{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Y7JgKfzlPBrr"
      },
      "source": [
        "![taller_python](https://github.com/fifabsas/talleresfifabsas/blob/master/python/2_Numerico/fig/logo_fifa.png?raw=true)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "os_60KoG9612"
      },
      "source": [
        "# Taller de Python Capítulo 3:  Práctica\n",
        "[Link al notebook en Google Colaboratory](https://colab.research.google.com/drive/1K188p9vwJIG25aP3yi8EKm5xhDhe_wZm?usp=sharing)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "w5EORpIB961-"
      },
      "source": [
        "## Nuestra motivación para hoy\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oe2yJvZN6CXS"
      },
      "source": [
        "La idea de hoy es que aprendan un poquito sobre otro tipo de objeto que existe en Python: los `diccionarios` y sobre una función que puede serles útil en el futuro: `find_peaks`.\n",
        "\n",
        "Una vez aprendido esto, ¡Ponemos las manos en la masa y nos peleamos mucho rato con ejercicios re divertidos!.\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "687Ww3T3dDe4"
      },
      "source": [
        "## Diccionarios\n",
        "\n",
        "Los diccionarios son otro tipo de objetos útiles, en cierta forma similares a las listas, que nos permiten vincular un valor con otro.\n",
        "\n",
        "Estos se definen abriendo y cerrando **llaves**.\n",
        "\n",
        "Supongamos que queremos guardar en una variable los nombres de personajes importantes en la ciencia y relacionarlos a los campos en los que trabajaron."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ZC1BhdjJdIUf"
      },
      "outputs": [],
      "source": [
        "diccionario = {'Rosalind Franklin':'Química', 'Luis Caffarelli':'Matemática', 'Juan G. Roederer':'Física', 'Emmy Noether':'Matemática'}"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wQ9BkJiaiB6T"
      },
      "source": [
        "La parte que va a la _izquierda_ de los `:` se llama **llave**, mientras que lo que escribimos a la _derecha_ se llama **valor**.\n",
        "\n",
        "Es decir, la llave `Rosalind Franklin` tiene el valor `Química`.\n",
        "\n",
        "¿Cómo accedo a esto?"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IhRW-IaSd4ua",
        "outputId": "adfa3031-47bc-4ac9-f6de-4b26f93df4ae"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Química\n"
          ]
        }
      ],
      "source": [
        "print(diccionario[\"Rosalind Franklin\"])"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZJQClDxdeENq"
      },
      "source": [
        "Podemos acceder a todas las llaves y valores del diccionario."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vO7oQLYFeWsb",
        "outputId": "d671a1fb-0b48-421b-a5f6-72998f9d2394"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "dict_keys(['Rosalind Franklin', 'Luis Caffarelli', 'Juan G. Roederer', 'Emmy Noether'])\n",
            "\n",
            "\n",
            "dict_values(['Química', 'Matemática', 'Física', 'Matemática'])\n"
          ]
        }
      ],
      "source": [
        "llaves = diccionario.keys()\n",
        "print(llaves)\n",
        "\n",
        "print(\"\\n\")\n",
        "\n",
        "valores = diccionario.values()\n",
        "print(valores)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XFTD4V6qd1Ln"
      },
      "source": [
        "Hay varias formas de recorrer estos objetos con un `for`, pero la más importante es la siguiente, utilizando el método `.items()`:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rcGAdLcjj-gO",
        "outputId": "afbcdf10-0b63-4ce3-aa27-8d1693a001b2"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "La persona Rosalind Franklin se dedica a la Química\n",
            "\n",
            "La persona Luis Caffarelli se dedica a la Matemática\n",
            "\n",
            "La persona Juan G. Roederer se dedica a la Física\n",
            "\n",
            "La persona Emmy Noether se dedica a la Matemática\n",
            "\n"
          ]
        }
      ],
      "source": [
        "for llave, valor in diccionario.items():\n",
        "    print(f\"La persona {llave} se dedica a la {valor}\")\n",
        "    print()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "E0grxNXjkTnR"
      },
      "source": [
        "Para agregar un elemento al diccionario se hace de la siguiente manera:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "M6f7DSkIkkmb",
        "outputId": "69691a77-bcbe-4bdc-cba4-3e30685f04ec"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "{'Rosalind Franklin': 'Química', 'Luis Caffarelli': 'Matemática', 'Juan G. Roederer': 'Física', 'Emmy Noether': 'Matemática', 'Ada Lovelace': 'Computación'}\n"
          ]
        }
      ],
      "source": [
        "diccionario['Ada Lovelace'] = 'Computación'\n",
        "\n",
        "print(diccionario)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5g-PmLgR6rXB"
      },
      "source": [
        "Cada llave tiene un valor **único** y pueden tener adentro números, strings, listas o inclusive otro diccionario."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "vt21KpEM6bnx"
      },
      "outputs": [],
      "source": [
        "diccionario_raro = {\"Milanesa\": 42, \"Almohada\": \"No tengo\", \"Precios boleto\": [270,300,330,404, \"Carísimo\"]}"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "XubHgmF99MT8"
      },
      "outputs": [],
      "source": [
        "diccionario_raro[[12,13,14]] = \"¿Podré hacer esto?\""
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "EhenfPIp8f2v"
      },
      "source": [
        "## `find_peaks`: *como encontrar máximos y mínimos*"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "oOr1YICgFz5X"
      },
      "outputs": [],
      "source": [
        "# Importamos las librerías que vamos a usar\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DRKKliyjFsHn"
      },
      "source": [
