: 20px;\">\n",
-       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
-       "            <div style=\"margin-left: 48px;\">\n",
-       "            <details>\n",
-       "                <summary>\n",
-       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 4</h4>\n",
-       "                </summary>\n",
-       "                <table style=\"width: 100%; text-align: left;\">\n",
-       "                    <tr>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Comm: </strong> tcp://127.0.0.1:36523\n",
-       "                        </td>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Total threads: </strong> 1\n",
-       "                        </td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:42299/status\" target=\"_blank\">http://127.0.0.1:42299/status</a>\n",
-       "                        </td>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Memory: </strong> 4.57 GiB\n",
-       "                        </td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Nanny: </strong> tcp://127.0.0.1:46839\n",
-       "                        </td>\n",
-       "                        <td style=\"text-align: left;\"></td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
-       "                            <strong>Local directory: </strong> /jobfs/132563736.gadi-pbs/dask-scratch-space/worker-bhjnq7mf\n",
-       "                        </td>\n",
-       "                    </tr>\n",
-       "\n",
-       "                    \n",
-       "\n",
-       "                    \n",
-       "\n",
-       "                </table>\n",
-       "            </details>\n",
-       "            </div>\n",
-       "        </div>\n",
-       "        \n",
-       "        <div style=\"margin-bottom: 20px;\">\n",
-       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
-       "            <div style=\"margin-left: 48px;\">\n",
-       "            <details>\n",
-       "                <summary>\n",
-       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 5</h4>\n",
-       "                </summary>\n",
-       "                <table style=\"width: 100%; text-align: left;\">\n",
-       "                    <tr>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Comm: </strong> tcp://127.0.0.1:34583\n",
-       "                        </td>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Total threads: </strong> 1\n",
-       "                        </td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:39185/status\" target=\"_blank\">http://127.0.0.1:39185/status</a>\n",
-       "                        </td>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Memory: </strong> 4.57 GiB\n",
-       "                        </td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Nanny: </strong> tcp://127.0.0.1:44951\n",
-       "                        </td>\n",
-       "                        <td style=\"text-align: left;\"></td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
-       "                            <strong>Local directory: </strong> /jobfs/132563736.gadi-pbs/dask-scratch-space/worker-zpzse13n\n",
-       "                        </td>\n",
-       "                    </tr>\n",
-       "\n",
-       "                    \n",
-       "\n",
-       "                    \n",
-       "\n",
-       "                </table>\n",
-       "            </details>\n",
-       "            </div>\n",
-       "        </div>\n",
-       "        \n",
-       "        <div style=\"margin-bottom: 20px;\">\n",
-       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
-       "            <div style=\"margin-left: 48px;\">\n",
-       "            <details>\n",
-       "                <summary>\n",
-       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 6</h4>\n",
-       "                </summary>\n",
-       "                <table style=\"width: 100%; text-align: left;\">\n",
-       "                    <tr>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Comm: </strong> tcp://127.0.0.1:37101\n",
-       "                        </td>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Total threads: </strong> 1\n",
-       "                        </td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:34173/status\" target=\"_blank\">http://127.0.0.1:34173/status</a>\n",
-       "                        </td>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Memory: </strong> 4.57 GiB\n",
-       "                        </td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <td style=\"text-align: left;\">\n",
