From 9001f659645e98fe981d1ac1655ffe8e4cf6e330 Mon Sep 17 00:00:00 2001 From: XyDrKRulof Date: Thu, 14 Nov 2024 13:46:29 +0100 Subject: [PATCH] Updated the GEM_cookbook to work with GEM 3.0.0 and fix issue #225. Additionally, the deprecation error message for the initialization in utils.py was changed from 2.0 to 3.0.0 --- .../environment_features/GEM_cookbook.ipynb | 146 ++++++++++-------- src/gym_electric_motor/utils.py | 2 +- 2 files changed, 84 insertions(+), 64 deletions(-) diff --git a/examples/environment_features/GEM_cookbook.ipynb b/examples/environment_features/GEM_cookbook.ipynb index 176b4fd6..d06ee0fb 100644 --- a/examples/environment_features/GEM_cookbook.ipynb +++ b/examples/environment_features/GEM_cookbook.ipynb @@ -34,23 +34,6 @@ "For this notebook, we can install it by executing the following cell." ] }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "^C\n" - ] - } - ], - "source": [ - "!pip install -q git+https://github.com/upb-lea/gym-electric-motor.git" - ] - }, { "attachments": {}, "cell_type": "markdown", @@ -77,10 +60,11 @@ "- series motor\n", "- shunt motor\n", "\n", - "Two three phase motors:\n", + "Three three phase symchronous motors:\n", "\n", "- PMSM (permanent magnet synchronous motor)\n", "- SynRM (synchronous reluctance motor)\n", + "- EESM (externally excited synchronous motor)\n", "\n", "Two variants of the induction motor:\n", "\n", @@ -170,38 +154,42 @@ "source": [ "When the environment is run in a jupiter notebook, it is recommended to split the enviromnent creation and execution into two cells. Furthermore, the ``visu.initialize()`` call is required. The dashboard is per default the first (and only) visualization in an environment.\n", "\n", - "If the environment is run from a script, the ``visu.initialize()`` call is not necessary." + "If the environment is run from a script, the ``visu.initialize()`` call is not necessary. For execution in Visual Studio Code you might have to install `ipympl`" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 1, "metadata": {}, "outputs": [ { - "name": "stdout", + "name": "stderr", "output_type": "stream", "text": [ - "Warning: Cannot change to a different GUI toolkit: widget. Using notebook instead.\n" + "c:\\Users\\jakobeit\\Anaconda3\\envs\\GEMUpdate\\lib\\site-packages\\gymnasium\\core.py:311: UserWarning: \u001b[33mWARN: env.visualizations to get variables from other wrappers is deprecated and will be removed in v1.0, to get this variable you can do `env.unwrapped.visualizations` for environment variables or `env.get_wrapper_attr('visualizations')` that will search the reminding wrappers.\u001b[0m\n", + " logger.warn(\n" ] }, { "data": { - "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n if (typeof WebSocket !== 'undefined') {\n return WebSocket;\n } else if (typeof MozWebSocket !== 'undefined') {\n return MozWebSocket;\n } else {\n alert(\n 'Your browser does not have WebSocket support. ' +\n 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n 'Firefox 4 and 5 are also supported but you ' +\n 'have to enable WebSockets in about:config.'\n );\n }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n this.id = figure_id;\n\n this.ws = websocket;\n\n this.supports_binary = this.ws.binaryType !== undefined;\n\n if (!this.supports_binary) {\n var warnings = document.getElementById('mpl-warnings');\n if (warnings) {\n warnings.style.display = 'block';\n warnings.textContent =\n 'This browser does not support binary websocket messages. ' +\n 'Performance may be slow.';\n }\n }\n\n this.imageObj = new Image();\n\n this.context = undefined;\n this.message = undefined;\n this.canvas = undefined;\n this.rubberband_canvas = undefined;\n this.rubberband_context = undefined;\n this.format_dropdown = undefined;\n\n this.image_mode = 'full';\n\n this.root = document.createElement('div');\n this.root.setAttribute('style', 'display: inline-block');\n this._root_extra_style(this.root);\n\n parent_element.appendChild(this.root);\n\n this._init_header(this);\n this._init_canvas(this);\n this._init_toolbar(this);\n\n var fig = this;\n\n this.waiting = false;\n\n this.ws.onopen = function () {\n fig.send_message('supports_binary', { value: fig.supports_binary });\n fig.send_message('send_image_mode', {});\n if (fig.ratio !