        "Supongamos que tenemos los datos de la siguiente figura y queremos saber cuales son los máximos de la señal.\n",
        "\n",
        "¿Cómo hacemos?"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 465
        },
        "id": "QXEnKevEFsTZ",
        "outputId": "1f73b3c5-85fe-499a-8dbc-dd45bccc3309"
      },
      "outputs": [
        {
          "data": {
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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Definimos el dominio y la imagen\n",
        "x = np.linspace(0, 2*np.pi, 500)\n",
        "y = np.abs(np.sin(x)*np.sin(2.5*x))\n",
        "\n",
        "# Graficamos la función\n",
        "plt.plot(x, y)\n",
        "plt.xlabel('Eje de $\\hat x$', fontsize = 14)\n",
        "plt.ylabel('Eje de $\\hat y$', fontsize = 14)\n",
        "\n",
        "plt.grid()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dm9_5LnRJTH_"
      },
      "source": [
        "Para eso existe ```find_peaks```, una función de la librería llamada ```scipy``` que tiene un montón de cosas útiles para hacer ciencia."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "DZBCiNuVJEkx"
      },
      "outputs": [],
      "source": [
        "# De esta manera importamos solo la función y no la librería entera, que puede ser pesada\n",
        "from scipy.signal import find_peaks"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qMnGDRRHLMpd"
      },
      "source": [
        "```find_peaks``` recibe una lista/array de una dimensión y calcula los máximos locales.\n",
        "\n",
        "Apliquemos la función a nuestra tira de datos ```y``` para ver que nos devuelve."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-X-SUoAtJlpp",
        "outputId": "94603850-62d7-4bd5-bf01-7c23a5ece723"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "[ 62 146 223 276 353 437]\n",
            "\n",
            "\n",
            "{}\n"
          ]
        }
      ],
      "source": [
        "picos, diccionario = find_peaks(y) # Recordemos esta forma de nombrar varias variables\n",
        "\n",
        "print(picos)\n",
        "\n",
        "print(\"\\n\")\n",
        "\n",
        "print(diccionario)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "urDOxL7eMDmW"
      },
      "source": [
        "```find_peaks``` devuelve primero un array con los índices donde encontró máximos y luego un diccionario, que está vacío, pero más adelante vamos a ver que cosas puede contener.\n",
        "\n",
        "De momento, graficamos los picos para ver que encontró ```find_peaks``` de base."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 465
        },
        "id": "EN0VWY1wJwgF",
        "outputId": "c907ac32-59e1-4b9e-c040-a81d693d8e9d"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Graficamos la función\n",
        "plt.plot(x, y)\n",
        "\n",
        "plt.plot(x[picos], y[picos],\"o\", color = \"k\")\n",
        "\n",
        "\n",
        "plt.xlabel('Eje de $\\hat x$', fontsize = 14)\n",
        "plt.ylabel('Eje de $\\hat y$', fontsize = 14)\n",
        "\n",
        "plt.grid()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fGwxx0puNcuV"
      },
      "source": [
        "¡```find_peaks``` logró hallar todos los picos! ¡Es increíble!\n",
        "\n",
        "Veamos ahora otro caso."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 461
        },
        "id": "PbfcCTNdN88Z",
        "outputId": "9748a7b8-2358-49bc-c5fd-02d66006bec9"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Definimos el dominio y la imagen\n",
        "x = np.linspace(0, 2*np.pi, 500)\n",
        "y = np.abs(np.sin(x))+np.cos(5*x)/1.2\n",
        "\n",
        "# Graficamos la función\n",
        "plt.plot(x, y)\n",
        "plt.xlabel('Eje de $\\hat x$', fontsize = 14)\n",
        "plt.ylabel('Eje de $\\hat y$', fontsize = 14)\n",
        "\n",
        "plt.grid()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AM5Ya2w8OKiI"
      },
      "source": [
        "Ahora quiero los picos más grandes nada más.\n",
        "\n",
        "¿Que parámetro los caracteriza como para que  ```find_peaks``` encuentre solo esos?\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3kCEzuC5QVuR"
      },
      "source": [
        " ### Respuesta ***(¡Animense a contestar dale!)***"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2vZEUSdfQb0K"
      },
      "source": [
        "**Hay varias cosas que podríamos usar:**\n",
        "\n",
        "\n",
        "*   La altura de los picos.\n",
        "*   La distancia entre los picos (en índices)\n",
        "\n",
        "**Si utilizamos la altura de los picos obtenemos:**\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 461
        },
        "id": "MZbO5JqXQ09y",
        "outputId": "e179ed0f-a39c-40b9-c426-c7de130deeb2"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Calculamos los picos\n",
        "picos, diccionario = find_peaks(y, height = 1.5) # Acá agrego el parámetro\n",
        "\n",
        "# Graficamos la función\n",
        "plt.plot(x, y)\n",
        "plt.plot(x[picos], y[picos],\".\", c = \"k\", ms = 10)\n",
        "plt.xlabel('Eje de $\\hat x$', fontsize = 14)\n",
        "plt.ylabel('Eje de $\\hat y$', fontsize = 14)\n",
        "\n",
        "plt.grid()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7iEHO2yWREoa"
      },
      "source": [
        "¡Conseguimos lo que queremos! También podriamos haberle pasado la distancia u otro parámetro para que la función cuente con la mayor información posible.\n",
        "\n",
        "Podemos ver ahora que cambio el diccionario, este contiene ahora la altura de los picos."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "k9vuiphqRMfW",
        "outputId": "396c80be-3364-410c-bbf5-32e4fd28779f"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "{'peak_heights': array([1.78657323, 1.78657323])}"
            ]
          },
          "execution_count": 38,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "diccionario"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kjs-AUxVfe_K"
