{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Freesurfer Hippocampal Subfields"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"SUBJECTS_DIR = '../tests/subjects'\n",
"SUBJECT = 'bert'"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['lh.hippoSfVolumes-T1.v10.txt', 'lh.hippoSfVolumes-T1-T2.v10.txt']"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import os\n",
"from freesurfer_volume_reader.freesurfer import HippocampalSubfieldsVolumeFile\n",
"\n",
"volume_files = list(filter(lambda f: f.subject == SUBJECT, \n",
" HippocampalSubfieldsVolumeFile.find(SUBJECTS_DIR)))\n",
"[os.path.basename(f.absolute_path) for f in volume_files]"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>subfield</th>\n",
" <th>volume_mm^3</th>\n",
" <th>subject</th>\n",
" <th>hemisphere</th>\n",
" <th>T1_input</th>\n",
" <th>analysis_id</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Hippocampal_tail</td>\n",
" <td>123.456789</td>\n",
" <td>bert</td>\n",
" <td>left</td>\n",
" <td>True</td>\n",
" <td>None</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>subiculum</td>\n",
" <td>234.567891</td>\n",
" <td>bert</td>\n",
" <td>left</td>\n",
" <td>True</td>\n",
" <td>None</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>CA1</td>\n",
" <td>34.567891</td>\n",
" <td>bert</td>\n",
" <td>left</td>\n",
" <td>True</td>\n",
" <td>None</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>hippocampal-fissure</td>\n",
" <td>345.678912</td>\n",
" <td>bert</td>\n",
" <td>left</td>\n",
" <td>True</td>\n",
" <td>None</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>presubiculum</td>\n",
" <td>456.789123</td>\n",
" <td>bert</td>\n",
" <td>left</td>\n",
" <td>True</td>\n",
" <td>None</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" subfield volume_mm^3 subject hemisphere T1_input analysis_id\n",
"0 Hippocampal_tail 123.456789 bert left True None\n",
"1 subiculum 234.567891 bert left True None\n",
"2 CA1 34.567891 bert left True None\n",
"3 hippocampal-fissure 345.678912 bert left True None\n",
"4 presubiculum 456.789123 bert left True None"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import pandas\n",
"volume_frame = pandas.concat([f.read_volumes_dataframe() for f in volume_files])\n",
"volume_frame.head()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['CA1',\n",
" 'CA3',\n",
" 'CA4',\n",
" 'GC-ML-DG',\n",
" 'HATA',\n",
" 'Hippocampal_tail',\n",
" 'Whole_hippocampus',\n",
" 'fimbria',\n",
" 'hippocampal-fissure',\n",
" 'molecular_layer_HP',\n",
" 'parasubiculum',\n",
" 'presubiculum',\n",
" 'subiculum']"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sorted(volume_frame['subfield'].unique())"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[None, 'T2']"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"list(volume_frame['analysis_id'].unique())"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"T1 13\n",
"T1 & T2 13\n",
"Name: segmentation_mode, dtype: int64"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"def generate_mode_label(row):\n",
" mri_sequences = ['T1' if row['T1_input'] else None,\n",
" row['analysis_id'].split('_')[0] if row['analysis_id'] else None]\n",
" return ' & '.join(filter(None, mri_sequences))\n",
"\n",
"volume_frame['segmentation_mode'] = volume_frame.apply(generate_mode_label, axis=1)\n",
"volume_frame.to_csv('freesurfer_hipposf_volumes_{}.csv'.format(SUBJECT),\n",
" index=False)\n",
"volume_frame['segmentation_mode'].value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>segmentation_mode</th>\n",
" <th>T1</th>\n",
" <th>T1 & T2</th>\n",
" </tr>\n",
" <tr>\n",
" <th>subfield</th>\n",
" <th>hemisphere</th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>CA1</th>\n",
" <th>left</th>\n",
" <td>34.567891</td>\n",
" <td>44.567891</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CA3</th>\n",
" <th>left</th>\n",
" <td>678.912345</td>\n",
" <td>678.912445</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CA4</th>\n",
" <th>left</th>\n",
" <td>789.123456</td>\n",
" <td>789.124456</td>\n",
" </tr>\n",
" <tr>\n",
" <th>GC-ML-DG</th>\n",
" <th>left</th>\n",
" <td>567.891234</td>\n",
" <td>567.891244</td>\n",
" </tr>\n",
" <tr>\n",
" <th>HATA</th>\n",
" <th>left</th>\n",
" <td>91.234567</td>\n",
" <td>91.244567</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Hippocampal_tail</th>\n",
" <th>left</th>\n",
" <td>123.456789</td>\n",
" <td>124.456789</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Whole_hippocampus</th>\n",
" <th>left</th>\n",
" <td>1234.567899</td>\n",
" <td>1244.567899</td>\n",
" </tr>\n",
" <tr>\n",
" <th>fimbria</th>\n",
" <th>left</th>\n",
" <td>89.123456</td>\n",
" <td>89.124456</td>\n",
" </tr>\n",
" <tr>\n",
" <th>hippocampal-fissure</th>\n",
" <th>left</th>\n",
" <td>345.678912</td>\n",
" <td>445.678912</td>\n",
" </tr>\n",
" <tr>\n",
" <th>molecular_layer_HP</th>\n",
" <th>left</th>\n",
" <td>56.789123</td>\n",
" <td>56.789124</td>\n",
" </tr>\n",
" <tr>\n",
" <th>parasubiculum</th>\n",
" <th>left</th>\n",
" <td>45.678912</td>\n",
" <td>45.678912</td>\n",
" </tr>\n",
" <tr>\n",
" <th>presubiculum</th>\n",
" <th>left</th>\n",
" <td>456.789123</td>\n",
" <td>456.789124</td>\n",
" </tr>\n",
" <tr>\n",
" <th>subiculum</th>\n",
" <th>left</th>\n",
" <td>234.567891</td>\n",
" <td>244.567891</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
"segmentation_mode T1 T1 & T2\n",
"subfield hemisphere \n",
"CA1 left 34.567891 44.567891\n",
"CA3 left 678.912345 678.912445\n",
"CA4 left 789.123456 789.124456\n",
"GC-ML-DG left 567.891234 567.891244\n",
"HATA left 91.234567 91.244567\n",
"Hippocampal_tail left 123.456789 124.456789\n",
"Whole_hippocampus left 1234.567899 1244.567899\n",
"fimbria left 89.123456 89.124456\n",
"hippocampal-fissure left 345.678912 445.678912\n",
"molecular_layer_HP left 56.789123 56.789124\n",
"parasubiculum left 45.678912 45.678912\n",
"presubiculum left 456.789123 456.789124\n",
"subiculum left 234.567891 244.567891"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"volume_frame.pivot_table(values='volume_mm^3',\n",
" index=['subfield', 'hemisphere'],\n",
" columns='segmentation_mode')"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
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" alert('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",
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"\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",
