diff --git a/experiments/test_notebook.ipynb b/experiments/test_notebook.ipynb
index bac465598e8943cf46f8651c520ecc9a6c7ebd46..1b9515f3202b1b6028f65ae6c4b7b2026653999d 100644
--- a/experiments/test_notebook.ipynb
+++ b/experiments/test_notebook.ipynb
@@ -26,7 +26,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
- "/tmp/ipykernel_2455/4095267831.py:5: DeprecationWarning: Importing display from IPython.core.display is deprecated since IPython 7.14, please import from IPython display\n",
+ "/tmp/ipykernel_8229/4095267831.py:5: DeprecationWarning: Importing display from IPython.core.display is deprecated since IPython 7.14, please import from IPython display\n",
" from IPython.core.display import display, HTML\n"
]
}
@@ -60,287 +60,8 @@
},
{
"data": {
- "application/javascript": [
- "(function(root) {\n",
- " function now() {\n",
- " return new Date();\n",
- " }\n",
- "\n",
- " const 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",
- "const JS_MIME_TYPE = 'application/javascript';\n",
- " const HTML_MIME_TYPE = 'text/html';\n",
- " const EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
- " const CLASS_NAME = 'output_bokeh rendered_html';\n",
- "\n",
- " /**\n",
- " * Render data to the DOM node\n",
- " */\n",
- " function render(props, node) {\n",
- " const script = document.createElement(\"script\");\n",
- " node.appendChild(script);\n",
- " }\n",
- "\n",
- " /**\n",
- " * Handle when an output is cleared or removed\n",
- " */\n",
- " function handleClearOutput(event, handle) {\n",
- " const cell = handle.cell;\n",
- "\n",
- " const id = cell.output_area._bokeh_element_id;\n",
- " const server_id = cell.output_area._bokeh_server_id;\n",
- " // Clean up Bokeh references\n",
- " if (id != null && id in Bokeh.index) {\n",
- " Bokeh.index[id].model.document.clear();\n",
- " delete Bokeh.index[id];\n",
- " }\n",
- "\n",
- " if (server_id !== undefined) {\n",
- " // Clean up Bokeh references\n",
- " const cmd_clean = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
- " cell.notebook.kernel.execute(cmd_clean, {\n",
- " iopub: {\n",
- " output: function(msg) {\n",
- " const id = msg.content.text.trim();\n",
- " if (id in Bokeh.index) {\n",
- " Bokeh.index[id].model.document.clear();\n",
- " delete Bokeh.index[id];\n",
- " }\n",
- " }\n",
- " }\n",
- " });\n",
- " // Destroy server and session\n",
- " const cmd_destroy = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
- " cell.notebook.kernel.execute(cmd_destroy);\n",
- " }\n",
- " }\n",
- "\n",
- " /**\n",
- " * Handle when a new output is added\n",
- " */\n",
- " function handleAddOutput(event, handle) {\n",
- " const output_area = handle.output_area;\n",
- " const output = handle.output;\n",
- "\n",
- " // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n",
- " if ((output.output_type != \"display_data\") || (!Object.prototype.hasOwnProperty.call(output.data, EXEC_MIME_TYPE))) {\n",
- " return\n",
- " }\n",
- "\n",
- " const toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
- "\n",
- " if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
- " toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n",
- " // store reference to embed id on output_area\n",
- " output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
- " }\n",
- " if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
- " const bk_div = document.createElement(\"div\");\n",
- " bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
- " const script_attrs = bk_div.children[0].attributes;\n",
- " for (let i = 0; i < script_attrs.length; i++) {\n",
- " toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
- " toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n",
- " }\n",
- " // store reference to server id on output_area\n",
- " output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
- " }\n",
- " }\n",
- "\n",
- " function register_renderer(events, OutputArea) {\n",
- "\n",
- " function append_mime(data, metadata, element) {\n",
- " // create a DOM node to render to\n",
- " const toinsert = this.create_output_subarea(\n",
- " metadata,\n",
- " CLASS_NAME,\n",
- " EXEC_MIME_TYPE\n",
- " );\n",
- " this.keyboard_manager.register_events(toinsert);\n",
- " // Render to node\n",
- " const props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
- " render(props, toinsert[toinsert.length - 1]);\n",
- " element.append(toinsert);\n",
- " return toinsert\n",
- " }\n",
- "\n",
- " /* Handle when an output is cleared or removed */\n",
- " events.on('clear_output.CodeCell', handleClearOutput);\n",
- " events.on('delete.Cell', handleClearOutput);\n",
- "\n",
- " /* Handle when a new output is added */\n",
- " events.on('output_added.OutputArea', handleAddOutput);\n",
- "\n",
- " /**\n",
- " * Register the mime type and append_mime function with output_area\n",
- " */\n",
- " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
- " /* Is output safe? */\n",
- " safe: true,\n",
- " /* Index of renderer in `output_area.display_order` */\n",
- " index: 0\n",
- " });\n",
- " }\n",
- "\n",
- " // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
- " if (root.Jupyter !== undefined) {\n",
- " const events = require('base/js/events');\n",
- " const OutputArea = require('notebook/js/outputarea').OutputArea;\n",
- "\n",
- " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
- " register_renderer(events, OutputArea);\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",
- " const NB_LOAD_WARNING = {'data': {'text/html':\n",
- " \"<div style='background-color: #fdd'>\\n\"+\n",
- " \"<p>\\n\"+\n",
- " \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
- " \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
- " \"</p>\\n\"+\n",
- " \"<ul>\\n\"+\n",
- " \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
- " \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
- " \"</ul>\\n\"+\n",
- " \"<code>\\n\"+\n",
- " \"from bokeh.resources import INLINE\\n\"+\n",
- " \"output_notebook(resources=INLINE)\\n\"+\n",
- " \"</code>\\n\"+\n",
- " \"</div>\"}};\n",
- "\n",
- " function display_loaded() {\n",
- " const el = document.getElementById(\"1001\");\n",
- " if (el != null) {\n",
- " el.textContent = \"BokehJS is loading...\";\n",
- " }\n",
- " if (root.Bokeh !== undefined) {\n",
- " if (el != null) {\n",
- " el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
- " }\n",
- " } else if (Date.now() < root._bokeh_timeout) {\n",
- " setTimeout(display_loaded, 100)\n",
- " }\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, callback) {\n",
- " if (css_urls == null) css_urls = [];\n",
- " if (js_urls == null) js_urls = [];\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 == null || js_urls.length === 0) {\n",
- " run_callbacks();\n",
- " return null;\n",
- " }\n",
- " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
- " root._bokeh_is_loading = css_urls.length + js_urls.length;\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(url) {\n",
- " console.error(\"failed to load \" + url);\n",
- " }\n",
- "\n",
- " for (let i = 0; i < css_urls.length; i++) {\n",
- " const url = css_urls[i];\n",
- " const element = document.createElement(\"link\");\n",
- " element.onload = on_load;\n",
- " element.onerror = on_error.bind(null, url);\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",
- " for (let i = 0; i < js_urls.length; i++) {\n",
- " const url = js_urls[i];\n",
- " const element = document.createElement('script');\n",
- " element.onload = on_load;\n",
- " element.onerror = on_error.bind(null, url);\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",
- " };\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",
- " const 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\"];\n",
- " const css_urls = [];\n",
- "\n",
- " const inline_js = [ function(Bokeh) {\n",
- " Bokeh.set_log_level(\"info\");\n",
- " },\n",
- "function(Bokeh) {\n",
- " }\n",
- " ];\n",
- "\n",
- " function run_inline_js() {\n",
- " if (root.Bokeh !== undefined || force === true) {\n",
- " for (let i = 0; i < inline_js.length; i++) {\n",
