folha_de_pixels.ipynb

folha_de_pixels.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "folha_de_pixels.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyOIvA/FyWVVR+z3/4QPMALf",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/jbrenorv/928692bf5ea66dc2f324c0eee1277f8e/folha_de_pixels.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FFNcTY-fogKc"
      },
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import math"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FTiM0GemtxRN"
      },
      "source": [
        "WHITE = 255\n",
        "\n",
        "def draw(im, lbd):\n",
        "  \"\"\"\n",
        "  im:  image. np.ndarray with shape (x,y,)\n",
        "  lbd: lambda for drawer\n",
        "  \"\"\"\n",
        "\n",
        "  for y in range(im.shape[0]):\n",
        "    for x in range(im.shape[1]):\n",
        "\n",
        "      # subtrair um certo valor para mudar o centro\n",
        "      if lbd(x - 256, y - 156):\n",
        "\n",
        "        # pinta o pixel (x, y) de branco\n",
        "        im[y][x] = WHITE\n",
        "  \n",
        "  return im"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LS9tjoyV0lIW"
      },
      "source": [
        "Uma imagem (512 x 512)px preta"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ycUDJcSPpHyS",
        "outputId": "5b6207d2-c110-49e9-e768-537174f07376"
      },
      "source": [
        "img = np.zeros((512, 512))\n",
        "img"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[0., 0., 0., ..., 0., 0., 0.],\n",
              "       [0., 0., 0., ..., 0., 0., 0.],\n",
              "       [0., 0., 0., ..., 0., 0., 0.],\n",
              "       ...,\n",
              "       [0., 0., 0., ..., 0., 0., 0.],\n",
              "       [0., 0., 0., ..., 0., 0., 0.],\n",
              "       [0., 0., 0., ..., 0., 0., 0.]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 111
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 269
        },
        "id": "gJKs6y0FtLGh",
        "outputId": "303d4556-1d4a-4013-fcb4-288d7a27b1d8"
      },
      "source": [
        "# raio do circulo que define o cardioide\n",
        "a = 100\n",
        "\n",
        "# cardioide: r = a(1 - senθ) em coordenadas polares\n",
        "drawp = lambda x, y: (x**2 + y**2) < a * (math.sqrt(x**2 + y**2) + y)\n",
        "\n",
        "result = draw(img, drawp)\n",
        "\n",
        "\n",
        "plt.imshow(result, cmap='gray')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}