astrometry.ipynb

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    "# Astrometry (WIP)\n",
    "\n",
    "Lets study and implement an alternative to [astrometry.net](https://astrometry.net) in pure-python. There is an implementation currently available called [twirl](https://github.com/lgrcia/twirl), that uses the same algorithms, but is pure-python. However, this implementation seems to fail on our tests, probably due to not use gnomonic tangencial projection for the catalog.\n",
    "\n",
    "## Astrometry.net Algorithm\n",
    "\n",
    "Astrometry.net algorithm, described by [Lang et. al. (2010)](https://ui.adsabs.harvard.edu/abs/2010AJ....139.1782L) uses asterism matching between quads in a catalog and quads in the image that will be solved.\n",
    "\n",
    "These quads are organized in a way that the most distant stars form a primary diagonal of a ortogonal xy axis and one of the stars ($A$) correspond to coordinate $(0, 0)$ and the other ($B$) correspond to coordinate $(1, 1)$. With these axis defined, the other two stars ($C$ and $D$) are projected in the axis and their x and y coordinates form a quad *hash*, defined and $[Cx, Cy, Dx, Dy]$. A good quad, acoording Lang, respect the following rules:\n",
    "- $C_x <= D_x$\n",
    "- $C_x+D_x <= 1$\n",
    "- All stars must be contained in a circle with radius $\\sqrt{2}/2$ and centered in the middle point between A and B.\n",
    "\n",
    "These quads are generated in image and catalog stars. After the creation, a KD-Tree is created for the catalog quads hashes. The maching is performed using quering the closest neighbor of a quad from the image in the KD-Tree.\n",
    "\n",
    "With a good match, all image stars are transformed and matched to the catalog. If the percentage of stars that match the catalog is bellow a tolerance, the operation is repeated with another quad.\n",
    "\n",
    "With the stars matched in the catalog, the $(x, y)$ pixels are related to their correspondent $(ra, dec)$ world coordinates and a WCS is fitted.\n",
    "\n",
    "## Our Approach\n",
    "\n",
    "We want to be able to:\n",
    "- Operate online (downloading catalogs from server) or offline (using astrometry.net local indexes? or local downloaded simplified catalog).\n",
    "- Use proper motions to fix the positions of the stars to dates.\n",
    "- Handle flipped images. When an quad has its coordinates flipped horizontally (or vertically), the $x$ and $y$ local coordinates of the hash are flipped for each star.\n",
    "- ...?"
   ]
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   "source": [
    "from astropy.io import fits\n",
    "import numpy as np\n",
    "from astropy import units as u\n",
    "from astropy.coordinates import SkyCoord\n",
    "from matplotlib import pyplot as plt\n",
    "from astropop.photometry import starfind\n",
    "from astropop.logger import logger\n",
    "logger.setLevel('DEBUG')\n",
    "%matplotlib notebook"
   ]
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  {
   "cell_type": "code",
   "execution_count": 5,
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   "source": [
    "data = fits.getdata('/home/julio/astropop-tutorial/photometry-example/reduced/HD5980_V_0.fits')\n",
    "center = SkyCoord('00h59m56s -72d09m53s')\n",
    "center = [center.ra.value, center.dec.value]\n",
    "fov = 1.0  # degree"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
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    {
     "name": "stderr",
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     "text": [
      "2022-03-26 11:21:27,713 astropop - DEBUG - Relative error computed from FWHM: 1.193839  [detection]\n",
      "2022-03-26 11:21:27,723 astropop - DEBUG - Found 1438 pixels above threshold  [detection]\n",
      "2022-03-26 11:21:27,724 astropop - DEBUG - 189 localmaxima located above threshold.  [detection]\n",
      "2022-03-26 11:21:27,753 astropop - DEBUG - merging 186 close stars in 186 sources  [detection]\n",
