diff --git a/run.py b/run.py
index ce7f4df..ef87bc1 100644
--- a/run.py
+++ b/run.py
@@ -111,7 +111,7 @@ def on_update(self, delta_time: float):
 
         dead_sprites = self.world.step()
         for sprite_index in dead_sprites:
-            self.grid_sprite_list[sprite_index].visible = False
+            self.grid_sprite_list[sprite_index].color = arcade.color.BLACK
             self.available_sprites.append(sprite_index)
 
     def on_draw(self):
diff --git a/src/being.py b/src/being.py
index 966a6c6..21732ad 100644
--- a/src/being.py
+++ b/src/being.py
@@ -6,8 +6,8 @@
 ENERGY_LOSS_GENERAL = 0.001
 ENERGY_LOSS_ACTIONS = 0.005
 
-FOOD_TO_ENERGY = 0.1
-WATER_TO_ENERGY = 0.1
+FOOD_TO_ENERGY = 0.001
+WATER_TO_ENERGY = 0.001
 
 # Rotation vectors for movement
 theta = np.deg2rad(45)
@@ -23,18 +23,18 @@ class Being:
     """
     def __init__(self, sprite_index):
         # Subjective states (things the "brain" feels)
-        self.happiness = 1
-        self.hunger = 0
-        self.thirst = 0
+        self.happiness = 1.
+        self.hunger = 0.
+        self.thirst = 0.
 
         # Objective states (hidden from the "brain")
-        self.food = 1
-        self.water = 1
-        self.energy = 1
+        self.food = 1.
+        self.water = 1.
+        self.energy = 1.
 
-        self.angle = 0
+        self.angle = 0.
         self.direction = [1, 0]  # vector from (0,0) (the being) to the direction its facing
-        self.speed = 0
+        self.speed = 0.
         self.action_space = ['NOOP', 'TURN_LEFT', 'TURN_RIGHT', 'MOVE', 'STOP', 'EAT', 'DRINK']
 
         self.sprite_index = sprite_index
@@ -50,18 +50,19 @@ def choose_action(self):
         return action
 
     def step(self):
-        self.energy -= ENERGY_LOSS_GENERAL
+        self.energy = max(0, self.energy - ENERGY_LOSS_GENERAL)
 
-        if self.food > 0:
-            self.food -= FOOD_TO_ENERGY
-            self.energy += FOOD_TO_ENERGY
+        if self.energy < 1:
+            if self.food > 0:
+                self.food = max(0, self.food - FOOD_TO_ENERGY)
+                self.energy = min(1, self.energy + FOOD_TO_ENERGY)
 
-        if self.water > 0:
-            self.water -= WATER_TO_ENERGY
-            self.energy += WATER_TO_ENERGY
+            if self.water > 0:
+                self.water = max(0, self.water - WATER_TO_ENERGY)
+                self.energy = min(1, self.energy + WATER_TO_ENERGY)
 
         if self.speed > 0:
-            self.energy -= ENERGY_LOSS_ACTIONS
+            self.energy = max(0, self.energy - ENERGY_LOSS_ACTIONS)
 
     def is_alive(self):
         return self.energy > 0
\ No newline at end of file
diff --git a/src/playground.ipynb b/src/playground.ipynb
index e30c7ee..8ee04b3 100644
--- a/src/playground.ipynb
+++ b/src/playground.ipynb
@@ -9,197 +9,76 @@
    "outputs": [],
    "source": [
     "import numpy as np\n",
-    "import matplotlib.pyplot as plt\n",
     "import random\n",
-    "from math import cos, sin\n",
-    "import matplotlib.animation as animation\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "# from math import cos, sin\n",
+    "# import matplotlib.animation as animation\n",
     "\n",
     "random.seed(1)\n",
     "\n",
-    "plt.rcParams[\"figure.figsize\"] = (10, 10)\n",
+    "plt.rcParams[\"figure.figsize\"] = (10, 5)\n",
     "\n",
-    "%matplotlib notebook"
+    "%load_ext autoreload\n",
+    "%autoreload 2"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 2,
+   "outputs": [],
+   "source": [
+    "WORLD_SIZE = 250\n",
+    "INITIAL_POPULATION = 1000"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
    "outputs": [
     {
      "data": {
-      "text/plain": "<IPython.core.display.Javascript object>",
-      "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.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(\n            '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\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 = document.createElement('div');\n    this.root.setAttribute('style', 'display: inline-block');\n    this._root_extra_style(this.root);\n\n    parent_element.appendChild(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 (fig.ratio !== 1) {\n            fig.send_message('set_device_pixel_ratio', {\n                device_pixel_ratio: fig.ratio,\n            });\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\nmpl.figure.prototype._init_header = function () {\n    var titlebar = document.createElement('div');\n    titlebar.classList =\n        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n    var titletext = document.createElement('div');\n    titletext.classList = 'ui-dialog-title';\n    titletext.setAttribute(\n        'style',\n        'width: 100%; text-align: center; padding: 3px;'\n    );\n    titlebar.appendChild(titletext);\n    this.root.appendChild(titlebar);\n    this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n    var fig = this;\n\n    var canvas_div = (this.canvas_div = document.createElement('div'));\n    canvas_div.setAttribute(\n        'style',\n        'border: 1px solid #ddd;' +\n            'box-sizing: content-box;' +\n            'clear: both;' +\n            'min-height: 1px;' +\n            'min-width: 1px;' +\n            'outline: 0;' +\n            'overflow: hidden;' +\n            'position: relative;' +\n            'resize: both;'\n    );\n\n    function on_keyboard_event_closure(name) {\n        return function (event) {\n            return fig.key_event(event, name);\n        };\n    }\n\n    canvas_div.addEventListener(\n        'keydown',\n        on_keyboard_event_closure('key_press')\n    );\n    canvas_div.addEventListener(\n        'keyup',\n        