From 87def9151964fc06351c9bc5c24571cf86a639b4 Mon Sep 17 00:00:00 2001 From: Patrick Date: Tue, 12 Dec 2023 09:11:58 -0800 Subject: [PATCH] Delete data/reports directory --- data/reports/dataset_report.ipynb | 540 ------------------------------ 1 file changed, 540 deletions(-) delete mode 100644 data/reports/dataset_report.ipynb diff --git a/data/reports/dataset_report.ipynb b/data/reports/dataset_report.ipynb deleted file mode 100644 index b2c4c32..0000000 --- a/data/reports/dataset_report.ipynb +++ /dev/null @@ -1,540 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Dataset Insights" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "import json\n", - "import math\n", - "import os\n", - "import sqlite3\n", - "import sys\n", - "import types\n", - "\n", - "from functools import partial\n", - "\n", - "import matplotlib.pyplot as plt\n", - "import numpy as np\n", - "import pandas as pd\n", - "\n", - "from osgeo import gdal\n", - "\n", - "# Allow import from src dir\n", - "sys.path.append(\"../..\")\n", - "\n", - "from src.utils.db import dict_factory, get_dataset_labels\n", - "\n", - "\n", - "# Instantiate DB conn\n", - "metadata_path = \"../metadata.sqlite3\"\n", - "db_path = os.path.abspath(metadata_path)\n", - "conn = sqlite3.connect(db_path)\n", - "conn.row_factory = dict_factory\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "##### Point Label Annotations" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "61655 total point labels.\n" - ] - } - ], - "source": [ - "# Count point labels\n", - "dataset_id = 1\n", - "splits = [\"jan-march-may-2022-point-train\",\n", - " \"jan-march-may-2022-point-val\",\n", - " \"jun-july-aug-2022-point-train\",\n", - " \"jun-july-aug-2022-point-val\",\n", - " \"apr-2022-point-train\",\n", - " \"apr-2022-point-val\",\n", - " \"nov-2021-point-train\", \n", - " \"nov-2021-point-val\", \n", - " \"jun-2020-point-train\",\n", - " \"jun-2020-point-val\"]\n", - "labels_by_split = {split: get_dataset_labels(conn, dataset_id, splits=[split]) for split in splits}\n", - "all_labels = []\n", - "for split, labels in labels_by_split.items():\n", - " all_labels.extend(labels)\n", - "print(f\"{len(all_labels)} total point labels.\")\n" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Hist of point detections by split\n", - "data = []\n", - "columns = []\n", - "for split, labels in labels_by_split.items():\n", - " data.append(len(labels))\n", - " columns.append(split)\n", - "X = np.arange(len(data))\n", - "\n", - "# Get some pastel shades for the colors\n", - "color = plt.cm.BuPu(.5)\n", - "\n", - "index = np.arange(len(data))\n", - "bar_width = .8\n", - "\n", - "fig, ax = plt.subplots(figsize=(10, 8))\n", - "bar = ax.barh(columns, data, bar_width, color=color)\n", - "ax.bar_label(bar, label_type=\"center\")\n", - "plt.ylabel(\"Split\")\n", - "plt.xlabel(\"Count\")\n", - "plt.yticks(X)\n", - "plt.title('Point Detection Counts By Split')\n", - "\n", - "plt.show()\n" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "# Utilities for extracting lat/lon from labels\n", - "WEB_MERCATOR_M = 2 * math.pi * 6378137\n", - "\n", - "\n", - "def pixel_to_crs(point, zoom=13, tile_size=512):\n", - " \"\"\"Get absolute Web Mercator coordinates given pixel coordinates on a specified Web-Mercator tiling.\"\"\"\n", - " x, y = point[0], point[1]\n", - "\n", - " # Number of web-mercator meter units covered by a single\n", - " # pixel in a tiling with (tile_size x tile_size) pixels and zoom.