{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Tutorial 1\n", "This shows how qdiv can be used to analyze data from 16S amplicon sequencing experiments. In this tutorial, we focus on preparing the data for analysis, checking the most abundant taxa, and calculating alpha and beta diversity.\n", "\n", "The example data in this tutorial is from an experiment with microbial fuel cells (MFCs) and can be found at [qdiv's github pages](https://github.com/omvatten/qdiv/tree/master/example_files). The data set has 8 samples: 4 samples are from acetate-fed MFCs and 4 are from glucose-fed MFC. The meta data file shows information about the samples.\n", "\n", "## TABLE OF CONTENTS\n", "* [Prepare the data files](#PREPARE-THE-DATA-FILES)\n", "* [A first look at the data](#A-FIRST-LOOK-AT-THE-DATA)\n", "* [Rarefying](#RAREFYING)\n", "* [Alpha diversity](#ALPHA-DIVERSITY)\n", "* [Beta diversity](#BETA-DIVERSITY)\n", "\n", "## PREPARE THE DATA FILES\n", "Let's assume we have two count tables: one generated with DADA2 and one with UNOISE. For each count table we also have a fasta file with the sequences and a meta data file. All files are located in a folder called 'tutorial/'. We will inspect the data, make a consensus count table, and save the results.\n", "* [Inspect the data](#Inspect-the-data)\n", "* [Consensus count table](#Consensus-count-table)\n", "* [Changing taxonomic information](#Changing-taxonomic-information)\n", "* [Save files](#Save-files)\n", "\n", "### Inspect the data\n", "Run the code below to inspect the data." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CHECKING THE DADA2 DATA:\n", "Running files.load .. Done!\n", "Dataframes in object: ['tab', 'ra', 'tax', 'seq', 'meta']\n", "Total number of samples= 8\n", "Total number of ASVs= 108\n", "Total reads= 877889\n", "Minimum number of reads in a sample= 50627\n", "Taxonomic levels: ['Domain', 'Phylum', 'Class', 'Order', 'Family', 'Genus', 'Species']\n", "Column headings in meta data:\n", "['feed', 'order']\n", "First row in meta data:\n", "['acetate', 1]\n", "--------------\n", "CHECKING THE UNOISE DATA:\n", "Running files.load .. Done!\n", "Dataframes in object: ['tab', 'ra', 'seq', 'meta']\n", "Total number of samples= 8\n", "Total number of ASVs= 98\n", "Total reads= 1062191\n", "Minimum number of reads in a sample= 63754\n", "Column headings in meta data:\n", "['feed', 'order']\n", "First row in meta data:\n", "['acetate', 1]\n", "--------------\n" ] } ], "source": [ "import qdiv\n", "\n", "path_to_folder = '../example_files/'\n", "metadata = 'example_metadata.csv'\n", "unoise_tab = 'example_Unoise_table.csv'\n", "unoise_seq = 'example_Unoise_seq.fa'\n", "dada2_tab = 'example_DADA2_table.csv'\n", "dada2_seq = 'example_DADA2_seq.fa'\n", "\n", "#Load the files into qdiv objects and inspect the data\n", "print('CHECKING THE DADA2 DATA:')\n", "dada2_obj = qdiv.files.load(path=path_to_folder, tab=dada2_tab, fasta=dada2_seq, meta=metadata)\n", "qdiv.stats.print_info(dada2_obj)\n", "print('--------------')\n", "\n", "print('CHECKING THE UNOISE DATA:')\n", "unoise_obj = qdiv.files.load(path=path_to_folder, tab=unoise_tab, fasta=unoise_seq, meta=metadata)\n", "qdiv.stats.print_info(unoise_obj)\n", "print('--------------')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We see that we have 8 samples in the data set. We can also see that in the DADA2 count table we have 108 ASVs and in the UNOISE table with have 98. The DADA2 count table also contain taxonomic information, the UNOISE table does not.\n", "We decide to make a consensus table based on the two count tables.\n", "\n", "### Consensus count table\n", "The input to the *subset.consensus* command is a list of the qdiv objects used to build the consensus table. We input the following list \\[dada2_obj, unoise_obj\\]. Since we only have taxonomic information in the DADA2 table, we specify that we want to keep this information in the consensus table. This is done by setting the input parameter *taxa* to the position in the list occupied by the DADA2 object. In Python, the first item in a list is at position 0, so we specify *taxa=0*." ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Running subset.consensus..\n", "Aligning ASVs in 2 objects: 1.. 2.. \n", "Changing ASV names in 2 objects: 1.. 