      "2022-03-26 11:21:27,756 astropop - DEBUG - merging 186 close stars in 186 sources  [detection]\n",
      "2022-03-26 11:21:27,756 astropop - DEBUG - 1 sources rejected by sharpness  [detection]\n",
      "2022-03-26 11:21:27,757 astropop - DEBUG - 6 sources rejected by roundness  [detection]\n",
      "2022-03-26 11:21:27,757 astropop - DEBUG - 0 sources rejected by invalid centroid  [detection]\n"
     ]
    },
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       "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 https://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",
       " * https://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\", \"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(\"<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_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",
       "        '<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 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 = '<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 '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",
       "    // 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": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f39746c86d0>]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "med = np.median(data)\n",
    "hd5980 = starfind(data, threshold=1, background=med, noise=np.std(data))\n",
    "plt.figure(figsize=(8,8))\n",
    "plt.imshow(data, cmap=\"Greys_r\", vmax=np.std(data)*5 + med, vmin=med)\n",
    "plt.plot(hd5980['x'], hd5980['y'], \"o\", fillstyle=\"none\", c=\"w\", ms=12)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Implementation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from itertools import combinations\n",
    "\n",
    "\n",
    "SQRT_TWO_OVER_TWO = np.sqrt(2)/2\n",
    "SQRT_TWO = np.sqrt(2)\n",
    "\n",
    "\n",
    "def _total_combinations(n, k):\n",
    "    \"\"\"Compute the total number of combinations.\"\"\"\n",
    "    def _fac(x):\n",
    "        return np.prod(np.arange(2, x+1), dtype='f16')\n",
    "    return int(_fac(n)/(_fac(k)*_fac(n-k)))\n",
    "\n",
    "\n",
    "# rotation matrixes\n",
    "rot_mat_p = [[SQRT_TWO_OVER_TWO, -SQRT_TWO_OVER_TWO],\n",
    "             [SQRT_TWO_OVER_TWO, SQRT_TWO_OVER_TWO]]\n",
    "rot_mat_m = [[SQRT_TWO_OVER_TWO, SQRT_TWO_OVER_TWO],\n",
    "             [-SQRT_TWO_OVER_TWO, SQRT_TWO_OVER_TWO]]\n",
    "\n",
    "\n",
    "def _get_axis(a, b):\n",
    "    \"\"\"Get the quad-defined xy axis.\"\"\"\n",
    "    vec = b - a\n",
    "    norm = np.hypot(*vec)\n",
    "    x = -np.cross(vec, rot_mat_p)/norm\n",
    "    y = np.cross(vec, rot_mat_m)/norm\n",
    "    \n",
    "    # unitary x,y vectors\n",
    "    return x, y\n",
    "\n",
    "\n",
    "def _hash_quad(a, b, c, d):\n",
    "    \"\"\"Compute the quad hash.\"\"\"\n",
    "    # get x,y axis and project normalized c and d in the axis\n",
    "    axis = _get_axis(a, b)\n",
    "    # b has normalized coordinates 1, so axis have lenght sqrt(2)/2\n",
    "    norm = np.hypot(*(b-a))/SQRT_TWO\n",
    "\n",
    "    c_proj = (c-a)/norm\n",
    "    c_proj = np.dot(c_proj, axis[0]), np.dot(c_proj, axis[1])\n",
    "    d_proj = (d-a)/norm\n",
    "    d_proj = np.dot(d_proj, axis[0]), np.dot(d_proj, axis[1])\n",
    "    return np.array([*c_proj, *d_proj])\n",
    "\n",
    "\n",
    "def _break_quad_symetry(quad_indx, quad_hash):\n",
    "    \"\"\"Check the quad and tries to flip if necessary.\"\"\"\n",
    "    # this needs flipping a and b\n",
    "    if quad_hash[0]+quad_hash[2] > 1:\n",
    "        # quad[:2] = [quad[1], quad[0]]\n",
    "        quad_indx[:2] = [quad_indx[1], quad_indx[0]]\n",
    "        # new = 1 - old\n",
    "        quad_hash = 1-quad_hash\n",
    "    \n",
    "    # this needs to flip c and d\n",
    "    if quad_hash[0] > quad_hash[2]:\n",
    "        # quad[2:] = [quad[3], quad[2]]\n",
    "        quad_indx[2:] = [quad_indx[3], quad_indx[2]]\n",
    "        # just invert the order\n",
    "        quad_hash = np.array([*quad_hash[2:], *quad_hash[:2]])\n",