\n", - " tile_pixel_size = WEB_MERCATOR_M / (tile_size * (2**zoom))\n", - "\n", - " x *= tile_pixel_size\n", - " y *= tile_pixel_size\n", - " x = x - (WEB_MERCATOR_M / 2)\n", - " y = WEB_MERCATOR_M - (y + (WEB_MERCATOR_M / 2))\n", - "\n", - " return (x, y)\n", - "\n", - "def crs_to_pixel(point, zoom=13, tile_size=512):\n", - " \"\"\"Get pixel coordinates on a specified Web-Mercator tiling given absolute Web Mercator coordinates.\"\"\"\n", - " x, y = point[0], point[1]\n", - " \n", - " # Translate coordinates to pos. quadrant\n", - " x = x + (WEB_MERCATOR_M / 2)\n", - " y = y + (WEB_MERCATOR_M / 2)\n", - " \n", - " # Reverse y coordinate\n", - " y = WEB_MERCATOR_M - y\n", - " \n", - " num_tiles = 2**zoom\n", - " num_pixels = num_tiles*tile_size\n", - " \n", - " x_crs_ratio = x / WEB_MERCATOR_M\n", - " y_crs_ratio = y / WEB_MERCATOR_M\n", - " \n", - " x_pixel = x_crs_ratio*num_pixels\n", - " y_pixel = y_crs_ratio*num_pixels\n", - " \n", - " return (x_pixel, y_pixel)\n", - "\n", - "\n", - "def get_lat_lon(col, row, transformer, zoom=13, tile_size=512):\n", - " \"\"\"\"Get latitude and longitude for points specified in pixel coordinates on a specified Web-Mercator tiling.\"\"\"\n", - " col, row = pixel_to_crs((col, row), zoom, tile_size)\n", - " success, point = transformer.TransformPoint(0, float(col), float(row), 0)\n", - " lon, lat, _ = point\n", - " return lat, lon\n", - "\n", - "\n", - "get_lat_lon = partial(get_lat_lon, transformer=gdal.Transformer(None, None, ['SRC_SRS=epsg:3857', 'DST_SRS=WGS84']))\n", - "\n", - "\n", - "def construct_lat_lon_df(labels, save_path=None):\n", - " \"\"\"Construct a dataframe of latitudes and longitudes for given point labels.\"\"\"\n", - " lats = []\n", - " lons = []\n", - " for label in labels:\n", - " col, row = label[\"column\"], label[\"row\"]\n", - " lat, lon = get_lat_lon(col, row)\n", - " lats.append(lat)\n", - " lons.append(lon)\n", - "\n", - " d = {'Latitude': lats, 'Longitude': lons}\n", - " df = pd.DataFrame(data=d)\n", - " if save_path:\n", - " df.to_csv(save_path, index=False)\n", - " return df\n" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "# Record lat/long for point labels in each split (TODO: plot loc distributions here)\n", - "for split, labels in labels_by_split.items():\n", - " split_df = construct_lat_lon_df(labels, save_path=f\"{split}_coords.csv\")\n", - "full_df = construct_lat_lon_df(all_labels, save_path=f\"full_coords.csv\")\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "##### Attribute Annotations" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "# Get attribute labels\n", - "splits = [\"jan-march-may-2022-attrs-train\", \"jun-july-aug-2022-attrs-train\", \"apr-2022-attrs-train\",\n", - " \"jan-march-may-2022-attrs-val\", \"jun-july-aug-2022-attrs-val\", \"apr-2022-attrs-val\"]\n", - "dataset_id = 2\n", - "attr_labels_by_split = {split: get_dataset_labels(conn, dataset_id, splits=[split]) for split in splits}\n", - "all_attr_labels = []\n", - "for split, labels in attr_labels_by_split.items():\n", - " all_attr_labels.extend(labels)\n", - "\n", - "\n", - "def get_attribute_dists(labels):\n", - " \"\"\"Extract individual attribute labels from attribute label dict.