on_keyboard_event_closure('key_release')\n    );\n\n    this._canvas_extra_style(canvas_div);\n    this.root.appendChild(canvas_div);\n\n    var canvas = (this.canvas = document.createElement('canvas'));\n    canvas.classList.add('mpl-canvas');\n    canvas.setAttribute('style', 'box-sizing: content-box;');\n\n    this.context = canvas.getContext('2d');\n\n    var backingStore =\n        this.context.backingStorePixelRatio ||\n        this.context.webkitBackingStorePixelRatio ||\n        this.context.mozBackingStorePixelRatio ||\n        this.context.msBackingStorePixelRatio ||\n        this.context.oBackingStorePixelRatio ||\n        this.context.backingStorePixelRatio ||\n        1;\n\n    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n\n    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n        'canvas'\n    ));\n    rubberband_canvas.setAttribute(\n        'style',\n        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n    );\n\n    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n    if (this.ResizeObserver === undefined) {\n        if (window.ResizeObserver !== undefined) {\n            this.ResizeObserver = window.ResizeObserver;\n        } else {\n            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n            this.ResizeObserver = obs.ResizeObserver;\n        }\n    }\n\n    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n        var nentries = entries.length;\n        for (var i = 0; i < nentries; i++) {\n            var entry = entries[i];\n            var width, height;\n            if (entry.contentBoxSize) {\n                if (entry.contentBoxSize instanceof Array) {\n                    // Chrome 84 implements new version of spec.\n                    width = entry.contentBoxSize[0].inlineSize;\n                    height = entry.contentBoxSize[0].blockSize;\n                } else {\n                    // Firefox implements old version of spec.\n                    width = entry.contentBoxSize.inlineSize;\n                    height = entry.contentBoxSize.blockSize;\n                }\n            } else {\n                // Chrome <84 implements even older version of spec.\n                width = entry.contentRect.width;\n                height = entry.contentRect.height;\n            }\n\n            // Keep the size of the canvas and rubber band canvas in sync with\n            // the canvas container.\n            if (entry.devicePixelContentBoxSize) {\n                // Chrome 84 implements new version of spec.\n                canvas.setAttribute(\n                    'width',\n                    entry.devicePixelContentBoxSize[0].inlineSize\n                );\n                canvas.setAttribute(\n                    'height',\n                    entry.devicePixelContentBoxSize[0].blockSize\n                );\n            } else {\n                canvas.setAttribute('width', width * fig.ratio);\n                canvas.setAttribute('height', height * fig.ratio);\n            }\n            canvas.setAttribute(\n                'style',\n                'width: ' + width + 'px; height: ' + height + 'px;'\n            );\n\n            rubberband_canvas.setAttribute('width', width);\n            rubberband_canvas.setAttribute('height', height);\n\n            // And update the size in Python. We ignore the initial 0/0 size\n            // that occurs as the element is placed into the DOM, which should\n            // otherwise not happen due to the minimum size styling.\n            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n                fig.request_resize(width, height);\n            }\n        }\n    });\n    this.resizeObserverInstance.observe(canvas_div);\n\n    function on_mouse_event_closure(name) {\n        return function (event) {\n            return fig.mouse_event(event, name);\n        };\n    }\n\n    rubberband_canvas.addEventListener(\n        'mousedown',\n        on_mouse_event_closure('button_press')\n    );\n    rubberband_canvas.addEventListener(\n        'mouseup',\n        on_mouse_event_closure('button_release')\n    );\n    rubberband_canvas.addEventListener(\n        'dblclick',\n        on_mouse_event_closure('dblclick')\n    );\n    // Throttle sequential mouse events to 1 every 20ms.\n    rubberband_canvas.addEventListener(\n        'mousemove',\n        on_mouse_event_closure('motion_notify')\n    );\n\n    rubberband_canvas.addEventListener(\n        'mouseenter',\n        on_mouse_event_closure('figure_enter')\n    );\n    rubberband_canvas.addEventListener(\n        'mouseleave',\n        on_mouse_event_closure('figure_leave')\n    );\n\n    canvas_div.addEventListener('wheel', function (event) {\n        if (event.deltaY < 0) {\n            event.step = 1;\n        } else {\n            event.step = -1;\n        }\n        on_mouse_event_closure('scroll')(event);\n    });\n\n    canvas_div.appendChild(canvas);\n    canvas_div.appendChild(rubberband_canvas);\n\n    this.rubberband_context = rubberband_canvas.getContext('2d');\n    this.rubberband_context.strokeStyle = '#000000';\n\n    this._resize_canvas = function (width, height, forward) {\n        if (forward) {\n            canvas_div.style.width = width + 'px';\n            canvas_div.style.height = height + 'px';\n        }\n    };\n\n    // Disable right mouse context menu.