- " inline_js[i].call(root, root.Bokeh);\n",
- " }\n",
- "if (force === true) {\n",
- " display_loaded();\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",
- " } else if (force !== true) {\n",
- " const cell = $(document.getElementById(\"1001\")).parents('.cell').data().cell;\n",
- " cell.output_area.append_execute_result(NB_LOAD_WARNING)\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, function() {\n",
- " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
- " run_inline_js();\n",
- " });\n",
- " }\n",
- "}(window));"
- ],
- "application/vnd.bokehjs_load.v0+json": "(function(root) {\n function now() {\n return new Date();\n }\n\n const 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\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 const NB_LOAD_WARNING = {'data': {'text/html':\n \"<div style='background-color: #fdd'>\\n\"+\n \"<p>\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"</p>\\n\"+\n \"<ul>\\n\"+\n \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n \"<li>use INLINE resources instead, as so:</li>\\n\"+\n \"</ul>\\n\"+\n \"<code>\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"</code>\\n\"+\n \"</div>\"}};\n\n function display_loaded() {\n const el = document.getElementById(\"1001\");\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\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, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\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 == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = css_urls.length + js_urls.length;\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(url) {\n console.error(\"failed to load \" + url);\n }\n\n for (let i = 0; i < css_urls.length; i++) {\n const url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error.bind(null, url);\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 for (let i = 0; i < js_urls.length; i++) {\n const url = js_urls[i];\n const element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error.bind(null, url);\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 };\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 const 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\"];\n const css_urls = [];\n\n const inline_js = [ function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\nfunction(Bokeh) {\n }\n ];\n\n function run_inline_js() {\n if (root.Bokeh !== undefined || force === true) {\n for (let i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\nif (force === true) {\n display_loaded();\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 } else if (force !== true) {\n const cell = $(document.getElementById(\"1001\")).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\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, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));"
+ "application/javascript": "(function(root) {\n function now() {\n return new Date();\n }\n\n const 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\nconst JS_MIME_TYPE = 'application/javascript';\n const HTML_MIME_TYPE = 'text/html';\n const EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n const CLASS_NAME = 'output_bokeh rendered_html';\n\n /**\n * Render data to the DOM node\n */\n function render(props, node) {\n const script = document.createElement(\"script\");\n node.appendChild(script);\n }\n\n /**\n * Handle when an output is cleared or removed\n */\n function handleClearOutput(event, handle) {\n const cell = handle.cell;\n\n const id = cell.output_area._bokeh_element_id;\n const server_id = cell.output_area._bokeh_server_id;\n // Clean up Bokeh references\n if (id != null && id in Bokeh.index) {\n Bokeh.index[id].model.document.clear();\n delete Bokeh.index[id];\n }\n\n if (server_id !== undefined) {\n // Clean up Bokeh references\n const cmd_clean = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n cell.notebook.kernel.execute(cmd_clean, {\n iopub: {\n output: function(msg) {\n const id = msg.content.text.trim();\n if (id in Bokeh.index) {\n Bokeh.index[id].model.document.clear();\n delete Bokeh.index[id];\n }\n }\n }\n });\n // Destroy server and session\n const cmd_destroy = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n cell.notebook.kernel.execute(cmd_destroy);\n }\n }\n\n /**\n * Handle when a new output is added\n */\n function handleAddOutput(event, handle) {\n const output_area = handle.output_area;\n const output = handle.output;\n\n // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n if ((output.output_type != \"display_data\") || (!Object.prototype.hasOwnProperty.call(output.data, EXEC_MIME_TYPE))) {\n return\n }\n\n const toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n\n if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n // store reference to embed id on output_area\n output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n }\n if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n const bk_div = document.createElement(\"div\");\n bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n const script_attrs = bk_div.children[0].attributes;\n for (let i = 0; i < script_attrs.length; i++) {\n toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n }\n // store reference to server id on output_area\n output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n }\n }\n\n function register_renderer(events, OutputArea) {\n\n function append_mime(data, metadata, element) {\n // create a DOM node to render to\n const toinsert = this.create_output_subarea(\n metadata,\n CLASS_NAME,\n EXEC_MIME_TYPE\n );\n this.keyboard_manager.register_events(toinsert);\n // Render to node\n const props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n render(props, toinsert[toinsert.length - 1]);\n element.append(toinsert);\n return toinsert\n }\n\n /* Handle when an output is cleared or removed */\n events.on('clear_output.CodeCell', handleClearOutput);\n events.on('delete.Cell', handleClearOutput);\n\n /* Handle when a new output is added */\n events.on('output_added.OutputArea', handleAddOutput);\n\n /**\n * Register the mime type and append_mime function with output_area\n */\n OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n /* Is output safe? */\n safe: true,\n /* Index of renderer in `output_area.display_order` */\n index: 0\n });\n }\n\n // register the mime type if in Jupyter Notebook environment and previously unregistered\n if (root.Jupyter !== undefined) {\n const events = require('base/js/events');\n const OutputArea = require('notebook/js/outputarea').OutputArea;\n\n if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n register_renderer(events, OutputArea);\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 const NB_LOAD_WARNING = {'data': {'text/html':\n \"<div style='background-color: #fdd'>\\n\"+\n \"<p>\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"</p>\\n\"+\n \"<ul>\\n\"+\n \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n \"<li>use INLINE resources instead, as so:</li>\\n\"+\n \"</ul>\\n\"+\n \"<code>\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"</code>\\n\"+\n \"</div>\"}};\n\n function display_loaded() {\n const el = document.getElementById(\"1001\");\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\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, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\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 == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = css_urls.length + js_urls.length;\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(url) {\n console.error(\"failed to load \" + url);\n }\n\n for (let i = 0; i < css_urls.length; i++) {\n const url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error.bind(null, url);\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 for (let i = 0; i < js_urls.length; i++) {\n const url = js_urls[i];\n const element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error.bind(null, url);\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 };\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 const 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\"];\n const css_urls = [];\n\n const inline_js = [ function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\nfunction(Bokeh) {\n }\n ];\n\n function run_inline_js() {\n if (root.Bokeh !== undefined || force === true) {\n for (let i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\nif (force === true) {\n display_loaded();\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 } else if (force !== true) {\n const cell = $(document.getElementById(\"1001\")).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\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, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));",