      },
      "source": [
        "Veamos otro parámetro más: el ```distance```.\n",
        "\n",
        "El ```distance``` define la cantidad de datos intermedios que debe haber entre picos. Hay que tener en cuenta que ```find_peaks``` recibe un array 1D, por lo que esta distancia es en índices y no en nuestra variable ```x```."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 461
        },
        "id": "eugTtoz7AMe0",
        "outputId": "87334321-5c05-4c62-abf2-ec4d56687673"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Calculamos los picos\n",
        "picos, diccionario = find_peaks(y, distance = 100) # Acá agrego el parámetro\n",
        "\n",
        "# Graficamos la función\n",
        "plt.plot(x, y)\n",
        "plt.plot(x[picos], y[picos],\".\", c = \"k\", ms = 10)\n",
        "plt.xlabel('Eje de $\\hat x$', fontsize = 14)\n",
        "plt.ylabel('Eje de $\\hat y$', fontsize = 14)\n",
        "\n",
        "plt.grid()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BGhdZ0bAjH7k"
      },
      "source": [
        "Existen muchos otros parámetros opcionales más tales como:\n",
        "\n",
        "\n",
        "\n",
        "*   **width**: Ancho de los picos (en índices)\n",
        "*   **threshold**: Delimita de cuanto puede ser el salto del máximo respecto a los otros puntos, verticalmente.\n",
        "*   **prominence**: Prominencia de los picos (que tan picudos son los picos)\n",
        "\n",
        "\n",
        "Si no, siempre conviene leer la [documentación](https://docs.scipy.org/doc/scipy/reference/generated/scipy.signal.find_peaks.html).\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HIL8fx8PqcVt"
      },
      "source": [
        "### Muy lindo todo esto... ¿Pero cómo puedo calcular los mínimos con ```find_peaks```?"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zQJemJQPry7e"
      },
      "source": [
        "Muy fácil: ¡Invertimos los datos!\n",
        "\n",
        "Así los mínimos pasan a ser los máximos y viceversa."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 461
        },
        "id": "UMce2R_Rrx5j",
        "outputId": "05be6edb-6bc6-4864-c02c-09b728d0c0e8"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Definimos el dominio y la imagen\n",
        "x = np.linspace(0, 2*np.pi, 500)\n",
        "y = np.abs(np.sin(x))+np.cos(5*x)/1.2\n",
        "\n",
        "# Calculamos los picos\n",
        "picos, diccionario = find_peaks(-y) # Acá agrego el parámetro\n",
        "\n",
        "# Graficamos la función\n",
        "plt.plot(x, y, label = \"Datos originales\")\n",
        "plt.plot(x, -y, label = \"Datos invertidos\")\n",
        "\n",
        "plt.xlabel('Eje de $\\hat x$', fontsize = 14)\n",
        "plt.ylabel('Eje de $\\hat y$', fontsize = 14)\n",
        "plt.legend(loc = \"upper left\", fontsize = 12)\n",
        "\n",
        "plt.grid()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 461
        },
        "id": "JbdhDMohsj4w",
        "outputId": "b7d5f022-f225-4a65-f556-4bfb9f66ea43"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Calculamos los picos\n",
        "picos, diccionario = find_peaks(-y) # Le paso los datos invertidos\n",
        "\n",
        "# Graficamos la función\n",
        "plt.plot(x, y)\n",
        "plt.plot(x[picos], y[picos],\".\", c = \"k\", ms = 10)\n",
        "plt.xlabel('Eje de $\\hat x$', fontsize = 14)\n",
        "plt.ylabel('Eje de $\\hat y$', fontsize = 14)\n",
        "\n",
        "plt.grid()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "y4CQvLRBCDN1"
      },
      "source": [
        "Con esto termina todo lo que teníamos para enseñarles hoy, ahora les toca aprender por su cuenta, llegó la hora de elegir un problema y pensar un rato largo.\n",
        "\n",
        "## ¡Manos a la obra!\n",
        "\n",
        "## Les pedimos por favor que **lean y respeten las consignas**."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9fVj0z1tbvSz"
      },
      "source": [
        "# _Problema integrador 1 (Física)_\n",
        "\n",
        "En un laboratorio se armó el montaje que se muestra a continuación: un carrito sujeto a un resorte fijo en uno de sus extremos.\n",
        "\n",
        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)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jJFe_UW05ZfX"
      },
      "source": [
        "Se propuso estudiar como la masa del carrito (que se podía variar agregando pesas sobre el) afectaba su frecuencia de oscilación. Con este objetivo, se realizó el siguiente procedimiento 9 veces, comenzando con el carrito vacío y agregando una pesa en cada iteración:\n",
        "\n",
        "1. Se comenzaba a grabar el carrito con una cámara lateral al montaje.\n",
        "2. El carrito se alejaba $5~\\mathrm{cm}$ de su posición de equilibrio y se soltaba.\n",
        "3. $10~\\mathrm{s}$ después de soltar el carrito, se cortaba la grabación. Esta se guardaba como `[n].mp4`, con `[n]` el número de pesas sobre el carrito.\n",
        "\n",
        "Finalmente se subieron todas las grabaciones a un software de trackeo, calibrado para poder medir la distancia del carrito a su posición de equilibrio cada $0.2~\\mathrm{s}$ desde que se soltó. Los datos de cada grabación se guardaron en archivos nombrados `[n].csv`, con `[n]` el número de pesas correspondiente.\n",
        "\n",
        "La idea es ahora hacer el análisis de las mediciones, que se pueden encontrar en este [link](https://github.com/fifabsas/talleresfifabsas/blob/4e61cb2c20365fd6c299ce317c963ff2b09d6201/python/3_Ejercicios/Datos%20Ejercicio%201%20-%20F%C3%ADsica/Datos%20Ejercicio%201%20-%20F%C3%ADsica.zip), en Python."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ccs3GpRG962T"
      },
      "source": [
        "---\n",
        "\n",
        "### Ejercicio 1 (para ir entrando en calor)\n",
        "\n",
        "Escribir una función llamada `masa_carrito(n)` que tome:\n",
        "- `n`: el número de pesas colocadas en el carro.\n",
