From 3cc1b623cac45c986fac899fb69a7b4dcfcbd961 Mon Sep 17 00:00:00 2001
From: cywhale <cyrain@gmail.com>
Date: Wed, 29 Nov 2023 12:09:48 +0800
Subject: [PATCH] ver 0.3.0 Breaking upgrade to GEBCO(2023) now. Change to use
 pipenv for package version management

---
 Pipfile                                       |   21 +
 Pipfile.lock                                  |  675 ++++
 __init__.py                                   |    0
 change_log.md                                 |    3 +
 conf/ecosystem.config.js                      |    2 +-
 data_src/GEBCO_2023_Grid_documentation.pdf    |  Bin 0 -> 199494 bytes
 data_src/GEBCO_Grid_terms_of_use.pdf          |  Bin 0 -> 139067 bytes
 dev/read_gebco_raw01.ipynb                    | 2977 +++++++++++++++++
 simu_gebco01.py => dev/simu_gebco01.py        |    6 +-
 wireframe01.ipynb => dev/wireframe01.ipynb    |    0
 zprofile01.ipynb => dev/zprofile01.ipynb      | 1632 +++++----
 .../zprofile02_crosszero.ipynb                |    0
 gebco_app.py                                  |   38 +-
 read_gebco_raw01.ipynb                        | 1917 -----------
 requirements.txt                              |   17 +-
 setup.py                                      |    4 +
 src.egg-info/PKG-INFO                         |    3 +
 src.egg-info/SOURCES.txt                      |   19 +
 src.egg-info/dependency_links.txt             |    1 +
 src.egg-info/top_level.txt                    |    1 +
 src/__init__.py                               |    0
 xmeridian.py => src/xmeridian.py              |    0
 22 files changed, 4532 insertions(+), 2784 deletions(-)
 create mode 100644 Pipfile
 create mode 100644 Pipfile.lock
 create mode 100644 __init__.py
 create mode 100755 data_src/GEBCO_2023_Grid_documentation.pdf
 create mode 100755 data_src/GEBCO_Grid_terms_of_use.pdf
 create mode 100644 dev/read_gebco_raw01.ipynb
 rename simu_gebco01.py => dev/simu_gebco01.py (99%)
 rename wireframe01.ipynb => dev/wireframe01.ipynb (100%)
 rename zprofile01.ipynb => dev/zprofile01.ipynb (63%)
 rename zprofile02_crosszero.ipynb => dev/zprofile02_crosszero.ipynb (100%)
 delete mode 100644 read_gebco_raw01.ipynb
 create mode 100644 setup.py
 create mode 100644 src.egg-info/PKG-INFO
 create mode 100644 src.egg-info/SOURCES.txt
 create mode 100644 src.egg-info/dependency_links.txt
 create mode 100644 src.egg-info/top_level.txt
 create mode 100644 src/__init__.py
 rename xmeridian.py => src/xmeridian.py (100%)

diff --git a/Pipfile b/Pipfile
new file mode 100644
index 0000000..a73c1f6
--- /dev/null
+++ b/Pipfile
@@ -0,0 +1,21 @@
+[[source]]
+url = "https://pypi.org/simple"
+verify_ssl = true
+name = "pypi"
+
+[packages]
+dask = "==2023.11.0"
+fastapi = "==0.104.1"
+geopy = "==2.4.1"
+gunicorn = "==21.2.0"
+numpy = "==1.26.2"
+polars = "==0.19.17"
+requests = "==2.31.0"
+uvicorn = "==0.24.0.post1"
+xarray = "==2023.11.0"
+zarr = "==2.16.1"
+
+[dev-packages]
+
+[requires]
+python_version = "3.11"
diff --git a/Pipfile.lock b/Pipfile.lock
new file mode 100644
index 0000000..2142e57
--- /dev/null
+++ b/Pipfile.lock
@@ -0,0 +1,675 @@
+{
+    "_meta": {
+        "hash": {
+            "sha256": "13e9ff18b162ea783b2abd159e100ab72769e901cadbb6c79a4a7215c0290828"
+        },
+        "pipfile-spec": 6,
+        "requires": {
+            "python_version": "3.11"
+        },
+        "sources": [
+            {
+                "name": "pypi",
+                "url": "https://pypi.org/simple",
+                "verify_ssl": true
+            }
+        ]
+    },
+    "default": {
+        "annotated-types": {
+            "hashes": [
+                "sha256:0641064de18ba7a25dee8f96403ebc39113d0cb953a01429249d5c7564666a43",
+                "sha256:563339e807e53ffd9c267e99fc6d9ea23eb8443c08f112651963e24e22f84a5d"
+            ],
+            "markers": "python_version >= '3.8'",
+            "version": "==0.6.0"
+        },
+        "anyio": {
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+                "sha256:44a3c9aba0f5defa43261a8b3efb97891f2bd7d804e0e1f56419befa1adfc780",
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+            "version": "==3.7.1"
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+}
diff --git a/__init__.py b/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/change_log.md b/change_log.md
index 75425e7..6dfaf96 100644
--- a/change_log.md
+++ b/change_log.md
@@ -43,3 +43,6 @@
 ###### ver 0.2.4 Add jsonsrc can feed JSON url/string, and fix openapi.json in /swagger
 
 ###### ver 0.2.5 Package upgrade/improve pm2 restart by pre_stop
+
+
+#### ver 0.3.0 Breaking upgrade to GEBCO(2023) now. Change to use pipenv for package version management 
diff --git a/conf/ecosystem.config.js b/conf/ecosystem.config.js
index 28116ac..9f99de8 100644
--- a/conf/ecosystem.config.js
+++ b/conf/ecosystem.config.js
@@ -1,7 +1,7 @@
 module.exports = {
   apps : [{
     name: 'gebco',
-    script: 'gunicorn gebco_app:app -w 4 -k uvicorn.workers.UvicornWorker -b 127.0.0.1:8013 --keyfile conf/privkey.pem --certfile conf/fullchain.pem --reload',
+    script: 'gunicorn gebco_app:app -w 2 -k uvicorn.workers.UvicornWorker -b 127.0.0.1:8013 --keyfile conf/privkey.pem --certfile conf/fullchain.pem --reload',
     args: '',
     merge_logs: true,
     autorestart: true,
diff --git a/data_src/GEBCO_2023_Grid_documentation.pdf b/data_src/GEBCO_2023_Grid_documentation.pdf
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diff --git a/dev/read_gebco_raw01.ipynb b/dev/read_gebco_raw01.ipynb
new file mode 100644
index 0000000..aa8f409
--- /dev/null
+++ b/dev/read_gebco_raw01.ipynb
@@ -0,0 +1,2977 @@
+{
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+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
+       "Dimensions:    (lon: 86400, lat: 43200)\n",
+       "Coordinates:\n",
+       "  * lon        (lon) float64 -180.0 -180.0 -180.0 -180.0 ... 180.0 180.0 180.0\n",
+       "  * lat        (lat) float64 -90.0 -89.99 -89.99 -89.99 ... 89.99 89.99 90.0\n",
+       "Data variables:\n",
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+       "Attributes:\n",
+       "    Conventions:  CF-1.6\n",
+       "    title:        The GEBCO_2020 Grid - a continuous terrain model for oceans...\n",
+       "    institution:  On behalf of the General Bathymetric Chart of the Oceans (G...\n",
+       "    source:       The GEBCO_2020 Grid is the latest global bathymetric produc...\n",
+       "    history:      Information on the development of the data set and the sour...\n",
+       "    references:   DOI: 10.5285/836f016a-33be-6ddc-e053-6c86abc0788e\n",
+       "    comment:      The data in the GEBCO_2020 Grid should not be used for navi...\n",
+       "    node_offset:  1.0</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-bc04c1a7-488c-4574-aa9b-af8daf309c6c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-bc04c1a7-488c-4574-aa9b-af8daf309c6c' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lon</span>: 86400</li><li><span class='xr-has-index'>lat</span>: 43200</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-57f4904d-c9cb-46b7-95e3-2a335e72f468' class='xr-section-summary-in' type='checkbox'  checked><label for='section-57f4904d-c9cb-46b7-95e3-2a335e72f468' 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 class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -180.0 ... 180.0 180.0</div><input id='attrs-78c16f70-0563-4f55-a327-2f441ae3caa4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-78c16f70-0563-4f55-a327-2f441ae3caa4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b727700-915e-4228-95aa-96cdc7504372' class='xr-var-data-in' type='checkbox'><label for='data-7b727700-915e-4228-95aa-96cdc7504372' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>sdn_parameter_urn :</span></dt><dd>SDN:P01::ALONZZ01</dd><dt><span>sdn_parameter_name :</span></dt><dd>Longitude east</dd><dt><span>sdn_uom_urn :</span></dt><dd>SDN:P06::DEGE</dd><dt><span>sdn_uom_name :</span></dt><dd>Degrees east</dd></dl></div><div class='xr-var-data'><pre>array([-179.997917, -179.99375 , -179.989583, ...,  179.989583,  179.99375 ,\n",
+       "        179.997917])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.99 -89.99 ... 89.99 90.0</div><input id='attrs-2aebc3aa-0fee-49de-a7fb-9f9384d61b5b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2aebc3aa-0fee-49de-a7fb-9f9384d61b5b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a32b746f-3405-426b-8273-3f0ac124f603' class='xr-var-data-in' type='checkbox'><label for='data-a32b746f-3405-426b-8273-3f0ac124f603' 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>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>sdn_parameter_urn :</span></dt><dd>SDN:P01::ALATZZ01</dd><dt><span>sdn_parameter_name :</span></dt><dd>Latitude north</dd><dt><span>sdn_uom_urn :</span></dt><dd>SDN:P06::DEGN</dd><dt><span>sdn_uom_name :</span></dt><dd>Degrees north</dd></dl></div><div class='xr-var-data'><pre>array([-89.997917, -89.99375 , -89.989583, ...,  89.989583,  89.99375 ,\n",
+       "        89.997917])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ca5cddfa-cea1-4a18-b15d-48f9a8974479' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ca5cddfa-cea1-4a18-b15d-48f9a8974479' 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>elevation</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(43200, 86400), meta=np.ndarray&gt;</div><input id='attrs-29992c20-6db1-4fa8-845d-57e0e287429b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-29992c20-6db1-4fa8-845d-57e0e287429b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5be6d85c-b4df-491a-bc56-4da5cd302c3a' class='xr-var-data-in' type='checkbox'><label for='data-5be6d85c-b4df-491a-bc56-4da5cd302c3a' 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>standard_name :</span></dt><dd>height_above_reference_ellipsoid</dd><dt><span>long_name :</span></dt><dd>Elevation relative to sea level</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>sdn_parameter_urn :</span></dt><dd>SDN:P01::ALATZZ01</dd><dt><span>sdn_parameter_name :</span></dt><dd>Sea floor height (above mean sea level) {bathymetric height}</dd><dt><span>sdn_uom_urn :</span></dt><dd>SDN:P06::ULAA</dd><dt><span>sdn_uom_name :</span></dt><dd>Metres</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.95 GiB </td>\n",
+       "                        <td> 6.95 GiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (43200, 86400) </td>\n",
+       "                        <td> (43200, 86400) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> int16 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"110\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"60\" x2=\"120\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,60.0 0.0,60.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"80.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >86400</text>\n",
+       "  <text x=\"140.000000\" y=\"30.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,30.000000)\">43200</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-e5aaa53d-12e6-4782-bfd5-8b8daf4f6b05' class='xr-section-summary-in' type='checkbox'  ><label for='section-e5aaa53d-12e6-4782-bfd5-8b8daf4f6b05' class='xr-section-summary' >Indexes: <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-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-bdca829a-aa7c-4cbc-8355-ddcf25cb3d85' class='xr-index-data-in' type='checkbox'/><label for='index-bdca829a-aa7c-4cbc-8355-ddcf25cb3d85' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-179.99791666666667,          -179.99375, -179.98958333333334,\n",
+       "       -179.98541666666668,          -179.98125, -179.97708333333333,\n",
+       "       -179.97291666666666,          -179.96875, -179.96458333333334,\n",
+       "       -179.96041666666667,\n",
+       "       ...\n",
+       "        179.96041666666667,  179.96458333333334,           179.96875,\n",
+       "        179.97291666666666,  179.97708333333333,           179.98125,\n",
+       "        179.98541666666665,  179.98958333333331,  179.99374999999998,\n",
+       "        179.99791666666667],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=86400))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f8db5908-110e-4dce-8728-65b1d104dc62' class='xr-index-data-in' type='checkbox'/><label for='index-f8db5908-110e-4dce-8728-65b1d104dc62' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-89.99791666666667,          -89.99375, -89.98958333333333,\n",
+       "       -89.98541666666667,          -89.98125, -89.97708333333334,\n",
+       "       -89.97291666666666,          -89.96875, -89.96458333333334,\n",
+       "       -89.96041666666666,\n",
+       "       ...\n",
+       "        89.96041666666667,  89.96458333333334,           89.96875,\n",
+       "        89.97291666666666,  89.97708333333333,  89.98124999999999,\n",
+       "        89.98541666666665,  89.98958333333334,           89.99375,\n",
+       "        89.99791666666667],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=43200))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2ea85a28-67b3-44bd-86f5-8db7bf7a57c8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2ea85a28-67b3-44bd-86f5-8db7bf7a57c8' class='xr-section-summary' >Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>title :</span></dt><dd>The GEBCO_2020 Grid - a continuous terrain model for oceans and land at 15 arc-second intervals</dd><dt><span>institution :</span></dt><dd>On behalf of the General Bathymetric Chart of the Oceans (GEBCO), the data are held at the British Oceanographic Data Centre (BODC).</dd><dt><span>source :</span></dt><dd>The GEBCO_2020 Grid is the latest global bathymetric product released by the General Bathymetric Chart of the Oceans (GEBCO) and has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and GEBCO. The Seabed 2030 Project aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor and make it available to all.</dd><dt><span>history :</span></dt><dd>Information on the development of the data set and the source data sets included in the grid can be found in the data set documentation available from https://www.gebco.net</dd><dt><span>references :</span></dt><dd>DOI: 10.5285/836f016a-33be-6ddc-e053-6c86abc0788e</dd><dt><span>comment :</span></dt><dd>The data in the GEBCO_2020 Grid should not be used for navigation or any purpose relating to safety at sea.</dd><dt><span>node_offset :</span></dt><dd>1.0</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset>\n",
+       "Dimensions:    (lon: 86400, lat: 43200)\n",
+       "Coordinates:\n",
+       "  * lon        (lon) float64 -180.0 -180.0 -180.0 -180.0 ... 180.0 180.0 180.0\n",
+       "  * lat        (lat) float64 -90.0 -89.99 -89.99 -89.99 ... 89.99 89.99 90.0\n",
+       "Data variables:\n",
+       "    elevation  (lat, lon) int16 dask.array<chunksize=(43200, 86400), meta=np.ndarray>\n",
+       "Attributes:\n",
+       "    Conventions:  CF-1.6\n",
+       "    title:        The GEBCO_2020 Grid - a continuous terrain model for oceans...\n",
+       "    institution:  On behalf of the General Bathymetric Chart of the Oceans (G...\n",
+       "    source:       The GEBCO_2020 Grid is the latest global bathymetric produc...\n",
+       "    history:      Information on the development of the data set and the sour...\n",
+       "    references:   DOI: 10.5285/836f016a-33be-6ddc-e053-6c86abc0788e\n",
+       "    comment:      The data in the GEBCO_2020 Grid should not be used for navi...\n",
+       "    node_offset:  1.0"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import xarray as xr\n",
+    "import time, sys\n",
+    "st = time.time()\n",
+    "#xr.open_mfdataset('~/R/gebco/*.nc', parallel=True)\n",
+    "ds = xr.open_mfdataset(\n",
+    "    '../data_src/GEBCO_2023_sub_ice_topo.nc', chunks={0: 60, 1: 60}, \n",
+    "    decode_cf=False, decode_times=False) #.load()\n",
+    "et = time.time()\n",
+    "print('Exe time: ', et-st, 'sec')\n",
+    "ds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "112\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "6.9522857666015625"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "print(sys.getsizeof(ds))\n",
+    "ds['elevation'].nbytes/(1024 ** 3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<xarray.Dataset>\n",
+      "Dimensions:    (lon: 86400, lat: 43200)\n",
+      "Coordinates:\n",
+      "  * lon        (lon) float64 -180.0 -180.0 -180.0 -180.0 ... 180.0 180.0 180.0\n",
+      "  * lat        (lat) float64 -90.0 -89.99 -89.99 -89.99 ... 89.99 89.99 90.0\n",
+      "Data variables:\n",
+      "    crs        |S1 ...\n",
+      "    elevation  (lat, lon) int16 dask.array<chunksize=(43200, 86400), meta=np.ndarray>\n",
+      "Attributes: (12/36)\n",
+      "    title:                           The GEBCO_2022 Grid - a continuous terra...\n",
+      "    summary:                         The GEBCO_2022 Grid is a continuous, glo...\n",
+      "    keywords:                        BATHYMETRY/SEAFLOOR TOPOGRAPHY, DIGITAL ...\n",
+      "    Conventions:                     CF-1.6, ACDD-1.3\n",
+      "    id:                              DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c8...\n",
+      "    naming_authority:                https://dx.doi.org\n",
+      "    ...                              ...\n",
+      "    geospatial_vertical_units:       meters\n",
+      "    geospatial_vertical_resolution:  1.0\n",
+      "    geospatial_vertical_positive:    up\n",
+      "    identifier_product_doi:          DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c8...\n",
+      "    references:                      DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c8...\n",
+      "    node_offset:                     1.0\n",
+      "<xarray.Dataset>\n",
+      "Dimensions:    (lon: 86400, lat: 43200)\n",
+      "Coordinates:\n",
+      "  * lon        (lon) float64 -180.0 -180.0 -180.0 -180.0 ... 180.0 180.0 180.0\n",
+      "  * lat        (lat) float64 -90.0 -89.99 -89.99 -89.99 ... 89.99 89.99 90.0\n",
+      "Data variables:\n",
+      "    elevation  (lat, lon) int16 dask.array<chunksize=(43200, 86400), meta=np.ndarray>\n",
+      "Attributes:\n",
+      "    Conventions:  CF-1.6\n",
+      "    title:        The GEBCO_2020 Grid - a continuous terrain model for oceans...\n",
+      "    institution:  On behalf of the General Bathymetric Chart of the Oceans (G...\n",
+      "    source:       The GEBCO_2020 Grid is the latest global bathymetric produc...\n",
+      "    history:      Information on the development of the data set and the sour...\n",
+      "    references:   DOI: 10.5285/836f016a-33be-6ddc-e053-6c86abc0788e\n",
+      "    comment:      The data in the GEBCO_2020 Grid should not be used for navi...\n",
+      "    node_offset:  1.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "import xarray as xr\n",
+    "import dask\n",
+    "\n",
+    "# Open the GEBCO_2022 dataset\n",
+    "ds1 = xr.open_mfdataset('../data_src/GEBCO_2022_sub_ice_topo.nc', chunks={0: 60, 1: 60},\n",
+    "                        decode_cf=False, decode_times=False)\n",
+    "\n",
+    "# Open the GEBCO_2023 dataset\n",
+    "ds2 = xr.open_mfdataset('../data_src/GEBCO_2023_sub_ice_topo.nc', chunks={0: 60, 1: 60},\n",
+    "                        decode_cf=False, decode_times=False)\n",
+    "\n",
+    "# Inspect the structure and metadata\n",
+    "print(ds1)\n",
+    "print(ds2)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "True\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(isinstance(ds1['elevation'].data, dask.array.Array))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Assuming ds1 uses Dask, get its chunk sizes\n",
+    "# chunk_sizes = {dim: ds1[dim].data.chunksize for dim in ds1.dims}\n",
+    "\n",
+    "# Apply these chunk sizes to ds2\n",
+    "# ds2 = ds2.chunk(chunk_sizes)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'title': 'The GEBCO_2022 Grid - a continuous terrain model for oceans and land at 15 arc-second intervals', 'summary': 'The GEBCO_2022 Grid is a continuous, global terrain model for ocean and land with a spatial resolution of 15 arc seconds.The grid uses as a base-map Version 2.4 of the SRTM15+ data set (Tozer et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. It is augmented with gridded bathymetric data sets developed as part of the Nippon Foundation-GEBCO Seabed 2030 Project.', 'keywords': 'BATHYMETRY/SEAFLOOR TOPOGRAPHY, DIGITAL ELEVATION/DIGITAL TERRAIN MODELS', 'Conventions': 'CF-1.6, ACDD-1.3', 'id': 'DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c86abc0289c', 'naming_authority': 'https://dx.doi.org', 'history': 'Information on the development of the data set and the source data sets included in the grid can be found in the data set documentation available from https://www.gebco.net', 'source': 'The GEBCO_2022 Grid is the latest global bathymetric product released by the General Bathymetric Chart of the Oceans (GEBCO) and has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and GEBCO. The Seabed 2030 Project aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor and make it available to all.', 'comment': 'The data in the GEBCO_2022 Grid should not be used for navigation or any purpose relating to safety at sea.', 'license': 'The GEBCO Grid is placed in the public domain and may be used free of charge. Use of the GEBCO Grid indicates that the user accepts the conditions of use and disclaimer information: https://www.gebco.net/data_and_products/gridded_bathymetry_data/gebco_2019/grid_terms_of_use.html', 'date_created': '2022-06-22', 'creator_name': 'GEBCO through the Nippon Foundation-GEBCO Seabed 2030 Project', 'creator_email': 'gdacc@seabed2030.org', 'creator_url': 'https://www.gebco.net', 'institution': 'On behalf of the General Bathymetric Chart of the Oceans (GEBCO), the data are held at the British Oceanographic Data Centre (BODC).', 'project': 'Nippon Foundation - GEBCO Seabed2030 Project', 'creator_type': 'International organisation', 'geospatial_bounds': array([-180.,  -90.,  180.,   90.]), 'geospatial_bounds_crs': 'WGS84', 'geospatial_bounds_vertical_crs': 'EPSG:5831', 'geospatial_lat_min': -90.0, 'geospatial_lat_max': 90.0, 'geospatial_lat_units': 'degrees_north', 'geospatial_lat_resolution': 0.004166666666666667, 'geospatial_lon_min': -180.0, 'geospatial_lon_max': 180.0, 'geospatial_lon_units': 'degrees_east', 'geospatial_lon_resolution': 0.004166666666666667, 'geospatial_vertical_min': -10977.0, 'geospatial_vertical_max': 8685.0, 'geospatial_vertical_units': 'meters', 'geospatial_vertical_resolution': 1.0, 'geospatial_vertical_positive': 'up', 'identifier_product_doi': 'DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c86abc0289c', 'references': 'DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c86abc0289c', 'node_offset': 1.0}\n",
+      "---------------\n",
+      "{'Conventions': 'CF-1.6', 'title': 'The GEBCO_2020 Grid - a continuous terrain model for oceans and land at 15 arc-second intervals', 'institution': 'On behalf of the General Bathymetric Chart of the Oceans (GEBCO), the data are held at the British Oceanographic Data Centre (BODC).', 'source': 'The GEBCO_2020 Grid is the latest global bathymetric product released by the General Bathymetric Chart of the Oceans (GEBCO) and has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and GEBCO. The Seabed 2030 Project aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor and make it available to all.', 'history': 'Information on the development of the data set and the source data sets included in the grid can be found in the data set documentation available from https://www.gebco.net', 'references': 'DOI: 10.5285/836f016a-33be-6ddc-e053-6c86abc0788e', 'comment': 'The data in the GEBCO_2020 Grid should not be used for navigation or any purpose relating to safety at sea.', 'node_offset': 1.0}\n",
+      "--------------- data_vars\n",
+      "{'grid_mapping_name': 'latitude_longitude', 'epsg_code': 'EPSG:4326', 'inverse_flattening': 298.257223563, 'semi_major_axis': 6378137.0}\n",
+      "{'standard_name': 'height_above_mean_sea_level', 'long_name': 'Elevation relative to sea level', 'units': 'm', 'grid_mapping': 'crs', 'sdn_parameter_urn': 'SDN:P01::ALATZZ01', 'sdn_parameter_name': 'Sea floor height (above mean sea level) {bathymetric height}', 'sdn_uom_urn': 'SDN:P06::ULAA', 'sdn_uom_name': 'Metres'}\n",
+      "--------------- data_vars in ds2\n",
+      "{'standard_name': 'height_above_reference_ellipsoid', 'long_name': 'Elevation relative to sea level', 'units': 'm', 'sdn_parameter_urn': 'SDN:P01::ALATZZ01', 'sdn_parameter_name': 'Sea floor height (above mean sea level) {bathymetric height}', 'sdn_uom_urn': 'SDN:P06::ULAA', 'sdn_uom_name': 'Metres'}\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(ds1.attrs)\n",
+    "print(\"---------------\")\n",
+    "print(ds2.attrs)\n",
+    "print(\"--------------- data_vars\")\n",
+    "for var in ds1.data_vars:\n",
+    "    print(ds1[var].attrs)\n",
+    "\n",
+    "print(\"--------------- data_vars in ds2\")\n",
+    "\n",
+    "for var in ds2.data_vars:\n",
+    "    print(ds2[var].attrs)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Example: Copying global attributes\n",
+    "# ds2.attrs = ds1.attrs\n",
+    "\n",