+ "application/vnd.bokehjs_load.v0+json": ""
},
"metadata": {},
"output_type": "display_data"
@@ -394,7 +115,7 @@
{
"data": {
"text/plain": [
- "'/host_home/Repos/nuplan-devkit/experiments'"
+ "'/home/sacardoz/nuplan-devkit/experiments'"
]
},
"execution_count": 3,
@@ -406,26 +127,6 @@
"%pwd"
]
},
- {
- "cell_type": "code",
- "execution_count": 4,
- "id": "c8b59d7c",
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "env: NUPLAN_DATA_ROOT=/home/ehdykhne/Repos/Datasets/nuplan/dataset\n",
- "env: NUPLAN_MAPS_ROOT=/home/ehdykhne/Repos/Datasets/nuplan/dataset/maps\n"
- ]
- }
- ],
- "source": [
- "%env NUPLAN_DATA_ROOT=/home/ehdykhne/Repos/Datasets/nuplan/dataset\n",
- "%env NUPLAN_MAPS_ROOT=/home/ehdykhne/Repos/Datasets/nuplan/dataset/maps"
- ]
- },
{
"cell_type": "markdown",
"id": "db337ceb",
@@ -436,7 +137,7 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 4,
"id": "11b08c6d",
"metadata": {},
"outputs": [],
@@ -455,7 +156,7 @@
" \"scenario_filter.log_names=['2021.06.14.16.48.02_veh-12_04057_04438']\",\n",
" 'scenario_filter.limit_total_scenarios=1', # use 1 total scenarios\n",
"]\n",
- "ckpt_dir = '/home/ehdykhne/Repos/nuplan-devkit/experiments/pretrained_checkpoints/pdm_offset_checkpoint.ckpt'\n",
+ "ckpt_dir = '/home/sacardoz/checkpoints/urbandriver_checkpoint.ckpt'\n",
"#'/home/sacardoz/checkpoints/urbandriver_checkpoint.ckpt'\n",
"#\"/home/sacardoz/tutorial_vector_framework/training_simple_vector_experiment/train_default_simple_vector/2023.11.23.09.55.21/best_model/epoch.ckpt\"\n",
"#\"/home/sacardoz/training_raster_experiment/train_default_raster/2023.11.23.07.36.36/best_model/epoch.ckpt\"\n",
@@ -465,21 +166,20 @@
"\n",
"# Compose the configuration\n",
"cfg = hydra.compose(config_name=simulation_hydra_paths.config_name, overrides=[\n",
- " '+simulation=closed_loop_reactive_agents',\n",
- " #'model=pgm_hybrid_model',\n",
- " 'planner=pdm_hybrid_planner',\n",
- " f\"planner.pdm_hybrid_planner.checkpoint_path={ckpt_dir}\" ,\n",
- " #'planner.ml_planner.model_config=${model}',\n",
- " #f'planner.ml_planner.checkpoint_path={ckpt_dir}',\n",
- " #f'observation=idm_agents_observation',\n",
- " #'observation.model_config=${model}',\n",
- " #f'observation.checkpoint_path={ckpt_dir}',\n",
+ " '+simulation=closed_loop_multiagent',\n",
+ " 'model=urban_driver_open_loop_model',\n",
+ " 'planner=ml_planner',\n",
+ " #f\"planner.pdm_hybrid_planner.checkpoint_path={ckpt_dir}\" ,\n",
+ " 'planner.ml_planner.model_config=${model}',\n",
+ " f'planner.ml_planner.checkpoint_path={ckpt_dir}',\n",
+ " 'observation.model_config=${model}',\n",
+ " f'observation.checkpoint_path={ckpt_dir}',\n",
" 'worker=sequential',\n",
" '+occlusion=true',\n",
- " '+occlusion.manager_type=wedge', #options: [range, shadow, wedge]\n",
- " \"hydra.searchpath=[pkg://tuplan_garage.planning.script.config.common, pkg://tuplan_garage.planning.script.config.simulation, pkg://nuplan.planning.script.config.common, pkg://nuplan.planning.script.experiments]\",\n",
+ " '+occlusion.manager_type=shadow', #options: [range, shadow, wedge]\n",
+ " \"hydra.searchpath=[pkg://nuplan_garage.planning.script.config.common, pkg://nuplan_garage.planning.script.config.simulation, pkg://nuplan.planning.script.config.common, pkg://nuplan.planning.script.experiments]\",\n",
" *DATASET_PARAMS,\n",
- "])"
+ "])\n"
]
},
{
@@ -492,7 +192,7 @@
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 5,
"id": "161cc166",
"metadata": {
"scrolled": true
@@ -502,6 +202,8 @@
"name": "stderr",
"output_type": "stream",
"text": [
+ "INFO:nuplan.planning.script.utils:Setting default NUPLAN_DATA_ROOT: /home/sacardoz/nuplan/dataset\n",
+ "INFO:nuplan.planning.script.utils:Setting default NUPLAN_EXP_ROOT: /home/sacardoz/nuplan/exp\n",
"Global seed set to 0\n",
"INFO:nuplan.planning.script.builders.main_callback_builder:Building MultiMainCallback...\n",
"INFO:nuplan.planning.script.builders.main_callback_builder:Building MultiMainCallback: 4...DONE!\n"
@@ -511,32 +213,36 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "2023-12-04 23:36:26,261 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/worker_pool_builder.py:19} Building WorkerPool...\n",
- "2023-12-04 23:36:26,263 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/utils/multithreading/worker_pool.py:101} Worker: Sequential\n",
- "2023-12-04 23:36:26,263 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/utils/multithreading/worker_pool.py:102} Number of nodes: 1\n",
+ "2023-12-05 02:14:01,684 INFO {/home/sacardoz/nuplan-devkit/nuplan/planning/script/builders/worker_pool_builder.py:19} Building WorkerPool...\n",
+ "2023-12-05 02:14:01,685 INFO {/home/sacardoz/nuplan-devkit/nuplan/planning/utils/multithreading/worker_pool.py:101} Worker: Sequential\n",
+ "2023-12-05 02:14:01,685 INFO {/home/sacardoz/nuplan-devkit/nuplan/planning/utils/multithreading/worker_pool.py:102} Number of nodes: 1\n",
"Number of CPUs per node: 1\n",
"Number of GPUs per node: 0\n",
"Number of threads across all nodes: 1\n",
- "2023-12-04 23:36:26,263 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/worker_pool_builder.py:27} Building WorkerPool...DONE!\n",
- "2023-12-04 23:36:26,263 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/folder_builder.py:32} Building experiment folders...\n",
- "2023-12-04 23:36:26,263 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/folder_builder.py:35} \n",
+ "2023-12-05 02:14:01,685 INFO {/home/sacardoz/nuplan-devkit/nuplan/planning/script/builders/worker_pool_builder.py:27} Building WorkerPool...DONE!\n",
+ "2023-12-05 02:14:01,685 INFO {/home/sacardoz/nuplan-devkit/nuplan/planning/script/builders/folder_builder.py:32} Building experiment folders...\n",
+ "2023-12-05 02:14:01,685 INFO {/home/sacardoz/nuplan-devkit/nuplan/planning/script/builders/folder_builder.py:35} \n",
"\n",
- "\tFolder where all results are stored: /home/ehdykhne/Repos/Datasets/nuplan/exp/exp/simulation/closed_loop_reactive_agents/2023.12.04.23.36.25\n",
+ "\tFolder where all results are stored: /home/sacardoz/nuplan/exp/exp/simulation/closed_loop_multiagent/2023.12.05.02.14.01\n",
"\n",
- "2023-12-04 23:36:26,293 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/folder_builder.py:70} Building experiment folders...DONE!\n",
- "2023-12-04 23:36:26,293 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/simulation_callback_builder.py:52} Building AbstractCallback...\n",
- "2023-12-04 23:36:26,293 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/simulation_callback_builder.py:68} Building AbstractCallback: 0...DONE!\n",
- "2023-12-04 23:36:26,293 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/simulation_builder.py:49} Building simulations...\n",
- "2023-12-04 23:36:26,293 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/simulation_builder.py:55} Extracting scenarios...\n",
- "2023-12-04 23:36:26,294 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/common/utils/distributed_scenario_filter.py:83} Building Scenarios in mode DistributedMode.SINGLE_NODE\n",
- "2023-12-04 23:36:26,294 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/scenario_building_builder.py:18} Building AbstractScenarioBuilder...\n",
- "2023-12-04 23:36:26,305 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/scenario_building_builder.py:21} Building AbstractScenarioBuilder...DONE!\n",
