CloudModel.ipynb

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   "cell_type": "markdown",
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    "# Cloud model implementation\n",
    "Felix Zaussinger, 01.04.2019\n",
    "\n",
    "## 1) Definition of the backscattering coefficient\n",
    "\n",
    "The scattering coefficient is defined as the differential scattering cross section $d\\sigma$ per differential unit area $dA$:\n",
    "\n",
    "$$\\sigma_0 = \\frac{d\\sigma}{dA}$$\n",
    "\n",
    "Equivalent names are __sigma nought__ or __normalised radar cross section__ and in the case of a monostatic radar, $\\sigma_0$ is called the __backscattering coefficient__.\n",
    "\n",
    "Assumptions:\n",
    "1. Observed area consists of many individual point scatters with random locations and amplitudes\n",
    "2. No single scatterer's amplitude dominates\n",
    "\n",
    "## 2) Backscatter from Vegetation\n",
    "We need to consider:\n",
    "1. Volume scattering from vegetation canopies\n",
    "2. Surface scattering from the underlying soil surface\n",
    "3. Volume-surface scattering interaction term\n",
    "\n",
    "The total backscatter can then be written as:\n",
    "\n",
    "$$\\sigma^{0}_{can} = \\sigma^{0}_{v} + \\sigma^{0}_{s} + \\sigma^{0}_{sv}$$\n",
    "\n",
    "One approach to model these interactions is the __Cloud Model__, which consists of three layers:\n",
    "1. Air\n",
    "    - Downwelling radiation is not attenuated until reaching the air-vegetation boundary.\n",
    "2. Vegetation\n",
    "    - Individual scatteres are uniformly distibuted throughout a homogenous volume such as air. \n",
    "    - The vegetation layer can be thought of as a cloud which droplets are held in place by vegetative matter. \n",
    "    - The incoming radiation is exponentially attenuated as a function of extinction coefficient $k_e$ and distance $z$.\n",
    "3. Soil\n",
    "    - The downwelling radiation which has penetrated the vegetation layer is partly reflected backwards as a function of the Fresnel coefficient $r_I$.\n",
    "    - The $\\sigma^{0}$ due to soil scattering is governed by the reflection properties of the soil and the loss in the vegetation layer."
   ]
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  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy import constants\n",
    "import ipywidgets as widgets\n",
    "\n",
    "%matplotlib notebook\n",
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# incidence angle\n",
    "thetas = np.linspace(20,75,100)\n",
    "thetas_rad = np.deg2rad(thetas)"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "### Bare-soil model (Champion 1996)\n",
    "\n",
    "Function of soil moisture and incidence angle. Multiplicative effect in the linear domain, additive effect in the decibel domain. In a linear model, the radar response from bare soil is related to volumetric soil water content of the first soil centimeters $m_v$, where D is the sensitivity of the radar signal to variations in $m_v$/SMC.\n",
    "\n",
    "$$ \\sigma^{0}_{s}(dB) = C_{\\theta} + D m_v $$\n",
    "\n",
    "$C_{\\theta}$ is the value of $\\sigma^{0}_{s}$ for a perfectly dry soil (i.e., $m_v=0 g cm^{-3}$) and calculated through a simple cosine model:\n",
    "\n",
    "$$ C_{\\theta} = C1 + C2 \\cos(\\theta)^{C3}$$\n",
    "\n",
    "The dependence of backscatter on incidence angle is accounted for by the C-parameters:\n",
    "\n",
    "- C1: $\\sigma^{0}_{s}$ for $\\theta=90°$\n",
    "- C2: $\\sigma^{0}_{s}$ over $\\theta=[0°-60°]$\n",
    "- C3: shape factor of the cosine model (connected to angular decrease)"
   ]
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  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def bare_soil_model(theta, mv):\n",
