From 9e5e4e5474f8654d0ead9e48faaaab6840c5a848 Mon Sep 17 00:00:00 2001
From: byersiiasa <byers@iiasa.ac.at>
Date: Thu, 15 Feb 2024 18:21:47 +0100
Subject: [PATCH] change requriements and setup for poetry

---
 poetry.lock                    | 2105 ++++++++++++++++
 pyproject.toml                 |   35 +
 rime/pp_combined_example.ipynb | 4190 ++++----------------------------
 setup.cfg                      |   48 -
 setup.py                       |    3 -
 5 files changed, 2655 insertions(+), 3726 deletions(-)
 create mode 100644 poetry.lock
 create mode 100644 pyproject.toml
 delete mode 100644 setup.cfg
 delete mode 100644 setup.py

diff --git a/poetry.lock b/poetry.lock
new file mode 100644
index 0000000..f7c549c
--- /dev/null
+++ b/poetry.lock
@@ -0,0 +1,2105 @@
+# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
+
+[[package]]
+name = "about-time"
+version = "4.2.1"
+description = "Easily measure timing and throughput of code blocks, with beautiful human friendly representations."
+optional = false
+python-versions = ">=3.7, <4"
+files = [
+    {file = "about-time-4.2.1.tar.gz", hash = "sha256:6a538862d33ce67d997429d14998310e1dbfda6cb7d9bbfbf799c4709847fece"},
+    {file = "about_time-4.2.1-py3-none-any.whl", hash = "sha256:8bbf4c75fe13cbd3d72f49a03b02c5c7dca32169b6d49117c257e7eb3eaee341"},
+]
+
+[[package]]
+name = "alive-progress"
+version = "3.1.5"
+description = "A new kind of Progress Bar, with real-time throughput, ETA, and very cool animations!"
+optional = false
+python-versions = ">=3.7, <4"
+files = [
+    {file = "alive-progress-3.1.5.tar.gz", hash = "sha256:42e399a66c8150dc507602dff7b7953f105ef11faf97ddaa6d27b1cbf45c4c98"},
+    {file = "alive_progress-3.1.5-py3-none-any.whl", hash = "sha256:347220c1858e3abe137fa0746895668c04df09c5261a13dc03f05795e8a29be5"},
+]
+
+[package.dependencies]
+about-time = "4.2.1"
+grapheme = "0.6.0"
+
+[[package]]
+name = "anyio"
+version = "4.2.0"
+description = "High level compatibility layer for multiple asynchronous event loop implementations"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "anyio-4.2.0-py3-none-any.whl", hash = "sha256:745843b39e829e108e518c489b31dc757de7d2131d53fac32bd8df268227bfee"},
+    {file = "anyio-4.2.0.tar.gz", hash = "sha256:e1875bb4b4e2de1669f4bc7869b6d3f54231cdced71605e6e64c9be77e3be50f"},
+]
+
+[package.dependencies]
+exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""}
+idna = ">=2.8"
+sniffio = ">=1.1"
+typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""}
+
+[package.extras]
+doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
+test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
+trio = ["trio (>=0.23)"]
+
+[[package]]
+name = "bleach"
+version = "6.1.0"
+description = "An easy safelist-based HTML-sanitizing tool."
+optional = false
+python-versions = ">=3.8"
+files = [
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+]
+
+[package.dependencies]
+six = ">=1.9.0"
+webencodings = "*"
+
+[package.extras]
+css = ["tinycss2 (>=1.1.0,<1.3)"]
+
+[[package]]
+name = "bokeh"
+version = "3.3.4"
+description = "Interactive plots and applications in the browser from Python"
+optional = false
+python-versions = ">=3.9"
+files = [
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+
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+Jinja2 = ">=2.9"
+numpy = ">=1.16"
+packaging = ">=16.8"
+pandas = ">=1.2"
+pillow = ">=7.1.0"
+PyYAML = ">=3.10"
+tornado = ">=5.1"
+xyzservices = ">=2021.09.1"
+
+[[package]]
+name = "certifi"
+version = "2024.2.2"
+description = "Python package for providing Mozilla's CA Bundle."
+optional = false
+python-versions = ">=3.6"
+files = [
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+
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+optional = false
+python-versions = ">=3.7.0"
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+testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy (>=0.9.1)", "pytest-ruff"]
+
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diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000..6309cee
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,35 @@
+[tool.poetry]
+name = "rime"
+authors = ["Edward Byers <byers@iiasa.ac.at>",
+			"Mia Werning <werning@iiasa.ac.at>"]
+
+author_email = "byers@iiasa.ac.at"
+description = "Rapid Impact Model Emulator"
+repository = "https://github.com/iiasa/rime"
+homepage = "https://iiasa.ac.at/programs/ece"
+documentation = "https://github.com/iiasa/rime"
+version = "0.1.0"
+license = "GNU CPL v3"
+readme = "README.md"
+
+[tool.poetry.dependencies]
+python = ">=3.10, <3.11"
+alive-progress = "^3.1.5"
+dask = "^2024.2.0"
+numpy = "^1.23"
+pandas = "^2.2.0"
+pyam-iamc = "^1.7"
+xarray = "^2024.1.1"
+scipy = "^1.12.0"
+holoviews = "^1.18.3"
+matplotlib = "^3.8.3"
+seaborn = "^0.13.2"
+rich = "^13.7.0"
+pyyaml = "^6.0.1"
+hvplot = "^0.9.2"
+distributed = "^2024.2.0"
+
+
+[build-system]
+requires = ["poetry-core"]
+build-backend = "poetry.core.masonry.api"
diff --git a/rime/pp_combined_example.ipynb b/rime/pp_combined_example.ipynb
index f122d9c..82bd19a 100644
--- a/rime/pp_combined_example.ipynb
+++ b/rime/pp_combined_example.ipynb
@@ -23,13 +23,11 @@
        "  }\n",
        "\n",
        "  var force = true;\n",
+       "  var py_version = '3.3.4'.replace('rc', '-rc.').replace('.dev', '-dev.');\n",
+       "  var reloading = false;\n",
+       "  var Bokeh = root.Bokeh;\n",
        "\n",
-       "  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n",
-       "    root._bokeh_onload_callbacks = [];\n",
-       "    root._bokeh_is_loading = undefined;\n",
-       "  }\n",
-       "\n",
-       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
+       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force) {\n",
        "    root._bokeh_timeout = Date.now() + 5000;\n",
        "    root._bokeh_failed_load = false;\n",
        "  }\n",
@@ -41,26 +39,30 @@
        "          callback();\n",
        "      });\n",
        "    } finally {\n",
-       "      delete root._bokeh_onload_callbacks\n",
+       "      delete root._bokeh_onload_callbacks;\n",
        "    }\n",
        "    console.debug(\"Bokeh: all callbacks have finished\");\n",
        "  }\n",
        "\n",
-       "  function load_libs(css_urls, js_urls, js_modules, callback) {\n",
+       "  function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n",
        "    if (css_urls == null) css_urls = [];\n",
        "    if (js_urls == null) js_urls = [];\n",
        "    if (js_modules == null) js_modules = [];\n",
+       "    if (js_exports == null) js_exports = {};\n",
        "\n",
        "    root._bokeh_onload_callbacks.push(callback);\n",
+       "\n",
        "    if (root._bokeh_is_loading > 0) {\n",
        "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
        "      return null;\n",
        "    }\n",
-       "    if (js_urls.length === 0 && js_modules.length === 0) {\n",
+       "    if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n",
        "      run_callbacks();\n",
        "      return null;\n",
        "    }\n",
-       "    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
+       "    if (!reloading) {\n",
+       "      console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
+       "    }\n",
        "\n",
        "    function on_load() {\n",
        "      root._bokeh_is_loading--;\n",
@@ -69,26 +71,37 @@
        "        run_callbacks()\n",
        "      }\n",
        "    }\n",
+       "    window._bokeh_on_load = on_load\n",
        "\n",
        "    function on_error() {\n",
        "      console.error(\"failed to load \" + url);\n",
        "    }\n",
        "\n",
-       "    for (var i = 0; i < css_urls.length; i++) {\n",
-       "      var url = css_urls[i];\n",
-       "      const element = document.createElement(\"link\");\n",
-       "      element.onload = on_load;\n",
-       "      element.onerror = on_error;\n",
-       "      element.rel = \"stylesheet\";\n",
-       "      element.type = \"text/css\";\n",
-       "      element.href = url;\n",
-       "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
-       "      document.body.appendChild(element);\n",
-       "    }\n",
-       "\n",
        "    var skip = [];\n",
        "    if (window.requirejs) {\n",
-       "      window.requirejs.config({'packages': {}, 'paths': {'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@4.2.5/dist/gridstack-h5', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'gridstack': {'exports': 'GridStack'}}});\n",
+       "      window.requirejs.config({'packages': {}, 'paths': {'jspanel': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/jspanel', 'jspanel-modal': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal', 'jspanel-tooltip': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip', 'jspanel-hint': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint', 'jspanel-layout': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout', 'jspanel-contextmenu': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu', 'jspanel-dock': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock', 'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@7.2.3/dist/gridstack-all', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'jspanel': {'exports': 'jsPanel'}, 'gridstack': {'exports': 'GridStack'}}});\n",
+       "      require([\"jspanel\"], function(jsPanel) {\n",
+       "\twindow.jsPanel = jsPanel\n",
+       "\ton_load()\n",
+       "      })\n",
+       "      require([\"jspanel-modal\"], function() {\n",
+       "\ton_load()\n",
+       "      })\n",
+       "      require([\"jspanel-tooltip\"], function() {\n",
+       "\ton_load()\n",
+       "      })\n",
+       "      require([\"jspanel-hint\"], function() {\n",
+       "\ton_load()\n",
+       "      })\n",
+       "      require([\"jspanel-layout\"], function() {\n",
+       "\ton_load()\n",
+       "      })\n",
+       "      require([\"jspanel-contextmenu\"], function() {\n",
+       "\ton_load()\n",
+       "      })\n",
+       "      require([\"jspanel-dock\"], function() {\n",
+       "\ton_load()\n",
+       "      })\n",
        "      require([\"gridstack\"], function(GridStack) {\n",
        "\twindow.GridStack = GridStack\n",
        "\ton_load()\n",
@@ -96,22 +109,59 @@
        "      require([\"notyf\"], function() {\n",
        "\ton_load()\n",
        "      })\n",
-       "      root._bokeh_is_loading = css_urls.length + 2;\n",
+       "      root._bokeh_is_loading = css_urls.length + 9;\n",
        "    } else {\n",
-       "      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length;\n",
+       "      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n",
+       "    }\n",
+       "\n",
+       "    var existing_stylesheets = []\n",
+       "    var links = document.getElementsByTagName('link')\n",
+       "    for (var i = 0; i < links.length; i++) {\n",
+       "      var link = links[i]\n",
+       "      if (link.href != null) {\n",
+       "\texisting_stylesheets.push(link.href)\n",
+       "      }\n",
+       "    }\n",
+       "    for (var i = 0; i < css_urls.length; i++) {\n",
+       "      var url = css_urls[i];\n",
+       "      if (existing_stylesheets.indexOf(url) !== -1) {\n",
+       "\ton_load()\n",
+       "\tcontinue;\n",
+       "      }\n",
+       "      const element = document.createElement(\"link\");\n",
+       "      element.onload = on_load;\n",
+       "      element.onerror = on_error;\n",
+       "      element.rel = \"stylesheet\";\n",
+       "      element.type = \"text/css\";\n",
+       "      element.href = url;\n",
+       "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
+       "      document.body.appendChild(element);\n",
+       "    }    if (((window['jsPanel'] !== undefined) && (!(window['jsPanel'] instanceof HTMLElement))) || window.requirejs) {\n",
+       "      var urls = ['https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/jspanel.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock.js'];\n",
+       "      for (var i = 0; i < urls.length; i++) {\n",
+       "        skip.push(urls[i])\n",
+       "      }\n",
        "    }    if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n",
-       "      var urls = ['https://cdn.holoviz.org/panel/0.14.4/dist/bundled/gridstack/gridstack@4.2.5/dist/gridstack-h5.js'];\n",
+       "      var urls = ['https://cdn.holoviz.org/panel/1.3.8/dist/bundled/gridstack/gridstack@7.2.3/dist/gridstack-all.js'];\n",
        "      for (var i = 0; i < urls.length; i++) {\n",
        "        skip.push(urls[i])\n",
        "      }\n",
        "    }    if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n",
-       "      var urls = ['https://cdn.holoviz.org/panel/0.14.4/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n",
+       "      var urls = ['https://cdn.holoviz.org/panel/1.3.8/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n",
        "      for (var i = 0; i < urls.length; i++) {\n",
        "        skip.push(urls[i])\n",
        "      }\n",
-       "    }    for (var i = 0; i < js_urls.length; i++) {\n",
+       "    }    var existing_scripts = []\n",
+       "    var scripts = document.getElementsByTagName('script')\n",
+       "    for (var i = 0; i < scripts.length; i++) {\n",
+       "      var script = scripts[i]\n",
+       "      if (script.src != null) {\n",
+       "\texisting_scripts.push(script.src)\n",
+       "      }\n",
+       "    }\n",
+       "    for (var i = 0; i < js_urls.length; i++) {\n",
        "      var url = js_urls[i];\n",
-       "      if (skip.indexOf(url) >= 0) {\n",
+       "      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n",
        "\tif (!window.requirejs) {\n",
        "\t  on_load();\n",
        "\t}\n",
@@ -127,7 +177,7 @@
        "    }\n",
        "    for (var i = 0; i < js_modules.length; i++) {\n",
        "      var url = js_modules[i];\n",
-       "      if (skip.indexOf(url) >= 0) {\n",
+       "      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n",
        "\tif (!window.requirejs) {\n",
        "\t  on_load();\n",
        "\t}\n",
@@ -142,6 +192,26 @@
        "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
        "      document.head.appendChild(element);\n",
        "    }\n",
+       "    for (const name in js_exports) {\n",
+       "      var url = js_exports[name];\n",
+       "      if (skip.indexOf(url) >= 0 || root[name] != null) {\n",
+       "\tif (!window.requirejs) {\n",
+       "\t  on_load();\n",
+       "\t}\n",
+       "\tcontinue;\n",
+       "      }\n",
+       "      var element = document.createElement('script');\n",
+       "      element.onerror = on_error;\n",
+       "      element.async = false;\n",
+       "      element.type = \"module\";\n",
+       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
+       "      element.textContent = `\n",
+       "      import ${name} from \"${url}\"\n",
+       "      window.${name} = ${name}\n",
+       "      window._bokeh_on_load()\n",
+       "      `\n",
+       "      document.head.appendChild(element);\n",
+       "    }\n",
        "    if (!js_urls.length && !js_modules.length) {\n",
        "      on_load()\n",
        "    }\n",
@@ -153,12 +223,11 @@
        "    document.body.appendChild(element);\n",
        "  }\n",
        "\n",
-       "  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-2.4.3.min.js\", \"https://unpkg.com/@holoviz/panel@0.14.4/dist/panel.min.js\"];\n",
+       "  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.3.4.min.js\", \"https://cdn.holoviz.org/panel/1.3.8/dist/panel.min.js\"];\n",
        "  var js_modules = [];\n",
-       "  var css_urls = [\"https://cdn.holoviz.org/panel/0.14.4/dist/css/alerts.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/card.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/dataframe.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/debugger.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/json.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/loading.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/markdown.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/widgets.css\"];\n",
+       "  var js_exports = {};\n",
+       "  var css_urls = [];\n",