- "2023-12-04 23:36:26,305 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/scenario_filter_builder.py:35} Building ScenarioFilter...\n",
- "2023-12-04 23:36:26,306 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/scenario_filter_builder.py:44} Building ScenarioFilter...DONE!\n",
- "2023-12-04 23:36:26,381 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/simulation_builder.py:76} Building metric engines...\n",
- "2023-12-04 23:36:26,403 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/simulation_builder.py:78} Building metric engines...DONE\n",
- "2023-12-04 23:36:26,403 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/simulation_builder.py:82} Building simulations from 1 scenarios...\n",
- "2023-12-04 23:36:26,979 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/script/builders/simulation_builder.py:142} Building simulations...DONE!\n"
+ "2023-12-05 02:14:01,687 INFO {/home/sacardoz/nuplan-devkit/nuplan/planning/script/builders/folder_builder.py:70} Building experiment folders...DONE!\n",
+ "2023-12-05 02:14:01,687 INFO {/home/sacardoz/nuplan-devkit/nuplan/planning/script/builders/simulation_callback_builder.py:52} Building AbstractCallback...\n",
+ "2023-12-05 02:14:01,687 INFO {/home/sacardoz/nuplan-devkit/nuplan/planning/script/builders/simulation_callback_builder.py:68} Building AbstractCallback: 0...DONE!\n",
+ "2023-12-05 02:14:01,687 INFO {/home/sacardoz/nuplan-devkit/nuplan/planning/script/builders/simulation_builder.py:49} Building simulations...\n",
+ "2023-12-05 02:14:01,687 INFO {/home/sacardoz/nuplan-devkit/nuplan/planning/script/builders/simulation_builder.py:55} Extracting scenarios...\n",
+ "2023-12-05 02:14:01,687 INFO {/home/sacardoz/nuplan-devkit/nuplan/common/utils/distributed_scenario_filter.py:83} Building Scenarios in mode DistributedMode.SINGLE_NODE\n",
+ "2023-12-05 02:14:01,687 INFO {/home/sacardoz/nuplan-devkit/nuplan/planning/script/builders/scenario_building_builder.py:18} Building AbstractScenarioBuilder...\n",
+ "2023-12-05 02:14:01,700 INFO {/home/sacardoz/nuplan-devkit/nuplan/planning/script/builders/scenario_building_builder.py:21} Building AbstractScenarioBuilder...DONE!\n",
+ "2023-12-05 02:14:01,700 INFO {/home/sacardoz/nuplan-devkit/nuplan/planning/script/builders/scenario_filter_builder.py:35} Building ScenarioFilter...\n",
+ "2023-12-05 02:14:01,701 INFO {/home/sacardoz/nuplan-devkit/nuplan/planning/script/builders/scenario_filter_builder.py:44} Building ScenarioFilter...DONE!\n",
+ "2023-12-05 02:14:01,719 INFO {/home/sacardoz/nuplan-devkit/nuplan/planning/script/builders/simulation_builder.py:76} Building metric engines...\n",
+ "2023-12-05 02:14:01,744 INFO {/home/sacardoz/nuplan-devkit/nuplan/planning/script/builders/simulation_builder.py:78} Building metric engines...DONE\n",
+ "2023-12-05 02:14:01,744 INFO {/home/sacardoz/nuplan-devkit/nuplan/planning/script/builders/simulation_builder.py:82} Building simulations from 1 scenarios...\n",
+ "2023-12-05 02:14:01,746 INFO {/home/sacardoz/nuplan-devkit/nuplan/planning/script/builders/model_builder.py:18} Building TorchModuleWrapper...\n",
+ "2023-12-05 02:14:01,787 INFO {/home/sacardoz/nuplan-devkit/nuplan/planning/script/builders/model_builder.py:21} Building TorchModuleWrapper...DONE!\n",
+ "2023-12-05 02:14:01,912 INFO {/home/sacardoz/nuplan-devkit/nuplan/planning/script/builders/model_builder.py:18} Building TorchModuleWrapper...\n",
+ "2023-12-05 02:14:01,956 INFO {/home/sacardoz/nuplan-devkit/nuplan/planning/script/builders/model_builder.py:21} Building TorchModuleWrapper...DONE!\n",
+ "2023-12-05 02:14:02,577 INFO {/home/sacardoz/nuplan-devkit/nuplan/planning/script/builders/simulation_builder.py:142} Building simulations...DONE!\n"
]
}
],
@@ -550,7 +256,7 @@
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 6,
"id": "223284d4",
"metadata": {},
"outputs": [],
@@ -558,193 +264,186 @@
"runner = runners[0]"
]
},
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "id": "907ad940",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from nuplan.common.actor_state.agent import Agent\n",
+ "from nuplan.common.actor_state.oriented_box import OrientedBox\n",
+ "from nuplan.common.actor_state.scene_object import SceneObjectMetadata\n",
+ "from nuplan.common.actor_state.state_representation import StateSE2, StateVector2D\n",
+ "\n",
+ "inserted_agent = Agent(tracked_object_type=TrackedObjectType.VEHICLE,\n",
+ " oriented_box=OrientedBox(StateSE2(664433, 3997400, 3 * 3.14 / 2), 5, 2, 2),\n",
+ " velocity=StateVector2D(0,0),\n",
+ " metadata=SceneObjectMetadata(1623707858950113, \"inserted\", -2, \"inserted\"),\n",
+ " angular_velocity=0.0)\n",
+ "\n",
+ "inserted_goal = StateSE2(664433, 3997000, 3 * 3.14 / 2)"
+ ]
+ },
{
"cell_type": "code",
"execution_count": 8,
"id": "90b79421",
"metadata": {},
"outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- " \r"
- ]
- },
{
"name": "stdout",
"output_type": "stream",
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+ "SimulationIteration(time_point=TimePoint(time_us=1623707859150076), index=128)\n",
+ "SimulationIteration(time_point=TimePoint(time_us=1623707859250064), index=129)\n",
+ "SimulationIteration(time_point=TimePoint(time_us=1623707859350064), index=130)\n",
+ "SimulationIteration(time_point=TimePoint(time_us=1623707859450064), index=131)\n",
+ "SimulationIteration(time_point=TimePoint(time_us=1623707859550063), index=132)\n",
+ "SimulationIteration(time_point=TimePoint(time_us=1623707859650055), index=133)\n",
+ "SimulationIteration(time_point=TimePoint(time_us=1623707859750047), index=134)\n",
+ "SimulationIteration(time_point=TimePoint(time_us=1623707859850041), index=135)\n",
+ "SimulationIteration(time_point=TimePoint(time_us=1623707859950028), index=136)\n",
+ "SimulationIteration(time_point=TimePoint(time_us=1623707860050018), index=137)\n",
+ "SimulationIteration(time_point=TimePoint(time_us=1623707860150002), index=138)\n",
+ "SimulationIteration(time_point=TimePoint(time_us=1623707860249979), index=139)\n",
+ "SimulationIteration(time_point=TimePoint(time_us=1623707860349963), index=140)\n",
+ "SimulationIteration(time_point=TimePoint(time_us=1623707860449960), index=141)\n",
+ "SimulationIteration(time_point=TimePoint(time_us=1623707860549964), index=142)\n",
+ "SimulationIteration(time_point=TimePoint(time_us=1623707860649965), index=143)\n",
+ "SimulationIteration(time_point=TimePoint(time_us=1623707860749961), index=144)\n",
+ "SimulationIteration(time_point=TimePoint(time_us=1623707860849946), index=145)\n",
+ "SimulationIteration(time_point=TimePoint(time_us=1623707860949927), index=146)\n",
+ "SimulationIteration(time_point=TimePoint(time_us=1623707861049906), index=147)\n",
+ "SimulationIteration(time_point=TimePoint(time_us=1623707861149865), index=148)\n"
]
}
],
@@ -755,6 +454,10 @@
"runner._initialize()\n",
"\n",
"while runner.simulation.is_simulation_running():\n",
+ "\n",
+ " if runner.simulation._time_controller.get_iteration().index == 125:\n",
+ " runner.simulation._observations.add_agent_to_scene(inserted_agent, inserted_goal, iteration.time_point)\n",
+ "\n",
" # Execute specific callback\n",
" runner.simulation.callback.on_step_start(runner.simulation.setup, runner.planner)\n",
"\n",
@@ -771,7 +474,7 @@
" runner._simulation.callback.on_planner_end(runner.simulation.setup, runner.planner, trajectory)\n",
"\n",
" iteration = runner.simulation._time_controller.get_iteration()\n",
- "\n",
+ " print(iteration)\n",
" runner.simulation.propagate(trajectory)\n",
"\n",
" # Execute specific callback\n",
@@ -782,7 +485,7 @@
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": null,
"id": "e6c22f5f",
"metadata": {
"scrolled": true
@@ -792,7 +495,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
- "INFO:bokeh.server.server:Starting Bokeh server version 2.4.3 (running on Tornado 6.2)\n",
+ "INFO:bokeh.server.server:Starting Bokeh server version 2.4.3 (running on Tornado 6.3.3)\n",
