Pocal.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jrpqCVxMI9lJ",
        "outputId": "330dc9f2-173a-45cd-e553-c51f4c4caeb7"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting pocal\n",
            "  Downloading pocal-0.61-py3-none-any.whl (15 kB)\n",
            "Installing collected packages: pocal\n",
            "Successfully installed pocal-0.61\n"
          ]
        }
      ],
      "source": [
        "!pip install pocal"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pocal"
      ],
      "metadata": {
        "id": "Z0IyTn7-I-Gl"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!unzip resources"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cpohVbMmJWS1",
        "outputId": "a2bcec92-dcfb-4db3-dcb9-97fb01b29e2e"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Archive:  resources.zip\n",
            "   creating: resources/\n",
            "   creating: resources/resources/\n",
            "  inflating: resources/resources/3layers.txt  \n",
            "  inflating: resources/resources/a.txt  \n",
            "  inflating: resources/resources/absorbance.png  \n",
            "  inflating: resources/resources/absorbance.txt  \n",
            "  inflating: resources/resources/c.txt  \n",
            "  inflating: resources/resources/CIE.png  \n",
            "  inflating: resources/resources/cmf1931.txt  \n",
            "  inflating: resources/resources/cmf1964.txt  \n",
            "  inflating: resources/resources/d65.txt  \n",
            "  inflating: resources/resources/e.txt  \n",
            "  inflating: resources/resources/GD_trans.png  \n",
            "  inflating: resources/resources/GD_trans.txt  \n",
            "  inflating: resources/resources/LICENSE.txt  \n",
            "  inflating: resources/resources/materialLibrary.json  \n",
            "  inflating: resources/resources/reflected_phase_shift.png  \n",
            "  inflating: resources/resources/reflected_phase_shift.txt  \n",
            "  inflating: resources/resources/target.txt  \n",
            "  inflating: resources/resources/transmittance.png  \n",
            "  inflating: resources/resources/transmittance.txt  \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "os.chdir('resources')\n",
        "test = pocal.pocal(r'3layers.txt',40,200,1500,1,600,False,None)"
      ],
      "metadata": {
        "id": "ABgUd1vBJM3a"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#test.s_polarization('reflected_phase_shift')\n",
        "#test.s_polarization('GD_trans')\n",
        "#test.s_polarization('GDD_trans')\n",
        "#test.s_polarization('absorbance')\n",
        "#test.s_polarization('reflectance',True,True) # True,True arguments for savefile or savefig\n",
        "#test.admittance()\n",
        "test.electricField()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "id": "3c-M0S3ZJa_9",
        "outputId": "1362fc38-e741-4462-f944-8c6613b4b3f9"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "'''***************************sample script for refinement******************'''\n",
        "'''define a file target.txt with wavlengths in first column and - \n",
        "target transmittance or reflectance % in the second column'''\n",
        "test = pocal.pocal(r'3layers.txt',0,400,1500,1,600,False,'reflectance')\n",
        "test.refinement(10) # Value inside is for tolerance\n",
        "refined_test = pocal.pocal(r'C:\\Users\\u0151864\\.spyder-py3\\Material_for_the_library\\refined_prescription.txt',0,400,1500,1,600,False,None)\n",
        "refined_test.s_polarization('reflectance',True,True)\n",
        "'''*************************end of sample***********************************'''"
      ],
      "metadata": {
        "id": "hulf2MFmJcXT"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "GlZNkGv5Jgnn"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}