{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# AVO Explorer v2\n",
    "\n",
    "Interactive tool to explore AVO classes.  \n",
    "2016-2017, Alessandro Amato del Monte\n",
    "\n",
    "***\n",
    "\n",
    "Four functions are provided in the accompanying library `avo_explorer_library`:\n",
    "\n",
    "* `make_avoclasses`: to plot a reference chart with the AVO classes.\n",
    "* `avomod1`: to build AVO curves, synthetic gather and Intercept-Gradient crossplot for a half-space model.\n",
    "* `avomod2`: like above but for two different configurations for the lower medium (usually different fluids).\n",
    "* `make_avo_explorer`: builds on top `avomod2` a simple selection to plot the reference AVO classes given by Hilterman (2001) for shale/brine sand scenarios and performs fluid replacement to make gas and oil sands."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\ag19324\\GOOGLEDRIVE\\PYTHON\\avo_explorer_library.py:209: SyntaxWarning: \"is not\" with a literal. Did you mean \"!=\"?\n",
      "  if polarity is not 'normal':\n",
      "C:\\Users\\ag19324\\GOOGLEDRIVE\\PYTHON\\avo_explorer_library.py:336: SyntaxWarning: \"is\" with a literal. Did you mean \"==\"?\n",
      "  if fluid is 'gas':\n"
     ]
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib as mpl\n",
    "mpl.rcParams['figure.dpi'] = 100\n",
    "from ipywidgets import interact, interactive, fixed\n",
    "from avo_explorer_library import make_avoclasses,avomod1,avomod2,make_avo_explorer"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## AVO classes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "make_avoclasses()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Interactive AVO explorer"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Upper layer elastic properties are specified by `vp1`, `vs1`, `rho1`.\n",
    "\n",
    "Lower layer elastic properties are `vp2`, `vs2`, `rho2`.\n",
    "\n",
    "P-wave and S-wave velocities ar in m/s, density in g/cc.\n",
    "\n",
    "Maximum angle of incidence in degrees is `angmax`.\n",
    "\n",
    "When setting polarity to `normal` it means SEG-normal, i.e. increase in acoustic impedance is a peak or positive number.\n",
    "\n",
    "The checkbox `black` draws the synthetic seismogram by filling peaks in black, otherwise peaks are blue and troughs are red.\n",
    "\n",
    "The parameter `mx` controls the scale of the intercept and gradient crossplot as well as the vertical scale (i.e., reflection magnitude) of the AVO plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "afcef9de5eba42a7b8cdb75d08fe08f6",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(IntSlider(value=3094, description='vp1', max=6000, min=1500, step=100), IntSlider(value=…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "interact(avomod1,vp1=(1500,6000,100),vp2=(1500,6000,100),vs1=(1000,3000,100),vs2=(1000,3000,100),rho1=(1.5,3.0,0.1),rho2=(1.5,3.0,0.1), angmin=fixed(0), angmax=(30,60,10), polarity=['normal','reverse'], black=(False), mx=(0.1,1.0,0.2), continuous_update=False);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Interactive AVO classes explorer, with fluid and porosity variations\n",
    "\n",
    "In the plot below, *black* is always brine, *red* is either gas or oil according to the selection in the drop-down box."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b640b3b180a34196b341f7dad25a3add",
       "version_major": 2,
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      },
      "text/plain": [
       "interactive(children=(Dropdown(description='avoclass', index=2, options={'Class 1': 1, 'Class 2': 2, 'Class 3'…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "interact(make_avo_explorer,phimod=(-0.1,0.1,0.02),avoclass={'Class 1':1,'Class 2':2,'Class 3':3,'Class 4':4},fluid=['oil','gas'], continuous_update=False);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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44AHOP/30MmuLi4u54IILmDZtGvvn5PD2qFEcctBBlX9TIiIiySvdzFoAbmaN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\ngP79+5OZmVlh/cyZr7J9+xa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' +\n              'Firefox 4 and 5 are also supported but you ' +\n              'have to enable WebSockets in about:config.');\n    };\n}\n\nmpl.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        this.ws.close();\n    }\n\n    this.ws.onmessage = this._make_on_message_function(this);\n\n    this.ondownload = ondownload;\n}\n\nmpl.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\nmpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n\n}\n\n\nmpl.figure.prototype._root_extra_style = function(canvas_div) {\n\n}\n\nmpl.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\nmpl.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\nmpl.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\nmpl.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\nmpl.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\nmpl.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\nmpl.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\nmpl.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\nmpl.figure.prototype.handle_figure_label = function(fig, msg) {\n    // Updates the figure title.\n    fig.header.textContent = msg['label'];\n}\n\nmpl.