\n    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n        event.preventDefault();\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 toolbar = document.createElement('div');\n    toolbar.classList = 'mpl-toolbar';\n    this.root.appendChild(toolbar);\n\n    function on_click_closure(name) {\n        return function (_event) {\n            return fig.toolbar_button_onclick(name);\n        };\n    }\n\n    function on_mouseover_closure(tooltip) {\n        return function (event) {\n            if (!event.currentTarget.disabled) {\n                return fig.toolbar_button_onmouseover(tooltip);\n            }\n        };\n    }\n\n    fig.buttons = {};\n    var buttonGroup = document.createElement('div');\n    buttonGroup.classList = 'mpl-button-group';\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            /* Instead of a spacer, we start a new button group. */\n            if (buttonGroup.hasChildNodes()) {\n                toolbar.appendChild(buttonGroup);\n            }\n            buttonGroup = document.createElement('div');\n            buttonGroup.classList = 'mpl-button-group';\n            continue;\n        }\n\n        var button = (fig.buttons[name] = document.createElement('button'));\n        button.classList = 'mpl-widget';\n        button.setAttribute('role', 'button');\n        button.setAttribute('aria-disabled', 'false');\n        button.addEventListener('click', on_click_closure(method_name));\n        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n\n        var icon_img = document.createElement('img');\n        icon_img.src = '_images/' + image + '.png';\n        icon_img.srcset = '_images/' + image + '_large.png 2x';\n        icon_img.alt = tooltip;\n        button.appendChild(icon_img);\n\n        buttonGroup.appendChild(button);\n    }\n\n    if (buttonGroup.hasChildNodes()) {\n        toolbar.appendChild(buttonGroup);\n    }\n\n    var fmt_picker = document.createElement('select');\n    fmt_picker.classList = 'mpl-widget';\n    toolbar.appendChild(fmt_picker);\n    this.format_dropdown = fmt_picker;\n\n    for (var ind in mpl.extensions) {\n        var fmt = mpl.extensions[ind];\n        var option = document.createElement('option');\n        option.selected = fmt === mpl.default_extension;\n        option.innerHTML = fmt;\n        fmt_picker.appendChild(option);\n    }\n\n    var status_bar = document.createElement('span');\n    status_bar.classList = 'mpl-message';\n    toolbar.appendChild(status_bar);\n    this.message = status_bar;\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\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\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], msg['forward']);\n        fig.send_message('refresh', {});\n    }\n};\n\nmpl.figure.prototype.handle_rubberband = function (fig, msg) {\n    var x0 = msg['x0'] / fig.ratio;\n    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n    var x1 = msg['x1'] / fig.ratio;\n    var y1 = (fig.canvas.height - msg['y1']) / fig.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,\n        0,\n        fig.canvas.width / fig.ratio,\n        fig.canvas.height / fig.ratio\n    );\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    fig.rubberband_canvas.style.cursor = msg['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.handle_history_buttons = function (fig, msg) {\n    for (var key in msg) {\n        if (!(key in fig.buttons)) {\n            continue;\n        }\n        fig.buttons[key].disabled = !msg[key];\n        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n    }\n};\n\nmpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n    if (msg['mode'] === 'PAN') {\n        fig.buttons['Pan'].classList.add('active');\n        fig.buttons['Zoom'].classList.remove('active');\n    } else if (msg['mode'] === 'ZOOM') {\n        fig.buttons['Pan'].classList.remove('active');\n        fig.buttons['Zoom'].classList.add('active');\n    } else {\n        fig.buttons['Pan'].classList.remove('active');\n        fig.buttons['Zoom'].classList.remove('active');\n    }\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            var img = evt.data;\n            if (img.type !== 'image/png') {\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                img.type = 'image/png';\n            }\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\n            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n                img\n            );\n            fig.updated_canvas_event();\n            fig.waiting = false;\n            return;\n        } else if (\n            typeof evt.data === 'string' &&\n            evt.data.slice(0, 21) === 'data:image/png;base64'\n        ) {\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(\n                \"No handler for the '\" + msg_type + \"' message type: \",\n                msg\n            );\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(\n                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n                    e,\n                    e.stack,\n                    msg\n                );\n            }\n        }\n    };\n};\n\n// from https://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    }\n    if (e.target) {\n        targ = e.target;\n    } else if (e.srcElement) {\n        targ = e.srcElement;\n    }\n    if (targ.nodeType === 3) {\n        // defeat Safari bug\n        targ = targ.parentNode;\n    }\n\n    // pageX,Y are the mouse positions relative to the document\n    var boundingRect = targ.getBoundingClientRect();\n    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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 * https://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        }\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        this.canvas.focus();\n        this.canvas_div.focus();\n    }\n\n    var x = canvas_pos.x * this.ratio;\n    var y = canvas_pos.y * this.ratio;\n\n    this.send_message(name, {\n        x: x,\n        y: y,\n        button: event.button,\n        step: event.step,\n        guiEvent: simpleKeys(event),\n    });\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    // Prevent repeat events\n    if (name === 'key_press') {\n        if (event.key === this._key) {\n            return;\n        } else {\n            this._key = event.key;\n        }\n    }\n    if (name === 'key_release') {\n        this._key = null;\n    }\n\n    var value = '';\n    if (event.ctrlKey && event.key !