diff --git a/_sources/notebooks/getting_started.ipynb.txt b/_sources/notebooks/getting_started.ipynb.txt
index 469a3a1..6ec3d79 100644
--- a/_sources/notebooks/getting_started.ipynb.txt
+++ b/_sources/notebooks/getting_started.ipynb.txt
@@ -96,7 +96,7 @@
},
{
"cell_type": "code",
- "execution_count": 1,
+ "execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2023-10-03T18:40:37.823425184Z",
@@ -111,660 +111,14 @@
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2023-10-03T18:40:54.073256475Z",
"start_time": "2023-10-03T18:40:49.561354059Z"
}
},
- "outputs": [
- {
- "data": {
- "application/javascript": [
- "(function(root) {\n",
- " function now() {\n",
- " return new Date();\n",
- " }\n",
- "\n",
- " var force = true;\n",
- " var py_version = '3.3.2'.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/1.3.6/dist/bundled/floatpanel/jspanel4@4.12.0/dist/jspanel.js', 'https://cdn.holoviz.org/panel/1.3.6/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal.js', 'https://cdn.holoviz.org/panel/1.3.6/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip.js', 'https://cdn.holoviz.org/panel/1.3.6/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint.js', 'https://cdn.holoviz.org/panel/1.3.6/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout.js', 'https://cdn.holoviz.org/panel/1.3.6/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu.js', 'https://cdn.holoviz.org/panel/1.3.6/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/1.3.6/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/1.3.6/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-3.3.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.3.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.3.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.3.2.min.js\", \"https://cdn.holoviz.org/panel/1.3.6/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",
- " },\n",
- "function(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));"
- ],
- "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 = '3.3.2'.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/1.3.6/dist/bundled/floatpanel/jspanel4@4.12.0/dist/jspanel.js', 'https://cdn.holoviz.org/panel/1.3.6/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal.js', 'https://cdn.holoviz.org/panel/1.3.6/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip.js', 'https://cdn.holoviz.org/panel/1.3.6/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint.js', 'https://cdn.holoviz.org/panel/1.3.6/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout.js', 'https://cdn.holoviz.org/panel/1.3.6/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu.js', 'https://cdn.holoviz.org/panel/1.3.6/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/1.3.6/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/1.3.6/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; 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+ "outputs": [],
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@@ -1801,37 +345,9 @@
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- " warnings.warn(\n",
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- " warnings.warn(\n",
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- "Spatial operations: processing polygon 042102 with era5_reanalysis_single_levels: : 0it [00:00, ?it/s]/home/slanglois/mambaforge/envs/xdatasets/lib/python3.11/site-packages/xarray/core/utils.py:494: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.\n",
- " warnings.warn(\n",
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- " warnings.warn(\n",
- "/home/slanglois/mambaforge/envs/xdatasets/lib/python3.11/site-packages/xarray/core/utils.py:494: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.\n",
- " warnings.warn(\n",
- "Spatial operations: processing polygon 042103 with era5_reanalysis_single_levels: : 1it [00:00, 4.63it/s]/home/slanglois/mambaforge/envs/xdatasets/lib/python3.11/site-packages/xarray/core/utils.py:494: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.\n",