-       "                            <strong>Nanny: </strong> tcp://127.0.0.1:45001\n",
-       "                        </td>\n",
-       "                        <td style=\"text-align: left;\"></td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
-       "                            <strong>Local directory: </strong> /jobfs/132563736.gadi-pbs/dask-scratch-space/worker-_txsdv3w\n",
-       "                        </td>\n",
-       "                    </tr>\n",
-       "\n",
-       "                    \n",
-       "\n",
-       "                    \n",
-       "\n",
-       "                </table>\n",
-       "            </details>\n",
-       "            </div>\n",
-       "        </div>\n",
-       "        \n",
-       "\n",
-       "    </details>\n",
-       "</div>\n",
-       "\n",
-       "        </details>\n",
-       "    </div>\n",
-       "</div>\n",
-       "            </details>\n",
-       "        \n",
-       "\n",
-       "    </div>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "<Client: 'tcp://127.0.0.1:44181' processes=7 threads=7, memory=32.00 GiB>"
-      ]
-     },
-     "execution_count": 1,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "import regional_mom6 as rmom6\n",
     "\n",
@@ -507,41 +50,39 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
-    "expt_name = \"rotated-demo5\"\n",
-    "\n",
-    "#latitude_extent = [16., 27]\n",
-    "#longitude_extent = [192, 209] #fill will nones and test these are optional so remove\n",
+    "expt_name = \"rotated-demo\"\n",
     "\n",
     "date_range = [\"2020-01-01 00:00:00\", \"2020-02-01 00:00:00\"]\n",
     "\n",
     "## Place where all your input files go \n",
-    "input_dir = Path(f\"/scratch/tm70/hm6113/regional_ncar/{expt_name}/\")\n",
+    "input_dir = Path(f\"mom6_input_directories/{expt_name}/\")\n",
     "\n",
     "## Directory where you'll run the experiment from\n",
-    "run_dir = Path(f\"/scratch/tm70/hm6113/regional_ncar/{expt_name}/\")\n",
+    "run_dir = Path(f\"mom6_run_directories/{expt_name}/\")\n",
     "\n",
     "## Directory where compiled FRE tools are located (needed for construction of mask tables)\n",
     "toolpath_dir = Path(\"/g/data/tm70/hm6113/repo/FRE-NCtools\")\n",
     "\n",
     "## Path to where your raw ocean forcing files are stored\n",
-    "glorys_path = Path(f\"/g/data/tm70/hm6113/glorys/{expt_name}\" )\n",
+    "glorys_path = Path(f\"PATH_TO_GLORYS_DATA/{expt_name}\" )\n",
     "\n",
     "#Directory where the ERA raw atmospheric output files are stored\n",
-    "era_path = Path(\"/g/data/rt52/era5/single-levels/reanalysis\")\n",
+    "era_path = Path(\"PATH_TO_ERA_DATA/era5/single-levels/reanalysis\")\n",
     "\n",
     "#Location of TPXO raw tidal file\n",
-    "tide_h_path = Path(\"/g/data/tm70/hm6113/tides/DATA/h_tpxo10.v2.nc\")\n",
-    "tide_u_path = Path(\"/g/data/tm70/hm6113/tides/DATA/u_tpxo10.v2.nc\")\n",
+    "#note that you will need to swap ## to the version number for each of the file names\n",
+    "tide_h_path = Path(\"PATH_TO_TPXO_H_FILE/h_tpxo##.nc\")\n",
+    "tide_u_path = Path(\"PATH_TO_TPXO_U_FILE/u_tpxo##.nc\")\n",
     "\n",
     "#location of the BYO hgrid file\n",
-    "byogrid_path = \"/scratch/tm70/hm6113/regional_ncar/rotated-demo/hgrid.nc\"\n",
+    "byogrid_path = \"PATH_TO_YOUR_HORIZONTAL_GRID/hgrid.nc\"\n",
     "\n",
     "#location to where your bathymetry data is stored\n",
-    "bathy_path = Path(\"/scratch/tm70/hm6113/GEBCO_2024.nc\")\n",
+    "bathy_path = Path(\"PATH_TO_GEBCO_DATA/GEBCO_2024.nc\")\n",
     "\n",
     "## if directories don't exist, create them\n",
     "for path in (run_dir, glorys_path, input_dir):\n",
@@ -550,20 +91,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'/scratch/tm70/hm6113/regional_ncar/rotated-demo5/hgrid.nc'"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "##Copy hgrid.nc into the experinment folder\n",
     "import shutil\n",
@@ -580,7 +110,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -643,28 +173,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The script `get_glorys_data.sh` has been generated at:\n",
-      "  /g/data/tm70/hm6113/glorys/rotated-demo5.\n",
-      "To download the data, run this script using `bash` in a terminal with internet access.\n",
-      "\n",
-      "Important instructions:\n",
-      "1. You will need your Copernicus Marine username and password.\n",
-      "   If you do not have an account, you can create one here: \n",
-      "   https://data.marine.copernicus.eu/register\n",