== 1) {\n fig.send_message('set_device_pixel_ratio', {\n device_pixel_ratio: fig.ratio,\n });\n }\n fig.send_message('refresh', {});\n };\n\n this.imageObj.onload = function () {\n if (fig.image_mode === 'full') {\n // Full images could contain transparency (where diff images\n // almost always do), so we need to clear the canvas so that\n // there is no ghosting.\n fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n }\n fig.context.drawImage(fig.imageObj, 0, 0);\n };\n\n this.imageObj.onunload = function () {\n fig.ws.close();\n };\n\n this.ws.onmessage = this._make_on_message_function(this);\n\n this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n var titlebar = document.createElement('div');\n titlebar.classList =\n 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n var titletext = document.createElement('div');\n titletext.classList = 'ui-dialog-title';\n titletext.setAttribute(\n 'style',\n 'width: 100%; 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It doesn't seem\n * to be part of the websocket stream */\n img.type = 'image/png';\n }\n\n /* Free the memory for the previous frames */\n if (fig.imageObj.src) {\n (window.URL || window.webkitURL).revokeObjectURL(\n fig.imageObj.src\n );\n }\n\n fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n img\n );\n fig.updated_canvas_event();\n fig.waiting = false;\n return;\n } else if (\n typeof evt.data === 'string' &&\n evt.data.slice(0, 21) === 'data:image/png;base64'\n ) {\n fig.imageObj.src = evt.data;\n fig.updated_canvas_event();\n fig.waiting = false;\n return;\n }\n\n var msg = JSON.parse(evt.data);\n var msg_type = msg['type'];\n\n // Call the \"handle_{type}\" callback, which takes\n // the figure and JSON message as its only arguments.\n try {\n var callback = fig['handle_' + msg_type];\n } catch (e) {\n console.log(\n \"No handler for the '\" + msg_type + \"' message type: \",\n msg\n );\n return;\n }\n\n if (callback) {\n try {\n // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n callback(fig, msg);\n } catch (e) {\n console.log(\n \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n e,\n e.stack,\n msg\n );\n }\n }\n };\n};\n\nfunction getModifiers(event) {\n var mods = [];\n if (event.ctrlKey) {\n mods.push('ctrl');\n }\n if (event.altKey) {\n mods.push('alt');\n }\n if (event.shiftKey) {\n mods.push('shift');\n }\n if (event.metaKey) {\n mods.push('meta');\n }\n return mods;\n}\n\n/*\n * return a copy of an object with only non-object keys\n * we need this to avoid circular references\n * https://stackoverflow.com/a/24161582/3208463\n */\nfunction simpleKeys(original) {\n return Object.keys(original).reduce(function (obj, key) {\n if (typeof original[key] !== 'object') {\n obj[key] = original[key];\n }\n return obj;\n }, {});\n}\n\nmpl.figure.prototype.mouse_event = function (event, name) {\n if (name === 'button_press') {\n this.canvas.focus();\n this.canvas_div.focus();\n }\n\n // from https://stackoverflow.com/q/1114465\n var boundingRect = this.canvas.getBoundingClientRect();\n var x = (event.clientX - boundingRect.left) * this.ratio;\n var y = (event.clientY - boundingRect.top) * this.ratio;\n\n this.send_message(name, {\n x: x,\n y: y,\n button: event.button,\n step: event.step,\n modifiers: getModifiers(event),\n guiEvent: simpleKeys(event),\n });\n\n return false;\n};\n\nmpl.figure.prototype._key_event_extra = function (_event, _name) {\n // Handle any extra behaviour associated with a key event\n};\n\nmpl.figure.prototype.key_event = function (event, name) {\n // Prevent repeat events\n if (name === 'key_press') {\n if (event.key === this._key) {\n return;\n } else {\n this._key = event.key;\n }\n }\n if (name === 'key_release') {\n this._key = null;\n }\n\n var value = '';\n if (event.ctrlKey && event.key !== 'Control') {\n value += 'ctrl+';\n }\n else if (event.altKey && event.key !== 'Alt') {\n value += 'alt+';\n }\n else if (event.shiftKey && event.key !