        "  var inline_js = [    function(Bokeh) {\n",
-       "      inject_raw_css(\"\\n    .bk.pn-loading.arc:before {\\n      background-image: url(\\\"data:image/svg+xml;base64,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\\\");\\n      background-size: auto calc(min(50%, 400px));\\n    }\\n    \");\n",
-       "    },    function(Bokeh) {\n",
        "      Bokeh.set_log_level(\"info\");\n",
        "    },\n",
        "function(Bokeh) {} // ensure no trailing comma for IE\n",
@@ -167,27 +236,67 @@
        "  function run_inline_js() {\n",
        "    if ((root.Bokeh !== undefined) || (force === true)) {\n",
        "      for (var i = 0; i < inline_js.length; i++) {\n",
-       "        inline_js[i].call(root, root.Bokeh);\n",
+       "\ttry {\n",
+       "          inline_js[i].call(root, root.Bokeh);\n",
+       "\t} catch(e) {\n",
+       "\t  if (!reloading) {\n",
+       "\t    throw e;\n",
+       "\t  }\n",
+       "\t}\n",
+       "      }\n",
+       "      // Cache old bokeh versions\n",
+       "      if (Bokeh != undefined && !reloading) {\n",
+       "\tvar NewBokeh = root.Bokeh;\n",
+       "\tif (Bokeh.versions === undefined) {\n",
+       "\t  Bokeh.versions = new Map();\n",
+       "\t}\n",
+       "\tif (NewBokeh.version !== Bokeh.version) {\n",
+       "\t  Bokeh.versions.set(NewBokeh.version, NewBokeh)\n",
+       "\t}\n",
+       "\troot.Bokeh = Bokeh;\n",
        "      }} else if (Date.now() < root._bokeh_timeout) {\n",
        "      setTimeout(run_inline_js, 100);\n",
        "    } else if (!root._bokeh_failed_load) {\n",
        "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
        "      root._bokeh_failed_load = true;\n",
        "    }\n",
+       "    root._bokeh_is_initializing = false\n",
        "  }\n",
        "\n",
-       "  if (root._bokeh_is_loading === 0) {\n",
-       "    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
-       "    run_inline_js();\n",
-       "  } else {\n",
-       "    load_libs(css_urls, js_urls, js_modules, function() {\n",
-       "      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
-       "      run_inline_js();\n",
-       "    });\n",
+       "  function load_or_wait() {\n",
+       "    // Implement a backoff loop that tries to ensure we do not load multiple\n",
+       "    // versions of Bokeh and its dependencies at the same time.\n",
+       "    // In recent versions we use the root._bokeh_is_initializing flag\n",
+       "    // to determine whether there is an ongoing attempt to initialize\n",
+       "    // bokeh, however for backward compatibility we also try to ensure\n",
+       "    // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n",
+       "    // before older versions are fully initialized.\n",
+       "    if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n",
+       "      root._bokeh_is_initializing = false;\n",
+       "      root._bokeh_onload_callbacks = undefined;\n",
+       "      console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n",
+       "      load_or_wait();\n",
+       "    } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n",
+       "      setTimeout(load_or_wait, 100);\n",
+       "    } else {\n",
+       "      root._bokeh_is_initializing = true\n",
+       "      root._bokeh_onload_callbacks = []\n",
+       "      var bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n",
+       "      if (!reloading && !bokeh_loaded) {\n",
+       "\troot.Bokeh = undefined;\n",
+       "      }\n",
+       "      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n",
+       "\tconsole.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
+       "\trun_inline_js();\n",
+       "      });\n",
+       "    }\n",
        "  }\n",
+       "  // Give older versions of the autoload script a head-start to ensure\n",
+       "  // they initialize before we start loading newer version.\n",
+       "  setTimeout(load_or_wait, 100)\n",
        "}(window));"
       ],
-      "application/vnd.holoviews_load.v0+json": "(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, js_modules, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n    if (js_modules == null) js_modules = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls.length === 0 && js_modules.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (var i = 0; i < css_urls.length; i++) {\n      var url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }\n\n    var skip = [];\n    if (window.requirejs) {\n      window.requirejs.config({'packages': {}, 'paths': {'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@4.2.5/dist/gridstack-h5', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'gridstack': {'exports': 'GridStack'}}});\n      require([\"gridstack\"], function(GridStack) {\n\twindow.GridStack = GridStack\n\ton_load()\n      })\n      require([\"notyf\"], function() {\n\ton_load()\n      })\n      root._bokeh_is_loading = css_urls.length + 2;\n    } else {\n      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length;\n    }    if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/0.14.4/dist/bundled/gridstack/gridstack@4.2.5/dist/gridstack-h5.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/0.14.4/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      if (skip.indexOf(url) >= 0) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (var i = 0; i < js_modules.length; i++) {\n      var url = js_modules[i];\n      if (skip.indexOf(url) >= 0) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    if (!js_urls.length && !js_modules.length) {\n      on_load()\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-2.4.3.min.js\", \"https://unpkg.com/@holoviz/panel@0.14.4/dist/panel.min.js\"];\n  var js_modules = [];\n  var css_urls = [\"https://cdn.holoviz.org/panel/0.14.4/dist/css/alerts.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/card.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/dataframe.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/debugger.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/json.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/loading.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/markdown.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/widgets.css\"];\n  var inline_js = [    function(Bokeh) {\n      inject_raw_css(\"\\n    .bk.pn-loading.arc:before {\\n      background-image: url(\\\"data:image/svg+xml;base64,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\\\");\\n      background-size: auto calc(min(50%, 400px));\\n    }\\n    \");\n    },    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n  ];\n\n  function run_inline_js() {\n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (var i = 0; i < inline_js.length; i++) {\n        inline_js[i].call(root, root.Bokeh);\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    }\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, js_modules, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
+      "application/vnd.holoviews_load.v0+json": "(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n  var py_version = '3.3.4'.replace('rc', '-rc.').replace('.dev', '-dev.');\n  var reloading = false;\n  var Bokeh = root.Bokeh;\n\n  if (typeof (root._bokeh_timeout) === \"undefined\" || force) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks;\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n    if (js_modules == null) js_modules = [];\n    if (js_exports == null) js_exports = {};\n\n    root._bokeh_onload_callbacks.push(callback);\n\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n      run_callbacks();\n      return null;\n    }\n    if (!reloading) {\n      console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    }\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n    window._bokeh_on_load = on_load\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    var skip = [];\n    if (window.requirejs) {\n      window.requirejs.config({'packages': {}, 'paths': {'jspanel': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/jspanel', 'jspanel-modal': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal', 'jspanel-tooltip': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip', 'jspanel-hint': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint', 'jspanel-layout': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout', 'jspanel-contextmenu': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu', 'jspanel-dock': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock', 'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@7.2.3/dist/gridstack-all', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'jspanel': {'exports': 'jsPanel'}, 'gridstack': {'exports': 'GridStack'}}});\n      require([\"jspanel\"], function(jsPanel) {\n\twindow.jsPanel = jsPanel\n\ton_load()\n      })\n      require([\"jspanel-modal\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-tooltip\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-hint\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-layout\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-contextmenu\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-dock\"], function() {\n\ton_load()\n      })\n      require([\"gridstack\"], function(GridStack) {\n\twindow.GridStack = GridStack\n\ton_load()\n      })\n      require([\"notyf\"], function() {\n\ton_load()\n      })\n      root._bokeh_is_loading = css_urls.length + 9;\n    } else {\n      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n    }\n\n    var existing_stylesheets = []\n    var links = document.getElementsByTagName('link')\n    for (var i = 0; i < links.length; i++) {\n      var link = links[i]\n      if (link.href != null) {\n\texisting_stylesheets.push(link.href)\n      }\n    }\n    for (var i = 0; i < css_urls.length; i++) {\n      var url = css_urls[i];\n      if (existing_stylesheets.indexOf(url) !== -1) {\n\ton_load()\n\tcontinue;\n      }\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }    if (((window['jsPanel'] !== undefined) && (!(window['jsPanel'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/jspanel.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/1.3.8/dist/bundled/gridstack/gridstack@7.2.3/dist/gridstack-all.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/1.3.8/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    var existing_scripts = []\n    var scripts = document.getElementsByTagName('script')\n    for (var i = 0; i < scripts.length; i++) {\n      var script = scripts[i]\n      if (script.src != null) {\n\texisting_scripts.push(script.src)\n      }\n    }\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (var i = 0; i < js_modules.length; i++) {\n      var url = js_modules[i];\n      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (const name in js_exports) {\n      var url = js_exports[name];\n      if (skip.indexOf(url) >= 0 || root[name] != null) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onerror = on_error;\n      element.async = false;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      element.textContent = `\n      import ${name} from \"${url}\"\n      window.${name} = ${name}\n      window._bokeh_on_load()\n      `\n      document.head.appendChild(element);\n    }\n    if (!js_urls.length && !js_modules.length) {\n      on_load()\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.3.4.min.js\", \"https://cdn.holoviz.org/panel/1.3.8/dist/panel.min.js\"];\n  var js_modules = [];\n  var js_exports = {};\n  var css_urls = [];\n  var inline_js = [    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n  ];\n\n  function run_inline_js() {\n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (var i = 0; i < inline_js.length; i++) {\n\ttry {\n          inline_js[i].call(root, root.Bokeh);\n\t} catch(e) {\n\t  if (!reloading) {\n\t    throw e;\n\t  }\n\t}\n      }\n      // Cache old bokeh versions\n      if (Bokeh != undefined && !reloading) {\n\tvar NewBokeh = root.Bokeh;\n\tif (Bokeh.versions === undefined) {\n\t  Bokeh.versions = new Map();\n\t}\n\tif (NewBokeh.version !== Bokeh.version) {\n\t  Bokeh.versions.set(NewBokeh.version, NewBokeh)\n\t}\n\troot.Bokeh = Bokeh;\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    }\n    root._bokeh_is_initializing = false\n  }\n\n  function load_or_wait() {\n    // Implement a backoff loop that tries to ensure we do not load multiple\n    // versions of Bokeh and its dependencies at the same time.\n    // In recent versions we use the root._bokeh_is_initializing flag\n    // to determine whether there is an ongoing attempt to initialize\n    // bokeh, however for backward compatibility we also try to ensure\n    // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n    // before older versions are fully initialized.\n    if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n      root._bokeh_is_initializing = false;\n      root._bokeh_onload_callbacks = undefined;\n      console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n      load_or_wait();\n    } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n      setTimeout(load_or_wait, 100);\n    } else {\n      root._bokeh_is_initializing = true\n      root._bokeh_onload_callbacks = []\n      var bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n      if (!reloading && !bokeh_loaded) {\n\troot.Bokeh = undefined;\n      }\n      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n\tconsole.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n\trun_inline_js();\n      });\n    }\n  }\n  // Give older versions of the autoload script a head-start to ensure\n  // they initialize before we start loading newer version.\n  setTimeout(load_or_wait, 100)\n}(window));"
      },
      "metadata": {},
      "output_type": "display_data"
@@ -443,10 +552,20 @@
     {
      "data": {
       "text/html": [
-       "<style>.bk-root, .bk-root .bk:before, .bk-root .bk:after {\n",
-       "  font-family: var(--jp-ui-font-size1);\n",
+       "<style>*[data-root-id],\n",
+       "*[data-root-id] > * {\n",
+       "  box-sizing: border-box;\n",
+       "  font-family: var(--jp-ui-font-family);\n",
        "  font-size: var(--jp-ui-font-size1);\n",
-       "  color: var(--jp-ui-font-color1);\n",
+       "  color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n",
+       "}\n",
+       "\n",
+       "/* Override VSCode background color */\n",
+       ".cell-output-ipywidget-background:has(\n",
+       "    > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]\n",
+       "  ),\n",
+       ".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n",
+       "  background-color: transparent !important;\n",
        "}\n",
        "</style>"
       ]
@@ -455,12 +574,82 @@
      "output_type": "display_data"
     },
     {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "C:\\Users\\byers\\Anaconda3\\envs\\py310\\lib\\site-packages\\pyproj\\__init__.py:89: UserWarning: pyproj unable to set database path.\n",
-      "  _pyproj_global_context_initialize()\n"
-     ]
+     "data": {
+      "application/vnd.holoviews_exec.v0+json": "",
+      "text/html": [
+       "<div id='p1002'>\n",
+       "  <div id=\"fc1220ad-b159-42d8-9a9c-645cce21afe4\" data-root-id=\"p1002\" style=\"display: contents;\"></div>\n",
+       "</div>\n",
+       "<script type=\"application/javascript\">(function(root) {\n",