-      "2. You will be prompted to enter your Copernicus Marine credentials multiple times: once for each dataset.\n",
-      "3. Depending on the dataset size, the download process may take significant time and resources.\n",
-      "4. Thus, on certain systems, you may need to run this script as a batch job.\n",
-      "\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "expt.get_glorys(\n",
     "    raw_boundaries_path=glorys_path\n",
@@ -684,469 +195,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Begin regridding bathymetry...\n",
-      "\n",
-      "Original bathymetry size: 9.96 Mb\n",
-      "Regridded size: 0.06 Mb\n",
-      "Automatic regridding may fail if your domain is too big! If this process hangs or crashes,open a terminal with appropriate computational and resources try calling ESMF directly in the input directory /scratch/tm70/hm6113/regional_ncar/rotated-demo5 via\n",
-      "\n",
-      "`mpirun -np NUMBER_OF_CPUS ESMF_Regrid -s bathymetry_original.nc -d bathymetry_unfinished.nc -m bilinear --src_var depth --dst_var depth --netcdf4 --src_regional --dst_regional`\n",
-      "\n",
-      "For details see https://xesmf.readthedocs.io/en/latest/large_problems_on_HPC.html\n",
-      "\n",
-      "Afterwards, we run the 'expt.tidy_bathymetry' method to skip the expensive interpolation step, and finishing metadata, encoding and cleanup.\n",
-      "\n",
-      "\n",
-      "\n",
-      "Regridding successful! Now calling `tidy_bathymetry` method for some finishing touches...\n",
-      "Tidy bathymetry: Reading in regridded bathymetry to fix up metadata...done. Filling in inland lakes and channels... done.\n",
-      "setup bathymetry has finished successfully.\n"
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-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
-       "Dimensions:  (ny: 49, nx: 49)\n",
-       "Coordinates:\n",
-       "    lat      (ny, nx) float64 55.67 55.67 55.68 55.68 ... 58.31 58.32 58.32\n",
-       "    lon      (ny, nx) float64 -41.52 -41.43 -41.34 ... -37.72 -37.63 -37.53\n",
-       "Dimensions without coordinates: ny, nx\n",
-       "Data variables:\n",
-       "    depth    (ny, nx) float64 3.16e+03 3.271e+03 ... 3.192e+03 3.195e+03\n",
-       "Attributes:\n",
-       "    regrid_method:  bilinear\n",
-       "    depth:          meters\n",
-       "    standard_name:  bathymetric depth at T-cell centers\n",
-       "    coordinates:    zi</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-7fafad43-c9f1-4823-80b1-5f15193c4d1c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7fafad43-c9f1-4823-80b1-5f15193c4d1c' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>ny</span>: 49</li><li><span>nx</span>: 49</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-e0a4a8f9-199c-41da-8ab8-de47763b53ac' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e0a4a8f9-199c-41da-8ab8-de47763b53ac' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(ny, nx)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>55.67 55.67 55.68 ... 58.32 58.32</div><input id='attrs-c84a2b6d-a9af-40e2-bed2-fcb91af0ba0c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c84a2b6d-a9af-40e2-bed2-fcb91af0ba0c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-362289ac-bf3b-41fe-b9e9-88a1964a2064' class='xr-var-data-in' type='checkbox'><label for='data-362289ac-bf3b-41fe-b9e9-88a1964a2064' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>_FillValue :</span></dt><dd>1e+20</dd></dl></div><div class='xr-var-data'><pre>array([[55.6690997 , 55.67328048, 55.67743919, ..., 55.83789644,\n",
-       "        55.84101611, 55.84411171],\n",
-       "       [55.72089853, 55.72509551, 55.72927036, ..., 55.89036387,\n",
-       "        55.89349627, 55.89660452],\n",
-       "       [55.77265672, 55.77686994, 55.78106095, ..., 55.94279202,\n",
-       "        55.94593718, 55.94905812],\n",
-       "       ...,\n",
-       "       [58.0107782 , 58.01573698, 58.02067038, ..., 58.21178447,\n",
-       "        58.21552027, 58.21922829],\n",
-       "       [58.06077514, 58.0657516 , 58.0707026 , ..., 58.26251586,\n",
-       "        58.26626577, 58.26998782],\n",
-       "       [58.11073443, 58.1157286 , 58.12069724, ..., 58.31321112,\n",
-       "        58.31697517, 58.32071128]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(ny, nx)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-41.52 -41.43 ... -37.63 -37.53</div><input id='attrs-aecaa246-8ac7-4cd4-83d8-89a5e4375a4c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aecaa246-8ac7-4cd4-83d8-89a5e4375a4c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b6a83b4-1550-4b1f-afc6-fd533e8ea768' class='xr-var-data-in' type='checkbox'><label for='data-5b6a83b4-1550-4b1f-afc6-fd533e8ea768' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>_FillValue :</span></dt><dd>1e+20</dd></dl></div><div class='xr-var-data'><pre>array([[-41.52154418, -41.43233012, -41.34309817, ..., -37.40009819,\n",