        "\n",
        "y que devuelva:\n",
        "- `m`: la masa total del carrito.\n",
        "\n",
        "Considerar que la masa del carrito sin pesas era de $0.15~\\mathrm{Kg}$ y cada una de las pesas agregadas tenía una masa de $0.10~\\mathrm{Kg}$.\n",
        "\n",
        "---"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6Fd9nZca639_"
      },
      "source": [
        "Cada `.csv` tiene 3 columnas: \"T [s]\" para los tiempos, \"X [cm]\" para la posición, y \"X_err [cm]\" para la incerteza en la posicion. Las mediciones de tiempo también tienen incerteza, pero mucho más chica y la vamos a despreciar en el análisis. También despreciariemos las incertezas en las mediciones de masa. (Si llegan a encontrarse con un experimento similar en un labo, registren todas las incertezas y hablen con sus profes antes de no tener en cuenta incertezas en algún cálculo o ajuste).\n",
        "\n",
        "De cada archivo queremos obtener una frecuencia de oscilación. Para enfrentar esta tarea, vamos a empezar analizando solo un archivo, `0.csv`, y luego veremos como adaptar el código para poder analizar los otros .csv's sin hacer mucho más trabajo."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bHA-u8QgHhRm"
      },
      "source": [
        "---\n",
        "### Ejercicio 2: Abrir y graficar `0.csv`\n",
        "\n",
        "Queremos empezar graficando la posición en función del tiempo del carrito sin pesitas, para observar las mediciones registradas que pueden encontrar [acá](https://github.com/fifabsas/talleresfifabsas/blob/4e61cb2c20365fd6c299ce317c963ff2b09d6201/python/3_Ejercicios/Datos%20Ejercicio%201%20-%20F%C3%ADsica/Datos%20Ejercicio%201%20-%20F%C3%ADsica.zip).\n",
        "\n",
        "1. Importar `numpy` y `matplotlib.pyplot` para poder acceder a las funciones de Numpy y del módulo `pyplot` de Matplotlib. Usar las abreviaciones estandar `np` y `plt` (ver clase pasada).\n",
        "2. Cargar los datos del archivo `\"0.csv\"` subiendolo a Colab y usando la función `np.loadtxt`. Guardar:\n",
        "    - los _tiempos_ de las mediciones en la variable `ts`,\n",
        "    - las _posiciones_ medidas en `xs`,\n",
        "    - y las _incertezas_ de las posiciones en `xs_err`.\n",
        "    \n",
        "    _Para usar la función `np.loadtxt` tienen de referencia el material de la clase pasada o la documentación de Numpy_.\n",
        "3. Usar la función `plt.errorbar` para gráficar `xs` en función de `ts` (`ts` corresponde al eje $\\hat x$ del gráfico, mientras que `xs` corresponde al eje $\\hat y$). Incluir las incertezas en la posición.\n",
        "4. Etiquetar los ejes del gráfico \"Tiempo [s]\" (eje $\\hat x$) y \"Posición [cm]\" (eje $\\hat y$). De título poner \"0 pesas sobre el carrito\".\n",
        "5. _(opcional)_ Embellecer.\n",
        "\n",
        "---"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RjQre3h1GGPV"
      },
      "source": [
        "### UN PROBLEMA COMÚN\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ePqT8OJIHgpo"
      },
      "source": [
        "Ahora que vimos que los datos tienen un comportamiento oscilatorio, como es de esperar por la naturaleza del experimento, nuestro objetivo es medir su frecuencia de oscilación. Nos gustaría hacer un ajuste sinusoidal, pero como vimos la vez pasada, `curve_fit` no siempre devuelve los parámetros más óptimos. A veces devuelve los parámetros correspondientes a algún otro mínimo local de la función RMSE. Veamoslo con los datos de `0.csv`, ajustandolos con un coseno:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "cellView": "form",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 452
        },
        "id": "A5Bc6FOrHdBz",
        "outputId": "2d875ccb-9b9b-4eec-9e82-6494b6ef3042"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "#@title código secreto (solo abrir con doble-click **luego de haber intentado el Ejercicio 2**)\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "from scipy.optimize import curve_fit\n",
        "\n",
        "ts, xs, xs_err = np.loadtxt(\"0.csv\", delimiter = \",\", unpack = True, skiprows = 1)\n",
        "\n",
        "def sinusoidal(t, A, w, phi):\n",
        "    return A*np.cos(w*t + phi)\n",
        "\n",
        "popt, pcov = curve_fit(sinusoidal, ts, xs)\n",
        "A, w, phi = popt\n",
        "\n",
        "ts_ajuste = np.linspace(min(ts), max(ts), 1000)\n",
        "xs_ajuste = sinusoidal(ts_ajuste, A, w, phi)\n",
        "\n",
        "plt.errorbar(ts, xs, yerr = xs_err, fmt = \"s\", ms = 2, capsize = 2, color = \"k\")\n",
        "plt.plot(ts_ajuste, xs_ajuste, color = \"r\")\n",
        "plt.xlabel(\"$t$ [s]\")\n",
        "plt.ylabel(\"$x$ [cm]\")\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7U8MYWCSP77k"
      },
      "source": [
        "**¿Como solucionamos esto?** Como repaso, queremos que `curve_fit` empieze a buscar los parámetros óptimos _cerca de la solución que esperamos_, que se puede hacer pasandole parámetros iniciales a través del argumento `p0`:\n",
        "```python\n",
        "popt, pcov = curve_fit(sinusoidal, t, x, p0 = [5, w_aprox, 0])\n",
        "```\n",
        "De esta forma, la función va a buscar la frecuencia óptima cerca de la frecuencia aproximada `w_aprox`.\n",
        "\n",
        "La pregunta es ahora, **¿de donde sacamos estos parámetros iniciales?** Algunas posibilidades:\n",
        "- **Usando más información:** Por ejemplo, ya sabemos que la amplitud de la curva debe ser aproximadamente 5 cm por el procedimiento llevado a cabo en el laboratorio. De la misma forma, sabemos que el defasaje `phi` del coseno debe estar cerca del 0 (si no les resulta intuitivo pregunten).\n",
        "- **A ojo:** Observamos el gráfico y elegímos parámetros razonables. Se puede aproximar la frecuencia estimando primero el período $T$ de las oscilaciones. $T$ está dado por el tiempo que tarda el carrito en alejarse de y volver a un máximo, como se puede ver en el siguiente gráfico:\n",