== 'Control') {\n        value += 'ctrl+';\n    }\n    else if (event.altKey && event.key !== 'Alt') {\n        value += 'alt+';\n    }\n    else if (event.shiftKey && event.key !== 'Shift') {\n        value += 'shift+';\n    }\n\n    value += 'k' + event.key;\n\n    this._key_event_extra(event, name);\n\n    this.send_message(name, { key: value, 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};\n\n///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n// prettier-ignore\nvar _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\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\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n\nmpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n\nmpl.default_extension = \"png\";/* global mpl */\n\nvar 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.binaryType = comm.kernel.ws.binaryType;\n    ws.readyState = comm.kernel.ws.readyState;\n    function updateReadyState(_event) {\n        if (comm.kernel.ws) {\n            ws.readyState = comm.kernel.ws.readyState;\n        } else {\n            ws.readyState = 3; // Closed state.\n        }\n    }\n    comm.kernel.ws.addEventListener('open', updateReadyState);\n    comm.kernel.ws.addEventListener('close', updateReadyState);\n    comm.kernel.ws.addEventListener('error', updateReadyState);\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        var data = msg['content']['data'];\n        if (data['blob'] !== undefined) {\n            data = {\n                data: new Blob(msg['buffers'], { type: data['blob'] }),\n            };\n        }\n        // Pass the mpl event to the overridden (by mpl) onmessage function.\n        ws.onmessage(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 = document.getElementById(id);\n    var ws_proxy = comm_websocket_adapter(comm);\n\n    function ondownload(figure, _format) {\n        window.open(figure.canvas.toDataURL());\n    }\n\n    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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    fig.cell_info[0].output_area.element.on(\n        'cleared',\n        { fig: fig },\n        fig._remove_fig_handler\n    );\n};\n\nmpl.figure.prototype.handle_close = function (fig, msg) {\n    var width = fig.canvas.width / fig.ratio;\n    fig.cell_info[0].output_area.element.off(\n        'cleared',\n        fig._remove_fig_handler\n    );\n    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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.innerHTML =\n        '<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 / this.ratio;\n    var dataURL = this.canvas.toDataURL();\n    this.cell_info[1]['text/html'] =\n        '<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 () {\n        fig.push_to_output();\n    }, 1000);\n};\n\nmpl.figure.prototype._init_toolbar = function () {\n    var fig = this;\n\n    var toolbar = document.createElement('div');\n    toolbar.classList = 'btn-toolbar';\n    this.root.appendChild(toolbar);\n\n    function on_click_closure(name) {\n        return function (_event) {\n            return fig.toolbar_button_onclick(name);\n        };\n    }\n\n    function on_mouseover_closure(tooltip) {\n        return function (event) {\n            if (!event.currentTarget.disabled) {\n                return fig.toolbar_button_onmouseover(tooltip);\n            }\n        };\n    }\n\n    fig.buttons = {};\n    var buttonGroup = document.createElement('div');\n    buttonGroup.classList = 'btn-group';\n    var button;\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            /* Instead of a spacer, we start a new button group. */\n            if (buttonGroup.hasChildNodes()) {\n                toolbar.appendChild(buttonGroup);\n            }\n            buttonGroup = document.createElement('div');\n            buttonGroup.classList = 'btn-group';\n            continue;\n        }\n\n        button = fig.buttons[name] = document.createElement('button');\n        button.classList = 'btn btn-default';\n        button.href = '#';\n        button.title = name;\n        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n        button.addEventListener('click', on_click_closure(method_name));\n        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n        buttonGroup.appendChild(button);\n    }\n\n    if (buttonGroup.hasChildNodes()) {\n        toolbar.appendChild(buttonGroup);\n    }\n\n    // Add the status bar.\n    var status_bar = document.createElement('span');\n    status_bar.classList = 'mpl-message pull-right';\n    toolbar.appendChild(status_bar);\n    this.message = status_bar;\n\n    // Add the close button to the window.\n    var buttongrp = document.createElement('div');\n    buttongrp.classList = 'btn-group inline pull-right';\n    button = document.createElement('button');\n    button.classList = 'btn btn-mini btn-primary';\n    button.href = '#';\n    button.title = 'Stop Interaction';\n    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n    button.addEventListener('click', function (_evt) {\n        fig.handle_close(fig, {});\n    });\n    button.addEventListener(\n        'mouseover',\n        on_mouseover_closure('Stop Interaction')\n    );\n    buttongrp.appendChild(button);\n    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n};\n\nmpl.figure.prototype._remove_fig_handler = function (event) {\n    var fig = event.data.fig;\n    if (event.target !