+    "# Example: Copying variable-specific attributes\n",
+    "# for var in ds2.data_vars:\n",
+    "#    if var in ds1.data_vars:\n",
+    "#        ds2[var].attrs = ds1[var].attrs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<xarray.backends.zarr.ZarrStore at 0x7fd3e21d7450>"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "chunk_sizes = {'lat': 60, 'lon': 60}  # Replace with the actual chunk sizes used for ds1\n",
+    "\n",
+    "# Apply these chunk sizes to ds2\n",
+    "ds2 = ds2.chunk(chunk_sizes)\n",
+    "ds2.to_zarr('../data/GEBCO_2023_sub_ice_topo.zarr', mode='w')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "larger-chunk read time:  0.007239341735839844 sec\n",
+      "112\n",
+      "smaller-chunk read time:  0.0065441131591796875 sec\n",
+      "112\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "6.9522857666015625"
+      ]
+     },
+     "execution_count": 43,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "st = time.time()\n",
+    "#larger chunk size\n",
+    "ds2 = xr.open_mfdataset(\n",
+    "    '../data_src/GEBCO_2023_sub_ice_topo.nc', chunks={0: 45, 1: 45}, #{0: 120, 1: 120}\n",
+    "    decode_cf=False, decode_times=False) #.load()\n",
+    "et = time.time()\n",
+    "print('larger-chunk read time: ', et-st, 'sec')\n",
+    "print(sys.getsizeof(ds2))\n",
+    "ds2['elevation'].nbytes/(1024 ** 3)\n",
+    "\n",
+    "st = time.time()\n",
+    "#smaller chunk size\n",
+    "ds3 = xr.open_mfdataset(\n",
+    "    '../data_src/GEBCO_2023_sub_ice_topo.nc', chunks={0: 30, 1: 30}, \n",
+    "    decode_cf=False, decode_times=False) #.load()\n",
+    "et = time.time()\n",
+    "print('smaller-chunk read time: ', et-st, 'sec')\n",
+    "print(sys.getsizeof(ds2))\n",
+    "ds2['elevation'].nbytes/(1024 ** 3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "-4008\n",
+      "-4311\n",
+      "-4805\n",
+      "-4770\n",
+      "-3752\n",
+      "-3739\n",
+      "-3761\n",
+      "-3691\n",
+      "-3840\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(ds.sel(lat=23.326173, lon=123.978125, method='nearest')['elevation'].values)\n",
+    "print(ds.sel(lat=23.317670, lon=123.973958, method='nearest')['elevation'].values)\n",
+    "print(ds.sel(lat=21.336378, lon=123.003125, method='nearest')['elevation'].values)\n",
+    "print(ds.sel(lat=21.33, lon=123.0, method='nearest')['elevation'].values)\n",
+    "print(ds[\"elevation\"].values[27200,72956]) #this is correct value (got depth = -3729)\n",
+    "print(ds[\"elevation\"].values[27200,72957])\n",
+    "print(ds[\"elevation\"].values[27200,72955])\n",
+    "print(ds[\"elevation\"].values[27201,72956])\n",
+    "print(ds[\"elevation\"].values[27199,72956]) #But we got -3813, this is: after subset got a latitude offset 1? why (in zprofile01.ipynb correct it)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Slicing time for chunk-60:  0.006575822830200195 sec\n",
+      "Slicing time for larger chunk:  0.005826711654663086 sec\n",
+      "Exe time for smaller chunk:  0.0052683353424072266 sec\n"
+     ]
+    }
+   ],
+   "source": [
+    "#The following try different subsetting and index methods\n",
+    "st = time.time()\n",
+    "ds_s1 = ds.sel(lon=slice(105, 135), lat=slice(2, 35)) \n",
+    "ds_s1.close() #try if it can close\n",
+    "et = time.time()\n",
+    "print('Slicing time for chunk-60: ', et-st, 'sec')\n",
+    "\n",
+    "st = time.time()\n",
+    "ds_s2 = ds2.sel(lon=slice(105, 135), lat=slice(2, 35)) \n",
+    "ds_s2.close() #try if it can close\n",
+    "et = time.time()\n",
+    "print('Slicing time for larger chunk: ', et-st, 'sec')\n",
+    "\n",
+    "st = time.time()\n",
+    "ds_s3 = ds3.sel(lon=slice(105, 135), lat=slice(2, 35)) \n",
+    "ds_s3.close() #try if it can close\n",
+    "et = time.time()\n",
+    "print('Exe time for smaller chunk: ', et-st, 'sec')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.1062154769897461"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_s1['elevation'].nbytes/(1024 ** 3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
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+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
+       "Dimensions:    (lon: 7200, lat: 7920)\n",
+       "Coordinates:\n",
+       "  * lon        (lon) float64 105.0 105.0 105.0 105.0 ... 135.0 135.0 135.0 135.0\n",
+       "  * lat        (lat) float64 2.002 2.006 2.01 2.015 ... 34.99 34.99 34.99 35.0\n",
+       "Data variables:\n",
+       "    crs        |S1 ...\n",
+       "    elevation  (lat, lon) int16 dask.array&lt;chunksize=(7920, 7200), meta=np.ndarray&gt;\n",
+       "Attributes: (12/36)\n",
+       "    title:                           The GEBCO_2022 Grid - a continuous terra...\n",
+       "    summary:                         The GEBCO_2022 Grid is a continuous, glo...\n",
+       "    keywords:                        BATHYMETRY/SEAFLOOR TOPOGRAPHY, DIGITAL ...\n",
+       "    Conventions:                     CF-1.6, ACDD-1.3\n",
+       "    id:                              DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c8...\n",
+       "    naming_authority:                https://dx.doi.org\n",
+       "    ...                              ...\n",
+       "    geospatial_vertical_units:       meters\n",
+       "    geospatial_vertical_resolution:  1.0\n",
+       "    geospatial_vertical_positive:    up\n",
+       "    identifier_product_doi:          DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c8...\n",
+       "    references:                      DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c8...\n",
+       "    node_offset:                     1.0</pre><div class='xr-wrap' hidden><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-5d64e4ef-29b9-4a87-9945-b74cd9f500bc' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5d64e4ef-29b9-4a87-9945-b74cd9f500bc' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lon</span>: 7200</li><li><span class='xr-has-index'>lat</span>: 7920</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-830255de-6beb-436b-9b78-0e4079cde244' class='xr-section-summary-in' type='checkbox'  checked><label for='section-830255de-6beb-436b-9b78-0e4079cde244' 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 class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>105.0 105.0 105.0 ... 135.0 135.0</div><input id='attrs-695f8fc4-70dd-4622-8f8d-673c681a4ebc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-695f8fc4-70dd-4622-8f8d-673c681a4ebc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8af14c85-2fb3-4957-b018-62cdc624d5a6' class='xr-var-data-in' type='checkbox'><label for='data-8af14c85-2fb3-4957-b018-62cdc624d5a6' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>sdn_parameter_urn :</span></dt><dd>SDN:P01::ALONZZ01</dd><dt><span>sdn_parameter_name :</span></dt><dd>Longitude east</dd><dt><span>sdn_uom_urn :</span></dt><dd>SDN:P06::DEGE</dd><dt><span>sdn_uom_name :</span></dt><dd>Degrees east</dd></dl></div><div class='xr-var-data'><pre>array([105.002083, 105.00625 , 105.010417, ..., 134.989583, 134.99375 ,\n",
+       "       134.997917])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.002 2.006 2.01 ... 34.99 35.0</div><input id='attrs-252c09ae-d9a6-412c-a99e-a540ee14bbc4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-252c09ae-d9a6-412c-a99e-a540ee14bbc4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-01365b4f-5fa3-4e68-8b55-d4f491b0af2e' class='xr-var-data-in' type='checkbox'><label for='data-01365b4f-5fa3-4e68-8b55-d4f491b0af2e' 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>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>sdn_parameter_urn :</span></dt><dd>SDN:P01::ALATZZ01</dd><dt><span>sdn_parameter_name :</span></dt><dd>Latitude north</dd><dt><span>sdn_uom_urn :</span></dt><dd>SDN:P06::DEGN</dd><dt><span>sdn_uom_name :</span></dt><dd>Degrees north</dd></dl></div><div class='xr-var-data'><pre>array([ 2.002083,  2.00625 ,  2.010417, ..., 34.989583, 34.99375 , 34.997917])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-bad99005-5590-422f-9dc6-f068d24f2000' class='xr-section-summary-in' type='checkbox'  checked><label for='section-bad99005-5590-422f-9dc6-f068d24f2000' class='xr-section-summary' >Data variables: <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>crs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>|S1</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-60b7ac49-66c9-4d07-b075-ab16cfc195a7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-60b7ac49-66c9-4d07-b075-ab16cfc195a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dab2cc4d-942e-4d00-81b0-dd3bb4cc2f77' class='xr-var-data-in' type='checkbox'><label for='data-dab2cc4d-942e-4d00-81b0-dd3bb4cc2f77' 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>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>epsg_code :</span></dt><dd>EPSG:4326</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd></dl></div><div class='xr-var-data'><pre>array(b&#x27;&#x27;, dtype=&#x27;|S1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>elevation</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(7920, 7200), meta=np.ndarray&gt;</div><input id='attrs-5e6e806d-07f4-4534-a1e3-c4f900d206ac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5e6e806d-07f4-4534-a1e3-c4f900d206ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2fb102c6-fbf1-42e9-9103-b0600b56b813' class='xr-var-data-in' type='checkbox'><label for='data-2fb102c6-fbf1-42e9-9103-b0600b56b813' 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>standard_name :</span></dt><dd>height_above_mean_sea_level</dd><dt><span>long_name :</span></dt><dd>Elevation relative to sea level</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>sdn_parameter_urn :</span></dt><dd>SDN:P01::ALATZZ01</dd><dt><span>sdn_parameter_name :</span></dt><dd>Sea floor height (above mean sea level) {bathymetric height}</dd><dt><span>sdn_uom_urn :</span></dt><dd>SDN:P06::ULAA</dd><dt><span>sdn_uom_name :</span></dt><dd>Metres</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 108.76 MiB </td>\n",
+       "                        <td> 108.76 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (7920, 7200) </td>\n",
+       "                        <td> (7920, 7200) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> int16 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"159\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"109\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"109\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"109\" y1=\"0\" x2=\"109\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 109.09090909090908,0.0 109.09090909090908,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"54.545455\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >7200</text>\n",
+       "  <text x=\"129.090909\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,129.090909,60.000000)\">7920</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-6fe8b7f1-5238-43f6-ab42-5151cc15f013' class='xr-section-summary-in' type='checkbox'  ><label for='section-6fe8b7f1-5238-43f6-ab42-5151cc15f013' class='xr-section-summary' >Attributes: <span>(36)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>title :</span></dt><dd>The GEBCO_2022 Grid - a continuous terrain model for oceans and land at 15 arc-second intervals</dd><dt><span>summary :</span></dt><dd>The GEBCO_2022 Grid is a continuous, global terrain model for ocean and land with a spatial resolution of 15 arc seconds.The grid uses as a base-map Version 2.4 of the SRTM15+ data set (Tozer et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. It is augmented with gridded bathymetric data sets developed as part of the Nippon Foundation-GEBCO Seabed 2030 Project.</dd><dt><span>keywords :</span></dt><dd>BATHYMETRY/SEAFLOOR TOPOGRAPHY, DIGITAL ELEVATION/DIGITAL TERRAIN MODELS</dd><dt><span>Conventions :</span></dt><dd>CF-1.6, ACDD-1.3</dd><dt><span>id :</span></dt><dd>DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c86abc0289c</dd><dt><span>naming_authority :</span></dt><dd>https://dx.doi.org</dd><dt><span>history :</span></dt><dd>Information on the development of the data set and the source data sets included in the grid can be found in the data set documentation available from https://www.gebco.net</dd><dt><span>source :</span></dt><dd>The GEBCO_2022 Grid is the latest global bathymetric product released by the General Bathymetric Chart of the Oceans (GEBCO) and has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and GEBCO. The Seabed 2030 Project aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor and make it available to all.</dd><dt><span>comment :</span></dt><dd>The data in the GEBCO_2022 Grid should not be used for navigation or any purpose relating to safety at sea.</dd><dt><span>license :</span></dt><dd>The GEBCO Grid is placed in the public domain and may be used free of charge. Use of the GEBCO Grid indicates that the user accepts the conditions of use and disclaimer information: https://www.gebco.net/data_and_products/gridded_bathymetry_data/gebco_2019/grid_terms_of_use.html</dd><dt><span>date_created :</span></dt><dd>2022-06-22</dd><dt><span>creator_name :</span></dt><dd>GEBCO through the Nippon Foundation-GEBCO Seabed 2030 Project</dd><dt><span>creator_email :</span></dt><dd>gdacc@seabed2030.org</dd><dt><span>creator_url :</span></dt><dd>https://www.gebco.net</dd><dt><span>institution :</span></dt><dd>On behalf of the General Bathymetric Chart of the Oceans (GEBCO), the data are held at the British Oceanographic Data Centre (BODC).</dd><dt><span>project :</span></dt><dd>Nippon Foundation - GEBCO Seabed2030 Project</dd><dt><span>creator_type :</span></dt><dd>International organisation</dd><dt><span>geospatial_bounds :</span></dt><dd>[-180.  -90.  180.   90.]</dd><dt><span>geospatial_bounds_crs :</span></dt><dd>WGS84</dd><dt><span>geospatial_bounds_vertical_crs :</span></dt><dd>EPSG:5831</dd><dt><span>geospatial_lat_min :</span></dt><dd>-90.0</dd><dt><span>geospatial_lat_max :</span></dt><dd>90.0</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees_north</dd><dt><span>geospatial_lat_resolution :</span></dt><dd>0.004166666666666667</dd><dt><span>geospatial_lon_min :</span></dt><dd>-180.0</dd><dt><span>geospatial_lon_max :</span></dt><dd>180.0</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees_east</dd><dt><span>geospatial_lon_resolution :</span></dt><dd>0.004166666666666667</dd><dt><span>geospatial_vertical_min :</span></dt><dd>-10977.0</dd><dt><span>geospatial_vertical_max :</span></dt><dd>8685.0</dd><dt><span>geospatial_vertical_units :</span></dt><dd>meters</dd><dt><span>geospatial_vertical_resolution :</span></dt><dd>1.0</dd><dt><span>geospatial_vertical_positive :</span></dt><dd>up</dd><dt><span>identifier_product_doi :</span></dt><dd>DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c86abc0289c</dd><dt><span>references :</span></dt><dd>DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c86abc0289c</dd><dt><span>node_offset :</span></dt><dd>1.0</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset>\n",
+       "Dimensions:    (lon: 7200, lat: 7920)\n",
+       "Coordinates:\n",
+       "  * lon        (lon) float64 105.0 105.0 105.0 105.0 ... 135.0 135.0 135.0 135.0\n",
+       "  * lat        (lat) float64 2.002 2.006 2.01 2.015 ... 34.99 34.99 34.99 35.0\n",
+       "Data variables:\n",
+       "    crs        |S1 ...\n",
+       "    elevation  (lat, lon) int16 dask.array<chunksize=(7920, 7200), meta=np.ndarray>\n",
+       "Attributes: (12/36)\n",
+       "    title:                           The GEBCO_2022 Grid - a continuous terra...\n",
+       "    summary:                         The GEBCO_2022 Grid is a continuous, glo...\n",
+       "    keywords:                        BATHYMETRY/SEAFLOOR TOPOGRAPHY, DIGITAL ...\n",
+       "    Conventions:                     CF-1.6, ACDD-1.3\n",
+       "    id:                              DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c8...\n",
+       "    naming_authority:                https://dx.doi.org\n",
+       "    ...                              ...\n",
+       "    geospatial_vertical_units:       meters\n",
+       "    geospatial_vertical_resolution:  1.0\n",
+       "    geospatial_vertical_positive:    up\n",
+       "    identifier_product_doi:          DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c8...\n",
+       "    references:                      DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c8...\n",
+       "    node_offset:                     1.0"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#da1 = getattr(ds_s1, 'elevation')\n",
+    "#da1\n",
+    "#https://www.programcreek.com/python/example/123571/xarray.decode_cf\n",
+    "#da1.attrs['_Unsigned']='false'\n",
+    "ds_s1\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#da1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Exe time:  0.009853124618530273 sec\n",
+      "[[-121 -119 -116 -111 -106 -101  -94  -88  -82  -76]\n",
+      " [-123 -121 -119 -115 -109 -103  -97  -91  -86  -79]\n",
+      " [-126 -124 -122 -118 -113 -106 -100  -95  -88  -83]\n",
+      " [-127 -127 -126 -123 -116 -110 -103  -97  -91  -86]\n",
+      " [-127 -127 -128 -126 -118 -112 -106  -99  -94  -88]\n",
+      " [-127 -127 -126 -125 -119 -113 -107 -102  -96  -91]\n",
+      " [-127 -127 -126 -123 -118 -113 -108 -103  -99  -94]\n",
+      " [-126 -125 -124 -122 -118 -113 -109 -104 -100  -96]\n",
+      " [-125 -124 -123 -120 -118 -114 -110 -107 -102  -98]\n",
+      " [-123 -123 -121 -120 -118 -114 -112 -108 -104 -100]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "st = time.time()\n",
+    "st1 = ds_s1.isel(lon=slice(1000, 1010), lat=slice(2000, 2010))\n",
+    "xt1 = st1['elevation'].values\n",
+    "et = time.time()\n",
+    "print('Exe time: ', et-st, 'sec')\n",
+    "print(xt1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(10, 10)\n",
+      "3.1 Get index of point by two subsetting time:  0.004407644271850586 sec\n",
+      "[[3 4]\n",
+      " [1 2]]\n",
+      "(array([3, 1]), array([4, 2]))\n",
+      "3.2 Get index of point by numpy ix_ time:  0.002244710922241211 sec\n",
+      "[-116, -119]\n",
+      "[-116 -119]\n"
+     ]
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "print(st1[\"elevation\"].shape)\n",
+    "st = time.time()\n",
+    "pt1 = [st1[\"elevation\"].values[3,4], st1[\"elevation\"].values[1,2]]\n",
+    "et = time.time()\n",
+    "print('3.1 Get index of point by two subsetting time: ', et-st, 'sec')\n",
+    "\n",
+    "st = time.time()\n",
+    "#pt2 = st1[\"elevation\"].values[np.ix_([3,4],[1,2])]\n",
+    "idx_arr = np.array([[3,4],[1,2]])\n",
+    "print(idx_arr)\n",
+    "print(tuple(idx_arr.T))\n",
+    "#https://stackoverflow.com/questions/43034563/numpy-array-of-multiple-indices-replace-with-a-different-matrix\n",
+    "pt2=st1['elevation'].values[tuple(idx_arr.T)]\n",
+    "et = time.time()\n",
+    "print('3.2 Get index of point by numpy ix_ time: ', et-st, 'sec')\n",
+    "print(pt1)\n",
+    "print(pt2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#slow\n",
+    "x = xr.DataArray([-45,-44.95833,-44,-43.95822], dims=['longitude'])\n",
+    "y = xr.DataArray([35,35.004167,36,36.004168], dims=['latitude'])\n",
+    "st = time.time()\n",
+    "#ds_s2 = ds.sel(lon=x, lat=y, method='nearest')  \n",
+    "et = time.time()\n",
+    "#print('Exe time: ', et-st, 'sec')\n",
+    "#print(ds_s2)               \n",
+    "#print(ds_s2['elevation'].values)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#https://stackoverflow.com/questions/58706834/angled-slice-in-xarray\n",
+    "startLat = 35.0\n",
+    "startLon = -45.0\n",
+    "endLat = 36.0\n",
+    "endLon = -43.0\n",
+    "n = 3600/15 #15 arc-second\n",
+    "# not work, need another dimension to project\n",
+    "#x = xr.DataArray(np.linspace(startLon,endLon,n), dims='z')\n",
+    "#y = xr.DataArray(np.linspace(startLat,endLat,n), dims='z')\n",
+    "#st = time.time()\n",
+    "#ds_s3 = ds.interp(lon=x, lat=y, method='linear')\n",
+    "#et = time.time()\n",
+    "#print('Exe time: ', et-st, 'sec')\n",
+    "#print(ds_s3)               \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import orjson\n",
+    "import json\n",
+    "st = time.time()\n",
+    "jt1 = orjson.dumps(xt1.tolist(), option=orjson.OPT_NAIVE_UTC | orjson.OPT_SERIALIZE_NUMPY)\n",
+    "et = time.time()\n",
+    "print('4.1 Convert JSON by orjson time: ', et-st, 'sec')\n",
+    "st = time.time()\n",
+    "jt2 = json.dumps(xt1.tolist())\n",
+    "et = time.time()\n",
+    "print('4.2 Convert JSON by json.dump time: ', et-st, 'sec')\n",
+    "\n",
+    "print(jt1)\n",
+    "print(jt2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds.close()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import zarr\n",
+    "import dask"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<dask.config.set at 0x7efbd97829d0>"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#compressor = zarr.Blosc(cname='zstd', clevel=3, shuffle=2)\n",
+    "dask.config.set(scheduler='single-threaded')\n",
+    "#da = getattr(ds, 'elevation')\n",
+    "#https://www.programcreek.com/python/example/123571/xarray.decode_cf\n",
+    "#da.attrs['_Unsigned']='false'\n",
+    "#ds3 #### try 0:30 chunk #### not work\n",
+    "#In GEBCO_2022 it works but in GEBCO_2023, it encounter ValueError: Codec does not support buffers of > 2147483647 bytes\n",
+    "# https://chat.openai.com/c/67eaa069-b863-4924-9f56-1a1ef98c8b79 \n",
+    "#ds.to_zarr('../data/GEBCO_2023_sub_ice_topo.zarr', mode='w',\n",
+    "#           #encoding={\"elevation\": {\"_Unsigned\": \"false\"}},\n",
+    "#           group='gebco') ##compute=False, , encoding={'gebbco': {'compressor': compressor}})\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "##import xarray as xr\n",
+    "##import zarr\n",
+    "#from numcodecs import Zlib\n",
+    "\n",
+    "## Open your dataset\n",
+    "#ds = xr.open_mfdataset('../data_src/GEBCO_2023_sub_ice_topo.nc', chunks={0: 60, 1: 60}, \n",
+    "#                       decode_cf=False, decode_times=False)\n",
+    "\n",
+    "## Specify the compressor\n",
+    "#compressor = Zlib(level=1)  # Level can be adjusted for compression speed vs ratio\n",
+    "\n",
+    "## Update encoding for each variable in dataset\n",
+    "#encoding = {var: {'compressor': compressor} for var in ds.data_vars}\n",
+    "\n",
+    "## Convert to Zarr\n",
+    "#ds.to_zarr('../data/GEBCO_2023_sub_ice_topo_compressor.zarr', mode='w', group='gebco', encoding=encoding)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#import xarray as xr\n",
+    "#import zarr\n",
+    "from numcodecs import Zlib\n",
+    "#from numcodecs import Blosc\n",
+    "\n",
+    "\n",
+    "# Open your dataset from NetCDF\n",
+    "ds = xr.open_mfdataset('../data_src/GEBCO_2023_sub_ice_topo.nc', chunks={0: 60, 1: 60}, \n",
+    "                       decode_cf=False, decode_times=False)\n",
+    "\n",
+    "# Specify the compressor\n",
+    "compressor = Zlib(level=1)  # Level can be adjusted for compression speed vs ratio\n",
+    "\n",
+    "# Define the Blosc compressor\n",
+    "# blosc_compressor = Blosc(cname='lz4', clevel=5, shuffle=Blosc.SHUFFLE, blocksize=0)\n",
+    "\n",
+    "# Apply the Blosc compressor to all variables\n",
+    "\n",
+    "# Convert to Zarr without specifying a group, and with the new encoding\n",
+    "# Update encoding for each variable in dataset\n",
+    "encoding = {var: {'compressor': compressor} for var in ds.data_vars}\n",
+    "#encoding = {var: {'compressor': blosc_compressor} for var in ds.data_vars}\n",
+    "\n",
+    "# Convert to Zarr without specifying a group\n",
+    "ds.to_zarr('../data/GEBCO_2023_sub_ice_topo_compressor.zarr', mode='w', encoding=encoding)\n",
+    "#ds.to_zarr('../data/GEBCO_2023_sub_ice_topo.zarr', mode='w', encoding=encoding)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Dask Dashboard is available at http://localhost:8787/status\n"
+     ]
+    },
+    {
+     "ename": "TypeError",
+     "evalue": "__init__() got an unexpected keyword argument 'max_buffer_size'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[1], line 17\u001b[0m\n\u001b[1;32m     11\u001b[0m ds \u001b[39m=\u001b[39m xr\u001b[39m.\u001b[39mopen_mfdataset(\u001b[39m'\u001b[39m\u001b[39m../data_src/GEBCO_2023_sub_ice_topo.nc\u001b[39m\u001b[39m'\u001b[39m, \n\u001b[1;32m     12\u001b[0m                        \u001b[39m# chunks={'lat': 30, 'lon': 30}, #why it's too slow\u001b[39;00m\n\u001b[1;32m     13\u001b[0m                        chunks\u001b[39m=\u001b[39m{\u001b[39m0\u001b[39m: \u001b[39m60\u001b[39m, \u001b[39m1\u001b[39m: \u001b[39m60\u001b[39m},\n\u001b[1;32m     14\u001b[0m                        decode_cf\u001b[39m=\u001b[39m\u001b[39mFalse\u001b[39;00m, decode_times\u001b[39m=\u001b[39m\u001b[39mFalse\u001b[39;00m)\n\u001b[1;32m     16\u001b[0m \u001b[39m# Define the Blosc compressor\u001b[39;00m\n\u001b[0;32m---> 17\u001b[0m blosc_compressor \u001b[39m=\u001b[39m Blosc(cname\u001b[39m=\u001b[39;49m\u001b[39m'\u001b[39;49m\u001b[39mlz4\u001b[39;49m\u001b[39m'\u001b[39;49m, clevel\u001b[39m=\u001b[39;49m\u001b[39m5\u001b[39;49m, shuffle\u001b[39m=\u001b[39;49mBlosc\u001b[39m.\u001b[39;49mSHUFFLE, blocksize\u001b[39m=\u001b[39;49m\u001b[39m0\u001b[39;49m, max_buffer_size\u001b[39m=\u001b[39;49m\u001b[39m2\u001b[39;49m\u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49m\u001b[39m40\u001b[39;49m \u001b[39m-\u001b[39;49m \u001b[39m1\u001b[39;49m)\n\u001b[1;32m     19\u001b[0m \u001b[39m# Apply the Blosc compressor to all variables\u001b[39;00m\n\u001b[1;32m     20\u001b[0m encoding \u001b[39m=\u001b[39m {var: {\u001b[39m'\u001b[39m\u001b[39mcompressor\u001b[39m\u001b[39m'\u001b[39m: blosc_compressor} \u001b[39mfor\u001b[39;00m var \u001b[39min\u001b[39;00m ds\u001b[39m.\u001b[39mdata_vars}\n",