\"\"\"\n", - " lengths = []\n", - " widths = []\n", - " headings = []\n", - " ship_types = []\n", - " speeds = []\n", - " prop_dicts = [json.loads(label[\"properties\"]) for label in labels]\n", - " lengths.extend([prop_dict[\"Length\"] for prop_dict in prop_dicts])\n", - " widths.extend([prop_dict[\"Width\"] for prop_dict in prop_dicts])\n", - " headings.extend([prop_dict[\"Heading\"] for prop_dict in prop_dicts])\n", - " ship_types.extend([prop_dict[\"ShipAndCargoType\"] for prop_dict in prop_dicts])\n", - " speeds.extend([prop_dict[\"Speed\"] for prop_dict in prop_dicts])\n", - " return lengths, widths, headings, ship_types, speeds\n" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Split: jan-march-may-2022-attrs-train\n", - "\tAnnotations of fishing vessels: 87/5553 = 0.02%\n", - "Split: jun-july-aug-2022-attrs-train\n", - "\tAnnotations of fishing vessels: 199/5332 = 0.04%\n", - "Split: apr-2022-attrs-train\n", - "\tAnnotations of fishing vessels: 201/4939 = 0.04%\n", - "Split: jan-march-may-2022-attrs-val\n", - "\tAnnotations of fishing vessels: 10/617 = 0.02%\n", - "Split: jun-july-aug-2022-attrs-val\n", - "\tAnnotations of fishing vessels: 22/592 = 0.04%\n", - "Split: apr-2022-attrs-val\n", - "\tAnnotations of fishing vessels: 22/549 = 0.04%\n", - "Total Dataset:\n", - "\tAnnotations of fishing vessels: 541/17582 = 0.03%\n" - ] - } - ], - "source": [ - "def get_fishing_ratio(ship_types):\n", - " \"\"\"\"Get ratio of labels reported with fishing vessel type\"\"\"\n", - "\n", - " # Ship Counts by Type\n", - " ship_types, ship_counts = np.unique(ship_types, return_counts=True)\n", - " count_sort_idx = np.argsort(-ship_counts)\n", - " ship_types, ship_counts = ship_types[count_sort_idx], ship_counts[count_sort_idx]\n", - "\n", - " # Fishing Count\n", - " fishing_index_locs = np.where(ship_types == 30)[0]\n", - " if len(fishing_index_locs) > 0:\n", - " fishing_index = np.where(ship_types == 30)[0][0]\n", - " fishing_ships = ship_counts[fishing_index]\n", - " else:\n", - " fishing_ships = 0\n", - " total_ships = ship_counts.sum()\n", - " pos_weight = total_ships / fishing_ships\n", - " print(f\"\\tAnnotations of fishing vessels: {fishing_ships}/{total_ships} = {round(fishing_ships/total_ships, 2)}%\")\n", - " return ship_types, ship_counts, fishing_index\n", - "\n", - "\n", - "# Get fishing counts per split\n", - "for split, attr_labels in attr_labels_by_split.items():\n", - " lengths, widths, headings, ship_types, speeds = get_attribute_dists(attr_labels)\n", - " print(f\"Split: {split}\")\n", - " _, _, _ = get_fishing_ratio(ship_types)\n", - "\n", - "# Get all attributes for total dataset\n", - "lengths, widths, headings, ship_types, speeds = get_attribute_dists(all_attr_labels)\n", - "print(f\"Total Dataset:\")\n", - "ship_types, ship_counts, fishing_index = get_fishing_ratio(ship_types)\n" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Plot Distribution of Ship Types\n", - "code_to_type = {0: \"Not Available\", 70: \"Cargo, all types\", 80: \"Tanker, all types\", 89: \"Tanker, no additional info\",\n", - " 52: \"Tug Boat\", 30: \"Fishing\", 90: \"Other Type, all ships of this type\",\n", - " 79: \"Cargo, no additional info\", 37: \"Pleasure Craft\", 71: \"Cargo, hazardous category A\"}\n", - "\n", - "num_types = 5\n", - "labels = list(ship_types[:num_types])\n", - "sizes = list(ship_counts[:num_types])\n", - "if fishing_index >= num_types:\n", - " labels.append(ship_types[fishing_index])\n", - " sizes.append(ship_counts[fishing_index])\n", - "labels = [f\"{code_to_type[label]} \" + f\"({label})\" for label in labels]\n", - "labels.append(\"Everything Else\")\n", - "sizes.append(ship_counts.sum() - sum(sizes))\n", - "explode = len(sizes) * [0]\n", - "explode[len(sizes) - 2] = .4\n", - "\n", - "fig1, ax1 = plt.subplots()\n", - "ax1.pie(sizes,\n", - " explode=explode,\n", - " labels=labels,\n", - " autopct='%1.1f%%',\n", - " shadow=False, startangle=90)\n", - "ax1.axis('equal') # Equal aspect ratio ensures that pie is drawn as a circle.