        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        "La frecuencia aproximada se calcula entonces con $\\omega_\\text_{aprox} = 2\\pi/T$.\n",
        "\n",
        "- **Usando `find_peaks`:** Una forma de automatizar el método \"a ojo\" es midiendo el período de las oscilaciones usando `find_peaks`. Esto es lo que vamos a usar ahora, ya que tenemos muchos datos para analizar y el método \"a ojo\" puede ser tedioso.\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Nk-SViwj2GK1"
      },
      "source": [
        "---\n",
        "### Ejercicio 3: Estimar la frecuencia de las oscilaciones usando `find_peaks`\n",
        "\n",
        "Lo que queremos hacer es medir el intervalo de tiempo entre los dos primeros picos de amplitud. Recordemos que `find_peaks` devuelve los indices de los picos del array que le damos y un diccionario con más información.\n",
        "\n",
        "1. Importar `find_peaks` de `scipy.signal` y aplicarlo al array de posiciónes `xs` de `0.csv`. Imprimir `picos` y el diccionario.\n",
        "\n",
        "2. Graficar los datos de `0.csv` nuevamente (podés copiar y pegar!!). Luego, graficar los picos encontrados por `find_peaks` con `plt.plot(ts[picos], xs[picos], \"o\")`. ¿Coinciden los picos con lo que esperan?\n",
        "\n",
        "3. Calcular el periódo `T` e imprimir el resultado (`f'Período estimado: {T} s'`). _Ayuda: ¿cuanto vale el tiempo en el segundo pico? ¿y en el primero? Restando estos valores van a poder obtener la respuesta!_\n",
        "\n",
        "4. Calcular la frecuencia `w0` usando que está dada por  $2\\pi / T$. Imprimir el resultado (`f'Frecuencia estimada: {w0} 1/s'`).\n",
        "\n",
        "_Nota: Estamos usando este método para estimar los parámetros iniciales, pero se podría usar para medir la frecuencia. El tema es que no estamos calculando la incerteza del valor del $\\omega$ que obtenemos, y **una medición tiene incerteza**. Además, un ajuste usa todos los datos, no solo los picos, lo que está bueno para tener más información. Si queres conversar un poco más del tema, llama a un profe!_\n",
        "\n",
        "---"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cFmXk2MVCaek"
      },
      "source": [
        "---\n",
        "### Ejercicio 4: Hacer un ajuste sinusoidal usando la frecuencia estimada\n",
        "\n",
        "1. Definir una función llamada `sinusoidal` que tome la variable independiente `t` y los parámetros a determinar `A, w` y `phi` (amplitud, frecuencia, y fase), y que devuelva el resultado de $A\\cos(\\text{w}t + \\text{phi})$.\n",
        "2. Usando `curve_fit` (hay que importarlo), ajustar los datos de `xs` en función de `ts` y obtener la frecuencia óptima `w` de `popt` (los parámetros óptimos), y su error `w_err` de `pcov` (la matriz de covarianza). Imprimir el resultado usando `f'Frecuencia: {w} ± {w_err} 1/s'`. _Ayuda: ver clase pasada!_\n",
        "3. Graficar la función ajustada sobre los datos.\n",
        "---"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8VNHb10jC1Zr"
      },
      "source": [
        "---\n",
        "### Ejercicio 5: Repetir para los demás archivos guardando los datos de la masa y la frecuencia.\n",
        "\n",
        "**Acá**, _esto_ es porque programar es _super útil_. Ya trabajaste un montón para analizar `0.csv`. El solo pensamiento de repetirlo 10 veces te pone los pelos de punta. ¡Pero no lo tenés que hacer! Copiando el código que ya hiciste, ordenandolo un poco y usando la mágia de las iteraciones vas a haber analizado todo en un suspiro.\n",
        "\n",
        "1. Inicializar tres listas vacías, `[]`, guardandolas en las variables `ms`, `ws`, y `ws_err`. En estas listas vamos a guardar la masa y frecuencia correspondientes a cada archivo.\n",
        "\n",
        "2. Recorrer los archivos `\"0.csv\"` a `\"8.csv\"` _(recordar subirlos a Colab)_ con un `for`, obteniendo la frecuencia de los datos y la masa total del carrito en cada uno. Si les ayuda, pueden usar la siguiente planilla. _TIP: hagan un gráfico en cada ciclo del for para verificar que find_peaks está agarrando \"bien\" los picos y vayan probando si el for funciona mientras lo van armando._\n",
        "\n",
        "```python\n",
        "for i in range(9):\n",
        "    ts, xs, xs_err = np.loadtxt(f\"{COMPLETAR}.csv\", delimiter = COMPLETAR, skiprows = COMPLETAR, unpack = COMPLETAR)\n",
        "\n",
        "\n",
        "    # USAR FIND_PEAKS PARA ESTIMAR LA FRECUENCIA (COPIAR CÓDIGO ANTERIOR, OJO CON LAS INDENTACIONES).\n",
        "\n",
        "    # GRAFICAR SEÑAL\n",
        "    # GRAFICAR PICOS\n",
        "    plt.show() # para que los gráficos queden en figuras distintas\n",
        "\n",
        "    # USAR CURVE_FIT PARA CONSEGUIR EL VALOR DE LA FRECUENCIA Y SU ERROR (COPIAR CÓDIGO ANTERIOR, OJO CON LAS INDENTACIONES).\n",
        "\n",
        "    # AGREGAR FRECUENCIA OBTENIDA A LA LISTA ws\n",
        "    # AGREGAR ERROR DE LA FRECUENCIA OBTENIDA A LA LISTA ws_err\n",
        "    # AGREGAR MASA CORRESPONDIENTE A LA LISTA ms\n",
        "```\n",
        "\n",
        "---"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FfWUVs5eDyQL"
      },
      "source": [
        "---\n",
        "### Ejercicio 6: El Ajuste Final\n",
        "\n",
        "El modelo de un oscilador sin amortiguamiento cuya fuerza restitutiva está dada por:\n",
        "$$\n",
        "F_\\text{resorte} = -kx\\qquad \\text{(Ley de Hooke)}\n",
        "$$\n",
        "con $k$ una constante y $x$ el desplazamiento del oscilador del equilibrio, tiene como frecuencia natural:\n",
        "$$\n",
        "\\omega(m) = \\sqrt{\\frac{k}{m}}\n",
        "$$\n",
        "1. Graficar `ws` en función de `ms`, mostrando el error de `ws`.\n",
        "2. Ajustar la función $\\omega(m) = \\sqrt{k/m}$ a los datos de $\\omega$ y $m$ que se guardaron en el item anterior, obteniendo el parámetro óptimo para $k$ y su error. Graficar la función ajustada encima de los datos y juzgar si el modelo es apropiado. _Nota: En los labos van a ver herramientas útiles para realizar estas evaluaciones de forma sistemática._\n",