    "    \n",
    "    # TODO: it looks like all quads get out of here good\n",
    "    return quad_indx, quad_hash\n",
    "\n",
    "\n",
    "def _make_quad(stars, indx):\n",
    "    \"\"\"Make a single quad using Lang 2010 convention.\"\"\"\n",
    "    indx = np.array(indx)\n",
    "    s = stars[indx]\n",
    "\n",
    "    # compute the distance between each pair of srcs\n",
    "    ds = np.linalg.norm(s[:, :, None] - s.T[None, :, :], axis=1)\n",
    "    # find the first star of the most distant pair\n",
    "    # the first index is star a and second is star b\n",
    "    max_dist = np.max(ds)\n",
    "    ai, bi = np.unravel_index(np.argmax(ds), ds.shape)\n",
    "    a, b = s[[ai, bi]]\n",
    "    ai, bi = indx[[ai, bi]]\n",
    "\n",
    "    ci, di = [i for i in indx if i not in (ai, bi)]\n",
    "    c, d = stars[[ci, di]]\n",
    "    center = (a+b)/2\n",
    "    r = np.hypot(*(b-a))/2\n",
    "    if np.abs(np.hypot(*(c-center))) > r or np.abs(np.hypot(*(d-center))) > r:\n",
    "        # logger.debug('quad (%f,%f) (%f,%f) (%f,%f) (%f,%f) rejected by circle', *a, *b, *c, *d)\n",
    "        return None, None\n",
    "\n",
    "    quad_indx = np.array([ai, bi, ci, di])\n",
    "    quad_hash = _hash_quad(a, b, c, d)\n",
    "    \n",
    "    quad_indx, quad_hash = _break_quad_symetry(quad_indx, quad_hash)\n",
    "    \n",
    "    return quad_indx, quad_hash\n",
    "\n",
    "\n",
    "def tangential_projection(coords, center, pixel_scale=1./3600.):\n",
    "    \"\"\"Project a list of (ra, dec) coordinates using gnomonic tangential projetion.\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    coords : `~astropy.coordinates.SkyCoord` or list\n",
    "        List of coordinates to project. If a list is passed, it must be (n, 2)\n",
    "        dimention containing decimal degrees RA and DEC coordinates.\n",
    "    center : `~astropy.coordinates.SkyCoord` or list\n",
    "        Coordinates of the center ofthe tangential plane. If a list, it must have\n",
    "        length 2 and contain decimal degrees of RA and DEC coordinates.\n",
    "    pixel_scale : float (optional)\n",
    "        Angular size of each pixel (or unit) in the tangential plane.\n",
    "        Default: 1./3600. (1 arcsec/px)\n",
    "    \n",
    "    Returns\n",
    "    -------\n",
    "    list :\n",
    "        list containing (x, y) coordinates projected in the plane for each\n",
    "        input position. (n, 2) dimension.\n",
    "    \"\"\"\n",
    "    if isinstance(coords, (list, tuple, np.ndarray)):\n",
    "        coords = SkyCoord(coords, unit='deg')\n",
    "    if not isinstance(coords, SkyCoord):\n",
    "        raise TypeError('coords must by SkyCoord compatible.')\n",
    "    \n",
    "    if not isinstance(center, SkyCoord):\n",
    "        center = SkyCoord(*center, unit='deg')\n",
    "    \n",
    "    center = [center.ra.degree, center.dec.degree]\n",
    "    \n",
    "    w = WCS(naxis=2)\n",
    "    w.wcs.crpix = [0, 0]\n",
    "    w.wcs.crval = center\n",
    "    w.wcs.ctype = ['RA---TAN', 'DEC--TAN']\n",
    "    w.wcs.cdelt = [pixel_scale, pixel_scale]\n",
    "    \n",
    "    return np.transpose(coords.to_pixel(w))\n",
    "\n",
    "\n",
    "class AstrometrySolver:\n",
    "    \"\"\"Astrometry solver using a Astrometry.net algorithm.\n",
    "\n",
    "    This class reimplements in pure-python the algorithm os Astrometry.net[1]_\n",
    "    software. It uses special 4-stars asterisms to match the stars in a online\n",
    "    catalog and uses it to find a initial astrometric solution.\n",
    "\n",
    "    After the other stars have their coordinates determined and matched in the\n",
    "    catalog and, for the final solution, all matched stars are used in a WCS\n",
    "    fitting using astropy routines. For more details, check [2]_.\n",
    "\n",
    "    Differently from the original astrometry.net, this code is not meant to\n",
    "    operate blindly. We must guess the center of the field and the search\n",