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\nmpl.figure.prototype.handle_message = function(fig, msg) {\n    fig.message.textContent = msg['message'];\n}\n\nmpl.figure.prototype.handle_draw = function(fig, msg) {\n    // Request the server to send over a new figure.\n    fig.send_draw_message();\n}\n\nmpl.figure.prototype.handle_image_mode = function(fig, msg) {\n    fig.image_mode = msg['mode'];\n}\n\nmpl.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.\nmpl.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\nmpl.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 */\nfunction 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\nmpl.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\nmpl.figure.prototype._key_event_extra = function(event, name) {\n    // Handle any extra behaviour associated with a key event\n}\n\nmpl.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\nmpl.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\nmpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n    this.message.textContent = tooltip;\n};\nmpl.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\nmpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n\nmpl.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\nmpl.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\nmpl.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\nmpl.figure.prototype.close_ws = function(fig, msg){\n    fig.send_message('closing', msg);\n    // fig.ws.close()\n}\n\nmpl.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\nmpl.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\nmpl.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; 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xCuhmZh8ABlxuZjcDX7j76zHWuQd41sx6EDmL0D+UTkVEJNmq1DFAAVkkg1WnIRbuvgu4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\nmzYJ1x555JFxaxcvjlzXuHX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          "\u001b[1;32m~\\GoogleDrive\\PYTHON\\geophysical_notes\\avo_explorer_library.py\u001b[0m in \u001b[0;36mmake_avo_explorer\u001b[1;34m(avoclass, fluid, phimod)\u001b[0m\n\u001b[0;32m    344\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    345\u001b[0m                 \u001b[0mrhof_new\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkf_new\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m0.80\u001b[0m\u001b[1;33m,\u001b[0m  \u001b[1;36m1.02\u001b[0m \u001b[1;31m# oil density & bulk modulus\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 346\u001b[1;33m         \u001b[0mvp2B\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mvs2B\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mrho2B\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mb\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrockphysics\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mavseth_fluidsub\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvp2\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mvs2\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mrho2\u001b[0m\u001b[1;33m*\u001b[0m\u001b[1;36m1e3\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mphi2\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mrhob\u001b[0m\u001b[1;33m*\u001b[0m\u001b[1;36m1e3\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mrhof_new\u001b[0m\u001b[1;33m*\u001b[0m\u001b[1;36m1e3\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mk0\u001b[0m\u001b[1;33m*\u001b[0m\u001b[1;36m1e9\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mkb\u001b[0m\u001b[1;33m*\u001b[0m\u001b[1;36m1e9\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mkf_new\u001b[0m\u001b[1;33m*\u001b[0m\u001b[1;36m1e9\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    347\u001b[0m         \u001b[0mrho2B\u001b[0m \u001b[1;33m/=\u001b[0m \u001b[1;36m1e3\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    348\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
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xM0Zedx0jfvpTMho23GX9li1buO6663jiiScAuObss/n7rbdSr5Ir5m3bto1b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\n9SCLSGjcfQtwzi5ev2UXr12ejDaJiEh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        {
         "name": "stdout",
         "output_type": "stream",
         "text": "Shale:  Vp=2192, Vs=818, rho=2.16\nSand (brine): Vp=2134, Vs=860, rho=2.11, porosity=0.33\nSand (gas): Vp=1521, Vs=911, rho=1.88\n"
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j7C0tz1dFRJxHsQ3kFuCMzPxq68PrOW2br0GTmdsi4i4azw1l+YOZ+esm55vObUQcRLF9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Sh/keoH2ccSxJyp16KadQL+Osgv8oLC9MhSe5sPwGkIBPteUkhT80fw4sAJ4t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\nDAAIGP369VOTJk0cY2+NGaPXR41yLdMYo08++US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582vWrFlq2rRptjMkacaM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PAAAg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\n7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      "state": {
       "layout": "IPY_MODEL_02479e00172749b9a3dfb015f4d23832",
       "outputs": [
        {
         "name": "stdout",
         "output_type": "stream",
         "text": "Shale:  Vp=2192, Vs=818, rho=2.16\nSand (brine): Vp=2134, Vs=860, rho=2.11, porosity=0.33\nSand (gas): Vp=1521, Vs=911, rho=1.88\n"
        },
        {
         "ename": "TypeError",