2.. \n", "Done with subset.align_sequences\n", "Done with subset.consensus (note that this function does not keep tree in the object).\n", "{'Kept obj pos': 1, 'Relative abundance (%) of reads associated with retained ASVs': [98.06342259670642, 98.68978366414326], 'Maximum relative abundance (%) of lost reads in a sample': [2.7677307752791322, 2.5104796466388977]}\n" ] } ], "source": [ "cons_obj, info = qdiv.subset.consensus([dada2_obj, unoise_obj], taxa=0)\n", "print(info)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "From the print(info) statement we can see the the object in position 1 in the input list was kept and subsetted to the consensus ASVs (that is the unoise_obj), 98.69% of the reads were associated with consensus ASVs; and in the individual samples, the maximum relative abundance associated with discarded ASVs was 2.51%.\n", "We can also use the qdiv.stats.print_info function to get more information about the consensus object we have generated." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Dataframes in object: ['tab', 'ra', 'seq', 'meta', 'tax']\n", "Total number of samples= 8\n", "Total number of ASVs= 82\n", "Total reads= 1048274\n", "Minimum number of reads in a sample= 62508\n", "Taxonomic levels: ['Domain', 'Phylum', 'Class', 'Order', 'Family', 'Genus', 'Species']\n", "Column headings in meta data:\n", "['feed', 'order']\n", "First row in meta data:\n", "['acetate', 1]\n" ] } ], "source": [ "qdiv.stats.print_info(cons_obj)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here we can see we have a total of 82 ASVs in the consensus object. This can be compared to 108 and 98 ASVs in the original DADA2 and Unoise count tables, respectively.\n", "\n", "### Changing taxonomic information\n", "Let's say we are not happy we the taxonomic information we have in the object and we want to change it. Or perhaps we didn't even have any taxonomic information from the beginning. qdiv has options to add taxonomy from files generated with RDP, sintax, and the SINA classifiers. In this case, we want to add sintax-generated taxonomy from the file Consensus_sintax.txt located in the example_files/ folder." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "cons_obj = qdiv.files.read_sintax(cons_obj, '../example_files/Consensus_sintax.txt')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To check the taxonomy dataframe specifically, we can run the following command using the Python package pandas. (Note that a qdiv object is bunch of pandas dataframes.) " ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " Domain Phylum Class \\\n", "ASV1 d__Bacteria p__Proteobacteria c__Deltaproteobacteria \n", "ASV10 d__Bacteria p__Bacteroidetes c__Bacteroidia \n", "ASV11 d__Bacteria p__Spirochaetes c__Spirochaetia \n", "ASV12 d__Bacteria p__Bacteroidetes c__Bacteroidia \n", "ASV13 d__Bacteria p__Synergistetes c__Synergistia \n", "\n", " Order Family Genus \\\n", "ASV1 NaN NaN NaN \n", "ASV10 o__Bacteroidales f__Rikenellaceae g__midas_g_6724 \n", "ASV11 o__Spirochaetales f__Spirochaetaceae g__midas_g_5121 \n", "ASV12 o__Sphingobacteriales NaN NaN \n", "ASV13 o__Synergistales f__Synergistaceae g__midas_g_249 \n", "\n", " Species \n", "ASV1 NaN \n", "ASV10 s__midas_s_6724 \n", "ASV11 s__midas_s_5121 \n", "ASV12 NaN \n", "ASV13 NaN \n" ] } ], "source": [ "import pandas as pd\n", "print(cons_obj['tax'].head())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Save files\n", "Ok, now we are happy with our consensus object. We save the files to have them for later analysis." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Files saved\n" ] } ], "source": [ "qdiv.files.printout(cons_obj, path='../example_files/', savename='Consensus')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## A FIRST LOOK AT THE DATA\n", "* [Number of different taxa](#Number-of-different-taxa)\n", "* [Heatmap](#Heatmap)\n", "\n", "Ok, we are done with making a consensus table and preparing the data and now want to see how the data looks. First, we load our consensus files into a qdiv object." ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Running files.load .. Done!