+       "  var docs_json = {\"3b746880-659e-4ac9-9e3b-01cad746924b\":{\"version\":\"3.3.4\",\"title\":\"Bokeh Application\",\"roots\":[{\"type\":\"object\",\"name\":\"panel.models.browser.BrowserInfo\",\"id\":\"p1002\"},{\"type\":\"object\",\"name\":\"panel.models.comm_manager.CommManager\",\"id\":\"p1003\",\"attributes\":{\"plot_id\":\"p1002\",\"comm_id\":\"c789c3beffce4302b41642bf1d6aa964\",\"client_comm_id\":\"4d94852314b04e4aa47db103bacfe147\"}}],\"defs\":[{\"type\":\"model\",\"name\":\"ReactiveHTML1\"},{\"type\":\"model\",\"name\":\"FlexBox1\",\"properties\":[{\"name\":\"align_content\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"align_items\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"flex_direction\",\"kind\":\"Any\",\"default\":\"row\"},{\"name\":\"flex_wrap\",\"kind\":\"Any\",\"default\":\"wrap\"},{\"name\":\"justify_content\",\"kind\":\"Any\",\"default\":\"flex-start\"}]},{\"type\":\"model\",\"name\":\"FloatPanel1\",\"properties\":[{\"name\":\"config\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"contained\",\"kind\":\"Any\",\"default\":true},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"right-top\"},{\"name\":\"offsetx\",\"kind\":\"Any\",\"default\":null},{\"name\":\"offsety\",\"kind\":\"Any\",\"default\":null},{\"name\":\"theme\",\"kind\":\"Any\",\"default\":\"primary\"},{\"name\":\"status\",\"kind\":\"Any\",\"default\":\"normalized\"}]},{\"type\":\"model\",\"name\":\"GridStack1\",\"properties\":[{\"name\":\"mode\",\"kind\":\"Any\",\"default\":\"warn\"},{\"name\":\"ncols\",\"kind\":\"Any\",\"default\":null},{\"name\":\"nrows\",\"kind\":\"Any\",\"default\":null},{\"name\":\"allow_resize\",\"kind\":\"Any\",\"default\":true},{\"name\":\"allow_drag\",\"kind\":\"Any\",\"default\":true},{\"name\":\"state\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"drag1\",\"properties\":[{\"name\":\"slider_width\",\"kind\":\"Any\",\"default\":5},{\"name\":\"slider_color\",\"kind\":\"Any\",\"default\":\"black\"},{\"name\":\"value\",\"kind\":\"Any\",\"default\":50}]},{\"type\":\"model\",\"name\":\"click1\",\"properties\":[{\"name\":\"terminal_output\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"debug_name\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"clears\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"copy_to_clipboard1\",\"properties\":[{\"name\":\"fill\",\"kind\":\"Any\",\"default\":\"none\"},{\"name\":\"value\",\"kind\":\"Any\",\"default\":null}]},{\"type\":\"model\",\"name\":\"FastWrapper1\",\"properties\":[{\"name\":\"object\",\"kind\":\"Any\",\"default\":null},{\"name\":\"style\",\"kind\":\"Any\",\"default\":null}]},{\"type\":\"model\",\"name\":\"NotificationAreaBase1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"NotificationArea1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"notifications\",\"kind\":\"Any\",\"default\":[]},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0},{\"name\":\"types\",\"kind\":\"Any\",\"default\":[{\"type\":\"map\",\"entries\":[[\"type\",\"warning\"],[\"background\",\"#ffc107\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-exclamation-triangle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]},{\"type\":\"map\",\"entries\":[[\"type\",\"info\"],[\"background\",\"#007bff\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-info-circle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]}]}]},{\"type\":\"model\",\"name\":\"Notification\",\"properties\":[{\"name\":\"background\",\"kind\":\"Any\",\"default\":null},{\"name\":\"duration\",\"kind\":\"Any\",\"default\":3000},{\"name\":\"icon\",\"kind\":\"Any\",\"default\":null},{\"name\":\"message\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"notification_type\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_destroyed\",\"kind\":\"Any\",\"default\":false}]},{\"type\":\"model\",\"name\":\"TemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"BootstrapTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"MaterialTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]}]}};\n",
+       "  var render_items = [{\"docid\":\"3b746880-659e-4ac9-9e3b-01cad746924b\",\"roots\":{\"p1002\":\"fc1220ad-b159-42d8-9a9c-645cce21afe4\"},\"root_ids\":[\"p1002\"]}];\n",
+       "  var docs = Object.values(docs_json)\n",
+       "  if (!docs) {\n",
+       "    return\n",
+       "  }\n",
+       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
+       "  function embed_document(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
+       "    for (const render_item of render_items) {\n",
+       "      for (const root_id of render_item.root_ids) {\n",
+       "\tconst id_el = document.getElementById(root_id)\n",
+       "\tif (id_el.children.length && (id_el.children[0].className === 'bk-root')) {\n",
+       "\t  const root_el = id_el.children[0]\n",
+       "\t  root_el.id = root_el.id + '-rendered'\n",
+       "\t}\n",
+       "      }\n",
+       "    }\n",
+       "  }\n",
+       "  function get_bokeh(root) {\n",
+       "    if (root.Bokeh === undefined) {\n",
+       "      return null\n",
+       "    } else if (root.Bokeh.version !== py_version) {\n",
+       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
+       "\treturn null\n",
+       "      }\n",
+       "      return root.Bokeh.versions.get(py_version);\n",
+       "    } else if (root.Bokeh.version === py_version) {\n",
+       "      return root.Bokeh\n",
+       "    }\n",
+       "    return null\n",
+       "  }\n",
+       "  function is_loaded(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
+       "  }\n",
+       "  if (is_loaded(root)) {\n",
+       "    embed_document(root);\n",
+       "  } else {\n",
+       "    var attempts = 0;\n",
+       "    var timer = setInterval(function(root) {\n",
+       "      if (is_loaded(root)) {\n",
+       "        clearInterval(timer);\n",
+       "        embed_document(root);\n",
+       "      } else if (document.readyState == \"complete\") {\n",
+       "        attempts++;\n",
+       "        if (attempts > 200) {\n",
+       "          clearInterval(timer);\n",
+       "\t  var Bokeh = get_bokeh(root)\n",
+       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
+       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
+       "\t  } else {\n",
+       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
+       "\t    embed_document(root)\n",
+       "\t  }\n",
+       "        }\n",
+       "      }\n",
+       "    }, 25, root)\n",
+       "  }\n",
+       "})(window);</script>"
+      ]
+     },
+     "metadata": {
+      "application/vnd.holoviews_exec.v0+json": {
+       "id": "p1002"
+      }
+     },
+     "output_type": "display_data"
     },
     {
      "data": {
@@ -482,8 +671,9 @@
     "\n",
     "import dask\n",
     "import dask.dataframe as dd\n",
-    "from dask.diagnostics import ProgressBar\n",
-    "from dask.diagnostics import Profiler, ResourceProfiler, CacheProfiler\n",
+    "# from dask.diagnostics import ProgressBar\n",
+    "from dask.diagnostics import Profiler, ResourceProfiler, CacheProfiler, ProgressBar\n",
+    "from dask.distributed import Client\n",
     "\n",
     "# from dask.distributed import Client # uncomment this to open Dask client to see performance\n",
     "import glob\n",
@@ -503,6 +693,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "\n",
     "# Load a yaml file that will help select multiple climate indicator files (not necessarily needed)\n",
     "with open(\"indicator_params.yml\", \"r\") as f:\n",
     "    params = yaml.full_load(f)"
@@ -513,18 +704,7 @@
    "execution_count": 3,
    "id": "0da81a1a",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<dask.config.set at 0x292e5b5f610>"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "dask.config.set(scheduler=\"processes\")\n",
     "dask.config.set(num_workers=num_workers)\n",
@@ -561,8 +741,22 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
+      "pyam - INFO: Running in a notebook, setting up a basic logging at level INFO\n",
       "pyam.core - INFO: Reading file emissions_temp_AR6_small.xlsx\n",
-      "pyam.core - INFO: Found column 'exclude' in sheet 'meta', moved to attribute `IamDataFrame.exclude`.\n"
+      "/home/byers/py311/lib/python3.10/site-packages/pyam/core.py:2692: FutureWarning: unique with argument that is not not a Series, Index, ExtensionArray, or np.ndarray is deprecated and will raise in a future version.\n",
+      "  index = pd.unique(index)\n",
+      "pyam.core - INFO: Reading meta indicators\n",
+      "/home/byers/py311/lib/python3.10/site-packages/pyam/core.py:2692: FutureWarning: unique with argument that is not not a Series, Index, ExtensionArray, or np.ndarray is deprecated and will raise in a future version.\n",
+      "  index = pd.unique(index)\n",
+      "/home/byers/rime/rime/utils.py:92: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.\n",
+      "The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.\n",
+      "\n",
+      "For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.\n",
+      "\n",
+      "\n",
+      "  dft[ssp_meta_col].replace(\n",
+      "/home/byers/py311/lib/python3.10/site-packages/pyam/core.py:2692: FutureWarning: unique with argument that is not not a Series, Index, ExtensionArray, or np.ndarray is deprecated and will raise in a future version.\n",
+      "  index = pd.unique(index)\n"
      ]
     }
    ],
@@ -588,6 +782,25 @@
    "id": "0f6cae87-9717-4304-b841-5d61e87b55d3",
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/byers/py311/lib/python3.10/site-packages/pyam/core.py:2692: FutureWarning: unique with argument that is not not a Series, Index, ExtensionArray, or np.ndarray is deprecated and will raise in a future version.\n",
+      "  index = pd.unique(index)\n",
+      "/home/byers/py311/lib/python3.10/site-packages/pyam/core.py:2692: FutureWarning: unique with argument that is not not a Series, Index, ExtensionArray, or np.ndarray is deprecated and will raise in a future version.\n",
+      "  index = pd.unique(index)\n",
+      "/home/byers/rime/rime/utils.py:92: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.\n",
+      "The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.\n",
+      "\n",
+      "For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.\n",
+      "\n",
+      "\n",
+      "  dft[ssp_meta_col].replace(\n",
+      "/home/byers/py311/lib/python3.10/site-packages/pyam/core.py:2692: FutureWarning: unique with argument that is not not a Series, Index, ExtensionArray, or np.ndarray is deprecated and will raise in a future version.\n",
+      "  index = pd.unique(index)\n"
+     ]
+    },
     {
      "data": {
       "text/plain": [
@@ -646,7 +859,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
+   "id": "256391d3-798f-4c63-b5b8-0f3b2e1da325",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Requires some configuration - need to download the data from https://zenodo.org/records/10212339, and set the file paths in the file process_config.py"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
    "id": "f4c31c82",
    "metadata": {},
    "outputs": [
@@ -654,33 +877,19 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Test multiple IAM scenarios, 1 indicator\n",
-      "Single indicator mode (multi-scenarios possible)\n",
-      "COFFEE_1_1_EN_NPi2020_400f_lowBECCS\n",
-      "GCAM_5_3_NGFS2_Current Policies\n",
-      "IMAGE_3_0_EN_INDCi2030_3000f\n",
-      "IMAGE_3_0_1_SSP1-26\n",
-      "IMAGE_3_0_1_SSP2-45\n",
-      "IMAGE_3_0_1_SSP3-Baseline\n",
-      "IMAGE_3_0_1_SSP5-Baseline\n",
-      "REMIND-MAgPIE_2_1-4_2_SusDev_SDP-PkBudg1000\n",
-      "WITCH_5_0_CO_Bridge\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "c:\\github\\rime\\rime\\utils.py:103: UserWarning: rename 'threshold' to 'gmt' does not create an index anymore. Try using swap_dims instead or use set_index after rename to create an indexed coordinate.\n",
-      "  mapdata = mapdata.rename({'threshold':'gmt'})\n"
+      "Test multiple IAM scenarios, 1 indicator\n"
      ]
     },
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "FINISHED Test multiple scenarios, 1 indicator\n",
-      "19.469594478607178\n"
+     "ename": "OSError",
+     "evalue": "no files to open",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mOSError\u001b[0m                                   Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[7], line 14\u001b[0m\n\u001b[1;32m     10\u001b[0m ssp \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mssp2\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m     13\u001b[0m files \u001b[38;5;241m=\u001b[39m glob\u001b[38;5;241m.\u001b[39mglob(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mimpact_data_dir\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;130;01m\\\\\u001b[39;00m\u001b[38;5;132;01m{\u001b[39;00mind\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;130;01m\\\\\u001b[39;00m\u001b[38;5;124m*\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mshort\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m_\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mssp\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m*\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mftype\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.nc4\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m---> 14\u001b[0m mapdata \u001b[38;5;241m=\u001b[39m \u001b[43mxr\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen_mfdataset\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m     15\u001b[0m \u001b[43m    \u001b[49m\u001b[43mfiles\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpreprocess\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mremove_ssp_from_ds\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcombine\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mnested\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconcat_dim\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mgmt\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\n\u001b[1;32m     16\u001b[0m \u001b[43m)\u001b[49m\n\u001b[1;32m     18\u001b[0m mapdata \u001b[38;5;241m=\u001b[39m tidy_mapdata(mapdata)\n\u001b[1;32m     20\u001b[0m map_out_MS \u001b[38;5;241m=\u001b[39m map_transform_gmt_wrapper(\n\u001b[1;32m     21\u001b[0m     ssps_imp,\n\u001b[1;32m     22\u001b[0m     mapdata,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m     29\u001b[0m     interpolation\u001b[38;5;241m=\u001b[39minterpolation,\n\u001b[1;32m     30\u001b[0m )\n",
+      "File \u001b[0;32m~/py311/lib/python3.10/site-packages/xarray/backends/api.py:990\u001b[0m, in \u001b[0;36mopen_mfdataset\u001b[0;34m(paths, chunks, concat_dim, compat, preprocess, engine, data_vars, coords, combine, parallel, join, attrs_file, combine_attrs, **kwargs)\u001b[0m\n\u001b[1;32m    987\u001b[0m paths \u001b[38;5;241m=\u001b[39m _find_absolute_paths(paths, engine\u001b[38;5;241m=\u001b[39mengine, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m    989\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m paths:\n\u001b[0;32m--> 990\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mOSError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mno files to open\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m    992\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m combine \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnested\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m    993\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(concat_dim, (\u001b[38;5;28mstr\u001b[39m, DataArray)) \u001b[38;5;129;01mor\u001b[39;00m concat_dim \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n",
+      "\u001b[0;31mOSError\u001b[0m: no files to open"
      ]
     }
    ],
@@ -727,3468 +936,208 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "id": "d596a52f-3304-4cbb-b0cb-c86e83e39ecf",
    "metadata": {},
+   "outputs": [],
+   "source": [
+    "mapdata"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "794bd1c3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "map_out_MS"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f31bf98d",
+   "metadata": {},
+   "source": [
+    "## Example 2: 1 scenario, multiple indicators\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "07f26175",
+   "metadata": {},
+   "source": [
+    "### Build combined dataset with multiple indicators"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "85bab5fb",
+   "metadata": {},
    "outputs": [
     {
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-       "\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",
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-       "  padding-right: 10px;\n",
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-       "\n",
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-       "\n",
-       ".xr-icon-database,\n",
-       ".xr-icon-file-text2,\n",
-       ".xr-no-icon {\n",
-       "  display: inline-block;\n",
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-       "  width: 1em;\n",
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-       "  stroke: currentColor;\n",
-       "  fill: currentColor;\n",
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-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