- " warnings.warn(\n",
- "/home/slanglois/mambaforge/envs/xdatasets/lib/python3.11/site-packages/xarray/core/utils.py:494: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.\n",
- " warnings.warn(\n",
- "/home/slanglois/mambaforge/envs/xdatasets/lib/python3.11/site-packages/xarray/core/utils.py:494: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.\n",
- " warnings.warn(\n",
- "Spatial operations: processing polygon 042103 with era5_reanalysis_single_levels: : 2it [00:00, 4.69it/s]\n",
- "Temporal operations: processing tp with era5_reanalysis_single_levels: 100%|██████████████████████████████████████████████| 2/2 [00:07<00:00, 3.69s/it]\n",
- "Spatial operations: processing polygon 042102 with era5_land_reanalysis: : 0it [00:00, ?it/s]/home/slanglois/mambaforge/envs/xdatasets/lib/python3.11/site-packages/xarray/core/utils.py:494: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.\n",
- " warnings.warn(\n",
- "/home/slanglois/mambaforge/envs/xdatasets/lib/python3.11/site-packages/xarray/core/utils.py:494: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.\n",
- " warnings.warn(\n",
- "/home/slanglois/mambaforge/envs/xdatasets/lib/python3.11/site-packages/xarray/core/utils.py:494: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.\n",
- " warnings.warn(\n",
- "Spatial operations: processing polygon 042103 with era5_land_reanalysis: : 1it [00:00, 4.24it/s]/home/slanglois/mambaforge/envs/xdatasets/lib/python3.11/site-packages/xarray/core/utils.py:494: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.\n",
- " warnings.warn(\n",
- "/home/slanglois/mambaforge/envs/xdatasets/lib/python3.11/site-packages/xarray/core/utils.py:494: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.\n",
- " warnings.warn(\n",
- "/home/slanglois/mambaforge/envs/xdatasets/lib/python3.11/site-packages/xarray/core/utils.py:494: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.\n",
- " warnings.warn(\n",
- "Spatial operations: processing polygon 042103 with era5_land_reanalysis: : 2it [00:00, 4.30it/s]\n",
- "Temporal operations: processing tp with era5_land_reanalysis: 100%|███████████████████████████████████████████████████████| 2/2 [00:07<00:00, 3.79s/it]\n"
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Coordinates: (5)
Data variables: (3)
t2m_nanmax
(spatial_agg, timestep, Station, time, source)
float64
272.8 nan 275.1 ... nan 278.3 nan
GRIB_NV : 0 GRIB_Nx : 1440 GRIB_Ny : 721 GRIB_cfName : unknown GRIB_cfVarName : t2m GRIB_dataType : an GRIB_gridDefinitionDescription : Latitude/Longitude Grid GRIB_gridType : regular_ll GRIB_iDirectionIncrementInDegrees : 0.25 GRIB_iScansNegatively : 0 GRIB_jDirectionIncrementInDegrees : 0.25 GRIB_jPointsAreConsecutive : 0 GRIB_jScansPositively : 0 GRIB_latitudeOfFirstGridPointInDegrees : 90.0 GRIB_latitudeOfLastGridPointInDegrees : -90.0 GRIB_longitudeOfFirstGridPointInDegrees : -180.0 GRIB_longitudeOfLastGridPointInDegrees : 179.75 GRIB_missingValue : 3.4028234663852886e+38 GRIB_name : 2 metre temperature GRIB_numberOfPoints : 1038240 GRIB_paramId : 167 GRIB_shortName : 2t GRIB_stepType : instant GRIB_stepUnits : 1 GRIB_totalNumber : 0 GRIB_typeOfLevel : surface GRIB_units : K long_name : 2 metre temperature standard_name : unknown units : K array([[[[[272.82241918, nan],\n",
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(spatial_agg, timestep, Station, time, source)
float64
268.7 nan 273.1 ... nan 274.1 nan
