PRI_Práctica_en_clase_Convolución.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "PRI - Práctica en clase - Convolución",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyObckTb29oa2IcKI/uaFYd1",
      "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/github/mgarbanzo/PercepcionRemota/blob/main/PRI_Pr%C3%A1ctica_en_clase_Convoluci%C3%B3n.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0jXCtAT20FM4"
      },
      "source": [
        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)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6LubUbvk0YNC"
      },
      "source": [
        "Curso: Percepción Remota I\n",
        "\n",
        "Profesor: Marcial Garbanzo Salas\n",
        "\n",
        "Semestre: II-2021\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mmj0pZqbzZqf"
      },
      "source": [
        "# Práctica de convolución\n",
        "Enunciado:\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oBrdsbpG01rJ"
      },
      "source": [
        "import numpy as np\n",
        "import pylab as plt\n",
        "from scipy.constants import c\n",
        "from scipy import signal"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TzM9TrfwV2ub"
      },
      "source": [
        "Rmax = 6000\n",
        "tmax = Rmax/c\n",
        "Smax = 400\n",
        "smax = Smax/c"
      ],
      "execution_count": 53,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9THmQ1VAWVAM",
        "outputId": "2bd11af4-e42c-4c9e-c3a3-3da0882c5997"
      },
      "source": [
        "tmax, smax"
      ],
      "execution_count": 54,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(2.0013845711889123e-05, 1.3342563807926082e-06)"
            ]
          },
          "metadata": {},
          "execution_count": 54
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3CdS_UrNdu5Y"
      },
      "source": [
        "dt = 1E-9"
      ],
      "execution_count": 71,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xvHj7fSEXGqM"
      },
      "source": [
        "## Generar la señal"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lm5GQr0OXMSR"
      },
      "source": [
        "ts = np.arange(0,smax,dt)"
      ],
      "execution_count": 72,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WooaMXuYXf7N"
      },
      "source": [
        "fo = 40E6\n",
        "w = 2 * np.pi * fo"
      ],
      "execution_count": 73,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Mo9U-yQH1Ip0"
      },
      "source": [
        "Sx = np.sin(w*(ts-smax/2))/(w*(ts-smax/2))\n",
        "W = np.hamming(len(ts)) # Esta es la ventana que vamos a utilizar\n",
        "signal = Sx*W"
      ],
      "execution_count": 74,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uW1XxnBzd2Pf"
      },
      "source": [
        ""
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "id": "uUNaMphx1PhU",
        "outputId": "81d5aaec-5f4b-410c-cdca-513f5512320e"
      },
      "source": [
        "plt.figure()\n",
        "plt.plot(ts, signal, '-b')"
      ],
      "execution_count": 75,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7fc8b3283690>]"
            ]
          },
          "metadata": {},
          "execution_count": 75
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZG7RT38JYXBl"
      },
      "source": [
        "## Generar el entorno"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bmwsaCTWd4aj"
      },
      "source": [
        "t = np.arange(0,tmax,dt)"
      ],
      "execution_count": 76,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iVmfCqfIeFhw"
      },
      "source": [
        "S = np.zeros_like(t)"
      ],
      "execution_count": 80,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zL09Xo42eLuW"
      },
      "source": [
        "S[t<=smax] = signal"
      ],
      "execution_count": 81,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "id": "FHa-7hUzeTBI",
        "outputId": "83341609-ffa3-4e3f-e766-0b33d3a73806"
      },
      "source": [
        "plt.figure()\n",
        "plt.plot(t, S, '-b')"
      ],
      "execution_count": 82,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7fc8b3508710>]"
            ]
          },
          "metadata": {},
          "execution_count": 82
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IEbC5eraaSbe"
      },
      "source": [
        "N = 10\n",
        "ubicaciones= np.random.randint(0,len(t),size=N)"
      ],
      "execution_count": 126,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IQrHSvrzalP4"
      },
      "source": [
        "entorno = np.zeros_like(t)\n",
        "entorno[ubicaciones] = 1"
      ],
      "execution_count": 127,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "qJZEhXKEatSk",
        "outputId": "ad19f761-0aa0-4b4f-f999-4c4839a5c10f"