-       "        -37.3101249 , -37.22013666],\n",
-       "       [-41.52922026, -41.43996836, -41.35069844, ..., -37.40590856,\n",
-       "        -37.31589203, -37.22586044],\n",
-       "       [-41.53693718, -41.44764726, -41.3583392 , ..., -37.4117512 ,\n",
-       "        -37.32169123, -37.23161609],\n",
-       "       ...,\n",
-       "       [-41.91968483, -41.82854577, -41.7373822 , ..., -37.70314762,\n",
-       "        -37.61096659, -37.51876501],\n",
-       "       [-41.92943237, -41.8382471 , -41.74703715, ..., -37.71060748,\n",
-       "        -37.61837324, -37.5261183 ],\n",
-       "       [-41.93922967, -41.84799799, -41.75674147, ..., -37.71810726,\n",
-       "        -37.62581957, -37.53351105]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1e4d5e64-f861-434d-818d-d9940041adbd' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1e4d5e64-f861-434d-818d-d9940041adbd' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>depth</span></div><div class='xr-var-dims'>(ny, nx)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.16e+03 3.271e+03 ... 3.195e+03</div><input id='attrs-1ec7dd58-c12c-47b3-a25f-c6611693fc32' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1ec7dd58-c12c-47b3-a25f-c6611693fc32' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cba4f3be-15f6-475d-8351-2f1afeec5722' class='xr-var-data-in' type='checkbox'><label for='data-cba4f3be-15f6-475d-8351-2f1afeec5722' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[3160.36657358, 3270.61654519, 3266.93203466, ..., 2597.47483393,\n",
-       "        2618.89837899, 2591.9801311 ],\n",
-       "       [3172.34092229, 3241.2481837 , 3233.95678481, ..., 2670.31937566,\n",
-       "        2651.44231632, 2687.01991238],\n",
-       "       [3226.00061779, 3200.45005269, 3265.77030518, ..., 2728.03887684,\n",
-       "        2616.99505535, 2771.49403649],\n",
-       "       ...,\n",
-       "       [3179.05082962, 3186.33035899, 3174.51301978, ..., 3194.        ,\n",
-       "        3197.57995344, 3190.77000804],\n",
-       "       [3162.4707476 , 3165.        , 3168.7553868 , ..., 3203.03091696,\n",
-       "        3199.33676776, 3200.73145629],\n",
-       "       [3154.05598178, 3145.57785207, 3144.59549248, ..., 3193.67066656,\n",
-       "        3192.4708743 , 3195.        ]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8c552900-a6f0-4b73-8cc5-cd5853f8cfb7' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-8c552900-a6f0-4b73-8cc5-cd5853f8cfb7' class='xr-section-summary'  title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-2c9a7535-1e8e-4f60-8767-7f0db47da100' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2c9a7535-1e8e-4f60-8767-7f0db47da100' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>regrid_method :</span></dt><dd>bilinear</dd><dt><span>depth :</span></dt><dd>meters</dd><dt><span>standard_name :</span></dt><dd>bathymetric depth at T-cell centers</dd><dt><span>coordinates :</span></dt><dd>zi</dd></dl></div></li></ul></div></div>"
-      ],
-      "text/plain": [
-       "<xarray.Dataset>\n",
-       "Dimensions:  (ny: 49, nx: 49)\n",
-       "Coordinates:\n",
-       "    lat      (ny, nx) float64 55.67 55.67 55.68 55.68 ... 58.31 58.32 58.32\n",
-       "    lon      (ny, nx) float64 -41.52 -41.43 -41.34 ... -37.72 -37.63 -37.53\n",
-       "Dimensions without coordinates: ny, nx\n",
-       "Data variables:\n",
-       "    depth    (ny, nx) float64 3.16e+03 3.271e+03 ... 3.192e+03 3.195e+03\n",
-       "Attributes:\n",
-       "    regrid_method:  bilinear\n",
-       "    depth:          meters\n",
-       "    standard_name:  bathymetric depth at T-cell centers\n",
-       "    coordinates:    zi"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "expt.setup_bathymetry(\n",
     "    bathymetry_path=bathy_path,\n",
@@ -1168,35 +219,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "metadata": {
     "tags": [
      "nbval-ignore-output",
      "nbval-skip"
     ]
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.collections.QuadMesh at 0x1500729805d0>"
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "#In x/y coords\n",
     "expt.bathymetry.depth.plot()"
@@ -1204,35 +234,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "metadata": {