== 'Shift') {\n value += 'shift+';\n }\n\n value += 'k' + event.key;\n\n this._key_event_extra(event, name);\n\n this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n return false;\n};\n\nmpl.figure.prototype.toolbar_button_onclick = function (name) {\n if (name === 'download') {\n this.handle_save(this, null);\n } else {\n this.send_message('toolbar_button', { name: name });\n }\n};\n\nmpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n this.message.textContent = tooltip;\n};\n\n///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n// prettier-ignore\nvar _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\nmpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n\nmpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n\nmpl.default_extension = \"png\";/* global mpl */\n\nvar comm_websocket_adapter = function (comm) {\n // Create a \"websocket\"-like object which calls the given IPython comm\n // object with the appropriate methods. Currently this is a non binary\n // socket, so there is still some room for performance tuning.\n var ws = {};\n\n ws.binaryType = comm.kernel.ws.binaryType;\n ws.readyState = comm.kernel.ws.readyState;\n function updateReadyState(_event) {\n if (comm.kernel.ws) {\n ws.readyState = comm.kernel.ws.readyState;\n } else {\n ws.readyState = 3; // Closed state.\n }\n }\n comm.kernel.ws.addEventListener('open', updateReadyState);\n comm.kernel.ws.addEventListener('close', updateReadyState);\n comm.kernel.ws.addEventListener('error', updateReadyState);\n\n ws.close = function () {\n comm.close();\n };\n ws.send = function (m) {\n //console.log('sending', m);\n comm.send(m);\n };\n // Register the callback with on_msg.\n comm.on_msg(function (msg) {\n //console.log('receiving', msg['content']['data'], msg);\n var data = msg['content']['data'];\n if (data['blob'] !== undefined) {\n data = {\n data: new Blob(msg['buffers'], { type: data['blob'] }),\n };\n }\n // Pass the mpl event to the overridden (by mpl) onmessage function.\n ws.onmessage(data);\n });\n return ws;\n};\n\nmpl.mpl_figure_comm = function (comm, msg) {\n // This is the function which gets called when the mpl process\n // starts-up an IPython Comm through the \"matplotlib\" channel.\n\n var id = msg.content.data.id;\n // Get hold of the div created by the display call when the Comm\n // socket was opened in Python.\n var element = document.getElementById(id);\n var ws_proxy = comm_websocket_adapter(comm);\n\n function ondownload(figure, _format) {\n window.open(figure.canvas.toDataURL());\n }\n\n var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n\n // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n // web socket which is closed, not our websocket->open comm proxy.\n ws_proxy.onopen();\n\n fig.parent_element = element;\n fig.cell_info = mpl.find_output_cell(\"
\");\n if (!fig.cell_info) {\n console.error('Failed to find cell for figure', id, fig);\n return;\n }\n fig.cell_info[0].output_area.element.on(\n 'cleared',\n { fig: fig },\n fig._remove_fig_handler\n );\n};\n\nmpl.figure.prototype.handle_close = function (fig, msg) {\n var width = fig.canvas.width / fig.ratio;\n fig.cell_info[0].output_area.element.off(\n 'cleared',\n fig._remove_fig_handler\n );\n fig.resizeObserverInstance.unobserve(fig.canvas_div);\n\n // Update the output cell to use the data from the current canvas.\n fig.push_to_output();\n var dataURL = fig.canvas.toDataURL();\n // Re-enable the keyboard manager in IPython - without this line, in FF,\n // the notebook keyboard shortcuts fail.\n IPython.keyboard_manager.enable();\n fig.parent_element.innerHTML =\n '';\n fig.close_ws(fig, msg);\n};\n\nmpl.figure.prototype.close_ws = function (fig, msg) {\n fig.send_message('closing', msg);\n // fig.ws.close()\n};\n\nmpl.figure.prototype.push_to_output = function (_remove_interactive) {\n // Turn the data on the canvas into data in the output cell.\n var width = this.canvas.width / this.ratio;\n var dataURL = this.canvas.toDataURL();\n this.cell_info[1]['text/html'] =\n '';\n};\n\nmpl.figure.prototype.updated_canvas_event = function () {\n // Tell IPython that the notebook contents must change.\n IPython.notebook.set_dirty(true);\n this.send_message('ack', {});\n var fig = this;\n // Wait a second, then push the new image to the DOM so\n // that it is saved nicely (might be nice to debounce this).