From 64f51adf3487731b1a29fa80974d29a8d3c62af9 Mon Sep 17 00:00:00 2001
From: kponder <kap146@pitt.edu>
Date: Tue, 8 Nov 2016 11:23:26 -0500
Subject: [PATCH] Working code to write new data files. Can only run cell once

---
 Generate_Mock_Lightcurves.ipynb | 989 ++------------------------------
 1 file changed, 62 insertions(+), 927 deletions(-)

diff --git a/Generate_Mock_Lightcurves.ipynb b/Generate_Mock_Lightcurves.ipynb
index 5d08af2..060d7c4 100644
--- a/Generate_Mock_Lightcurves.ipynb
+++ b/Generate_Mock_Lightcurves.ipynb
@@ -171,856 +171,17 @@
     "collapsed": false,
     "scrolled": false
    },
-   "outputs": [
-    {
-     "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\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('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",
-       "            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",
-       "        this.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 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);\n",
-       "        canvas.attr('height', height);\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'];\n",
-       "    var y0 = fig.canvas.height - msg['y0'];\n",
-       "    var x1 = msg['x1'];\n",
-       "    var y1 = fig.canvas.height - msg['y1'];\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;\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": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<img src=\"data:image/png;base64,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\">"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "&lt;Table length=103&gt;\n",
-       "<table id=\"table4378186960\" class=\"table-striped table-bordered table-condensed\">\n",
-       "<thead><tr><th>mjd</th><th>filter</th><th>flux</th><th>flux_error</th><th>zp</th><th>zpsys</th></tr></thead>\n",
-       "<thead><tr><th>float64</th><th>str4</th><th>float64</th><th>float64</th><th>float64</th><th>str2</th></tr></thead>\n",
-       "<tr><td>0.0</td><td>desg</td><td>-1.628</td><td>10.48</td><td>27.5</td><td>ab</td></tr>\n",
-       "<tr><td>0.0160000000033</td><td>desr</td><td>-12.65</td><td>7.845</td><td>27.5</td><td>ab</td></tr>\n",
-       "<tr><td>0.0320000000065</td><td>desi</td><td>-10.86</td><td>9.314</td><td>27.5</td><td>ab</td></tr>\n",
-       "<tr><td>0.977000000006</td><td>desz</td><td>-4.156</td><td>5.328</td><td>27.5</td><td>ab</td></tr>\n",
-       "<tr><td>1.985</td><td>desg</td><td>-2.024</td><td>3.205</td><td>27.5</td><td>ab</td></tr>\n",
-       "<tr><td>2.0</td><td>desr</td><td>0.0281</td><td>2.425</td><td>27.5</td><td>ab</td></tr>\n",
-       "<tr><td>2.016</td><td>desi</td><td>0.3376</td><td>4.31</td><td>27.5</td><td>ab</td></tr>\n",
-       "<tr><td>9.957</td><td>desz</td><td>-6.591</td><td>27.32</td><td>27.5</td><td>ab</td></tr>\n",
-       "<tr><td>10.106</td><td>desg</td><td>3.678</td><td>25.57</td><td>27.5</td><td>ab</td></tr>\n",
-       "<tr><td>10.121</td><td>desr</td><td>-1.047</td><td>4.152</td><td>27.5</td><td>ab</td></tr>\n",
-       "<tr><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td></tr>\n",
-       "<tr><td>113.957</td><td>desi</td><td>14.87</td><td>5.61</td><td>27.5</td><td>ab</td></tr>\n",
-       "<tr><td>113.965</td><td>desz</td><td>13.31</td><td>5.166</td><td>27.5</td><td>ab</td></tr>\n",
-       "<tr><td>125.817</td><td>desg</td><td>-0.2672</td><td>2.48</td><td>27.5</td><td>ab</td></tr>\n",
-       "<tr><td>125.821</td><td>desr</td><td>2.634</td><td>1.659</td><td>27.5</td><td>ab</td></tr>\n",
-       "<tr><td>125.836</td><td>desi</td><td>5.357</td><td>2.513</td><td>27.5</td><td>ab</td></tr>\n",
-       "<tr><td>125.852</td><td>desz</td><td>9.238</td><td>3.94</td><td>27.5</td><td>ab</td></tr>\n",
-       "<tr><td>133.821</td><td>desg</td><td>-0.5652</td><td>7.568</td><td>27.5</td><td>ab</td></tr>\n",
-       "<tr><td>133.832</td><td>desr</td><td>1.952</td><td>2.963</td><td>27.5</td><td>ab</td></tr>\n",