     "tags": [
      "nbval-ignore-output",
      "nbval-skip"
     ]
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.collections.QuadMesh at 0x15006a8163d0>"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "#In lat/lon coords\n",
     "import xarray as xr\n",
@@ -1255,68 +264,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Setting up Initial Conditions\n",
-      "Regridding Velocities... Done.\n",
-      "Regridding Tracers... Done.\n",
-      "Regridding Free surface... Done.\n",
-      "Saving outputs... done setting up initial condition.\n",
-      "Processing north boundary velocity & tracers..."
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
-      "All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Done.\n",
-      "Processing south boundary velocity & tracers..."
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Done.\n",
-      "Processing east boundary velocity & tracers..."
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Done.\n",
-      "Processing west boundary velocity & tracers...Done.\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Define a mapping from the GLORYS variables and dimensions to the MOM6 ones\n",
     "ocean_varnames = {\"time\": \"time\",\n",
@@ -1353,30 +303,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Text(0.5, 1.0, 'lon/lat coords')"
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1600x400 with 4 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "## Preview the initial temperature at the surface in x/y and lat/lon coordinates\n",
     "from matplotlib import pyplot as plt\n",
@@ -1393,30 +322,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.collections.QuadMesh at 0x15006a3ce310>"
-      ]
-     },
-     "execution_count": 11,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "## u boundary forcing for segment 1 (south)\n",
     "expt.segment_001.u_segment_001.isel(time = 5).plot()\n"
@@ -1435,80 +343,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Processing north boundary..."
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
-      "All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Done\n",
-      "Processing south boundary..."
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
-      "All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Done\n",
-      "Processing east boundary..."
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
-      "All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Done\n",
-      "Processing west boundary..."
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
-      "All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Done\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "expt.setup_boundary_tides(\n",
     "        tide_h_path,\n",
@@ -1529,78 +366,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Running GFDL's FRE Tools. The following information is all printed by the FRE tools themselves\n",
-      "i=0, yb1=58.1331888751, yb2=58.3479205820, dy= 0.2147317068\n",
-      "NOTE from make_solo_mosaic: there are 0 contacts (align-contact)\n",
-      "congratulation: You have successfully run make_solo_mosaic\n",
-      "OUTPUT FROM MAKE SOLO MOSAIC:\n",
-      "\n",
-      "CompletedProcess(args='/g/data/tm70/hm6113/repo/FRE-NCtools/make_solo_mosaic/make_solo_mosaic --num_tiles 1 --dir . --mosaic_name ocean_mosaic --tile_file hgrid.nc', returncode=0)\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "cp: './ocean_mosaic.nc' and 'ocean_mosaic.nc' are the same file\n",
-      "cp: './hgrid.nc' and 'hgrid.nc' are the same file\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "cp ./hgrid.nc hgrid.nc \n",
-      "\n",
-      "NOTE from make_coupler_mosaic: the ocean land/sea mask will be determined by field depth from file bathymetry.nc\n",
-      "mosaic_file is grid_spec.nc\n",
-      "\n",
-      "***** Congratulation! You have successfully run make_quick_mosaic\n",
-      "OUTPUT FROM QUICK MOSAIC:\n",
-      "\n",
-      "CompletedProcess(args='/g/data/tm70/hm6113/repo/FRE-NCtools/make_quick_mosaic/make_quick_mosaic --input_mosaic ocean_mosaic.nc --mosaic_name grid_spec --ocean_topog bathymetry.nc', returncode=0)\n",
-      "\n",
-      " ===>NOTE from check_mask: when layout is specified, min_pe and max_pe is set to layout(1)*layout(2)=100\n",
-      "\n",
-      " ===>NOTE from check_mask: Below is the list of command line arguments.\n",
-      "\n",
-      "grid_file = ocean_mosaic.nc\n",
-      "model = ocean\n",
-      "topog_file = bathymetry.nc\n",
-      "min_pe = 100\n",
-      "max_pe = 100\n",
-      "layout = 10, 10\n",
