notebook.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/MartinPdeS/PyMieSim/blob/master/notebook.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "R5xUQ2lfZ1Jn"
      },
      "source": [
        "Build latest package version\n",
        "============================\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "lwOEi7pZMPIa",
        "outputId": "4d3719a3-fe81-49d2-9bd9-b5a1455bce6d",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[?25l   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/2.6 MB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K   \u001b[91m╸\u001b[0m\u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.1/2.6 MB\u001b[0m \u001b[31m1.6 MB/s\u001b[0m eta \u001b[36m0:00:02\u001b[0m\r\u001b[2K   \u001b[91m━━\u001b[0m\u001b[91m╸\u001b[0m\u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.2/2.6 MB\u001b[0m \u001b[31m2.4 MB/s\u001b[0m eta \u001b[36m0:00:02\u001b[0m\r\u001b[2K   \u001b[91m━━━━━━━\u001b[0m\u001b[90m╺\u001b[0m\u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.5/2.6 MB\u001b[0m \u001b[31m4.5 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K   \u001b[91m━━━━━━━━━━━━━━━━\u001b[0m\u001b[91m╸\u001b[0m\u001b[90m━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.1/2.6 MB\u001b[0m \u001b[31m7.8 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K   \u001b[91m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[91m╸\u001b[0m\u001b[90m━━━━━━\u001b[0m \u001b[32m2.2/2.6 MB\u001b[0m \u001b[31m12.6 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.6/2.6 MB\u001b[0m \u001b[31m13.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h\u001b[?25l   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/41.6 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m41.6/41.6 kB\u001b[0m \u001b[31m184.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m301.8/301.8 kB\u001b[0m \u001b[31m192.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m84.9/84.9 kB\u001b[0m \u001b[31m223.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.4/1.4 MB\u001b[0m \u001b[31m195.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.9/1.9 MB\u001b[0m \u001b[31m197.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m92.1/92.1 MB\u001b[0m \u001b[31m113.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h"
          ]
        }
      ],
      "source": [
        "!python -m pip install PyMieSim --no-cache-dir --quiet"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Experiment imports\n",
        "------------------"
      ],
      "metadata": {
        "id": "QYdt8JUqprps"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from PyMieSim import experiment\n",
        "import numpy as np\n",
        "from PyMieSim.experiment.scatterer import Sphere\n",
        "from PyMieSim.experiment.source import Gaussian\n",
        "from PyMieSim.experiment.detector import Photodiode\n",
        "from PyMieSim.experiment import Setup\n",
        "from PyMieSim.units import nanometer, degree, AU, RIU, watt\n",
        "from PyOptik import Material"
      ],
      "metadata": {
        "id": "h4ILEJ-Jm3qt"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Defining the source to be employed.\n",
        "source = Gaussian(\n",
        "    wavelength=1200 * nanometer,\n",
        "    polarization=0 * degree,\n",
        "    optical_power=1e-3 * watt,\n",
        "    NA=0.2 * AU\n",
        ")\n",
        "\n",
        "# Defining the ranging parameters for the scatterer distribution\n",
        "scatterer = Sphere(\n",
        "    diameter=2000 * nanometer,\n",
        "    property=Material.BK7,\n",
        "    medium_property=1 * RIU,\n",
        "    source=source\n",
        ")\n",
        "\n",
        "\n",
        "# Defining the detector to be employed.\n",
        "detector = Photodiode(\n",
        "    NA=[0.5, 0.3, 0.1, 0.05] * AU,\n",
        "    phi_offset=np.linspace(-180, 180, 400) * degree,\n",
        "    gamma_offset=0 * degree,\n",
        "    sampling=400 * AU,\n",
        "    polarization_filter=None\n",
        ")\n",
        "\n",
        "# Defining the experiment setup\n",
        "experiment = Setup(scatterer=scatterer, source=source, detector=detector)\n",
        "\n",
        "# Measuring the properties\n",
        "dataframe = experiment.get('coupling')\n",
        "\n",
        "# Plotting the results\n",
        "dataframe.plot_data(x=\"phi_offset\")\n"
      ],
      "metadata": {
        "id": "XizIYmO0_kZy",
        "outputId": "65c75351-c6ed-4784-e446-af23759f77a7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 456
        }
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "zNE0opqbACRw"
      },
      "execution_count": null,
      "outputs": []
    }
  ],
  "metadata": {
    "colab": {
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}