\n setTimeout(function () {\n fig.push_to_output();\n }, 1000);\n};\n\nmpl.figure.prototype._init_toolbar = function () {\n var fig = this;\n\n var toolbar = document.createElement('div');\n toolbar.classList = 'btn-toolbar';\n this.root.appendChild(toolbar);\n\n function on_click_closure(name) {\n return function (_event) {\n return fig.toolbar_button_onclick(name);\n };\n }\n\n function on_mouseover_closure(tooltip) {\n return function (event) {\n if (!event.currentTarget.disabled) {\n return fig.toolbar_button_onmouseover(tooltip);\n }\n };\n }\n\n fig.buttons = {};\n var buttonGroup = document.createElement('div');\n buttonGroup.classList = 'btn-group';\n var button;\n for (var toolbar_ind in mpl.toolbar_items) {\n var name = mpl.toolbar_items[toolbar_ind][0];\n var tooltip = mpl.toolbar_items[toolbar_ind][1];\n var image = mpl.toolbar_items[toolbar_ind][2];\n var method_name = mpl.toolbar_items[toolbar_ind][3];\n\n if (!name) {\n /* Instead of a spacer, we start a new button group. */\n if (buttonGroup.hasChildNodes()) {\n toolbar.appendChild(buttonGroup);\n }\n buttonGroup = document.createElement('div');\n buttonGroup.classList = 'btn-group';\n continue;\n }\n\n button = fig.buttons[name] = document.createElement('button');\n button.classList = 'btn btn-default';\n button.href = '#';\n button.title = name;\n button.innerHTML = '';\n button.addEventListener('click', on_click_closure(method_name));\n button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n buttonGroup.appendChild(button);\n }\n\n if (buttonGroup.hasChildNodes()) {\n toolbar.appendChild(buttonGroup);\n }\n\n // Add the status bar.\n var status_bar = document.createElement('span');\n status_bar.classList = 'mpl-message pull-right';\n toolbar.appendChild(status_bar);\n this.message = status_bar;\n\n // Add the close button to the window.\n var buttongrp = document.createElement('div');\n buttongrp.classList = 'btn-group inline pull-right';\n button = document.createElement('button');\n button.classList = 'btn btn-mini btn-primary';\n button.href = '#';\n button.title = 'Stop Interaction';\n button.innerHTML = '';\n button.addEventListener('click', function (_evt) {\n fig.handle_close(fig, {});\n });\n button.addEventListener(\n 'mouseover',\n on_mouseover_closure('Stop Interaction')\n );\n buttongrp.appendChild(button);\n var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n titlebar.insertBefore(buttongrp, titlebar.firstChild);\n};\n\nmpl.figure.prototype._remove_fig_handler = function (event) {\n var fig = event.data.fig;\n if (event.target !== this) {\n // Ignore bubbled events from children.\n return;\n }\n fig.close_ws(fig, {});\n};\n\nmpl.figure.prototype._root_extra_style = function (el) {\n el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n};\n\nmpl.figure.prototype._canvas_extra_style = function (el) {\n // this is important to make the div 'focusable\n el.setAttribute('tabindex', 0);\n // reach out to IPython and tell the keyboard manager to turn it's self\n // off when our div gets focus\n\n // location in version 3\n if (IPython.notebook.keyboard_manager) {\n IPython.notebook.keyboard_manager.register_events(el);\n } else {\n // location in version 2\n IPython.keyboard_manager.register_events(el);\n }\n};\n\nmpl.figure.prototype._key_event_extra = function (event, _name) {\n // Check for shift+enter\n if (event.shiftKey && event.which === 13) {\n this.canvas_div.blur();\n // select the cell after this one\n var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n IPython.notebook.select(index + 1);\n }\n};\n\nmpl.figure.prototype.handle_save = function (fig, _msg) {\n fig.ondownload(fig, null);\n};\n\nmpl.find_output_cell = function (html_output) {\n // Return the cell and output element which can be found *uniquely* in the notebook.\n // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n // IPython event is triggered only after the cells have been serialised, which for\n // our purposes (turning an active figure into a static one), is too late.