         "evalue": "avomod2() got an unexpected keyword argument 'method'",
         "output_type": "error",
         "traceback": [
          "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
          "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
          "\u001b[1;32m~\\AppData\\Local\\Continuum\\Miniconda3\\lib\\site-packages\\ipywidgets\\widgets\\interaction.py\u001b[0m in \u001b[0;36mupdate\u001b[1;34m(self, *args)\u001b[0m\n\u001b[0;32m    248\u001b[0m                     \u001b[0mvalue\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mwidget\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_interact_value\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    249\u001b[0m                     \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mwidget\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_kwarg\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 250\u001b[1;33m                 \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m**\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    251\u001b[0m                 \u001b[0mshow_inline_matplotlib_plots\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    252\u001b[0m                 \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mauto_display\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mresult\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
          "\u001b[1;32m~\\GoogleDrive\\PYTHON\\geophysical_notes\\avo_explorer_library.py\u001b[0m in \u001b[0;36mmake_avo_explorer\u001b[1;34m(avoclass, fluid, phimod)\u001b[0m\n\u001b[0;32m    356\u001b[0m         \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Sand ({:s}): Vp={:.0f}, Vs={:.0f}, rho={:.2f}'\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfluid\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mvp2B\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mvs2B\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mrho2B\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    357\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 358\u001b[1;33m         \u001b[0mavomod2\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvp1\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mvs1\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mrho1\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mvp2\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mvs2\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mrho2\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mvp2B\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mvs2B\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mrho2B\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mangmin\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mangmax\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m30\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mmethod\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'shuey'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
          "\u001b[1;31mTypeError\u001b[0m: avomod2() got an unexpected keyword argument 'method'"
         ]
        }
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        {
         "name": "stdout",
         "output_type": "stream",
         "text": "Shale:  Vp=3094, Vs=1515, rho=2.40\nSand (brine): Vp=4115, Vs=2453, rho=2.32, porosity=0.20\nSand (gas): Vp=4099, Vs=2529, rho=2.18\n"
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giZlxxRVXMGvWLA444ICEvo0bN3L66adz0003sXXr1ogSiojULSqQRaTmSkoK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\n+AGtrYVJ5iZZK8mTSaYn2abFcDtwYq/NQ1v53Uk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          "text/plain": "<matplotlib.figure.Figure at 0xa1f7e10>"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ]
      }
     },
     "e55e846fbf0241428ebd78f2bd06fcc1": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.0.0",
      "model_name": "FloatSliderModel",
      "state": {
       "description": "rho1",
       "layout": "IPY_MODEL_94c8b767f2fd44d8ab5f236daf648101",
       "max": 3,
       "min": 1.5,
       "step": 0.1,
       "style": "IPY_MODEL_c843f9aac8dd41478b79ce5e64f2d9f9",
       "value": 2.16
      }
     },
     "e5761ed97ed04db19a0ab9db8d85c201": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "layout": "IPY_MODEL_27b832e8781c45b7b24535443d54ed0a",
       "outputs": [
        {
         "data": {
          "image/png": 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OcAzAQOqXAHfYVv72y/M+Az6Y5N1JVid5b5KfJ/mLJJ/ZhWO9PslpM1caAADQ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\n+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       "style": "IPY_MODEL_f7cb3a118ca44926b68bbdd1c486468b"
      }
     },
     "f0c295ebabe540838051be3b5898cd96": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.0.0",
      "model_name": "IntSliderModel",
      "state": {
       "description": "vs1",
       "layout": "IPY_MODEL_6038535946014ed7a9ab98b06a6a8ca5",
       "max": 3000,
       "min": 1000,
       "step": 100,
       "style": "IPY_MODEL_d111ab33f4894f45bff1e586ecabcb94",
       "value": 1000
      }
     },
     "f0d49c87eb134479af1b263b2a7b3b38": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.0.0",
      "model_name": "CheckboxModel",
      "state": {
       "description": "black",
       "disabled": false,
       "layout": "IPY_MODEL_cf1e7df697224301bf1961640efb9528",