GRIB_NV : 0 GRIB_Nx : 1440 GRIB_Ny : 721 GRIB_cfName : unknown GRIB_cfVarName : t2m GRIB_dataType : an GRIB_gridDefinitionDescription : Latitude/Longitude Grid GRIB_gridType : regular_ll GRIB_iDirectionIncrementInDegrees : 0.25 GRIB_iScansNegatively : 0 GRIB_jDirectionIncrementInDegrees : 0.25 GRIB_jPointsAreConsecutive : 0 GRIB_jScansPositively : 0 GRIB_latitudeOfFirstGridPointInDegrees : 90.0 GRIB_latitudeOfLastGridPointInDegrees : -90.0 GRIB_longitudeOfFirstGridPointInDegrees : -180.0 GRIB_longitudeOfLastGridPointInDegrees : 179.75 GRIB_missingValue : 3.4028234663852886e+38 GRIB_name : 2 metre temperature GRIB_numberOfPoints : 1038240 GRIB_paramId : 167 GRIB_shortName : 2t GRIB_stepType : instant GRIB_stepUnits : 1 GRIB_totalNumber : 0 GRIB_typeOfLevel : surface GRIB_units : K long_name : 2 metre temperature standard_name : unknown units : K array([[[[[268.74626406, nan],\n",
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- " [274.1184743 , nan]]]]]) tp_nansum
(spatial_agg, timestep, Station, time, source)
float64
0.0005841 nan ... 0.0003093 nan
long_name : Total precipitation units : m array([[[[[5.84104060e-04, nan],\n",
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- " [4.06324203e-05, nan],\n",
- " [1.03919736e-05, nan],\n",
- " [3.09322019e-04, nan]]]]]) Indexes: (5)
PandasIndex
PandasIndex(Index(['polygon'], dtype='object', name='spatial_agg')) PandasIndex
PandasIndex(Index(['D'], dtype='object', name='timestep')) PandasIndex
PandasIndex(Index(['042102', '042103'], dtype='object', name='Station')) PandasIndex
PandasIndex(DatetimeIndex(['1950-01-01', '1950-01-02', '1950-01-03', '1950-01-04',\n",
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- " '2023-12-10', '2023-12-11', '2023-12-12', '2023-12-13',\n",
- " '2023-12-14', '2023-12-15'],\n",
- " dtype='datetime64[ns]', name='time', length=27012, freq='D')) PandasIndex
PandasIndex(Index(['era5_land_reanalysis', 'era5_reanalysis_single_levels'], dtype='object', name='source')) Attributes: (30)
GRIB_NV : 0 GRIB_Nx : 1440 GRIB_Ny : 721 GRIB_cfName : unknown GRIB_cfVarName : t2m GRIB_dataType : an GRIB_gridDefinitionDescription : Latitude/Longitude Grid GRIB_gridType : regular_ll GRIB_iDirectionIncrementInDegrees : 0.25 GRIB_iScansNegatively : 0 GRIB_jDirectionIncrementInDegrees : 0.25 GRIB_jPointsAreConsecutive : 0 GRIB_jScansPositively : 0 GRIB_latitudeOfFirstGridPointInDegrees : 90.0 GRIB_latitudeOfLastGridPointInDegrees : -90.0 GRIB_longitudeOfFirstGridPointInDegrees : -180.0 GRIB_longitudeOfLastGridPointInDegrees : 179.75 GRIB_missingValue : 3.4028234663852886e+38 GRIB_name : 2 metre temperature GRIB_numberOfPoints : 1038240 GRIB_paramId : 167 GRIB_shortName : 2t GRIB_stepType : instant GRIB_stepUnits : 1 GRIB_totalNumber : 0 GRIB_typeOfLevel : surface GRIB_units : K long_name : 2 metre temperature standard_name : unknown units : K "
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@@ -3845,7 +567,7 @@
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@@ -3868,474 +590,9 @@
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Coordinates: (4)
latitude
(latitude)
float64
46.9 46.8 46.7 ... 46.3 46.2 46.1
long_name : latitude standard_name : latitude stored_direction : decreasing units : degrees_north array([46.9, 46.8, 46.7, 46.6, 46.5, 46.4, 46.3, 46.2, 46.1]) longitude
(longitude)
float64
-78.9 -78.8 -78.7 ... -78.0 -77.9
long_name : longitude standard_name : longitude units : degrees_east array([-78.9, -78.8, -78.7, -78.6, -78.5, -78.4, -78.3, -78.2, -78.1, -78. ,\n",
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(time)
datetime64[ns]
1959-01-01 ... 1970-12-31T23:00:00
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array(['era5_land_reanalysis'], dtype='<U20') Data variables: (1)
tp
(time, latitude, longitude)
float32
1.08e-07 1.08e-07 ... 0.0 0.0
GRIB_NV : 0 GRIB_Nx : 1171 GRIB_Ny : 701 GRIB_cfName : unknown GRIB_cfVarName : tp GRIB_dataType : fc GRIB_gridDefinitionDescription : Latitude/Longitude Grid GRIB_gridType : regular_ll GRIB_iDirectionIncrementInDegrees : 0.1 GRIB_iScansNegatively : 0 GRIB_jDirectionIncrementInDegrees : 0.1 GRIB_jPointsAreConsecutive : 0 GRIB_jScansPositively : 0 GRIB_latitudeOfFirstGridPointInDegrees : 85.0 GRIB_latitudeOfLastGridPointInDegrees : 15.0 GRIB_longitudeOfFirstGridPointInDegrees : -167.0 GRIB_longitudeOfLastGridPointInDegrees : -50.0 GRIB_missingValue : 9999 GRIB_name : Total precipitation GRIB_numberOfPoints : 820871 GRIB_paramId : 228 GRIB_shortName : tp GRIB_stepType : accum GRIB_stepUnits : 1 GRIB_totalNumber : 0 GRIB_typeOfLevel : surface GRIB_units : m long_name : Total precipitation standard_name : unknown units : m array([[[1.0803342e-07, 1.0803342e-07, 8.9406967e-08, ...,\n",