-       "<tr><td>133.856</td><td>desi</td><td>0.3662</td><td>5.022</td><td>27.5</td><td>ab</td></tr>\n",
-       "<tr><td>133.879</td><td>desz</td><td>19.26</td><td>5.441</td><td>27.5</td><td>ab</td></tr>\n",
-       "</table>"
-      ],
-      "text/plain": [
-       "<Table length=103>\n",
-       "      mjd       filter   flux  flux_error    zp   zpsys\n",
-       "    float64      str4  float64  float64   float64  str2\n",
-       "--------------- ------ ------- ---------- ------- -----\n",
-       "            0.0   desg  -1.628      10.48    27.5    ab\n",
-       "0.0160000000033   desr  -12.65      7.845    27.5    ab\n",
-       "0.0320000000065   desi  -10.86      9.314    27.5    ab\n",
-       " 0.977000000006   desz  -4.156      5.328    27.5    ab\n",
-       "          1.985   desg  -2.024      3.205    27.5    ab\n",
-       "            2.0   desr  0.0281      2.425    27.5    ab\n",
-       "          2.016   desi  0.3376       4.31    27.5    ab\n",
-       "          9.957   desz  -6.591      27.32    27.5    ab\n",
-       "         10.106   desg   3.678      25.57    27.5    ab\n",
-       "         10.121   desr  -1.047      4.152    27.5    ab\n",
-       "            ...    ...     ...        ...     ...   ...\n",
-       "        113.957   desi   14.87       5.61    27.5    ab\n",
-       "        113.965   desz   13.31      5.166    27.5    ab\n",
-       "        125.817   desg -0.2672       2.48    27.5    ab\n",
-       "        125.821   desr   2.634      1.659    27.5    ab\n",
-       "        125.836   desi   5.357      2.513    27.5    ab\n",
-       "        125.852   desz   9.238       3.94    27.5    ab\n",
-       "        133.821   desg -0.5652      7.568    27.5    ab\n",
-       "        133.832   desr   1.952      2.963    27.5    ab\n",
-       "        133.856   desi  0.3662      5.022    27.5    ab\n",
-       "        133.879   desz   19.26      5.441    27.5    ab"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "#test_table = dat.data['DES_SN001695.DAT'] #get_lightcurve\n",
     "\n",
-    "dat.plot_all()\n",
-    "dat.data[dat.object_names[0]]"
+    "#dat.plot_all()\n",
+    "#dat.data[dat.object_names[0]]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 9,
    "metadata": {
     "collapsed": false
    },
@@ -1033,7 +194,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 10,
    "metadata": {
     "collapsed": false
    },
@@ -1046,7 +207,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 11,
    "metadata": {
     "collapsed": true
    },
@@ -1059,7 +220,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 12,
    "metadata": {
     "collapsed": false
    },
@@ -1106,24 +267,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 14,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "True"
-      ]
-     },
-     "execution_count": 19,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
-    "isinstance(dat.object_names, np.ndarray)"
+    "#isinstance(dat.object_names, np.ndarray)"
    ]
   },
   {
@@ -1134,56 +284,23 @@
    },
    "outputs": [],
    "source": [
-    "test_table_II = dat.data['DES_SN002457.DAT']"
+    "#test_table_II = dat.data['DES_SN002457.DAT']"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 111,
+   "execution_count": 13,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['_Dataset__ind',\n",
-       " '_Dataset__on_press',\n",
-       " '_Dataset__plot_this',\n",
-       " '__doc__',\n",
-       " '__init__',\n",
-       " '__module__',\n",
-       " 'data',\n",
-       " 'filter_set',\n",
-       " 'get_lightcurve',\n",
-       " 'get_max_length',\n",
-       " 'get_object_names',\n",
-       " 'get_redshift',\n",
-       " 'get_types',\n",
-       " 'models',\n",
-       " 'object_names',\n",
-       " 'plot_all',\n",
-       " 'plot_lc',\n",
-       " 'plot_model',\n",
-       " 'reduced_chi_squared',\n",
-       " 'rootdir',\n",
-       " 'set_model',\n",