+      "File \u001b[0;32mnumcodecs/blosc.pyx:548\u001b[0m, in \u001b[0;36mnumcodecs.blosc.Blosc.__init__\u001b[0;34m()\u001b[0m\n",
+      "\u001b[0;31mTypeError\u001b[0m: __init__() got an unexpected keyword argument 'max_buffer_size'"
+     ]
+    }
+   ],
+   "source": [
+    "import xarray as xr\n",
+    "from numcodecs import Blosc\n",
+    "from dask.distributed import Client, progress\n",
+    "\n",
+    "# Start a Dask distributed client for parallel processing and monitoring\n",
+    "client = Client('tcp://localhost:8786')\n",
+    "\n",
+    "print(f\"Dask Dashboard is available at {client.dashboard_link}\")\n",
+    "\n",
+    "# Open your dataset with specified chunk sizes\n",
+    "ds = xr.open_mfdataset('../data_src/GEBCO_2023_sub_ice_topo.nc', \n",
+    "                       # chunks={'lat': 30, 'lon': 30}, #why it's too slow\n",
+    "                       chunks={0: 60, 1: 60},\n",
+    "                       decode_cf=False, decode_times=False)\n",
+    "\n",
+    "# Define the Blosc compressor\n",
+    "blosc_compressor = Blosc(cname='lz4', clevel=5, shuffle=Blosc.SHUFFLE, blocksize=0, max_buffer_size=2**40 - 1)\n",
+    "\n",
+    "# Apply the Blosc compressor to all variables\n",
+    "encoding = {var: {'compressor': blosc_compressor} for var in ds.data_vars}\n",
+    "\n",
+    "# Convert to Zarr\n",
+    "future = client.persist(ds.to_zarr('../data/GEBCO_2023_sub_ice_topo.zarr', mode='w', encoding=encoding))\n",
+    "progress(future) "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "NameError",
+     "evalue": "name 'time' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[15], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m st \u001b[39m=\u001b[39m time\u001b[39m.\u001b[39mtime()\n\u001b[1;32m      2\u001b[0m dz1 \u001b[39m=\u001b[39m xr\u001b[39m.\u001b[39mopen_zarr(\n\u001b[1;32m      3\u001b[0m     \u001b[39m'\u001b[39m\u001b[39m../data/GEBCO_2023_sub_ice_topo.zarr\u001b[39m\u001b[39m'\u001b[39m, chunks\u001b[39m=\u001b[39m\u001b[39m'\u001b[39m\u001b[39mauto\u001b[39m\u001b[39m'\u001b[39m, \n\u001b[1;32m      4\u001b[0m     group\u001b[39m=\u001b[39m\u001b[39m'\u001b[39m\u001b[39mgebco\u001b[39m\u001b[39m'\u001b[39m, decode_cf\u001b[39m=\u001b[39m\u001b[39mFalse\u001b[39;00m, decode_times\u001b[39m=\u001b[39m\u001b[39mFalse\u001b[39;00m)\n\u001b[1;32m      6\u001b[0m et \u001b[39m=\u001b[39m time\u001b[39m.\u001b[39mtime()\n",
+      "\u001b[0;31mNameError\u001b[0m: name 'time' is not defined"
+     ]
+    }
+   ],
+   "source": [
+    "st = time.time()\n",
+    "dz1 = xr.open_zarr(\n",
+    "    '../data/GEBCO_2023_sub_ice_topo.zarr', chunks='auto', \n",
+    "    group='gebco', decode_cf=False, decode_times=False)\n",
+    "\n",
+    "et = time.time()\n",
+    "print('Exe time: ', et-st, 'sec')\n",
+    "dz1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Exe time:  0.007412433624267578 sec\n"
+     ]
+    },
+    {
+     "data": {
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+       "  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",
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+       ".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",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "}\n",
+       "\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",
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+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
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+       "\n",
+       ".xr-section-summary {\n",
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+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
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+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
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+       "\n",
+       ".xr-section-summary-in + label:before {\n",
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+       "  font-size: 11px;\n",
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+       "\n",
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+       "  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",
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+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
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+       "\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",
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+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
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+       "\n",
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+       "  content: '(';\n",
+       "}\n",
+       "\n",
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+       "  content: ')';\n",
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+       "  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",
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+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
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+       "\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",
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+       "  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:    (lat: 43200, lon: 86400)\n",
+       "Coordinates:\n",
+       "  * lat        (lat) float64 -90.0 -89.99 -89.99 -89.99 ... 89.99 89.99 90.0\n",
+       "  * lon        (lon) float64 -180.0 -180.0 -180.0 -180.0 ... 180.0 180.0 180.0\n",
+       "Data variables:\n",
+       "    elevation  (lat, lon) int16 dask.array&lt;chunksize=(43200, 86400), meta=np.ndarray&gt;\n",
+       "Attributes:\n",
+       "    Conventions:  CF-1.6\n",
+       "    comment:      The data in the GEBCO_2020 Grid should not be used for navi...\n",
+       "    history:      Information on the development of the data set and the sour...\n",
+       "    institution:  On behalf of the General Bathymetric Chart of the Oceans (G...\n",
+       "    node_offset:  1.0\n",
+       "    references:   DOI: 10.5285/836f016a-33be-6ddc-e053-6c86abc0788e\n",
+       "    source:       The GEBCO_2020 Grid is the latest global bathymetric produc...\n",
+       "    title:        The GEBCO_2020 Grid - a continuous terrain model for oceans...</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-38fcac3f-5086-4ad5-8d38-4ff93ddd1f67' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-38fcac3f-5086-4ad5-8d38-4ff93ddd1f67' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 43200</li><li><span class='xr-has-index'>lon</span>: 86400</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-8d805965-33a5-4115-8acc-ab2b01bd486a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8d805965-33a5-4115-8acc-ab2b01bd486a' 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 class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.99 -89.99 ... 89.99 90.0</div><input id='attrs-e9118613-4926-4349-b9d9-de9827f1a0b3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e9118613-4926-4349-b9d9-de9827f1a0b3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-90fca54e-84ed-49a4-8f71-42457b031074' class='xr-var-data-in' type='checkbox'><label for='data-90fca54e-84ed-49a4-8f71-42457b031074' 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>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>sdn_parameter_name :</span></dt><dd>Latitude north</dd><dt><span>sdn_parameter_urn :</span></dt><dd>SDN:P01::ALATZZ01</dd><dt><span>sdn_uom_name :</span></dt><dd>Degrees north</dd><dt><span>sdn_uom_urn :</span></dt><dd>SDN:P06::DEGN</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>_FillValue :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([-89.997917, -89.99375 , -89.989583, ...,  89.989583,  89.99375 ,\n",
+       "        89.997917])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -180.0 ... 180.0 180.0</div><input id='attrs-1472c868-79c2-4cd8-93ac-67f495b0bb4e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1472c868-79c2-4cd8-93ac-67f495b0bb4e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-85f0691f-5566-40d0-aff4-27c97cbdd1f0' class='xr-var-data-in' type='checkbox'><label for='data-85f0691f-5566-40d0-aff4-27c97cbdd1f0' 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>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>sdn_parameter_name :</span></dt><dd>Longitude east</dd><dt><span>sdn_parameter_urn :</span></dt><dd>SDN:P01::ALONZZ01</dd><dt><span>sdn_uom_name :</span></dt><dd>Degrees east</dd><dt><span>sdn_uom_urn :</span></dt><dd>SDN:P06::DEGE</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>_FillValue :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([-179.997917, -179.99375 , -179.989583, ...,  179.989583,  179.99375 ,\n",
+       "        179.997917])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7c5d1056-aef5-42b9-b08d-e995a3275a13' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7c5d1056-aef5-42b9-b08d-e995a3275a13' 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>elevation</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(43200, 86400), meta=np.ndarray&gt;</div><input id='attrs-8319d57f-b838-480d-9b7a-82cc4cceced6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8319d57f-b838-480d-9b7a-82cc4cceced6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-88c597e7-723e-45c5-a39e-cbc98d45bf88' class='xr-var-data-in' type='checkbox'><label for='data-88c597e7-723e-45c5-a39e-cbc98d45bf88' 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>long_name :</span></dt><dd>Elevation relative to sea level</dd><dt><span>sdn_parameter_name :</span></dt><dd>Sea floor height (above mean sea level) {bathymetric height}</dd><dt><span>sdn_parameter_urn :</span></dt><dd>SDN:P01::ALATZZ01</dd><dt><span>sdn_uom_name :</span></dt><dd>Metres</dd><dt><span>sdn_uom_urn :</span></dt><dd>SDN:P06::ULAA</dd><dt><span>standard_name :</span></dt><dd>height_above_reference_ellipsoid</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.95 GiB </td>\n",
+       "                        <td> 6.95 GiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (43200, 86400) </td>\n",
+       "                        <td> (43200, 86400) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> int16 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"110\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
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+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"60\" style=\"stroke-width:2\" />\n",
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+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"80.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >86400</text>\n",
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+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-4a731010-122d-4255-9bf1-5abe6cf7ee4f' class='xr-section-summary-in' type='checkbox'  ><label for='section-4a731010-122d-4255-9bf1-5abe6cf7ee4f' class='xr-section-summary' >Indexes: <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-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4e2b1e80-67b6-4f07-89c1-3db1a4bd2874' class='xr-index-data-in' type='checkbox'/><label for='index-4e2b1e80-67b6-4f07-89c1-3db1a4bd2874' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-89.99791666666667,          -89.99375, -89.98958333333333,\n",
+       "       -89.98541666666667,          -89.98125, -89.97708333333334,\n",
+       "       -89.97291666666666,          -89.96875, -89.96458333333334,\n",
+       "       -89.96041666666666,\n",
+       "       ...\n",
+       "        89.96041666666667,  89.96458333333334,           89.96875,\n",
+       "        89.97291666666666,  89.97708333333333,  89.98124999999999,\n",
+       "        89.98541666666665,  89.98958333333334,           89.99375,\n",
+       "        89.99791666666667],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=43200))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-132af578-d100-490e-b15e-7f78aece2c2d' class='xr-index-data-in' type='checkbox'/><label for='index-132af578-d100-490e-b15e-7f78aece2c2d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-179.99791666666667,          -179.99375, -179.98958333333334,\n",
+       "       -179.98541666666668,          -179.98125, -179.97708333333333,\n",
+       "       -179.97291666666666,          -179.96875, -179.96458333333334,\n",
+       "       -179.96041666666667,\n",
+       "       ...\n",
+       "        179.96041666666667,  179.96458333333334,           179.96875,\n",
+       "        179.97291666666666,  179.97708333333333,           179.98125,\n",
+       "        179.98541666666665,  179.98958333333331,  179.99374999999998,\n",
+       "        179.99791666666667],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=86400))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-66447db5-2a37-4e07-931c-f79b6681b3aa' class='xr-section-summary-in' type='checkbox'  checked><label for='section-66447db5-2a37-4e07-931c-f79b6681b3aa' class='xr-section-summary' >Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>comment :</span></dt><dd>The data in the GEBCO_2020 Grid should not be used for navigation or any purpose relating to safety at sea.</dd><dt><span>history :</span></dt><dd>Information on the development of the data set and the source data sets included in the grid can be found in the data set documentation available from https://www.gebco.net</dd><dt><span>institution :</span></dt><dd>On behalf of the General Bathymetric Chart of the Oceans (GEBCO), the data are held at the British Oceanographic Data Centre (BODC).</dd><dt><span>node_offset :</span></dt><dd>1.0</dd><dt><span>references :</span></dt><dd>DOI: 10.5285/836f016a-33be-6ddc-e053-6c86abc0788e</dd><dt><span>source :</span></dt><dd>The GEBCO_2020 Grid is the latest global bathymetric product released by the General Bathymetric Chart of the Oceans (GEBCO) and has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and GEBCO. The Seabed 2030 Project aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor and make it available to all.</dd><dt><span>title :</span></dt><dd>The GEBCO_2020 Grid - a continuous terrain model for oceans and land at 15 arc-second intervals</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset>\n",
+       "Dimensions:    (lat: 43200, lon: 86400)\n",
+       "Coordinates:\n",
+       "  * lat        (lat) float64 -90.0 -89.99 -89.99 -89.99 ... 89.99 89.99 90.0\n",
+       "  * lon        (lon) float64 -180.0 -180.0 -180.0 -180.0 ... 180.0 180.0 180.0\n",
+       "Data variables:\n",
+       "    elevation  (lat, lon) int16 dask.array<chunksize=(43200, 86400), meta=np.ndarray>\n",
+       "Attributes:\n",
+       "    Conventions:  CF-1.6\n",
+       "    comment:      The data in the GEBCO_2020 Grid should not be used for navi...\n",
+       "    history:      Information on the development of the data set and the sour...\n",
+       "    institution:  On behalf of the General Bathymetric Chart of the Oceans (G...\n",
+       "    node_offset:  1.0\n",
+       "    references:   DOI: 10.5285/836f016a-33be-6ddc-e053-6c86abc0788e\n",
+       "    source:       The GEBCO_2020 Grid is the latest global bathymetric produc...\n",
+       "    title:        The GEBCO_2020 Grid - a continuous terrain model for oceans..."
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "st = time.time()\n",
+    "dz2 = xr.open_zarr(\n",
+    "    '../data/GEBCO_2023_sub_ice_topo_compressor.zarr', chunks='auto', \n",
+    "    group='gebco', decode_cf=False, decode_times=False)\n",
+    "\n",
+    "et = time.time()\n",
+    "print('Exe time: ', et-st, 'sec')\n",
+    "dz2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "ValueError",
+     "evalue": "Codec does not support buffers of > 2147483647 bytes",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[39], line 13\u001b[0m\n\u001b[1;32m     10\u001b[0m encoding \u001b[39m=\u001b[39m {var: {\u001b[39m'\u001b[39m\u001b[39mcompressor\u001b[39m\u001b[39m'\u001b[39m: blosc_compressor} \u001b[39mfor\u001b[39;00m var \u001b[39min\u001b[39;00m ds\u001b[39m.\u001b[39mdata_vars}\n\u001b[1;32m     12\u001b[0m \u001b[39m# Convert to Zarr without specifying a group, and with the new encoding\u001b[39;00m\n\u001b[0;32m---> 13\u001b[0m ds_compress\u001b[39m.\u001b[39;49mto_zarr(\u001b[39m'\u001b[39;49m\u001b[39m../data/GEBCO_2023_sub_ice_topo.zarr\u001b[39;49m\u001b[39m'\u001b[39;49m, mode\u001b[39m=\u001b[39;49m\u001b[39m'\u001b[39;49m\u001b[39mw\u001b[39;49m\u001b[39m'\u001b[39;49m, encoding\u001b[39m=\u001b[39;49mencoding)\n\u001b[1;32m     14\u001b[0m            \u001b[39m#encoding={\"elevation\": {\"_Unsigned\": \"false\"}},\u001b[39;00m\n\u001b[1;32m     15\u001b[0m            \u001b[39m#group='gebco') \u001b[39;00m\n",
+      "File \u001b[0;32m~/.pyenv/versions/3.11.3/envs/py311/lib/python3.11/site-packages/xarray/core/dataset.py:2497\u001b[0m, in \u001b[0;36mDataset.to_zarr\u001b[0;34m(self, store, chunk_store, mode, synchronizer, group, encoding, compute, consolidated, append_dim, region, safe_chunks, storage_options, zarr_version, write_empty_chunks, chunkmanager_store_kwargs)\u001b[0m\n\u001b[1;32m   2359\u001b[0m \u001b[39m\u001b[39m\u001b[39m\"\"\"Write dataset contents to a zarr group.\u001b[39;00m\n\u001b[1;32m   2360\u001b[0m \n\u001b[1;32m   2361\u001b[0m \u001b[39mZarr chunks are determined in the following way:\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   2493\u001b[0m \u001b[39m    The I/O user guide, with more details and examples.\u001b[39;00m\n\u001b[1;32m   2494\u001b[0m \u001b[39m\"\"\"\u001b[39;00m\n\u001b[1;32m   2495\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mxarray\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mbackends\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mapi\u001b[39;00m \u001b[39mimport\u001b[39;00m to_zarr\n\u001b[0;32m-> 2497\u001b[0m \u001b[39mreturn\u001b[39;00m to_zarr(  \u001b[39m# type: ignore[call-overload,misc]\u001b[39;49;00m\n\u001b[1;32m   2498\u001b[0m     \u001b[39mself\u001b[39;49m,\n\u001b[1;32m   2499\u001b[0m     store\u001b[39m=\u001b[39;49mstore,\n\u001b[1;32m   2500\u001b[0m     chunk_store\u001b[39m=\u001b[39;49mchunk_store,\n\u001b[1;32m   2501\u001b[0m     storage_options\u001b[39m=\u001b[39;49mstorage_options,\n\u001b[1;32m   2502\u001b[0m     mode\u001b[39m=\u001b[39;49mmode,\n\u001b[1;32m   2503\u001b[0m     synchronizer\u001b[39m=\u001b[39;49msynchronizer,\n\u001b[1;32m   2504\u001b[0m     group\u001b[39m=\u001b[39;49mgroup,\n\u001b[1;32m   2505\u001b[0m     encoding\u001b[39m=\u001b[39;49mencoding,\n\u001b[1;32m   2506\u001b[0m     compute\u001b[39m=\u001b[39;49mcompute,\n\u001b[1;32m   2507\u001b[0m     consolidated\u001b[39m=\u001b[39;49mconsolidated,\n\u001b[1;32m   2508\u001b[0m     append_dim\u001b[39m=\u001b[39;49mappend_dim,\n\u001b[1;32m   2509\u001b[0m     region\u001b[39m=\u001b[39;49mregion,\n\u001b[1;32m   2510\u001b[0m     safe_chunks\u001b[39m=\u001b[39;49msafe_chunks,\n\u001b[1;32m   2511\u001b[0m     zarr_version\u001b[39m=\u001b[39;49mzarr_version,\n\u001b[1;32m   2512\u001b[0m     write_empty_chunks\u001b[39m=\u001b[39;49mwrite_empty_chunks,\n\u001b[1;32m   2513\u001b[0m     chunkmanager_store_kwargs\u001b[39m=\u001b[39;49mchunkmanager_store_kwargs,\n\u001b[1;32m   2514\u001b[0m )\n",
+      "File \u001b[0;32m~/.pyenv/versions/3.11.3/envs/py311/lib/python3.11/site-packages/xarray/backends/api.py:1775\u001b[0m, in \u001b[0;36mto_zarr\u001b[0;34m(dataset, store, chunk_store, mode, synchronizer, group, encoding, compute, consolidated, append_dim, region, safe_chunks, storage_options, zarr_version, write_empty_chunks, chunkmanager_store_kwargs)\u001b[0m\n\u001b[1;32m   1773\u001b[0m \u001b[39m# TODO: figure out how to properly handle unlimited_dims\u001b[39;00m\n\u001b[1;32m   1774\u001b[0m dump_to_store(dataset, zstore, writer, encoding\u001b[39m=\u001b[39mencoding)\n\u001b[0;32m-> 1775\u001b[0m writes \u001b[39m=\u001b[39m writer\u001b[39m.\u001b[39;49msync(\n\u001b[1;32m   1776\u001b[0m     compute\u001b[39m=\u001b[39;49mcompute, chunkmanager_store_kwargs\u001b[39m=\u001b[39;49mchunkmanager_store_kwargs\n\u001b[1;32m   1777\u001b[0m )\n\u001b[1;32m   1779\u001b[0m \u001b[39mif\u001b[39;00m compute:\n\u001b[1;32m   1780\u001b[0m     _finalize_store(writes, zstore)\n",
+      "File \u001b[0;32m~/.pyenv/versions/3.11.3/envs/py311/lib/python3.11/site-packages/xarray/backends/common.py:256\u001b[0m, in \u001b[0;36mArrayWriter.sync\u001b[0;34m(self, compute, chunkmanager_store_kwargs)\u001b[0m\n\u001b[1;32m    253\u001b[0m \u001b[39mif\u001b[39;00m chunkmanager_store_kwargs \u001b[39mis\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[1;32m    254\u001b[0m     chunkmanager_store_kwargs \u001b[39m=\u001b[39m {}\n\u001b[0;32m--> 256\u001b[0m delayed_store \u001b[39m=\u001b[39m chunkmanager\u001b[39m.\u001b[39;49mstore(\n\u001b[1;32m    257\u001b[0m     \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49msources,\n\u001b[1;32m    258\u001b[0m     \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mtargets,\n\u001b[1;32m    259\u001b[0m     lock\u001b[39m=\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mlock,\n\u001b[1;32m    260\u001b[0m     compute\u001b[39m=\u001b[39;49mcompute,\n\u001b[1;32m    261\u001b[0m     flush\u001b[39m=\u001b[39;49m\u001b[39mTrue\u001b[39;49;00m,\n\u001b[1;32m    262\u001b[0m     regions\u001b[39m=\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mregions,\n\u001b[1;32m    263\u001b[0m     \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mchunkmanager_store_kwargs,\n\u001b[1;32m    264\u001b[0m )\n\u001b[1;32m    265\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39msources \u001b[39m=\u001b[39m []\n\u001b[1;32m    266\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mtargets \u001b[39m=\u001b[39m []\n",
+      "File \u001b[0;32m~/.pyenv/versions/3.11.3/envs/py311/lib/python3.11/site-packages/xarray/core/daskmanager.py:211\u001b[0m, in \u001b[0;36mDaskManager.store\u001b[0;34m(self, sources, targets, **kwargs)\u001b[0m\n\u001b[1;32m    203\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mstore\u001b[39m(\n\u001b[1;32m    204\u001b[0m     \u001b[39mself\u001b[39m,\n\u001b[1;32m    205\u001b[0m     sources: DaskArray \u001b[39m|\u001b[39m Sequence[DaskArray],\n\u001b[1;32m    206\u001b[0m     targets: Any,\n\u001b[1;32m    207\u001b[0m     \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs,\n\u001b[1;32m    208\u001b[0m ):\n\u001b[1;32m    209\u001b[0m     \u001b[39mfrom\u001b[39;00m \u001b[39mdask\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39marray\u001b[39;00m \u001b[39mimport\u001b[39;00m store\n\u001b[0;32m--> 211\u001b[0m     \u001b[39mreturn\u001b[39;00m store(\n\u001b[1;32m    212\u001b[0m         sources\u001b[39m=\u001b[39;49msources,\n\u001b[1;32m    213\u001b[0m         targets\u001b[39m=\u001b[39;49mtargets,\n\u001b[1;32m    214\u001b[0m         \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs,\n\u001b[1;32m    215\u001b[0m     )\n",
+      "File \u001b[0;32m~/.pyenv/versions/3.11.3/envs/py311/lib/python3.11/site-packages/dask/array/core.py:1236\u001b[0m, in \u001b[0;36mstore\u001b[0;34m(***failed resolving arguments***)\u001b[0m\n\u001b[1;32m   1234\u001b[0m \u001b[39melif\u001b[39;00m compute:\n\u001b[1;32m   1235\u001b[0m     store_dsk \u001b[39m=\u001b[39m HighLevelGraph(layers, dependencies)\n\u001b[0;32m-> 1236\u001b[0m     compute_as_if_collection(Array, store_dsk, map_keys, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m   1237\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mNone\u001b[39;00m\n\u001b[1;32m   1239\u001b[0m \u001b[39melse\u001b[39;00m:\n",
+      "File \u001b[0;32m~/.pyenv/versions/3.11.3/envs/py311/lib/python3.11/site-packages/dask/base.py:369\u001b[0m, in \u001b[0;36mcompute_as_if_collection\u001b[0;34m(cls, dsk, keys, scheduler, get, **kwargs)\u001b[0m\n\u001b[1;32m    367\u001b[0m schedule \u001b[39m=\u001b[39m get_scheduler(scheduler\u001b[39m=\u001b[39mscheduler, \u001b[39mcls\u001b[39m\u001b[39m=\u001b[39m\u001b[39mcls\u001b[39m, get\u001b[39m=\u001b[39mget)\n\u001b[1;32m    368\u001b[0m dsk2 \u001b[39m=\u001b[39m optimization_function(\u001b[39mcls\u001b[39m)(dsk, keys, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs)\n\u001b[0;32m--> 369\u001b[0m \u001b[39mreturn\u001b[39;00m schedule(dsk2, keys, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n",