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PandasIndex
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- " dtype='float64', name='latitude')) PandasIndex
PandasIndex(Index([-78.90000000000501, -78.80000000000501, -78.70000000000502,\n",
- " -78.60000000000502, -78.50000000000503, -78.40000000000504,\n",
- " -78.30000000000504, -78.20000000000505, -78.10000000000505,\n",
- " -78.00000000000506, -77.90000000000506],\n",
- " dtype='float64', name='longitude')) PandasIndex
PandasIndex(DatetimeIndex(['1959-01-01 00:00:00', '1959-01-01 01:00:00',\n",
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PandasIndex(Index(['era5_land_reanalysis'], dtype='object', name='source')) Attributes: (4)
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@@ -4514,1343 +664,11 @@
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- " streamflow (id, time, variable, spatial_agg, timestep, time_agg, source) float32 dask.array<chunksize=(1, 60631, 1, 1, 1, 1, 1), meta=np.ndarray> Dimensions: id : 744variable : 2spatial_agg : 2timestep : 1time_agg : 1source : 1time : 60631
Coordinates: (15)
drainage_area
(id)
float32
dask.array<chunksize=(744,), meta=np.ndarray>
long_name : drainage_area units : km2 \n",
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end_date
(variable, id, spatial_agg, timestep, time_agg, source)
datetime64[ns]
dask.array<chunksize=(2, 744, 2, 1, 1, 1), meta=np.ndarray>
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- " 1 \n",
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id
(id)
object
'010101' '010801' ... '120201'
array(['010101', '010801', '010802', ..., '104803', '104804', '120201'],\n",
- " dtype=object) latitude
(id)
float32
dask.array<chunksize=(744,), meta=np.ndarray>
long_name : latitude standard_name : latitude units : decimal_degrees \n",
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longitude
(id)
float32
dask.array<chunksize=(744,), meta=np.ndarray>
long_name : longitude standard_name : longitude units : decimal_degrees \n",
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name
(id)
object
dask.array<chunksize=(744,), meta=np.ndarray>
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- " \n",
- " \n",
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- "
province
(id)
object
dask.array<chunksize=(744,), meta=np.ndarray>
\n",
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regulated
(id)
object
dask.array<chunksize=(744,), meta=np.ndarray>
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source
(source)
object
'Ministère de l’Environnement, d...
array(['Ministère de l’Environnement, de la Lutte contre les changements climatiques, de la Faune et des Parcs'],\n",
- " dtype=object) spatial_agg
(spatial_agg)
object
'point' 'watershed'
array(['point', 'watershed'], dtype=object) start_date
(variable, id, spatial_agg, timestep, time_agg, source)
datetime64[ns]
dask.array<chunksize=(2, 744, 2, 1, 1, 1), meta=np.ndarray>
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- " Bytes \n",
- " 23.25 kiB \n",
- " 23.25 kiB \n",
- " \n",
- " \n",
- " \n",
- " Shape \n",
- " (2, 744, 2, 1, 1, 1) \n",
- " (2, 744, 2, 1, 1, 1) \n",
- " \n",
- " \n",
- " Dask graph \n",
- " 1 chunks in 2 graph layers \n",
- " \n",
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- " \n",
- " 2 \n",
- " 744 \n",
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- " \n",
- " 1 \n",
- " 1 \n",
- " 1 \n",
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- " \n",
- "
time
(time)
datetime64[ns]
1860-01-01 ... 2025-12-31