-       "Dimensions:  (lon: 720, lat: 360, gmt: 6)\n",
-       "Coordinates:\n",
-       "  * lon      (lon) float64 -179.8 -179.2 -178.8 -178.2 ... 178.8 179.2 179.8\n",
-       "  * lat      (lat) float64 89.75 89.25 88.75 88.25 ... -88.75 -89.25 -89.75\n",
-       "  * gmt      (gmt) float64 1.2 1.5 2.0 2.5 3.0 3.5\n",
-       "Data variables:\n",
-       "    sdii     (gmt, lat, lon) float64 dask.array&lt;chunksize=(1, 360, 720), meta=np.ndarray&gt;</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-fe84dcae-d9c9-43a1-a370-dd7c89f0f859' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-fe84dcae-d9c9-43a1-a370-dd7c89f0f859' 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>: 720</li><li><span class='xr-has-index'>lat</span>: 360</li><li><span class='xr-has-index'>gmt</span>: 6</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-16f989de-1c73-4fc7-b859-601bc007dc22' class='xr-section-summary-in' type='checkbox'  checked><label for='section-16f989de-1c73-4fc7-b859-601bc007dc22' class='xr-section-summary' >Coordinates: <span>(3)</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'>-179.8 -179.2 ... 179.2 179.8</div><input id='attrs-78c0620b-685a-4706-a765-3215f0dc57f4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-78c0620b-685a-4706-a765-3215f0dc57f4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-20b81dec-5573-49c4-b47f-34e17693a818' class='xr-var-data-in' type='checkbox'><label for='data-20b81dec-5573-49c4-b47f-34e17693a818' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-179.75, -179.25, -178.75, ...,  178.75,  179.25,  179.75])</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'>89.75 89.25 88.75 ... -89.25 -89.75</div><input id='attrs-4bf972e1-2248-42fa-a237-f6aaca1005b4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4bf972e1-2248-42fa-a237-f6aaca1005b4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b0b3d9c4-55eb-47c9-885d-059d498aedc7' class='xr-var-data-in' type='checkbox'><label for='data-b0b3d9c4-55eb-47c9-885d-059d498aedc7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 89.75,  89.25,  88.75, ..., -88.75, -89.25, -89.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>gmt</span></div><div class='xr-var-dims'>(gmt)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.5 2.0 2.5 3.0 3.5</div><input id='attrs-45420902-a08d-4175-b2a1-9bb6a601269e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-45420902-a08d-4175-b2a1-9bb6a601269e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f0634f9-7365-4286-bdd5-cbf9c078de33' class='xr-var-data-in' type='checkbox'><label for='data-9f0634f9-7365-4286-bdd5-cbf9c078de33' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1.2, 1.5, 2. , 2.5, 3. , 3.5])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-132a8c0b-e45d-4a97-ae88-ff912cb9791a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-132a8c0b-e45d-4a97-ae88-ff912cb9791a' 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>sdii</span></div><div class='xr-var-dims'>(gmt, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 360, 720), meta=np.ndarray&gt;</div><input id='attrs-8c4d58a5-c56e-47fd-8c36-76d97999bc49' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8c4d58a5-c56e-47fd-8c36-76d97999bc49' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c430a7e3-492a-45a7-9a04-1ec35c90c99b' class='xr-var-data-in' type='checkbox'><label for='data-c430a7e3-492a-45a7-9a04-1ec35c90c99b' 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>authors :</span></dt><dd>M. Werning, E. Byers &amp; colleagues</dd><dt><span>institution :</span></dt><dd>IIASA</dd><dt><span>contact :</span></dt><dd>werning@iiasa.ac.at</dd><dt><span>long_name :</span></dt><dd>Precipitation intensity index</dd><dt><span>short_name :</span></dt><dd>sdii</dd><dt><span>description :</span></dt><dd>Precipitation intensity index risk score</dd><dt><span>scen :</span></dt><dd>1.2°C</dd><dt><span>scenario :</span></dt><dd>ssp2_1p2</dd><dt><span>model :</span></dt><dd>climate-solutions</dd><dt><span>layerid :</span></dt><dd>sdii_ssp2_1p2_score</dd><dt><span>variable :</span></dt><dd>sdii_ssp2_1p2|score</dd></dl></div><div class='xr-var-data'><table>\n",
-       "    <tr>\n",
-       "        <td>\n",
-       "            <table style=\"border-collapse: collapse;\">\n",
-       "                <thead>\n",
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-       "                <tbody>\n",
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-       "                        <th> Bytes </th>\n",
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-       "                        <td> 1.98 MiB </td>\n",
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-       "                        <td> (1, 360, 720) </td>\n",
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-       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-af422f7b-fca0-4c2b-912f-8eeac62420ee' class='xr-section-summary-in' type='checkbox'  ><label for='section-af422f7b-fca0-4c2b-912f-8eeac62420ee' class='xr-section-summary' >Indexes: <span>(3)</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-9e32dbcf-83ca-43c2-8028-c14328caa16e' class='xr-index-data-in' type='checkbox'/><label for='index-9e32dbcf-83ca-43c2-8028-c14328caa16e' 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(Float64Index([-179.75, -179.25, -178.75, -178.25, -177.75, -177.25, -176.75,\n",
-       "              -176.25, -175.75, -175.25,\n",
-       "              ...\n",
-       "               175.25,  175.75,  176.25,  176.75,  177.25,  177.75,  178.25,\n",
-       "               178.75,  179.25,  179.75],\n",
-       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=720))</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-9d131e08-a02b-4807-b5c4-45490a5a7c4c' class='xr-index-data-in' type='checkbox'/><label for='index-9d131e08-a02b-4807-b5c4-45490a5a7c4c' 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(Float64Index([ 89.75,  89.25,  88.75,  88.25,  87.75,  87.25,  86.75,  86.25,\n",
-       "               85.75,  85.25,\n",
-       "              ...\n",
-       "              -85.25, -85.75, -86.25, -86.75, -87.25, -87.75, -88.25, -88.75,\n",
-       "              -89.25, -89.75],\n",
-       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=360))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>gmt</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4739b73e-8a60-400d-b614-ea17ab8fcdad' class='xr-index-data-in' type='checkbox'/><label for='index-4739b73e-8a60-400d-b614-ea17ab8fcdad' 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(Float64Index([1.2, 1.5, 2.0, 2.5, 3.0, 3.5], dtype=&#x27;float64&#x27;, name=&#x27;gmt&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5f61e29f-9d45-4a94-94a6-f049262c422b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5f61e29f-9d45-4a94-94a6-f049262c422b' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
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-       "  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:  (lon: 720, lat: 360, year: 18)\n",
-       "Coordinates:\n",
-       "  * lon      (lon) float64 -179.8 -179.2 -178.8 -178.2 ... 178.8 179.2 179.8\n",
-       "  * lat      (lat) float64 89.75 89.25 88.75 88.25 ... -88.75 -89.25 -89.75\n",
-       "  * year     (year) int32 2015 2020 2025 2030 2035 ... 2080 2085 2090 2095 2100\n",
-       "Data variables:\n",
-       "    sdii     (lat, lon, year) float64 999.0 nan nan nan nan ... nan nan nan nan\n",
-       "Attributes:\n",
-       "    indicator:  sdii</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-7cf8a69b-8356-4a2e-b741-391a9b729ecf' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7cf8a69b-8356-4a2e-b741-391a9b729ecf' 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>: 720</li><li><span class='xr-has-index'>lat</span>: 360</li><li><span class='xr-has-index'>year</span>: 18</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-0093d423-e036-4ba4-935b-b1a084d79578' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0093d423-e036-4ba4-935b-b1a084d79578' class='xr-section-summary' >Coordinates: <span>(3)</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'>-179.8 -179.2 ... 179.2 179.8</div><input id='attrs-7e610d91-e275-4a37-8613-a672d5a1733d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7e610d91-e275-4a37-8613-a672d5a1733d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b6fa0c66-eca7-4ab5-b1f9-e374426f317f' class='xr-var-data-in' type='checkbox'><label for='data-b6fa0c66-eca7-4ab5-b1f9-e374426f317f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-179.75, -179.25, -178.75, ...,  178.75,  179.25,  179.75])</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'>89.75 89.25 88.75 ... -89.25 -89.75</div><input id='attrs-354589cc-61a6-45a3-927c-0e7dd3a39b65' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-354589cc-61a6-45a3-927c-0e7dd3a39b65' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-444289a7-6557-4f69-bdf3-72e1bbe718ff' class='xr-var-data-in' type='checkbox'><label for='data-444289a7-6557-4f69-bdf3-72e1bbe718ff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 89.75,  89.25,  88.75, ..., -88.75, -89.25, -89.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>year</span></div><div class='xr-var-dims'>(year)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>2015 2020 2025 ... 2090 2095 2100</div><input id='attrs-dc8c8188-5b08-4207-8bed-0e32ebf101de' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-dc8c8188-5b08-4207-8bed-0e32ebf101de' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd2a869f-f26e-4bcc-8d02-50084ea27388' class='xr-var-data-in' type='checkbox'><label for='data-dd2a869f-f26e-4bcc-8d02-50084ea27388' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([2015, 2020, 2025, 2030, 2035, 2040, 2045, 2050, 2055, 2060, 2065, 2070,\n",
-       "       2075, 2080, 2085, 2090, 2095, 2100])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0019fe4d-5697-484c-a31d-d255784c88a8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0019fe4d-5697-484c-a31d-d255784c88a8' 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>sdii</span></div><div class='xr-var-dims'>(lat, lon, year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>999.0 nan nan nan ... nan nan nan</div><input id='attrs-524d764e-f83e-46db-9a38-f31481802c92' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-524d764e-f83e-46db-9a38-f31481802c92' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cdc04350-b63b-4770-b361-ae4abf7d5f6e' class='xr-var-data-in' type='checkbox'><label for='data-cdc04350-b63b-4770-b361-ae4abf7d5f6e' 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>authors :</span></dt><dd>M. Werning, E. Byers &amp; colleagues</dd><dt><span>institution :</span></dt><dd>IIASA</dd><dt><span>contact :</span></dt><dd>werning@iiasa.ac.at</dd><dt><span>long_name :</span></dt><dd>Precipitation intensity index</dd><dt><span>short_name :</span></dt><dd>sdii</dd><dt><span>description :</span></dt><dd>Precipitation intensity index risk score</dd><dt><span>scen :</span></dt><dd>1.2°C</dd><dt><span>scenario :</span></dt><dd>ssp2_1p2</dd><dt><span>model :</span></dt><dd>climate-solutions</dd><dt><span>layerid :</span></dt><dd>sdii_ssp2_1p2_score</dd><dt><span>variable :</span></dt><dd>sdii_ssp2_1p2|score</dd></dl></div><div class='xr-var-data'><pre>array([[[999.,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "        [999.,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "        [999.,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "        ...,\n",
-       "        [999.,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "        [999.,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "        [999.,  nan,  nan, ...,  nan,  nan,  nan]],\n",
-       "\n",
-       "       [[999.,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "        [999.,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "        [999.,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "        ...,\n",
-       "        [999.,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "        [999.,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "        [999.,  nan,  nan, ...,  nan,  nan,  nan]],\n",
-       "\n",
-       "       [[999.,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "        [999.,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "        [999.,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "        ...,\n",
-       "...\n",
-       "        ...,\n",
-       "        [999.,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "        [999.,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "        [999.,  nan,  nan, ...,  nan,  nan,  nan]],\n",
-       "\n",
-       "       [[999.,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "        [999.,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "        [999.,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "        ...,\n",
-       "        [999.,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "        [999.,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "        [999.,  nan,  nan, ...,  nan,  nan,  nan]],\n",
-       "\n",
-       "       [[999.,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "        [999.,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "        [999.,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "        ...,\n",
-       "        [999.,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "        [999.,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "        [999.,  nan,  nan, ...,  nan,  nan,  nan]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ad41ccfa-20a8-4b26-83be-47d976804b61' class='xr-section-summary-in' type='checkbox'  ><label for='section-ad41ccfa-20a8-4b26-83be-47d976804b61' class='xr-section-summary' >Indexes: <span>(3)</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-54c76384-fefd-48ca-ae9d-a10053c56346' class='xr-index-data-in' type='checkbox'/><label for='index-54c76384-fefd-48ca-ae9d-a10053c56346' 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(Float64Index([-179.75, -179.25, -178.75, -178.25, -177.75, -177.25, -176.75,\n",
-       "              -176.25, -175.75, -175.25,\n",
-       "              ...\n",
-       "               175.25,  175.75,  176.25,  176.75,  177.25,  177.75,  178.25,\n",
-       "               178.75,  179.25,  179.75],\n",
-       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=720))</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-0ab79b2b-e1d0-48e7-8302-7efcdc05740f' class='xr-index-data-in' type='checkbox'/><label for='index-0ab79b2b-e1d0-48e7-8302-7efcdc05740f' 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(Float64Index([ 89.75,  89.25,  88.75,  88.25,  87.75,  87.25,  86.75,  86.25,\n",
-       "               85.75,  85.25,\n",
-       "              ...\n",
-       "              -85.25, -85.75, -86.25, -86.75, -87.25, -87.75, -88.25, -88.75,\n",
-       "              -89.25, -89.75],\n",
-       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=360))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9fb10feb-082d-4bb0-b80a-7d18f69480d6' class='xr-index-data-in' type='checkbox'/><label for='index-9fb10feb-082d-4bb0-b80a-7d18f69480d6' 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(Int64Index([2015, 2020, 2025, 2030, 2035, 2040, 2045, 2050, 2055, 2060, 2065,\n",
-       "            2070, 2075, 2080, 2085, 2090, 2095, 2100],\n",
-       "           dtype=&#x27;int64&#x27;, name=&#x27;year&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-dd0e0cc0-d820-4398-a0fd-a55a154d0212' class='xr-section-summary-in' type='checkbox'  checked><label for='section-dd0e0cc0-d820-4398-a0fd-a55a154d0212' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>indicator :</span></dt><dd>sdii</dd></dl></div></li></ul></div></div>"
-      ],
-      "text/plain": [
-       "<xarray.Dataset>\n",
-       "Dimensions:  (lon: 720, lat: 360, year: 18)\n",
-       "Coordinates:\n",
-       "  * lon      (lon) float64 -179.8 -179.2 -178.8 -178.2 ... 178.8 179.2 179.8\n",
-       "  * lat      (lat) float64 89.75 89.25 88.75 88.25 ... -88.75 -89.25 -89.75\n",
-       "  * year     (year) int32 2015 2020 2025 2030 2035 ... 2080 2085 2090 2095 2100\n",
-       "Data variables:\n",
-       "    sdii     (lat, lon, year) float64 999.0 nan nan nan nan ... nan nan nan nan\n",