+      "File \u001b[0;32m~/.pyenv/versions/3.11.3/envs/py311/lib/python3.11/site-packages/dask/threaded.py:90\u001b[0m, in \u001b[0;36mget\u001b[0;34m(dsk, keys, cache, num_workers, pool, **kwargs)\u001b[0m\n\u001b[1;32m     87\u001b[0m     \u001b[39melif\u001b[39;00m \u001b[39misinstance\u001b[39m(pool, multiprocessing\u001b[39m.\u001b[39mpool\u001b[39m.\u001b[39mPool):\n\u001b[1;32m     88\u001b[0m         pool \u001b[39m=\u001b[39m MultiprocessingPoolExecutor(pool)\n\u001b[0;32m---> 90\u001b[0m results \u001b[39m=\u001b[39m get_async(\n\u001b[1;32m     91\u001b[0m     pool\u001b[39m.\u001b[39;49msubmit,\n\u001b[1;32m     92\u001b[0m     pool\u001b[39m.\u001b[39;49m_max_workers,\n\u001b[1;32m     93\u001b[0m     dsk,\n\u001b[1;32m     94\u001b[0m     keys,\n\u001b[1;32m     95\u001b[0m     cache\u001b[39m=\u001b[39;49mcache,\n\u001b[1;32m     96\u001b[0m     get_id\u001b[39m=\u001b[39;49m_thread_get_id,\n\u001b[1;32m     97\u001b[0m     pack_exception\u001b[39m=\u001b[39;49mpack_exception,\n\u001b[1;32m     98\u001b[0m     \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs,\n\u001b[1;32m     99\u001b[0m )\n\u001b[1;32m    101\u001b[0m \u001b[39m# Cleanup pools associated to dead threads\u001b[39;00m\n\u001b[1;32m    102\u001b[0m \u001b[39mwith\u001b[39;00m pools_lock:\n",
+      "File \u001b[0;32m~/.pyenv/versions/3.11.3/envs/py311/lib/python3.11/site-packages/dask/local.py:512\u001b[0m, in \u001b[0;36mget_async\u001b[0;34m(submit, num_workers, dsk, result, cache, get_id, rerun_exceptions_locally, pack_exception, raise_exception, callbacks, dumps, loads, chunksize, **kwargs)\u001b[0m\n\u001b[1;32m    510\u001b[0m         _execute_task(task, data)  \u001b[39m# Re-execute locally\u001b[39;00m\n\u001b[1;32m    511\u001b[0m     \u001b[39melse\u001b[39;00m:\n\u001b[0;32m--> 512\u001b[0m         raise_exception(exc, tb)\n\u001b[1;32m    513\u001b[0m res, worker_id \u001b[39m=\u001b[39m loads(res_info)\n\u001b[1;32m    514\u001b[0m state[\u001b[39m\"\u001b[39m\u001b[39mcache\u001b[39m\u001b[39m\"\u001b[39m][key] \u001b[39m=\u001b[39m res\n",
+      "File \u001b[0;32m~/.pyenv/versions/3.11.3/envs/py311/lib/python3.11/site-packages/dask/local.py:320\u001b[0m, in \u001b[0;36mreraise\u001b[0;34m(exc, tb)\u001b[0m\n\u001b[1;32m    318\u001b[0m \u001b[39mif\u001b[39;00m exc\u001b[39m.\u001b[39m__traceback__ \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m tb:\n\u001b[1;32m    319\u001b[0m     \u001b[39mraise\u001b[39;00m exc\u001b[39m.\u001b[39mwith_traceback(tb)\n\u001b[0;32m--> 320\u001b[0m \u001b[39mraise\u001b[39;00m exc\n",
+      "File \u001b[0;32m~/.pyenv/versions/3.11.3/envs/py311/lib/python3.11/site-packages/dask/local.py:225\u001b[0m, in \u001b[0;36mexecute_task\u001b[0;34m(key, task_info, dumps, loads, get_id, pack_exception)\u001b[0m\n\u001b[1;32m    223\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[1;32m    224\u001b[0m     task, data \u001b[39m=\u001b[39m loads(task_info)\n\u001b[0;32m--> 225\u001b[0m     result \u001b[39m=\u001b[39m _execute_task(task, data)\n\u001b[1;32m    226\u001b[0m     \u001b[39mid\u001b[39m \u001b[39m=\u001b[39m get_id()\n\u001b[1;32m    227\u001b[0m     result \u001b[39m=\u001b[39m dumps((result, \u001b[39mid\u001b[39m))\n",
+      "File \u001b[0;32m~/.pyenv/versions/3.11.3/envs/py311/lib/python3.11/site-packages/dask/core.py:127\u001b[0m, in \u001b[0;36m_execute_task\u001b[0;34m(arg, cache, dsk)\u001b[0m\n\u001b[1;32m    123\u001b[0m     func, args \u001b[39m=\u001b[39m arg[\u001b[39m0\u001b[39m], arg[\u001b[39m1\u001b[39m:]\n\u001b[1;32m    124\u001b[0m     \u001b[39m# Note: Don't assign the subtask results to a variable. numpy detects\u001b[39;00m\n\u001b[1;32m    125\u001b[0m     \u001b[39m# temporaries by their reference count and can execute certain\u001b[39;00m\n\u001b[1;32m    126\u001b[0m     \u001b[39m# operations in-place.\u001b[39;00m\n\u001b[0;32m--> 127\u001b[0m     \u001b[39mreturn\u001b[39;00m func(\u001b[39m*\u001b[39;49m(_execute_task(a, cache) \u001b[39mfor\u001b[39;49;00m a \u001b[39min\u001b[39;49;00m args))\n\u001b[1;32m    128\u001b[0m \u001b[39melif\u001b[39;00m \u001b[39mnot\u001b[39;00m ishashable(arg):\n\u001b[1;32m    129\u001b[0m     \u001b[39mreturn\u001b[39;00m arg\n",
+      "File \u001b[0;32m~/.pyenv/versions/3.11.3/envs/py311/lib/python3.11/site-packages/dask/array/core.py:4402\u001b[0m, in \u001b[0;36mstore_chunk\u001b[0;34m(x, out, index, lock, return_stored)\u001b[0m\n\u001b[1;32m   4399\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mstore_chunk\u001b[39m(\n\u001b[1;32m   4400\u001b[0m     x: ArrayLike, out: ArrayLike, index: \u001b[39mslice\u001b[39m, lock: Any, return_stored: \u001b[39mbool\u001b[39m\n\u001b[1;32m   4401\u001b[0m ):\n\u001b[0;32m-> 4402\u001b[0m     \u001b[39mreturn\u001b[39;00m load_store_chunk(x, out, index, lock, return_stored, \u001b[39mFalse\u001b[39;49;00m)\n",
+      "File \u001b[0;32m~/.pyenv/versions/3.11.3/envs/py311/lib/python3.11/site-packages/dask/array/core.py:4384\u001b[0m, in \u001b[0;36mload_store_chunk\u001b[0;34m(x, out, index, lock, return_stored, load_stored)\u001b[0m\n\u001b[1;32m   4382\u001b[0m \u001b[39mif\u001b[39;00m x \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[1;32m   4383\u001b[0m     \u001b[39mif\u001b[39;00m is_arraylike(x):\n\u001b[0;32m-> 4384\u001b[0m         out[index] \u001b[39m=\u001b[39m x\n\u001b[1;32m   4385\u001b[0m     \u001b[39melse\u001b[39;00m:\n\u001b[1;32m   4386\u001b[0m         out[index] \u001b[39m=\u001b[39m np\u001b[39m.\u001b[39masanyarray(x)\n",
+      "File \u001b[0;32m~/.pyenv/versions/3.11.3/envs/py311/lib/python3.11/site-packages/zarr/core.py:1495\u001b[0m, in \u001b[0;36mArray.__setitem__\u001b[0;34m(self, selection, value)\u001b[0m\n\u001b[1;32m   1493\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mvindex[selection] \u001b[39m=\u001b[39m value\n\u001b[1;32m   1494\u001b[0m \u001b[39melif\u001b[39;00m is_pure_orthogonal_indexing(pure_selection, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mndim):\n\u001b[0;32m-> 1495\u001b[0m     \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mset_orthogonal_selection(pure_selection, value, fields\u001b[39m=\u001b[39;49mfields)\n\u001b[1;32m   1496\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m   1497\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mset_basic_selection(pure_selection, value, fields\u001b[39m=\u001b[39mfields)\n",
+      "File \u001b[0;32m~/.pyenv/versions/3.11.3/envs/py311/lib/python3.11/site-packages/zarr/core.py:1684\u001b[0m, in \u001b[0;36mArray.set_orthogonal_selection\u001b[0;34m(self, selection, value, fields)\u001b[0m\n\u001b[1;32m   1681\u001b[0m \u001b[39m# setup indexer\u001b[39;00m\n\u001b[1;32m   1682\u001b[0m indexer \u001b[39m=\u001b[39m OrthogonalIndexer(selection, \u001b[39mself\u001b[39m)\n\u001b[0;32m-> 1684\u001b[0m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_set_selection(indexer, value, fields\u001b[39m=\u001b[39;49mfields)\n",
+      "File \u001b[0;32m~/.pyenv/versions/3.11.3/envs/py311/lib/python3.11/site-packages/zarr/core.py:2038\u001b[0m, in \u001b[0;36mArray._set_selection\u001b[0;34m(self, indexer, value, fields)\u001b[0m\n\u001b[1;32m   2035\u001b[0m                 chunk_value \u001b[39m=\u001b[39m chunk_value[item]\n\u001b[1;32m   2037\u001b[0m         \u001b[39m# put data\u001b[39;00m\n\u001b[0;32m-> 2038\u001b[0m         \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_chunk_setitem(chunk_coords, chunk_selection, chunk_value, fields\u001b[39m=\u001b[39;49mfields)\n\u001b[1;32m   2039\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m   2040\u001b[0m     lchunk_coords, lchunk_selection, lout_selection \u001b[39m=\u001b[39m \u001b[39mzip\u001b[39m(\u001b[39m*\u001b[39mindexer)\n",
+      "File \u001b[0;32m~/.pyenv/versions/3.11.3/envs/py311/lib/python3.11/site-packages/zarr/core.py:2304\u001b[0m, in \u001b[0;36mArray._chunk_setitem\u001b[0;34m(self, chunk_coords, chunk_selection, value, fields)\u001b[0m\n\u001b[1;32m   2301\u001b[0m     lock \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_synchronizer[ckey]\n\u001b[1;32m   2303\u001b[0m \u001b[39mwith\u001b[39;00m lock:\n\u001b[0;32m-> 2304\u001b[0m     \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_chunk_setitem_nosync(chunk_coords, chunk_selection, value, fields\u001b[39m=\u001b[39;49mfields)\n",
+      "File \u001b[0;32m~/.pyenv/versions/3.11.3/envs/py311/lib/python3.11/site-packages/zarr/core.py:2314\u001b[0m, in \u001b[0;36mArray._chunk_setitem_nosync\u001b[0;34m(self, chunk_coords, chunk_selection, value, fields)\u001b[0m\n\u001b[1;32m   2312\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_chunk_delitem(ckey)\n\u001b[1;32m   2313\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[0;32m-> 2314\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mchunk_store[ckey] \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_encode_chunk(cdata)\n",
+      "File \u001b[0;32m~/.pyenv/versions/3.11.3/envs/py311/lib/python3.11/site-packages/zarr/core.py:2444\u001b[0m, in \u001b[0;36mArray._encode_chunk\u001b[0;34m(self, chunk)\u001b[0m\n\u001b[1;32m   2442\u001b[0m \u001b[39m# compress\u001b[39;00m\n\u001b[1;32m   2443\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_compressor:\n\u001b[0;32m-> 2444\u001b[0m     cdata \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_compressor\u001b[39m.\u001b[39;49mencode(chunk)\n\u001b[1;32m   2445\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m   2446\u001b[0m     cdata \u001b[39m=\u001b[39m chunk\n",
+      "File \u001b[0;32mnumcodecs/blosc.pyx:559\u001b[0m, in \u001b[0;36mnumcodecs.blosc.Blosc.encode\u001b[0;34m()\u001b[0m\n",
+      "File \u001b[0;32m~/.pyenv/versions/3.11.3/envs/py311/lib/python3.11/site-packages/numcodecs/compat.py:155\u001b[0m, in \u001b[0;36mensure_contiguous_ndarray\u001b[0;34m(buf, max_buffer_size, flatten)\u001b[0m\n\u001b[1;32m    126\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mensure_contiguous_ndarray\u001b[39m(buf, max_buffer_size\u001b[39m=\u001b[39m\u001b[39mNone\u001b[39;00m, flatten\u001b[39m=\u001b[39m\u001b[39mTrue\u001b[39;00m) \u001b[39m-\u001b[39m\u001b[39m>\u001b[39m np\u001b[39m.\u001b[39marray:\n\u001b[1;32m    127\u001b[0m \u001b[39m    \u001b[39m\u001b[39m\"\"\"Convenience function to coerce `buf` to a numpy array, if it is not already a\u001b[39;00m\n\u001b[1;32m    128\u001b[0m \u001b[39m    numpy array. Also ensures that the returned value exports fully contiguous memory,\u001b[39;00m\n\u001b[1;32m    129\u001b[0m \u001b[39m    and supports the new-style buffer interface. If the optional max_buffer_size is\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    151\u001b[0m \u001b[39m    return a view on memory exported by `buf`.\u001b[39;00m\n\u001b[1;32m    152\u001b[0m \u001b[39m    \"\"\"\u001b[39;00m\n\u001b[1;32m    154\u001b[0m     \u001b[39mreturn\u001b[39;00m ensure_ndarray(\n\u001b[0;32m--> 155\u001b[0m         ensure_contiguous_ndarray_like(\n\u001b[1;32m    156\u001b[0m             buf, max_buffer_size\u001b[39m=\u001b[39;49mmax_buffer_size, flatten\u001b[39m=\u001b[39;49mflatten\n\u001b[1;32m    157\u001b[0m         )\n\u001b[1;32m    158\u001b[0m     )\n",
+      "File \u001b[0;32m~/.pyenv/versions/3.11.3/envs/py311/lib/python3.11/site-packages/numcodecs/compat.py:121\u001b[0m, in \u001b[0;36mensure_contiguous_ndarray_like\u001b[0;34m(buf, max_buffer_size, flatten)\u001b[0m\n\u001b[1;32m    119\u001b[0m \u001b[39mif\u001b[39;00m max_buffer_size \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m \u001b[39mand\u001b[39;00m arr\u001b[39m.\u001b[39mnbytes \u001b[39m>\u001b[39m max_buffer_size:\n\u001b[1;32m    120\u001b[0m     msg \u001b[39m=\u001b[39m \u001b[39m\"\u001b[39m\u001b[39mCodec does not support buffers of > \u001b[39m\u001b[39m{}\u001b[39;00m\u001b[39m bytes\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m.\u001b[39mformat(max_buffer_size)\n\u001b[0;32m--> 121\u001b[0m     \u001b[39mraise\u001b[39;00m \u001b[39mValueError\u001b[39;00m(msg)\n\u001b[1;32m    123\u001b[0m \u001b[39mreturn\u001b[39;00m arr\n",
+      "\u001b[0;31mValueError\u001b[0m: Codec does not support buffers of > 2147483647 bytes"
+     ]
+    }
+   ],
+   "source": [
+    "# import xarray as xr\n",
+    "from numcodecs import Blosc\n",
+    "\n",
+    "# Open the existing Zarr dataset\n",
+    "ds_compress = xr.open_zarr('../data/GEBCO_2023_sub_ice_topo_compressor.zarr')\n",
+    "\n",
+    "blosc_compressor = Blosc(cname='lz4', clevel=5, shuffle=Blosc.SHUFFLE, blocksize=0)\n",
+    "\n",
+    "# Apply the Blosc compressor to all variables\n",
+    "encoding = {var: {'compressor': blosc_compressor} for var in ds.data_vars}\n",
+    "\n",
+    "# Convert to Zarr without specifying a group, and with the new encoding\n",
+    "ds_compress.to_zarr('../data/GEBCO_2023_sub_ice_topo.zarr', mode='w', encoding=encoding)\n",
+    "           #encoding={\"elevation\": {\"_Unsigned\": \"false\"}},\n",
+    "           #group='gebco') \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Exe time:  0.008665800094604492 sec\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
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+       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
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+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
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+       "\n",
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+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
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+       "\n",
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+       "  display: contents;\n",
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+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
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+       "\n",
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+       "  padding-right: 5px;\n",
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+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
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+       "  display: block;\n",
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+       ".xr-var-data > table {\n",
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+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
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+       "\n",
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+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
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+       "  padding-right: 10px;\n",
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+       "}\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:    (lat: 43200, lon: 86400)\n",
+       "Coordinates:\n",
+       "  * lat        (lat) float64 -90.0 -89.99 -89.99 -89.99 ... 89.99 89.99 90.0\n",
+       "  * lon        (lon) float64 -180.0 -180.0 -180.0 -180.0 ... 180.0 180.0 180.0\n",
+       "Data variables:\n",
+       "    elevation  (lat, lon) int16 dask.array&lt;chunksize=(60, 60), meta=np.ndarray&gt;\n",
+       "Attributes:\n",
+       "    Conventions:  CF-1.6\n",
+       "    comment:      The data in the GEBCO_2020 Grid should not be used for navi...\n",
+       "    history:      Information on the development of the data set and the sour...\n",
+       "    institution:  On behalf of the General Bathymetric Chart of the Oceans (G...\n",
+       "    node_offset:  1.0\n",
+       "    references:   DOI: 10.5285/836f016a-33be-6ddc-e053-6c86abc0788e\n",
+       "    source:       The GEBCO_2020 Grid is the latest global bathymetric produc...\n",
+       "    title:        The GEBCO_2020 Grid - a continuous terrain model for oceans...</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-e91abc6a-6aa0-4519-b9ab-b00d18fcc7c4' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e91abc6a-6aa0-4519-b9ab-b00d18fcc7c4' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 43200</li><li><span class='xr-has-index'>lon</span>: 86400</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-0216f8df-7215-4182-b3c7-6514720dbe69' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0216f8df-7215-4182-b3c7-6514720dbe69' 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 class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.99 -89.99 ... 89.99 90.0</div><input id='attrs-86ab54be-3fc5-42ce-9ec9-43897f09d737' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-86ab54be-3fc5-42ce-9ec9-43897f09d737' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-45d92d66-8f8c-443d-80df-da72a1ea1787' class='xr-var-data-in' type='checkbox'><label for='data-45d92d66-8f8c-443d-80df-da72a1ea1787' 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>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>sdn_parameter_name :</span></dt><dd>Latitude north</dd><dt><span>sdn_parameter_urn :</span></dt><dd>SDN:P01::ALATZZ01</dd><dt><span>sdn_uom_name :</span></dt><dd>Degrees north</dd><dt><span>sdn_uom_urn :</span></dt><dd>SDN:P06::DEGN</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>_FillValue :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([-89.997917, -89.99375 , -89.989583, ...,  89.989583,  89.99375 ,\n",
+       "        89.997917])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -180.0 ... 180.0 180.0</div><input id='attrs-2948029e-dd17-4e49-9fe6-8bdfa16cfecb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2948029e-dd17-4e49-9fe6-8bdfa16cfecb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d485d090-b0f9-4188-9133-a21c5cd37800' class='xr-var-data-in' type='checkbox'><label for='data-d485d090-b0f9-4188-9133-a21c5cd37800' 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>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>sdn_parameter_name :</span></dt><dd>Longitude east</dd><dt><span>sdn_parameter_urn :</span></dt><dd>SDN:P01::ALONZZ01</dd><dt><span>sdn_uom_name :</span></dt><dd>Degrees east</dd><dt><span>sdn_uom_urn :</span></dt><dd>SDN:P06::DEGE</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>_FillValue :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([-179.997917, -179.99375 , -179.989583, ...,  179.989583,  179.99375 ,\n",
+       "        179.997917])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b346784e-e01e-4afc-a560-80767f7d0908' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b346784e-e01e-4afc-a560-80767f7d0908' 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>elevation</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(60, 60), meta=np.ndarray&gt;</div><input id='attrs-9f270a8f-4ca7-4c3c-81be-99e48487c8b0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9f270a8f-4ca7-4c3c-81be-99e48487c8b0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a325b3fe-46fc-46db-839b-bd3e04e005bb' class='xr-var-data-in' type='checkbox'><label for='data-a325b3fe-46fc-46db-839b-bd3e04e005bb' 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>long_name :</span></dt><dd>Elevation relative to sea level</dd><dt><span>sdn_parameter_name :</span></dt><dd>Sea floor height (above mean sea level) {bathymetric height}</dd><dt><span>sdn_parameter_urn :</span></dt><dd>SDN:P01::ALATZZ01</dd><dt><span>sdn_uom_name :</span></dt><dd>Metres</dd><dt><span>sdn_uom_urn :</span></dt><dd>SDN:P06::ULAA</dd><dt><span>standard_name :</span></dt><dd>height_above_reference_ellipsoid</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.95 GiB </td>\n",
+       "                        <td> 7.03 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (43200, 86400) </td>\n",
+       "                        <td> (60, 60) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1036800 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> int16 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
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+       "  <line x1=\"0\" y1=\"28\" x2=\"120\" y2=\"28\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" />\n",
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+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" />\n",
+       "  <line x1=\"0\" y1=\"41\" x2=\"120\" y2=\"41\" />\n",
+       "  <line x1=\"0\" y1=\"44\" x2=\"120\" y2=\"44\" />\n",
+       "  <line x1=\"0\" y1=\"47\" x2=\"120\" y2=\"47\" />\n",
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+       "  <line x1=\"0\" y1=\"60\" x2=\"120\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"6\" y1=\"0\" x2=\"6\" y2=\"60\" />\n",
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+       "  <line x1=\"44\" y1=\"0\" x2=\"44\" y2=\"60\" />\n",
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+       "  <line x1=\"107\" y1=\"0\" x2=\"107\" y2=\"60\" />\n",
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+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"60\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,60.0 0.0,60.0\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"80.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >86400</text>\n",
+       "  <text x=\"140.000000\" y=\"30.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,30.000000)\">43200</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-763a78c6-2397-49f1-9201-edd66be1383f' class='xr-section-summary-in' type='checkbox'  ><label for='section-763a78c6-2397-49f1-9201-edd66be1383f' class='xr-section-summary' >Indexes: <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-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-cb2af3af-d9b3-48c4-b230-cf79c667369a' class='xr-index-data-in' type='checkbox'/><label for='index-cb2af3af-d9b3-48c4-b230-cf79c667369a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-89.99791666666667,          -89.99375, -89.98958333333333,\n",
+       "       -89.98541666666667,          -89.98125, -89.97708333333334,\n",
+       "       -89.97291666666666,          -89.96875, -89.96458333333334,\n",
+       "       -89.96041666666666,\n",
+       "       ...\n",
+       "        89.96041666666667,  89.96458333333334,           89.96875,\n",
+       "        89.97291666666666,  89.97708333333333,  89.98124999999999,\n",
+       "        89.98541666666665,  89.98958333333334,           89.99375,\n",
+       "        89.99791666666667],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=43200))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-84e3627d-72e5-4708-818d-627bef172dae' class='xr-index-data-in' type='checkbox'/><label for='index-84e3627d-72e5-4708-818d-627bef172dae' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-179.99791666666667,          -179.99375, -179.98958333333334,\n",
+       "       -179.98541666666668,          -179.98125, -179.97708333333333,\n",
+       "       -179.97291666666666,          -179.96875, -179.96458333333334,\n",
+       "       -179.96041666666667,\n",
+       "       ...\n",
+       "        179.96041666666667,  179.96458333333334,           179.96875,\n",
+       "        179.97291666666666,  179.97708333333333,           179.98125,\n",
+       "        179.98541666666665,  179.98958333333331,  179.99374999999998,\n",
+       "        179.99791666666667],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=86400))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-73d58aa3-1a35-4827-9496-46ee0c497146' class='xr-section-summary-in' type='checkbox'  checked><label for='section-73d58aa3-1a35-4827-9496-46ee0c497146' class='xr-section-summary' >Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>comment :</span></dt><dd>The data in the GEBCO_2020 Grid should not be used for navigation or any purpose relating to safety at sea.</dd><dt><span>history :</span></dt><dd>Information on the development of the data set and the source data sets included in the grid can be found in the data set documentation available from https://www.gebco.net</dd><dt><span>institution :</span></dt><dd>On behalf of the General Bathymetric Chart of the Oceans (GEBCO), the data are held at the British Oceanographic Data Centre (BODC).</dd><dt><span>node_offset :</span></dt><dd>1.0</dd><dt><span>references :</span></dt><dd>DOI: 10.5285/836f016a-33be-6ddc-e053-6c86abc0788e</dd><dt><span>source :</span></dt><dd>The GEBCO_2020 Grid is the latest global bathymetric product released by the General Bathymetric Chart of the Oceans (GEBCO) and has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and GEBCO. The Seabed 2030 Project aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor and make it available to all.</dd><dt><span>title :</span></dt><dd>The GEBCO_2020 Grid - a continuous terrain model for oceans and land at 15 arc-second intervals</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset>\n",
+       "Dimensions:    (lat: 43200, lon: 86400)\n",
+       "Coordinates:\n",
+       "  * lat        (lat) float64 -90.0 -89.99 -89.99 -89.99 ... 89.99 89.99 90.0\n",
+       "  * lon        (lon) float64 -180.0 -180.0 -180.0 -180.0 ... 180.0 180.0 180.0\n",
+       "Data variables:\n",
+       "    elevation  (lat, lon) int16 dask.array<chunksize=(60, 60), meta=np.ndarray>\n",
+       "Attributes:\n",
+       "    Conventions:  CF-1.6\n",
+       "    comment:      The data in the GEBCO_2020 Grid should not be used for navi...\n",
+       "    history:      Information on the development of the data set and the sour...\n",
+       "    institution:  On behalf of the General Bathymetric Chart of the Oceans (G...\n",
+       "    node_offset:  1.0\n",
+       "    references:   DOI: 10.5285/836f016a-33be-6ddc-e053-6c86abc0788e\n",
+       "    source:       The GEBCO_2020 Grid is the latest global bathymetric produc...\n",
+       "    title:        The GEBCO_2020 Grid - a continuous terrain model for oceans..."