array(['1860-01-01T00:00:00.000000000', '1860-01-02T00:00:00.000000000',\n",
- " '1860-01-03T00:00:00.000000000', ..., '2025-12-29T00:00:00.000000000',\n",
- " '2025-12-30T00:00:00.000000000', '2025-12-31T00:00:00.000000000'],\n",
- " dtype='datetime64[ns]') time_agg
(time_agg)
object
'mean'
array(['mean'], dtype=object) timestep
(timestep)
object
'D'
array(['D'], dtype=object) variable
(variable)
object
'level' 'streamflow'
array(['level', 'streamflow'], dtype=object) Data variables: (2)
level
(id, time, variable, spatial_agg, timestep, time_agg, source)
float32
dask.array<chunksize=(1, 60631, 1, 1, 1, 1, 1), meta=np.ndarray>
\n",
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- " Bytes \n",
- " 688.32 MiB \n",
- " 236.84 kiB \n",
- " \n",
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- " Shape \n",
- " (744, 60631, 2, 2, 1, 1, 1) \n",
- " (1, 60631, 1, 1, 1, 1, 1) \n",
- " \n",
- " \n",
- " Dask graph \n",
- " 2976 chunks in 2 graph layers \n",
- " \n",
- " \n",
- " Data type \n",
- " float32 numpy.ndarray \n",
- " \n",
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- "
\n",
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- " 60631 \n",
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- "\n",
- " \n",
- " 1 \n",
- " 1 \n",
- " 1 \n",
- " \n",
- " \n",
- " \n",
- "
streamflow
(id, time, variable, spatial_agg, timestep, time_agg, source)
float32
dask.array<chunksize=(1, 60631, 1, 1, 1, 1, 1), meta=np.ndarray>
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- " \n",
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- " \n",
- " \n",
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- " \n",
- " Array \n",
- " Chunk \n",
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- " \n",
- " \n",
- " Bytes \n",
- " 688.32 MiB \n",
- " 236.84 kiB \n",
- " \n",
- " \n",
- " \n",
- " Shape \n",
- " (744, 60631, 2, 2, 1, 1, 1) \n",
- " (1, 60631, 1, 1, 1, 1, 1) \n",
- " \n",
- " \n",
- " Dask graph \n",
- " 2976 chunks in 2 graph layers \n",
- " \n",
- " \n",
- " Data type \n",
- " float32 numpy.ndarray \n",
- " \n",
- " \n",
- "
\n",
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- "\n",
- " \n",
- " 744 \n",
- " 1 \n",
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- " \n",
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- " \n",
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- " \n",
- " \n",
- "\n",
- " \n",
- " \n",
- "\n",
- " \n",
- " 2 \n",
- " 2 \n",
- " 60631 \n",
- "\n",
- "\n",
- " \n",
- " \n",
- " \n",
- "\n",
- " \n",
- " \n",
- " \n",
- "\n",
- " \n",
- " \n",
- "\n",
- " \n",
- " \n",
- " \n",
- "\n",
- " \n",
- " \n",
- " \n",
- "\n",
- " \n",
- " \n",
- "\n",
- " \n",
- " \n",
- " \n",
- "\n",
- " \n",
- " \n",
- " \n",
- "\n",
- " \n",
- " \n",
- "\n",
- " \n",
- " 1 \n",
- " 1 \n",
- " 1 \n",
- " \n",
- " \n",
- " \n",
- "
Indexes: (7)
PandasIndex
PandasIndex(Index(['010101', '010801', '010802', '010901', '010902', '010903', '011001',\n",
- " '011002', '011003', '011201',\n",
- " ...\n",
- " '103704', '103714', '103715', '103801', '104001', '104401', '104801',\n",
- " '104803', '104804', '120201'],\n",
- " dtype='object', name='id', length=744)) PandasIndex
PandasIndex(Index(['Ministère de l’Environnement, de la Lutte contre les changements climatiques, de la Faune et des Parcs'], dtype='object', name='source')) PandasIndex
PandasIndex(Index(['point', 'watershed'], dtype='object', name='spatial_agg')) PandasIndex
PandasIndex(DatetimeIndex(['1860-01-01', '1860-01-02', '1860-01-03', '1860-01-04',\n",
- " '1860-01-05', '1860-01-06', '1860-01-07', '1860-01-08',\n",
- " '1860-01-09', '1860-01-10',\n",
- " ...\n",
- " '2025-12-22', '2025-12-23', '2025-12-24', '2025-12-25',\n",
- " '2025-12-26', '2025-12-27', '2025-12-28', '2025-12-29',\n",
- " '2025-12-30', '2025-12-31'],\n",
- " dtype='datetime64[ns]', name='time', length=60631, freq=None)) PandasIndex
PandasIndex(Index(['mean'], dtype='object', name='time_agg')) PandasIndex