-       "Attributes:\n",
-       "    indicator:  sdii"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "map_out_MS"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "f31bf98d",
-   "metadata": {},
-   "source": [
-    "## Example 2: 1 scenario, multiple indicators\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "07f26175",
-   "metadata": {},
-   "source": [
-    "### Build combined dataset with multiple indicators"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "id": "85bab5fb",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Test 1 scenario, multiple indicators\n",
-      "cdd\n",
-      "pr_r10\n",
-      "pr_r20\n",
-      "pr_r95p\n",
-      "pr_r99p\n",
-      "sdii\n",
-      "dri\n",
-      "sdd_c_18p3\n",
-      "sdd_c_24p0\n",
-      "seas\n",
-      "wsi\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "c:\\github\\rime\\rime\\utils.py:103: UserWarning: rename 'threshold' to 'gmt' does not create an index anymore. Try using swap_dims instead or use set_index after rename to create an indexed coordinate.\n",
-      "  mapdata = mapdata.rename({'threshold':'gmt'})\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Doesn't work -0\n",
-    "# AttributeError: 'DataArray' object has no attribute 'rename_vars'\n",
-    "# lines 230-233 in map_transform_gmt\n",
-    "\n",
-    "gmt_name = \"gmt\"\n",
-    "print(\"Test 1 scenario, multiple indicators\")\n",
-    "start = time.time()\n",
-    "ssp = \"ssp2\"\n",
-    "mapdata = xr.Dataset()\n",
-    "indicators = [\n",
-    "    \"cdd\",\n",
-    "    \"precip\",\n",
-    "    \"dri\",\n",
-    "    # \"dri_qtot\",\n",
-    "    # \"ia_var\",\n",
-    "    # \"ia_var_qtot\",\n",
-    "    \"sdd_18p3\",\n",
-    "    \"sdd_24p0\",\n",
-    "    \"seas\",\n",
-    "    \"wsi\",\n",
-    "]  #'heatwave']\n",
-    "\n",
-    "for ind in indicators:\n",
-    "    for var in params[\"indicators\"][ind]:\n",
-    "        short = params[\"indicators\"][ind][var][\"short_name\"]\n",
-    "        print(short)\n",
-    "        files = glob.glob(\n",
-    "            os.path.join(impact_data_dir, ind, f\"*{short}_{ssp}*{ftype}.nc4\")\n",
-    "        )\n",
-    "        mapdata[short] = xr.open_mfdataset(\n",
-    "            files, preprocess=remove_ssp_from_ds, combine=\"nested\", concat_dim=\"gmt\"\n",
-    "        )[short]\n",
-    "\n",
-    "mapdata = tidy_mapdata(mapdata)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "cc24e437",
-   "metadata": {},
-   "source": [
-    "### Run transformation (12 impact indicators) (faster with dask=False)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "id": "bd26a126",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Single scenario mode, multiple indicators possible\n",
-      "Warning! Min temperature below 1.2°C  1.12, data before not possible\n",
-      "FINISHED 1 scenario, multiple indicators\n",
-      "198.64874148368835\n"
-     ]
-    }
-   ],
-   "source": [
-    "map_out_MI = map_transform_gmt_wrapper(\n",
-    "    ssps_imp.filter(IMP_marker=\"CurPol\"),\n",
-    "    mapdata,\n",
-    "    years,\n",
-    "    use_dask=False,\n",
-    "    gmt_name=\"gmt\",\n",
-    ")\n",
-    "\n",
-    "comp = dict(zlib=True, complevel=5)\n",
-    "encoding = {var: comp for var in map_out_MI.data_vars}\n",
-    "filename = f\"{output_folder_maps}scenario_maps_multiindicator_{ftype}_test_notebook.nc\"\n",
-    "# map_out_MI.to_netcdf(filename, encoding=encoding)\n",
-    "\n",
-    "print(\"FINISHED 1 scenario, multiple indicators\")\n",
-    "print(f\"{time.time()-start}\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "8c7c007c",
-   "metadata": {},
-   "source": [
-    "### Data is now transformed to 5 year interval starting 2015"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 20,
-   "id": "169f89a5",
-   "metadata": {},
-   "outputs": [
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-       "Dimensions:     (lon: 720, lat: 360, year: 18)\n",
-       "Coordinates:\n",
-       "  * lon         (lon) float64 -179.8 -179.2 -178.8 -178.2 ... 178.8 179.2 179.8\n",
-       "  * lat         (lat) float64 89.75 89.25 88.75 88.25 ... -88.75 -89.25 -89.75\n",
-       "  * year        (year) int32 2015 2020 2025 2030 2035 ... 2085 2090 2095 2100\n",
-       "Data variables:\n",
-       "    cdd         (lat, lon, year) float64 dask.array&lt;chunksize=(360, 720, 1), meta=np.ndarray&gt;\n",
-       "    pr_r10      (lat, lon, year) float64 dask.array&lt;chunksize=(360, 720, 1), meta=np.ndarray&gt;\n",
-       "    pr_r20      (lat, lon, year) float64 dask.array&lt;chunksize=(360, 720, 1), meta=np.ndarray&gt;\n",
-       "    pr_r95p     (lat, lon, year) float64 dask.array&lt;chunksize=(360, 720, 1), meta=np.ndarray&gt;\n",
-       "    pr_r99p     (lat, lon, year) float64 dask.array&lt;chunksize=(360, 720, 1), meta=np.ndarray&gt;\n",
-       "    sdii        (lat, lon, year) float64 dask.array&lt;chunksize=(360, 720, 1), meta=np.ndarray&gt;\n",
-       "    dri         (lat, lon, year) float64 dask.array&lt;chunksize=(360, 720, 1), meta=np.ndarray&gt;\n",
-       "    sdd_c_18p3  (lat, lon, year) float64 dask.array&lt;chunksize=(360, 720, 1), meta=np.ndarray&gt;\n",
-       "    sdd_c_24p0  (lat, lon, year) float64 dask.array&lt;chunksize=(360, 720, 1), meta=np.ndarray&gt;\n",
-       "    seas        (lat, lon, year) float64 dask.array&lt;chunksize=(360, 720, 1), meta=np.ndarray&gt;\n",
-       "    wsi         (lat, lon, year) float64 dask.array&lt;chunksize=(360, 720, 1), meta=np.ndarray&gt;\n",
-       "Attributes:\n",
-       "    model:     GCAM 5.3\n",
-       "    scenario:  NGFS2_Current Policies</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-501624c5-769a-41b0-8490-34feeb7f9f27' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-501624c5-769a-41b0-8490-34feeb7f9f27' 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>: 720</li><li><span class='xr-has-index'>lat</span>: 360</li><li><span class='xr-has-index'>year</span>: 18</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-4b49337d-48bb-4792-b0cb-9dd5aec57cfd' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4b49337d-48bb-4792-b0cb-9dd5aec57cfd' class='xr-section-summary' >Coordinates: <span>(3)</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'>-179.8 -179.2 ... 179.2 179.8</div><input id='attrs-00dac689-06e8-4956-98e1-d64c75814fdc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-00dac689-06e8-4956-98e1-d64c75814fdc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5a744e3-a75e-4bc5-8bff-08d68c71965d' class='xr-var-data-in' type='checkbox'><label for='data-d5a744e3-a75e-4bc5-8bff-08d68c71965d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-179.75, -179.25, -178.75, ...,  178.75,  179.25,  179.75])</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'>89.75 89.25 88.75 ... -89.25 -89.75</div><input id='attrs-f19d0073-84db-482f-8493-c0e1f8575921' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f19d0073-84db-482f-8493-c0e1f8575921' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-405b6900-35a5-4b25-afe3-c07ccf02539b' class='xr-var-data-in' type='checkbox'><label for='data-405b6900-35a5-4b25-afe3-c07ccf02539b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 89.75,  89.25,  88.75, ..., -88.75, -89.25, -89.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>year</span></div><div class='xr-var-dims'>(year)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>2015 2020 2025 ... 2090 2095 2100</div><input id='attrs-ef76d164-f535-48e3-a554-426f97c0d3f9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ef76d164-f535-48e3-a554-426f97c0d3f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1e9167b5-535c-4e45-8db3-dcbec0ca9539' class='xr-var-data-in' type='checkbox'><label for='data-1e9167b5-535c-4e45-8db3-dcbec0ca9539' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([2015, 2020, 2025, 2030, 2035, 2040, 2045, 2050, 2055, 2060, 2065, 2070,\n",
-       "       2075, 2080, 2085, 2090, 2095, 2100])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9acee097-2007-43ab-a20c-800eda682a2c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9acee097-2007-43ab-a20c-800eda682a2c' class='xr-section-summary' >Data variables: <span>(11)</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>cdd</span></div><div class='xr-var-dims'>(lat, lon, year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(360, 720, 1), meta=np.ndarray&gt;</div><input id='attrs-2afe3cb2-a761-4e8c-bae9-b9be50932555' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2afe3cb2-a761-4e8c-bae9-b9be50932555' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-272f4826-25ae-4066-83fe-c36d51d78cfa' class='xr-var-data-in' type='checkbox'><label for='data-272f4826-25ae-4066-83fe-c36d51d78cfa' 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>authors :</span></dt><dd>M. Werning, E. Byers &amp; colleagues</dd><dt><span>institution :</span></dt><dd>IIASA</dd><dt><span>contact :</span></dt><dd>werning@iiasa.ac.at</dd><dt><span>long_name :</span></dt><dd>Consecutive dry days</dd><dt><span>short_name :</span></dt><dd>cdd</dd><dt><span>description :</span></dt><dd>Consecutive dry days risk score</dd><dt><span>scen :</span></dt><dd>1.2°C</dd><dt><span>scenario :</span></dt><dd>ssp2_1p2</dd><dt><span>model :</span></dt><dd>climate-solutions</dd><dt><span>layerid :</span></dt><dd>cdd_ssp2_1p2_score</dd><dt><span>variable :</span></dt><dd>cdd_ssp2_1p2|score</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> 35.60 MiB </td>\n",
-       "                        <td> 33.62 MiB </td>\n",
-       "                    </tr>\n",
-       "                    \n",
-       "                    <tr>\n",
-       "                        <th> Shape </th>\n",
-       "                        <td> (360, 720, 18) </td>\n",
-       "                        <td> (360, 720, 17) </td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <th> Dask graph </th>\n",
-       "                        <td colspan=\"2\"> 2 chunks in 31 graph layers </td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <th> Data type </th>\n",
-       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pr_r10</span></div><div class='xr-var-dims'>(lat, lon, year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(360, 720, 1), meta=np.ndarray&gt;</div><input id='attrs-048865fd-1b40-41ee-a5a1-5da70a993369' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-048865fd-1b40-41ee-a5a1-5da70a993369' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bc9c142e-f484-4e37-a969-222a656af26f' class='xr-var-data-in' type='checkbox'><label for='data-bc9c142e-f484-4e37-a969-222a656af26f' 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>authors :</span></dt><dd>M. Werning, E. Byers &amp; colleagues</dd><dt><span>institution :</span></dt><dd>IIASA</dd><dt><span>contact :</span></dt><dd>werning@iiasa.ac.at</dd><dt><span>long_name :</span></dt><dd>Heavy precipitation days</dd><dt><span>short_name :</span></dt><dd>pr_r10</dd><dt><span>description :</span></dt><dd>Heavy precipitation days risk score</dd><dt><span>scen :</span></dt><dd>1.2°C</dd><dt><span>scenario :</span></dt><dd>ssp2_1p2</dd><dt><span>model :</span></dt><dd>climate-solutions</dd><dt><span>layerid :</span></dt><dd>pr_r10_ssp2_1p2_score</dd><dt><span>variable :</span></dt><dd>pr_r10_ssp2_1p2|score</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",
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-       "                </thead>\n",
-       "                <tbody>\n",
-       "                    \n",
-       "                    <tr>\n",
-       "                        <th> Bytes </th>\n",
-       "                        <td> 35.60 MiB </td>\n",
-       "                        <td> 33.62 MiB </td>\n",
-       "                    </tr>\n",
-       "                    \n",
-       "                    <tr>\n",
-       "                        <th> Shape </th>\n",
-       "                        <td> (360, 720, 18) </td>\n",
-       "                        <td> (360, 720, 17) </td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <th> Dask graph </th>\n",
-       "                        <td colspan=\"2\"> 2 chunks in 31 graph layers </td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <th> Data type </th>\n",
-       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pr_r20</span></div><div class='xr-var-dims'>(lat, lon, year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(360, 720, 1), meta=np.ndarray&gt;</div><input id='attrs-9e0cb5d0-a0d4-4376-97be-1f2040b9a811' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9e0cb5d0-a0d4-4376-97be-1f2040b9a811' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1ba7b916-a6a7-4d50-8a25-bfd92ea6ea29' class='xr-var-data-in' type='checkbox'><label for='data-1ba7b916-a6a7-4d50-8a25-bfd92ea6ea29' 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>authors :</span></dt><dd>M. Werning, E. Byers &amp; colleagues</dd><dt><span>institution :</span></dt><dd>IIASA</dd><dt><span>contact :</span></dt><dd>werning@iiasa.ac.at</dd><dt><span>long_name :</span></dt><dd>Very heavy precipitation days</dd><dt><span>short_name :</span></dt><dd>pr_r20</dd><dt><span>description :</span></dt><dd>Very heavy precipitation days risk score</dd><dt><span>scen :</span></dt><dd>1.2°C</dd><dt><span>scenario :</span></dt><dd>ssp2_1p2</dd><dt><span>model :</span></dt><dd>climate-solutions</dd><dt><span>layerid :</span></dt><dd>pr_r20_ssp2_1p2_score</dd><dt><span>variable :</span></dt><dd>pr_r20_ssp2_1p2|score</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",
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-       "                </thead>\n",
-       "                <tbody>\n",
-       "                    \n",
-       "                    <tr>\n",
-       "                        <th> Bytes </th>\n",
-       "                        <td> 35.60 MiB </td>\n",
-       "                        <td> 33.62 MiB </td>\n",
-       "                    </tr>\n",
-       "                    \n",
-       "                    <tr>\n",
-       "                        <th> Shape </th>\n",
-       "                        <td> (360, 720, 18) </td>\n",
-       "                        <td> (360, 720, 17) </td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <th> Dask graph </th>\n",
-       "                        <td colspan=\"2\"> 2 chunks in 31 graph layers </td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <th> Data type </th>\n",
-       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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-       "    <tr>\n",
-       "        <td>\n",
-       "            <table style=\"border-collapse: collapse;\">\n",
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-       "                    <tr>\n",
-       "                        <td> </td>\n",
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-       "                        <th> Chunk </th>\n",
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-       "                <tbody>\n",
-       "                    \n",
-       "                    <tr>\n",
-       "                        <th> Bytes </th>\n",
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-       "                    \n",
-       "                    <tr>\n",
-       "                        <th> Shape </th>\n",
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-       "                        <td> (360, 720, 17) </td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <th> Dask graph </th>\n",
-       "                        <td colspan=\"2\"> 2 chunks in 31 graph layers </td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
-       "                        <th> Data type </th>\n",
-       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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-       "        <td>\n",
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-       "                <tbody>\n",
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-       "                    <tr>\n",
-       "                        <th> Bytes </th>\n",
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-       "                    \n",
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-       "                        <th> Shape </th>\n",