    "    radius.\n",
    "\n",
    "    References\n",
    "    ----------\n",
    "    .. [1] `astrometry.net <https://astrometry.net>`_\n",
    "    .. [2] :DOI:`10.1088/0004-6256/139/5/1782`\n",
    "    \"\"\"\n",
    "\n",
    "    def __init__(self, tolerance=0.5, catalog='gaia',\n",
    "                 max_catalog_sources=2000):\n",
    "        \"\"\"Initialize the AstrometrySolver.\n",
    "\n",
    "        Parameters\n",
    "        ----------\n",
    "        tolerance : float, optional\n",
    "            The minimum fraction of the field stars that must match stars in\n",
    "            the online catalog.\n",
    "            Default: 0.5\n",
    "        catalog : {'gaia'}, optional\n",
    "            Catalog to be used in astrometric solution.\n",
    "            Default: 'gaia'\n",
    "        max_catalog_sources : int, optional\n",
    "            Maximum number of stars from the catalog to be used to compute\n",
    "            the astrometric solution.\n",
    "            Default: 2000\n",
    "        \"\"\"\n",
    "\n",
    "    def _compute_quads(self, points, max_quads=1000, use_flipped=False):\n",
    "        \"\"\"Compute the quads.\"\"\"\n",
    "        n = len(points)\n",
    "        points = np.array(points)\n",
    "        if n < 4:\n",
    "            raise ValueError('We need at least 4 sources to compute quads.')\n",
    "        if points.shape[1] != 2:\n",
    "            raise ValueError('Each point must have 2 coordinates. '\n",
    "                             f'{points.shape[1]} found.')\n",
    "\n",
    "        if max_quads < 1 or max_quads is None or np.isnan(max_quads):\n",
    "            # Undefined goes to inf\n",
    "            max_quads = np.inf\n",
    "\n",
    "        if _total_combinations(len(points), 4) < max_quads:\n",
    "            # use all quads\n",
    "            logger.debug('Using all %i combinations.',\n",
    "                         _total_combinations(len(points), 4))\n",
    "            for indx in combinations(np.arange(n), 4):\n",
    "                yield _make_quad(points, indx)\n",
    "                # TODO: flipped here\n",
    "        else:\n",
    "            # choose random quads\n",
    "            logger.debug('Using random %i combinations.', max_quads)\n",
    "            n_quads = 0\n",
    "            while n_quads < max_quads:\n",
    "                # Select random 4 stars\n",
    "                indx = np.random.choice(len(points), 4, replace=False)\n",
    "                quad_indx, quad_hash = _make_quad(points, indx)\n",
    "                n_quads += 1\n",
    "                yield quad_indx, quad_hash\n",
    "                if use_flipped:\n",
    "                    # for a flipped image, x and y of the hash is flipped\n",
    "                    quad_hash = quad_hash[[1, 0, 3, 2]]\n",
    "                    quad_indx = quad_indx[[1, 0, 3, 2]]\n",
    "                    yield _break_quad_symetry(quad_indx, quad_hash)\n",
    "\n",
    "    def solve_sources_wcs(self, src, guess_center, radius='1d', n=20):\n",
    "        \"\"\"Solve the WCS for a sources (x,y) list.\n",
    "\n",
    "        Parameters\n",
    "        ----------\n",
    "        src : list of (x, y)\n",
    "            The list of the sources coordinates used to compute the\n",
    "            astrometric solution. Must be ordered from brightest to faintest.\n",
    "        guess_center : tuple, list or `~astropy.coordinates.SkyCoord`\n",
    "            Initial guess for the center of the field. If tuple or list, must\n",
    "            be size 2 containing RA and DEC in float decimal degrees.\n",
    "        radius : string or `~astropy.coordinates.Angle`, optional\n",
    "            Search radius for astrometric solution.\n",
    "            Default: '1d'\n",
    "        n : int, optional\n",
    "            Number of stars to form the quads in each run. For example, if\n",