-      "halo = 4\n",
-      "sea_level = 0\n",
-      "show_valid_only is not set\n",
-      "nobc = 0\n",
-      "\n",
-      " ===>NOTE from check_mask: End of command line arguments.\n",
-      "\n",
-      " ===>NOTE from check_mask: the grid file is version 2 (solo mosaic grid) grid which contains field gridfiles\n",
-      "\n",
-      "==>NOTE from get_boundary_type: x_boundary_type is solid_walls\n",
-      "\n",
-      "==>NOTE from get_boundary_type: y_boundary_type is solid_walls\n",
-      "\n",
-      "==>NOTE from check_mask: Checking for possible masking:\n",
-      "==>NOTE from check_mask: Assume 4 halo rows\n",
-      "==>NOTE from check_mask: Total domain size is 49, 49\n",
-      "\n",
-      "***** Congratulation! You have successfully run check_mask\n",
-      "OUTPUT FROM CHECK MASK:\n",
-      "\n",
-      " CompletedProcess(args='/g/data/tm70/hm6113/repo/FRE-NCtools/check_mask/check_mask --grid_file ocean_mosaic.nc --ocean_topog bathymetry.nc --layout 10,10 --halo 4', returncode=0)\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "expt.run_FRE_tools(layout=(10, 10)) ##the tiling/no processors"
    ]
@@ -1636,7 +404,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1656,25 +424,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Could not find premade run directories at  /scratch/tm70/hm6113/code/rm6_helen_update/regional-mom6/regional_mom6/demos/premade_run_directories\n",
-      "Perhaps the package was imported directly rather than installed with conda. Checking if this is the case... Found run files. Continuing...\n",
-      "No mask table found, but the cpu layout has been set to (10, 10) This suggests the domain is mostly water, so there are no `non compute` cells that are entirely land. If this doesn't seem right, ensure you've already run the `FRE_tools` method which sets up the cpu mask table. Keep an eye on any errors that might print whilethe FRE tools (which run C++ in the background) are running.\n",
-      "Number of CPUs required:  100\n",
-      "Deleting indexed OBC keys from MOM_input_dict in case we have a different number of segments\n",
-      "Changed OBC_TIDE_REF_DATE from 2020, 1, 1 to 2020, 01, 01in MOM_override!\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "expt.setup_run_directory(surface_forcing = \"era5\",using_payu = True, with_tides = True) "
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
diff --git a/demos/reanalysis-forced.ipynb b/demos/reanalysis-forced.ipynb
index 8a3b3deb..4fbd0d6e 100644
--- a/demos/reanalysis-forced.ipynb
+++ b/demos/reanalysis-forced.ipynb
@@ -45,7 +45,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -99,7 +99,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -351,120 +351,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 57,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Processing north boundary...2025-01-10 14:36:52,454 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
-      "2025-01-10 14:36:52,458 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
-      "2025-01-10 14:37:13,744 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:37:13,747 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:37:13,756 - regional_mom6.regridding.add_or_update_time_dim - INFO - Adding time dimension\n",
-      "2025-01-10 14:37:13,760 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
-      "2025-01-10 14:37:13,762 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to zamp_segment_001\n",
-      "2025-01-10 14:37:13,765 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to zphase_segment_001\n",
-      "2025-01-10 14:37:13,767 - regional_mom6.regridding.mask_dataset - WARNING - All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
-      "2025-01-10 14:37:13,768 - regional_mom6.regridding.generate_encoding - INFO - Generating encoding dictionary\n",
-      "2025-01-10 14:37:13,861 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
-      "2025-01-10 14:37:35,116 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
-      "2025-01-10 14:37:56,654 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:37:56,655 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:37:56,657 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:37:56,659 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:37:56,675 - regional_mom6.regridding.add_or_update_time_dim - INFO - Adding time dimension\n",
-      "2025-01-10 14:37:56,680 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:37:56,684 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