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-       "                        <td> (360, 720, 17) </td>\n",
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-       "                    <tr>\n",
-       "                        <th> Dask graph </th>\n",
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-       "                    <tr>\n",
-       "                        <th> Data type </th>\n",
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-       "                        <td> 33.62 MiB </td>\n",
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-       "                    <tr>\n",
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-       "                        <th> Data type </th>\n",
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-       "    <tr>\n",
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-       "                <tbody>\n",
-       "                    \n",
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-       "                        <th> Bytes </th>\n",
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-       "                        <th> Data type </th>\n",
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-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wsi</span></div><div class='xr-var-dims'>(lat, lon, year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(360, 720, 1), meta=np.ndarray&gt;</div><input id='attrs-c66181c4-1e8e-4ceb-85e8-95def2fd085e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c66181c4-1e8e-4ceb-85e8-95def2fd085e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7225894d-63c4-4416-9973-4c77ee07940f' class='xr-var-data-in' type='checkbox'><label for='data-7225894d-63c4-4416-9973-4c77ee07940f' 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>authors :</span></dt><dd>M. Werning, E. Byers &amp; colleagues</dd><dt><span>institution :</span></dt><dd>IIASA</dd><dt><span>contact :</span></dt><dd>werning@iiasa.ac.at</dd><dt><span>long_name :</span></dt><dd>Water stress index</dd><dt><span>short_name :</span></dt><dd>wsi</dd><dt><span>description :</span></dt><dd>Water stress index risk score</dd><dt><span>scen :</span></dt><dd>1.2°C</dd><dt><span>scenario :</span></dt><dd>ssp2_1p2</dd><dt><span>model :</span></dt><dd>climate-solutions</dd><dt><span>layerid :</span></dt><dd>wsi_ssp2_1p2_score</dd><dt><span>variable :</span></dt><dd>wsi_ssp2_1p2|score</dd></dl></div><div class='xr-var-data'><table>\n",
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-       "                <tbody>\n",
-       "                    \n",
-       "                    <tr>\n",
-       "                        <th> Bytes </th>\n",
-       "                        <td> 35.60 MiB </td>\n",
-       "                        <td> 33.62 MiB </td>\n",
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-       "                    <tr>\n",
-       "                        <th> Dask graph </th>\n",
-       "                        <td colspan=\"2\"> 2 chunks in 31 graph layers </td>\n",
-       "                    </tr>\n",
-       "                    <tr>\n",
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-       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-4180a5db-ae98-4c6f-8483-e0f71331fd36' class='xr-section-summary-in' type='checkbox'  ><label for='section-4180a5db-ae98-4c6f-8483-e0f71331fd36' class='xr-section-summary' >Indexes: <span>(3)</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-cfa48461-7138-43f4-9a22-fbabbf9bcdbc' class='xr-index-data-in' type='checkbox'/><label for='index-cfa48461-7138-43f4-9a22-fbabbf9bcdbc' 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(Float64Index([-179.75, -179.25, -178.75, -178.25, -177.75, -177.25, -176.75,\n",
-       "              -176.25, -175.75, -175.25,\n",
-       "              ...\n",
-       "               175.25,  175.75,  176.25,  176.75,  177.25,  177.75,  178.25,\n",
-       "               178.75,  179.25,  179.75],\n",
-       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=720))</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-6357f45d-7a05-4dc4-a8fd-34f7d06d56ed' class='xr-index-data-in' type='checkbox'/><label for='index-6357f45d-7a05-4dc4-a8fd-34f7d06d56ed' 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(Float64Index([ 89.75,  89.25,  88.75,  88.25,  87.75,  87.25,  86.75,  86.25,\n",
-       "               85.75,  85.25,\n",
-       "              ...\n",
-       "              -85.25, -85.75, -86.25, -86.75, -87.25, -87.75, -88.25, -88.75,\n",
-       "              -89.25, -89.75],\n",
-       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=360))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1b7a15ed-28fe-40f5-b3ab-92e6f8eaf2fd' class='xr-index-data-in' type='checkbox'/><label for='index-1b7a15ed-28fe-40f5-b3ab-92e6f8eaf2fd' 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(Int64Index([2015, 2020, 2025, 2030, 2035, 2040, 2045, 2050, 2055, 2060, 2065,\n",
-       "            2070, 2075, 2080, 2085, 2090, 2095, 2100],\n",
-       "           dtype=&#x27;int64&#x27;, name=&#x27;year&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7b1ee93f-9055-4976-9498-41ee66ba4390' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7b1ee93f-9055-4976-9498-41ee66ba4390' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>model :</span></dt><dd>GCAM 5.3</dd><dt><span>scenario :</span></dt><dd>NGFS2_Current Policies</dd></dl></div></li></ul></div></div>"
-      ],
-      "text/plain": [
-       "<xarray.Dataset>\n",
-       "Dimensions:     (lon: 720, lat: 360, year: 18)\n",
-       "Coordinates:\n",
-       "  * lon         (lon) float64 -179.8 -179.2 -178.8 -178.2 ... 178.8 179.2 179.8\n",
-       "  * lat         (lat) float64 89.75 89.25 88.75 88.25 ... -88.75 -89.25 -89.75\n",
-       "  * year        (year) int32 2015 2020 2025 2030 2035 ... 2085 2090 2095 2100\n",
-       "Data variables:\n",
-       "    cdd         (lat, lon, year) float64 dask.array<chunksize=(360, 720, 1), meta=np.ndarray>\n",
-       "    pr_r10      (lat, lon, year) float64 dask.array<chunksize=(360, 720, 1), meta=np.ndarray>\n",
-       "    pr_r20      (lat, lon, year) float64 dask.array<chunksize=(360, 720, 1), meta=np.ndarray>\n",
-       "    pr_r95p     (lat, lon, year) float64 dask.array<chunksize=(360, 720, 1), meta=np.ndarray>\n",
-       "    pr_r99p     (lat, lon, year) float64 dask.array<chunksize=(360, 720, 1), meta=np.ndarray>\n",
-       "    sdii        (lat, lon, year) float64 dask.array<chunksize=(360, 720, 1), meta=np.ndarray>\n",
-       "    dri         (lat, lon, year) float64 dask.array<chunksize=(360, 720, 1), meta=np.ndarray>\n",
-       "    sdd_c_18p3  (lat, lon, year) float64 dask.array<chunksize=(360, 720, 1), meta=np.ndarray>\n",
-       "    sdd_c_24p0  (lat, lon, year) float64 dask.array<chunksize=(360, 720, 1), meta=np.ndarray>\n",
-       "    seas        (lat, lon, year) float64 dask.array<chunksize=(360, 720, 1), meta=np.ndarray>\n",
-       "    wsi         (lat, lon, year) float64 dask.array<chunksize=(360, 720, 1), meta=np.ndarray>\n",
-       "Attributes:\n",
-       "    model:     GCAM 5.3\n",
-       "    scenario:  NGFS2_Current Policies"
-      ]
-     },
-     "execution_count": 20,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "map_out_MI"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "b4ff7baa",
-   "metadata": {},
-   "source": [
-    "## Plot dashboard (takes some minutes)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 21,
-   "id": "b407883b",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Warning: year not in original data, interpolating now\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "C:\\Users\\byers\\Anaconda3\\envs\\py310\\lib\\site-packages\\geoviews\\operation\\__init__.py:14: HoloviewsDeprecationWarning: 'ResamplingOperation' is deprecated and will be removed in version 1.18, use 'ResampleOperation2D' instead.\n",
-      "  from holoviews.operation.datashader import (\n"
-     ]
-    }
-   ],
-   "source": [
-    "filename = \"test_map_notebook.html\"\n",
-    "plot_maps_dashboard(\n",
-    "    map_out_MI,\n",
-    "    filename=filename,\n",
-    "    year=2063,\n",
-    "    cmap=\"magma_r\",\n",
-    "    shared_axes=True,\n",
-    "    clim=None,\n",
-    ")\n",
-    "os.startfile(filename)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "53155084",
-   "metadata": {},
-   "source": [
-    "## Process corresponding table data, aggregated by country"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "534c8807",
-   "metadata": {},
-   "source": [
-    "### Import the climate impacts database files\n",
-    "Here is an example for sdii - standard precipitation index, and multiple variables, e.g.  \n",
-    "Exposure of land area  \n",
-    "Exposure of population  \n",
-    "Hazard value  \n",
-    "...  \n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 22,
-   "id": "a9ee85cf",
-   "metadata": {},
-   "outputs": [
-    {
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-       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
-       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
-       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
-       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
-       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
-       "  --xr-background-color: var(--jp-layout-color0, white);\n",
-       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
-       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
-       "}\n",
-       "\n",
-       "html[theme=dark],\n",
-       "body[data-theme=dark],\n",
-       "body.vscode-dark {\n",
-       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
-       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
-       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
-       "  --xr-border-color: #1F1F1F;\n",
-       "  --xr-disabled-color: #515151;\n",
-       "  --xr-background-color: #111111;\n",
-       "  --xr-background-color-row-even: #111111;\n",
-       "  --xr-background-color-row-odd: #313131;\n",
-       "}\n",
-       "\n",
-       ".xr-wrap {\n",
-       "  display: block !important;\n",
-       "  min-width: 300px;\n",
-       "  max-width: 700px;\n",
-       "}\n",
-       "\n",
-       ".xr-text-repr-fallback {\n",
-       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-header {\n",
-       "  padding-top: 6px;\n",
-       "  padding-bottom: 6px;\n",
-       "  margin-bottom: 4px;\n",
-       "  border-bottom: solid 1px var(--xr-border-color);\n",
-       "}\n",
-       "\n",
-       ".xr-header > div,\n",
-       ".xr-header > ul {\n",
-       "  display: inline;\n",
-       "  margin-top: 0;\n",
-       "  margin-bottom: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-obj-type,\n",
-       ".xr-array-name {\n",
-       "  margin-left: 2px;\n",
-       "  margin-right: 10px;\n",
-       "}\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",
-       "}\n",
-       "\n",
-       ".xr-section-item input:enabled + label:hover {\n",
-       "  color: var(--xr-font-color0);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary {\n",
-       "  grid-column: 1;\n",
-       "  color: var(--xr-font-color2);\n",
-       "  font-weight: 500;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary > span {\n",
-       "  display: inline-block;\n",
-       "  padding-left: 0.5em;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:disabled + label {\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in + label:before {\n",
-       "  display: inline-block;\n",
-       "  content: '►';\n",
-       "  font-size: 11px;\n",
-       "  width: 15px;\n",
-       "  text-align: center;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:disabled + label:before {\n",
-       "  color: var(--xr-disabled-color);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked + label:before {\n",
-       "  content: '▼';\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked + label > span {\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary,\n",
-       ".xr-section-inline-details {\n",
-       "  padding-top: 4px;\n",
-       "  padding-bottom: 4px;\n",
-       "}\n",
-       "\n",
-       ".xr-section-inline-details {\n",
-       "  grid-column: 2 / -1;\n",
-       "}\n",
-       "\n",
-       ".xr-section-details {\n",
-       "  display: none;\n",
-       "  grid-column: 1 / -1;\n",
-       "  margin-bottom: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-array-wrap {\n",
-       "  grid-column: 1 / -1;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 20px auto;\n",
-       "}\n",
-       "\n",
-       ".xr-array-wrap > label {\n",
-       "  grid-column: 1;\n",
-       "  vertical-align: top;\n",
-       "}\n",
-       "\n",
-       ".xr-preview {\n",
-       "  color: var(--xr-font-color3);\n",
-       "}\n",
-       "\n",
-       ".xr-array-preview,\n",
-       ".xr-array-data {\n",
-       "  padding: 0 5px !important;\n",
-       "  grid-column: 2;\n",
-       "}\n",
-       "\n",
-       ".xr-array-data,\n",
-       ".xr-array-in:checked ~ .xr-array-preview {\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-array-in:checked ~ .xr-array-data,\n",
-       ".xr-array-preview {\n",
-       "  display: inline-block;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list {\n",
-       "  display: inline-block !important;\n",
-       "  list-style: none;\n",
-       "  padding: 0 !important;\n",
-       "  margin: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list li {\n",
-       "  display: inline-block;\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list:before {\n",
-       "  content: '(';\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list:after {\n",
-       "  content: ')';\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list li:not(:last-child):after {\n",
-       "  content: ',';\n",
-       "  padding-right: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-has-index {\n",
-       "  font-weight: bold;\n",
-       "}\n",
-       "\n",
-       ".xr-var-list,\n",
-       ".xr-var-item {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-var-item > div,\n",
-       ".xr-var-item label,\n",
-       ".xr-var-item > .xr-var-name span {\n",
-       "  background-color: var(--xr-background-color-row-even);\n",
-       "  margin-bottom: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-var-item > .xr-var-name:hover span {\n",
-       "  padding-right: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-var-list > li:nth-child(odd) > div,\n",
-       ".xr-var-list > li:nth-child(odd) > label,\n",
-       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
-       "  background-color: var(--xr-background-color-row-odd);\n",
-       "}\n",
-       "\n",
-       ".xr-var-name {\n",
-       "  grid-column: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-var-dims {\n",
-       "  grid-column: 2;\n",
-       "}\n",
-       "\n",
-       ".xr-var-dtype {\n",
-       "  grid-column: 3;\n",
-       "  text-align: right;\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-var-preview {\n",
-       "  grid-column: 4;\n",
-       "}\n",
-       "\n",
-       ".xr-index-preview {\n",
-       "  grid-column: 2 / 5;\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-var-name,\n",
-       ".xr-var-dims,\n",
-       ".xr-var-dtype,\n",
-       ".xr-preview,\n",
-       ".xr-attrs dt {\n",
-       "  white-space: nowrap;\n",
-       "  overflow: hidden;\n",
-       "  text-overflow: ellipsis;\n",
-       "  padding-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-var-name:hover,\n",
-       ".xr-var-dims:hover,\n",
-       ".xr-var-dtype:hover,\n",
-       ".xr-attrs dt:hover {\n",
-       "  overflow: visible;\n",
-       "  width: auto;\n",
-       "  z-index: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-var-attrs,\n",
-       ".xr-var-data,\n",
-       ".xr-index-data {\n",
-       "  display: none;\n",
-       "  background-color: var(--xr-background-color) !important;\n",
-       "  padding-bottom: 5px !important;\n",
-       "}\n",
-       "\n",
-       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
-       ".xr-var-data-in:checked ~ .xr-var-data,\n",