    "            n=20, the code will try with the first 20 stars. If not find a\n",
    "            good solution, it will try the next 20, unitl all stars are used.\n",
    "            Default: 20\n",
    "        \"\"\"\n",
    "\n",
    "    def solve_image_wcs(self, image, guess_center, radius='1d', n=20):\n",
    "        \"\"\"Solve the WCS for a sources (x,y) list.\n",
    "\n",
    "        Parameters\n",
    "        ----------\n",
    "        image : array_like or `~astropop.framedata.FrameData`\n",
    "            Image containing stars to get the astrometry solved.\n",
    "        guess_center : tuple, list or `~astropy.coordinates.SkyCoord`\n",
    "            Initial guess for the center of the field. If tuple or list, must\n",
    "            be size 2 containing RA and DEC in float decimal degrees.\n",
    "        radius : string or `~astropy.coordinates.Angle`, optional\n",
    "            Search radius for astrometric solution.\n",
    "            Default: '1d'\n",
    "        n : int, optional\n",
    "            Number of stars to form the quads in each run. For example, if\n",
    "            n=20, the code will try with the first 20 stars. If not find a\n",
    "            good solution, it will try the next 20, unitl all stars are used.\n",
    "            Default: 20\n",
    "        \"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.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",
       "\n",
       "mpl.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%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-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 = 'mpl-button-group';\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 = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. 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",
       "    fig.rubberband_canvas.style.cursor = msg['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 https://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",
       " * https://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\", \"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(\"<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_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",
       "        '<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 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 = '<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 '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",
       "    // 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": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img 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\" width=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.11764706 0.52941176 0.70588235 0.17647059]\n"
     ]
    }
   ],
   "source": [
    "sources = np.array([(0, 0), (40, 60), (80, 20), (100, 60)])\n",
    "\n",
    "indx, quad_hash = _make_quad(sources, [0, 1, 2, 3])\n",
    "stars = sources[indx]\n",
    "a, b, c, d = stars\n",
    "norm = np.linalg.norm(b-a)\n",
    "norm_axis = _get_axis(a, b)\n",
    "\n",
    "fig, ax = plt.subplots(1, 2, figsize=(10, 4))\n",
    "ax[0].add_patch(plt.Polygon(stars[[0, 2, 1, 3]], facecolor='y', alpha=0.1))\n",
    "ax[0].plot(*sources.T, 'o')\n",
    "for i, name in zip(indx, ['A', 'B', 'C', 'D']):\n",
    "    ax[0].annotate(name, sources[i]+0.5)\n",
    "axis = np.array(norm_axis)*norm/np.sqrt(2)\n",
    "ax[0].plot([a[0], axis[0][0]+a[0]], [a[1], axis[0][1]+a[1]], 'k--')\n",
    "ax[0].annotate('x', (axis[0][0]+a[0], axis[0][1]+a[1]))\n",
    "ax[0].plot([a[0], axis[1][0]+a[0]], [a[1], axis[1][1]+a[1]], 'k--')\n",
    "ax[0].annotate('y', (axis[1][0]+a[0], axis[1][1]+a[1]))\n",
    "ax[0].set_aspect('equal')\n",
    "ax[0].add_patch(plt.Circle((a+b)/2, radius=norm/2, fill=False))\n",
    "\n",
    "norm_stars = np.sqrt(2)*(stars-a)/norm\n",
    "ax[1].add_patch(plt.Polygon(norm_stars[[0, 2, 1, 3]], facecolor='y', alpha=0.1))\n",
    "ax[1].plot(*np.transpose([norm_stars[1], norm_axis[0]]), 'c--')\n",
    "ax[1].annotate('x', norm_axis[0])\n",