"WARNING:bokeh.server.util:Host wildcard '*' will allow connections originating from multiple (or possibly all) hostnames or IPs. Use non-wildcard values to restrict access explicitly\n",
"INFO:bokeh.server.tornado:User authentication hooks NOT provided (default user enabled)\n"
]
@@ -805,7 +508,7 @@
" (function() {\n",
" const xhr = new XMLHttpRequest()\n",
" xhr.responseType = 'blob';\n",
- " xhr.open('GET', \"http://localhost:5006/autoload.js?bokeh-autoload-element=1003&bokeh-absolute-url=http://localhost:5006&resources=none\", true);\n",
+ " xhr.open('GET', \"http://localhost:5008/autoload.js?bokeh-autoload-element=1003&bokeh-absolute-url=http://localhost:5008&resources=none\", true);\n",
" xhr.onload = function (event) {\n",
" const script = document.createElement('script');\n",
" const src = URL.createObjectURL(event.target.response);\n",
@@ -819,7 +522,7 @@
},
"metadata": {
"application/vnd.bokehjs_exec.v0+json": {
- "server_id": "e6e966ebbd494438b1ac64effae4c8b2"
+ "server_id": "98f8c05cc9d14e8a9b309f39e6f6f8e6"
}
},
"output_type": "display_data"
@@ -828,59 +531,23 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "2023-12-04 23:37:42,023 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/nuboard/base/experiment_file_data.py:140} Could not open Parquet input source '<Buffer>': Parquet magic bytes not found in footer. Either the file is corrupted or this is not a parquet file.\n",
- "2023-12-04 23:37:42,024 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/nuboard/base/experiment_file_data.py:140} Could not open Parquet input source '<Buffer>': Parquet magic bytes not found in footer. Either the file is corrupted or this is not a parquet file.\n",
- "2023-12-04 23:37:42,026 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/nuboard/base/experiment_file_data.py:140} Error creating dataset. Could not read schema from 'pretrained_checkpoints/gc_pgp_checkpoint.ckpt'. Is this a 'parquet' file?: Could not open Parquet input source 'pretrained_checkpoints/gc_pgp_checkpoint.ckpt': Parquet magic bytes not found in footer. Either the file is corrupted or this is not a parquet file.\n",
- "2023-12-04 23:37:42,027 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/nuboard/base/experiment_file_data.py:140} Error creating dataset. Could not read schema from '.ipynb_checkpoints/test_notebook-checkpoint.ipynb'. Is this a 'parquet' file?: Could not open Parquet input source '.ipynb_checkpoints/test_notebook-checkpoint.ipynb': Parquet magic bytes not found in footer. Either the file is corrupted or this is not a parquet file.\n",
- "2023-12-04 23:37:42,028 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/nuboard/base/experiment_file_data.py:140} Error creating dataset. Could not read schema from 'run_sim_closed_loop/training_raster_experiment/train_default_raster/2023.11.14.22.55.23/hparams.yaml'. Is this a 'parquet' file?: Could not open Parquet input source 'run_sim_closed_loop/training_raster_experiment/train_default_raster/2023.11.14.22.55.23/hparams.yaml': Parquet magic bytes not found in footer. Either the file is corrupted or this is not a parquet file.\n",
- "2023-12-04 23:37:42,028 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/nuboard/base/experiment_file_data.py:140} Could not open Parquet input source '<Buffer>': Parquet magic bytes not found in footer. Either the file is corrupted or this is not a parquet file.\n",
- "2023-12-04 23:37:42,032 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/nuboard/base/simulation_tile.py:172} Minimum frame time=0.017 s\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "Rendering a scenario: 100%|██████████| 1/1 [00:00<00:00, 157.64it/s]\n",
- "WARNING:bokeh.core.validation.check:W-1000 (MISSING_RENDERERS): Plot has no renderers: Figure(id='1005', ...)\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "2023-12-04 23:37:44,012 INFO {/opt/conda/lib/python3.9/site-packages/tornado/web.py:2271} 200 GET / (10.40.117.44) 2030.70ms\n",
- "2023-12-04 23:37:44,023 INFO {/home/ehdykhne/Repos/nuplan-devkit/tutorials/utils/tutorial_utils.py:267} Done rendering!\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "INFO:tornado.access:200 GET / (10.40.117.44) 2030.70ms\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "2023-12-04 23:37:44,370 INFO {/opt/conda/lib/python3.9/site-packages/tornado/web.py:2271} 200 GET /static/js/bokeh-gl.min.js?v=e5df31fd9010eacff0aa72d315264604b5e34972ba445acea6fce98080eecf33acf2d2986126360faaa5852813cffa16f6f6f4889923318300f062497c02da4e (10.40.117.44) 271.87ms\n",
- "2023-12-04 23:37:44,398 INFO {/opt/conda/lib/python3.9/site-packages/tornado/web.py:2271} 200 GET /static/js/bokeh.min.js?v=3c61e952b808bb7e346ce828a565a5f23aaf7708d034fa9d0906403813355d45bb4e8d8b0b23a93f032c76831d4f0221846f28699c7f5147caa62e0d31668314 (10.40.117.44) 299.84ms\n",
- "2023-12-04 23:37:44,400 INFO {/opt/conda/lib/python3.9/site-packages/tornado/web.py:2271} 200 GET /static/js/bokeh-widgets.min.js?v=8a1ff6f5aa0d967f4998d275803bbb111d928fd9f605ef9e1f30cfd021df0e77224ee3d13f83edb3a942f6e4ccc569ee5dd8951a8aa6cb600602463b90c65a87 (10.40.117.44) 301.22ms\n",
- "2023-12-04 23:37:44,435 INFO {/opt/conda/lib/python3.9/site-packages/tornado/web.py:2271} 200 GET /static/js/bokeh-tables.min.js?v=ae2903e57cf57f52819fdf4d938c648982b51c34f73b6e653a0f3bb3c8ab44f338505931ace43eafc1636e215492e2314acf54c54baffb47813b86b4923a7fe0 (10.40.117.44) 37.66ms\n"
+ "2023-12-05 02:24:51,738 INFO {/home/sacardoz/nuplan-devkit/nuplan/planning/nuboard/base/experiment_file_data.py:140} Could not open Parquet input source '<Buffer>': Parquet magic bytes not found in footer. Either the file is corrupted or this is not a parquet file.\n",
+ "2023-12-05 02:24:51,739 INFO {/home/sacardoz/nuplan-devkit/nuplan/planning/nuboard/base/experiment_file_data.py:140} Could not open Parquet input source '<Buffer>': Parquet magic bytes not found in footer. Either the file is corrupted or this is not a parquet file.\n",
+ "2023-12-05 02:24:51,740 INFO {/home/sacardoz/nuplan-devkit/nuplan/planning/nuboard/base/experiment_file_data.py:140} Error creating dataset. Could not read schema from 'pretrained_checkpoints/gc_pgp_checkpoint.ckpt'. Is this a 'parquet' file?: Could not open Parquet input source 'pretrained_checkpoints/gc_pgp_checkpoint.ckpt': Parquet magic bytes not found in footer. Either the file is corrupted or this is not a parquet file.\n",
+ "2023-12-05 02:24:51,740 INFO {/home/sacardoz/nuplan-devkit/nuplan/planning/nuboard/base/experiment_file_data.py:140} Could not open Parquet input source '<Buffer>': Parquet magic bytes not found in footer. Either the file is corrupted or this is not a parquet file.\n",
+ "2023-12-05 02:24:51,740 INFO {/home/sacardoz/nuplan-devkit/nuplan/planning/nuboard/base/experiment_file_data.py:140} Error creating dataset. Could not read schema from 'run_sim_closed_loop/training_raster_experiment/train_default_raster/2023.11.14.22.55.23/hparams.yaml'. Is this a 'parquet' file?: Could not open Parquet input source 'run_sim_closed_loop/training_raster_experiment/train_default_raster/2023.11.14.22.55.23/hparams.yaml': Parquet magic bytes not found in footer. Either the file is corrupted or this is not a parquet file.\n",
+ "2023-12-05 02:24:51,742 INFO {/home/sacardoz/nuplan-devkit/nuplan/planning/nuboard/base/simulation_tile.py:172} Minimum frame time=0.017 s\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
- "INFO:tornado.access:200 GET /static/js/bokeh-gl.min.js?v=e5df31fd9010eacff0aa72d315264604b5e34972ba445acea6fce98080eecf33acf2d2986126360faaa5852813cffa16f6f6f4889923318300f062497c02da4e (10.40.117.44) 271.87ms\n",
- "INFO:tornado.access:200 GET /static/js/bokeh.min.js?v=3c61e952b808bb7e346ce828a565a5f23aaf7708d034fa9d0906403813355d45bb4e8d8b0b23a93f032c76831d4f0221846f28699c7f5147caa62e0d31668314 (10.40.117.44) 299.84ms\n",
- "INFO:tornado.access:200 GET /static/js/bokeh-widgets.min.js?v=8a1ff6f5aa0d967f4998d275803bbb111d928fd9f605ef9e1f30cfd021df0e77224ee3d13f83edb3a942f6e4ccc569ee5dd8951a8aa6cb600602463b90c65a87 (10.40.117.44) 301.22ms\n",