\n", - "plt.title('Breakdown of AIS Ship Type Codes')\n", - "plt.show()\n" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Same data as bar plot\n", - "\n", - "X = np.arange(len(sizes))\n", - "\n", - "# Get some pastel shades for the colors\n", - "color = plt.cm.BuPu(.5)\n", - "\n", - "index = np.arange(len(sizes))\n", - "bar_width = .8\n", - "\n", - "fig, ax = plt.subplots(figsize=(10, 8))\n", - "bar = ax.barh(labels, sizes, bar_width, color=color)\n", - "ax.bar_label(bar, label_type=\"center\")\n", - "plt.ylabel(\"Vessel Type\")\n", - "plt.xlabel(\"Count\")\n", - "plt.yticks(X)\n", - "plt.title('Ship Type Counts')\n", - "\n", - "plt.show()\n" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Length histogram\n", - "\n", - "n, bins, patches = plt.hist(lengths, 50, density=False, facecolor='g', alpha=0.5)\n", - "\n", - "\n", - "plt.xlabel('Ship Length (meters)')\n", - "plt.ylabel('Count')\n", - "plt.title('Ship Length Distribution (Full)')\n", - "plt.grid(False)\n", - "plt.show()\n" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Width histogram\n", - "\n", - "n, bins, patches = plt.hist(widths, 50, density=False, facecolor='g', alpha=0.5)\n", - "\n", - "\n", - "plt.xlabel('Ship Width (meters)')\n", - "plt.ylabel('Count')\n", - "plt.title('Ship Width Distribution (Full)')\n", - "plt.grid(False)\n", - "plt.show()\n" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Speed histogram\n", - "\n", - "n, bins, patches = plt.hist(speeds, 30, density=False, facecolor='g', alpha=0.5)\n", - "\n", - "\n", - "plt.xlabel('Ship Speed (knots)')\n", - "plt.ylabel('Count')\n", - "plt.title('Ship Speed Distribution (Full)')\n", - "plt.grid(False)\n", - "plt.show()\n" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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PqkePHnrllVduuH5oaKjatm2rRo0aqWTJktq0aZO+/vprp4nP6bdtDxkyRBEREXJ1dVWPHj2yNeaiRYtqyZIlioyMVLNmzbR48WJ9//33+te//mVNzPb19dXDDz+syZMny+FwqEqVKlq4cGGmXx56K7W9+uqriomJUcuWLfXss8+qSJEi+uijj5SSkqKJEydmazyZadmypUqVKqUff/xR99xzzy2t++STT+qdd95RRESE+vXrp1OnTmnatGmqXbt2hknfWRUTE6OKFStyyz3+li/3tgEFzOLFi82TTz5patasaby9vY27u7upWrWqGTx4sImPj3fqK8kMGjQowzauvW37erfdd+7c2fzwww+mXr16xsPDw9SsWdPMmTMnS3Veb99X7+/q2+6NMebgwYOmd+/eJiAgwLi5uZly5cqZ+++/33z99ddWn+TkZPPPf/7TBAYGmmLFipkWLVqY2NjYTG91PnLkiPnHP/5hPD09TenSpc1zzz1nlixZkuXb7t98881Mx3X1bdLGGPPll1+amjVrGg8PD1OnTh2zYMEC0717d1OzZs2bHqc2bdo43brt7e1tqlWrZp544gmzdOnSTNe59vV79dVXTdOmTY2fn58pVqyYqVmzpnnttdecvorhypUrZvDgwaZMmTLG4XBYt7nfaKzXu+3ey8vLHDx40HTo0MF4enoaf39/M3bs2Axfh3D69GnTvXt34+npaUqUKGGefvpps3PnzgzbvF5txmR+vLds2WIiIiKMt7e38fT0NO3atTPr1q1z6nO999j1vg4gM0OGDDFVq1bN9Jhkdryu9vnnn5vKlSsbd3d306BBA/PDDz9k+7b71NRUExgYaF566aWb1gx7cBhTgGaBAne44OBg1alTRwsXLszvUgqlBg0aqEyZMjn6A63IW7/99ptq1qypxYsXW5cC88O8efP0+OOP6+DBgwoMDMy3OlBwMIcIQIFz+fJlXblyxalt5cqV2rZtW6Y/34DCo3LlyurXr58mTJiQr3W88cYbioqKIgzBwhkiIA9xhihrDh8+rPDwcD3xxBMKCgrS3r17NW3aNPn6+mrnzp03/XkUALhVTKoGUOCUKFFCjRo10ieffKLTp0/Ly8tLnTt31oQJEwhDAHIFZ4gAAIDtMYcIAADYHoEIAADYHnOIsiAtLU0nTpxQ8eLF+RFAAAAKCWOMzp07p6CgILm43PgcEIEoC06cOJFjv+UDAADy1rFjx1S+fPkb9iEQZUHx4sUl/X1Ac+o3fQAAQO5KSkpShQoVrM/xGyEQZUH6ZTIfHx8CEQAAhUxWprvk66Tq1atX64EHHlBQUJAcDofmzZvntNwYozFjxigwMFDFihVTeHi49u/f79TnzJkz6tmzp3x8fOTn56d+/fpl+PHH7du3q1WrVipatKgqVKiQoz9WCAAACr98DUQXLlxQ/fr1NWXKlEyXT5w4UZMmTdK0adO0fv16eXl5KSIiQsnJyVafnj17ateuXYqJidHChQu1evVqDRgwwFqelJSkDh06qFKlStq8ebPefPNNjRs3Th9//HGujw8AABQS+fe7ss4kmblz51rP09LSTEBAgNOvHyckJBgPDw/zxRdfGGOM2b17d4ZfXl68eLFxOBzm+PHjxhhjPvzwQ1