-      "2025-01-10 14:37:56,687 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to uamp_segment_001\n",
-      "2025-01-10 14:37:56,688 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to vamp_segment_001\n",
-      "2025-01-10 14:37:56,690 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to uphase_segment_001\n",
-      "2025-01-10 14:37:56,692 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to vphase_segment_001\n",
-      "2025-01-10 14:37:56,694 - regional_mom6.regridding.mask_dataset - WARNING - All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
-      "2025-01-10 14:37:56,695 - regional_mom6.regridding.generate_encoding - INFO - Generating encoding dictionary\n",
-      "Done\n",
-      "Processing south boundary...2025-01-10 14:37:56,755 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
-      "2025-01-10 14:37:56,757 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
-      "2025-01-10 14:38:17,931 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:38:17,934 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:38:17,939 - regional_mom6.regridding.add_or_update_time_dim - INFO - Adding time dimension\n",
-      "2025-01-10 14:38:17,944 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
-      "2025-01-10 14:38:17,946 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to zamp_segment_002\n",
-      "2025-01-10 14:38:17,948 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to zphase_segment_002\n",
-      "2025-01-10 14:38:17,950 - regional_mom6.regridding.mask_dataset - WARNING - All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
-      "2025-01-10 14:38:17,952 - regional_mom6.regridding.generate_encoding - INFO - Generating encoding dictionary\n",
-      "2025-01-10 14:38:17,982 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
-      "2025-01-10 14:38:39,684 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
-      "2025-01-10 14:39:01,135 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:39:01,136 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:39:01,137 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:39:01,139 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:39:01,152 - regional_mom6.regridding.add_or_update_time_dim - INFO - Adding time dimension\n",
-      "2025-01-10 14:39:01,155 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:39:01,159 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
-      "2025-01-10 14:39:01,161 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to uamp_segment_002\n",
-      "2025-01-10 14:39:01,163 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to vamp_segment_002\n",
-      "2025-01-10 14:39:01,165 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to uphase_segment_002\n",
-      "2025-01-10 14:39:01,167 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to vphase_segment_002\n",
-      "2025-01-10 14:39:01,168 - regional_mom6.regridding.mask_dataset - WARNING - All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
-      "2025-01-10 14:39:01,170 - regional_mom6.regridding.generate_encoding - INFO - Generating encoding dictionary\n",
-      "Done\n",
-      "Processing east boundary...2025-01-10 14:39:01,241 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
-      "2025-01-10 14:39:01,243 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
-      "2025-01-10 14:39:22,804 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:39:22,806 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:39:22,811 - regional_mom6.regridding.add_or_update_time_dim - INFO - Adding time dimension\n",
-      "2025-01-10 14:39:22,815 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
-      "2025-01-10 14:39:22,817 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to zamp_segment_003\n",
-      "2025-01-10 14:39:22,820 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to zphase_segment_003\n",
-      "2025-01-10 14:39:22,822 - regional_mom6.regridding.mask_dataset - WARNING - All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
-      "2025-01-10 14:39:22,823 - regional_mom6.regridding.generate_encoding - INFO - Generating encoding dictionary\n",
-      "2025-01-10 14:39:22,850 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
-      "2025-01-10 14:39:43,725 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
-      "2025-01-10 14:40:04,730 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:40:04,733 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:40:04,738 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:40:04,740 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:40:04,756 - regional_mom6.regridding.add_or_update_time_dim - INFO - Adding time dimension\n",