== this) {\n        // Ignore bubbled events from children.\n        return;\n    }\n    fig.close_ws(fig, {});\n};\n\nmpl.figure.prototype._root_extra_style = function (el) {\n    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n};\n\nmpl.figure.prototype._canvas_extra_style = function (el) {\n    // this is important to make the div 'focusable\n    el.setAttribute('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    } else {\n        // location in version 2\n        IPython.keyboard_manager.register_events(el);\n    }\n};\n\nmpl.figure.prototype._key_event_extra = function (event, _name) {\n    // Check for shift+enter\n    if (event.shiftKey && event.which === 13) {\n        this.canvas_div.blur();\n        // select the cell after this one\n        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n        IPython.notebook.select(index + 1);\n    }\n};\n\nmpl.figure.prototype.handle_save = function (fig, _msg) {\n    fig.ondownload(fig, null);\n};\n\nmpl.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.\nif (IPython.notebook.kernel !== null) {\n    IPython.notebook.kernel.comm_manager.register_target(\n        'matplotlib',\n        mpl.mpl_figure_comm\n    );\n}\n"
+      "text/plain": "<Figure size 432x288 with 1 Axes>",
+      "image/png": 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\n"
      },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": "<IPython.core.display.HTML object>",
-      "text/html": "<div id='8f20078f-42e0-4262-b7b3-1447f9863122'></div>"
+     "metadata": {
+      "needs_background": "light"
      },
-     "metadata": {},
      "output_type": "display_data"
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/opt/homebrew/Caskroom/miniforge/base/envs/evolving/lib/python3.8/site-packages/matplotlib/animation.py:887: UserWarning: Animation was deleted without rendering anything. This is most likely not intended. To prevent deletion, assign the Animation to a variable, e.g. `anim`, that exists until you have outputted the Animation using `plt.show()` or `anim.save()`.\n",
-      "  warnings.warn(\n"
-     ]
     }
    ],
    "source": [
-    "# Hyper-parameters\n",
-    "ENERGY_LOSS_GENERAL = 0.1\n",
-    "ENERGY_LOSS_ACTIONS = 0.2\n",
-    "\n",
-    "FOOD_TO_ENERGY = 0.1\n",
-    "WATER_TO_ENERGY = 0.1\n",
-    "\n",
-    "# Rotation vectors for movement\n",
-    "theta = np.deg2rad(45)\n",
-    "rot_right = np.array([[cos(theta), -sin(theta)], [sin(theta), cos(theta)]])\n",
-    "rot_left = np.array([[cos(-theta), -sin(-theta)], [sin(-theta), cos(-theta)]])\n",
-    "\n",
-    "class Being:\n",
-    "    \"\"\"\n",
-    "    Living being representation. If energy reaches 0 it will be dead\n",
-    "\n",
-    "    Energy goes down when performing actions, low energy leads to lower happiness.\n",
-    "    \"\"\"\n",
-    "    # Subjective states (things the \"brain\" feels)\n",
-    "    happiness = 1\n",
-    "    hunger = 0\n",
-    "    thirst = 0\n",
-    "\n",
-    "    # Objective states (hidden from the \"brain\")\n",
-    "    food = 1\n",
-    "    water = 1\n",
-    "    energy = 1\n",
-    "\n",
-    "    direction = [1, 0] # vector from (0,0) (the being) to the direction its facing\n",
-    "    action_space = ['NOOP', 'TURN_LEFT', 'TURN_RIGHT', 'MOVE', 'EAT', 'DRINK']\n",
-    "\n",
-    "    def choose_action(self):\n",
-    "        action = random.choice(self.action_space)\n",
-    "\n",
-    "        if action != 'NOOP':\n",
-    "            self.energy -= ENERGY_LOSS_ACTIONS\n",
-    "\n",
-    "        if action == 'TURN_LEFT' or action == 'TURN_RIGHT':\n",
-    "            rot = rot_left if action == 'TURN_LEFT' else rot_right\n",
-    "            self.direction = np.round(np.dot(rot, self.direction), 0).astype(int)\n",
-    "\n",
-    "        return action\n",
-    "\n",
-    "    def step(self):\n",
-    "        self.energy -= ENERGY_LOSS_GENERAL\n",
-    "\n",
-    "        if self.food > 0:\n",
-    "            self.food -= FOOD_TO_ENERGY\n",
-    "            self.energy += FOOD_TO_ENERGY\n",
-    "\n",
-    "        if self.water > 0:\n",
-    "            self.water -= WATER_TO_ENERGY\n",
-    "            self.energy += WATER_TO_ENERGY\n",
-    "\n",
-    "    def color(self):\n",
-    "        return 155 + self.energy * 100\n",
-    "\n",
-    "class Cell:\n",
-    "    def __init__(self, x, y):\n",
-    "        self.x = x\n",
-    "        self.y = y\n",
-    "        self.type = 'NONE'\n",
-    "        self.content = None\n",
-    "\n",
-    "    def update(self, type, content=None):\n",
-    "        self.type = type\n",
-    "        self.content = content\n",
-    "\n",
-    "    def color(self):\n",
-    "        if self.type == 'NONE':\n",
-    "            return 0\n",
-    "\n",
-    "        if self.type == 'BEING':\n",
-    "            return self.content.color()\n",
-    "\n",
-    "class World:\n",
-    "    def __init__(self, w=128, h=128):\n",
-    "        self.w = w\n",
-    "        self.h = h\n",
-    "        self.state = np.empty((w, h), dtype=object)\n",
-    "        for i in range(w):\n",
-    "            for j in range(h):\n",
-    "                self.state[i, j] = Cell(i, j)\n",
-    "\n",
-    "        self.im = plt.imshow(np.zeros((self.w, self.h)), cmap='gray', vmin=0, vmax=255, animated=True)\n",
-    "\n",
-    "    def step(self):\n",
-    "        state = np.copy(self.state)\n",
-    "\n",
-    "        for i, row in enumerate(self.state):\n",
-    "            for j, cell in enumerate(row):\n",
-    "                if cell.type != 'BEING':\n",