        "---"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nEM1fRoYJkAo"
      },
      "source": [
        "# _Problema integrador 2 (Estadística)_\n",
        "\n",
        "Vamos a resolver probabilísticamente un problema simple.\n",
        "\n",
        "Si tiramos 100 monedas y las ordenamos en una secuencia como la siguiente:\n",
        "\n",
        "*\"... Cara Cruz Cara Cara Cruz ...\"*\n",
        "\n",
        "¿Qué es más probable? ¿Encontrar la secuencia \"Cara Cara\" o encontrar la secuencia \"Cruz Cara\"? ¿Son equiprobables?\n",
        "\n",
        "Rompamos nuestra cabeza."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9hkbVPC4M59g"
      },
      "source": [
        "Vamos a hacer todo de a pasos.\n",
        "\n",
        "### **1)** Función ```generar_secuencia(largo)```\n",
        "Lo primero que tenemos que poder hacer es generar una secuencia de caras y cruces. Como tanto cara como cruz empiezan con la misma letra, las vamos a cambiar por 0 y 1, es decir, estudiaremos cuantas veces aparece la secuencia 00 y cuantas aparece la secuencia 01.\n",
        "\n",
        "*Creá una función que reciba el largo de la secuencia y devuelva una lista llena de ceros y unos. Para esto, realizá un bucle ```for``` en el genere con cada iteración un 0 o un 1.*\n",
        "\n",
        "**AYUDA**: La función ```np.random.randint(0,n)``` genera un número aleatorio entre ```0``` y ```n-1```, es decir, no incluye a ```n```, al igual que el ```range```.\n",
        "\n",
        "### **2)** Función ```calcular_puntajes(secuencia)```\n",
        "\n",
        "Ahora tenemos que calcular los puntajes de las secuencias que generamos, es decir, hay que recorrer la secuencia y si encuentro un 0 y en el siguiente elemento de la lista otro 0 sumo un punto para la secuencia 00 mientras que si encuentro un 1 y luego un 0 sumo un punto para la secuencia 01.\n",
        "\n",
        "*Creá una función que reciba una secuencia y devuelva el puntaje obtenido para la secuencia 00 y para la secuencia 01.*\n",
        "\n",
        "**AYUDITA**: Recorrer la secuencia y fijarse si estoy parado en un 0 ¿Cómo debe ser el siguiente elemento de la lista para que sume un punto a la secuencia 00?\n",
        "\n",
        "### **3)** *¡A simular!*\n",
        "\n",
        "Ahora necesitamos hacer estadística, queremos ver que secuencia es más probable que la otra.\n",
        "\n",
        "Vamos a estudiar secuencias de distintos largos, desde 2 hasta 100 números. ¿Por qué empezamos en 2?\n",
        "\n",
        "*Para **cada largo**, realizá 1000 secuencias utilizando la función ```generar_secuencia(largo)``` y calculá los puntajes de cada secuencia con  ```calcular_puntajes(secuencia)```. Guardá en variables la cantidad de victorias de cada secuencia **¡y acordate de los empates!**, transformalas en probabilidad (dividilas por 1000, cof cof) y **guardalas en tres listas (POR FAVOR TE LO PIDO)**, una para 00, otra para 01 y otra para los empates.*\n",
        "\n",
        "No hagan más de 1000 secuencias porque sino el código va a empezar a tardar en ejecutarse y acá queremos las cosas ¡YA!. Si tienen ganas de esperar más tiempo pasen a 10000, pero solo pueden hacerlo una vez saben que funciona el código, sino la compu **explota**.\n",
        "\n",
        "¿Que secuencia crees que va a ser más probable que la otra?\n",
        "\n",
        "\n",
        "### **4)** *¡Es hora de graficar!*\n",
        "\n",
        "Llegó el momento de responder la tan esperada pregunta y vamos a hacerlo utilizando un gráfico.\n",
        "\n",
        "*Graficá las probabilidades de cada secuencia y los empates, en función del largo de la secuencia.*\n",
        "\n",
        "Es decir, en el eje $\\hat{x}$ tendremos el largo de la secuencia y en el eje $\\hat{y}$ la probabilidad de cada secuencia.\n",
        "\n",
        "¡Hacé el gráfico lo más hermoso posible! Ponele grilla, leyenda, nombres a los ejes y labels a cada curva. Si tenés ganas jugá con los colores y preguntanos que tan lindo te quedó el gráfico *(por contrato tenemos que responder que quedó hermoso)*, *(mentira no hay contrato)*.\n",
        "\n",
        "### **5)** *¡¿Qué está pasando?!*\n",
        "\n",
        "Respondimos la pregunta de que secuencia tiene más chances de ganar, pero el gráfico no responde el porqué ocurre esto, así que vamos a ahondar más profundo.\n",
        "\n",
        "*Generá 100000 secuencias de largo 4, calculá la diferencia de puntaje entre 00 y 01 y guardalas en una lista. Hacé un histograma de esa lista utilizando ```plt.hist(lista)``` y hacé el gráfico lo más bello que puedas. ¿Hay alguna tendencia? ¿Con cuanto puntaje máximo gana una secuencia y con cuanto gana la otra?*\n",
        "\n",
        "Luego, **LUEGO** de hacer esto. Abrí el siguiente enlace. ***¡¡LUEGO ES LUEGO!!***\n",
        "\n",
        "[¡SOLO LUEGO DE RESOLVER EL INCISO!](https://drive.google.com/file/d/1E6mq9gDdjaWj0hhhsFbvDU-Bb1glLmP0/view?usp=sharing)\n",
        "\n",
        "Si querés jugá a cambiar el largo de la secuencia para ver como cambian los histogramas.\n",
        "\n",
        "### **6)** *¡Felicitaciones!*\n",
        "\n",
        "Con esto hemos podido responder la pregunta, o al menos iluminar bastante la respuesta. Sin embargo podemos seguir aprendiendo cosas.\n",
        "\n",
        "*Calculá el valor medio y la desviación estándar del histograma que calculaste recién. Utilizá las funciones de numpy ```np.mean(lista)``` y ```np.std(lista)``` y aprendé inglés para saber cual es cual. Anotate en el Laboratorio de idiomas de la UBA y... bueno paro.*\n",
        "\n",
        "¿Tenes ganas de charlar un rato? Preguntanos que significa ```ddof = 1```.\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oqMfNBFVoSYS"
      },
      "source": [
        "# _Problema integrador 3 (Biología)_\n",