-       " 'sim_stats',\n",
-       " 'survey_name']"
-      ]
-     },
-     "execution_count": 111,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
-    "dir(dat)"
+    "#dir(dat)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 15,
    "metadata": {
     "collapsed": false
    },
@@ -1201,16 +318,16 @@
     "    MWEBV = data[11].split()\n",
     "    table.meta = {survey[0][:-1]: survey[1], stuffRA[0][:-1]: stuffRA[1], stuffDec[0][:-1]: stuffDec[1],filters[0][:-1]: filters[1],\n",
     "                 MWEBV[0][:-1]: MWEBV[1]}\n",
-    "    table.rename_column('mjd', 'MJD')\n",
+    "    #table.rename_column('mjd', 'MJD')\n",
     "    #table.rename_column('filter ', 'FLT')\n",
-    "    table.rename_column('flux', 'FLUXCAL')\n",
-    "    table.rename_column('flux_error', 'FLUXCALERR')\n",
+    "    #table.rename_column('flux', 'FLUXCAL')\n",
+    "    #table.rename_column('flux_error', 'FLUXCALERR')\n",
     "    sncosmo.write_lc(table, 'new_mocks/%s.dat'%output,pedantic=True, format = 'snana')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 16,
    "metadata": {
     "collapsed": false
    },
@@ -1219,46 +336,64 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "0\n"
-     ]
-    },
-    {
-     "ename": "KeyError",
-     "evalue": "u'Column mjd does not exist'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-26-31f769d11a3e>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     23\u001b[0m     \u001b[0mtest_table_II\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreplace_column\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'FLUXCAL'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtype_II\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     24\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 25\u001b[0;31m     \u001b[0mmake_new_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilename_Ibc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtest_table_Ibc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'Ibc_%s'\u001b[0m\u001b[0;34m%\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     26\u001b[0m     \u001b[0mmake_new_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilename_II\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtest_table_II\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'II_%s'\u001b[0m\u001b[0;34m%\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     27\u001b[0m     \u001b[0mmake_new_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilename_Ia\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtest_table_Ia\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'Ia_%s'\u001b[0m\u001b[0;34m%\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m<ipython-input-24-08013994a48f>\u001b[0m in \u001b[0;36mmake_new_data\u001b[0;34m(filename, table, output)\u001b[0m\n\u001b[1;32m     11\u001b[0m     table.meta = {survey[0][:-1]: survey[1], stuffRA[0][:-1]: stuffRA[1], stuffDec[0][:-1]: stuffDec[1],filters[0][:-1]: filters[1],\n\u001b[1;32m     12\u001b[0m                  MWEBV[0][:-1]: MWEBV[1]}\n\u001b[0;32m---> 13\u001b[0;31m     \u001b[0mtable\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrename_column\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'mjd'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'MJD'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     14\u001b[0m     \u001b[0;31m#table.rename_column('filter ', 'FLT')\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     15\u001b[0m     \u001b[0mtable\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrename_column\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'flux'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'FLUXCAL'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m//anaconda/lib/python2.7/site-packages/astropy/table/table.pyc\u001b[0m in \u001b[0;36mrename_column\u001b[0;34m(self, name, new_name)\u001b[0m\n\u001b[1;32m   1972\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1973\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mname\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1974\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Column {0} does not exist\"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1975\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1976\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mBaseColumn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;31mKeyError\u001b[0m: u'Column mjd does not exist'"