OiRAmTkpJi9Rk5cqSpUaNGlmtLTEw0kkxiYmJ2hwcAAPLYrXx+F9jvITp06JDi4uIUHh5utfn6+qpZs2aKjY2VJMXGxsrPz0+NGze2+oSHh8vFxUXr16+3+rRu3Vru7u5Wn4iICO3bt09nz57No9EAAICCrMBOqo6Li5Mk+fv7O7X7+/tby+Li4lS2bFmn5UWKFFHJkiWd+oSEhGTYRvqyEiVKZNh3SkqKUlJSrOdJSUm3ORoAAFCQFdgzRPkpOjpavr6+1oPvIAIA4M5WYANRQECAJCk+Pt6pPT4+3loWEBCgU6dOOS2/cuWKzpw549Qns21cvY9rjRo1SomJidbj2LFjtz8gAABQYBXYQBQSEqKAgAAtW7bMaktKStL69esVFhYmSQoLC1NCQoI2b95s9Vm+fLnS0tLUrFkzq8/q1at1+fJlq09MTIxq1KiR6eUySfLw8LC+c4jvHgIA4M6Xr4Ho/Pnz2rp1q7Zu3Srp74nUW7du1dGjR+VwODR06FC9+uqrWrBggXbs2KHevXsrKChIXbt2lSTVqlVLHTt2VP/+/bVhwwatXbtWUVFR6tGjh4KCgiRJjz/+uNzd3dWvXz/t2rVLX331ld5//30NHz48n0YNAAAKnDy46+26VqxYYSRleERGRhpj/r71fvTo0cbf3994eHiY9u3bm3379jlt488//zSPPfaY8fb2Nj4+PqZv377m3LlzTn22bdtmWrZsaTw8PEy5cuXMhAkTbqlObrsHAKDwuZXPb4cxxuRjHisUkpKS5Ovrq8TERC6fAQBQSNzK53eBnUMEAACQVwhEAADA9ghEAADA9ghEAADA9grsT3fYybiV47K/btvsrwsAAP7GGSIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BCIAAGB7BToQpaamavTo0QoJCVGxYsVUpUoVvfLKKzLGWH2MMRozZowCAwNVrFgxhYeHa//+/U7bOXPmjHr27CkfHx/5+fmpX79+On/+fF4PBwAAFFAFOhC98cYbmjp1qj744APt2bNHb7zxhiZOnKjJkydbfSZOnKhJkyZp2rRpWr9+vby8vBQREaHk5GSrT8+ePbVr1y7FxMRo4cKFWr16tQYMGJAfQwIAAAVQkfwu4EbWrVunLl26qHPnzpKk4OBgffHFF9qwYYOkv88Ovffee3rppZfUpUsXSdKnn34qf39/zZs3Tz169NCePXu0ZMkSbdy4UY0bN5YkTZ48Wffdd5/eeustBQUF5c/gAABAgVGgzxA1b95cy5Yt06+//ipJ2rZtm9asWaNOnTpJkg4dOqS4uDiFh4db6/j6+qpZs2aKjY2VJMXGxsrPz88KQ5IUHh4uFxcXrV+/PtP9pqSkKCkpyekBAADuXAX6DNGLL76opKQk1axZU66urkpNTdVrr72mnj17SpLi4uIkSf7+/k7r+fv7W8vi4uJUtmxZp+VFihRRyZIlrT7Xio6O1ssvv5zTwwEAAAVUgT5D9L///U+zZs3S7NmztWXLFs2cOVNvvfWWZs6cmav7HTVqlBITE63HsWPHcnV/AAAgfxXoM0QjRozQiy++qB49ekiS6tatqyNHjig6OlqRkZEKCAiQJMXHxyswMNBaLz4+Xg0aNJAkBQQE6NSpU07bvXLlis6cOWOtfy0PDw95eHjkwogAAEBBVKDPEF28eFEuLs4lurq6Ki0tTZIUEhKigIAALVu2zFqelJSk9evXKywsTJIUFhamhIQEbd682eqzfPlypaWlqVmzZnkwCgAAUNAV6DNEDzzwgF577TVVrFhRtWvX1i+//KJ33nlHTz75pCTJ4XBo6NChevXVV1WtWjWFhIRo9OjRCgoKUteuXSVJtWrVUseOHdW/f39NmzZNly9fVlRUlHr06MEdZgAAQFIBD0STJ0/W6NGj9eyzz+rUqVMKCgrS008/rTFjxlh9XnjhBV24cEEDBgxQQkKCWrZsqSVLlqho0aJWn1mzZikqKkrt27eXi4uLunfvrkmTJuXHkAAAQAHkMFd/7TMylZSUJF9fXyUmJsrHxyfHtz9u5bjsr9s2++sCAHAnu5XP7wI9hwgAACAvEIgAAIDtEYgAAIDtEYgAAIDtEYgAAIDtEYgAAIDtEYgAAIDtEYgAAIDtEYgAAIDtEYgAAIDtEYgAAIDtEYgAAIDtEYgAAIDtEYgAAIDtEYgAAIDtEYgAAIDtEYgAAIDtEYgAAIDtEYgAAIDtEYgAAIDtEYgAAIDtEYgAAIDtEYgAAIDtEYgAAIDtEYgAAIDtEYgAAIDtEYgAAIDtEYgAAIDtEYgAAIDtFcnvAnB7xq0cl/1122Z/XQAA7iScIQIAALZHIAIAALZHIAIAALZHIAIAALZHIAIAALZHIAIAALZHIAIAALZHIAIAALZHIAIAALZHIAIAALZHIAIAALbHb5kBsD1+ExAAgQgA8glBDCg4uGQGAABsj0AEAABsj0AEAABsj0AEAABsj0AEAABsj7vMUKhwVw4AIDdwhggAANgegQgAANgegQgAANgec4gAAECOKMzzPAlEsI3C/BcVAJC7uGQGAABsj0AEAABsj0AEAABsj0AEAABsj0nVQBYwIRsA7mwEIgAAYLmd/wAWZlwyAwAAtlfgzxAdP35cI0eO1OLFi3Xx4kVVrVpV06dPV+PGjSVJxhiNHTtW//73v5WQkKAWLVpo6tSpqlatmrWNM2fOaPDgwfruu+/k4uKi7t276/3335e3t3d+DQvAHaKw/m+ay8CAswJ9hujs2bNq0aKF3NzctHjxYu3evVtvv/22SpQoYfWZOHGiJk2apGnTpmn9+vXy8vJSRESEkpOTrT49e/bUrl27FBMTo4ULF2r16tUaMGBAfgwJAAAUQAX6DNEbb7yhChUqaPr06VZbSEiI9WdjjN577z299NJL6tKliyTp008/lb+/v+bNm6cePXpoz549WrJkiTZu3GidVZo8ebLuu+8+vfXWWwoKCsrbQQEAgAKnQAeiBQsWKCIiQg8//LBWrVqlcuXK6dlnn1X//v0lSYcOHVJcXJzCw8OtdXx9fdWsWTPFxsaqR48eio2NlZ+fnxWGJCk8PFwuLi5av369HnzwwQz7TUlJUUpKivU8KSkpF0dZOBXWywQAAGSmQF8y++2336z5QD/88IMGDhyoIUOGaObMmZKkuLg4SZK/v7/Tev7+/tayuLg4lS1b1ml5kSJFVLJkSavPtaKjo+Xr62s9KlSokNNDAwAABUiBDkRpaWm666679Prrr6thw4YaMGCA+vfvr2nTpuXqfkeNGqXExETrcezYsVzdHwAAyF8FOhAFBgYqNDTUqa1WrVo6evSoJCkgIECSFB8f79QnPj7eWhYQEKBTp045Lb9y5YrOnDlj9bmWh4eHfHx8nB4AAODOVaDnELVo0UL79u1zavv1119VqVIlSX9PsA4ICNCyZcvUoEEDSX/P91m/fr0GDhwoSQoLC1NCQoI2b96sRo0aSZKWL1+utLQ0NWvWLO8GUwAxDwgAgL8V6EA0bNgwNW/eXK+//roeeeQRbdiwQR9//LE+/vhjSZLD4dDQoUP16quvqlq1agoJCdHo0aMVFBSkrl27Svr7jFLHjh2tS22XL19WVFSUevTowR1mAABAUgEPRE2aNNHcuXM1atQojR8/XiEhIXrvvffUs2dPq88LL7ygCxcuaMCAAUpISFDLli21ZMkSFS1a1Ooza9YsRUVFqX379tYXM06aNCk/hgQAAAqgAh2IJOn+++/X/ffff93lDodD48eP1/jx46/bp2TJkpo9e3ZulAcAAO4ABT4QAYUdP5EAAAVfgb7LDAAAIC8QiAAAgO0RiAAAgO0RiAAAgO0xqRoACiG+WBXIWQQiAHcEAgKA28ElMwAAYHvZOkNUuXJlbdy4UaVKlXJqT0hI0F133aXffvstR4oDAAC3jjOmty5bZ4gOHz6s1NTUDO0pKSk6fvz4bRcFAACQl27pDNGCBQusP//www/y9fW1nqempmrZsmUKDg7OseIAAADywi0FovRfkHc4HIqMjHRa5ubmpuDgYL399ts5VhwAAEBeuKVAlJaWJkkKCQnRxo0bVbp06VwpCgAAu2MeUN7K1qTqQ4cO5XQdAAAA+Sbb30O0bNkyLVu2TKdOnbLOHKX773//e9uFAQAA5JVsBaKXX35Z48ePV+PGjRUYGCiHw5HTdQEA4OR2LiGNa5v9dWEP2QpE06ZN04wZM9SrV6+crgcAACDPZSsQXbp0Sc2bN8/pWgAAhQBnanAnytYXMz711FOaPXt2TtcCAACQL7J1hig5OVkff/yxfvzxR9WrV09ubm5Oy995550cKQ4AACAvZCsQbd++XQ0aNJAk7dy502kZE6wBZBffuwIgv2QrEK1YsSKn6wAAAMg32ZpDBAAAcCfJ1hmidu3a3fDS2PLly7NdEIDCjcteuNNwV509ZCsQpc8fSnf58mVt3bpVO3fuzPCjrwAA2BX/QSg8shWI3n333Uzbx40bp/Pnz99WQQAAAHktR+cQPfHEE/yOGQAAKHRyNBDFxsaqaNGiOblJAACAXJetS2bdunVzem6M0cmTJ7Vp0yaNHj06RwoDAADIK9kKRL6+vk7PXVxcVKNGDY0fP14dOnTIkcIAAMgpTG7GzWQrEE2fPj2n6wAAAMg32QpE6TZv3qw9e/ZIkmrXrq2GDRvmSFEAgDsTZ2pQUGUrEJ06dUo9evTQypUr5efnJ0lKSEhQu3bt9OWXX6pMmTI5WSMAAECuylYgGjx4sM6dO6ddu3apVq1akqTdu3crMjJSQ4YM0RdffJGjRQJ2xTfkAkDeyFYgWrJkiX788UcrDElSaGiopkyZwqRqAABQ6GTre4jS0tLk5uaWod3NzU1paWm3XRQAAEBeylYguueee/Tcc8/pxIkTVtvx48c1bNgwtW/fPseKAwAAyAvZCkQffPCBkpKSFBwcrCpVqqhKlSoKCQlRUlKSJk+enNM1AgAA5KpszSGqUKGCtmzZoh9//FF79+6VJNWqVUvh4eE5WhwAAEBeuKUzRMuXL1doaKiSkpLkcDh07733avDgwRo8eLCaNGmi2rVr66effsqtWgEAAHLFLQWi9957T/3795ePj0+GZb6+vnr66af1zjvv5FhxAAAAeeGWAtG2bdvUsWPH6y7v0KGDNm/efNtFAQAA5KVbmkMUHx+f6e321saKFNHp06dvuygAt48vdQSArLulM0TlypXTzp07r7t8+/btCgwMvO2iAAAA8tItBaL77rtPo0ePVnJycoZlf/31l8aOHav7778/x4oDAADIC7d0yeyll17St99+q+rVqysqKko1atSQJO3du1dTpkxRamqq/u///i9XCgWQd/hFcgB2c0uByN/fX+vWrdPAgQM1atQoGWMkSQ6HQxEREZoyZYr8/f1zpVAAAIDccstfzFipUiUtWrRIZ8+e1YEDB2SMUbVq1VSiRIncqA8AACDXZeubqiWpRIkSatKkSU7WAgAAkC+y9VtmAAAAdxICEQAAsD0CEQAAsD0CEQAAsD0CEQAAsD0CEQAAsD0CEQAAsD0CEQAAsD0CEQAAsD0CEQAAsD0CEQAAsD0CEQAAsD0CEQAAsL1CFYgmTJggh8OhoUOHWm3JyckaNGiQSpUqJW9vb3Xv3l3x8fFO6x09elSdO3eWp6enypYtqxEjRujKlSt5XD0AACioCk0g2rhxoz766CPVq1fPqX3YsGH67rvvNGfOHK1atUonTpxQt27drOWpqanq3LmzLl26pHXr1mnmzJmaMWOGxowZk9dDAAAABVShCETnz59Xz5499e9//1slSpSw2hMTE/Wf//xH77zzju655x41atRI06dP17p16/Tzzz9LkpYuXardu3fr888/V4MGDdSpUye98sormjJlii5dupRfQwIAAAVIoQhEgwYNUufOnRUeHu7UvnnzZl2+fNmpvWbNmqpYsaJiY2MlSbGxsapbt678/f2tPhEREUpKStKuXbsy3V9KSoqSkpKcHgAA4M5VJL8LuJkvv/xSW7Zs0caNGzMsi4uLk7u7u/z8/Jza/f39FRcXZ/W5OgylL09flpno6Gi9/PLLOVA9AAAoDAr0GaJjx47pueee06xZs1S0aNE82++oUaOUmJhoPY4dO5Zn+wYAAHmvQAeizZs369SpU7rrrrtUpEgRFSlSRKtWrdKkSZNUpEgR+fv769KlS0pISHBaLz4+XgEBAZKkgICADHedpT9P73MtDw8P+fj4OD0AAMCdq0AHovbt22vHjh3aunWr9WjcuLF69uxp/dnNzU3Lli2z1tm3b5+OHj2qsLAwSVJYWJh27NihU6dOWX1iYmLk4+Oj0NDQPB8TAAAoeAr0HKLixYurTp06Tm1eXl4qVaqU1d6vXz8NHz5cJUuWlI+PjwYPHqywsDDdfffdkqQOHTooNDRUvXr10sSJExUXF6eXXnpJgwYNkoeHR56PCQAAFDwFOhBlxbvvvisXFxd1795dKSkpioiI0Icffmgtd3V11cKFCzVw4ECFhYXJy8tLkZGRGj9+fD5WDQAAChKHMcbkdxEFXVJSknx9fZWYmJgr84nGrRyX49sEAKAwGdd2XI5v81Y+vwv0HCIAAIC8QCACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2RyACAAC2V6ADUXR0tJo0aaLixYurbNmy6tq1q/bt2+fUJzk5WYMGDVKpUqXk7e2t7t27Kz4+3qnP0aNH1blzZ3l6eqps2bIaMWKErly5kpdDAQAABViBDkSrVq3SoEGD9PPPPysmJkaXL19Whw4ddOHCBavPsGHD9N1332nOnDlatWqVTpw4oW7dulnLU1NT1blzZ126dEnr1q3TzJkzNWPGDI0ZMyY/hgQAAAoghzHG5HcRWXX69GmVLVtWq1atUuvWrZWYmKgyZcpo9uzZeuihhyRJe/fuVa1atRQbG6u7775bixcv1v33368TJ07I399fkjRt2jSNHDlSp0+flru7+033m5SUJF9fXyUmJsrHxyfHxzVu5bgc3yYAAIXJuLbjcnybt/L5XaDPEF0rMTFRklSyZElJ0ubNm3X58mWFh4dbfWrWrKmKFSsqNjZWkhQbG6u6detaYUiSIiIilJSUpF27dmW6n5SUFCUlJTk9AADAnavQBKK0tDQNHTpULVq0UJ06dSRJcXFxcnd3l5+fn1Nff39/xcXFWX2uDkPpy9OXZSY6Olq+vr7Wo0KFCjk8GgAAUJAUmkA0aNAg7dy5U19++WWu72vUqFFKTEy0HseOHcv1fQIAgPxTJL8LyIqoqCgtXLhQq1evVvny5a32gIAAXbp0SQkJCU5nieLj4xUQEGD12bBhg9P20u9CS+9zLQ8PD3l4eOTwKAAAQEFVoM8QGWMUFRWluXPnavny5QoJCXFa3qhRI7m5uWnZsmVW2759+3T06FGFhYVJksLCwrRjxw6dOnXK6hMTEyMfHx+FhobmzUAAAECBVqDPEA0aNEizZ8/W/PnzVbx4cWvOj6+vr4oVKyZfX1/169dPw4cPV8mSJeXj46PBgwcrLCxMd999tySpQ4cOCg0NVa9evTRx4kTFxcXppZde0qBBgzgLBAAAJBXwQDR16lRJUtu2bZ3ap0+frj59+kiS3n33Xbm4uKh79+5KSUlRRESEPvzwQ6uvq6urFi5cqIEDByosLExeXl6KjIzU+PHj82oYAACggCvQgSgrX5FUtGhRTZkyRVOmTLlun0qVKmnRokU5WRoAALiDFOg5RAAAAHmBQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGyPQAQAAGzPVoFoypQpCg4OVtGiRdWsWTNt2LAhv0sCAAAFgG0C0VdffaXhw4dr7Nix2rJli+rXr6+IiAidOnUqv0sDAAD5zDaB6J133lH//v3Vt29fhYaGatq0afL09NR///vf/C4NAADkM1sEokuXLmnz5s0KDw+32lxcXBQeHq7Y2Nh8rAwAABQERfK7gLzwxx9/KDU1Vf7+/k7t/v7+2rt3b4b+KSkpSklJsZ4nJiZKkpKSknKlvpQLKTfvBADAHSw3PmPTt2mMuWlfWwSiWxUdHa2XX345Q3uFChXyoRoAAO58EzQh17Z97tw5+fr63rCPLQJR6dKl5erqqvj4eKf2+Ph4BQQEZOg/atQoDR8+3HqelpamM2fOqFSpUnI4HDlaW1JSkipUqKBjx47Jx8cnR7dd0DF2+43druOWGDtjZ+z5wRijc+fOKSgo6KZ9bRGI3N3d1ahRIy1btkxdu3aV9HfIWbZsmaKiojL09/DwkIeHh1Obn59frtbo4+Nju78s6Ri7/cZu13FLjJ2x209+j/1mZ4bS2SIQSdLw4cMVGRmpxo0bq2nTpnrvvfd04cIF9e3bN79LAwAA+cw2gejRRx/V6dOnNWbMGMXFxalBgwZasmRJhonWAADAfmwTiCQpKioq00tk+cnDw0Njx47NcInODhi7/cZu13FLjJ2xM/aCzmGyci8aAADAHcwWX8wIAABwIwQiAABgewQiAABgewQiAABgewSifDRlyhQFBweraNGiatasmTZs2JDfJeW4cePGyeFwOD1q1qxpLU9OTtagQYNUqlQpeXt7q3v37hm+UbywWL16tR544AEFBQXJ4XBo3rx5TsuNMRozZowCAwNVrFgxhYeHa//+/U59zpw5o549e8rHx0d+fn7q16+fzp8/n4ejyJ6bjb1Pnz4Z3gcdO3Z06lMYxx4dHa0mTZqoePHiKlu2rLp27ap9+/Y59cnKe/zo0aPq3LmzPD09VbZsWY0YMUJXrlzJy6HcsqyMvW3bthle92eeecapT2Ec+9SpU1WvXj3rCwfDwsK0ePFia/md+prfbNyF/fUmEOWTr776SsOHD9fYsWO1ZcsW1a9fXxERETp16lR+l5bjateurZMnT1qPNWvWWMuGDRum7777TnPmzNGqVat04sQJdevWLR+rzb4LFy6ofv36mjJlSqbLJ06cqEmTJmnatGlav369vLy8FBERoeTkZKtPz549tWvXLsXExGjhwoVavXq1BgwYkFdDyLabjV2SOnbs6PQ++OKLL5yWF8axr1q1SoMGDdLPP/+smJgYXb58WR06dNCFCxesPjd7j6empqpz5866dOmS1q1bp5kzZ2rGjBkaM2ZMfgwpy7Iydknq37+/0+s+ceJEa1lhHXv58uU1YcIEbd68WZs2bdI999yjLl26aNeuXZLu3Nf8ZuOWCvnrbZAvmjZtagYNGmQ9T01NNUFBQSY6Ojofq8p5Y8eONfXr1890WUJCgnFzczNz5syx2vbs2WMkmdjY2DyqMHdIMnPnzrWep6WlmYCAAPPmm29abQkJCcbDw8N88cUXxhhjdu/ebSSZjRs3Wn0WL15sHA6HOX78eJ7VfruuHbsxxkRGRpouXbpcd507ZeynTp0yksyqVauMMVl7jy9atMi4uLiYuLg4q8/UqVONj4+PSUlJydsB3IZrx26MMW3atDHPPffcdde5U8ZujDElSpQwn3zyia1ec2P+/3EbU/hfb84Q5YNLly5p8+bNCg8Pt9pcXFwUHh6u2NjYfKwsd+zfv19BQUGqXLmyevbsqaNHj0qSNm/erMuXLzsdh5o1a6pixYp33HE4dOiQ4uLinMbq6+urZs2aWWONjY2Vn5+fGjdubPUJDw+Xi4uL1q9fn+c157SVK1eqbNmyqlGjhgYOHKg///zTWnanjD0xMVGSVLJkSUlZe4/Hxsaqbt26Tt+aHxERoaSkJKf/eRd014493axZs1S6dGnVqVNHo0aN0sWLF61ld8LYU1NT9eWXX+rChQsKCwuzzWt+7bjTFebX21bfVF1Q/PHHH0pNTc3wsyH+/v7au3dvPlWVO5o1a6YZM2aoRo0aOnnypF5++WW1atVKO3fuVFxcnNzd3TP8cK6/v7/i4uLyp+Bckj6ezF7z9GVxcXEqW7as0/IiRYqoZMmShf54dOzYUd26dVNISIgOHjyof/3rX+rUqZNiY2Pl6up6R4w9LS1NQ4cOVYsWLVSnTh1JytJ7PC4uLtP3RfqywiCzsUvS448/rkqVKikoKEjbt2/XyJEjtW/fPn377beSCvfYd+zYobCwMCUnJ8vb21tz585VaGiotm7deke/5tcbt1T4X28CEXJVp06drD/Xq1dPzZo1U6VKlfS///1PxYoVy8fKkJd69Ohh/blu3bqqV6+eqlSpopUrV6p9+/b5WFnOGTRokHbu3Ok0R84urjf2q+eA1a1bV4GBgWrfvr0OHjyoKlWq5HWZOapGjRraunWrEhMT9fXXXysyMlKrVq3K77Jy3fXGHRoaWuhfby6Z5YPSpUvL1dU1w10H8fHxCggIyKeq8oafn5+qV6+uAwcOKCAgQJcuXVJCQoJTnzvxOKSP50aveUBAQIZJ9VeuXNGZM2fuuONRuXJllS5dWgcOHJBU+MceFRWlhQsXasWKFSpfvrzVnpX3eEBAQKbvi/RlBd31xp6ZZs2aSZLT615Yx+7u7q6qVauqUaNGio6OVv369fX+++/f8