    "ax[1].plot(*np.transpose([norm_stars[1], norm_axis[1]]), 'c--')\n",
    "ax[1].annotate('y', norm_axis[1])\n",
    "ax[1].plot([0, norm_axis[0][0]], [0, norm_axis[0][1]], 'g--')\n",
    "ax[1].plot([0, norm_axis[1][0]], [0, norm_axis[1][1]], 'g--')\n",
    "ax[1].plot(*norm_stars.T, 'ro')\n",
    "ax[1].set_aspect(\"equal\")\n",
    "\n",
    "print(quad_hash)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Benchmarking\n",
    "\n",
    "### _make_quad function\n",
    "\n",
    "For _make_quad function, our timings are:\n",
    "- Pure-python implementation: 120 µs ± 5.92 µs per loop (mean ± std. dev. of 7 runs, 1,000 loops each)\n",
    "- Cython implementation: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-03-26 11:21:35,624 astropop - DEBUG - Using random 1 combinations.  [2550347427]\n",
      "2022-03-26 11:21:35,629 astropop - INFO - 1 quads 0.0062 s  [3263864062]\n",
      "2022-03-26 11:21:35,632 astropop - DEBUG - Using random 10 combinations.  [2550347427]\n",
      "2022-03-26 11:21:35,648 astropop - INFO - 10 quads 0.0170 s  [3263864062]\n",
      "2022-03-26 11:21:35,650 astropop - DEBUG - Using random 100 combinations.  [2550347427]\n",
      "2022-03-26 11:21:35,730 astropop - INFO - 100 quads 0.0809 s  [3263864062]\n",
      "2022-03-26 11:21:35,733 astropop - DEBUG - Using random 1000 combinations.  [2550347427]\n",
      "2022-03-26 11:21:36,031 astropop - INFO - 1000 quads 0.2988 s  [3263864062]\n",
      "2022-03-26 11:21:36,031 astropop - DEBUG - Using random 10000 combinations.  [2550347427]\n",
      "2022-03-26 11:21:37,278 astropop - INFO - 10000 quads 1.2465 s  [3263864062]\n",
      "2022-03-26 11:21:37,278 astropop - DEBUG - Using random 100000 combinations.  [2550347427]\n",
      "2022-03-26 11:21:49,783 astropop - INFO - 100000 quads 12.5044 s  [3263864062]\n",
      "2022-03-26 11:21:49,783 astropop - DEBUG - Using all 230299 combinations.  [2550347427]\n",
      "2022-03-26 11:22:12,911 astropop - INFO - 230300 quads 23.1277 s  [3263864062]\n"
     ]
    }
   ],
   "source": [
    "# benchmark quads creation\n",
    "a = AstrometrySolver()\n",
    "import time\n",
    "for i in range(7):\n",
    "    begin = time.time()\n",
    "    quads = list(a._compute_quads(np.transpose([hd5980['x'][:50], hd5980['y'][:50]]), max_quads=10**i))\n",
    "    logger.info('%i quads %.4f s', len(quads), time.time()-begin)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "119 µs ± 2.94 µs per loop (mean ± std. dev. of 7 runs, 10,000 loops each)\n"
     ]
    }
   ],
   "source": [
    "# Pure-Python\n",
    "x = np.array((20, 50, 30, 10))\n",
    "y = np.array((15, 45, 12, 80))\n",
    "indx = np.arange(4)\n",
    "%timeit _make_quad(np.array(list(zip(x, y))), indx)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Flipped image\n",
    "\n",
    "If a image is flipped, the coordinates of the stars change to:\n",
    "- $x_n = size_H-x_o$ if flipped horizontally.\n",
    "- $y_n = size_V-y_o$ if flipped vertically.\n",
    "\n",
    "In both of these flips, the axis $x$ and $y$ are swapped, so the respective coordinates of each star in the quad hash. As the coordinates are swapped and the symmetry breaking is done using $x$, the order of $C$ and $D$ stars may be swapped too."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(array([2, 3, 0, 1]), array([-0.04299363,  0.20382166,  0.76910828, -0.03503185]))\n",
      "(array([2, 3, 1, 0]), array([-0.03503185,  0.76910828,  0.20382166, -0.04299363]))\n",
      "(array([2, 3, 1, 0]), array([-0.03503185,  0.76910828,  0.20382166, -0.04299363]))\n"
     ]
    }
   ],
   "source": [
    "x = np.array((20, 50, 30, 10))\n",
    "y = np.array((15, 45, 12, 80))\n",
    "indx = np.arange(4)\n",
    "print(_make_quad(np.array(list(zip(x, y))), indx))\n",
    "print(_make_quad(np.array(list(zip(100-x, y))), indx))\n",
    "print(_make_quad(np.array(list(zip(x, 100-y))), indx))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Catalog Quads\n",
    "\n",