PandasIndex(Index(['D'], dtype='object', name='timestep')) PandasIndex
PandasIndex(Index(['level', 'streamflow'], dtype='object', name='variable')) Attributes: (0)
"
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- "text/plain": [
- "\n",
- "Dimensions: (id: 744, variable: 2, spatial_agg: 2, timestep: 1,\n",
- " time_agg: 1, source: 1, time: 60631)\n",
- "Coordinates: (12/15)\n",
- " drainage_area (id) float32 dask.array\n",
- " end_date (variable, id, spatial_agg, timestep, time_agg, source) datetime64[ns] dask.array\n",
- " * id (id) object '010101' '010801' '010802' ... '104804' '120201'\n",
- " latitude (id) float32 dask.array\n",
- " longitude (id) float32 dask.array\n",
- " name (id) object dask.array\n",
- " ... ...\n",
- " * spatial_agg (spatial_agg) object 'point' 'watershed'\n",
- " start_date (variable, id, spatial_agg, timestep, time_agg, source) datetime64[ns] dask.array\n",
- " * time (time) datetime64[ns] 1860-01-01 1860-01-02 ... 2025-12-31\n",
- " * time_agg (time_agg) object 'mean'\n",
- " * timestep (timestep) object 'D'\n",
- " * variable (variable) object 'level' 'streamflow'\n",
- "Data variables:\n",
- " level (id, time, variable, spatial_agg, timestep, time_agg, source) float32 dask.array\n",
- " streamflow (id, time, variable, spatial_agg, timestep, time_agg, source) float32 dask.array"
- ]
- },
- "execution_count": 30,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"query = {\"datasets\": \"deh\"}\n",
"xds = xd.Query(**query)\n",
@@ -5859,443 +677,9 @@
},
{
"cell_type": "code",
- "execution_count": 31,
+ "execution_count": null,
"metadata": {},
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Coordinates: (15)
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array(['QC', 'QC', 'QC', 'QC', 'QC'], dtype=object) regulated
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()
<U102
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<U1
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<U10
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array('streamflow', dtype='<U10') Data variables: (1)
Indexes: (2)
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PandasIndex(DatetimeIndex(['1970-01-01', '1970-01-02', '1970-01-03', '1970-01-04',\n",
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- " \n",
- " 1 \n",
- " 1 \n",
- " 2 \n",
- " \n",
- " \n",
- " \n",
- "
time
(time)
datetime64[ns]
1860-01-01 ... 2022-08-31
array(['1860-01-01T00:00:00.000000000', '1860-01-02T00:00:00.000000000',\n",
- " '1860-01-03T00:00:00.000000000', ..., '2022-08-29T00:00:00.000000000',\n",
- " '2022-08-30T00:00:00.000000000', '2022-08-31T00:00:00.000000000'],\n",
- " dtype='datetime64[ns]') time_agg
(time_agg)
<U4
'mean'
array(['mean'], dtype='<U4') timestep
(timestep)
<U3
'day'
array(['day'], dtype='<U3') Data variables: (2)
mask
(id, latitude, longitude)
float64
dask.array<chunksize=(1, 500, 500), meta=np.ndarray>
grid_mapping : spatial_ref \n",
- " \n",
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- " Array \n",
- " Chunk \n",
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- " Bytes \n",
- " 769.44 GiB \n",
- " 1.91 MiB \n",
- " \n",
- " \n",
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- " Shape \n",
- " (7881, 2800, 4680) \n",
- " (1, 500, 500) \n",
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- " Dask graph \n",
- " 472860 chunks in 2 graph layers \n",
- " \n",
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- " Data type \n",
- " float64 numpy.ndarray \n",
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- "\n",
- " \n",
- " 4680 \n",
- " 2800 \n",
- " 7881 \n",
- " \n",
- " \n",
- " \n",
- "
value
(id, time, data_type, spatial_agg, timestep, time_agg)
float64
dask.array<chunksize=(10, 59413, 1, 1, 1, 1), meta=np.ndarray>
\n",
- " \n",
- " \n",
- " \n",
- " \n",
- " \n",
- " \n",
- " Array \n",
- " Chunk \n",
- " \n",
- " \n",
- " \n",
- " \n",
- " \n",