        "\n",
        "Vamos a estudiar la dinámica de poblaciones según un modelo clásico de depredador-presa.\n",
        "\n",
        "¡Lotka-Volterra!\n",
        "\n",
        "Tanto Lotka como Volterra propusieron de manera independiente un sistema de ecuaciones diferenciales para describir la dinámica de las poblaciones de una población de depredadores y una de presas que interactúan entre sí.\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5BAn1MvrzaSV"
      },
      "source": [
        "### **1)** *Primero de todo, los datos.com (**No es necesario entrar a esta página**).*\n",
        "\n",
        "Para arrancar a trabajar necesitamos los datos, sino no podemos hacer nada.\n",
        "\n",
        "*Utilizando la función ```np.loadtxt()``` (recordar la clase pasada) cargá los datos deL archivo  ```\"datos_poblaciones.csv\"```. A cada columna asignale el nombre apropiado, es decir, definí las variables ```tiempo```, ```pob_presas``` y ```pob_depredadores```.*\n",
        "\n",
        "Los datos pueden encontrarse dentro de una carpeta en el siguiente enlace:\n",
        "[Mercado Pago de la FIFA](https://github.com/fifabsas/talleresfifabsas/tree/master/python/3_Ejercicios)\n",
        "\n",
        "### **2)** *¡El momento de graficar!*\n",
        "\n",
        "Lo primero que tenemos que hacer cuando nos dan unos datos, a parte de cargarlos, es graficarlos, así vemos cual es su pinta y podemos pensar en que análisis realizar.\n",
        "\n",
        "*Utilizando lo que vimos la clase pasada de ```matplotlib```, graficá las poblaciones de presas y depredadores en función del tiempo y hacé que el gráfico sea lo más canchero posible, ponele grilla, leyenda, los colores que vos quieras, etc.*\n",
        "\n",
        "¿Son las poblaciones como esperabas? *¿No?* $\\;$ **Enseñanos algo de biología... ¡Por favor!**\n",
        "\n",
        "### **3)** *Aprendiendo un poco sobre las poblaciones*\n",
        "\n",
        "Estaría bueno tener cierto conocimiento general de las poblaciones, como su promedio y cuanto se desvían las poblaciones de este.\n",
        "\n",
        "*Calculá el promedio de la población de presas utilizando la función de numpy ```np.mean(pob_presas)```.*\n",
        "\n",
        "¿Es un valor representativo de la población?\n",
        "\n",
        "*Graficá este promedio en la figura anterior que hiciste, utilizando ```plt.axhline(valor_medio, c = \"g\", linestyle = \"--\")```. Probá cambiando los parámetros opcionales.*\n",
        "\n",
        "*Calculá también la desviación estandar, utilizando ```np.std(pob_presas)```.*\n",
        "\n",
        "¿Este valor te dice algo más respecto al promedio?\n",
        "### **4)** *El momento de utilizar ```find_peaks```*\n",
        "\n",
        "Observamos que las poblaciones oscilan y en particular notamos varios picos.\n",
        "\n",
        "*Utilizar la función ```find_peaks``` aplicada a la población de las presas, para determinar la posición de los máximos. Grafica los picos en un nuevo gráfico junto a la población de las presas en función del tiempo.*\n",
        "\n",
        "¿Cuanta población de presas hay en estos picos?\n",
        "\n",
        "### **5)** *Ciclos poblacionales: ¿¡El espacio de fases??*\n",
        "\n",
        "Vamos a tomarnos el laburo de hacer un gráfico bello, pero que les puede resultar complicado, así que vamos de a poco.\n",
        "\n",
        "\n",
        "*Graficá la población de depredadores en función de la población de presas. ¿Qué se observa? ¿¿Alguna especie de ciclo?? Guiño guiño.*\n",
        "\n",
        "\n",
        "Si lo pensas, en este gráfico perdemos la noción del tiempo, no sabemos de donde parte la población ni donde termina (aunque quizá sí te des cuenta), así que vamos a tomarnos el trabajo de agregarle esto.\n",
        "\n",
        "*Copiá las siguientes líneas (no hace falta que las entiendas del todo):*\n",
        "\n",
        "```python\n",
        "from matplotlib import colors\n",
        "colormap = plt.cm.plasma\n",
        "norm = colors.Normalize(vmin=min(tiempo), vmax= max(tiempo))\n",
        "scalar_map = plt.cm.ScalarMappable(norm=norm, cmap=colormap)\n",
        "```\n",
        "\n",
        "*Buscá en el navegador: matplotlib colormaps y cambia donde dice ```plasma``` por el colormap que más te guste. Puede ser que el que más te guste sea ```plasma```, a mí me gusta...*\n",
        "\n",
        "Ahora se viene lo lindo.\n",
        "\n",
        "*Realizá un ciclo ```for``` que recorra las listas de las poblaciones y graficá para cada ```i```:*\n",
        "\n",
        "```python\n",
        "plt.plot([pob_presa[i], pob_presa[i + 1]], [pob_depredador[i], pob_depredador[i + 1]], color= colormap(tiempo[i]/max(tiempo)))\n",
        "```\n",
        "\n",
        "¿Que tal el gráfico ahora? Para agregar la barra de colores del tiempo, copiá:\n",
        "\n",
        "```python\n",
        "cbar = plt.colorbar(scalar_map)\n",
        "cbar.set_label(\"Tiempo\")\n",
        "```\n",
        "\n",
        "¿Te molesta como quedaron los números del eje x?\n",
        "\n",
        "*Agregale al gráfico la línea ```plt.xticks(rotation = 45)```, mirá a los ojos a algún docente y decile que pensas que no queda mucho mejor.*\n",
        "\n",
        "\n",
        "### **6)** *¿Qué te pareció?*\n",
        "\n",
        "Este fue un ejercicio de biología pensado por una persona que no sabe de biología, así que nos re sirve tener tu opinión!\n",
        "\n",
        "Te dejamos tu última misión.\n",
        "\n",
        "*Aprendé programación por tu cuenta el tiempo que sea necesario para formar parte del plantel docente del taller de Python de la FIFA, cambiá este ejercicio y lentamente añadí gente de Biología al taller hasta que pase a ser un taller de estudiantes de Biología **para** estudiantes de Biología. **El taller de Python de la FIBA**.*"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "242J7FqPfFun"
      },