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "st = time.time()\n",
+    "dz = xr.open_zarr(\n",
+    "    '../data/GEBCO_2023_sub_ice_topo.zarr', chunks='auto', #group='gebco', \n",
+    "    decode_cf=False, decode_times=False)\n",
+    "\n",
+    "et = time.time()\n",
+    "print('Exe time: ', et-st, 'sec')\n",
+    "dz"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['crs', 'elevation', 'gebco', 'lat', 'lon']\n",
+      "Variable: crs\n",
+      "Compression: None\n",
+      "Chunk Size: ()\n",
+      "Variable: elevation\n",
+      "Compression: Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0)\n",
+      "Chunk Size: (43200, 86400)\n",
+      "Variable: lat\n",
+      "Compression: Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0)\n",
+      "Chunk Size: (21600,)\n",
+      "Variable: lon\n",
+      "Compression: Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0)\n",
+      "Chunk Size: (43200,)\n"
+     ]
+    }
+   ],
+   "source": [
+    "import zarr\n",
+    "\n",
+    "# Open the Zarr store\n",
+    "store = zarr.open_group('../data/GEBCO_2022_sub_ice_topo.zarr', mode='r')\n",
+    "print(list(store.keys()))\n",
+    "# Inspect attributes\n",
+    "for var in store.array_keys():\n",
+    "    arr = store[var]\n",
+    "    print(f\"Variable: {var}\")\n",
+    "    print(f\"Compression: {arr.compressor}\")\n",
+    "    print(f\"Chunk Size: {arr.chunks}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['elevation', 'lat', 'lon']\n",
+      "Variable: elevation\n",
+      "Compression: Zlib(level=1)\n",
+      "Chunk Size: (43200, 86400)\n",
+      "Variable: lat\n",
+      "Compression: Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0)\n",
+      "Chunk Size: (21600,)\n",
+      "Variable: lon\n",
+      "Compression: Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0)\n",
+      "Chunk Size: (43200,)\n"
+     ]
+    }
+   ],
+   "source": [
+    "#import zarr\n",
+    "\n",
+    "# Open the Zarr store\n",
+    "store2 = zarr.open_group('../data/GEBCO_2023_sub_ice_topo_compressor.zarr', mode='r')\n",
+    "print(list(store2.keys()))\n",
+    "## Inspect attributes\n",
+    "## Access the 'gebco' group\n",
+    "# gebco_group = store2['gebco']\n",
+    "\n",
+    "## Inspect attributes within the 'gebco' group\n",
+    "#for var in gebco_group.array_keys():\n",
+    "#    arr = gebco_group[var]\n",
+    "#    print(f\"Variable: {var}\")\n",
+    "#    print(f\"Compression: {arr.compressor}\")\n",
+    "#    print(f\"Chunk Size: {arr.chunks}\")\n",
+    "\n",
+    "for var in store2.array_keys():\n",
+    "    arr = store2[var]\n",
+    "    print(f\"Variable: {var}\")\n",
+    "    print(f\"Compression: {arr.compressor}\")\n",
+    "    print(f\"Chunk Size: {arr.chunks}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['elevation', 'lat', 'lon']\n",
+      "Variable: elevation\n",
+      "Compression: Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0)\n",
+      "Chunk Size: (60, 60)\n",
+      "Variable: lat\n",
+      "Compression: Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0)\n",
+      "Chunk Size: (21600,)\n",
+      "Variable: lon\n",
+      "Compression: Blosc(cname='lz4', clevel=5, shuffle=SHUFFLE, blocksize=0)\n",
+      "Chunk Size: (43200,)\n"
+     ]
+    }
+   ],
+   "source": [
+    "#import zarr\n",
+    "\n",
+    "# Open the Zarr store\n",
+    "store = zarr.open_group('../data/GEBCO_2023_sub_ice_topo.zarr', mode='r')\n",
+    "print(list(store.keys()))\n",
+    "# Inspect attributes\n",
+    "for var in store.array_keys():\n",
+    "    arr = store[var]\n",
+    "    print(f\"Variable: {var}\")\n",
+    "    print(f\"Compression: {arr.compressor}\")\n",
+    "    print(f\"Chunk Size: {arr.chunks}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "112\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "6.9522857666015625"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "print(sys.getsizeof(dz))\n",
+    "dz['elevation'].nbytes/(1024 ** 3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Exe time:  40.998939990997314 sec\n",
+      "[[-121 -119 -116 -111 -106 -101  -94  -88  -82  -76]\n",
+      " [-123 -121 -119 -115 -109 -103  -97  -91  -86  -79]\n",
+      " [-126 -124 -122 -118 -113 -106 -100  -95  -88  -83]\n",
+      " [-127 -127 -126 -123 -116 -110 -103  -97  -91  -86]\n",
+      " [-127 -127 -128 -126 -118 -112 -106  -99  -94  -88]\n",
+      " [-127 -127 -126 -125 -119 -113 -107 -102  -96  -91]\n",
+      " [-127 -127 -126 -123 -118 -113 -108 -103  -99  -94]\n",
+      " [-126 -125 -124 -122 -118 -113 -109 -104 -100  -96]\n",
+      " [-125 -124 -123 -120 -118 -114 -110 -107 -102  -98]\n",
+      " [-123 -123 -121 -120 -118 -114 -112 -108 -104 -100]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "st = time.time()\n",
+    "dz_s1 = dz.sel(lon=slice(105, 135), lat=slice(2, 35)) \n",
+    "dz_s1.close() #try if it can close\n",
+    "zt1 = dz_s1.isel(lon=slice(1000, 1010), lat=slice(2000, 2010))\n",
+    "xz1 = zt1['elevation'].values\n",
+    "et = time.time()\n",
+    "print('Exe time: ', et-st, 'sec')\n",
+    "print(xz1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "st = time.time()\n",
+    "jz1 = orjson.dumps(xz1.tolist(), option=orjson.OPT_NAIVE_UTC | orjson.OPT_SERIALIZE_NUMPY)\n",
+    "et = time.time()\n",
+    "print('4.1z Convert JSON by orjson time: ', et-st, 'sec')\n",
+    "print(jz1)\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3.8.10 ('py39')",
+   "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": "3.11.3"
+  },
+  "orig_nbformat": 4,
+  "vscode": {
+   "interpreter": {
+    "hash": "e4b16f993b66de7f38f135ed21ea7c985362ee20cd8e4dede1c122c7165d5297"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/simu_gebco01.py b/dev/simu_gebco01.py
similarity index 99%
rename from simu_gebco01.py
rename to dev/simu_gebco01.py
index 02eeefc..805eef2 100644
--- a/simu_gebco01.py
+++ b/dev/simu_gebco01.py
@@ -12,7 +12,7 @@
 from typing import Union #, Optional
 # from loggerConfig import logger
 # from models import zprofSchema
-from xmeridian import *
+from src.xmeridian import *
 
 import dask
 # from multiprocessing.pool import Pool
@@ -39,7 +39,7 @@
 global ds
 #logger.info
 ds = xr.open_zarr(
-        'GEBCO_2022_sub_ice_topo.zarr', chunks='auto', group='gebco',
+        'data/GEBCO_2023_sub_ice_topo.zarr', chunks='auto', group='gebco',
         decode_cf=False, decode_times=False)
 
 # @app.on_event("shutdown")
@@ -382,7 +382,7 @@ def zprofile(lon: str, lat: str, mode: Union[str, None] = None):
     return JSONResponse(content=out)
 
 
-#print(zprofile(lon='123,123.15', lat='22.13,22', mode='dataframe'))
+print(zprofile(lon='123,123.15', lat='22.13,22', mode='dataframe'))
 #print(zprofile(lon='123,123.15', lat='22.13,22', mode='dataframe,zonly'))
 #out = zprofile(lon='123,123.15', lat='22.13', mode='dataframe')
 #print(out)
\ No newline at end of file
diff --git a/wireframe01.ipynb b/dev/wireframe01.ipynb
similarity index 100%
rename from wireframe01.ipynb
rename to dev/wireframe01.ipynb
diff --git a/zprofile01.ipynb b/dev/zprofile01.ipynb
similarity index 63%
rename from zprofile01.ipynb
rename to dev/zprofile01.ipynb
index b2628c4..73e1ebc 100644
--- a/zprofile01.ipynb
+++ b/dev/zprofile01.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 105,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -16,14 +16,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 102,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Exe time:  0.005364179611206055 sec\n"
+      "Exe time:  0.5036609172821045 sec\n"
      ]
     },
     {
@@ -72,7 +72,7 @@
        "}\n",
        "\n",
        ".xr-wrap {\n",
-       "  display: block;\n",
+       "  display: block !important;\n",
        "  min-width: 300px;\n",
        "  max-width: 700px;\n",
        "}\n",
@@ -386,24 +386,18 @@
        "  * lat        (lat) float64 -90.0 -89.99 -89.99 -89.99 ... 89.99 89.99 90.0\n",
        "  * lon        (lon) float64 -180.0 -180.0 -180.0 -180.0 ... 180.0 180.0 180.0\n",
        "Data variables:\n",
-       "    crs        |S1 ...\n",
-       "    elevation  (lat, lon) int16 dask.array&lt;chunksize=(675, 2700), meta=np.ndarray&gt;\n",
-       "Attributes: (12/36)\n",
-       "    Conventions:                     CF-1.6, ACDD-1.3\n",
-       "    comment:                         The data in the GEBCO_2022 Grid should n...\n",
-       "    creator_email:                   gdacc@seabed2030.org\n",
-       "    creator_name:                    GEBCO through the Nippon Foundation-GEBC...\n",
-       "    creator_type:                    International organisation\n",
-       "    creator_url:                     https://www.gebco.net\n",
-       "    ...                              ...\n",
-       "    node_offset:                     1.0\n",
-       "    project:                         Nippon Foundation - GEBCO Seabed2030 Pro...\n",
-       "    references:                      DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c8...\n",
-       "    source:                          The GEBCO_2022 Grid is the latest global...\n",
-       "    summary:                         The GEBCO_2022 Grid is a continuous, glo...\n",
-       "    title:                           The GEBCO_2022 Grid - a continuous terra...</pre><div class='xr-wrap' hidden><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-2da71065-719d-4f88-a11f-a0d582b62b4e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2da71065-719d-4f88-a11f-a0d582b62b4e' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 43200</li><li><span class='xr-has-index'>lon</span>: 86400</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-f3dc1302-428e-40e8-8fbd-9208cfefd778' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f3dc1302-428e-40e8-8fbd-9208cfefd778' 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 class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.99 -89.99 ... 89.99 90.0</div><input id='attrs-d4d2e7b6-39e6-4bad-a838-c4759092a8cc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d4d2e7b6-39e6-4bad-a838-c4759092a8cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c00f113c-f96d-4af4-b851-10fd36f969c9' class='xr-var-data-in' type='checkbox'><label for='data-c00f113c-f96d-4af4-b851-10fd36f969c9' 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>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>sdn_parameter_name :</span></dt><dd>Latitude north</dd><dt><span>sdn_parameter_urn :</span></dt><dd>SDN:P01::ALATZZ01</dd><dt><span>sdn_uom_name :</span></dt><dd>Degrees north</dd><dt><span>sdn_uom_urn :</span></dt><dd>SDN:P06::DEGN</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>_FillValue :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([-89.997917, -89.99375 , -89.989583, ...,  89.989583,  89.99375 ,\n",
-       "        89.997917])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -180.0 ... 180.0 180.0</div><input id='attrs-984cf2fc-c65b-4d2e-b637-93659149c530' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-984cf2fc-c65b-4d2e-b637-93659149c530' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-864eec50-9571-4a9c-a95f-a7dd9a4c87b7' class='xr-var-data-in' type='checkbox'><label for='data-864eec50-9571-4a9c-a95f-a7dd9a4c87b7' 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>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>sdn_parameter_name :</span></dt><dd>Longitude east</dd><dt><span>sdn_parameter_urn :</span></dt><dd>SDN:P01::ALONZZ01</dd><dt><span>sdn_uom_name :</span></dt><dd>Degrees east</dd><dt><span>sdn_uom_urn :</span></dt><dd>SDN:P06::DEGE</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>_FillValue :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([-179.997917, -179.99375 , -179.989583, ...,  179.989583,  179.99375 ,\n",
-       "        179.997917])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-525bc09e-bf2a-4da9-8ef3-744c7e71cc87' class='xr-section-summary-in' type='checkbox'  checked><label for='section-525bc09e-bf2a-4da9-8ef3-744c7e71cc87' class='xr-section-summary' >Data variables: <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>crs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>|S1</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0abd3abd-d986-4816-8bb3-661aebbb724b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0abd3abd-d986-4816-8bb3-661aebbb724b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-42e13ff6-2c50-4091-9258-9c602e22074a' class='xr-var-data-in' type='checkbox'><label for='data-42e13ff6-2c50-4091-9258-9c602e22074a' 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>epsg_code :</span></dt><dd>EPSG:4326</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd></dl></div><div class='xr-var-data'><pre>array(b&#x27;&#x27;, dtype=&#x27;|S1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>elevation</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(675, 2700), meta=np.ndarray&gt;</div><input id='attrs-574be852-cbe4-415e-ac70-1e03cd28d924' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-574be852-cbe4-415e-ac70-1e03cd28d924' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-935fe99a-f228-48f4-a8ef-2f0c212257cb' class='xr-var-data-in' type='checkbox'><label for='data-935fe99a-f228-48f4-a8ef-2f0c212257cb' 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>_Unsigned :</span></dt><dd>false</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Elevation relative to sea level</dd><dt><span>sdn_parameter_name :</span></dt><dd>Sea floor height (above mean sea level) {bathymetric height}</dd><dt><span>sdn_parameter_urn :</span></dt><dd>SDN:P01::ALATZZ01</dd><dt><span>sdn_uom_name :</span></dt><dd>Metres</dd><dt><span>sdn_uom_urn :</span></dt><dd>SDN:P06::ULAA</dd><dt><span>standard_name :</span></dt><dd>height_above_mean_sea_level</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    elevation  (lat, lon) int16 dask.array&lt;chunksize=(43200, 86400), meta=np.ndarray&gt;\n",
+       "Attributes:\n",
+       "    Conventions:  CF-1.6\n",
+       "    comment:      The data in the GEBCO_2020 Grid should not be used for navi...\n",
+       "    history:      Information on the development of the data set and the sour...\n",
+       "    institution:  On behalf of the General Bathymetric Chart of the Oceans (G...\n",
+       "    node_offset:  1.0\n",
+       "    references:   DOI: 10.5285/836f016a-33be-6ddc-e053-6c86abc0788e\n",
+       "    source:       The GEBCO_2020 Grid is the latest global bathymetric produc...\n",
+       "    title:        The GEBCO_2020 Grid - a continuous terrain model for oceans...</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-e47fe406-45da-4f6f-9968-64c01bbe08cd' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e47fe406-45da-4f6f-9968-64c01bbe08cd' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 43200</li><li><span class='xr-has-index'>lon</span>: 86400</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-06c42599-86c4-474a-8afa-9f74428d4701' class='xr-section-summary-in' type='checkbox'  checked><label for='section-06c42599-86c4-474a-8afa-9f74428d4701' 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 class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.99 -89.99 ... 89.99 90.0</div><input id='attrs-a7aa8a4d-696f-48a3-a91b-af9a8da57007' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a7aa8a4d-696f-48a3-a91b-af9a8da57007' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f272015d-be01-4212-a412-5fd32beb91c1' class='xr-var-data-in' type='checkbox'><label for='data-f272015d-be01-4212-a412-5fd32beb91c1' 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>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>sdn_parameter_name :</span></dt><dd>Latitude north</dd><dt><span>sdn_parameter_urn :</span></dt><dd>SDN:P01::ALATZZ01</dd><dt><span>sdn_uom_name :</span></dt><dd>Degrees north</dd><dt><span>sdn_uom_urn :</span></dt><dd>SDN:P06::DEGN</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>_FillValue :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([-89.997917, -89.99375 , -89.989583, ...,  89.989583,  89.99375 ,\n",
+       "        89.997917])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -180.0 ... 180.0 180.0</div><input id='attrs-3fd369df-6f8a-4616-a2cb-38ea60933b54' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3fd369df-6f8a-4616-a2cb-38ea60933b54' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a310b6f-0c9a-49ac-bfeb-d5656005fe25' class='xr-var-data-in' type='checkbox'><label for='data-6a310b6f-0c9a-49ac-bfeb-d5656005fe25' 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>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>sdn_parameter_name :</span></dt><dd>Longitude east</dd><dt><span>sdn_parameter_urn :</span></dt><dd>SDN:P01::ALONZZ01</dd><dt><span>sdn_uom_name :</span></dt><dd>Degrees east</dd><dt><span>sdn_uom_urn :</span></dt><dd>SDN:P06::DEGE</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>_FillValue :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([-179.997917, -179.99375 , -179.989583, ...,  179.989583,  179.99375 ,\n",
+       "        179.997917])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4224320e-831e-4816-8306-0becb413ac45' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4224320e-831e-4816-8306-0becb413ac45' 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>elevation</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(43200, 86400), meta=np.ndarray&gt;</div><input id='attrs-e4c17c78-4156-4b4e-8c83-f963267c1109' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e4c17c78-4156-4b4e-8c83-f963267c1109' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3de7f074-57e2-4677-8112-cd54da170e0e' class='xr-var-data-in' type='checkbox'><label for='data-3de7f074-57e2-4677-8112-cd54da170e0e' 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>long_name :</span></dt><dd>Elevation relative to sea level</dd><dt><span>sdn_parameter_name :</span></dt><dd>Sea floor height (above mean sea level) {bathymetric height}</dd><dt><span>sdn_parameter_urn :</span></dt><dd>SDN:P01::ALATZZ01</dd><dt><span>sdn_uom_name :</span></dt><dd>Metres</dd><dt><span>sdn_uom_urn :</span></dt><dd>SDN:P06::ULAA</dd><dt><span>standard_name :</span></dt><dd>height_above_reference_ellipsoid</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
        "    <tr>\n",
        "        <td>\n",
        "            <table style=\"border-collapse: collapse;\">\n",
@@ -419,17 +413,17 @@
        "                    <tr>\n",
        "                        <th> Bytes </th>\n",
        "                        <td> 6.95 GiB </td>\n",
-       "                        <td> 3.48 MiB </td>\n",
+       "                        <td> 6.95 GiB </td>\n",
        "                    </tr>\n",
        "                    \n",
        "                    <tr>\n",
        "                        <th> Shape </th>\n",
        "                        <td> (43200, 86400) </td>\n",
-       "                        <td> (675, 2700) </td>\n",
+       "                        <td> (43200, 86400) </td>\n",
        "                    </tr>\n",
        "                    <tr>\n",
        "                        <th> Dask graph </th>\n",
-       "                        <td colspan=\"2\"> 2048 chunks in 2 graph layers </td>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
        "                    </tr>\n",
        "                    <tr>\n",
        "                        <th> Data type </th>\n",
@@ -443,50 +437,14 @@
        "\n",
        "  <!-- Horizontal lines -->\n",
        "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
-       "  <line x1=\"0\" y1=\"2\" x2=\"120\" y2=\"2\" />\n",
-       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
-       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
-       "  <line x1=\"0\" y1=\"12\" x2=\"120\" y2=\"12\" />\n",
-       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
-       "  <line x1=\"0\" y1=\"18\" x2=\"120\" y2=\"18\" />\n",
-       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
-       "  <line x1=\"0\" y1=\"24\" x2=\"120\" y2=\"24\" />\n",
-       "  <line x1=\"0\" y1=\"28\" x2=\"120\" y2=\"28\" />\n",
-       "  <line x1=\"0\" y1=\"30\" x2=\"120\" y2=\"30\" />\n",
-       "  <line x1=\"0\" y1=\"34\" x2=\"120\" y2=\"34\" />\n",
-       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" />\n",
-       "  <line x1=\"0\" y1=\"40\" x2=\"120\" y2=\"40\" />\n",
-       "  <line x1=\"0\" y1=\"44\" x2=\"120\" y2=\"44\" />\n",
-       "  <line x1=\"0\" y1=\"46\" x2=\"120\" y2=\"46\" />\n",
-       "  <line x1=\"0\" y1=\"49\" x2=\"120\" y2=\"49\" />\n",
-       "  <line x1=\"0\" y1=\"53\" x2=\"120\" y2=\"53\" />\n",
-       "  <line x1=\"0\" y1=\"56\" x2=\"120\" y2=\"56\" />\n",
        "  <line x1=\"0\" y1=\"60\" x2=\"120\" y2=\"60\" style=\"stroke-width:2\" />\n",
        "\n",
        "  <!-- Vertical lines -->\n",
        "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"60\" style=\"stroke-width:2\" />\n",
-       "  <line x1=\"3\" y1=\"0\" x2=\"3\" y2=\"60\" />\n",
-       "  <line x1=\"11\" y1=\"0\" x2=\"11\" y2=\"60\" />\n",
-       "  <line x1=\"18\" y1=\"0\" x2=\"18\" y2=\"60\" />\n",
-       "  <line x1=\"22\" y1=\"0\" x2=\"22\" y2=\"60\" />\n",
-       "  <line x1=\"30\" y1=\"0\" x2=\"30\" y2=\"60\" />\n",
-       "  <line x1=\"37\" y1=\"0\" x2=\"37\" y2=\"60\" />\n",
-       "  <line x1=\"41\" y1=\"0\" x2=\"41\" y2=\"60\" />\n",
-       "  <line x1=\"48\" y1=\"0\" x2=\"48\" y2=\"60\" />\n",
-       "  <line x1=\"56\" y1=\"0\" x2=\"56\" y2=\"60\" />\n",
-       "  <line x1=\"60\" y1=\"0\" x2=\"60\" y2=\"60\" />\n",
-       "  <line x1=\"67\" y1=\"0\" x2=\"67\" y2=\"60\" />\n",
-       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"60\" />\n",
-       "  <line x1=\"78\" y1=\"0\" x2=\"78\" y2=\"60\" />\n",
-       "  <line x1=\"86\" y1=\"0\" x2=\"86\" y2=\"60\" />\n",
-       "  <line x1=\"93\" y1=\"0\" x2=\"93\" y2=\"60\" />\n",
-       "  <line x1=\"97\" y1=\"0\" x2=\"97\" y2=\"60\" />\n",
-       "  <line x1=\"105\" y1=\"0\" x2=\"105\" y2=\"60\" />\n",
-       "  <line x1=\"112\" y1=\"0\" x2=\"112\" y2=\"60\" />\n",
        "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"60\" style=\"stroke-width:2\" />\n",
        "\n",
        "  <!-- Colored Rectangle -->\n",
-       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,60.0 0.0,60.0\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,60.0 0.0,60.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
        "\n",
        "  <!-- Text -->\n",
        "  <text x=\"60.000000\" y=\"80.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >86400</text>\n",
@@ -494,7 +452,7 @@
        "</svg>\n",
        "        </td>\n",
        "    </tr>\n",
-       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-f6ff796f-09dc-40d7-b40d-8d5a9a1a88a6' class='xr-section-summary-in' type='checkbox'  ><label for='section-f6ff796f-09dc-40d7-b40d-8d5a9a1a88a6' class='xr-section-summary' >Attributes: <span>(36)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6, ACDD-1.3</dd><dt><span>comment :</span></dt><dd>The data in the GEBCO_2022 Grid should not be used for navigation or any purpose relating to safety at sea.</dd><dt><span>creator_email :</span></dt><dd>gdacc@seabed2030.org</dd><dt><span>creator_name :</span></dt><dd>GEBCO through the Nippon Foundation-GEBCO Seabed 2030 Project</dd><dt><span>creator_type :</span></dt><dd>International organisation</dd><dt><span>creator_url :</span></dt><dd>https://www.gebco.net</dd><dt><span>date_created :</span></dt><dd>2022-06-22</dd><dt><span>geospatial_bounds :</span></dt><dd>[-180.0, -90.0, 180.0, 90.0]</dd><dt><span>geospatial_bounds_crs :</span></dt><dd>WGS84</dd><dt><span>geospatial_bounds_vertical_crs :</span></dt><dd>EPSG:5831</dd><dt><span>geospatial_lat_max :</span></dt><dd>90.0</dd><dt><span>geospatial_lat_min :</span></dt><dd>-90.0</dd><dt><span>geospatial_lat_resolution :</span></dt><dd>0.004166666666666667</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees_north</dd><dt><span>geospatial_lon_max :</span></dt><dd>180.0</dd><dt><span>geospatial_lon_min :</span></dt><dd>-180.0</dd><dt><span>geospatial_lon_resolution :</span></dt><dd>0.004166666666666667</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees_east</dd><dt><span>geospatial_vertical_max :</span></dt><dd>8685.0</dd><dt><span>geospatial_vertical_min :</span></dt><dd>-10977.0</dd><dt><span>geospatial_vertical_positive :</span></dt><dd>up</dd><dt><span>geospatial_vertical_resolution :</span></dt><dd>1.0</dd><dt><span>geospatial_vertical_units :</span></dt><dd>meters</dd><dt><span>history :</span></dt><dd>Information on the development of the data set and the source data sets included in the grid can be found in the data set documentation available from https://www.gebco.net</dd><dt><span>id :</span></dt><dd>DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c86abc0289c</dd><dt><span>identifier_product_doi :</span></dt><dd>DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c86abc0289c</dd><dt><span>institution :</span></dt><dd>On behalf of the General Bathymetric Chart of the Oceans (GEBCO), the data are held at the British Oceanographic Data Centre (BODC).</dd><dt><span>keywords :</span></dt><dd>BATHYMETRY/SEAFLOOR TOPOGRAPHY, DIGITAL ELEVATION/DIGITAL TERRAIN MODELS</dd><dt><span>license :</span></dt><dd>The GEBCO Grid is placed in the public domain and may be used free of charge. Use of the GEBCO Grid indicates that the user accepts the conditions of use and disclaimer information: https://www.gebco.net/data_and_products/gridded_bathymetry_data/gebco_2019/grid_terms_of_use.html</dd><dt><span>naming_authority :</span></dt><dd>https://dx.doi.org</dd><dt><span>node_offset :</span></dt><dd>1.0</dd><dt><span>project :</span></dt><dd>Nippon Foundation - GEBCO Seabed2030 Project</dd><dt><span>references :</span></dt><dd>DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c86abc0289c</dd><dt><span>source :</span></dt><dd>The GEBCO_2022 Grid is the latest global bathymetric product released by the General Bathymetric Chart of the Oceans (GEBCO) and has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and GEBCO. The Seabed 2030 Project aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor and make it available to all.</dd><dt><span>summary :</span></dt><dd>The GEBCO_2022 Grid is a continuous, global terrain model for ocean and land with a spatial resolution of 15 arc seconds.The grid uses as a base-map Version 2.4 of the SRTM15+ data set (Tozer et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. It is augmented with gridded bathymetric data sets developed as part of the Nippon Foundation-GEBCO Seabed 2030 Project.</dd><dt><span>title :</span></dt><dd>The GEBCO_2022 Grid - a continuous terrain model for oceans and land at 15 arc-second intervals</dd></dl></div></li></ul></div></div>"
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-ff3aca81-ce61-4979-8fc3-3a3fddb6ed65' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ff3aca81-ce61-4979-8fc3-3a3fddb6ed65' class='xr-section-summary' >Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>comment :</span></dt><dd>The data in the GEBCO_2020 Grid should not be used for navigation or any purpose relating to safety at sea.</dd><dt><span>history :</span></dt><dd>Information on the development of the data set and the source data sets included in the grid can be found in the data set documentation available from https://www.gebco.net</dd><dt><span>institution :</span></dt><dd>On behalf of the General Bathymetric Chart of the Oceans (GEBCO), the data are held at the British Oceanographic Data Centre (BODC).</dd><dt><span>node_offset :</span></dt><dd>1.0</dd><dt><span>references :</span></dt><dd>DOI: 10.5285/836f016a-33be-6ddc-e053-6c86abc0788e</dd><dt><span>source :</span></dt><dd>The GEBCO_2020 Grid is the latest global bathymetric product released by the General Bathymetric Chart of the Oceans (GEBCO) and has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and GEBCO. The Seabed 2030 Project aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor and make it available to all.</dd><dt><span>title :</span></dt><dd>The GEBCO_2020 Grid - a continuous terrain model for oceans and land at 15 arc-second intervals</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.Dataset>\n",
@@ -503,25 +461,19 @@
        "  * lat        (lat) float64 -90.0 -89.99 -89.99 -89.99 ... 89.99 89.99 90.0\n",
        "  * lon        (lon) float64 -180.0 -180.0 -180.0 -180.0 ... 180.0 180.0 180.0\n",
        "Data variables:\n",
-       "    crs        |S1 ...\n",
-       "    elevation  (lat, lon) int16 dask.array<chunksize=(675, 2700), meta=np.ndarray>\n",
-       "Attributes: (12/36)\n",
-       "    Conventions:                     CF-1.6, ACDD-1.3\n",
-       "    comment:                         The data in the GEBCO_2022 Grid should n...\n",
-       "    creator_email:                   gdacc@seabed2030.org\n",
-       "    creator_name:                    GEBCO through the Nippon Foundation-GEBC...\n",
-       "    creator_type:                    International organisation\n",
-       "    creator_url:                     https://www.gebco.net\n",
-       "    ...                              ...\n",
-       "    node_offset:                     1.0\n",
-       "    project:                         Nippon Foundation - GEBCO Seabed2030 Pro...\n",
-       "    references:                      DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c8...\n",
-       "    source:                          The GEBCO_2022 Grid is the latest global...\n",
-       "    summary:                         The GEBCO_2022 Grid is a continuous, glo...\n",
-       "    title:                           The GEBCO_2022 Grid - a continuous terra..."
+       "    elevation  (lat, lon) int16 dask.array<chunksize=(43200, 86400), meta=np.ndarray>\n",
+       "Attributes:\n",
+       "    Conventions:  CF-1.6\n",
+       "    comment:      The data in the GEBCO_2020 Grid should not be used for navi...\n",
+       "    history:      Information on the development of the data set and the sour...\n",
+       "    institution:  On behalf of the General Bathymetric Chart of the Oceans (G...\n",
+       "    node_offset:  1.0\n",
+       "    references:   DOI: 10.5285/836f016a-33be-6ddc-e053-6c86abc0788e\n",
+       "    source:       The GEBCO_2020 Grid is the latest global bathymetric produc...\n",
+       "    title:        The GEBCO_2020 Grid - a continuous terrain model for oceans..."