\n" ] } ], "source": [ "import qdiv\n", "\n", "path_to_folder = '../example_files/'\n", "metadata = 'Consensus_meta.csv'\n", "cons_tab = 'Consensus_table.csv'\n", "cons_seq = 'Consensus_seq.fa'\n", "\n", "obj = qdiv.files.load(path=path_to_folder, tab=cons_tab, fasta=cons_seq, meta=metadata)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now our files are loaded as a qdiv object called *obj*. We will use a heatmap to see the relative abundance of the most abundant taxa and we will save a file with information about the number of different taxa in the samples.\n", "\n", "### Number of different taxa\n", "Here we will get information about the number of different taxa in the samples. The following command will save a csv-file with the name 'Stats_on_taxa.csv' in the folder specified by the variable *path* in the code block above (i.e. '../example_files/'). The results will also be stored in a variable called *results*, which we will display with the print command." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " ASVs Reads Domain Phylum Class Order Family Genus Species\n", "Sample \n", "Total 82 1048274 1 9 17 19 26 31 33\n", "Smp1 64 192457 1 8 14 15 23 26 25\n", "Smp2 67 79318 1 8 15 16 23 27 26\n", "Smp3 68 164746 1 8 16 17 24 28 27\n", "Smp4 66 77709 1 8 15 17 25 29 28\n", "Smp5 69 97577 1 9 15 17 23 28 30\n", "Smp6 71 147216 1 9 17 19 25 29 30\n", "Smp7 67 62508 1 9 16 18 24 28 29\n", "Smp8 71 226743 1 9 17 19 25 29 30\n" ] } ], "source": [ "result = qdiv.stats.taxa(obj, savename=path_to_folder+'Stats_on_taxa')\n", "print(result)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here, we see that in total we have 9 phyla, 17 classes, 19 orders, 26 families, and 31 genera, and 33 different species classified taxonomically in our samples. For 16S amplicon sequencing data we will often get higher numbers under Genus than under Species. The reason is that very few ASVs are classified to the species level.\n", "\n", "### Heatmap\n", "The following command plots a heatmap. We specify that we want to include the 20 most abundant taxa, that the ASVs should be grouped at the genus level, and that the phylum level taxonomy should also be shown. The *plot.heatmap* command has many options for customizing the plot. See the [documentation](https://qdiv.readthedocs.io/en/latest/Plotting.html)." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "application/javascript": [ "/* Put everything inside the global mpl namespace */\n", "/* global mpl */\n", "window.mpl = {};\n", "\n", "mpl.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. 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Matplotlib will then trigger a resize in the client,\n", " // which will in turn request a refresh of the image.\n", " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", "};\n", "\n", "mpl.figure.prototype.send_message = function (type, properties) {\n", " properties['type'] = type;\n", " properties['figure_id'] = this.id;\n", " this.ws.send(JSON.stringify(properties));\n", "};\n", "\n", "mpl.figure.prototype.send_draw_message = function () {\n", " if (!this.waiting) {\n", " this.waiting = true;\n", " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", " }\n", "};\n", "\n", "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", " var format_dropdown = fig.format_dropdown;\n", " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", " fig.ondownload(fig, format);\n", "};\n", "\n", "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", " var size = msg['size'];\n", " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", " fig._resize_canvas(size[0], size[1], msg['forward']);\n", " fig.send_message('refresh', {});\n", " }\n", "};\n", "\n", "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", " var x0 = msg['x0'] / fig.ratio;\n", " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", " var x1 = msg['x1'] / fig.ratio;\n", " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", " x0 = Math.floor(x0) + 0.5;\n", " y0 = Math.floor(y0) + 0.5;\n", " x1 = Math.floor(x1) + 0.5;\n", " y1 = Math.floor(y1) + 0.5;\n", " var min_x = Math.min(x0, x1);\n", " var min_y = Math.min(y0, y1);\n", " var width = Math.abs(x1 - x0);\n", " var height = Math.abs(y1 - y0);\n", "\n", " fig.rubberband_context.clearRect(\n", " 0,\n", " 0,\n", " fig.canvas.width / fig.ratio,\n", " fig.canvas.height / fig.ratio\n", " );\n", "\n", " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", "};\n", "\n", "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", " // Updates the figure title.