-       ".xr-index-data-in:checked ~ .xr-index-data {\n",
-       "  display: block;\n",
-       "}\n",
-       "\n",
-       ".xr-var-data > table {\n",
-       "  float: right;\n",
-       "}\n",
-       "\n",
-       ".xr-var-name span,\n",
-       ".xr-var-data,\n",
-       ".xr-index-name div,\n",
-       ".xr-index-data,\n",
-       ".xr-attrs {\n",
-       "  padding-left: 25px !important;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs,\n",
-       ".xr-var-attrs,\n",
-       ".xr-var-data,\n",
-       ".xr-index-data {\n",
-       "  grid-column: 1 / -1;\n",
-       "}\n",
-       "\n",
-       "dl.xr-attrs {\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 125px auto;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt,\n",
-       ".xr-attrs dd {\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "  float: left;\n",
-       "  padding-right: 10px;\n",
-       "  width: auto;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt {\n",
-       "  font-weight: normal;\n",
-       "  grid-column: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt:hover span {\n",
-       "  display: inline-block;\n",
-       "  background: var(--xr-background-color);\n",
-       "  padding-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dd {\n",
-       "  grid-column: 2;\n",
-       "  white-space: pre-wrap;\n",
-       "  word-break: break-all;\n",
-       "}\n",
-       "\n",
-       ".xr-icon-database,\n",
-       ".xr-icon-file-text2,\n",
-       ".xr-no-icon {\n",
-       "  display: inline-block;\n",
-       "  vertical-align: middle;\n",
-       "  width: 1em;\n",
-       "  height: 1.5em !important;\n",
-       "  stroke-width: 0;\n",
-       "  stroke: currentColor;\n",
-       "  fill: currentColor;\n",
-       "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
-       "Dimensions:                                    (gmt: 251, year: 18, ssp: 3,\n",
-       "                                                region: 226)\n",
-       "Coordinates:\n",
-       "  * gmt                                        (gmt) float64 1.2 1.206 ... 3.5\n",
-       "  * year                                       (year) int64 2015 2020 ... 2100\n",
-       "  * ssp                                        (ssp) object &#x27;SSP1&#x27; &#x27;SSP2&#x27; &#x27;SSP3&#x27;\n",
-       "  * region                                     (region) object &#x27;AFG&#x27; ... &#x27;world&#x27;\n",
-       "Data variables:\n",
-       "    cdd|Exposure|Land area                     (gmt, year, ssp, region) float64 dask.array&lt;chunksize=(251, 18, 3, 226), meta=np.ndarray&gt;\n",
-       "    cdd|Exposure|Population                    (gmt, year, ssp, region) float64 dask.array&lt;chunksize=(251, 18, 3, 226), meta=np.ndarray&gt;\n",
-       "    cdd|Exposure|Population|%                  (gmt, year, ssp, region) float64 dask.array&lt;chunksize=(251, 18, 3, 226), meta=np.ndarray&gt;\n",
-       "    cdd|Hazard|Absolute|Land area weighted     (gmt, year, ssp, region) float64 dask.array&lt;chunksize=(251, 18, 3, 226), meta=np.ndarray&gt;\n",
-       "    cdd|Hazard|Absolute|Population weighted    (gmt, year, ssp, region) float64 dask.array&lt;chunksize=(251, 18, 3, 226), meta=np.ndarray&gt;\n",
-       "    cdd|Hazard|Risk score|Population weighted  (gmt, year, ssp, region) float64 dask.array&lt;chunksize=(251, 18, 3, 226), meta=np.ndarray&gt;</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-dfdc301e-a7a7-4a6d-8533-78ebec59ffec' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-dfdc301e-a7a7-4a6d-8533-78ebec59ffec' 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'>gmt</span>: 251</li><li><span class='xr-has-index'>year</span>: 18</li><li><span class='xr-has-index'>ssp</span>: 3</li><li><span class='xr-has-index'>region</span>: 226</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-d61959b6-04ad-44b9-a77f-edd7581d63eb' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d61959b6-04ad-44b9-a77f-edd7581d63eb' class='xr-section-summary' >Coordinates: <span>(4)</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'>gmt</span></div><div class='xr-var-dims'>(gmt)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.206 1.212 ... 3.48 3.49 3.5</div><input id='attrs-d5a2cd09-7e2a-4af7-ae8a-8f1dfc1fd3c9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d5a2cd09-7e2a-4af7-ae8a-8f1dfc1fd3c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4c64ddf-1b45-4803-a90c-fc8032f3cb96' class='xr-var-data-in' type='checkbox'><label for='data-f4c64ddf-1b45-4803-a90c-fc8032f3cb96' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1.2  , 1.206, 1.212, ..., 3.48 , 3.49 , 3.5  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>year</span></div><div class='xr-var-dims'>(year)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>2015 2020 2025 ... 2090 2095 2100</div><input id='attrs-158514ae-4e4b-4570-a7c3-f296f9990d4d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-158514ae-4e4b-4570-a7c3-f296f9990d4d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e6ec051-4093-40e4-8860-b49535653d31' class='xr-var-data-in' type='checkbox'><label for='data-4e6ec051-4093-40e4-8860-b49535653d31' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([2015, 2020, 2025, 2030, 2035, 2040, 2045, 2050, 2055, 2060, 2065, 2070,\n",
-       "       2075, 2080, 2085, 2090, 2095, 2100], dtype=int64)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>ssp</span></div><div class='xr-var-dims'>(ssp)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;SSP1&#x27; &#x27;SSP2&#x27; &#x27;SSP3&#x27;</div><input id='attrs-0d3f5761-eda7-4df0-8d71-f757511513d5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0d3f5761-eda7-4df0-8d71-f757511513d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-916862de-15c5-424f-a095-0ff450b99864' class='xr-var-data-in' type='checkbox'><label for='data-916862de-15c5-424f-a095-0ff450b99864' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;SSP1&#x27;, &#x27;SSP2&#x27;, &#x27;SSP3&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>region</span></div><div class='xr-var-dims'>(region)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;AFG&#x27; &#x27;AGO&#x27; &#x27;ALB&#x27; ... &#x27;ZWE&#x27; &#x27;world&#x27;</div><input id='attrs-7960c71d-e85e-4108-8562-e43f2a29b776' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7960c71d-e85e-4108-8562-e43f2a29b776' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f03bd3bb-5788-477d-aec8-a73cbab10ac2' class='xr-var-data-in' type='checkbox'><label for='data-f03bd3bb-5788-477d-aec8-a73cbab10ac2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;AFG&#x27;, &#x27;AGO&#x27;, &#x27;ALB&#x27;, ..., &#x27;ZMB&#x27;, &#x27;ZWE&#x27;, &#x27;world&#x27;], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b2bad547-e4b7-49f7-ba5e-7b93e7ae1e4f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b2bad547-e4b7-49f7-ba5e-7b93e7ae1e4f' class='xr-section-summary' >Data variables: <span>(6)</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>cdd|Exposure|Land area</span></div><div class='xr-var-dims'>(gmt, year, ssp, region)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(251, 18, 3, 226), meta=np.ndarray&gt;</div><input id='attrs-fd6d2d7c-1082-4be5-b1dd-b9140196b044' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fd6d2d7c-1082-4be5-b1dd-b9140196b044' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b0d2ae9-a321-4fbf-8ae3-844c1916ec9f' class='xr-var-data-in' type='checkbox'><label for='data-8b0d2ae9-a321-4fbf-8ae3-844c1916ec9f' 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>unit :</span></dt><dd>km2</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> 23.37 MiB </td>\n",
-       "                        <td> 23.37 MiB </td>\n",
-       "                    </tr>\n",
-       "                    \n",
-       "                    <tr>\n",
-       "                        <th> Shape </th>\n",
-       "                        <td> (251, 18, 3, 226) </td>\n",
-       "                        <td> (251, 18, 3, 226) </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\"> float64 numpy.ndarray </td>\n",
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-       "        </td>\n",
-       "    </tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cdd|Exposure|Population</span></div><div class='xr-var-dims'>(gmt, year, ssp, region)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(251, 18, 3, 226), meta=np.ndarray&gt;</div><input id='attrs-ac4ae772-742e-44f7-ad88-6d3d4d78af23' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac4ae772-742e-44f7-ad88-6d3d4d78af23' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-583350ca-bfb0-4c38-aa83-7c12d5b7f11d' class='xr-var-data-in' type='checkbox'><label for='data-583350ca-bfb0-4c38-aa83-7c12d5b7f11d' 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>unit :</span></dt><dd>people</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> 23.37 MiB </td>\n",
-       "                        <td> 23.37 MiB </td>\n",
-       "                    </tr>\n",
-       "                    \n",
-       "                    <tr>\n",
-       "                        <th> Shape </th>\n",
-       "                        <td> (251, 18, 3, 226) </td>\n",
-       "                        <td> (251, 18, 3, 226) </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\"> float64 numpy.ndarray </td>\n",
-       "                    </tr>\n",
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-       "            </table>\n",
-       "        </td>\n",
-       "        <td>\n",
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-       "        </td>\n",
-       "    </tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cdd|Exposure|Population|%</span></div><div class='xr-var-dims'>(gmt, year, ssp, region)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(251, 18, 3, 226), meta=np.ndarray&gt;</div><input id='attrs-53967ff3-50b2-4711-a1c3-3b401e8435c0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-53967ff3-50b2-4711-a1c3-3b401e8435c0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e8c13c55-d2db-4b72-beac-c7eeca59b1ef' class='xr-var-data-in' type='checkbox'><label for='data-e8c13c55-d2db-4b72-beac-c7eeca59b1ef' 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>unit :</span></dt><dd>%</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> 23.37 MiB </td>\n",
-       "                        <td> 23.37 MiB </td>\n",
-       "                    </tr>\n",
-       "                    \n",
-       "                    <tr>\n",
-       "                        <th> Shape </th>\n",
-       "                        <td> (251, 18, 3, 226) </td>\n",
-       "                        <td> (251, 18, 3, 226) </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\"> float64 numpy.ndarray </td>\n",
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-       "        </td>\n",
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-       "        </td>\n",
-       "    </tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cdd|Hazard|Absolute|Land area weighted</span></div><div class='xr-var-dims'>(gmt, year, ssp, region)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(251, 18, 3, 226), meta=np.ndarray&gt;</div><input id='attrs-0ef4d555-4b13-4a10-8835-8e3a24f21ba9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0ef4d555-4b13-4a10-8835-8e3a24f21ba9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-444ceba8-8d49-4cb0-909c-817d9dce47e2' class='xr-var-data-in' type='checkbox'><label for='data-444ceba8-8d49-4cb0-909c-817d9dce47e2' 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>unit :</span></dt><dd>days/yr</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> 23.37 MiB </td>\n",
-       "                        <td> 23.37 MiB </td>\n",
-       "                    </tr>\n",
-       "                    \n",
-       "                    <tr>\n",
-       "                        <th> Shape </th>\n",
-       "                        <td> (251, 18, 3, 226) </td>\n",
-       "                        <td> (251, 18, 3, 226) </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\"> float64 numpy.ndarray </td>\n",
-       "                    </tr>\n",
-       "                </tbody>\n",
-       "            </table>\n",
-       "        </td>\n",
-       "        <td>\n",
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-       "</svg>\n",
-       "        </td>\n",
-       "    </tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cdd|Hazard|Absolute|Population weighted</span></div><div class='xr-var-dims'>(gmt, year, ssp, region)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(251, 18, 3, 226), meta=np.ndarray&gt;</div><input id='attrs-bc1eb183-6fb1-4e58-ad2b-6a13d68f0ed3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bc1eb183-6fb1-4e58-ad2b-6a13d68f0ed3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2b7d7691-e6e7-4fb7-8254-b255a957d4f3' class='xr-var-data-in' type='checkbox'><label for='data-2b7d7691-e6e7-4fb7-8254-b255a957d4f3' 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>unit :</span></dt><dd>days/yr</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> 23.37 MiB </td>\n",
-       "                        <td> 23.37 MiB </td>\n",
-       "                    </tr>\n",
-       "                    \n",
-       "                    <tr>\n",
-       "                        <th> Shape </th>\n",
-       "                        <td> (251, 18, 3, 226) </td>\n",
-       "                        <td> (251, 18, 3, 226) </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\"> float64 numpy.ndarray </td>\n",
-       "                    </tr>\n",
-       "                </tbody>\n",
-       "            </table>\n",
-       "        </td>\n",
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-       "  <text x=\"190.789159\" y=\"57.075881\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,190.789159,57.075881)\">18</text>\n",
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-       "        </td>\n",
-       "    </tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cdd|Hazard|Risk score|Population weighted</span></div><div class='xr-var-dims'>(gmt, year, ssp, region)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(251, 18, 3, 226), meta=np.ndarray&gt;</div><input id='attrs-81bd52ce-d9c4-47fc-b038-d6d84e80ab79' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-81bd52ce-d9c4-47fc-b038-d6d84e80ab79' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-10d7a763-077f-4b7f-ba39-3a41b76a082e' class='xr-var-data-in' type='checkbox'><label for='data-10d7a763-077f-4b7f-ba39-3a41b76a082e' 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>unit :</span></dt><dd>risk score</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> 23.37 MiB </td>\n",
-       "                        <td> 23.37 MiB </td>\n",
-       "                    </tr>\n",
-       "                    \n",
-       "                    <tr>\n",
-       "                        <th> Shape </th>\n",
-       "                        <td> (251, 18, 3, 226) </td>\n",
-       "                        <td> (251, 18, 3, 226) </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\"> float64 numpy.ndarray </td>\n",
-       "                    </tr>\n",
-       "                </tbody>\n",
-       "            </table>\n",
-       "        </td>\n",
-       "        <td>\n",
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-       "\n",
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-       "  <text x=\"190.789159\" y=\"57.075881\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,190.789159,57.075881)\">18</text>\n",
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-       "        </td>\n",
-       "    </tr>\n",
-       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-7d453ec6-3ff4-44d0-8823-9a4c2e429641' class='xr-section-summary-in' type='checkbox'  ><label for='section-7d453ec6-3ff4-44d0-8823-9a4c2e429641' class='xr-section-summary' >Indexes: <span>(4)</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>gmt</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ec1f1e6e-bb70-4eac-9069-3f52ad3699f2' class='xr-index-data-in' type='checkbox'/><label for='index-ec1f1e6e-bb70-4eac-9069-3f52ad3699f2' 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(Float64Index([  1.2, 1.206, 1.212, 1.218, 1.224,  1.23, 1.236, 1.242, 1.248,\n",