- "INFO:tornado.access:200 GET /static/js/bokeh-tables.min.js?v=ae2903e57cf57f52819fdf4d938c648982b51c34f73b6e653a0f3bb3c8ab44f338505931ace43eafc1636e215492e2314acf54c54baffb47813b86b4923a7fe0 (10.40.117.44) 37.66ms\n",
- "INFO:tornado.access:200 GET /static/js/bokeh-mathjax.min.js?v=176c36fdbcd8fc1019fc828101a2804081a35baf4018d7f2633cd263156b593aa73112f400112b662daa0590138b74851bc91f1f2a5fbf5416ee8c876c3e0d0c (10.40.117.44) 135.59ms\n",
+ "Rendering a scenario: 100%|██████████| 1/1 [00:00<00:00, 17.42it/s]\n",
+ "WARNING:bokeh.core.validation.check:W-1000 (MISSING_RENDERERS): Plot has no renderers: Figure(id='1005', ...)\n",
+ "INFO:tornado.access:200 GET /autoload.js?bokeh-autoload-element=1003&bokeh-absolute-url=http://localhost:5008&resources=none (::1) 1379.10ms\n",
"INFO:bokeh.server.views.ws:WebSocket connection opened\n",
- "INFO:tornado.access:101 GET /ws (10.40.117.44) 1.63ms\n",
+ "INFO:tornado.access:101 GET /ws?id=5633698c-81fb-4686-8a38-bed76da7b3ba&origin=da2f890a-eb18-4637-9199-dd0f06169aef&swVersion=4&extensionId=&platform=electron&vscode-resource-base-authority=vscode-resource.vscode-cdn.net&parentOrigin=vscode-file%3A%2F%2Fvscode-app&purpose=notebookRenderer (::1) 0.61ms\n",
"INFO:bokeh.server.views.ws:ServerConnection created\n"
]
},
@@ -888,63 +555,16 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "2023-12-04 23:37:45,376 INFO {/opt/conda/lib/python3.9/site-packages/tornado/web.py:2271} 200 GET /static/js/bokeh-mathjax.min.js?v=176c36fdbcd8fc1019fc828101a2804081a35baf4018d7f2633cd263156b593aa73112f400112b662daa0590138b74851bc91f1f2a5fbf5416ee8c876c3e0d0c (10.40.117.44) 135.59ms\n",
- "2023-12-04 23:37:45,551 INFO {/opt/conda/lib/python3.9/site-packages/tornado/web.py:2271} 101 GET /ws (10.40.117.44) 1.63ms\n",
- "2023-12-04 23:37:45,664 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/nuboard/base/experiment_file_data.py:140} Could not open Parquet input source '<Buffer>': Parquet magic bytes not found in footer. Either the file is corrupted or this is not a parquet file.\n",
- "2023-12-04 23:37:45,666 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/nuboard/base/experiment_file_data.py:140} Could not open Parquet input source '<Buffer>': Parquet magic bytes not found in footer. Either the file is corrupted or this is not a parquet file.\n",
- "2023-12-04 23:37:45,666 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/nuboard/base/experiment_file_data.py:140} Error creating dataset. Could not read schema from 'pretrained_checkpoints/gc_pgp_checkpoint.ckpt'. Is this a 'parquet' file?: Could not open Parquet input source 'pretrained_checkpoints/gc_pgp_checkpoint.ckpt': Parquet magic bytes not found in footer. Either the file is corrupted or this is not a parquet file.\n",
- "2023-12-04 23:37:45,667 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/nuboard/base/experiment_file_data.py:140} Error creating dataset. Could not read schema from '.ipynb_checkpoints/test_notebook-checkpoint.ipynb'. Is this a 'parquet' file?: Could not open Parquet input source '.ipynb_checkpoints/test_notebook-checkpoint.ipynb': Parquet magic bytes not found in footer. Either the file is corrupted or this is not a parquet file.\n",
- "2023-12-04 23:37:45,667 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/nuboard/base/experiment_file_data.py:140} Error creating dataset. Could not read schema from 'run_sim_closed_loop/training_raster_experiment/train_default_raster/2023.11.14.22.55.23/hparams.yaml'. Is this a 'parquet' file?: Could not open Parquet input source 'run_sim_closed_loop/training_raster_experiment/train_default_raster/2023.11.14.22.55.23/hparams.yaml': Parquet magic bytes not found in footer. Either the file is corrupted or this is not a parquet file.\n",
- "2023-12-04 23:37:45,667 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/nuboard/base/experiment_file_data.py:140} Could not open Parquet input source '<Buffer>': Parquet magic bytes not found in footer. Either the file is corrupted or this is not a parquet file.\n",
- "2023-12-04 23:37:45,669 INFO {/home/ehdykhne/Repos/nuplan-devkit/nuplan/planning/nuboard/base/simulation_tile.py:172} Minimum frame time=0.017 s\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "Rendering a scenario: 100%|██████████| 1/1 [00:00<00:00, 10.45it/s]\n",
- "WARNING:bokeh.core.validation.check:W-1000 (MISSING_RENDERERS): Plot has no renderers: Figure(id='3857', ...)\n",
- "INFO:tornado.access:200 GET / (10.40.117.44) 805.62ms\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "2023-12-04 23:37:46,467 INFO {/opt/conda/lib/python3.9/site-packages/tornado/web.py:2271} 200 GET / (10.40.117.44) 805.62ms\n",
- "2023-12-04 23:37:46,513 INFO {/home/ehdykhne/Repos/nuplan-devkit/tutorials/utils/tutorial_utils.py:267} Done rendering!\n"
+ "2023-12-05 02:24:53,085 INFO {/home/sacardoz/miniconda3/envs/nuplan/lib/python3.9/site-packages/tornado/web.py:2344} 200 GET /autoload.js?bokeh-autoload-element=1003&bokeh-absolute-url=http://localhost:5008&resources=none (::1) 1379.10ms\n",
+ "2023-12-05 02:24:53,096 INFO {/home/sacardoz/nuplan-devkit/tutorials/utils/tutorial_utils.py:267} Done rendering!\n",
+ "2023-12-05 02:24:53,097 INFO {/home/sacardoz/miniconda3/envs/nuplan/lib/python3.9/site-packages/tornado/web.py:2344} 101 GET /ws?id=5633698c-81fb-4686-8a38-bed76da7b3ba&origin=da2f890a-eb18-4637-9199-dd0f06169aef&swVersion=4&extensionId=&platform=electron&vscode-resource-base-authority=vscode-resource.vscode-cdn.net&parentOrigin=vscode-file%3A%2F%2Fvscode-app&purpose=notebookRenderer (::1) 0.61ms\n"
]
}
],
"source": [
"from tutorials.utils.tutorial_utils import visualize_history\n",
- "visualize_history(runner.simulation._history, runner.scenario, bokeh_port=5006)"
+ "visualize_history(runner.simulation._history, runner.scenario, bokeh_port=5008)"
]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "887a51e2",
- "metadata": {},
- "outputs": [],
- "source": []
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "e0a12035",
- "metadata": {},
- "outputs": [],
- "source": []
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "67b67b86",
- "metadata": {},
- "outputs": [],
- "source": []
}
],
"metadata": {
@@ -963,7 +583,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.9.16"
+ "version": "3.9.18"
}
},
"nbformat": 4,
diff --git a/nuplan/planning/script/config/simulation/default_run_metric_aggregator.yaml b/nuplan/planning/script/config/simulation/default_run_metric_aggregator.yaml
index fdd8aa020519607f56b056ec972afe90676e5a65..443ed41d5fd53e280928b329caaa740e602a1f61 100644
--- a/nuplan/planning/script/config/simulation/default_run_metric_aggregator.yaml
+++ b/nuplan/planning/script/config/simulation/default_run_metric_aggregator.yaml
@@ -13,6 +13,7 @@ defaults:
- open_loop_boxes_weighted_average
- closed_loop_nonreactive_agents_weighted_average
- closed_loop_reactive_agents_weighted_average
+ - closed_loop_multiagent_weighted_average
- override hydra/job_logging: none # Disable hydra's logging
- override hydra/hydra_logging: none # Disable hydra's logging
diff --git a/nuplan/planning/script/config/simulation/metric_aggregator/closed_loop_multiagent_weighted_average.yaml b/nuplan/planning/script/config/simulation/metric_aggregator/closed_loop_multiagent_weighted_average.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..f490e7db9e22021d6adbf58df7db178cfa2ccfe3
--- /dev/null
+++ b/nuplan/planning/script/config/simulation/metric_aggregator/closed_loop_multiagent_weighted_average.yaml
@@ -0,0 +1,19 @@
+closed_loop_reactive_agents_weighted_average:
+ _target_: nuplan.planning.metrics.aggregator.weighted_average_metric_aggregator.WeightedAverageMetricAggregator
+ name: 'closed_loop_multiagent_weighted_average'
+ metric_weights: # Below we list the metrics used in the scenario scoring function and their corresponsing weights to calculate a weighted average score for each scenario,
+ # if not specified, the weight is set as default.
