{
“cells”: [
{

“cell_type”: “markdown”, “metadata”: {}, “source”: [

“# Surface animationsn”, “n”, “Here we show how to make animations of surface plots.n”, “n”, “First we need some imports:”

]

}, {

“cell_type”: “code”, “execution_count”: 1, “metadata”: {}, “outputs”: [], “source”: [

“%matplotlib notebookn”, “import numpy as npn”, “import matplotlib.pyplot as pltn”, “import animatplot as amp”

]

}, {

“cell_type”: “markdown”, “metadata”: {}, “source”: [

“Let’s use: $z = \sin(x^2+y^2-t)$.n”, “n”, “First, we generate the data.”

]

}, {

“cell_type”: “code”, “execution_count”: 2, “metadata”: {}, “outputs”: [], “source”: [

“x = np.linspace(-2, 2, 41)n”, “y = np.linspace(-2, 2, 41)n”, “t = np.linspace(0, 2 * np.pi, 30)n”, “n”, “X, Y, T = np.meshgrid(x, y, t)n”, “n”, “data = np.sin(X * X + Y * Y - T)”

]

}, {

“cell_type”: “markdown”, “metadata”: {}, “source”: [

“We need to be careful here. Our time axis is the last axis of our data, but animatplot assumes it is the first axis by default. Fortunately, we can use the `t_axis` argument.n”, “n”, “We need to create a special Axes object with a 3d projection to make surface animations. Here we do this by using plt.subplots(subplot_kw={"projection": "3d"}). In more complicated situations, you might need to pass an axes argument for various subplots, but here we only have one subplot, so we do not need to pass in the axes as animatplot can pick them up using plt.gca().”

]

}, {

“cell_type”: “code”, “execution_count”: 3, “metadata”: {

“scrolled”: false

}, “outputs”: [

{
“data”: {
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But how to set the MIME type? It doesn’t seemn”, “ * 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.srcn”, “ );n”, “ }n”, “n”, “ fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(n”, “ imgn”, “ );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 takesn”, “ // 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”, “ msgn”, “ );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”, “ msgn”, “ );n”, “ }n”, “ }n”, “ };n”, “};n”, “n”, “// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvasn”, “mpl.findpos = function (e) {n”, “ //this section is from http://www.quirksmode.org/js/events_properties.htmln”, “ var targ;n”, “ if (!e) {n”, “ e = window.event;n”, “ }n”, “ if (e.target) {n”, “ targ = e.target;n”, “ } else if (e.srcElement) {n”, “ targ = e.srcElement;n”, “ }n”, “ if (targ.nodeType === 3) {n”, “ // defeat Safari bugn”, “ targ = targ.parentNode;n”, “ }n”, “n”, “ // pageX,Y are the mouse positions relative to the documentn”, “ var boundingRect = targ.getBoundingClientRect();n”, “ var x = e.pageX - (boundingRect.left + document.body.scrollLeft);n”, “ var y = e.pageY - (boundingRect.top + document.body.scrollTop);n”, “n”, “ return { x: x, y: y };n”, “};n”, “n”, “/n”, “ * return a copy of an object with only non-object keysn”, “ * we need this to avoid circular referencesn”, “ * http://stackoverflow.com/a/24161582/3208463n”, “ /n”, “function 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”, “n”, “mpl.figure.prototype.mouse_event = function (event, name) {n”, “ var canvas_pos = mpl.findpos(event);n”, “n”, “ if (name === ‘button_press’) {n”, “ this.canvas.focus();n”, “ this.canvas_div.focus();n”, “ }n”, “n”, “ var x = canvas_pos.x * this.ratio;n”, “ var y = canvas_pos.y * this.ratio;n”, “n”, “ this.send_message(name, {n”, “ x: x,n”, “ y: y,n”, “ button: event.button,n”, “ step: event.step,n”, “ guiEvent: simpleKeys(event),n”, “ });n”, “n”, “ / This prevents the web browser from automatically changing ton”, “ * the text insertion cursor when the button is pressed. We wantn”, “ * to control all of the cursor setting manually through then”, “ * ‘cursor’ event from matplotlib /n”, “ event.preventDefault();n”, “ return false;n”, “};n”, “n”, “mpl.figure.prototype._key_event_extra = function (_event, _name) {n”, “ // Handle any extra behaviour associated with a key eventn”, “};n”, “n”, “mpl.figure.prototype.key_event = function (event, name) {n”, “ // Prevent repeat eventsn”, “ 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”, “n”, “mpl.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”, “n”, “mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {n”, “ this.message.textContent = tooltip;n”, “};n”, “n”, “///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////n”, “// prettier-ignoren”, “var _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-linen”, “mpl.toolbar_items = [["Home", "Reset original view", "fa fa-home icon-home", "home"], ["Back", "Back to previous view", "fa fa-arrow-left icon-arrow-left", "back"], ["Forward", "Forward to next view", "fa fa-arrow-right icon-arrow-right", "forward"], ["", "", "", ""], ["Pan", "Left button pans, Right button zooms\nx/y fixes axis, CTRL fixes aspect", "fa fa-arrows icon-move", "pan"], ["Zoom", "Zoom to rectangle\nx/y fixes axis, CTRL fixes aspect", "fa fa-square-o icon-check-empty", "zoom"], ["", "", "", ""], ["Download", "Download plot", "fa fa-floppy-o icon-save", "download"]];n”, “n”, “mpl.extensions = ["eps", "jpeg", "pgf", "pdf", "png", "ps", "raw", "svg", "tif"];n”, “n”, “mpl.default_extension = "png";/ global mpl /n”, “n”, “var comm_websocket_adapter = function (comm) {n”, “ // Create a "websocket"-like object which calls the given IPython commn”, “ // object with the appropriate methods. Currently this is a non binaryn”, “ // 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”, “n”, “mpl.mpl_figure_comm = function (comm, msg) {n”, “ // This is the function which gets called when the mpl processn”, “ // 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 Commn”, “ // 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 realn”, “ // 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("<div id=’" + id + "’></div>");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_handlern”, “ );n”, “};n”, “n”, “mpl.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_handlern”, “ );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”, “ ‘<img src="’ + dataURL + ‘" width="’ + width + ‘">’;n”, “ fig.close_ws(fig, msg);n”, “};n”, “n”, “mpl.figure.prototype.close_ws = function (fig, msg) {n”, “ fig.send_message(‘closing’, msg);n”, “ // fig.ws.close()n”, “};n”, “n”, “mpl.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”, “ ‘<img src="’ + dataURL + ‘" width="’ + width + ‘">’;n”, “};n”, “n”, “mpl.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 son”, “ // that it is saved nicely (might be nice to debounce this).n”, “ setTimeout(function () {n”, “ fig.push_to_output();n”, “ }, 1000);n”, “};n”, “n”, “mpl.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 = ‘<i class="fa ‘ + image + ‘ fa-lg"></i>’;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 = ‘<i class="fa fa-power-off icon-remove icon-large"></i>’;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”, “n”, “mpl.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”, “n”, “mpl.figure.prototype._root_extra_style = function (el) {n”, “ el.style.boxSizing = ‘content-box’; // override notebook setting of border-box.n”, “};n”, “n”, “mpl.figure.prototype._canvas_extra_style = function (el) {n”, “ // this is important to make the div ‘focusablen”, “ el.setAttribute(‘tabindex’, 0);n”, “ // reach out to IPython and tell the keyboard manager to turn it’s selfn”, “ // off when our div gets focusn”, “n”, “ // location in version 3n”, “ if (IPython.notebook.keyboard_manager) {n”, “ IPython.notebook.keyboard_manager.register_events(el);n”, “ } else {n”, “ // location in version 2n”, “ IPython.keyboard_manager.register_events(el);n”, “ }n”, “};n”, “n”, “mpl.figure.prototype._key_event_extra = function (event, _name) {n”, “ var manager = IPython.notebook.keyboard_manager;n”, “ if (!manager) {n”, “ manager = IPython.keyboard_manager;n”, “ }n”, “n”, “ // Check for shift+entern”, “ if (event.shiftKey && event.which === 13) {n”, “ this.canvas_div.blur();n”, “ // select the cell after this onen”, “ var index = IPython.notebook.find_cell_index(this.cell_info[0]);n”, “ IPython.notebook.select(index + 1);n”, “ }n”, “};n”, “n”, “mpl.figure.prototype.handle_save = function (fig, _msg) {n”, “ fig.ondownload(fig, null);n”, “};n”, “n”, “mpl.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 forn”, “ // 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 outputn”, “ 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.n”, “if (IPython.notebook.kernel !== null) {n”, “ IPython.notebook.kernel.comm_manager.register_target(n”, “ ‘matplotlib’,n”, “ mpl.mpl_figure_commn”, “ );n”, “}n”

