fig04_smrt_dmrt.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
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   },
   "outputs": [],
   "source": [
    "# general purpose imports\n",
    "import os\n",
    "import sys\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import scipy\n",
    "\n",
    "# SMRT imports\n",
    "from smrt import make_snowpack, sensor_list, make_model\n",
    "from smrt.utils import dB\n",
    "\n",
    "# DMRT-QMS bindings import\n",
    "# you can disable DMRT-QMS (long computation) by setting to False\n",
    "have_dmrtqms = True\n",
    "# note that to import this binding, you need to install oct2py.\n",
    "# If not available comment this line and don't execute the cell DMRT-QMS below\n",
    "if have_dmrtqms:\n",
    "    from smrt.utils import dmrt_qms_legacy\n",
    "\n",
    "# Import of DMRT-ML if available\n",
    "try:\n",
    "    dmrtml_path = os.environ['DMRTML_DIR']\n",
    "except KeyError:\n",
    "    have_dmrtml = False\n",
    "else:\n",
    "    have_dmrtml = True\n",
    "    sys.path.append(dmrtml_path)\n",
    "    import dmrtml\n",
    "\n",
    "# Graphics import\n",
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt\n",
    "color = ['#1f77b4','#ff7f0e','#2ca02c','#d62728']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "## prepare inputs: snowpack with two layers\n",
    "\n",
    "density = [300]\n",
    "temperature = [265]\n",
    "thickness = [200]\n",
    "radius = [100e-6]\n",
    "stickiness = [0.5]\n",
    "\n",
    "snowpack = make_snowpack(thickness, \"sticky_hard_spheres\",\n",
    "                        density=density, temperature=temperature, radius=radius, stickiness=stickiness)\n",
    "\n",
    "# create the sensor\n",
    "theta = np.arange(10, 65, 5)\n",
    "radiometer = sensor_list.passive(37e9, theta)\n",
    "radar = sensor_list.active(37e9, theta)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
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       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
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       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
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       "\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",
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       "\n",
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       "\n",
       "\n",
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       "    fig.ondownload(fig, format);\n",
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       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
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       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
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       "\n",
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       "\n",
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       "\n",
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       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
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       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
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       "        cursor = 'pointer';\n",
       "        break;\n",
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       "        break;\n",
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       "        break;\n",
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       "\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\", \"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",
       "    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=\"550\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f2325ac97b8>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create the SMRT Model with emmodel=\"dmrt_qcacp_shortrange\" and rtsolver=\"dort\"\n",
    "m = make_model(\"dmrt_qcacp_shortrange\", \"dort\")\n",
    "\n",
    "# run the model\n",
    "res_p = m.run(radiometer, snowpack)\n",
    "\n",
    "# plots\n",
    "f, axs =  plt.subplots(2, 1, figsize=(5.5,9))\n",
    "axs[0].plot(theta, res_p.TbV(), label='SMRT QCACP V', color=color[0])\n",
    "axs[0].plot(theta, res_p.TbH(), label='SMRT QCACP H', color=color[1])\n",
    "\n",
    "axs[0].set_xlabel('Incidence angle (Degree)')\n",
    "axs[0].set_ylabel ('Brightness temperature (K)')\n",
    "axs[0].legend(loc='best')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f23259cbf60>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m_qca = make_model(\"dmrt_qca_shortrange\", \"dort\")\n",
    "\n",
    "# run the model\n",
    "res_qca = m_qca.run(radiometer, snowpack)\n",
    "res_a = m_qca.run(radar, snowpack)\n",
    "\n",
    "# plots\n",
    "axs[0].plot(theta, res_qca.TbV(), '--', label='SMRT QCA V', color=color[0])\n",
    "axs[0].plot(theta, res_qca.TbH(), '--', label='SMRT QCA H', color=color[1])\n",
    "\n",
    "axs[1].plot(theta, dB(res_a.sigmaVV()), label='SMRT QCA VV', color=color[0])\n",
    "axs[1].plot(theta, dB(res_a.sigmaHH()), label='SMRT QCA HH', color=color[1])\n",
    "axs[1].plot(theta, dB(res_a.sigmaHV()), label='SMRT QCA HV', color=color[2])\n",
    "\n",
    "axs[1].set_xlabel('Incidence angle (Degree)')\n",