- " Bytes \n",
- " 13.95 GiB \n",
- " 4.53 MiB \n",
- " \n",
- " \n",
- " \n",
- " Shape \n",
- " (7881, 59413, 2, 2, 1, 1) \n",
- " (10, 59413, 1, 1, 1, 1) \n",
- " \n",
- " \n",
- " Dask graph \n",
- " 3156 chunks in 2 graph layers \n",
- " \n",
- " \n",
- " Data type \n",
- " float64 numpy.ndarray \n",
- " \n",
- " \n",
- "
\n",
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- "\n",
- " \n",
- " 2 \n",
- " 59413 \n",
- " 7881 \n",
- "\n",
- "\n",
- " \n",
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- " \n",
- "
Indexes: (8)
PandasIndex
PandasIndex(Index(['flow', 'level'], dtype='object', name='data_type')) PandasIndex
PandasIndex(Index(['01AA002', '01AD001', '01AD002', '01AD003', '01AD004', '01AD005',\n",
- " '01AD008', '01AD009', '01AD012', '01AD013',\n",
- " ...\n",
- " '11AE012', '11AE013', '11AE014', '11AE015', '11AE016', '11AE018',\n",
- " '11AF001', '11AF002', '11AF004', '11AF005'],\n",
- " dtype='object', name='id', length=7881)) PandasIndex
PandasIndex(Index([ 85.0, 84.975, 84.94999999999999,\n",
- " 84.92499999999998, 84.89999999999998, 84.87499999999997,\n",
- " 84.84999999999997, 84.82499999999996, 84.79999999999995,\n",
- " 84.77499999999995,\n",
- " ...\n",
- " 15.24999999998414, 15.224999999984135, 15.19999999998413,\n",
- " 15.174999999984124, 15.149999999984118, 15.124999999984112,\n",
- " 15.099999999984107, 15.074999999984101, 15.049999999984095,\n",
- " 15.02499999998409],\n",
- " dtype='float64', name='latitude', length=2800)) PandasIndex
PandasIndex(Index([ -167.0, -166.975, -166.95,\n",
- " -166.92499999999998, -166.89999999999998, -166.87499999999997,\n",
- " -166.84999999999997, -166.82499999999996, -166.79999999999995,\n",
- " -166.77499999999995,\n",
- " ...\n",
- " -50.249999999973454, -50.22499999997345, -50.19999999997344,\n",
- " -50.17499999997344, -50.14999999997343, -50.124999999973426,\n",
- " -50.09999999997342, -50.074999999973414, -50.04999999997341,\n",
- " -50.0249999999734],\n",
- " dtype='float64', name='longitude', length=4680)) PandasIndex
PandasIndex(Index(['point', 'watershed'], dtype='object', name='spatial_agg')) PandasIndex
PandasIndex(DatetimeIndex(['1860-01-01', '1860-01-02', '1860-01-03', '1860-01-04',\n",
- " '1860-01-05', '1860-01-06', '1860-01-07', '1860-01-08',\n",
- " '1860-01-09', '1860-01-10',\n",
- " ...\n",
- " '2022-08-22', '2022-08-23', '2022-08-24', '2022-08-25',\n",
- " '2022-08-26', '2022-08-27', '2022-08-28', '2022-08-29',\n",
- " '2022-08-30', '2022-08-31'],\n",
- " dtype='datetime64[ns]', name='time', length=59413, freq=None)) PandasIndex
PandasIndex(Index(['mean'], dtype='object', name='time_agg')) PandasIndex
PandasIndex(Index(['day'], dtype='object', name='timestep')) Attributes: (0)
"
- ],
- "text/plain": [
- "\n",
- "Dimensions: (data_type: 2, id: 7881, spatial_agg: 2, timestep: 1,\n",
- " time_agg: 1, latitude: 2800, longitude: 4680, time: 59413)\n",
- "Coordinates: (12/15)\n",
- " * data_type (data_type) \n",
- " end_date (id, data_type, spatial_agg, timestep, time_agg) object dask.array\n",
- " * id (id) \n",
- " * spatial_agg (spatial_agg) object 'point' 'watershed'\n",
- " start_date (id, data_type, spatial_agg, timestep, time_agg) object dask.array\n",
- " * time (time) datetime64[ns] 1860-01-01 1860-01-02 ... 2022-08-31\n",
- " * time_agg (time_agg) \n",
- " value (id, time, data_type, spatial_agg, timestep, time_agg) float64 dask.array"
- ]
- },
- "execution_count": 32,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"query = {\"datasets\": \"hydat\"}\n",
"xds = xd.Query(**query)\n",
@@ -7622,9 +733,6 @@
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.7"
- },
- "nbsphinx": {
- "execute": "never"
}
},
"nbformat": 4,
diff --git a/notebooks/getting_started.html b/notebooks/getting_started.html
index 0312d43..ac428a7 100644
--- a/notebooks/getting_started.html
+++ b/notebooks/getting_started.html
@@ -383,17 +383,17 @@ Query climate datasets