+ # metric name : metric weight in the weighted average function
+ ego_progress_along_expert_route: 5.0 # This metric has the highest weight equal to 5.0 in the weighted average function, its base score can take a value in [0,1] depending on the ratio of ego to expert progress
+ time_to_collision_within_bound: 5.0 # This metric has the highest weight equal to 5.0 in the weighted average function, its base score can be 0 or 1 depending on the minimum time to collision threshold
+ speed_limit_compliance: 4.0 # This metric has a weight equal to 4.0 in the weighted average function, its base score can take a value in [0,1] depending on the amount and duration of over-speeding
+ ego_is_comfortable: 2.0 # This metric has the lowest weight equal to 2.0 in the weighted average function, its base score can be 0 or 1 depending on the comfort thresholds on acceleration, jerk and yaw.
+ default: 1.0
+ file_name: closed_loop_multiagent_weighted_average_metrics_${now:${date_format}}
+ # The scenario score is defined as the weighted average score of the metrics listed above, multiplied by the score of the multiple_metrics below.
+ multiple_metrics:
+ - no_ego_at_fault_collisions # This metric score can be 0, 0.5 or 1 depending on whether there is an at fault collision with VRUs, vehicles or objects
+ - drivable_area_compliance # This metric score can be 0 or 1 depending on whether ego drives outside the drivable area
+ - ego_is_making_progress # This metric score can be 0 or 1 depending on whether ego makes progress more than a minimum threshold compared to expert's progress
+ - driving_direction_compliance # This metric score can be 0 or 0.5 or 1 depending on how much ego drives in the opposite direction if any
+ challenge_name: closed_loop_multiagent
diff --git a/nuplan/planning/script/config/simulation/observation/ml_planner_agents_observation.yaml b/nuplan/planning/script/config/simulation/observation/ml_planner_agents_observation.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..8f84c52cde0754838620a5600154adaa867534ff
--- /dev/null
+++ b/nuplan/planning/script/config/simulation/observation/ml_planner_agents_observation.yaml
@@ -0,0 +1,5 @@
+_target_: nuplan.planning.simulation.observation.ml_planner_agents.MLPlannerAgents
+_convert_: 'all'
+
+model_config: ??? # Dictionary key from existing planner model config (e.g. reactive_agents_model)
+checkpoint_path: ??? # Path to trained model checkpoint
diff --git a/nuplan/planning/script/experiments/simulation/closed_loop_multiagent.yaml b/nuplan/planning/script/experiments/simulation/closed_loop_multiagent.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..5b6d3fa902076cfd3b9053aabe0273b77be88c6d
--- /dev/null
+++ b/nuplan/planning/script/experiments/simulation/closed_loop_multiagent.yaml
@@ -0,0 +1,10 @@
+# @package _global_
+job_name: closed_loop_multiagent
+
+defaults:
+ - override /observation: ml_planner_agents_observation
+ - override /ego_controller: two_stage_controller
+ - override /planner: ml_planner
+ - override /simulation_metric: simulation_closed_loop_reactive_agents
+ - override /metric_aggregator:
+ - closed_loop_multiagent_weighted_average
diff --git a/nuplan/planning/simulation/observation/ml_planner_agents.py b/nuplan/planning/simulation/observation/ml_planner_agents.py
new file mode 100644
index 0000000000000000000000000000000000000000..fb4fa746dc57aa9182773fa363bae20441454582
--- /dev/null
+++ b/nuplan/planning/simulation/observation/ml_planner_agents.py
@@ -0,0 +1,268 @@
+from collections import deque
+from copy import deepcopy
+from typing import Dict, List, Type
+
+from nuplan.common.actor_state.agent import Agent
+from nuplan.common.actor_state.ego_state import EgoState
+from nuplan.common.actor_state.scene_object import SceneObjectMetadata
+from nuplan.common.actor_state.state_representation import StateSE2, StateVector2D, TimePoint
+from nuplan.common.actor_state.tracked_objects import TrackedObject, TrackedObjects
+from nuplan.common.actor_state.tracked_objects_types import TrackedObjectType
+from nuplan.common.actor_state.vehicle_parameters import VehicleParameters
+
+from nuplan.planning.scenario_builder.abstract_scenario import AbstractScenario
+from nuplan.planning.simulation.history.simulation_history_buffer import SimulationHistoryBuffer
+from nuplan.planning.simulation.observation.abstract_observation import AbstractObservation
+from nuplan.planning.simulation.observation.observation_type import Observation
+from nuplan.planning.simulation.observation.observation_type import DetectionsTracks
+from nuplan.planning.simulation.planner.abstract_planner import PlannerInitialization, PlannerInput
+from nuplan.planning.simulation.planner.ml_planner.ml_planner import MLPlanner
+from nuplan.planning.simulation.simulation_time_controller.simulation_iteration import SimulationIteration
+from nuplan.planning.training.modeling.torch_module_wrapper import TorchModuleWrapper
+
+
+OPEN_LOOP_DETECTION_TYPES = [TrackedObjectType.PEDESTRIAN, TrackedObjectType.BICYCLE, \
+ TrackedObjectType.CZONE_SIGN, TrackedObjectType.BARRIER, \
+ TrackedObjectType.TRAFFIC_CONE, TrackedObjectType.GENERIC_OBJECT]
+
+class MLPlannerAgents(AbstractObservation):
+ """
+ Simulate agents based on an ML model.
+ """
+
+ def __init__(self, model: TorchModuleWrapper, scenario: AbstractScenario) -> None:
+ """
+ Initializes the MLPlannerAgents class.
+ :param model: Model to use for inference.
+ :param scenario: scenario
+ """
+ self.current_iteration = 0
+ self.model = model
+ self._scenario = scenario
+ self._ego_state_history: Dict = {}
+ self._agent_prescence_threshold = 10
+ self._agents: Dict = None
+
+ def reset(self) -> None:
+ """Inherited, see superclass."""
+ self.current_iteration = 0
+ self._agents = None
+
+ def _get_agents(self):
+ """
+ Gets dict of tracked agents, or lazily creates them it
+ from vehicles at simulation start if it does not exist.
+ """
+
+ if not self._agents:
+ self._agents = {}
+ for agent in self._scenario.initial_tracked_objects.tracked_objects.get_tracked_objects_of_type(TrackedObjectType.VEHICLE):
+
+
+ # TODO: Support ego controllers - right now just doing perfect tracking.
+ # Revist whether there is a better way of translating agent states to ego states.
+ # Revist whether there is a better way of setting agent goals.
+ # Filter out impossible/off-road initial detections.
+
+ # Sets agent goal to be it's last known point in the simulation. This results in some strange driving behaviour
+ # if the agent disappears early in a scene.
+ goal = None
+
+ for frame in range(self._scenario.get_number_of_iterations()-1, self._agent_prescence_threshold, -1):
+ last_scenario_frame = self._scenario.get_tracked_objects_at_iteration(frame)
+ matched_track = None
+ for track in last_scenario_frame.tracked_objects.tracked_objects:
+ if track.metadata.track_token == agent.metadata.track_token:
+ matched_track = track
+ break
+
+ if matched_track:
+ goal = matched_track.center
+ break
+
+ if goal:
+ # Estimates ego states from agent state at simulation starts, stores metadata and creates planner for each agent
+ self._agents[agent.metadata.track_token] = {'ego_state': self._build_ego_state_from_agent(agent, self._scenario.start_time), \
+ 'metadata': agent.metadata,
+ 'planner': MLPlanner(self.model)}
+ # Initialize planner.