      "source": [
        "# _Ejercicios adicionales sueltos_"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZWmePcAzfKS3"
      },
      "source": [
        "La idea de estos ejercicios es que son cortos pero requieren conceptos que son importantes a la hora de programar o son problemas que se van a encontrar en algún momento en el futuro.\n",
        "\n",
        "Algunos son más divertidos o fáciles que otros, pero no por eso son menos importantes."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "x4ixQS1QsFsJ"
      },
      "source": [
        "### Histogramas\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OBq45yD8sp5J"
      },
      "source": [
        "Queremos generar numeros aleatorios con una cierta distribución de probabilidad, en este caso una Gaussiana, que es una distribución muy **normal** *(jajá que buen juego de palabras jajajajajajajajajajajajajajajajajajajajajajaja)* que aparece en todas las ciencias.\n",
        "\n",
        "Utilizando la función de `numpy` llamada `np.random.normal()` *(si, a la Gaussiana también se la llama la normal, ahora entendiste el chiste de arriba)* podemos generar números aleatorios según una distribución Gaussiana.\n",
        "\n",
        "**1)** *Generá 100 números aleatorios utilizando `np.random.normal()` y guardalos en una `lista`. Realizá un histograma utilizando `plt.hist(lista)` y hacé que el gráfico sea lo más canchero posible (recomendamos utilizar el parámetro opcional `edgecolor = \"k\"` para ponerle color negro a los bordes).*\n",
        "\n",
        "**2)** *Calcula `np.mean(lista)` y `np.std(lista)`. Estos devuelven el valor medio y la desviación estándar de los datos, respectivamente.*\n",
        "\n",
        "**3)** *Si conoces a la Gaussiana, sabés que esta tiene un valor medio, donde está centrada la campana, y una desviación estandar, que determina que tan dispersos están los datos. En particular `np.random.normal()` genera números aleatorios con valor medio 0 y desviación estándar 1. Probá cambiando los valores de la siguiente manera `np.random.normal(valor_medio, desviacion_estandar)` y ponele los valores que quieras. También jugá a cambiar la cantidad de números aleatorios que generas (100 por 1000 y así) y fijate como van cambiando `np.mean(lista)` y `np.std(lista)`.*\n",
        "\n",
        "**4)** *Si te pareció que hay demasiados chistes, dejalo en las encuestas, aprendé programación todo un cuatrimestre, vení la siguiente edición y modificá este ejercicio.*\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WpsKya5Llzy3"
      },
      "source": [
        "### Diccionarios\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Q2VXtb3Hsmvo"
      },
      "source": [
        "Tenemos la siguiente lista de nombres y carreras y queremos armar un diccionario que asocie cada nombre con su respectiva carrera.\n",
        "\n",
        "```python\n",
        "nombres = ['Rosalind Franklin', 'Juan G. Roederer', 'Albert-László Barabási', 'Emmy Noether', 'Phyllis Nicolson',\n",
        "           'Ada Lovelace', 'Luis Caffarelli', 'Miguel Ángel Virasoro', 'Luis Federico Leloir']\n",
        "\n",
        "carreras = ['Química', 'Física', 'Física', 'Matemática', 'Física',\n",
        "            'Computación', 'Matemática', 'Física', 'Química']\n",
        "```\n",
        "\n",
        "*Realizá un ciclo `for` para recorrer las listas. Ayuda: Al nombre i-ésimo le corresponde la carrera i-ésima.*\n",
        "\n",
        "*Una vez hayas hecho el diccionario, recorrelo e imprimí en pantalla los nombres de las personas cuya carrera sea \"Física\" (si así no sale ya no se que más hacer, te pido perdón).*"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3nQd9sjNEJwt"
      },
      "source": [
        "### Funciones\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wIwr1xfjF4Lb"
      },
      "source": [
        "#### Factorial"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zGFaKEjbGGqt"
      },
      "source": [
        "*Definir la función `factorial(n)`, que recibe un número entero y devuelve el factorial dicho número.*\n",
        "\n",
        "Expresión del factorial:\n",
        "\n",
        "$$n! = n \\cdot (n-1) \\cdot (n-2) \\cdot \\; ... \\cdot 1$$\n",
        "\n",
        "`math` ya tiene una función para realizar esto, llamada `math.factorial()`. Comparar los resultados."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "d40PFbF9F7AV"
      },
      "source": [
        "#### Valor absoluto"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jIPV3zSRGJIR"
      },
      "source": [
        "Definir la función `absoluto(x)` que recibe un número real (`float`) `x` y devuelve su módulo.\n",
        "*texto en cursiva*\n",
        "Si $x < 0$ debería devolver $-x$ y si $x \\geq 0$ debería devolver $x$.\n",
        "\n",
        "En Python ya existe una función que hace esto, llamada `abs()`. Comparar los resultados."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0jd-RU4fJZqX"
      },
      "source": [
        "### Listas"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0hi281OPJbTX"
      },
      "source": [
        "La idea de este ejercicio es familiarizarse con funciones super útiles aplicables a listas.\n",
        "\n",
        "```python\n",
        "numeros = [20,12,10,3,8,14,1,42]\n",
        "```\n",
        "\n",
        "*Copie la lista de arriba y aplique las funciones `max()` y `min()`.\n",
        "¿Qué devuelven?*\n",
        "\n",
        "Ahora aplicaremos `métodos` a la lista de números.\n",
        "\n",
        "*Aplique el método `pop()` a la lista de números, de la siguiente manera `numeros.pop()` (recuerde el `append()` de la primera clase).*\n",
        "\n",
        "Por último, aplicamos otro método.\n",
        "\n",
        "*Aplique el método `insert()` a la lista de números, de la siguiente manera `numeros.insert(0,77)`.*\n",
        "\n",
        "¿Qué hace cada método?"
      ]
    }
  ],
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