       ]
      },
-     "execution_count": 102,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -529,7 +481,7 @@
    "source": [
     "st = time.time()\n",
     "ds = xr.open_zarr(\n",
-    "    'GEBCO_2022_sub_ice_topo.zarr', chunks='auto', \n",
+    "    'data/GEBCO_2023_sub_ice_topo.zarr', chunks='auto', \n",
     "    group='gebco', decode_cf=False, decode_times=False)\n",
     "\n",
     "et = time.time()\n",
@@ -539,14 +491,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 104,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Estimated memory usage: 7120.129395484924 Mb\n"
+      "Estimated memory usage: 7120.12939453125 Mb\n"
      ]
     }
    ],
@@ -557,7 +509,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 100,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -598,16 +550,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 58,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "array([2.55682213])"
+       "array([2.55699391])"
       ]
      },
-     "execution_count": 58,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -621,12 +573,12 @@
     "                     geodesic((loc[lk-1, 1], loc[lk-1, 0]),\n",
     "                              (loc[lk, 1], loc[lk, 0])).km))\n",
     "\n",
-    "curDist(np.array([[121.53967066033685,25.070035818788032], [121.56499lonx[414543,25.06911681954908]]))"
+    "curDist(np.array([[121.53967066033685,25.070035818788032], [121.56499414543,25.06911681954908]]))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 86,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -671,377 +623,378 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 87,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "72369 27616\n",
+      "72368 27615\n",
       "m, b: 0.06490248512891315 17.175908845785813\n",
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       "m, b: 0.6648659566106117 -55.749993007023775\n",
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-      "line:  72389 121.62083333333334 0.6197916666666704 121.61979166666667 25.110866122217857 27627\n",
-      "line:  72390 121.625 0.6239583333333333 121.62395833333333 25.11363639703707 27628\n",
-      "line:  72391 121.62916666666666 0.6281249999999962 121.628125 25.116406671856268 27628\n",
-      "line:  72392 121.63333333333333 0.632291666666659 121.63229166666666 25.11917694667548 27629\n",
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-      "line:  72396 121.64999999999998 0.6489583333333105 121.64895833333331 25.130258045952317 27632\n",
-      "line:  72397 121.65416666666664 0.6531249999999734 121.65312499999997 25.13302832077153 27632\n",
-      "line:  72398 121.65833333333336 0.6572916666666931 121.6572916666667 25.13579859559077 27633\n",
-      "line:  72399 121.66250000000002 0.661458333333356 121.66145833333336 25.138568870409983 27634\n",
-      "line:  72400 121.66666666666669 0.6656250000000189 121.66562500000002 25.141339145229182 27634\n",
-      "line:  72401 121.67083333333335 0.6697916666666818 121.66979166666668 25.144109420048395 27635\n",
-      "line:  72402 121.67500000000001 0.6739583333333447 121.67395833333335 25.146879694867607 27636\n",
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-      "line:  72404 121.68333333333334 0.6822916666666704 121.68229166666667 25.15242024450602 27637\n",
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-      "line:  72413 121.72083333333336 0.7197916666666931 121.7197916666667 25.177352717878932 27643\n",
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-      "line:  72415 121.72916666666669 0.7281250000000189 121.72812500000002 25.182893267517343 27644\n",
-      "line:  72416 121.73333333333335 0.7322916666666818 121.73229166666668 25.185663542336556 27645\n",
-      "line:  72417 121.73750000000001 0.7364583333333447 121.73645833333335 25.18843381715577 27646\n",
-      "line:  72418 121.74166666666667 0.7406250000000075 121.74062500000001 25.19120409197498 27646\n",
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-      "line:  72420 121.75 0.7489583333333333 121.74895833333333 25.196744641613392 27648\n",
-      "line:  72421 121.75416666666666 0.7531249999999962 121.753125 25.199514916432605 27648\n",
-      "line:  72422 121.75833333333333 0.757291666666659 121.75729166666666 25.202285191251804 27649\n",
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-      "line:  72426 121.77499999999998 0.7739583333333105 121.77395833333331 25.21336629052864 27652\n",
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-      "line:  72430 121.79166666666669 0.7906250000000189 121.79062500000002 25.22444738980552 27654\n",
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-      "line:  72432 121.80000000000001 0.7989583333333447 121.79895833333335 25.22998793944393 27656\n",
-      "line:  72433 121.80416666666667 0.8031250000000075 121.80312500000001 25.232758214263143 27656\n",
-      "line:  72434 121.80833333333334 0.8072916666666704 121.80729166666667 25.23552848908234 27657\n",
-      "line:  72435 121.8125 0.8114583333333333 121.81145833333333 25.238298763901554 27658\n",
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-      "line:  72438 121.82499999999999 0.8239583333333219 121.82395833333332 25.246609588359178 27660\n",
-      "line:  72439 121.82916666666665 0.8281249999999848 121.82812499999999 25.24937986317839 27660\n",
-      "line:  72440 121.83333333333331 0.8322916666666477 121.83229166666665 25.252150137997603 27661\n",
-      "line:  72441 121.83749999999998 0.8364583333333105 121.83645833333331 25.2549204128168 27662\n",
-      "line:  72442 121.84166666666664 0.8406249999999734 121.84062499999997 25.257690687636014 27662\n",
-      "line:  72443 121.84583333333336 0.8447916666666931 121.8447916666667 25.260460962455255 27663\n",
-      "line:  72444 121.85000000000002 0.848958333333356 121.84895833333336 25.263231237274468 27664\n",
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-      "line:  72448 121.86666666666667 0.8656250000000075 121.86562500000001 25.274312336551304 27666\n",
-      "line:  72449 121.87083333333334 0.8697916666666704 121.86979166666667 25.277082611370503 27667\n",
-      "line:  72450 121.875 0.8739583333333333 121.87395833333333 25.279852886189715 27668\n",
-      "line:  72451 121.87916666666666 0.8781249999999962 121.878125 25.282623161008928 27668\n",
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-      "Exe time:  0.20121383666992188 sec\n",
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+      "line:  72720 123.0 -0.0010416666666666667 122.99895833333333 26.02782708737665 27846\n",
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+      "line:  72729 123.03750000000002 0.03645833333335607 123.03645833333336 26.052759560749564 27852\n",
+      "Exe time:  0.13093948364257812 sec\n",
       "[[  0   0]\n",
       " [  0   1]\n",
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       " [238 361]]\n",
       "[[121.5345976   25.06380626]\n",
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       " [121.540625    25.06419745]\n",
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       " [121.553125    25.06654173]\n",
       " [121.55729167  25.069312  ]\n",
       " [121.56145833  25.07208227]\n",
@@ -1770,67 +1725,67 @@
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+      " 0.51777402 0.5177662  0.51775838 0.51775055 0.50541871]\n"
      ]
     }
    ],
@@ -1991,42 +1946,43 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 88,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "(239, 362)\n",
-      "(array([  0,   0,   0,   0,   0,   0,   0,   1,   2,   2,   3,   4,   4,\n",
-      "         5,   6,   6,   7,   8,   8,   9,  10,  10,  11,  12,  12,  13,\n",
-      "        14,  14,  15,  16,  16,  17,  18,  18,  19,  20,  20,  21,  22,\n",
-      "        22,  23,  24,  24,  25,  26,  26,  27,  28,  28,  29,  30,  30,\n",
-      "        31,  32,  32,  33,  34,  34,  35,  36,  36,  37,  38,  38,  39,\n",
-      "        40,  40,  41,  42,  42,  43,  44,  44,  45,  46,  46,  47,  48,\n",
-      "        48,  49,  50,  50,  51,  52,  52,  53,  54,  54,  55,  56,  56,\n",
-      "        57,  58,  58,  59,  60,  60,  61,  62,  62,  63,  64,  64,  65,\n",
-      "        66,  66,  67,  68,  68,  69,  70,  70,  71,  72,  72,  73,  74,\n",
-      "        74,  75,  76,  76,  77,  78,  78,  79,  80,  80,  81,  82,  82,\n",
-      "        83,  84,  84,  85,  86,  86,  87,  88,  88,  89,  90,  90,  91,\n",
-      "        92,  92,  93,  94,  94,  95,  96,  96,  97,  98,  98,  99, 100,\n",
-      "       100, 101, 102, 102, 103, 104, 104, 105, 106, 106, 107, 108, 108,\n",
-      "       109, 110, 110, 111, 112, 112, 113, 113, 114, 115, 115, 116, 117,\n",
-      "       117, 118, 119, 119, 120, 121, 121, 122, 123, 123, 124, 125, 125,\n",
-      "       126, 127, 127, 128, 129, 129, 130, 131, 131, 132, 133, 133, 134,\n",
-      "       135, 135, 136, 137, 137, 138, 139, 139, 140, 141, 141, 142, 143,\n",
-      "       143, 144, 145, 145, 146, 147, 147, 148, 149, 149, 150, 151, 151,\n",
-      "       152, 153, 153, 154, 155, 155, 156, 157, 157, 158, 159, 159, 160,\n",
-      "       161, 161, 162, 163, 163, 164, 165, 165, 166, 167, 167, 168, 169,\n",
-      "       169, 170, 171, 171, 172, 173, 173, 174, 175, 175, 176, 177, 177,\n",
-      "       178, 179, 179, 180, 181, 181, 182, 183, 183, 184, 185, 185, 186,\n",
-      "       187, 187, 188, 189, 189, 190, 191, 191, 192, 193, 193, 194, 195,\n",
-      "       195, 196, 197, 197, 198, 199, 199, 200, 201, 201, 202, 203, 203,\n",
-      "       204, 205, 205, 206, 207, 207, 208, 209, 209, 210, 211, 211, 212,\n",
-      "       213, 213, 214, 215, 215, 216, 217, 217, 218, 219, 219, 220, 221,\n",
-      "       221, 222, 223, 223, 224, 225, 225, 226, 227, 227, 228, 229, 229,\n",
-      "       230, 231, 231, 232, 233, 233, 234, 235, 235, 236, 236, 237, 238]), array([  0,   1,   2,   3,   3,   3,   4,   5,   6,   7,   8,   9,  10,\n",
+      "(240, 363)\n",
+      "(array([  0,   0,   0,   0,   0,   0,   0,   0,   1,   2,   2,   3,   4,\n",
+      "         4,   5,   6,   6,   7,   8,   8,   9,  10,  10,  11,  12,  12,\n",
+      "        13,  14,  14,  15,  16,  16,  17,  18,  18,  19,  20,  20,  21,\n",
+      "        22,  22,  23,  24,  24,  25,  26,  26,  27,  28,  28,  29,  30,\n",
+      "        30,  31,  32,  32,  33,  34,  34,  35,  36,  36,  37,  38,  38,\n",
+      "        39,  40,  40,  41,  42,  42,  43,  44,  44,  45,  46,  46,  47,\n",
+      "        48,  48,  49,  50,  50,  51,  52,  52,  53,  54,  54,  55,  56,\n",
+      "        56,  57,  58,  58,  59,  60,  60,  61,  62,  62,  63,  64,  64,\n",
+      "        65,  66,  66,  67,  68,  68,  69,  70,  70,  71,  72,  72,  73,\n",
+      "        74,  74,  75,  76,  76,  77,  78,  78,  79,  80,  80,  81,  82,\n",
+      "        82,  83,  84,  84,  85,  86,  86,  87,  88,  88,  89,  90,  90,\n",
+      "        91,  92,  92,  93,  94,  94,  95,  96,  96,  97,  98,  98,  99,\n",
+      "       100, 100, 101, 102, 102, 103, 104, 104, 105, 106, 106, 107, 108,\n",
+      "       108, 109, 110, 110, 111, 112, 112, 113, 113, 114, 115, 115, 116,\n",
+      "       117, 117, 118, 119, 119, 120, 121, 121, 122, 123, 123, 124, 125,\n",
+      "       125, 126, 127, 127, 128, 129, 129, 130, 131, 131, 132, 133, 133,\n",
+      "       134, 135, 135, 136, 137, 137, 138, 139, 139, 140, 141, 141, 142,\n",
+      "       143, 143, 144, 145, 145, 146, 147, 147, 148, 149, 149, 150, 151,\n",
+      "       151, 152, 153, 153, 154, 155, 155, 156, 157, 157, 158, 159, 159,\n",
+      "       160, 161, 161, 162, 163, 163, 164, 165, 165, 166, 167, 167, 168,\n",
+      "       169, 169, 170, 171, 171, 172, 173, 173, 174, 175, 175, 176, 177,\n",
+      "       177, 178, 179, 179, 180, 181, 181, 182, 183, 183, 184, 185, 185,\n",
+      "       186, 187, 187, 188, 189, 189, 190, 191, 191, 192, 193, 193, 194,\n",
+      "       195, 195, 196, 197, 197, 198, 199, 199, 200, 201, 201, 202, 203,\n",
+      "       203, 204, 205, 205, 206, 207, 207, 208, 209, 209, 210, 211, 211,\n",
+      "       212, 213, 213, 214, 215, 215, 216, 217, 217, 218, 219, 219, 220,\n",
+      "       221, 221, 222, 223, 223, 224, 225, 225, 226, 227, 227, 228, 229,\n",
+      "       229, 230, 231, 231, 232, 233, 233, 234, 235, 235, 236, 236, 237,\n",
+      "       238]), array([  0,   1,   2,   3,   3,   3,   4,   5,   6,   7,   8,   9,  10,\n",
       "        11,  12,  13,  14,  15,  16,  17,  18,  19,  20,  21,  22,  23,\n",
       "        24,  25,  26,  27,  28,  29,  30,  31,  32,  33,  34,  35,  36,\n",
       "        37,  38,  39,  40,  41,  42,  43,  44,  45,  46,  47,  48,  49,\n",
@@ -2053,34 +2009,36 @@
       "       310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322,\n",
       "       323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335,\n",
       "       336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348,\n",
-      "       349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361]))\n",
-      "Get index of points, time:  0.018686294555664062 sec\n",
-      "[   7    7    5    3    3    3    3    2    7    7   13   31   38   51\n",
-      "  116  124  171  285  213  217  227  154  172  188  126  247  277  269\n",
-      "  216  203  184  214  171  181  225  279  280  214  116   86  144  135\n",
-      "   13  -19  -35  -39  -43  -39  -42  -53  -62  -57  -61  -66  -65  -87\n",
-      "  -87  -89  -90  -90  -98  -99  -96  -97  -98 -104 -111 -121 -117 -115\n",
-      " -114 -125 -136 -155 -157 -162 -151 -142 -139 -134 -137 -141 -155 -153\n",
-      " -154 -157 -157 -155 -161 -164 -165 -165 -160 -159 -157 -157 -155 -159\n",
-      " -165 -165 -173 -179 -179 -182 -190 -194 -200 -211 -211 -213 -214 -214\n",
-      " -199 -199 -199 -199 -199 -199 -199 -199 -199 -199 -199 -199 -199 -199\n",
-      " -199 -199 -199 -199 -199 -199 -199 -198 -197 -197 -196 -195 -194 -194\n",
-      " -194 -194 -194 -194 -195 -196 -198 -200 -201 -200 -203 -204 -205 -206\n",
-      " -208 -206 -207 -205 -202 -203 -200 -196 -198 -200 -199 -205 -211 -208\n",
-      " -213 -216 -215 -216 -215 -210 -209 -201 -198 -191 -186 -186 -182 -184\n",
-      " -186 -187 -187 -187 -187 -187 -189 -185 -186 -186 -181 -176 -176 -171\n",
-      " -166 -166 -163 -163 -165 -163 -161 -161 -158 -155 -156 -152 -153 -153\n",
-      " -151 -149 -151 -152 -151 -151 -153 -158 -164 -160 -154 -154 -150 -122\n",
-      " -125 -142 -144 -144 -139 -135 -136 -134 -132 -132 -131 -132 -133 -132\n",
-      " -130 -131 -124 -129 -126 -128 -129 -129 -127 -125 -125 -123 -121 -121\n",
-      " -119 -119 -120 -121 -124 -116 -115 -121 -121 -115 -115 -115 -115 -115\n",
-      " -115 -115 -115 -115 -115 -116 -117 -117 -116 -116 -116 -116 -116 -115\n",
-      " -116 -116 -115 -114 -114 -113 -112 -112 -112 -113 -113 -112 -110 -110\n",
-      " -110 -109 -109 -109 -110 -110 -110 -110 -111 -111 -112 -112 -113 -113\n",
-      " -114 -115 -115 -115 -115 -115 -115 -114 -113 -113 -112 -111 -110 -110\n",
-      " -109 -109 -108 -108 -108 -107 -104 -104 -103 -102 -101 -100 -100 -100\n",
-      " -100 -100 -100 -100 -100 -100 -100 -100 -100 -100 -100 -100 -100 -100\n",
-      " -100  -99 -100 -100 -100 -100 -100  -98 -101 -101 -102 -102 -102 -102]\n"
+      "       349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361,\n",
+      "       361]))\n",
+      "Get index of points, time:  62.418522119522095 sec\n",
+      "[  10   11   10    5    5    5    7    5    5    3    1   12   18   20\n",
+      "   46   68   73  101  220  153  171  158  107  111  158  108  184  222\n",
+      "  267  188  199  181  198  187  148  184  253  256  217  157   76   99\n",
+      "  109   38   -7  -13  -20  -42  -46  -47  -51  -52  -49  -55  -60  -59\n",
+      "  -66  -81  -81  -89  -93  -98 -126 -104  -93  -95 -105 -121 -127 -119\n",
+      " -117 -111 -112 -108 -113 -148 -135 -138 -136 -133 -133 -136 -140 -147\n",
+      " -154 -153 -157 -158 -158 -156 -153 -154 -153 -154 -155 -155 -155 -156\n",
+      " -159 -162 -163 -168 -172 -173 -178 -179 -183 -187 -198 -198 -204 -205\n",
+      " -202 -199 -199 -199 -199 -199 -199 -199 -199 -199 -199 -199 -199 -199\n",
+      " -199 -199 -199 -199 -199 -199 -199 -199 -198 -197 -197 -196 -196 -195\n",
+      " -194 -193 -194 -194 -194 -195 -196 -198 -200 -202 -201 -204 -206 -207\n",
+      " -209 -209 -208 -210 -209 -207 -208 -206 -201 -203 -201 -201 -207 -215\n",
+      " -212 -218 -219 -220 -221 -216 -215 -213 -207 -204 -197 -190 -190 -186\n",
+      " -185 -187 -190 -192 -192 -192 -192 -194 -191 -187 -187 -185 -181 -180\n",
+      " -176 -171 -171 -167 -164 -166 -167 -166 -166 -164 -161 -162 -159 -154\n",
+      " -154 -154 -153 -156 -157 -157 -157 -159 -159 -167 -171 -168 -168 -162\n",
+      " -156 -161 -135 -139 -140 -145 -142 -143 -138 -135 -135 -134 -133 -134\n",
+      " -134 -131 -133 -133 -129 -130 -131 -129 -129 -129 -128 -128 -127 -125\n",
+      " -125 -124 -122 -120 -119 -118 -118 -117 -115 -116 -116 -116 -116 -116\n",
+      " -116 -116 -116 -116 -116 -116 -116 -117 -118 -117 -117 -117 -117 -117\n",
+      " -117 -115 -116 -116 -116 -116 -116 -114 -114 -113 -113 -113 -113 -112\n",
+      " -112 -111 -110 -110 -109 -110 -109 -110 -112 -110 -111 -111 -111 -112\n",
+      " -113 -114 -114 -115 -115 -115 -115 -115 -114 -113 -113 -113 -112 -111\n",
+      " -110 -109 -109 -109 -108 -108 -107 -106 -106 -104 -103 -103 -101 -100\n",
+      " -100 -100 -100 -100 -100  -97 -100 -100 -100 -100 -100 -100 -100 -100\n",
+      "  -99 -100 -100 -100 -100 -100 -100 -100 -100  -99  -99 -101 -101 -101\n",
+      " -102]\n"
      ]
     }
    ],
@@ -2131,56 +2089,48 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 96,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Pandas time:  0.001234292984008789 sec\n",
+      "Pandas time:  0.01806473731994629 sec\n",
       "      longitude   latitude    z\n",
-      "0    121.534598  25.063806    7\n",
-      "1    121.540625  25.064197    7\n",
-      "2    121.544792  25.064468    5\n",
-      "3    121.548958  25.064738    3\n",
-      "4    121.549847  25.064796    3\n",
+      "0    121.534598  25.063806   10\n",
+      "1    121.536458  25.063927   11\n",
+      "2    121.540625  25.064197   10\n",
+      "3    121.544792  25.064468    5\n",
+      "4    121.549847  25.064796    5\n",
       "..          ...        ...  ...\n",
-      "359  123.023958  26.044449 -101\n",
-      "360  123.028125  26.047219 -102\n",
-      "361  123.032292  26.049989 -102\n",
-      "362  123.036458  26.052760 -102\n",
-      "363  123.040526  26.055464 -102\n",
+      "360  123.023958  26.044449  -99\n",
+      "361  123.028125  26.047219 -101\n",
+      "362  123.032292  26.049989 -101\n",
+      "363  123.036458  26.052760 -101\n",
+      "364  123.040526  26.055464 -102\n",
       "\n",
-      "[364 rows x 3 columns]\n",
-      "Polars time:  0.0002620220184326172 sec\n",
-      "shape: (364, 3)\n",
+      "[365 rows x 3 columns]\n",
+      "Polars time:  0.10485339164733887 sec\n",
+      "shape: (365, 3)\n",
       "┌────────────┬───────────┬──────┐\n",
       "│ longitude  ┆ latitude  ┆ z    │\n",
       "│ ---        ┆ ---       ┆ ---  │\n",
       "│ f64        ┆ f64       ┆ i64  │\n",
       "╞════════════╪═══════════╪══════╡\n",
-      "│ 121.534598 ┆ 25.063806 ┆ 7    │\n",
-      "├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
-      "│ 121.540625 ┆ 25.064197 ┆ 7    │\n",
-      "├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
+      "│ 121.534598 ┆ 25.063806 ┆ 10   │\n",
+      "│ 121.536458 ┆ 25.063927 ┆ 11   │\n",
+      "│ 121.540625 ┆ 25.064197 ┆ 10   │\n",
       "│ 121.544792 ┆ 25.064468 ┆ 5    │\n",
-      "├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
-      "│ 121.548958 ┆ 25.064738 ┆ 3    │\n",
-      "├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
       "│ ...        ┆ ...       ┆ ...  │\n",
-      "├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
-      "│ 123.028125 ┆ 26.047219 ┆ -102 │\n",
-      "├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
-      "│ 123.032292 ┆ 26.049989 ┆ -102 │\n",
-      "├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
-      "│ 123.036458 ┆ 26.05276  ┆ -102 │\n",
-      "├╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌┤\n",
+      "│ 123.028125 ┆ 26.047219 ┆ -101 │\n",
+      "│ 123.032292 ┆ 26.049989 ┆ -101 │\n",
+      "│ 123.036458 ┆ 26.05276  ┆ -101 │\n",
       "│ 123.040526 ┆ 26.055464 ┆ -102 │\n",
       "└────────────┴───────────┴──────┘\n",
-      "Output Pandas time:  0.002108335494995117 sec\n",
-      "Output Polars time:  0.0013206005096435547 sec\n",
-      "<starlette.responses.JSONResponse object at 0x7f4049593280>\n"
+      "Output Pandas time:  0.004413604736328125 sec\n",
+      "Output Polars time:  0.04501008987426758 sec\n",
+      "<starlette.responses.JSONResponse object at 0x7f97bc268940>\n"
      ]
     }
    ],
diff --git a/zprofile02_crosszero.ipynb b/dev/zprofile02_crosszero.ipynb
similarity index 100%
rename from zprofile02_crosszero.ipynb
rename to dev/zprofile02_crosszero.ipynb
diff --git a/gebco_app.py b/gebco_app.py
index c3f0fa1..e3ef689 100644
--- a/gebco_app.py
+++ b/gebco_app.py
@@ -10,6 +10,7 @@
 from fastapi.responses import JSONResponse
 from fastapi.openapi.docs import get_swagger_ui_html
 from fastapi.openapi.utils import get_openapi
+from contextlib import asynccontextmanager
 from typing import Optional #, Union
 #from pydantic import BaseModel, ValidationError, HttpUrl, validator
 import requests #, httpx
@@ -17,7 +18,7 @@
 # import orjson
 # from loggerConfig import logger
 # from models import zprofSchema
-from xmeridian import *
+from src.xmeridian import *
 
 import dask
 from multiprocessing.pool import Pool
@@ -31,7 +32,8 @@ def generate_custom_openapi():
         title="ODB API for GEBCO Bathymetry",
         version="1.0.0",
         description="Z-profile (and distances) between longitude/latitude points with 15-arcsec resolutions.\n" +
-                    "Data source: GEBCO Compilation Group (2022) GEBCO_2022 Grid (doi:10.5285/e0f0bb80-ab44-2739-e053-6c86abc0289c)",
+                    #"Data source: GEBCO Compilation Group (2022) GEBCO_2022 Grid (doi:10.5285/e0f0bb80-ab44-2739-e053-6c86abc0289c)",
+                    "Data source: GEBCO Compilation Group (2023) GEBCO 2023 Grid (doi:10.5285/f98b053b-0cbc-6c23-e053-6c86abc0af7b)",
         routes=app.routes,
     )
     openapi_schema["servers"] = [
@@ -42,7 +44,26 @@ def generate_custom_openapi():
     app.openapi_schema = openapi_schema
     return app.openapi_schema
 
-app = FastAPI(docs_url=None)
+
+# @app.on_event("startup")
+# async def startup():
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+
+    #if 'ds' in kwargs:
+    #    ds = kwargs['ds']
+    #else:
+    global ds
+    # logger.info
+    ds = xr.open_zarr(
+        #'data/GEBCO_2022_sub_ice_topo.zarr', chunks='auto', group='gebco',
+        'data/GEBCO_2023_sub_ice_topo.zarr', chunks='auto',
+        decode_cf=False, decode_times=False)
+    yield
+    ds.close()
+
+
+app = FastAPI(docs_url=None, lifespan=lifespan)
 
 @app.get("/gebco/openapi.json", include_in_schema=False)
 async def custom_openapi():
@@ -66,17 +87,6 @@ async def custom_swagger_ui_html():
 subsetFlag = True
 
 
-@app.on_event("startup")
-async def startup():
-    #if 'ds' in kwargs:
-    #    ds = kwargs['ds']
-    #else:
-    global ds
-    # logger.info
-    ds = xr.open_zarr(
-        'GEBCO_2022_sub_ice_topo.zarr', chunks='auto', group='gebco',
-        decode_cf=False, decode_times=False)
-
 # @app.on_event("shutdown")
 # def release_dataset():
 #   global ds
diff --git a/read_gebco_raw01.ipynb b/read_gebco_raw01.ipynb
deleted file mode 100644
index b523534..0000000
--- a/read_gebco_raw01.ipynb
+++ /dev/null
@@ -1,1917 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Exe time:  0.004761219024658203 sec\n"
-     ]
-    },
-    {
-     "data": {
-      "text/html": [
-       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
-       "<defs>\n",
-       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
-       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
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-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
-       "Dimensions:    (lon: 86400, lat: 43200)\n",
-       "Coordinates:\n",
-       "  * lon        (lon) float64 -180.0 -180.0 -180.0 -180.0 ... 180.0 180.0 180.0\n",
-       "  * lat        (lat) float64 -90.0 -89.99 -89.99 -89.99 ... 89.99 89.99 90.0\n",
-       "Data variables:\n",
-       "    crs        |S1 ...\n",
-       "    elevation  (lat, lon) int16 dask.array&lt;chunksize=(43200, 86400), meta=np.ndarray&gt;\n",
-       "Attributes: (12/36)\n",
-       "    title:                           The GEBCO_2022 Grid - a continuous terra...\n",
-       "    summary:                         The GEBCO_2022 Grid is a continuous, glo...\n",
-       "    keywords:                        BATHYMETRY/SEAFLOOR TOPOGRAPHY, DIGITAL ...\n",
-       "    Conventions:                     CF-1.6, ACDD-1.3\n",
-       "    id:                              DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c8...\n",
-       "    naming_authority:                https://dx.doi.org\n",
-       "    ...                              ...\n",
-       "    geospatial_vertical_units:       meters\n",
-       "    geospatial_vertical_resolution:  1.0\n",
-       "    geospatial_vertical_positive:    up\n",
-       "    identifier_product_doi:          DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c8...\n",
-       "    references:                      DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c8...\n",
-       "    node_offset:                     1.0</pre><div class='xr-wrap' hidden><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-ae1edb43-6c50-4333-a538-8f9920c9cb5e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ae1edb43-6c50-4333-a538-8f9920c9cb5e' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lon</span>: 86400</li><li><span class='xr-has-index'>lat</span>: 43200</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-e19d09ab-fd1a-48a1-8d6a-5f9c9a22da12' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e19d09ab-fd1a-48a1-8d6a-5f9c9a22da12' 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 class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -180.0 ... 180.0 180.0</div><input id='attrs-613f8089-dd23-4bb3-a201-e1e815d6d4af' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-613f8089-dd23-4bb3-a201-e1e815d6d4af' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c80accb7-e337-4155-96fb-a83aa2acc4a5' class='xr-var-data-in' type='checkbox'><label for='data-c80accb7-e337-4155-96fb-a83aa2acc4a5' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>sdn_parameter_urn :</span></dt><dd>SDN:P01::ALONZZ01</dd><dt><span>sdn_parameter_name :</span></dt><dd>Longitude east</dd><dt><span>sdn_uom_urn :</span></dt><dd>SDN:P06::DEGE</dd><dt><span>sdn_uom_name :</span></dt><dd>Degrees east</dd></dl></div><div class='xr-var-data'><pre>array([-179.997917, -179.99375 , -179.989583, ...,  179.989583,  179.99375 ,\n",
