add further preliminary work files

Author: njakuschona

preliminary_work/calculate_lengthGrid.ipynb

@@ -0,0 +1,385 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "name": "calculate_lengthGrid.ipynb",
+      "provenance": []
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "-VvDvbniw-e3"
+      },
+      "source": [
+        "import numpy as np\n",
+        "\n",
+        "arr = np.zeros([4, 3])"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "aM01OjlNxTix",
+        "outputId": "c502e7ef-8eed-46a6-ac43-51424c9c6def"
+      },
+      "source": [
+        "arr+"
+      ],
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "array([[0., 0., 0.],\n",
+              "       [0., 0., 0.],\n",
+              "       [0., 0., 0.],\n",
+              "       [0., 0., 0.]])"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 4
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "B55WHRI1_NPI",
+        "outputId": "6f62a051-2afd-473e-bd20-39f1e04e0b51"
+      },
+      "source": [
+        "grid= np.load(\"SOG_W.npy\")\n",
+        "print(grid)"
+      ],
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "[[-5. -5. -5. ... -5. -5. -5.]\n",
+            " [-5. -5. -5. ... -5. -5. -5.]\n",
+            " [-5. -5. -5. ... -5. -5. -5.]\n",
+            " ...\n",
+            " [-5. -5. -5. ... -5. -5. -5.]\n",
+            " [-5. -5. -5. ... -5. -5. -5.]\n",
+            " [-5. -5. -5. ... -5. -5. -5.]]\n"
+          ],
+          "name": "stdout"
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "9HBTiiNj_cro",
+        "outputId": "acd2bd11-477b-42c5-c900-480745ee639d"
+      },
+      "source": [
+        "grid.shape"
+      ],
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "(2041, 4320)"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 7
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "95TcVqUrAIR6"
+      },
+      "source": [
+        "arr = np.zeros(grid.shape)"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Y0fqCXjdALyC",
+        "outputId": "4dc746d7-1169-4a45-e8ea-941e4a97ad6c"
+      },
+      "source": [
+        "\n",
+        "km=[110.71,109.45 ,107.35,104.43,100.72, 96.2, 91.04, 85.13, 78.58, 71.44, 63.74 ,55.57,\t46.97,38.01, 28.76, 19.30, 9.69]\n",
+        "\n",
+        "for i in range(len(km)):\n",
+        "  print(i)\n",
+        "  for x in range(60*i,60*(i+1)):\n",
+        "    for y in range(4320):\n",
+        "      arr[x][y] = km[i]*0.083\n",
+        "\n",
+        "  for x in range(2040 - 60*(i+1),2040 - 60*i):\n",
+        "    for y in range(4320):\n",
+        "      arr[x][y] = km[i]*0.083"
+      ],
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "0\n",
+            "1\n",
+            "2\n",
+            "3\n",
+            "4\n",
+            "5\n",
+            "6\n",
+            "7\n",
+            "8\n",
+            "9\n",
+            "10\n",
+            "11\n",
+            "12\n",
+            "13\n",
+            "14\n",
+            "15\n",
+            "16\n"
+          ],
+          "name": "stdout"
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "OL3e6h0gCy2K"
+      },
+      "source": [
+        "for y in range(4320):\n",
+        "   arr[2040][y] = km[i]"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 227
+        },
+        "id": "90Ag5992DSld",
+        "outputId": "17b4bfb8-5616-473f-a98d-a091f001f546"
+      },
+      "source": [
+        "import matplotlib.pyplot as plt\n",
+        "\n",
+        "plt.imshow(arr)"
+      ],
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.image.AxesImage at 0x7f376a5be4d0>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 33
+        },
+        {
+          "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"
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "nTCYrrJ2dSI4"
+      },
+      "source": [
+        "np.save(\"lengthGridEW.npy\", arr)"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "nFG-DV89-lYZ"
+      },
+      "source": [
+        "Resources: \n",
+        "http://www.iaktueller.de/exx.php\n",
+        "https://de.wikipedia.org/wiki/Geographische_Breite"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "icdE7ysb7bhm"
+      },
+      "source": [
+        "arr2 = np.zeros(grid.shape)\n",
+        "\n",
+        "for x in range(2041):\n",
+        "    for y in range(4320):\n",
+        "      arr2[x][y] = 110*0.083\n"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 227
+        },
+        "id": "dseeYD7uN7lW",
+        "outputId": "885922ea-69e9-45a7-c595-013b74f9b494"
+      },
+      "source": [
+        "import matplotlib.pyplot as plt\n",
+        "\n",
+        "plt.imshow(arr2)"
+      ],
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.image.AxesImage at 0x7fed80f385d0>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 7
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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lqSOGviR1xNCXpI78H1GQjlAWoEYhAAAAAElFTkSuQmCC\n",
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": [],
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "zJR0ANjEOSw8",
+        "outputId": "cff54a65-5c0c-4cc7-d789-1c4a340625de"
+      },
+      "source": [
+        "print(arr2)"
+      ],
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "[[9.13 9.13 9.13 ... 9.13 9.13 9.13]\n",
+            " [9.13 9.13 9.13 ... 9.13 9.13 9.13]\n",
+            " [9.13 9.13 9.13 ... 9.13 9.13 9.13]\n",
+            " ...\n",
+            " [9.13 9.13 9.13 ... 9.13 9.13 9.13]\n",
+            " [9.13 9.13 9.13 ... 9.13 9.13 9.13]\n",
+            " [0.   0.   0.   ... 0.   0.   0.  ]]\n"
+          ],
+          "name": "stdout"
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "cdG1X806-ksn"
+      },
+      "source": [
+        "np.save(\"lengthGridNS.npy\", arr2)"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "am45jbWcBf8a"
+      },
+      "source": [
+        "1 5\n",
+        "2 10\n",
+        "3 15\n",
+        "4 20\n",
+        "5 25\n",
+        "6 30\n",
+        "7 35\n",
+        "8 40\n",
+        "9 45\n",
+        "10 50\n",
+        "11 55\n",
+        "12 60\n",
+        "13 65\n",
+        "14 70\n",
+        "15 75\n",
+        "16 80\n",
+        "17 85\n",
+        "19 90\n"
+      ]
+    }
+  ]
+}