    "Catalog return values of RA and DEC. Near the equator it seems ok to use directly these values to compute quads in the solution. However, going to poles the quads begin to deform and will not result in a good fitting.\n",
    "\n",
    "To get better quads near poles, we need to use tangencial gnomonic projection relative to the center of the query or the field. This can be easily done using the built-in projection of WCS. We set the reference values of a simple WCS to the center of the field and use this WCS to convert world to pixel coordinates. The scale don't need to be precise, as we are working with float point coordinates.\n",
    "\n",
    "In the figure bellow, we compare two fields near the celetial poles. The RA/DEC plots show very deformed asterisms. For comparison, it was added two perfect quads around the poles. Of course they don't look quads in the unprojected plots. Projecting it to gnomonic tangecial plane solves the problem, so we can use this method for our solution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
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       "        return function (event) {\n",
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       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
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       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
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       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
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       "        'canvas'\n",
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       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
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       "\n",
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       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
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       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-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",
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       "            if (!event.currentTarget.disabled) {\n",
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       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\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 = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. 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",
       "    fig.rubberband_canvas.style.cursor = msg['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 https://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",
       " * https://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\", \"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(\"<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_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",
       "        '<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 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 = '<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 '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",
       "    // 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": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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\" width=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import twirl\n",
    "from astropy.wcs import WCS\n",
    "# Use WCS for fast projection ofthe catalog\n",
    "# avoid distorded quads near poles\n",
    "\n",
    "fig, ax = plt.subplots(2, 2, figsize=(10, 10))\n",
    "\n",
    "# south pole\n",
    "center = SkyCoord('00h00m00s -90d00m00s')\n",
    "center = [center.ra.degree, center.dec.degree]\n",
    "fov = 1.0\n",
    "gaias = twirl.gaia_radecs(center, fov, limit=300)\n",
    "\n",
    "gaia = SkyCoord(gaias, unit='deg')\n",
    "pole = SkyCoord([(0, -90)], unit='deg')\n",
    "pole_quad = SkyCoord([(0, -89.9), (90, -89.9), (180, -89.9), (270, -89.9),\n",
    "                      (45, -89.7), (135, -89.7), (225, -89.7), (315, -89.7)], unit='deg')\n",
    "\n",