       "style": "IPY_MODEL_bddf589f92714f88bb2b008fc57e3591",
       "value": false
      }
     },
     "f0ecf998d69a42cfb54356502389debe": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.0.0",
      "model_name": "CheckboxModel",
      "state": {
       "description": "black",
       "disabled": false,
       "layout": "IPY_MODEL_05f5a57e9a274efe9b7b83015579139a",
       "style": "IPY_MODEL_4d06fcae9cb54077abdf3f965d373347",
       "value": false
      }
     },
     "f14cccc5011148cb859c714279e2658f": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "layout": "IPY_MODEL_82aedb43e02d42879570c17cfbf55c5b",
       "outputs": [
        {
         "data": {
          "image/png": 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44AHOP/30MmuLi4u54IILmDZtGvvn5PD2qFEcctBBlX9TIiIiySvdzFoAbmaN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\n",
          "text/plain": "<matplotlib.figure.Figure at 0xa253898>"
         },
         "metadata": {},
         "output_type": "display_data"
        },
        {
         "data": {
          "text/plain": "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,\n        17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30]),\n array([-0.24338299, -0.24341179, -0.24349814, -0.24364195, -0.24384303,\n        -0.24410115, -0.24441598, -0.24478715, -0.24521421, -0.24569662,\n        -0.24623381, -0.24682511, -0.24746982, -0.24816714, -0.24891623,\n        -0.24971616, -0.25056598, -0.25146463, -0.25241104, -0.25340403,\n        -0.25444241, -0.25552491, -0.25665021, -0.25781694, -0.25902367,\n        -0.26026894, -0.26155124, -0.26286899, -0.26422059, -0.2656044 ,\n        -0.26701872]),\n -0.24338298853988244,\n -0.094542937487458734)"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ]
      }
     },
     "f153db1168ab407797290934e3f740ea": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.0.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "f2b61954ba1d4f8094ba4cf2a2b8b2a2": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "layout": "IPY_MODEL_73941b473daa4ada9578893a20b30c71",
       "outputs": [
        {
         "ename": "ValueError",
         "evalue": "too many values to unpack (expected 3)",
         "output_type": "error",
         "traceback": [
          "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
          "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
          "\u001b[1;32m~\\AppData\\Local\\Continuum\\Miniconda3\\lib\\site-packages\\ipywidgets\\widgets\\interaction.py\u001b[0m in \u001b[0;36mupdate\u001b[1;34m(self, *args)\u001b[0m\n\u001b[0;32m    248\u001b[0m                     \u001b[0mvalue\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mwidget\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_interact_value\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    249\u001b[0m                     \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mwidget\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_kwarg\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 250\u001b[1;33m                 \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m**\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    251\u001b[0m                 \u001b[0mshow_inline_matplotlib_plots\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    252\u001b[0m                 \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mauto_display\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mresult\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
          "\u001b[1;32m~\\GoogleDrive\\PYTHON\\geophysical_notes\\avo_explorer_library.py\u001b[0m in \u001b[0;36mmake_avo_explorer\u001b[1;34m(avoclass, fluid, phimod)\u001b[0m\n\u001b[0;32m    347\u001b[0m                 \u001b[0mrhof_new\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkf_new\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m0.80\u001b[0m\u001b[1;33m,\u001b[0m  \u001b[1;36m1.02\u001b[0m \u001b[1;31m# oil density & bulk modulus\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    348\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 349\u001b[1;33m         \u001b[0mvp2B\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mvs2B\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mrho2B\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mgassmann\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvp2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mvs2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mrho2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mrhob\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkb\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mrhof_new\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkf_new\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mk0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mphi2\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    350\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    351\u001b[0m         \u001b[1;31m# vp2B,vs2B,rho2B=b.rockphysics.avseth_fluidsub(vp2,vs2,rho2*1e3,phi2,rhob*1e3,rhof_new*1e3,k0*1e9,kb*1e9,kf_new*1e9)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
          "\u001b[1;31mValueError\u001b[0m: too many values to unpack (expected 3)"
         ]
        }
       ]
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