    "    \"\"\"Returns sigma0_soil in dB given the incidence angle theta and volumetric soil water content mv.\"\"\"\n",
    "    \n",
    "    # Cosine model parameters for 5.3 GHz and HH pol from Champion (1996)\n",
    "    C1, C2, C3 = (-29.2, 27.2, 2.8)\n",
    "    \n",
    "    # Soil moisture sensitivity D\n",
    "    D = 0.28 # 0.32 also feasible\n",
    "\n",
    "    C_theta = C1 + C2 * np.cos(theta) ** C3\n",
    "    return C_theta + D * mv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
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       "            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:https://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http:https://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:https://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"499.4444576752042\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d54b8521560d4231bfa5bf872a3616d5",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(FloatSlider(value=0.0, description='$SMC (g/cm^{3})$', max=40.0, step=1.0), Output()), _…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<function __main__.update(smc)>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# mv: from 0.02 (dry) to 0.3 (wet)\n",
    "smc = 1\n",
    "\n",
    "sigma0_bare_soil = bare_soil_model(thetas_rad, smc)\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(5,5))\n",
    "ax.grid(color='#EEEEEE', linewidth=1, linestyle='solid')\n",
    "\n",
    "line, = ax.plot(thetas, sigma0_bare_soil)\n",
    "\n",
    "ax.set_title('Bare soil model')\n",
    "ax.set_xlabel(r'Incidence angle $\\theta$ (°)')\n",
    "ax.set_ylabel(r'$\\sigma^{0}_{s}$ (dB)')\n",
    "ax.set_ylim(-30, 5)\n",
    "\n",
    "\n",
    "def update(smc):\n",
    "    sigma0_bare_soil = bare_soil_model(thetas_rad, smc)\n",
    "    line.set_ydata(sigma0_bare_soil)\n",
    "\n",
    "smc_slider = widgets.FloatSlider(min=0, max=40, step=1, value=0, description=r'$SMC (g/cm^{3})$')\n",
    "widgets.interact(update, smc=smc_slider)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cloud model\n",
    "\n",
    "Single scattering albedo: $\\alpha = \\frac{k_s}{k_e}$\n",
    "\n",
    "Two-way attenuation factor: $\\gamma = e^{-\\frac{2\\tau}{\\cos(\\theta)}}$\n",
    "\n",
    "Parameters: $\\theta$, $k_s$, $k_e$, $\\tau$\n",
    "\n",
    "Individual contributions:\n",
    "- Volume component $\\sigma^{0}_{v} = \\frac{\\alpha}{2} (1-\\gamma^2)$ \n",
    "- Attenuated soil component: $\\gamma^2 \\sigma^{0}_{soil}$\n",
    "- Soil-volume interaction component: often neglected (1) due to it's complex relationship, 2) due to limited contribution)\n",
    "\n",
    "#### Abstract: Attema, E. P. W., and Fawwaz T. Ulaby. \"Vegetation modeled as a water cloud.\" Radio science 13.2 (1978): 357-364.\n",
    "\n",
    "\n",
    "Because the microwave dielectric constant of dry vegetative matter is much smaller (by an order of magnitude or more) than the dielectric constant of water, and because a vegetation canopy is usually composed of more than 99% air by volume, it is proposed that the canopy can be modeled as a water cloud whose droplets are held in place by the vegetative matter. Such a model was developed assuming that the canopy \"cloud\" contains identical water droplets randomly distributed within the canopy. By integrating the scattering and attenuation cross-section contributions of N droplets per unit volume over the signal pathlength through the canopy, an expression was derived for the backscattering coefficient as a function of three target parameters: volumetric moisture content of the soil, volumetric water content of the vegetation, and plant height. Regression analysis of the model predictions against scattering data acquired over a period of four months at several angles of incidence (0°-70°) and frequencies (8-18 GHz) for HH and VV polarizations yields correlation coefficients that range from .7 to .99 depending on frequency, polarization, and crop type. The corresponding standard errors of estimate range from 1.1 to 2.6 dB."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def dB2lin(x):\n",