\n", " fig.header.textContent = msg['label'];\n", "};\n", "\n", "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", " var cursor = msg['cursor'];\n", " switch (cursor) {\n", " case 0:\n", " cursor = 'pointer';\n", " break;\n", " case 1:\n", " cursor = 'default';\n", " break;\n", " case 2:\n", " cursor = 'crosshair';\n", " break;\n", " case 3:\n", " cursor = 'move';\n", " break;\n", " }\n", " fig.rubberband_canvas.style.cursor = cursor;\n", "};\n", "\n", "mpl.figure.prototype.handle_message = function (fig, msg) {\n", " fig.message.textContent = msg['message'];\n", "};\n", "\n", "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", " // Request the server to send over a new figure.\n", " fig.send_draw_message();\n", "};\n", "\n", "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", " fig.image_mode = msg['mode'];\n", "};\n", "\n", "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", " for (var key in msg) {\n", " if (!(key in fig.buttons)) {\n", " continue;\n", " }\n", " fig.buttons[key].disabled = !msg[key];\n", " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", " }\n", "};\n", "\n", "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", " if (msg['mode'] === 'PAN') {\n", " fig.buttons['Pan'].classList.add('active');\n", " fig.buttons['Zoom'].classList.remove('active');\n", " } else if (msg['mode'] === 'ZOOM') {\n", " fig.buttons['Pan'].classList.remove('active');\n", " fig.buttons['Zoom'].classList.add('active');\n", " } else {\n", " fig.buttons['Pan'].classList.remove('active');\n", " fig.buttons['Zoom'].classList.remove('active');\n", " }\n", "};\n", "\n", "mpl.figure.prototype.updated_canvas_event = function () {\n", " // Called whenever the canvas gets updated.\n", " this.send_message('ack', {});\n", "};\n", "\n", "// A function to construct a web socket function for onmessage handling.\n", "// Called in the figure constructor.\n", "mpl.figure.prototype._make_on_message_function = function (fig) {\n", " return function socket_on_message(evt) {\n", " if (evt.data instanceof Blob) {\n", " var img = evt.data;\n", " if (img.type !== 'image/png') {\n", " /* FIXME: We get \"Resource interpreted as Image but\n", " * transferred with MIME type text/plain:\" errors on\n", " * Chrome. But how to set the MIME type? 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", "\n", "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", "mpl.findpos = function (e) {\n", " //this section is from http://www.quirksmode.org/js/events_properties.html\n", " 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 bug\n", " targ = targ.parentNode;\n", " }\n", "\n", " // pageX,Y are the mouse positions relative to the document\n", " 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 keys\n", " * we need this to avoid circular references\n", " * http://stackoverflow.com/a/24161582/3208463\n", " */\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 to\n", " * the text insertion cursor when the button is pressed. We want\n", " * to control all of the cursor setting manually through the\n", " * '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 event\n", "};\n", "\n", "mpl.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", "\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-ignore\n", "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-line\n", "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 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", "\n", "mpl.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", "\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_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", "\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", " '';\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 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", "\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 = '';\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", "\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 '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", "\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+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", "\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 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.\n", "if (IPython.notebook.kernel !== null) {\n", " IPython.notebook.kernel.comm_manager.register_target(\n", " 'matplotlib',\n", " mpl.mpl_figure_comm\n", " );\n", "}\n" ], "text/plain": [ "