gratings.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Examples of grating patterns\n",
    "\n",
    "This notebook shows a few examples of grating patterns used as stimuli for the spatial opponency experiments. It corresponds to Figure 5 in the appendinx.\n",
    "\n",
    "**Note**: The easiest way to use this is as a colab notebook, which allows you to dive in with no setup.\n",
    "\n",
    "## Load Dependencies - Colab Only"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from os.path import exists\n",
    "if not exists('opponency.zip'):\n",
    "    !wget -O opponency.zip https://github.com/ecs-vlc/opponency/archive/master.zip\n",
    "    !unzip -qq opponency.zip\n",
    "    !mv opponency-master/* ./\n",
    "    !rm -r opponency-master"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Generate Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.6275 \tWARNING \tMonitor specification not found. Creating a temporary one...\n",
      "1.2914 \tWARNING \tMonitor specification not found. Creating a temporary one...\n",
      "1.8848 \tWARNING \tMonitor specification not found. Creating a temporary one...\n",
      "2.4509 \tWARNING \tMonitor specification not found. Creating a temporary one...\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt \n",
    "from statistics.gratings import *\n",
    "\n",
    "freq = 4\n",
    "for degrees in [0, 45, 90, 135]:\n",
    "    theta = degrees\n",
    "    grating = make_grating(freq, theta, 0).squeeze(0)\n",
    "    plt.figure()\n",
    "    plt.axis('off')\n",
    "    plt.imshow(grating.permute(1, 2, 0))\n",
    "    plt.savefig('figures/' + str(degrees) + \"_grey.pdf\", bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
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 },
 "nbformat": 4,
 "nbformat_minor": 2
}