-    "                    continue\n",
-    "\n",
-    "                cell.content.step()\n",
-    "                action = cell.content.choose_action()\n",
-    "\n",
-    "                if action == 'MOVE':\n",
-    "                    # lets see if the desired cell is empty\n",
-    "                    direction = cell.content.direction\n",
-    "                    next_loc = [\n",
-    "                        max(0, min(self.w - 1, cell.x + direction[0])),\n",
-    "                        max(0, min(self.h - 1, cell.y + direction[1]))\n",
-    "                    ]\n",
-    "\n",
-    "                    if state[next_loc[0], next_loc[1]].type == 'NONE':\n",
-    "                        # cell is empty, lets move!\n",
-    "                        state[next_loc[0], next_loc[1]].update('BEING', cell.content)\n",
-    "                        state[i, j].update('NONE')\n",
-    "\n",
-    "        self.state = state\n",
-    "\n",
-    "    def spawn(self, number):\n",
-    "        for _ in range(number):\n",
-    "            x = random.randint(0, self.w - 1)\n",
-    "            y = random.randint(0, self.h - 1)\n",
-    "\n",
-    "            while self.state[x, y].type != 'NONE':\n",
-    "                x = random.randint(0, self.w - 1)\n",
-    "                y = random.randint(0, self.h - 1)\n",
-    "                # TODO: this could be infinite\n",
+    "from src.world import World\n",
     "\n",
-    "            being = Being()\n",
-    "            self.state[x, y].update('BEING', being)\n",
+    "world = World(WORLD_SIZE, WORLD_SIZE)\n",
+    "for _ in range(INITIAL_POPULATION):\n",
+    "    location, _ = world.spawn(0)\n",
     "\n",
-    "    def render(self):\n",
-    "        state = np.zeros((self.w, self.h))\n",
-    "        for i, row in enumerate(self.state):\n",
-    "            for j, cell in enumerate(row):\n",
-    "                state[i, j] = cell.color()\n",
+    "population_size = []\n",
+    "avg_energy = []\n",
     "\n",
-    "        self.im.set_array(state)\n",
-    "        return [self.im]\n",
-    "\n",
-    "fig = plt.figure(figsize=(10, 10))\n",
-    "plt.xticks([])\n",
-    "plt.yticks([])\n",
-    "\n",
-    "world = World()\n",
-    "world.spawn(10)\n",
-    "world.render()\n",
-    "\n",
-    "def animate():\n",
+    "while len(world.locations) > 0:\n",
     "    world.step()\n",
-    "    return world.render()\n",
     "\n",
-    "fps = 30\n",
+    "    population_size.append(world.alive)\n",
+    "\n",
+    "    total_energy = 0\n",
+    "    for being in world.locations.values():\n",
+    "        total_energy += being.energy\n",
+    "\n",
+    "    avg_energy.append(total_energy)\n",
     "\n",
-    "animation.FuncAnimation(fig, animate, frames=100, interval=1000/fps)\n",
+    "plt.title(f'Stats per epoch ({len(population_size)} epochs)')\n",
+    "plt.plot(population_size, label='Population')\n",
+    "plt.plot(avg_energy, label='Energy')\n",
+    "plt.grid()\n",
+    "plt.legend()\n",
     "plt.show()"
    ],
    "metadata": {
@@ -211,117 +90,133 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 64,
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[ 0 -1]\n",
-      "[-1 -1]\n",
-      "[-1  0]\n",
-      "[-1  1]\n",
-      "[0 1]\n",
-      "[1 1]\n",
-      "[1 0]\n",
-      "[ 1 -1]\n",
-      "[ 0 -1]\n",
-      "[-1 -1]\n"
+      "vision_pixel_size 9\n",
+      "angles 247.5 292.5\n",
+      "(1, 0.5) 27\n",
+      "(-0.8, -0.5) 212\n",
+      "(-0.1, -0.6) 261\n",
+      "  chunk: 1 0.6082762530298219\n",
+      "(-0.67, 0.2) 163\n",
+      "\n",
+      "Vision array (shows a 1 when there is a being within viewing distance in that direction)\n",
+      "[0, 1, 0, 0, 0]\n"
      ]
+    },
+    {
+     "data": {
+      "text/plain": "<Figure size 720x720 with 1 Axes>",
+      "image/png": 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\n"
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
     }
    ],
    "source": [
-    "from math import cos, sin\n",
+    "import math\n",
     "\n",
-    "theta = np.deg2rad(45)\n",
-    "rot_right = np.array([[cos(theta), -sin(theta)], [sin(theta), cos(theta)]])\n",
-    "rot_left = np.array([[cos(-theta), -sin(-theta)], [sin(-theta), cos(-theta)]])\n",
+    "# Vision model\n",
     "\n",
-    "vec = np.array([0, -1])\n",
+    "vision_angle = 45\n",
+    "vision_pixels = 5\n",
+    "vision_distance = 1\n",
     "\n",
-    "print(vec)\n",
-    "for i in range(9):\n",
-    "    vec = np.round(np.dot(rot_left, vec), 0).astype(int)\n",
-    "    print(vec)"
-   ],
-   "metadata": {
-    "collapsed": false,
-    "pycharm": {
-     "name": "#%%\n"
-    }
-   }
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "outputs": [
-    {
-     "ename": "KeyboardInterrupt",
-     "evalue": "",
-     "output_type": "error",
-     "traceback": [
-      "\u001B[0;31m---------------------------------------------------------------------------\u001B[0m",
-      "\u001B[0;31mKeyboardInterrupt\u001B[0m                         Traceback (most recent call last)",
-      "Input \u001B[0;32mIn [5]\u001B[0m, in \u001B[0;36m<cell line: 33>\u001B[0;34m()\u001B[0m\n\u001B[1;32m     31\u001B[0m window \u001B[38;5;241m=\u001B[39m MyGame()\n\u001B[1;32m     32\u001B[0m window\u001B[38;5;241m.\u001B[39msetup()\n\u001B[0;32m---> 33\u001B[0m \u001B[43marcade\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mrun\u001B[49m\u001B[43m(\u001B[49m\u001B[43m)\u001B[49m\n",