+ planner_init = PlannerInitialization(
+ route_roadblock_ids=self._scenario.get_route_roadblock_ids(),
+ mission_goal=goal,
+ map_api=self._scenario.map_api,
+ )
+
+ self._agents[agent.metadata.track_token]['planner'].initialize(planner_init)
+
+ return self._agents
+
+ def observation_type(self) -> Type[Observation]:
+ """Inherited, see superclass."""
+ return DetectionsTracks # type: ignore
+
+ def initialize(self) -> None:
+ """Inherited, see superclass."""
+ pass
+
+ def get_observation(self) -> DetectionsTracks:
+ """Inherited, see superclass."""
+ agents = [self._build_agent_from_ego_state(v['ego_state'], v['metadata']) for v in self._get_agents().values()]
+ open_loop_detections = self._get_open_loop_track_objects(self.current_iteration)
+ open_loop_detections.extend(agents)
+ return DetectionsTracks(tracked_objects=TrackedObjects(open_loop_detections))
+
+ def update_observation(
+ self, iteration: SimulationIteration, next_iteration: SimulationIteration, history: SimulationHistoryBuffer
+ ) -> None:
+ """Inherited, see superclass."""
+ self.current_iteration = next_iteration.index
+ self.propagate_agents(iteration, next_iteration, history)
+
+ def _get_open_loop_track_objects(self, iteration: int) -> List[TrackedObject]:
+ """
+ Get open-loop tracked objects from scenario.
+ :param iteration: The simulation iteration.
+ :return: A list of TrackedObjects.
+ """
+
+ detections = self._scenario.get_tracked_objects_at_iteration(iteration)
+ return detections.tracked_objects.get_tracked_objects_of_types(OPEN_LOOP_DETECTION_TYPES)
+
+ def propagate_agents(self, iteration: SimulationIteration, next_iteration: SimulationIteration, history: SimulationHistoryBuffer):
+ """
+ Propagates agents into next timestep by constructing input for each agent planner, then interpolating new agent
+ states from the predicted trajectory for each from their respective planners. Caches computed agent states.
+ """
+
+ traffic_light_data = list(self._scenario.get_traffic_light_status_at_iteration(iteration.index))
+
+ # TODO: Find way to parallelize.
+ # TODO: Propagate non-ego and lower frequency to improve performance.
+ for agent_token, agent_data in self._agents.items():
+ history_input = self._build_history_input(agent_token, agent_data['ego_state'], history)
+ planner_input = PlannerInput(iteration=iteration, history=history_input, traffic_light_data=traffic_light_data)
+ trajectory = agent_data['planner'].compute_trajectory(planner_input)
+ agent_data['ego_state'] = trajectory.get_state_at_time(next_iteration.time_point)
+ self._ego_state_history[agent_token][next_iteration.time_point] = agent_data['ego_state']
+
+ def _build_ego_state_from_agent(self, agent: Agent, time_point: TimePoint) -> EgoState:
+ """
+ Builds ego state from corresponding agent state. Since this process is imperfect, it uses cached ego states from the propagation
+ so casting is only required for the beginning agent states for which we have no propagation information.
+ """
+
+ if agent.metadata.track_token in self._ego_state_history:
+ if time_point in self._ego_state_history[agent.metadata.track_token]:
+ return self._ego_state_history[agent.metadata.track_token][time_point]
+ else:
+ self._ego_state_history[agent.metadata.track_token] = {}
+
+ # Most of this is just eyeballed, so there may be a more principled way of setting these values.
+ output = EgoState.build_from_center(
+ center=agent.center,
+ center_velocity_2d=agent.velocity,
+ center_acceleration_2d=StateVector2D(0, 0),
+ tire_steering_angle=0,
+ time_point=time_point,
+ vehicle_parameters=VehicleParameters(
+ vehicle_name=agent.track_token,
+ vehicle_type="gen1",
+ width=agent.box.width,
+ front_length=agent.box.length * 4 / 5,
+ rear_length=agent.box.length * 1 / 5,
+ wheel_base=agent.box.length * 3 / 5,
+ cog_position_from_rear_axle=agent.box.length * 1.5 / 5,
+ height=agent.box.height,
+ ),
+ )
+
+ self._ego_state_history[agent.metadata.track_token][time_point] = output
+ return output
+
+ def _build_agent_from_ego_state(self, ego_state: EgoState, scene_object_metadata: SceneObjectMetadata) -> Agent:
+ """
+ Builds agent state from corresponding ego state. Unlike the inverse this process is well-defined.
+ """
+
+ agent_state = Agent(
+ metadata=scene_object_metadata,
+ tracked_object_type=TrackedObjectType.VEHICLE,
+ oriented_box=ego_state.car_footprint.oriented_box,
+ velocity=ego_state.dynamic_car_state.center_velocity_2d,
+ )
+ return agent_state
+
+ def _build_history_input(self, agent_track_token: str, current_state: EgoState, history: SimulationHistoryBuffer) -> SimulationHistoryBuffer:
+ """
+ Builds the planner history input for a given agent. This requires us the interchange the ego states of the actual ego with the
+ constructed ego states of the agent of interest, and create observations corresponding to the ego in the observation history buffer.
+ """
+ ego_state_buffer = history.ego_state_buffer
+ observation_buffer = history.observation_buffer
+
+ new_observations = []
+ faux_ego_obervations = []
+
+ # Construct a timestep/track_token to observation loopup table for faster proessing
+ track_token_agent_dict = {}
+ for t, observation in enumerate(observation_buffer):
+ track_token_agent_dict[t] = {}
+ for agent in observation.tracked_objects.tracked_objects:
+ track_token_agent_dict[t][agent.metadata.track_token] = agent
+
+ # Loop through history buffer
+ for t, (ego_state, observation) in enumerate(zip(ego_state_buffer, observation_buffer)):
+
+ # Convert actual ego state into agent object
+ ego_agent_object = self._build_agent_from_ego_state(ego_state, \
+ SceneObjectMetadata(token='ego', track_token="ego", track_id=-1, \
+ timestamp_us=ego_state.time_us))
+
+ # Get agent object corresponding to agent from observation buffer. If one does not exist for current timestep, take from the future,
+ # if one does not exist from the future, take the current state. This might occur at the first timestep for observations that have no
+ # logged history prior to simulation start, or observations inserted mid-simulation.
+ matched_agent = None
+
+ for i in range(t, len(observation_buffer)):
+ if i in track_token_agent_dict and agent_track_token in track_token_agent_dict[i]:
+ matched_agent = track_token_agent_dict[i][agent_track_token]
+ break
+
+ # Convert agent state to a corresponding "ego state" object, or pull it from cache if already computed.
+ if matched_agent is None:
+ faux_ego_observation = deepcopy(current_state)
+ faux_ego_observation._time_point = ego_state.time_point
+ else:
+ faux_ego_observation = self._build_ego_state_from_agent(matched_agent, ego_state.time_point)
+
+
+ # Rebuild timestep and buffer - creating a new observations object with old ego appended.
+ tracks = [ag for ag in observation.tracked_objects.tracked_objects if ag.metadata.track_token != agent_track_token]
+ tracks.append(ego_agent_object)
+
+ new_observations.append(DetectionsTracks(tracked_objects=TrackedObjects(tracks)))
+ faux_ego_obervations.append(faux_ego_observation)
+
+
+ output_buffer = SimulationHistoryBuffer(deque(faux_ego_obervations), \
+ deque(new_observations), \
+ history.sample_interval)
+
+ return output_buffer
+
+ def add_agent_to_scene(self, agent: Agent, goal: StateSE2, timepoint_record: TimePoint):
+ """
+ Adds agent to the scene with a given goal during the simulation runtime.
+ """
+ # TODO: Inject IDM agents (and non-ML agents more broadly)
+
+ self._agents[agent.metadata.track_token] = {'ego_state': self._build_ego_state_from_agent(agent, timepoint_record), \
+ 'metadata': agent.metadata,
+ 'planner': MLPlanner(self.model)}
+ planner_init = PlannerInitialization(
+ route_roadblock_ids=self._scenario.get_route_roadblock_ids(),
+ mission_goal=goal,
+ map_api=self._scenario.map_api,
+ )
+
+ self._agents[agent.metadata.track_token]['planner'].initialize(planner_init)