"\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]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.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, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.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",
" /* 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",
" evt.data.type = \"image/png\";\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",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\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(\"No handler for the '\" + msg_type + \"' message type: \", msg);\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(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" 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",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\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",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" 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",
"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\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
"\n",
"mpl.default_extension = \"png\";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.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",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['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 = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\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.get(0);\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",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\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).html('<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/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<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 () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\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) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('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",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\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('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
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},
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\" width=\"360.8\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"<matplotlib.legend.Legend at 0x7f04334ae4a8>"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"%matplotlib notebook\n",
"from matplotlib import pyplot\n",
"import seaborn\n",
"\n",
"ax = seaborn.barplot(data=volume_frame[volume_frame['subfield'] == 'Whole_hippocampus'],\n",
" x='hemisphere',\n",
" y='volume_mm^3',\n",
" hue='segmentation_mode')\n",
"ax.set_title('Hippocampal Volume of Subject {}'.format(SUBJECT))\n",
"ax.legend(loc='lower right')"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\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('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",
"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 = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(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 (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\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 = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\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 nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\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",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\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",
"\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",
"\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]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.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, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.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",
" /* 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",
" evt.data.type = \"image/png\";\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",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\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(\"No handler for the '\" + msg_type + \"' message type: \", msg);\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(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" 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",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\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",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" 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",
"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\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
"\n",
"mpl.default_extension = \"png\";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.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",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['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 = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\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.get(0);\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",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\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).html('<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/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<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 () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\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) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('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",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\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('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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\" width=\"873.6\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"Text(0.5, 1.0, 'Hippocampal Subfield Volumes of Subject bert\\nLeft Hemisphere')"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"subfield_volume_frame = volume_frame[volume_frame['subfield'] != 'Whole_hippocampus']\n",
"\n",
"pyplot.figure()\n",
"seaborn.set(font_scale=0.8)\n",
"ax = seaborn.barplot(data=subfield_volume_frame[subfield_volume_frame['hemisphere'] == 'left'],\n",
" x='subfield',\n",
" y='volume_mm^3',\n",
" hue='segmentation_mode')\n",
"ax.set_xticklabels(ax.get_xticklabels(), rotation=60)\n",
"ax.set_title('Hippocampal Subfield Volumes of Subject {}\\nLeft Hemisphere'.format(SUBJECT))"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.7"
}
},
"nbformat": 4,
"nbformat_minor": 2
}