-       "        179.997917])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.99 -89.99 ... 89.99 90.0</div><input id='attrs-54a49f87-3e38-4e59-b2f6-4d9ac4f26d51' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-54a49f87-3e38-4e59-b2f6-4d9ac4f26d51' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-043f276d-5498-459a-aa2b-f282f06fd8a1' class='xr-var-data-in' type='checkbox'><label for='data-043f276d-5498-459a-aa2b-f282f06fd8a1' 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>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>sdn_parameter_urn :</span></dt><dd>SDN:P01::ALATZZ01</dd><dt><span>sdn_parameter_name :</span></dt><dd>Latitude north</dd><dt><span>sdn_uom_urn :</span></dt><dd>SDN:P06::DEGN</dd><dt><span>sdn_uom_name :</span></dt><dd>Degrees north</dd></dl></div><div class='xr-var-data'><pre>array([-89.997917, -89.99375 , -89.989583, ...,  89.989583,  89.99375 ,\n",
-       "        89.997917])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-447d489a-8cad-4792-9070-646750890db2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-447d489a-8cad-4792-9070-646750890db2' class='xr-section-summary' >Data variables: <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>crs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>|S1</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-821651fe-b659-47b0-9fba-9e155af462ca' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-821651fe-b659-47b0-9fba-9e155af462ca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0aa7893-f372-4918-962e-150cc9591fdb' class='xr-var-data-in' type='checkbox'><label for='data-f0aa7893-f372-4918-962e-150cc9591fdb' 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>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>epsg_code :</span></dt><dd>EPSG:4326</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd></dl></div><div class='xr-var-data'><pre>array(b&#x27;&#x27;, dtype=&#x27;|S1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>elevation</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(43200, 86400), meta=np.ndarray&gt;</div><input id='attrs-52f8ad12-167a-4822-8d38-776d2a014fc7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-52f8ad12-167a-4822-8d38-776d2a014fc7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c47e3265-8e91-4064-bc65-6d1de783dfc0' class='xr-var-data-in' type='checkbox'><label for='data-c47e3265-8e91-4064-bc65-6d1de783dfc0' 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>standard_name :</span></dt><dd>height_above_mean_sea_level</dd><dt><span>long_name :</span></dt><dd>Elevation relative to sea level</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>sdn_parameter_urn :</span></dt><dd>SDN:P01::ALATZZ01</dd><dt><span>sdn_parameter_name :</span></dt><dd>Sea floor height (above mean sea level) {bathymetric height}</dd><dt><span>sdn_uom_urn :</span></dt><dd>SDN:P06::ULAA</dd><dt><span>sdn_uom_name :</span></dt><dd>Metres</dd></dl></div><div class='xr-var-data'><table>\n",
-       "    <tr>\n",
-       "        <td>\n",
-       "            <table style=\"border-collapse: collapse;\">\n",
-       "                <thead>\n",
-       "                    <tr>\n",
-       "                        <td> </td>\n",
-       "                        <th> Array </th>\n",
-       "                        <th> Chunk </th>\n",
-       "                    </tr>\n",
-       "                </thead>\n",
-       "                <tbody>\n",
-       "                    \n",
-       "                    <tr>\n",
-       "                        <th> Bytes </th>\n",
-       "                        <td> 6.95 GiB </td>\n",
-       "                        <td> 6.95 GiB </td>\n",
-       "                    </tr>\n",
-       "                    \n",
-       "                    <tr>\n",
-       "                        <th> Shape </th>\n",
-       "                        <td> (43200, 86400) </td>\n",
-       "                        <td> (43200, 86400) </td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <th> Dask graph </th>\n",
-       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <th> Data type </th>\n",
-       "                        <td colspan=\"2\"> int16 numpy.ndarray </td>\n",
-       "                    </tr>\n",
-       "                </tbody>\n",
-       "            </table>\n",
-       "        </td>\n",
-       "        <td>\n",
-       "        <svg width=\"170\" height=\"110\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
-       "\n",
-       "  <!-- Horizontal lines -->\n",
-       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
-       "  <line x1=\"0\" y1=\"60\" x2=\"120\" y2=\"60\" style=\"stroke-width:2\" />\n",
-       "\n",
-       "  <!-- Vertical lines -->\n",
-       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"60\" style=\"stroke-width:2\" />\n",
-       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"60\" style=\"stroke-width:2\" />\n",
-       "\n",
-       "  <!-- Colored Rectangle -->\n",
-       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,60.0 0.0,60.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
-       "\n",
-       "  <!-- Text -->\n",
-       "  <text x=\"60.000000\" y=\"80.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >86400</text>\n",
-       "  <text x=\"140.000000\" y=\"30.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,30.000000)\">43200</text>\n",
-       "</svg>\n",
-       "        </td>\n",
-       "    </tr>\n",
-       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-b8a71372-c317-4dbb-be96-94b2b77c318a' class='xr-section-summary-in' type='checkbox'  ><label for='section-b8a71372-c317-4dbb-be96-94b2b77c318a' class='xr-section-summary' >Attributes: <span>(36)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>title :</span></dt><dd>The GEBCO_2022 Grid - a continuous terrain model for oceans and land at 15 arc-second intervals</dd><dt><span>summary :</span></dt><dd>The GEBCO_2022 Grid is a continuous, global terrain model for ocean and land with a spatial resolution of 15 arc seconds.The grid uses as a base-map Version 2.4 of the SRTM15+ data set (Tozer et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. It is augmented with gridded bathymetric data sets developed as part of the Nippon Foundation-GEBCO Seabed 2030 Project.</dd><dt><span>keywords :</span></dt><dd>BATHYMETRY/SEAFLOOR TOPOGRAPHY, DIGITAL ELEVATION/DIGITAL TERRAIN MODELS</dd><dt><span>Conventions :</span></dt><dd>CF-1.6, ACDD-1.3</dd><dt><span>id :</span></dt><dd>DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c86abc0289c</dd><dt><span>naming_authority :</span></dt><dd>https://dx.doi.org</dd><dt><span>history :</span></dt><dd>Information on the development of the data set and the source data sets included in the grid can be found in the data set documentation available from https://www.gebco.net</dd><dt><span>source :</span></dt><dd>The GEBCO_2022 Grid is the latest global bathymetric product released by the General Bathymetric Chart of the Oceans (GEBCO) and has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and GEBCO. The Seabed 2030 Project aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor and make it available to all.</dd><dt><span>comment :</span></dt><dd>The data in the GEBCO_2022 Grid should not be used for navigation or any purpose relating to safety at sea.</dd><dt><span>license :</span></dt><dd>The GEBCO Grid is placed in the public domain and may be used free of charge. Use of the GEBCO Grid indicates that the user accepts the conditions of use and disclaimer information: https://www.gebco.net/data_and_products/gridded_bathymetry_data/gebco_2019/grid_terms_of_use.html</dd><dt><span>date_created :</span></dt><dd>2022-06-22</dd><dt><span>creator_name :</span></dt><dd>GEBCO through the Nippon Foundation-GEBCO Seabed 2030 Project</dd><dt><span>creator_email :</span></dt><dd>gdacc@seabed2030.org</dd><dt><span>creator_url :</span></dt><dd>https://www.gebco.net</dd><dt><span>institution :</span></dt><dd>On behalf of the General Bathymetric Chart of the Oceans (GEBCO), the data are held at the British Oceanographic Data Centre (BODC).</dd><dt><span>project :</span></dt><dd>Nippon Foundation - GEBCO Seabed2030 Project</dd><dt><span>creator_type :</span></dt><dd>International organisation</dd><dt><span>geospatial_bounds :</span></dt><dd>[-180.  -90.  180.   90.]</dd><dt><span>geospatial_bounds_crs :</span></dt><dd>WGS84</dd><dt><span>geospatial_bounds_vertical_crs :</span></dt><dd>EPSG:5831</dd><dt><span>geospatial_lat_min :</span></dt><dd>-90.0</dd><dt><span>geospatial_lat_max :</span></dt><dd>90.0</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees_north</dd><dt><span>geospatial_lat_resolution :</span></dt><dd>0.004166666666666667</dd><dt><span>geospatial_lon_min :</span></dt><dd>-180.0</dd><dt><span>geospatial_lon_max :</span></dt><dd>180.0</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees_east</dd><dt><span>geospatial_lon_resolution :</span></dt><dd>0.004166666666666667</dd><dt><span>geospatial_vertical_min :</span></dt><dd>-10977.0</dd><dt><span>geospatial_vertical_max :</span></dt><dd>8685.0</dd><dt><span>geospatial_vertical_units :</span></dt><dd>meters</dd><dt><span>geospatial_vertical_resolution :</span></dt><dd>1.0</dd><dt><span>geospatial_vertical_positive :</span></dt><dd>up</dd><dt><span>identifier_product_doi :</span></dt><dd>DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c86abc0289c</dd><dt><span>references :</span></dt><dd>DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c86abc0289c</dd><dt><span>node_offset :</span></dt><dd>1.0</dd></dl></div></li></ul></div></div>"
-      ],
-      "text/plain": [
-       "<xarray.Dataset>\n",
-       "Dimensions:    (lon: 86400, lat: 43200)\n",
-       "Coordinates:\n",
-       "  * lon        (lon) float64 -180.0 -180.0 -180.0 -180.0 ... 180.0 180.0 180.0\n",
-       "  * lat        (lat) float64 -90.0 -89.99 -89.99 -89.99 ... 89.99 89.99 90.0\n",
-       "Data variables:\n",
-       "    crs        |S1 ...\n",
-       "    elevation  (lat, lon) int16 dask.array<chunksize=(43200, 86400), meta=np.ndarray>\n",
-       "Attributes: (12/36)\n",
-       "    title:                           The GEBCO_2022 Grid - a continuous terra...\n",
-       "    summary:                         The GEBCO_2022 Grid is a continuous, glo...\n",
-       "    keywords:                        BATHYMETRY/SEAFLOOR TOPOGRAPHY, DIGITAL ...\n",
-       "    Conventions:                     CF-1.6, ACDD-1.3\n",
-       "    id:                              DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c8...\n",
-       "    naming_authority:                https://dx.doi.org\n",
-       "    ...                              ...\n",
-       "    geospatial_vertical_units:       meters\n",
-       "    geospatial_vertical_resolution:  1.0\n",
-       "    geospatial_vertical_positive:    up\n",
-       "    identifier_product_doi:          DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c8...\n",
-       "    references:                      DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c8...\n",
-       "    node_offset:                     1.0"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "import xarray as xr\n",
-    "import time\n",
-    "st = time.time()\n",
-    "#xr.open_mfdataset('~/R/gebco/*.nc', parallel=True)\n",
-    "ds = xr.open_mfdataset(\n",
-    "    'GEBCO_2022_sub_ice_topo.nc', chunks={0: 60, 1: 60}, \n",
-    "    decode_cf=False, decode_times=False) #.load()\n",
-    "et = time.time()\n",
-    "print('Exe time: ', et-st, 'sec')\n",
-    "ds"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "112\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "6.9522857666015625"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "print(sys.getsizeof(ds))\n",
-    "ds['elevation'].nbytes/(1024 ** 3)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "larger-chunk read time:  0.0073223114013671875 sec\n",
-      "112\n",
-      "smaller-chunk read time:  0.0045816898345947266 sec\n",
-      "112\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "6.9522857666015625"
-      ]
-     },
-     "execution_count": 11,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "st = time.time()\n",
-    "#larger chunk size\n",
-    "ds2 = xr.open_mfdataset(\n",
-    "    'GEBCO_2022_sub_ice_topo.nc', chunks={0: 120, 1: 120}, \n",
-    "    decode_cf=False, decode_times=False) #.load()\n",
-    "et = time.time()\n",
-    "print('larger-chunk read time: ', et-st, 'sec')\n",
-    "print(sys.getsizeof(ds2))\n",
-    "ds2['elevation'].nbytes/(1024 ** 3)\n",
-    "\n",
-    "st = time.time()\n",
-    "#smaller chunk size\n",
-    "ds3 = xr.open_mfdataset(\n",
-    "    'GEBCO_2022_sub_ice_topo.nc', chunks={0: 30, 1: 30}, \n",
-    "    decode_cf=False, decode_times=False) #.load()\n",
-    "et = time.time()\n",
-    "print('smaller-chunk read time: ', et-st, 'sec')\n",
-    "print(sys.getsizeof(ds2))\n",
-    "ds2['elevation'].nbytes/(1024 ** 3)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 33,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "-3949\n",
-      "-4278\n",
-      "-4819\n",
-      "-4766\n",
-      "-3729\n",
-      "-3714\n",
-      "-3739\n",
-      "-3677\n",
-      "-3813\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(ds.sel(lat=23.326173, lon=123.978125, method='nearest')['elevation'].values)\n",
-    "print(ds.sel(lat=23.317670, lon=123.973958, method='nearest')['elevation'].values)\n",
-    "print(ds.sel(lat=21.336378, lon=123.003125, method='nearest')['elevation'].values)\n",
-    "print(ds.sel(lat=21.33, lon=123.0, method='nearest')['elevation'].values)\n",
-    "print(ds[\"elevation\"].values[27200,72956]) #this is correct value (got depth = -3729)\n",
-    "print(ds[\"elevation\"].values[27200,72957])\n",
-    "print(ds[\"elevation\"].values[27200,72955])\n",
-    "print(ds[\"elevation\"].values[27201,72956])\n",
-    "print(ds[\"elevation\"].values[27199,72956]) #But we got -3813, this is: after subset got a latitude offset 1? why (in zprofile01.ipynb correct it)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Slicing time for chunk-60:  0.0011551380157470703 sec\n",
-      "Slicing time for larger chunk:  0.0008370876312255859 sec\n",
-      "Exe time for smaller chunk:  0.000701904296875 sec\n"
-     ]
-    }
-   ],
-   "source": [
-    "#The following try different subsetting and index methods\n",
-    "st = time.time()\n",
-    "ds_s1 = ds.sel(lon=slice(105, 135), lat=slice(2, 35)) \n",
-    "ds_s1.close() #try if it can close\n",
-    "et = time.time()\n",
-    "print('Slicing time for chunk-60: ', et-st, 'sec')\n",
-    "\n",
-    "st = time.time()\n",
-    "ds_s2 = ds2.sel(lon=slice(105, 135), lat=slice(2, 35)) \n",
-    "ds_s2.close() #try if it can close\n",
-    "et = time.time()\n",
-    "print('Slicing time for larger chunk: ', et-st, 'sec')\n",
-    "\n",
-    "st = time.time()\n",
-    "ds_s3 = ds3.sel(lon=slice(105, 135), lat=slice(2, 35)) \n",
-    "ds_s3.close() #try if it can close\n",
-    "et = time.time()\n",
-    "print('Exe time for smaller chunk: ', et-st, 'sec')"
-   ]
-  },
-  {
-   "cell_type": "code",
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-       "Dimensions:    (lon: 7200, lat: 7920)\n",
-       "Coordinates:\n",
-       "  * lon        (lon) float64 105.0 105.0 105.0 105.0 ... 135.0 135.0 135.0 135.0\n",
-       "  * lat        (lat) float64 2.002 2.006 2.01 2.015 ... 34.99 34.99 34.99 35.0\n",
-       "Data variables:\n",
-       "    crs        |S1 ...\n",
-       "    elevation  (lat, lon) int16 dask.array&lt;chunksize=(7920, 7200), meta=np.ndarray&gt;\n",
-       "Attributes: (12/36)\n",
-       "    title:                           The GEBCO_2022 Grid - a continuous terra...\n",
-       "    summary:                         The GEBCO_2022 Grid is a continuous, glo...\n",
-       "    keywords:                        BATHYMETRY/SEAFLOOR TOPOGRAPHY, DIGITAL ...\n",
-       "    Conventions:                     CF-1.6, ACDD-1.3\n",
-       "    id:                              DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c8...\n",
-       "    naming_authority:                https://dx.doi.org\n",
-       "    ...                              ...\n",
-       "    geospatial_vertical_units:       meters\n",
-       "    geospatial_vertical_resolution:  1.0\n",
-       "    geospatial_vertical_positive:    up\n",
-       "    identifier_product_doi:          DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c8...\n",
-       "    references:                      DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c8...\n",
-       "    node_offset:                     1.0</pre><div class='xr-wrap' hidden><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-5d64e4ef-29b9-4a87-9945-b74cd9f500bc' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5d64e4ef-29b9-4a87-9945-b74cd9f500bc' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lon</span>: 7200</li><li><span class='xr-has-index'>lat</span>: 7920</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-830255de-6beb-436b-9b78-0e4079cde244' class='xr-section-summary-in' type='checkbox'  checked><label for='section-830255de-6beb-436b-9b78-0e4079cde244' 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 class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>105.0 105.0 105.0 ... 135.0 135.0</div><input id='attrs-695f8fc4-70dd-4622-8f8d-673c681a4ebc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-695f8fc4-70dd-4622-8f8d-673c681a4ebc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8af14c85-2fb3-4957-b018-62cdc624d5a6' class='xr-var-data-in' type='checkbox'><label for='data-8af14c85-2fb3-4957-b018-62cdc624d5a6' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>sdn_parameter_urn :</span></dt><dd>SDN:P01::ALONZZ01</dd><dt><span>sdn_parameter_name :</span></dt><dd>Longitude east</dd><dt><span>sdn_uom_urn :</span></dt><dd>SDN:P06::DEGE</dd><dt><span>sdn_uom_name :</span></dt><dd>Degrees east</dd></dl></div><div class='xr-var-data'><pre>array([105.002083, 105.00625 , 105.010417, ..., 134.989583, 134.99375 ,\n",
-       "       134.997917])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.002 2.006 2.01 ... 34.99 35.0</div><input id='attrs-252c09ae-d9a6-412c-a99e-a540ee14bbc4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-252c09ae-d9a6-412c-a99e-a540ee14bbc4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-01365b4f-5fa3-4e68-8b55-d4f491b0af2e' class='xr-var-data-in' type='checkbox'><label for='data-01365b4f-5fa3-4e68-8b55-d4f491b0af2e' 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>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>sdn_parameter_urn :</span></dt><dd>SDN:P01::ALATZZ01</dd><dt><span>sdn_parameter_name :</span></dt><dd>Latitude north</dd><dt><span>sdn_uom_urn :</span></dt><dd>SDN:P06::DEGN</dd><dt><span>sdn_uom_name :</span></dt><dd>Degrees north</dd></dl></div><div class='xr-var-data'><pre>array([ 2.002083,  2.00625 ,  2.010417, ..., 34.989583, 34.99375 , 34.997917])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-bad99005-5590-422f-9dc6-f068d24f2000' class='xr-section-summary-in' type='checkbox'  checked><label for='section-bad99005-5590-422f-9dc6-f068d24f2000' class='xr-section-summary' >Data variables: <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>crs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>|S1</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-60b7ac49-66c9-4d07-b075-ab16cfc195a7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-60b7ac49-66c9-4d07-b075-ab16cfc195a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dab2cc4d-942e-4d00-81b0-dd3bb4cc2f77' class='xr-var-data-in' type='checkbox'><label for='data-dab2cc4d-942e-4d00-81b0-dd3bb4cc2f77' 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>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>epsg_code :</span></dt><dd>EPSG:4326</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd></dl></div><div class='xr-var-data'><pre>array(b&#x27;&#x27;, dtype=&#x27;|S1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>elevation</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(7920, 7200), meta=np.ndarray&gt;</div><input id='attrs-5e6e806d-07f4-4534-a1e3-c4f900d206ac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5e6e806d-07f4-4534-a1e3-c4f900d206ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2fb102c6-fbf1-42e9-9103-b0600b56b813' class='xr-var-data-in' type='checkbox'><label for='data-2fb102c6-fbf1-42e9-9103-b0600b56b813' 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>standard_name :</span></dt><dd>height_above_mean_sea_level</dd><dt><span>long_name :</span></dt><dd>Elevation relative to sea level</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>sdn_parameter_urn :</span></dt><dd>SDN:P01::ALATZZ01</dd><dt><span>sdn_parameter_name :</span></dt><dd>Sea floor height (above mean sea level) {bathymetric height}</dd><dt><span>sdn_uom_urn :</span></dt><dd>SDN:P06::ULAA</dd><dt><span>sdn_uom_name :</span></dt><dd>Metres</dd></dl></div><div class='xr-var-data'><table>\n",
-       "    <tr>\n",
-       "        <td>\n",
-       "            <table style=\"border-collapse: collapse;\">\n",
-       "                <thead>\n",
-       "                    <tr>\n",
-       "                        <td> </td>\n",
-       "                        <th> Array </th>\n",
-       "                        <th> Chunk </th>\n",
-       "                    </tr>\n",
-       "                </thead>\n",
-       "                <tbody>\n",
-       "                    \n",
-       "                    <tr>\n",
-       "                        <th> Bytes </th>\n",
-       "                        <td> 108.76 MiB </td>\n",
-       "                        <td> 108.76 MiB </td>\n",
-       "                    </tr>\n",
-       "                    \n",
-       "                    <tr>\n",
-       "                        <th> Shape </th>\n",
-       "                        <td> (7920, 7200) </td>\n",
-       "                        <td> (7920, 7200) </td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <th> Dask graph </th>\n",
-       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <th> Data type </th>\n",
-       "                        <td colspan=\"2\"> int16 numpy.ndarray </td>\n",
-       "                    </tr>\n",
-       "                </tbody>\n",
-       "            </table>\n",
-       "        </td>\n",
-       "        <td>\n",
-       "        <svg width=\"159\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
-       "\n",
-       "  <!-- Horizontal lines -->\n",
-       "  <line x1=\"0\" y1=\"0\" x2=\"109\" y2=\"0\" style=\"stroke-width:2\" />\n",
-       "  <line x1=\"0\" y1=\"120\" x2=\"109\" y2=\"120\" style=\"stroke-width:2\" />\n",
-       "\n",
-       "  <!-- Vertical lines -->\n",
-       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
-       "  <line x1=\"109\" y1=\"0\" x2=\"109\" y2=\"120\" style=\"stroke-width:2\" />\n",
-       "\n",
-       "  <!-- Colored Rectangle -->\n",
-       "  <polygon points=\"0.0,0.0 109.09090909090908,0.0 109.09090909090908,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
-       "\n",
-       "  <!-- Text -->\n",
-       "  <text x=\"54.545455\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >7200</text>\n",
-       "  <text x=\"129.090909\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,129.090909,60.000000)\">7920</text>\n",
-       "</svg>\n",
-       "        </td>\n",
-       "    </tr>\n",
-       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-6fe8b7f1-5238-43f6-ab42-5151cc15f013' class='xr-section-summary-in' type='checkbox'  ><label for='section-6fe8b7f1-5238-43f6-ab42-5151cc15f013' class='xr-section-summary' >Attributes: <span>(36)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>title :</span></dt><dd>The GEBCO_2022 Grid - a continuous terrain model for oceans and land at 15 arc-second intervals</dd><dt><span>summary :</span></dt><dd>The GEBCO_2022 Grid is a continuous, global terrain model for ocean and land with a spatial resolution of 15 arc seconds.The grid uses as a base-map Version 2.4 of the SRTM15+ data set (Tozer et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. It is augmented with gridded bathymetric data sets developed as part of the Nippon Foundation-GEBCO Seabed 2030 Project.</dd><dt><span>keywords :</span></dt><dd>BATHYMETRY/SEAFLOOR TOPOGRAPHY, DIGITAL ELEVATION/DIGITAL TERRAIN MODELS</dd><dt><span>Conventions :</span></dt><dd>CF-1.6, ACDD-1.3</dd><dt><span>id :</span></dt><dd>DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c86abc0289c</dd><dt><span>naming_authority :</span></dt><dd>https://dx.doi.org</dd><dt><span>history :</span></dt><dd>Information on the development of the data set and the source data sets included in the grid can be found in the data set documentation available from https://www.gebco.net</dd><dt><span>source :</span></dt><dd>The GEBCO_2022 Grid is the latest global bathymetric product released by the General Bathymetric Chart of the Oceans (GEBCO) and has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and GEBCO. The Seabed 2030 Project aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor and make it available to all.</dd><dt><span>comment :</span></dt><dd>The data in the GEBCO_2022 Grid should not be used for navigation or any purpose relating to safety at sea.</dd><dt><span>license :</span></dt><dd>The GEBCO Grid is placed in the public domain and may be used free of charge. Use of the GEBCO Grid indicates that the user accepts the conditions of use and disclaimer information: https://www.gebco.net/data_and_products/gridded_bathymetry_data/gebco_2019/grid_terms_of_use.html</dd><dt><span>date_created :</span></dt><dd>2022-06-22</dd><dt><span>creator_name :</span></dt><dd>GEBCO through the Nippon Foundation-GEBCO Seabed 2030 Project</dd><dt><span>creator_email :</span></dt><dd>gdacc@seabed2030.org</dd><dt><span>creator_url :</span></dt><dd>https://www.gebco.net</dd><dt><span>institution :</span></dt><dd>On behalf of the General Bathymetric Chart of the Oceans (GEBCO), the data are held at the British Oceanographic Data Centre (BODC).</dd><dt><span>project :</span></dt><dd>Nippon Foundation - GEBCO Seabed2030 Project</dd><dt><span>creator_type :</span></dt><dd>International organisation</dd><dt><span>geospatial_bounds :</span></dt><dd>[-180.  -90.  180.   90.]</dd><dt><span>geospatial_bounds_crs :</span></dt><dd>WGS84</dd><dt><span>geospatial_bounds_vertical_crs :</span></dt><dd>EPSG:5831</dd><dt><span>geospatial_lat_min :</span></dt><dd>-90.0</dd><dt><span>geospatial_lat_max :</span></dt><dd>90.0</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees_north</dd><dt><span>geospatial_lat_resolution :</span></dt><dd>0.004166666666666667</dd><dt><span>geospatial_lon_min :</span></dt><dd>-180.0</dd><dt><span>geospatial_lon_max :</span></dt><dd>180.0</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees_east</dd><dt><span>geospatial_lon_resolution :</span></dt><dd>0.004166666666666667</dd><dt><span>geospatial_vertical_min :</span></dt><dd>-10977.0</dd><dt><span>geospatial_vertical_max :</span></dt><dd>8685.0</dd><dt><span>geospatial_vertical_units :</span></dt><dd>meters</dd><dt><span>geospatial_vertical_resolution :</span></dt><dd>1.0</dd><dt><span>geospatial_vertical_positive :</span></dt><dd>up</dd><dt><span>identifier_product_doi :</span></dt><dd>DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c86abc0289c</dd><dt><span>references :</span></dt><dd>DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c86abc0289c</dd><dt><span>node_offset :</span></dt><dd>1.0</dd></dl></div></li></ul></div></div>"