-      "File \u001B[0;32m/opt/homebrew/Caskroom/miniforge/base/envs/evolving/lib/python3.8/site-packages/arcade/window_commands.py:289\u001B[0m, in \u001B[0;36mrun\u001B[0;34m()\u001B[0m\n\u001B[1;32m    286\u001B[0m \u001B[38;5;28;01mimport\u001B[39;00m \u001B[38;5;21;01msys\u001B[39;00m\n\u001B[1;32m    287\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m sys\u001B[38;5;241m.\u001B[39mplatform \u001B[38;5;241m!=\u001B[39m \u001B[38;5;124m'\u001B[39m\u001B[38;5;124mwin32\u001B[39m\u001B[38;5;124m'\u001B[39m:\n\u001B[1;32m    288\u001B[0m     \u001B[38;5;66;03m# For non windows platforms, just do pyglet run\u001B[39;00m\n\u001B[0;32m--> 289\u001B[0m     \u001B[43mpyglet\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mapp\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mrun\u001B[49m\u001B[43m(\u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m    290\u001B[0m \u001B[38;5;28;01melse\u001B[39;00m:\n\u001B[1;32m    291\u001B[0m     \u001B[38;5;66;03m# Ok, some Windows platforms have a timer resolution > 15 ms. That can\u001B[39;00m\n\u001B[1;32m    292\u001B[0m     \u001B[38;5;66;03m# drop our FPS to 32 FPS or so. This reduces resolution so we can keep\u001B[39;00m\n\u001B[1;32m    293\u001B[0m     \u001B[38;5;66;03m# FPS up.\u001B[39;00m\n\u001B[1;32m    294\u001B[0m     \u001B[38;5;28;01mimport\u001B[39;00m \u001B[38;5;21;01mcontextlib\u001B[39;00m\n",
-      "File \u001B[0;32m/opt/homebrew/Caskroom/miniforge/base/envs/evolving/lib/python3.8/site-packages/pyglet/app/__init__.py:107\u001B[0m, in \u001B[0;36mrun\u001B[0;34m(interval)\u001B[0m\n\u001B[1;32m     99\u001B[0m \u001B[38;5;28;01mdef\u001B[39;00m \u001B[38;5;21mrun\u001B[39m(interval\u001B[38;5;241m=\u001B[39m\u001B[38;5;241m1\u001B[39m\u001B[38;5;241m/\u001B[39m\u001B[38;5;241m60\u001B[39m):\n\u001B[1;32m    100\u001B[0m     \u001B[38;5;124;03m\"\"\"Begin processing events, scheduled functions and window updates.\u001B[39;00m\n\u001B[1;32m    101\u001B[0m \n\u001B[1;32m    102\u001B[0m \u001B[38;5;124;03m    This is a convenience function, equivalent to::\u001B[39;00m\n\u001B[0;32m   (...)\u001B[0m\n\u001B[1;32m    105\u001B[0m \n\u001B[1;32m    106\u001B[0m \u001B[38;5;124;03m    \"\"\"\u001B[39;00m\n\u001B[0;32m--> 107\u001B[0m     \u001B[43mevent_loop\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mrun\u001B[49m\u001B[43m(\u001B[49m\u001B[43minterval\u001B[49m\u001B[43m)\u001B[49m\n",
-      "File \u001B[0;32m/opt/homebrew/Caskroom/miniforge/base/envs/evolving/lib/python3.8/site-packages/pyglet/app/base.py:185\u001B[0m, in \u001B[0;36mEventLoop.run\u001B[0;34m(self, interval)\u001B[0m\n\u001B[1;32m    183\u001B[0m \u001B[38;5;28;01mwhile\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mhas_exit:\n\u001B[1;32m    184\u001B[0m     timeout \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39midle()\n\u001B[0;32m--> 185\u001B[0m     \u001B[43mplatform_event_loop\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mstep\u001B[49m\u001B[43m(\u001B[49m\u001B[43mtimeout\u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m    187\u001B[0m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mis_running \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mFalse\u001B[39;00m\n\u001B[1;32m    188\u001B[0m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mdispatch_event(\u001B[38;5;124m'\u001B[39m\u001B[38;5;124mon_exit\u001B[39m\u001B[38;5;124m'\u001B[39m)\n",
-      "File \u001B[0;32m/opt/homebrew/Caskroom/miniforge/base/envs/evolving/lib/python3.8/site-packages/pyglet/app/cocoa.py:142\u001B[0m, in \u001B[0;36mCocoaEventLoop.step\u001B[0;34m(self, timeout)\u001B[0m\n\u001B[1;32m    138\u001B[0m \u001B[38;5;66;03m# Retrieve the next event (if any).  We wait for an event to show up\u001B[39;00m\n\u001B[1;32m    139\u001B[0m \u001B[38;5;66;03m# and then process it, or if timeout_date expires we simply return.\u001B[39;00m\n\u001B[1;32m    140\u001B[0m \u001B[38;5;66;03m# We only process one event per call of step().\u001B[39;00m\n\u001B[1;32m    141\u001B[0m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_is_running\u001B[38;5;241m.\u001B[39mset()\n\u001B[0;32m--> 142\u001B[0m event \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mNSApp\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mnextEventMatchingMask_untilDate_inMode_dequeue_\u001B[49m\u001B[43m(\u001B[49m\n\u001B[1;32m    143\u001B[0m \u001B[43m    \u001B[49m\u001B[43mcocoapy\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mNSAnyEventMask\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mtimeout_date\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mcocoapy\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mNSDefaultRunLoopMode\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;28;43;01mTrue\u001B[39;49;00m\u001B[43m)\u001B[49m\n\u001B[1;32m    145\u001B[0m \u001B[38;5;66;03m# Dispatch the event (if any).\u001B[39;00m\n\u001B[1;32m    146\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m event \u001B[38;5;129;01mis\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m \u001B[38;5;28;01mNone\u001B[39;00m:\n",
-      "File \u001B[0;32m/opt/homebrew/Caskroom/miniforge/base/envs/evolving/lib/python3.8/site-packages/pyglet/libs/darwin/cocoapy/runtime.py:805\u001B[0m, in \u001B[0;36mObjCBoundMethod.__call__\u001B[0;34m(self, *args)\u001B[0m\n\u001B[1;32m    803\u001B[0m \u001B[38;5;28;01mdef\u001B[39;00m \u001B[38;5;21m__call__\u001B[39m(\u001B[38;5;28mself\u001B[39m, \u001B[38;5;241m*\u001B[39margs):\n\u001B[1;32m    804\u001B[0m     \u001B[38;5;124;03m\"\"\"Call the method with the given arguments.\"\"\"\u001B[39;00m\n\u001B[0;32m--> 805\u001B[0m     \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mmethod\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mobjc_id\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43margs\u001B[49m\u001B[43m)\u001B[49m\n",
