star_distance_plot3D.ipynb

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      "/Users/Meredith/Applications/Ureka/variants/common/lib/python2.7/site-packages/IPython/kernel/__init__.py:13: ShimWarning: The `IPython.kernel` package has been deprecated. You should import from ipykernel or jupyter_client instead.\n",
      "  \"You should import from ipykernel or jupyter_client instead.\", ShimWarning)\n"
     ]
    }
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   "source": [
    "%matplotlib notebook\n",
    "import numpy as np\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "import mpl_toolkits.mplot3d.art3d as art3d\n",
    "import astropy.units as u\n",
    "import astropy.coordinates as coord\n",
    "from astropy.coordinates import SkyCoord\n",
    "from astropy.coordinates import Distance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
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   "source": [
    "infile = 'RGEB_distinfo.txt'\n",
    "target_col = 0\n",
    "RA_col = 3; Dec_col = 4\n",
    "dist_col = 6; derr_col = 7\n",
    "FeH_col = 8\n",
    "usecols = (target_col, RA_col, Dec_col, dist_col, derr_col, FeH_col)\n",
    "\n",
    "# Read in target information from a text file\n",
    "targets, RAs, Decs, dists, derrs, FeHs = np.loadtxt(infile, comments='#', usecols=usecols, \n",
    "    dtype={'names': ('targets', 'RAs', 'Decs', 'dists', 'derrs', 'FeHs'),\n",
    "    'formats': (np.int, '|S11','|S11', np.float64, np.float64, np.float64)}, unpack=True)\n",
    "\n",
    "# Put the RAs, Decs, and distances in a more useful format\n",
    "RAs = coord.Angle(RAs, unit=u.hour)\n",
    "Decs = coord.Angle(Decs, unit=u.degree)\n",
    "dists = dists*u.pc\n",
    "derrs = derrs*u.pc\n",
    "\n",
    "# Define a SkyCoord object for each target\n",
    "starlocs = []\n",
    "for target, RA, Dec, dist, derr in zip(targets, RAs, Decs, dists, derrs):\n",
    "    starlocs.append( SkyCoord(ra=RA, dec=Dec, distance=dist) )\n",
    "\n",
    "# Create galactocentric coordinates for each target\n",
    "# Assign colors as a function of metallicity\n",
    "star_galcens = []\n",
    "colorlist = []\n",
    "for star, FeH in zip(starlocs, FeHs):\n",
    "    if star.distance > 0:\n",
    "        star_galcens.append(star.transform_to(coord.Galactocentric))\n",
    "        if FeH < -0.8: color='#ffffb2' #yellowest\n",
    "        elif FeH >= -0.8 and FeH < -0.6: color='#fed976'\n",
    "        elif FeH >= -0.6 and FeH < -0.4: color='#feb24c'\n",
    "        elif FeH >= -0.4 and FeH < -0.2: color='#fd8d3c'\n",
    "        elif FeH >= -0.2 and FeH < 0.0: color='#fc4e2a'\n",
    "        elif FeH >= 0.0 and FeH < 0.2: color='#e31a1c'\n",
    "        elif FeH >= 0.2: color='#b10026' #reddest\n",
    "        colorlist.append(color)"
   ]
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       "    // Request the server to send over a new figure.\n",
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       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
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       "        }\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",
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       "        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;\n",
       "    var y = canvas_pos.y;\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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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 overriden (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",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\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": [
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Make a figure\n",
    "fig = plt.figure()\n",
    "\n",
    "ax1 = fig.add_subplot(1,1,1, projection='3d', aspect='equal')\n",
    "ax1.set_axis_off() \n",
    "ax1.grid(False)\n",
    "ax1.xaxis.set_ticklabels([])\n",
    "ax1.yaxis.set_ticklabels([])\n",
    "ax1.zaxis.set_ticklabels([])\n",
    "ax1.xaxis.set_ticks([])\n",
    "ax1.yaxis.set_ticks([])\n",
    "ax1.zaxis.set_ticks([])\n",
    "for i, star in enumerate(star_galcens):\n",
    "    ax1.scatter(star.x, star.y, star.z, c=colorlist[i], edgecolors=colorlist[i], s=150)\n",
    "ax1.scatter(0, 0, 0, marker='o', c='k', edgecolors='k', s=50) # galactic center\n",
    "ax1.scatter(-8300, 0, 27, marker='*', c='k', edgecolors='k', s=150) # Sun\n",
    "\n",
    "# Contour-type circles that radiate out from the galactic center for reference\n",
    "circle1 = plt.Circle((0,0), 2000, color='0.75', fill=False)\n",
    "circle2 = plt.Circle((0,0), 4000, color='0.75', fill=False)\n",
    "circle3 = plt.Circle((0,0), 6000, color='0.75', fill=False)\n",
    "circle4 = plt.Circle((0,0), 8000, color='0.75', fill=False)\n",
    "circle5 = plt.Circle((0,0), 10000, color='0.75', fill=False)\n",
    "ax1.add_patch(circle1); ax1.add_patch(circle2)\n",
    "ax1.add_patch(circle3); ax1.add_patch(circle4)\n",
    "ax1.add_patch(circle5)\n",
    "art3d.pathpatch_2d_to_3d(circle1, z=0, zdir='z')\n",
    "art3d.pathpatch_2d_to_3d(circle2, z=0, zdir='z')\n",
    "art3d.pathpatch_2d_to_3d(circle3, z=0, zdir='z')\n",
    "art3d.pathpatch_2d_to_3d(circle4, z=0, zdir='z')\n",
    "art3d.pathpatch_2d_to_3d(circle5, z=0, zdir='z')\n",
    "\n",
    "# Colorbar key\n",
    "ax2 = fig.add_subplot(12,1,10)\n",
    "cmap = mpl.colors.ListedColormap(['#fed976', '#feb24c', '#fd8d3c', '#fc4e2a', '#e31a1c'])\n",
    "cmap.set_over('#b10026') #reddest, high Fe/H\n",
    "cmap.set_under('#ffffb2') #yellowest, low Fe/H\n",
    "bounds = [-0.8, -0.6, -0.4, -0.2, 0.0, 0.2]\n",
    "norm = mpl.colors.BoundaryNorm(bounds, cmap.N)\n",
    "cb = mpl.colorbar.ColorbarBase(ax2, cmap=cmap, norm=norm, ticks=bounds, extend='both', \n",
    "    boundaries=[-1.0]+bounds+[0.4], spacing='proportional', orientation='horizontal')\n",
    "cb.set_label('[Fe/H]', size=26)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}