-      ],
-      "text/plain": [
-       "<xarray.Dataset>\n",
-       "Dimensions:    (lon: 7200, lat: 7920)\n",
-       "Coordinates:\n",
-       "  * lon        (lon) float64 105.0 105.0 105.0 105.0 ... 135.0 135.0 135.0 135.0\n",
-       "  * lat        (lat) float64 2.002 2.006 2.01 2.015 ... 34.99 34.99 34.99 35.0\n",
-       "Data variables:\n",
-       "    crs        |S1 ...\n",
-       "    elevation  (lat, lon) int16 dask.array<chunksize=(7920, 7200), meta=np.ndarray>\n",
-       "Attributes: (12/36)\n",
-       "    title:                           The GEBCO_2022 Grid - a continuous terra...\n",
-       "    summary:                         The GEBCO_2022 Grid is a continuous, glo...\n",
-       "    keywords:                        BATHYMETRY/SEAFLOOR TOPOGRAPHY, DIGITAL ...\n",
-       "    Conventions:                     CF-1.6, ACDD-1.3\n",
-       "    id:                              DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c8...\n",
-       "    naming_authority:                https://dx.doi.org\n",
-       "    ...                              ...\n",
-       "    geospatial_vertical_units:       meters\n",
-       "    geospatial_vertical_resolution:  1.0\n",
-       "    geospatial_vertical_positive:    up\n",
-       "    identifier_product_doi:          DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c8...\n",
-       "    references:                      DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c8...\n",
-       "    node_offset:                     1.0"
-      ]
-     },
-     "execution_count": 14,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "#da1 = getattr(ds_s1, 'elevation')\n",
-    "#da1\n",
-    "#https://www.programcreek.com/python/example/123571/xarray.decode_cf\n",
-    "#da1.attrs['_Unsigned']='false'\n",
-    "ds_s1\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "#da1"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "NameError",
-     "evalue": "name 'ds_s1' is not defined",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[0;32m/tmp/ipykernel_1649730/530195383.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0mst\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mst1\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mds_s1\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0misel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlon\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mslice\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1000\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m1010\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlat\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mslice\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m2000\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m2010\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      3\u001b[0m \u001b[0mxt1\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mst1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'elevation'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0met\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Exe time: '\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0met\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0mst\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'sec'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;31mNameError\u001b[0m: name 'ds_s1' is not defined"
-     ]
-    }
-   ],
-   "source": [
-    "st = time.time()\n",
-    "st1 = ds_s1.isel(lon=slice(1000, 1010), lat=slice(2000, 2010))\n",
-    "xt1 = st1['elevation'].values\n",
-    "et = time.time()\n",
-    "print('Exe time: ', et-st, 'sec')\n",
-    "print(xt1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "(10, 10)\n",
-      "3.1 Get index of point by two subsetting time:  0.0030269622802734375 sec\n",
-      "[[3 4]\n",
-      " [1 2]]\n",
-      "(array([3, 1]), array([4, 2]))\n",
-      "<xarray.Dataset>\n",
-      "Dimensions:    (lon: 10, lat: 10)\n",
-      "Coordinates:\n",
-      "  * lon        (lon) float64 109.2 109.2 109.2 109.2 ... 109.2 109.2 109.2 109.2\n",
-      "  * lat        (lat) float64 10.34 10.34 10.34 10.35 ... 10.36 10.36 10.37 10.37\n",
-      "Data variables:\n",
-      "    crs        |S1 ...\n",
-      "    elevation  (lat, lon) int16 dask.array<chunksize=(10, 10), meta=np.ndarray>\n",
-      "Attributes: (12/36)\n",
-      "    title:                           The GEBCO_2022 Grid - a continuous terra...\n",
-      "    summary:                         The GEBCO_2022 Grid is a continuous, glo...\n",
-      "    keywords:                        BATHYMETRY/SEAFLOOR TOPOGRAPHY, DIGITAL ...\n",
-      "    Conventions:                     CF-1.6, ACDD-1.3\n",
-      "    id:                              DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c8...\n",
-      "    naming_authority:                https://dx.doi.org\n",
-      "    ...                              ...\n",
-      "    geospatial_vertical_units:       meters\n",
-      "    geospatial_vertical_resolution:  1.0\n",
-      "    geospatial_vertical_positive:    up\n",
-      "    identifier_product_doi:          DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c8...\n",
-      "    references:                      DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c8...\n",
-      "    node_offset:                     1.0\n",
-      "3.2 Get index of point by numpy ix_ time:  0.003170490264892578 sec\n",
-      "[-117, -119]\n",
-      "[-117 -119]\n"
-     ]
-    }
-   ],
-   "source": [
-    "import numpy as np\n",
-    "print(st1[\"elevation\"].shape)\n",
-    "st = time.time()\n",
-    "pt1 = [st1[\"elevation\"].values[3,4], st1[\"elevation\"].values[1,2]]\n",
-    "et = time.time()\n",
-    "print('3.1 Get index of point by two subsetting time: ', et-st, 'sec')\n",
-    "\n",
-    "st = time.time()\n",
-    "#pt2 = st1[\"elevation\"].values[np.ix_([3,4],[1,2])]\n",
-    "idx_arr = np.array([[3,4],[1,2]])\n",
-    "print(idx_arr)\n",
-    "print(tuple(idx_arr.T))\n",
-    "#https://stackoverflow.com/questions/43034563/numpy-array-of-multiple-indices-replace-with-a-different-matrix\n",
-    "pt2=st1['elevation'].values[tuple(idx_arr.T)]\n",
-    "et = time.time()\n",
-    "print('3.2 Get index of point by numpy ix_ time: ', et-st, 'sec')\n",
-    "print(pt1)\n",
-    "print(pt2)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "#slow\n",
-    "x = xr.DataArray([-45,-44.95833,-44,-43.95822], dims=['longitude'])\n",
-    "y = xr.DataArray([35,35.004167,36,36.004168], dims=['latitude'])\n",
-    "st = time.time()\n",
-    "#ds_s2 = ds.sel(lon=x, lat=y, method='nearest')  \n",
-    "et = time.time()\n",
-    "#print('Exe time: ', et-st, 'sec')\n",
-    "#print(ds_s2)               \n",
-    "#print(ds_s2['elevation'].values)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "#https://stackoverflow.com/questions/58706834/angled-slice-in-xarray\n",
-    "startLat = 35.0\n",
-    "startLon = -45.0\n",
-    "endLat = 36.0\n",
-    "endLon = -43.0\n",
-    "n = 3600/15 #15 arc-second\n",
-    "# not work, need another dimension to project\n",
-    "#x = xr.DataArray(np.linspace(startLon,endLon,n), dims='z')\n",
-    "#y = xr.DataArray(np.linspace(startLat,endLat,n), dims='z')\n",
-    "#st = time.time()\n",
-    "#ds_s3 = ds.interp(lon=x, lat=y, method='linear')\n",
-    "#et = time.time()\n",
-    "#print('Exe time: ', et-st, 'sec')\n",
-    "#print(ds_s3)               \n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import orjson\n",
-    "import json\n",
-    "st = time.time()\n",
-    "jt1 = orjson.dumps(xt1.tolist(), option=orjson.OPT_NAIVE_UTC | orjson.OPT_SERIALIZE_NUMPY)\n",
-    "et = time.time()\n",
-    "print('4.1 Convert JSON by orjson time: ', et-st, 'sec')\n",
-    "st = time.time()\n",
-    "jt2 = json.dumps(xt1.tolist())\n",
-    "et = time.time()\n",
-    "print('4.2 Convert JSON by json.dump time: ', et-st, 'sec')\n",
-    "\n",
-    "print(jt1)\n",
-    "print(jt2)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ds.close()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import zarr\n",
-    "import dask"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "#compressor = zarr.Blosc(cname='zstd', clevel=3, shuffle=2)\n",
-    "dask.config.set(scheduler='single-threaded')\n",
-    "#da = getattr(ds, 'elevation')\n",
-    "#https://www.programcreek.com/python/example/123571/xarray.decode_cf\n",
-    "#da.attrs['_Unsigned']='false'\n",
-    "ds\n",
-    "ds.to_zarr('GEBCO_2022_sub_ice_topo.zarr', mode='w',\n",
-    "           #encoding={\"elevation\": {\"_Unsigned\": \"false\"}},\n",
-    "           group='gebco') ##compute=False, , encoding={'gebbco': {'compressor': compressor}})\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Exe time:  0.004856586456298828 sec\n"
-     ]
-    },
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-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
-       "Dimensions:    (lat: 43200, lon: 86400)\n",
-       "Coordinates:\n",
-       "  * lat        (lat) float64 -90.0 -89.99 -89.99 -89.99 ... 89.99 89.99 90.0\n",
-       "  * lon        (lon) float64 -180.0 -180.0 -180.0 -180.0 ... 180.0 180.0 180.0\n",
-       "Data variables:\n",
-       "    crs        |S1 ...\n",
-       "    elevation  (lat, lon) int16 dask.array&lt;chunksize=(675, 2700), meta=np.ndarray&gt;\n",
-       "Attributes: (12/36)\n",
-       "    Conventions:                     CF-1.6, ACDD-1.3\n",
-       "    comment:                         The data in the GEBCO_2022 Grid should n...\n",
-       "    creator_email:                   gdacc@seabed2030.org\n",
-       "    creator_name:                    GEBCO through the Nippon Foundation-GEBC...\n",
-       "    creator_type:                    International organisation\n",
-       "    creator_url:                     https://www.gebco.net\n",
-       "    ...                              ...\n",
-       "    node_offset:                     1.0\n",
-       "    project:                         Nippon Foundation - GEBCO Seabed2030 Pro...\n",
-       "    references:                      DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c8...\n",
-       "    source:                          The GEBCO_2022 Grid is the latest global...\n",
-       "    summary:                         The GEBCO_2022 Grid is a continuous, glo...\n",
-       "    title:                           The GEBCO_2022 Grid - a continuous terra...</pre><div class='xr-wrap' hidden><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-a0886ffe-5ae7-413e-9664-8b88a9707ad7' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a0886ffe-5ae7-413e-9664-8b88a9707ad7' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 43200</li><li><span class='xr-has-index'>lon</span>: 86400</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-e552f1d9-2302-4ebe-900e-4cb963f499c9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e552f1d9-2302-4ebe-900e-4cb963f499c9' 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 class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.99 -89.99 ... 89.99 90.0</div><input id='attrs-856ab7cf-5ec6-47d1-adb5-257eae422adb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-856ab7cf-5ec6-47d1-adb5-257eae422adb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-63f96ed6-d4fc-4537-9743-1b8dc802a8b5' class='xr-var-data-in' type='checkbox'><label for='data-63f96ed6-d4fc-4537-9743-1b8dc802a8b5' 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>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>sdn_parameter_name :</span></dt><dd>Latitude north</dd><dt><span>sdn_parameter_urn :</span></dt><dd>SDN:P01::ALATZZ01</dd><dt><span>sdn_uom_name :</span></dt><dd>Degrees north</dd><dt><span>sdn_uom_urn :</span></dt><dd>SDN:P06::DEGN</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>_FillValue :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([-89.997917, -89.99375 , -89.989583, ...,  89.989583,  89.99375 ,\n",
-       "        89.997917])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -180.0 ... 180.0 180.0</div><input id='attrs-f822fc24-1718-4dab-b8df-78209373d8fe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f822fc24-1718-4dab-b8df-78209373d8fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-02cfd54a-3bca-41cc-9818-df805876f839' class='xr-var-data-in' type='checkbox'><label for='data-02cfd54a-3bca-41cc-9818-df805876f839' 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>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>sdn_parameter_name :</span></dt><dd>Longitude east</dd><dt><span>sdn_parameter_urn :</span></dt><dd>SDN:P01::ALONZZ01</dd><dt><span>sdn_uom_name :</span></dt><dd>Degrees east</dd><dt><span>sdn_uom_urn :</span></dt><dd>SDN:P06::DEGE</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>_FillValue :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([-179.997917, -179.99375 , -179.989583, ...,  179.989583,  179.99375 ,\n",
-       "        179.997917])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-01b62e36-8e3b-48cf-82cf-79376fc30af4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-01b62e36-8e3b-48cf-82cf-79376fc30af4' class='xr-section-summary' >Data variables: <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>crs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>|S1</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3d7c89e6-9327-4e1a-af8b-e6d8a4a919d8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3d7c89e6-9327-4e1a-af8b-e6d8a4a919d8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-42e42e9e-c671-4407-af5f-43488d55bdc2' class='xr-var-data-in' type='checkbox'><label for='data-42e42e9e-c671-4407-af5f-43488d55bdc2' 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>epsg_code :</span></dt><dd>EPSG:4326</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd></dl></div><div class='xr-var-data'><pre>array(b&#x27;&#x27;, dtype=&#x27;|S1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>elevation</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(675, 2700), meta=np.ndarray&gt;</div><input id='attrs-e990436f-b5d6-4f3d-a750-4c4416069420' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e990436f-b5d6-4f3d-a750-4c4416069420' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d64d8bc1-c957-48bf-b607-c3acc8e1f2d8' class='xr-var-data-in' type='checkbox'><label for='data-d64d8bc1-c957-48bf-b607-c3acc8e1f2d8' 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>_Unsigned :</span></dt><dd>false</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>long_name :</span></dt><dd>Elevation relative to sea level</dd><dt><span>sdn_parameter_name :</span></dt><dd>Sea floor height (above mean sea level) {bathymetric height}</dd><dt><span>sdn_parameter_urn :</span></dt><dd>SDN:P01::ALATZZ01</dd><dt><span>sdn_uom_name :</span></dt><dd>Metres</dd><dt><span>sdn_uom_urn :</span></dt><dd>SDN:P06::ULAA</dd><dt><span>standard_name :</span></dt><dd>height_above_mean_sea_level</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
-       "    <tr>\n",
-       "        <td>\n",
-       "            <table style=\"border-collapse: collapse;\">\n",
-       "                <thead>\n",
-       "                    <tr>\n",
-       "                        <td> </td>\n",
-       "                        <th> Array </th>\n",
-       "                        <th> Chunk </th>\n",
-       "                    </tr>\n",
-       "                </thead>\n",
-       "                <tbody>\n",
-       "                    \n",
-       "                    <tr>\n",
-       "                        <th> Bytes </th>\n",
-       "                        <td> 6.95 GiB </td>\n",
-       "                        <td> 3.48 MiB </td>\n",
-       "                    </tr>\n",
-       "                    \n",
-       "                    <tr>\n",
-       "                        <th> Shape </th>\n",
-       "                        <td> (43200, 86400) </td>\n",
-       "                        <td> (675, 2700) </td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <th> Dask graph </th>\n",
-       "                        <td colspan=\"2\"> 2048 chunks in 2 graph layers </td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <th> Data type </th>\n",
-       "                        <td colspan=\"2\"> int16 numpy.ndarray </td>\n",
-       "                    </tr>\n",
-       "                </tbody>\n",
-       "            </table>\n",
-       "        </td>\n",
-       "        <td>\n",
-       "        <svg width=\"170\" height=\"110\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
-       "\n",
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-       "</svg>\n",
-       "        </td>\n",
-       "    </tr>\n",
-       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-80e1e4fd-65ed-4e10-82bf-43c29d11b109' class='xr-section-summary-in' type='checkbox'  ><label for='section-80e1e4fd-65ed-4e10-82bf-43c29d11b109' class='xr-section-summary' >Attributes: <span>(36)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6, ACDD-1.3</dd><dt><span>comment :</span></dt><dd>The data in the GEBCO_2022 Grid should not be used for navigation or any purpose relating to safety at sea.</dd><dt><span>creator_email :</span></dt><dd>gdacc@seabed2030.org</dd><dt><span>creator_name :</span></dt><dd>GEBCO through the Nippon Foundation-GEBCO Seabed 2030 Project</dd><dt><span>creator_type :</span></dt><dd>International organisation</dd><dt><span>creator_url :</span></dt><dd>https://www.gebco.net</dd><dt><span>date_created :</span></dt><dd>2022-06-22</dd><dt><span>geospatial_bounds :</span></dt><dd>[-180.0, -90.0, 180.0, 90.0]</dd><dt><span>geospatial_bounds_crs :</span></dt><dd>WGS84</dd><dt><span>geospatial_bounds_vertical_crs :</span></dt><dd>EPSG:5831</dd><dt><span>geospatial_lat_max :</span></dt><dd>90.0</dd><dt><span>geospatial_lat_min :</span></dt><dd>-90.0</dd><dt><span>geospatial_lat_resolution :</span></dt><dd>0.004166666666666667</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees_north</dd><dt><span>geospatial_lon_max :</span></dt><dd>180.0</dd><dt><span>geospatial_lon_min :</span></dt><dd>-180.0</dd><dt><span>geospatial_lon_resolution :</span></dt><dd>0.004166666666666667</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees_east</dd><dt><span>geospatial_vertical_max :</span></dt><dd>8685.0</dd><dt><span>geospatial_vertical_min :</span></dt><dd>-10977.0</dd><dt><span>geospatial_vertical_positive :</span></dt><dd>up</dd><dt><span>geospatial_vertical_resolution :</span></dt><dd>1.0</dd><dt><span>geospatial_vertical_units :</span></dt><dd>meters</dd><dt><span>history :</span></dt><dd>Information on the development of the data set and the source data sets included in the grid can be found in the data set documentation available from https://www.gebco.net</dd><dt><span>id :</span></dt><dd>DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c86abc0289c</dd><dt><span>identifier_product_doi :</span></dt><dd>DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c86abc0289c</dd><dt><span>institution :</span></dt><dd>On behalf of the General Bathymetric Chart of the Oceans (GEBCO), the data are held at the British Oceanographic Data Centre (BODC).</dd><dt><span>keywords :</span></dt><dd>BATHYMETRY/SEAFLOOR TOPOGRAPHY, DIGITAL ELEVATION/DIGITAL TERRAIN MODELS</dd><dt><span>license :</span></dt><dd>The GEBCO Grid is placed in the public domain and may be used free of charge. Use of the GEBCO Grid indicates that the user accepts the conditions of use and disclaimer information: https://www.gebco.net/data_and_products/gridded_bathymetry_data/gebco_2019/grid_terms_of_use.html</dd><dt><span>naming_authority :</span></dt><dd>https://dx.doi.org</dd><dt><span>node_offset :</span></dt><dd>1.0</dd><dt><span>project :</span></dt><dd>Nippon Foundation - GEBCO Seabed2030 Project</dd><dt><span>references :</span></dt><dd>DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c86abc0289c</dd><dt><span>source :</span></dt><dd>The GEBCO_2022 Grid is the latest global bathymetric product released by the General Bathymetric Chart of the Oceans (GEBCO) and has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and GEBCO. The Seabed 2030 Project aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor and make it available to all.</dd><dt><span>summary :</span></dt><dd>The GEBCO_2022 Grid is a continuous, global terrain model for ocean and land with a spatial resolution of 15 arc seconds.The grid uses as a base-map Version 2.4 of the SRTM15+ data set (Tozer et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. It is augmented with gridded bathymetric data sets developed as part of the Nippon Foundation-GEBCO Seabed 2030 Project.</dd><dt><span>title :</span></dt><dd>The GEBCO_2022 Grid - a continuous terrain model for oceans and land at 15 arc-second intervals</dd></dl></div></li></ul></div></div>"
-      ],
-      "text/plain": [
-       "<xarray.Dataset>\n",
-       "Dimensions:    (lat: 43200, lon: 86400)\n",
-       "Coordinates:\n",
-       "  * lat        (lat) float64 -90.0 -89.99 -89.99 -89.99 ... 89.99 89.99 90.0\n",
-       "  * lon        (lon) float64 -180.0 -180.0 -180.0 -180.0 ... 180.0 180.0 180.0\n",
-       "Data variables:\n",
-       "    crs        |S1 ...\n",
-       "    elevation  (lat, lon) int16 dask.array<chunksize=(675, 2700), meta=np.ndarray>\n",
-       "Attributes: (12/36)\n",
-       "    Conventions:                     CF-1.6, ACDD-1.3\n",
-       "    comment:                         The data in the GEBCO_2022 Grid should n...\n",
-       "    creator_email:                   gdacc@seabed2030.org\n",
-       "    creator_name:                    GEBCO through the Nippon Foundation-GEBC...\n",
-       "    creator_type:                    International organisation\n",
-       "    creator_url:                     https://www.gebco.net\n",
-       "    ...                              ...\n",
-       "    node_offset:                     1.0\n",
-       "    project:                         Nippon Foundation - GEBCO Seabed2030 Pro...\n",
-       "    references:                      DOI: 10.5285/e0f0bb80-ab44-2739-e053-6c8...\n",
-       "    source:                          The GEBCO_2022 Grid is the latest global...\n",
-       "    summary:                         The GEBCO_2022 Grid is a continuous, glo...\n",
-       "    title:                           The GEBCO_2022 Grid - a continuous terra..."
-      ]
-     },
-     "execution_count": 17,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "st = time.time()\n",
-    "dz = xr.open_zarr(\n",
-    "    'GEBCO_2022_sub_ice_topo.zarr', chunks='auto', \n",
-    "    group='gebco', decode_cf=False, decode_times=False)\n",
-    "\n",
-    "et = time.time()\n",
-    "print('Exe time: ', et-st, 'sec')\n",
-    "dz"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "print(sys.getsizeof(dz))\n",
-    "dz['elevation'].nbytes/(1024 ** 3)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "st = time.time()\n",
-    "dz_s1 = dz.sel(lon=slice(105, 135), lat=slice(2, 35)) \n",
-    "dz_s1.close() #try if it can close\n",
-    "zt1 = dz_s1.isel(lon=slice(1000, 1010), lat=slice(2000, 2010))\n",
-    "xz1 = zt1['elevation'].values\n",
-    "et = time.time()\n",
-    "print('Exe time: ', et-st, 'sec')\n",
-    "print(xz1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "st = time.time()\n",
-    "jz1 = orjson.dumps(xz1.tolist(), option=orjson.OPT_NAIVE_UTC | orjson.OPT_SERIALIZE_NUMPY)\n",
-    "et = time.time()\n",
-    "print('4.1z Convert JSON by orjson time: ', et-st, 'sec')\n",
-    "print(jz1)\n"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3.8.10 ('py39')",
-   "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": "3.8.10"
-  },
-  "orig_nbformat": 4,
-  "vscode": {
-   "interpreter": {
-    "hash": "e4b16f993b66de7f38f135ed21ea7c985362ee20cd8e4dede1c122c7165d5297"
-   }
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/requirements.txt b/requirements.txt
index 4f258a1..dc48194 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,10 +1,11 @@
-dask==2023.8.0
-fastapi==0.101.0
-geopy==2.3.0
+dask==2023.11.0
+fastapi==0.104.1
+geopy==2.4.1
 gunicorn==21.2.0
-numpy==1.25.2
-polars==0.18.13
+numpy==1.26.2
+polars==0.19.17
 Requests==2.31.0
-uvicorn==0.23.2
-xarray==2023.07.0
-zarr==2.16.0
+setuptools==68.2.2
+uvicorn==0.24.0.post1
+xarray==2023.11.0
+zarr==2.16.1
diff --git a/setup.py b/setup.py
new file mode 100644
index 0000000..b658385
--- /dev/null
+++ b/setup.py
@@ -0,0 +1,4 @@
+from setuptools import setup, find_packages
+
+setup(name='src', version='1.0', packages=find_packages())
+
diff --git a/src.egg-info/PKG-INFO b/src.egg-info/PKG-INFO
new file mode 100644
index 0000000..fb2b9c6
--- /dev/null
+++ b/src.egg-info/PKG-INFO
@@ -0,0 +1,3 @@
+Metadata-Version: 2.1
+Name: src
+Version: 1.0
diff --git a/src.egg-info/SOURCES.txt b/src.egg-info/SOURCES.txt
new file mode 100644
index 0000000..385458e
--- /dev/null
+++ b/src.egg-info/SOURCES.txt
@@ -0,0 +1,19 @@
+.gitignore
+README.md
+change_log.md
+gebco_app.py
+requirements.txt
+setup.py
+conf/ecosystem.config.js
+conf/gebco_v1.json
+conf/simu.sh
+simu/Hidy_zseg_123E98_23N33_123_21N33.csv
+simu/gebco_xy_123E98_23N33_123_21N33.csv
+simu/gebco_z_123E98_23N33_123_21N33.csv
+simu/gebco_zseg_123E98_23N33_123_21N33.csv
+src/__init__.py
+src/xmeridian.py
+src.egg-info/PKG-INFO
+src.egg-info/SOURCES.txt
+src.egg-info/dependency_links.txt
+src.egg-info/top_level.txt
\ No newline at end of file
diff --git a/src.egg-info/dependency_links.txt b/src.egg-info/dependency_links.txt
new file mode 100644
index 0000000..8b13789
--- /dev/null
+++ b/src.egg-info/dependency_links.txt
@@ -0,0 +1 @@
+
diff --git a/src.egg-info/top_level.txt b/src.egg-info/top_level.txt
new file mode 100644
index 0000000..85de9cf
--- /dev/null
+++ b/src.egg-info/top_level.txt
@@ -0,0 +1 @@
+src
diff --git a/src/__init__.py b/src/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/xmeridian.py b/src/xmeridian.py
similarity index 100%
rename from xmeridian.py
rename to src/xmeridian.py