-      "File \u001B[0;32m/opt/homebrew/Caskroom/miniforge/base/envs/evolving/lib/python3.8/site-packages/pyglet/libs/darwin/cocoapy/runtime.py:775\u001B[0m, in \u001B[0;36mObjCMethod.__call__\u001B[0;34m(self, objc_id, *args)\u001B[0m\n\u001B[1;32m    773\u001B[0m f \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mget_callable()\n\u001B[1;32m    774\u001B[0m \u001B[38;5;28;01mtry\u001B[39;00m:\n\u001B[0;32m--> 775\u001B[0m     result \u001B[38;5;241m=\u001B[39m \u001B[43mf\u001B[49m\u001B[43m(\u001B[49m\u001B[43mobjc_id\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mselector\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43margs\u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m    776\u001B[0m     \u001B[38;5;66;03m# Convert result to python type if it is a instance or class pointer.\u001B[39;00m\n\u001B[1;32m    777\u001B[0m     \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mrestype \u001B[38;5;241m==\u001B[39m ObjCInstance:\n",
-      "\u001B[0;31mKeyboardInterrupt\u001B[0m: "
-     ]
-    }
-   ],
-   "source": [
-    "import arcade\n",
+    "vision_pixel_size = vision_angle // vision_pixels\n",
     "\n",
-    "SCREEN_WIDTH = 1000\n",
-    "SCREEN_HEIGHT = 650\n",
-    "SCREEN_TITLE = \"Platformer\"\n",
+    "print('vision_pixel_size', vision_pixel_size)\n",
     "\n",
+    "# Test data\n",
+    "main = (0, 0)\n",
+    "direction = [0, -1]\n",
     "\n",
-    "class MyGame(arcade.Window):\n",
-    "    \"\"\"\n",
-    "    Main application class.\n",
-    "    \"\"\"\n",
+    "beings_x = [1, -0.8, -0.1, -0.67]\n",
+    "beings_y = [0.5, -0.5, -0.6, 0.2]\n",
     "\n",
-    "    def __init__(self):\n",
+    "# Vision calculations\n",
     "\n",
-    "        # Call the parent class and set up the window\n",
-    "        super().__init__(SCREEN_WIDTH, SCREEN_HEIGHT, SCREEN_TITLE)\n",
+    "direction_angle = math.degrees(math.atan2(direction[1], direction[0]))\n",
+    "vision_line = (\n",
+    "    main[0] + direction[0] * vision_distance,\n",
+    "    main[1] + direction[1] * vision_distance,\n",
+    ")\n",
     "\n",
-    "        arcade.set_background_color(arcade.csscolor.CORNFLOWER_BLUE)\n",
+    "# calculate angles between the main being and each of the others\n",
+    "# the ones that are within +- 45 degrees + within the distance are \"visible\"\n",
+    "# either this or we ray trace (calculate equations for the lines and see if any being falls within it)\n",
+    "# and then use the distance for the color\n",
     "\n",
-    "    def setup(self):\n",
-    "        \"\"\"Set up the game here. Call this function to restart the game.\"\"\"\n",
-    "        pass\n",
+    "# the issue with the ray tracing is that as we get further, they'll be far from the lines\n",
+    "# I think it'll be best to do the angle thing, and then map angles to pixels of vision\n",
     "\n",
-    "    def on_draw(self):\n",
-    "        \"\"\"Render the screen.\"\"\"\n",
+    "min_angle = direction_angle - vision_angle / 2\n",
+    "max_angle = direction_angle + vision_angle / 2\n",
     "\n",
-    "        self.clear()\n",
-    "        # Code to draw the screen goes here\n",
+    "min_angle %= 360\n",
+    "max_angle %= 360\n",
     "\n",
+    "# min_angle = min_angle - 360 if min_angle > 180 else min_angle\n",
+    "# max_angle = max_angle - 360 if max_angle > 180 else max_angle\n",
     "\n",
-    "window = MyGame()\n",
-    "window.setup()\n",
-    "arcade.run()\n"
-   ],
-   "metadata": {
-    "collapsed": false,
-    "pycharm": {
-     "name": "#%%\n"
-    }
-   }
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "outputs": [],
-   "source": [
-    "window.close()\n",
-    "arcade.exit()"
+    "print('angles', min_angle, max_angle)\n",
+    "\n",
+    "vision = [0] * vision_pixels\n",
+    "\n",
+    "for coords in zip(beings_x, beings_y):\n",
+    "    # angle between two points:\n",
+    "    # project each coord to the x/y axis\n",
+    "    # PI = 180\n",
+    "    # xx = x\n",
+    "\n",
+    "    y = coords[1] - main[1]\n",
+    "    x = coords[0] - main[0]\n",
+    "\n",
+    "    angle = math.atan2(y, x)\n",
+    "    angle_deg = math.degrees(angle)\n",
+    "    angle_deg %= 360\n",
+    "\n",
+    "    print(coords, round(angle_deg))\n",
+    "\n",
+    "    if min_angle <= angle_deg <= max_angle:\n",
+    "        dist = math.hypot(x, y)\n",
+    "        if dist <= vision_distance:\n",
+    "            # visible\n",
+    "            vision_chunk = int((angle_deg - min_angle) // vision_pixel_size)\n",
+    "            vision[vision_chunk] += 1\n",
+    "\n",
+    "            print('  chunk:', vision_chunk, dist)\n",
+    "        else:\n",
+    "            print('  Too far')\n",
+    "\n",
+    "print()\n",
+    "print('Vision array (shows a 1 when there is a being within viewing distance in that direction)')\n",
+    "print(vision)\n",
+    "\n",
+    "plt.rcParams[\"figure.figsize\"] = (10, 10)\n",
+    "\n",
+    "plt.title('Vision system test')\n",
+    "plt.scatter(beings_x, beings_y)\n",
+    "plt.plot([main[0]], [main[1]], marker='o', color='red')\n",
+    "\n",
+    "# Draw some axis to make it easier to \"debug\"\n",
+    "plt.plot([main[0], -1], [main[1], -1], color='yellow')\n",
+    "plt.plot([main[0], 1], [main[1], 1], color='yellow')\n",
+    "plt.plot([main[0], 1], [main[1], -1], color='yellow')\n",
+    "plt.plot([main[0], -1], [main[1], 1], color='yellow')\n",
+    "\n",
+    "for coord in zip(beings_x, beings_y):\n",
+    "    plt.plot([main[0], coord[0]], [main[1], coord[1]], color='red')\n",
+    "\n",
+    "plt.plot([main[0], main[0] + direction[0] * vision_distance], [main[1], main[1] + direction[1] * vision_distance], color='green')\n",
+    "\n",
+    "plt.grid()\n",
+    "plt.show()"
    ],
    "metadata": {
     "collapsed": false,