    "axs[1].set_ylabel ('Backscattering coefficient (dB)')\n",
    "axs[1].legend(loc='best')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSD(DMRTML-SMRT QCA) 0.025368771103770373 0.033521161912417656\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def rmsd(x):\n",
    "    return float(np.sqrt(np.mean(np.square(x))))\n",
    "\n",
    "\n",
    "# run dmrtml if available\n",
    "if have_dmrtml:\n",
    "    freq = radiometer.frequency                # frequency unity: Hz \n",
    "\n",
    "    medium='S' # SNOW\n",
    "    n_max_stream = 64\n",
    "\n",
    "    res = dmrtml.dmrtml(freq,n_max_stream,thickness,density,radius,temperature, tau=stickiness)\n",
    "    axs[0].plot(theta,res.TbV(theta),'s',label='DMRT-ML Fortran V',alpha=0.3, color=color[0])\n",
    "    axs[0].plot(theta,res.TbH(theta),'s',label='DMRT-ML Fortran H', alpha=0.3, color=color[1])\n",
    "    \n",
    "    print(\"RMSD(DMRTML-SMRT QCA)\", rmsd(res.TbV(theta)-res_p.TbV()), rmsd(res.TbH(theta)-res_p.TbH()))\n",
    "have_dmrtml"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 0.32715\n",
      " 1.4791\n",
      "RMSD(DMRTQMS-SMRT QCA) nan nan\n"
     ]
    }
   ],
   "source": [
    "# run DMRT-QMS in passive mode\n",
    "if have_dmrtqms:\n",
    "    res_qms, ks_qms, ka_qms, eff_eps_snow = dmrt_qms_legacy.run(radiometer, snowpack, full_output=True)\n",
    "\n",
    "    axs[0].plot(theta, res_qms.TbV(), '>', label='DMRT-QMS V', color=color[0])\n",
    "    axs[0].plot(theta, res_qms.TbH(), '>', label='DMRT-QMS H', color=color[1])\n",
    "    \n",
    "    print(\"RMSD(DMRTQMS-SMRT QCA)\", rmsd(res_qms.TbV()-res_qca.TbV()), rmsd(res_qms.TbH()-res_qca.TbH()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ks= [ 0.00891995] 0.010851755389 ka= [ 0.27114819] 0.269180028514\n"
     ]
    },
    {
     "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\", \"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",
       "    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=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSD(DMRTQMS-SMRT PRE) nan nan\n"
     ]
    }
   ],
   "source": [
    "if have_dmrtqms:\n",
    "    # get ks and ka from DMRT QMS\n",
    "    \n",
    "    em = m_qca.emmodel(radiometer, snowpack.layers[0])\n",
    "    ks_qca = em.ks\n",
    "    ka_qca = em.ka\n",
    "    \n",
    "    print(\"ks=\", ks_qms, ks_qca, \"ka=\", ka_qms, ka_qca)\n",
    "    \n",
    "    m_tmp = make_model(\"prescribed_kskaeps\", \"dort\")\n",
    "    snowpack.layers[0].ks = ks_qms\n",
    "    snowpack.layers[0].ka = ka_qms\n",
    "    snowpack.layers[0].effective_permittivity = eff_eps_snow\n",
    "    \n",
    "    res = m_tmp.run(radiometer, snowpack)\n",
    "    \n",
    "    plt.figure()\n",
    "    plt.plot(theta, res_qms.TbV(), '>', label='DMRT-QMS V', color=color[0])\n",
    "    plt.plot(theta, res_qms.TbH(), '>', label='DMRT-QMS H', color=color[1])\n",
    "    \n",
    "    plt.plot(theta, res.TbV(), label='SMRT Prescribed V', color=color[0])\n",
    "    plt.plot(theta, res.TbH(), label='SMRT Prescribed H', color=color[1])\n",
    "    \n",
    "    print(\"RMSD(DMRTQMS-SMRT PRE)\", rmsd(res_qms.TbV()-res.TbV()), rmsd(res_qms.TbH()-res.TbH()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSD(DMRTQMS-SMRT PRE) 0.6476397691986127 0.6500142690019798 1.3636605432157485\n"
     ]
    }
   ],
   "source": [
    "# DMRT QMS does not work with Octave, the open source sibling of matlab (at least for some version of octave)\n",
    "# Henning Loewe ran DMRTQMS under matlab. The results are gather here:\n",
    "\n",
    "angle = [0.0,5.0,10.0,15.0,20.0,25.0,30.0,35.0,40.0,45.0,50.0,55.0,60.0,65.0,70.0,75.0,80.0]\n",
    "vv = [-17.7152,-17.7359,-17.7991,-17.9061,-18.0595,-18.2636,-18.5244,-18.8504,-19.2538,-19.7524,-20.3721,-21.1533,-22.1608,-23.4986,-25.3504,-28.0938,-32.7076]\n",
    "hh = [-17.715,-17.7381,-17.8078,-17.926,-18.096,-18.3228,-18.6134,-18.9782,-19.4318,-19.9951,-20.6982,-21.5886,-22.7417,-24.27,-26.3698,-29.447,-34.5717]\n",
    "hv = [-42.3597,-42.3891,-42.4776,-42.6269,-42.84,-43.1212,-43.4768,-43.9158,-44.451,-45.1007,-45.8911,-46.864,-48.0868,-49.6608,-51.7674,-54.7912,-59.7674]\n",
    "vh = [-42.3598,-42.3891,-42.4776,-42.6269,-42.84,-43.1212,-43.4768,-43.9159,-44.451,-45.1006,-45.8913,-46.8642,-48.085,-49.6601,-51.7784,-54.822,-59.7593]\n",
    "\n",
    "s = slice(2, -4)\n",
    "axs[1].plot(angle[s], vv[s], '>', label='DMRT-QMS VV', color=color[0])\n",
    "axs[1].plot(angle[s], hh[s], '>', label='DMRT-QMS HH', color=color[1])\n",
    "axs[1].plot(angle[s], hv[s], '>', label='DMRT-QMS HV', color=color[2])\n",
    "axs[1].set_xlim((10,60))\n",
    "axs[1].set_ylim((-60,-10))\n",
    "\n",
    "\n",
    "print(\"RMSD(DMRTQMS-SMRT PRE)\", rmsd(vv[s]-dB(res_a.sigmaVV())), rmsd(hh[s]-dB(res_a.sigmaHH())), rmsd(hv[s]-dB(res_a.sigmaHV())))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
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   },
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   "source": [
    "\n",
    "for ax in axs:\n",
    "    ncol = 2  ##if ax==axs[1] else 2\n",
    "    ax.legend(loc='best', prop={'size': 9}, ncol=ncol)\n",
    "#f.savefig(\"fig_smrt_dmrt.pdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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