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], “text/plain”: [

“<IPython.core.display.HTML object>”

]

}, “metadata”: {}, “output_type”: “display_data”

}

], “source”: [

“# standard matplotlib stuffn”, “# create the different plotting axesn”, “fig, ax = plt.subplots(subplot_kw={"projection": "3d"})n”, “n”, “ax.set_xlabel("x")n”, “ax.set_ylabel("y")n”, “ax.set_zlabel("z")n”, “n”, “# animatplot stuffn”, “# now we make our blockn”, “n”, “block = amp.blocks.Surface(X[:, :, 0], Y[:, :, 0], data, t_axis=2)n”, “timeline = amp.Timeline(t, fps=10)n”, “n”, “# now to contruct the animationn”, “anim = amp.Animation([block], timeline)n”, “anim.controls()n”, “n”, “anim.save_gif("images/surface")n”, “plt.show()”

]

}, {

“cell_type”: “markdown”, “metadata”: {}, “source”: [

“There is a lot going on here so lets break it down.n”, “n”, “Firstly, the `standard matplotlib stuff` is creating, and labeling all of our axes for our subplot. This is exactly how one might do a static, non-animated plot.n”, “n”, “When we make the Surface block, we pass in the x, y data as 2D arrays (`X[:,:,0]` and `Y[:,:,0]`), and the z data as a 3D array. We also specifify that the time axis is the last axis of the data `t_axis=2`.n”, “n”, “To set the axis limits, you need to use ax.set_xlim(), ax.set_ylim() and ax.set_zlim(). The keywords `vmin`, and `vmax` control the color scale if you pass a cmap argument.n”, “n”, “The rest simply brings the block and the timeline together into an animation.”

]

}, {

“cell_type”: “raw”, “metadata”: {

“raw_mimetype”: “text/restructuredtext”

}, “source”: [

“.. image:: surface.gif”

]

}, {

“cell_type”: “code”, “execution_count”: null, “metadata”: {}, “outputs”: [], “source”: []

}

], “metadata”: {

“celltoolbar”: “Raw Cell Format”, “kernelspec”: {

“display_name”: “Python 3”, “language”: “python”, “name”: “python3”

}, “language_info”: {

“codemirror_mode”: {

“name”: “ipython”, “version”: 3

}, “file_extension”: “.py”, “mimetype”: “text/x-python”, “name”: “python”, “nbconvert_exporter”: “python”, “pygments_lexer”: “ipython3”, “version”: “3.8.6”

}

}, “nbformat”: 4, “nbformat_minor”: 2

}