-      "2025-01-10 14:40:04,760 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:40:04,765 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
-      "2025-01-10 14:40:04,768 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to uamp_segment_003\n",
-      "2025-01-10 14:40:04,770 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to vamp_segment_003\n",
-      "2025-01-10 14:40:04,772 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to uphase_segment_003\n",
-      "2025-01-10 14:40:04,775 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to vphase_segment_003\n",
-      "2025-01-10 14:40:04,776 - regional_mom6.regridding.mask_dataset - WARNING - All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
-      "2025-01-10 14:40:04,778 - regional_mom6.regridding.generate_encoding - INFO - Generating encoding dictionary\n",
-      "Done\n",
-      "Processing west boundary...2025-01-10 14:40:04,815 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
-      "2025-01-10 14:40:04,817 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
-      "2025-01-10 14:40:25,799 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:40:25,801 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:40:25,806 - regional_mom6.regridding.add_or_update_time_dim - INFO - Adding time dimension\n",
-      "2025-01-10 14:40:25,810 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
-      "2025-01-10 14:40:25,813 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to zamp_segment_004\n",
-      "2025-01-10 14:40:25,816 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to zphase_segment_004\n",
-      "2025-01-10 14:40:25,818 - regional_mom6.regridding.mask_dataset - WARNING - All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
-      "2025-01-10 14:40:25,820 - regional_mom6.regridding.generate_encoding - INFO - Generating encoding dictionary\n",
-      "2025-01-10 14:40:25,850 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
-      "2025-01-10 14:40:47,150 - regional_mom6.regridding.create_regridder - INFO - Creating Regridder\n",
-      "2025-01-10 14:41:07,908 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:41:07,910 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:41:07,911 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:41:07,912 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:41:07,923 - regional_mom6.regridding.add_or_update_time_dim - INFO - Adding time dimension\n",
-      "2025-01-10 14:41:07,928 - regional_mom6.regridding.fill_missing_data - INFO - Filling in missing data horizontally, then vertically\n",
-      "2025-01-10 14:41:07,932 - regional_mom6.regridding.coords - INFO - Creating coordinates of the boundary q/u/v points\n",
-      "2025-01-10 14:41:07,934 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to uamp_segment_004\n",
-      "2025-01-10 14:41:07,936 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to vamp_segment_004\n",
-      "2025-01-10 14:41:07,937 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to uphase_segment_004\n",
-      "2025-01-10 14:41:07,938 - regional_mom6.regridding.add_secondary_dimension - INFO - Adding perpendicular dimension to vphase_segment_004\n",
-      "2025-01-10 14:41:07,941 - regional_mom6.regridding.mask_dataset - WARNING - All NaNs filled b/c bathymetry wasn't provided to the function. Add bathymetry_path to the segment class to avoid this\n",
-      "2025-01-10 14:41:07,943 - regional_mom6.regridding.generate_encoding - INFO - Generating encoding dictionary\n",
-      "Done\n"
-     ]
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "expt.setup_boundary_tides(\n",
     "        tide_h_path,\n",

From 341b4d2aea23930ff3bb84b58d0965d044c1c204 Mon Sep 17 00:00:00 2001
From: Helen Macdonald <179985228+helenmacdonald@users.noreply.github.com>
Date: Wed, 22 Jan 2025 10:46:05 +1100
Subject: [PATCH 8/8] Update demos/BYO-domain.ipynb

fixing path to bathymetry.nc

Co-authored-by: Manish Venumuddula <80477243+manishvenu@users.noreply.github.com>
---
 demos/BYO-domain.ipynb | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/demos/BYO-domain.ipynb b/demos/BYO-domain.ipynb
index aef92a4e..cc31d902 100644
--- a/demos/BYO-domain.ipynb
+++ b/demos/BYO-domain.ipynb
@@ -245,7 +245,7 @@
    "source": [
     "#In lat/lon coords\n",
     "import xarray as xr\n",
-    "bathy = xr.open_dataset(run_dir / \"bathymetry.nc\")\n",
+    "bathy = xr.open_dataset(input_dir / \"bathymetry.nc\")\n",
     "bathy.depth.plot(x=\"lon\",y=\"lat\")\n"
    ]
   },