\n var cells = IPython.notebook.get_cells();\n var ncells = cells.length;\n for (var i = 0; i < ncells; i++) {\n var cell = cells[i];\n if (cell.cell_type === 'code') {\n for (var j = 0; j < cell.output_area.outputs.length; j++) {\n var data = cell.output_area.outputs[j];\n if (data.data) {\n // IPython >= 3 moved mimebundle to data attribute of output\n data = data.data;\n }\n if (data['text/html'] === html_output) {\n return [cell, data, j];\n }\n }\n }\n }\n};\n\n// Register the function which deals with the matplotlib target/channel.\n// The kernel may be null if the page has been refreshed.\nif (IPython.notebook.kernel !== null) {\n IPython.notebook.kernel.comm_manager.register_target(\n 'matplotlib',\n mpl.mpl_figure_comm\n );\n}\n", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "0e429b867d7246fab80aa8287e110e80", + "version_major": 2, + "version_minor": 0 + }, + "image/png": 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Therefore the VersionID equals `v0`. Future versions will be named `v1, v2,...`.\n", " \n" @@ -306,7 +305,7 @@ " * `my_reference_generator = SinusoidalReferenceGenerator(amplitude_range=(0.2,0.8))`\n", " * The reference generator instance will be used in the environment.\n", "\n", - "* Passing a keystring:\n", + "* Passing a keystring **(deprecated with GEM 3.0.0)**:\n", " * `my_reference_generator='SinusoidalReference'`\n", " * The Sinusoidal Reference Generator will be used in the environment with its default parameters.\n", " * Equals: `my_reference_generator=SinusoidalReferenceGenerator()`\n", @@ -350,7 +349,9 @@ "metadata": {}, "outputs": [], "source": [ - "supply = 'IdealVoltageSupply'" + "from gym_electric_motor.physical_systems.voltage_supplies import IdealVoltageSupply\n", + "\n", + "supply = IdealVoltageSupply(u_nominal=350)" ] }, { @@ -405,7 +406,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -448,7 +449,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -471,7 +472,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -505,7 +506,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -542,7 +543,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -604,7 +605,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -634,7 +635,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -644,6 +645,25 @@ "# plots the states i_sd and i_sq and reward." ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 2.7 ODE Solvers\n", + "\n", + "In GEM, all motor classes are simulated by their respective ODEs. To solve these ODEs, different solvers are available such as the EulerSolver which utilized the Euler discretization. All Scipy solvers are available using GEM's built-in wrapper classes such as `ScipyOdeSolver`." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "from gym_electric_motor.physical_systems.solvers import EulerSolver\n", + "ode_solver = EulerSolver()" + ] + }, { "attachments": {}, "cell_type": "markdown", @@ -673,7 +693,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ @@ -721,7 +741,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 13, "metadata": {}, "outputs": [], "source": [ @@ -759,7 +779,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ @@ -834,7 +854,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 15, "metadata": {}, "outputs": [], "source": [ @@ -857,7 +877,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 16, "metadata": {}, "outputs": [], "source": [ @@ -877,9 +897,9 @@ " load=load,\n", " reward_function=rf,\n", " tau=tau,\n", - " #supply=supply,\n", + " supply=supply,\n", " reference_generator=rg,\n", - " ode_solver='euler',\n", + " ode_solver=ode_solver,\n", " callbacks=my_callback,\n", " physical_system_wrappers=physical_system_wrappers, # Pass the Physical System Wrappers\n", " constraints=constraints\n", @@ -891,7 +911,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### 2.9 Seeding\n", + "### 2.10 Seeding\n", "The random processes in the environment can be made reproducible by seeding the environments. The seeding takes place when resetting an environment, i.e. calling `env.reset(seed=seed)` with the keyword argument `seed`. " ] }, @@ -919,18 +939,18 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "da30fd6221fe4677b48a6d6c5295cadb", + "model_id": "d444ae6c11974e51b98d78dc2093d7ac", "version_major": 2, "version_minor": 0 }, - "image/png": 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", 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", 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