+      "      mjd       filter   flux  flux_error  zp  zpsys\n",
+      "--------------- ------ ------- ---------- ---- -----\n",
+      "            0.0   desg  -1.628      10.48 27.5    ab\n",
+      "0.0160000000033   desr  -12.65      7.845 27.5    ab\n",
+      "0.0320000000065   desi  -10.86      9.314 27.5    ab\n",
+      " 0.977000000006   desz  -4.156      5.328 27.5    ab\n",
+      "          1.985   desg  -2.024      3.205 27.5    ab\n",
+      "            2.0   desr  0.0281      2.425 27.5    ab\n",
+      "          2.016   desi  0.3376       4.31 27.5    ab\n",
+      "          9.957   desz  -6.591      27.32 27.5    ab\n",
+      "         10.106   desg   3.678      25.57 27.5    ab\n",
+      "         10.121   desr  -1.047      4.152 27.5    ab\n",
+      "            ...    ...     ...        ...  ...   ...\n",
+      "        113.868   desr   1.241      4.828 27.5    ab\n",
+      "        113.957   desi   14.87       5.61 27.5    ab\n",
+      "        113.965   desz   13.31      5.166 27.5    ab\n",
+      "        125.817   desg -0.2672       2.48 27.5    ab\n",
+      "        125.821   desr   2.634      1.659 27.5    ab\n",
+      "        125.836   desi   5.357      2.513 27.5    ab\n",
+      "        125.852   desz   9.238       3.94 27.5    ab\n",
+      "        133.821   desg -0.5652      7.568 27.5    ab\n",
+      "        133.832   desr   1.952      2.963 27.5    ab\n",
+      "        133.856   desi  0.3662      5.022 27.5    ab\n",
+      "        133.879   desz   19.26      5.441 27.5    ab\n",
+      "Length = 103 rows\n"
      ]
     }
    ],
    "source": [
-    "test_table_II = dat.data['DES_SN002457.DAT']\n",
     "filename_II = 'SPCC_SUBSET/DES_SN002457.DAT'\n",
-    "test_table_Ia = dat.data['DES_SN002542.DAT']\n",
     "filename_Ia = 'SPCC_SUBSET/DES_SN002542.DAT'\n",
-    "test_table_Ibc = dat.data['DES_SN005399.DAT']\n",
     "filename_Ibc = 'SPCC_SUBSET/DES_SN005399.DAT'\n",
     "\n",
+    "test_table_II = dat.data['DES_SN002457.DAT']\n",
+    "test_table_Ia = dat.data['DES_SN002542.DAT']\n",
+    "test_table_Ibc = dat.data['DES_SN005399.DAT']\n",
+    "#print test_table_II\n",
+    "\n",
+    "test_table_II.rename_column('flux', 'FLUXCAL')\n",
+    "test_table_II.rename_column('flux_error', 'FLUXCALERR')\n",
+    "    \n",
+    "test_table_Ibc.rename_column('flux', 'FLUXCAL')\n",
+    "test_table_Ibc.rename_column('flux_error', 'FLUXCALERR')\n",
+    "    \n",
+    "test_table_Ia.rename_column('flux', 'FLUXCAL')\n",
+    "test_table_Ia.rename_column('flux_error', 'FLUXCALERR')\n",
+    "\n",
     "objs=[]\n",
     "new_data={}\n",
     "\n",
     "for i in range(5):\n",
-    "    test_table_II = dat.data['DES_SN002457.DAT']\n",
-    "    test_table_Ia = dat.data['DES_SN002542.DAT']\n",
-    "    test_table_Ibc = dat.data['DES_SN005399.DAT']\n",
-    "    print i\n",
     "    \n",
-    "    test_table_Ia.replace_column('FLUXCAL', type_Ia[:,i])\n",
-    "    #new_light_curve_Ia= test_table_Ia\n",
     "    \n",
-    "    #new_light_curve_Ibc= \n",
+    "    test_table_Ia.replace_column('FLUXCAL', type_Ia[:,i])\n",
+    "\n",
+    "     \n",
     "    test_table_Ibc.replace_column('FLUXCAL', type_Ibc[:,i])\n",
-    "    #new_light_curve_II= \n",
+    " \n",
     "    test_table_II.replace_column('FLUXCAL', type_II[:,i])\n",
     "    \n",
     "    make_new_data(filename_Ibc, test_table_Ibc, 'Ibc_%s'%i)\n",