    "# ra and dec plot\n",
    "ax[0][0].plot(gaia.ra.degree, gaia.dec.degree, 'co', alpha=0.5)\n",
    "ax[0][0].plot(pole.ra.degree, pole.dec.degree, 'ko')\n",
    "ax[0][0].annotate('PS', (pole.ra.degree, pole.dec.degree))\n",
    "ax[0][0].plot(pole_quad.ra.degree, pole_quad.dec.degree, 'ro')\n",
    "ax[0][0].set_title('South Pole (RA/DEC)')\n",
    "\n",
    "# projected\n",
    "ax[0][1].plot(*tangential_projection(gaia, center).T, 'co', alpha=0.5)\n",
    "ax[0][1].add_patch(plt.Polygon(tangential_projection(pole_quad, center)[:4], facecolor='k', alpha=0.05))\n",
    "ax[0][1].plot(*tangential_projection(pole, center).T, 'ko')\n",
    "ax[0][1].annotate('PS', tangential_projection(pole, center).T)\n",
    "ax[0][1].plot(*tangential_projection(pole_quad, center).T, 'ro')\n",
    "ax[0][1].set_aspect('equal')\n",
    "ax[0][1].set_title('South Pole Projected')\n",
    "\n",
    "\n",
    "# Polaris\n",
    "center = SkyCoord('02h31m49s 89d15m50s')\n",
    "center = [center.ra.degree, center.dec.degree]\n",
    "fov = 1.0\n",
    "gaias = twirl.gaia_radecs(center, fov, limit=300)\n",
    "\n",
    "gaia = SkyCoord(gaias, unit='deg')\n",
    "pole = SkyCoord([(0, 90)], unit='deg')\n",
    "pole_quad = SkyCoord([(0, 89.9), (90, 89.9), (180, 89.9), (270, 89.9),\n",
    "                      (45, 89.7), (135, 89.7), (225, 89.7), (315, 89.7)], unit='deg')\n",
    "\n",
    "# ra and dec plot\n",
    "ax[1][0].plot(gaia.ra.degree, gaia.dec.degree, 'co', alpha=0.5)\n",
    "ax[1][0].plot(pole.ra.degree, pole.dec.degree, 'ko')\n",
    "ax[1][0].annotate('PN', (pole.ra.degree, pole.dec.degree))\n",
    "ax[1][0].plot(pole_quad.ra.degree, pole_quad.dec.degree, 'ro')\n",
    "ax[1][0].set_title('Polaris (RA/DEC)')\n",
    "\n",
    "# projected\n",
    "ax[1][1].plot(*tangential_projection(gaia, center).T, 'co', alpha=0.5)\n",
    "ax[1][1].add_patch(plt.Polygon(tangential_projection(pole_quad, center)[:4], facecolor='k', alpha=0.05))\n",
    "ax[1][1].plot(*tangential_projection(pole, center).T, 'ko')\n",
    "ax[1][1].annotate('PN', tangential_projection(pole, center).T)\n",
    "ax[1][1].plot(*tangential_projection(pole_quad, center).T, 'ro')\n",
    "ax[1][1].set_aspect('equal')\n",
    "ax[1][1].set_title('Polaris Projected')\n",
    "\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Astrometry.net index files\n",
    "\n",
    "Astrometry.net index files contains pre-computed quads for astrometric catalogs. Let's break down them and see how data is stored.\n",
    "\n",
    "It seems that all index files contains:\n",
    "- 14 extensions. Only the primary is named.\n",
    "    - 0: primary, only information in header\n",
    "      ```\n",
    "      ENDIAN  = '04:03:02:01' / Endianness detector: u32 0x01020304 written           \n",
    "              =               /  in the order it is stored in memory.          \n",
    "      AN_FILE = 'QUAD    ' / This file lists, for each quad, its stars.               \n",
    "      DIMQUADS=                    3 / Number of stars in a quad.                     \n",
    "      NQUADS  =                 1728 / Number of quads.                               \n",
    "      NSTARS  =                 1080 / Number of stars.                               \n",
    "      SCALE_U =       0.581776417331 / Upper-bound index scale (radians).             \n",
    "      SCALE_L =       0.407243492132 / Lower-bound index scale (radians).             \n",
    "      INDEXID =                 4219 / Index unique ID.                               \n",
    "      HEALPIX =                   -1 / Healpix of this index.                         \n",
    "      HPNSIDE =                    0 / Nside of the healpixelization\n",
    "      ```\n",
    "    - 1: list of quads coordinates. Are 12-bytes strings, must be converted.\n",
    "    - 2-10: kdtree codes\n",
    "    - 11: kdtree star data., 3d-data, 4-bytes each coordinate\n",
    "    - 13: tagalong (magnitude)"
   ]
  }
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