      },
      "source": [
        "plt.figure()\n",
        "plt.plot(c*t, entorno, '-b')"
      ],
      "execution_count": 128,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7fc8b75a40d0>]"
            ]
          },
          "metadata": {},
          "execution_count": 128
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "aS9GAyhpSi2m"
      },
      "source": [
        "# Calculando la convolución con numpy"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nPBXfhQ5bHy4"
      },
      "source": [
        "resultado = np.convolve(S,entorno, mode='full')"
      ],
      "execution_count": 144,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 283
        },
        "id": "rHv8La3FbN2l",
        "outputId": "86d0f7d3-7e75-4365-b765-951a1af4eba3"
      },
      "source": [
        "plt.figure()\n",
        "plt.plot(resultado)"
      ],
      "execution_count": 145,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7fc8a9f59dd0>]"
            ]
          },
          "metadata": {},
          "execution_count": 145
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JKU1MZtbbFk8"
      },
      "source": [
        "# Calculando la convolución espectralmente"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jUEhOlXrSmVD"
      },
      "source": [
        "FTS = np.fft.fft(S)\n",
        "FTE = np.fft.fft(entorno)\n",
        "XFT = np.fft.fftfreq(len(FTS),d=dt)"
      ],
      "execution_count": 131,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qQONU5PEYpSZ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "8e4a4fb6-bc61-450c-d7b1-af2e4c68f3d8"
      },
      "source": [
        "FTS"
      ],
      "execution_count": 132,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([12.50119208+8.88178420e-16j, 12.22798558-2.59914268e+00j,\n",
              "       11.42031339-5.08465875e+00j, ..., 10.11349405+7.34789325e+00j,\n",
              "       11.42031339+5.08465875e+00j, 12.22798558+2.59914268e+00j])"
            ]
          },
          "metadata": {},
          "execution_count": 132
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ajPxc5nqSdeV"
      },
      "source": [
        "# Visualizando espectros\n",
        "\n",
        "Primero graficamos los valores."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 324
        },
        "id": "YrNLLl_9UMVM",
        "outputId": "b6c88a9b-7021-4cf9-af63-ea80ae4de1fa"
      },
      "source": [
        "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12,4))\n",
        "fig.suptitle('Gráficos del cos(x)')\n",
        "ax1.plot(XFT,np.abs(FTS))\n",
        "ax2.plot(XFT,np.abs(FTE))"
      ],
      "execution_count": 133,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7fc8b30b7b50>]"
            ]
          },
          "metadata": {},
          "execution_count": 133
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sm1vEIGjfCMC"
      },
      "source": [
        "## Calculamos la convolución en Frecuencia"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vMFBdVg9fHsg"
      },
      "source": [
        "C = FTS * FTE"
      ],
      "execution_count": 134,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 324
        },
        "id": "AoLH43mPjAUJ",
        "outputId": "60932dad-6840-4f25-82a8-3fc3375572ee"
      },
      "source": [
        "fig, (ax1) = plt.subplots(1, 1, figsize=(12,4))\n",
        "fig.suptitle('Gráficos de la convolución')\n",
        "ax1.plot(XFT,np.abs(C))\n",
        "#plt.xlim((-1,1))"
      ],
      "execution_count": 135,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7fc8aa164910>]"
            ]
          },
          "metadata": {},
          "execution_count": 135
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "POV5PUzJfTHM"
      },
      "source": [
        "iFTC = np.fft.ifft(C)"
      ],
      "execution_count": 149,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 346
        },
        "id": "ygfg9sOofVs0",
        "outputId": "0f6a700d-6db2-4e0d-cc3f-e7095bdd9fea"
      },
      "source": [
        "fig, (ax1) = plt.subplots(1, 1, figsize=(12,4))\n",
        "fig.suptitle('Gráficos de la convolución')\n",
        "ax1.plot(iFTC)"
      ],
      "execution_count": 151,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/numpy/core/_asarray.py:83: ComplexWarning: Casting complex values to real discards the imaginary part\n",
            "  return array(a, dtype, copy=False, order=order)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7fc8a9d31090>]"
            ]
          },
          "metadata": {},
          "execution_count": 151
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NJ-OXEGNfaF8"
      },
      "source": [
        ""
      ],
      "execution_count": 137,
      "outputs": []
    }
  ]
}