    "    return np.power(10, x/10)\n",
    "\n",
    "def lin2dB(x):\n",
    "    return 10* np.log10(x)\n",
    "\n",
    "def cloud_model(theta, smc, alpha, tau):\n",
    "    \"\"\"\"\"\"\n",
    "    # Two-way attenuation factor\n",
    "    y2 = np.exp(-2*tau/np.cos(theta))\n",
    "    \n",
    "    # compute bare soil contribution and convert back to linear scale\n",
    "    sigma0_soil_dB = bare_soil_model(theta, smc)\n",
    "    sigma0_soil_linear = dB2lin(sigma0_soil_dB)\n",
    "    \n",
    "    # compute canopy backscattering coefficient using the cloud model and convert to dB scale\n",
    "    sigma0_can = ((3*alpha*np.cos(theta))/4 * (1-y2)) + (y2 * sigma0_soil_linear)\n",
    "    \n",
    "    # return total, volume, soil and soil-volume components\n",
    "    return {\"Canopy\": lin2dB(sigma0_can), # total canopy backscatter,\n",
    "            \"Volume\": lin2dB(((3*alpha*np.cos(theta))/4 * (1-y2))), # volume term\n",
    "            \"Soil\": lin2dB(y2 * sigma0_soil_linear)} # soil term"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http:https://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http:https://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:https://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"499.4444576752042\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5931fad7d26f475990a9d5e4be1e9809",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(FloatSlider(value=0.1, description='$\\\\tau$ (Np)', max=1.0, min=0.01, step=0.05), FloatS…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<function __main__.update(tau, alpha, smc)>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# params\n",
    "tau = 0.1\n",
    "alpha = 0.1\n",
    "smc = 1\n",
    "\n",
    "# calculate backscatter curves\n",
    "cloud_model_terms = cloud_model(thetas_rad, smc, alpha, tau) # canopy backscatter\n",
    "\n",
    "# create figure\n",
    "fig, ax = plt.subplots(figsize=(5,5))\n",
    "ax.grid(color='#EEEEEE', linewidth=1, linestyle='solid')\n",
    "\n",
    "# plot lines\n",
    "sigma0_canopy_plot, = ax.plot(thetas, cloud_model_terms['Canopy'], label=r'$\\sigma^{0}_{can}$', linestyle='--')\n",
    "sigma0_volume_plot, = ax.plot(thetas, cloud_model_terms['Volume'], label=r'$\\sigma^{0}_{v}$')\n",
    "sigma0_soil_plot, = ax.plot(thetas, cloud_model_terms['Soil'], label=r'$\\sigma^{0}_{s}$')\n",
    "\n",
    "# labelling\n",
    "ax.set_title('Cloud model')\n",
    "ax.set_xlabel(r'Incidence angle $\\theta$ (°)')\n",
    "ax.set_ylabel(r'$\\sigma^{0}$ (dB)')\n",
    "ax.set_ylim(-40, 10)\n",
    "ax.legend()\n",
    "\n",
    "# interactive plot\n",
    "def update(tau, alpha, smc):\n",
    "    # update model\n",
    "    cloud_model_terms = cloud_model(thetas_rad, smc, alpha, tau) # canopy backscatter\n",
    "    \n",
    "    # update figure\n",
    "    sigma0_canopy_plot.set_ydata(cloud_model_terms['Canopy'])\n",
    "    sigma0_volume_plot.set_ydata(cloud_model_terms['Volume'])\n",
    "    sigma0_soil_plot.set_ydata(cloud_model_terms['Soil'])\n",
    "\n",
    "# sliders\n",
    "tau_slider = widgets.FloatSlider(min=0.01, max=1, step=0.05, value=0.1, description=r'$\\tau$ (Np)')\n",
    "alpha_slider = widgets.FloatSlider(min=0.01, max=1, step=0.05, value=0.1, description=r'$\\alpha$')\n",
    "smc_slider = widgets.FloatSlider(min=0, max=40, step=1, value=0, description=r'$SMC (g(cm^{3})$')\n",
    "\n",
    "widgets.interact(update, tau=tau_slider, alpha=alpha_slider, smc=smc_slider)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}