-       "              1.254,\n",
-       "              ...\n",
-       "               3.41,  3.42,  3.43,  3.44,  3.45,  3.46,  3.47,  3.48,  3.49,\n",
-       "                3.5],\n",
-       "             dtype=&#x27;float64&#x27;, name=&#x27;gmt&#x27;, length=251))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2125adf1-dc3e-4a94-ae58-aa8414e689c6' class='xr-index-data-in' type='checkbox'/><label for='index-2125adf1-dc3e-4a94-ae58-aa8414e689c6' 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(Int64Index([2015, 2020, 2025, 2030, 2035, 2040, 2045, 2050, 2055, 2060, 2065,\n",
-       "            2070, 2075, 2080, 2085, 2090, 2095, 2100],\n",
-       "           dtype=&#x27;int64&#x27;, name=&#x27;year&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>ssp</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-46ea1b6b-2b40-435e-b233-ea4ede08b570' class='xr-index-data-in' type='checkbox'/><label for='index-46ea1b6b-2b40-435e-b233-ea4ede08b570' 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([&#x27;SSP1&#x27;, &#x27;SSP2&#x27;, &#x27;SSP3&#x27;], dtype=&#x27;object&#x27;, name=&#x27;ssp&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>region</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e3bc0a4a-af76-4f61-81dc-0439f67547d0' class='xr-index-data-in' type='checkbox'/><label for='index-e3bc0a4a-af76-4f61-81dc-0439f67547d0' 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([&#x27;AFG&#x27;, &#x27;AGO&#x27;, &#x27;ALB&#x27;, &#x27;AND&#x27;, &#x27;ARE&#x27;, &#x27;ARG&#x27;, &#x27;ARM&#x27;, &#x27;ASM&#x27;, &#x27;ATF&#x27;, &#x27;ATG&#x27;,\n",
-       "       ...\n",
-       "       &#x27;VGB&#x27;, &#x27;VIR&#x27;, &#x27;VNM&#x27;, &#x27;VUT&#x27;, &#x27;WSM&#x27;, &#x27;YEM&#x27;, &#x27;ZAF&#x27;, &#x27;ZMB&#x27;, &#x27;ZWE&#x27;, &#x27;world&#x27;],\n",
-       "      dtype=&#x27;object&#x27;, name=&#x27;region&#x27;, length=226))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6ff95a5b-6386-4ac8-a9f1-2d40d0cfc4f6' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6ff95a5b-6386-4ac8-a9f1-2d40d0cfc4f6' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
-      ],
-      "text/plain": [
-       "<xarray.Dataset>\n",
-       "Dimensions:                                    (gmt: 251, year: 18, ssp: 3,\n",
-       "                                                region: 226)\n",
-       "Coordinates:\n",
-       "  * gmt                                        (gmt) float64 1.2 1.206 ... 3.5\n",
-       "  * year                                       (year) int64 2015 2020 ... 2100\n",
-       "  * ssp                                        (ssp) object 'SSP1' 'SSP2' 'SSP3'\n",
-       "  * region                                     (region) object 'AFG' ... 'world'\n",
-       "Data variables:\n",
-       "    cdd|Exposure|Land area                     (gmt, year, ssp, region) float64 dask.array<chunksize=(251, 18, 3, 226), meta=np.ndarray>\n",
-       "    cdd|Exposure|Population                    (gmt, year, ssp, region) float64 dask.array<chunksize=(251, 18, 3, 226), meta=np.ndarray>\n",
-       "    cdd|Exposure|Population|%                  (gmt, year, ssp, region) float64 dask.array<chunksize=(251, 18, 3, 226), meta=np.ndarray>\n",
-       "    cdd|Hazard|Absolute|Land area weighted     (gmt, year, ssp, region) float64 dask.array<chunksize=(251, 18, 3, 226), meta=np.ndarray>\n",
-       "    cdd|Hazard|Absolute|Population weighted    (gmt, year, ssp, region) float64 dask.array<chunksize=(251, 18, 3, 226), meta=np.ndarray>\n",
-       "    cdd|Hazard|Risk score|Population weighted  (gmt, year, ssp, region) float64 dask.array<chunksize=(251, 18, 3, 226), meta=np.ndarray>"
-      ]
-     },
-     "execution_count": 22,
-     "metadata": {},
-     "output_type": "execute_result"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Test 1 scenario, multiple indicators\n",
+      "cdd\n"
+     ]
+    },
+    {
+     "ename": "OSError",
+     "evalue": "no files to open",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mOSError\u001b[0m                                   Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[8], line 30\u001b[0m\n\u001b[1;32m     26\u001b[0m         \u001b[38;5;28mprint\u001b[39m(short)\n\u001b[1;32m     27\u001b[0m         files \u001b[38;5;241m=\u001b[39m glob\u001b[38;5;241m.\u001b[39mglob(\n\u001b[1;32m     28\u001b[0m             os\u001b[38;5;241m.\u001b[39mpath\u001b[38;5;241m.\u001b[39mjoin(impact_data_dir, ind, \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m*\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mshort\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m_\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mssp\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m*\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mftype\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.nc4\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m     29\u001b[0m         )\n\u001b[0;32m---> 30\u001b[0m         mapdata[short] \u001b[38;5;241m=\u001b[39m \u001b[43mxr\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen_mfdataset\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m     31\u001b[0m \u001b[43m            \u001b[49m\u001b[43mfiles\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpreprocess\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mremove_ssp_from_ds\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcombine\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mnested\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconcat_dim\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mgmt\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\n\u001b[1;32m     32\u001b[0m \u001b[43m        \u001b[49m\u001b[43m)\u001b[49m[short]\n\u001b[1;32m     34\u001b[0m mapdata \u001b[38;5;241m=\u001b[39m tidy_mapdata(mapdata)\n",
+      "File \u001b[0;32m~/py311/lib/python3.10/site-packages/xarray/backends/api.py:990\u001b[0m, in \u001b[0;36mopen_mfdataset\u001b[0;34m(paths, chunks, concat_dim, compat, preprocess, engine, data_vars, coords, combine, parallel, join, attrs_file, combine_attrs, **kwargs)\u001b[0m\n\u001b[1;32m    987\u001b[0m paths \u001b[38;5;241m=\u001b[39m _find_absolute_paths(paths, engine\u001b[38;5;241m=\u001b[39mengine, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m    989\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m paths:\n\u001b[0;32m--> 990\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mOSError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mno files to open\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m    992\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m combine \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnested\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m    993\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(concat_dim, (\u001b[38;5;28mstr\u001b[39m, DataArray)) \u001b[38;5;129;01mor\u001b[39;00m concat_dim \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n",
+      "\u001b[0;31mOSError\u001b[0m: no files to open"
+     ]
     }
    ],
+   "source": [
+    "# Doesn't work -0\n",
+    "# AttributeError: 'DataArray' object has no attribute 'rename_vars'\n",
+    "# lines 230-233 in map_transform_gmt\n",
+    "\n",
+    "gmt_name = \"gmt\"\n",
+    "print(\"Test 1 scenario, multiple indicators\")\n",
+    "start = time.time()\n",
+    "ssp = \"ssp2\"\n",
+    "mapdata = xr.Dataset()\n",
+    "indicators = [\n",
+    "    \"cdd\",\n",
+    "    \"precip\",\n",
+    "    \"dri\",\n",
+    "    # \"dri_qtot\",\n",
+    "    # \"ia_var\",\n",
+    "    # \"ia_var_qtot\",\n",
+    "    \"sdd_18p3\",\n",
+    "    \"sdd_24p0\",\n",
+    "    \"seas\",\n",
+    "    \"wsi\",\n",
+    "]  #'heatwave']\n",
+    "\n",
+    "for ind in indicators:\n",
+    "    for var in params[\"indicators\"][ind]:\n",
+    "        short = params[\"indicators\"][ind][var][\"short_name\"]\n",
+    "        print(short)\n",
+    "        files = glob.glob(\n",
+    "            os.path.join(impact_data_dir, ind, f\"*{short}_{ssp}*{ftype}.nc4\")\n",
+    "        )\n",
+    "        mapdata[short] = xr.open_mfdataset(\n",
+    "            files, preprocess=remove_ssp_from_ds, combine=\"nested\", concat_dim=\"gmt\"\n",
+    "        )[short]\n",
+    "\n",
+    "mapdata = tidy_mapdata(mapdata)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cc24e437",
+   "metadata": {},
+   "source": [
+    "### Run transformation (12 impact indicators) (faster with dask=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bd26a126",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "map_out_MI = map_transform_gmt_wrapper(\n",
+    "    ssps_imp.filter(IMP_marker=\"CurPol\"),\n",
+    "    mapdata,\n",
+    "    years,\n",
+    "    use_dask=False,\n",
+    "    gmt_name=\"gmt\",\n",
+    ")\n",
+    "\n",
+    "comp = dict(zlib=True, complevel=5)\n",
+    "encoding = {var: comp for var in map_out_MI.data_vars}\n",
+    "filename = f\"{output_folder_maps}scenario_maps_multiindicator_{ftype}_test_notebook.nc\"\n",
+    "# map_out_MI.to_netcdf(filename, encoding=encoding)\n",
+    "\n",
+    "print(\"FINISHED 1 scenario, multiple indicators\")\n",
+    "print(f\"{time.time()-start}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8c7c007c",
+   "metadata": {},
+   "source": [
+    "### Data is now transformed to 5 year interval starting 2015"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "169f89a5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "map_out_MI"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b4ff7baa",
+   "metadata": {},
+   "source": [
+    "## Plot dashboard (takes some minutes)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b407883b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "filename = \"test_map_notebook.html\"\n",
+    "plot_maps_dashboard(\n",
+    "    map_out_MI,\n",
+    "    filename=filename,\n",
+    "    year=2063,\n",
+    "    cmap=\"magma_r\",\n",
+    "    shared_axes=True,\n",
+    "    clim=None,\n",
+    ")\n",
+    "os.startfile(filename)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "53155084",
+   "metadata": {},
+   "source": [
+    "## Process corresponding table data, aggregated by country"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "534c8807",
+   "metadata": {},
+   "source": [
+    "### Import the climate impacts database files\n",
+    "Here is an example for sdii - standard precipitation index, and multiple variables, e.g.  \n",
+    "Exposure of land area  \n",
+    "Exposure of population  \n",
+    "Hazard value  \n",
+    "...  \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a9ee85cf",
+   "metadata": {},
+   "outputs": [],
    "source": [
     "filesall = glob.glob(fname_input_climate)\n",
     "files = filesall  # [:6]\n",
@@ -4201,18 +1150,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": null,
    "id": "d1e3f825",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "# of variables = 6\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "varis = list(ds.data_vars.keys())[:lvaris]\n",
     "dsi = ds[varis]\n",
@@ -4232,7 +1173,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": null,
    "id": "e3551368",
    "metadata": {},
    "outputs": [],
@@ -4260,7 +1201,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": null,
    "id": "7f799e2a",
    "metadata": {},
    "outputs": [],
@@ -4279,7 +1220,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": null,
    "id": "ebe93e79-94ce-4127-9ef6-5aa1f789766f",
    "metadata": {},
    "outputs": [],
@@ -4303,37 +1244,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": null,
    "id": "d4d94aa4",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[                                        ] | 0% Completed | 115.69 ms"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "C:\\Users\\byers\\AppData\\Roaming\\Python\\Python310\\site-packages\\dask\\dataframe\\utils.py:312: FutureWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.\n",
-      "  return pd.Series([], dtype=dtype, name=name, index=index)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[########################################] | 100% Completed | 19.15 s\n",
-      " Done:  19.877137184143066\n",
-      " Saved: COUNTRIES yrs=10\n",
-      "  19.877137184143066\n",
-      "6 variables, 9 scenarios\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "start = time.time()\n",
     "year_res = 10\n",
@@ -4380,7 +1294,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": null,
    "id": "d1cc8871",
    "metadata": {},
    "outputs": [],
@@ -4390,57 +1304,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": null,
    "id": "4d08042a",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['RIME|cdd|Exposure|Land area',\n",
-       " 'RIME|cdd|Exposure|Population',\n",
-       " 'RIME|cdd|Exposure|Population|%',\n",
-       " 'RIME|cdd|Hazard|Absolute|Land area weighted',\n",
-       " 'RIME|cdd|Hazard|Absolute|Population weighted',\n",
-       " 'RIME|cdd|Hazard|Risk score|Population weighted']"
-      ]
-     },
-     "execution_count": 29,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "expandeddGMT.variable"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": null,
    "id": "0457fa1e-09db-4557-83e5-7f4e13064d84",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<Axes: title={'center': 'region: GBR - variable: RIME|cdd|Exposure|Population|%'}, xlabel='Year', ylabel='%'>"
-      ]
-     },
-     "execution_count": 30,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "# model = \"IMAG*\"\n",
     "scenario = [\n",
@@ -4462,57 +1339,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": null,
    "id": "614d21e6-345c-43d5-9e9c-06606ce3a3d2",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<Axes: title={'center': 'region: PAK - variable: RIME|cdd|Exposure|Population|%'}, xlabel='Year', ylabel='%'>"
-      ]
-     },
-     "execution_count": 31,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "expandeddGMT.filter(variable=variable, scenario=scenario, region=\"PAK\").plot()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": null,
    "id": "def35b50-a552-4a79-b481-08bceeca1918",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['RIME|cdd|Exposure|Land area',\n",
-       " 'RIME|cdd|Exposure|Population',\n",
-       " 'RIME|cdd|Exposure|Population|%',\n",
-       " 'RIME|cdd|Hazard|Absolute|Land area weighted',\n",
-       " 'RIME|cdd|Hazard|Absolute|Population weighted',\n",
-       " 'RIME|cdd|Hazard|Risk score|Population weighted']"
-      ]
-     },
-     "execution_count": 32,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "expandeddGMT.variable"
    ]
@@ -4594,7 +1434,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.8"
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,
diff --git a/setup.cfg b/setup.cfg
deleted file mode 100644
index a72c85c..0000000
--- a/setup.cfg
+++ /dev/null
@@ -1,48 +0,0 @@
-[metadata]
-name = rime
-author = Edward Byers, Mia Werning
-author_email = byers@iiasa.ac.at
-description = Rapid Impact Model Emulator
-long_description_content_type = text/markdown
-long_description = file:README.md
-url = https://www.iiasa.ac.at
-license = GNU CPL v3
-classifiers =
-    Development Status :: 2 - Pre-Alpha
-    Intended Audience :: Science/Research
-    Topic :: Scientific/Engineering
-    License :: OSI Approved :: GNU CPL v3
-    Natural Language :: English
-    Programming Language :: Python :: 3
-	
-[options]
-packages = rime
-include_package_data = True
-python_requires = >=3.10, <3.12
-
-# To check this, pip install pipreqs, then run pipreqs . in the rime directory
-install_requires =
-	alive-progress>=3.1.5
-	dask>2022.7.0
-	holoviews~=1.17.1
-	hvplot~=0.9.0
-	matplotlib~=3.5.2
-	numpy~=1.23.5
-	pandas>1.5.2
-	pyam_iamc>1.7
-	PyYAML~=6.0
-	rich~=13.6.0
-	scipy>1.9.3
-	seaborn~=0.13.0
-	xarray~=2022.11.0
-	
-setup_requires =
-    setuptools >= 41
-    setuptools_scm
-
-[options.extras_require]
-tests =
-    pytest
-doc =
-    sphinx
-    sphinx_rtd_theme
\ No newline at end of file
diff --git a/setup.py b/setup.py
deleted file mode 100644
index d5d43d7..0000000
--- a/setup.py
+++ /dev/null
@@ -1,3 +0,0 @@
-from setuptools import setup
-
-setup(use_scm_version=True)