a/59cadmcL2ehOI8oG7u7saNWqkZcuWWW1paWlatmyZ07XYO9H58+d18OBBBQYGqlGjRnJzc3M6Dvv27dPRo0fvuOMQEhKigIAAp7EmJSVp/fr11ljDwsKUkJCgzZs3W32WL1+utLQ06x+WO8Xvv/+uP//8U4GBgZIK79iNMYqKitLcuXO1fPlyhYSEOC3Pyns8LCxMO3bscAqEMTEx8vHxsS5FFEQ3G3tmtm7dKklOr3thHHtm0tLSlJKScke/5plJH3dmCt3rnd+zuu3qyy+/NB4eHmbGjBlm9+7dZsCAAcbPz89p9v2d4J///KdZuXKlOXTokFm7dq0JDw83pUuXNqdOnTLGGPPMM8+YihUrmuXLl5tNmzaZsLAwExYWls9VZ8+5c+fML7/8Yn755Rcjybzzzjvml19+MUeOHDHGGDNhwgTj5+dn5s+fb7Zv3266dOliQkJCzF9//WVto2PHjqZhw4Zm/fr1Zs2aNaZatWrmsccey68hZdmNxn7u3Dnz/PPPm9jYWHPo0CHz448/mrvuustUq1bNJCcnW9sojGMfOHCg8fX1NStXrjQnT560HhcvXrT63Ow9fuXKFVOnTh3ToUMHs3XrVrNkyRJTpkwZM2rUqPwYUpbdbOwHDhww48ePN5s2bTKHDh0y8+fPN5UrVzatW7e2tlFYx/7iiy+aVatWmUOHDpnt27ebF1980TgcDrN06VJjzJ37mt9o3HfC600gykeTJ082FStWNO7u7qZp06bm559/zu+Sctyjjz5qAgMDjbu7uylXrpx59NFHzYEDB6zlf/31l3n22WdNiRIljKenp3nwwQfNyZMn87Hi7FuxYoWRlOERGRlpjPn71vvRo0cbf39/4+HhYdq3b2/27dvntI0///zTPPbYY8bb29v4+PiYvn37mnPnzuXDaG7NjcZ+8eJF06FDB1OmTBnj5uZmKlWqZPr3758h/BfGsWc2Zklm+vTpVp+svMcPHz5sOnXqZIoVK2ZKly5t/vnPf5rLly/n8Whuzc3GfvToUdO6dWtTsmRJ4+HhYapWrWpGjBhhEhMTnbZTGMf+5JNPmkqVKhl3d3dTpkwZ0759eysMGXPnvuY3Gved8Ho7jDEm785HAQAAFDzMIQIAALZHIAIAALZHIAIAALZHIAIAALZHIAIAALZHIAIAALZHIAIAALZHIAIKiZUrV8rhcFi/kTRjxowMv6idm1q3bq3Zs2ffsI/D4dC8efPypqA8ZozRgAEDVLJkSTkcDutnCZC3xo0bpwYNGtywT48ePfT222/nTUG4YxCIgCzq06ePunbtmqH92qCSVx599FH9+uuvebKvBQsWKD4+3ulX6+1myZIlmjFjhhYuXKiTJ0+qTp06+V2SgoOD9d577+V3GbkmuwH7pZde0muvvabExMScLwp3LAIRUEgVK1ZMZcuWzZN9TZo0SX379pWLS/7/k3Hp0qV82W/6jxI3b95cAQEBKlKkSIY++VXbjaSmpiotLS2/y7glt3sc69SpoypVqujzzz/PoYpgB/n/rxtwB1qzZo1atWqlYsWKqUKFChoyZIguXLhgLf/ss8/UuHFjFS9eXAEBAXr88cedfgFakhYtWqTq1aurWLFiateunQ4fPuy0/NpLZumXEj777DMFBwfL19dXPXr00Llz56w+586dU8+ePeXl5aXAwEC9++67atu2rYYOHXrdsZw+fVrLly/XAw884NS+f/9+tW7dWkWLFlVoaKhiYmIyrHvs2DE98sgj8vPzU8mSJdWlSxencVy5ckVDhgyRn5+fSpUqpZEjRyoyMtLpTFzbtm0VFRWloUOHqnTp0oqIiJAk7dy5U506dZK3t7f8/f3Vq1cv/fHHH9Z6aWlpio6OVkhIiIoVK6b69evr66+/tpafPXtWPXv2VJkyZVSsWDFVq1ZN06dPz/QY9OnTR4MHD9bRo0flcDgUHBx8w9pWrVqlpk2bysPDQ4GBgXrxxRd15coVpzENHjxYQ4cOVYkSJeTv769///vfunDhgvr27avixYuratWqWrx48XVfl7Zt2+rIkSMaNmyYHA6HHA6HpP//fbFgwQKFhobKw8NDR48ezfR17tq1q/r06WM9T0lJ0fPPP69y5crJy8tLzZo108qVK69bg/T3WZxPPvlEDz74oDw9PVWtWjUtWLDAqU9Wjse1xzH9GD/44INOxzzdjd7nkvTAAw/oyy+/vGHtwNUIREAOO3jwoDp27Kju3btr+/bt+uqrr7RmzRpFRUVZfS5fvqxXXnlF27Zt07x583T48GGnD6Zjx46pW7dueuCBB7R161Y99dRTevHFF7O073nz5mnhwoVauHChVq1apQkTJljLhw8frrVr12rBggWKiYnRTz/9pC1bttxwm2vWrJGnp6dq1apltaWlpalbt25yd3fX+vXrNW3aNI0cOdJpvcuXLysiIkLFixfXTz/9pLVr18rb21sdO3a0zgC88cYbmjVrlqZPn661a9cqKSkp00skM2fOlLu7u9auXatp06YpISFB99xzjxo2bKhNmzZpyZIlio+P1yOPPGKtEx0drU8//VTTpk3Trl27NGzYMD3xxBNatWqVJGn06NHavXu3Fi9erD179mjq1KkqXbp0psfg/fff1/jx41W+fHmdPHlSGzduvG5tx48f13333acmTZpo27Ztmjp1qv7zn//o1VdfzTCm0qVLa8OGDRo8eLAGDhyohx9+WM2bN9eWLVvUoUMH9erVSxcvXsy0pm+//Vbly5fX+PHjdfLkSZ08edJadvHiRb3xxhv65JNPtGvXriyfSYyKilJsbKy+/PJLbd++XQ8//LA6duyo/fv333C9l19+WY888oi2b9+u++67Tz179tSZM2ck6ZaOx9XHMf0YT58+PcMxv9n7XJKaNm2qDRs2KCUlJUtjB/i1eyCLIiMjjaurq/Hy8nJ6FC1a1EgyZ8+eNcYY069fPzNgwACndX/66Sfj4uJi/vrrr0y3vXHjRiPJ+nX3UaNGmdDQUKc+I0eOdNrP9OnTja+vr7V87NixxtPT0yQlJVltI0aMMM2aNTPGGJOUlGTc3NzMnDlzrOUJCQnG09PTPPfcc9cd97vvvmsqV67s1PbDDz+YIkWKmOPHj1ttixcvNpLM3LlzjTHGfPbZZ6ZGjRomLS3N6pOSkmKKFStmfvjhB2OMMf7+/ubNN9+0ll+5csVUrFjRdOnSxWpr06aNadiwodP+X3nlFdOhQwentmPHjhlJZt++fSY5Odl4enqadevWOfXp16+feeyxx4wxxjzwwAOmb9++1x13ZsehUqVKTm2Z1favf/0rw7inTJlivL29TWpqqrVey5Ytncbt5eVlevXqZbWdPHnSSDKxsbHXralSpUrm3XffdWqbPn26kWS2bt2aodZrX+cuXbqYyMhIY4wxR44cMa6urk6vqTHGtG/f3owaNeq6NUgyL730kvX8/PnzRpJZvHixMSbrx+Pa45i+7fT3U7qbvc/Tbdu2zUgyhw8fvm7twNUyXgQHcF3t2rXT1KlTndrWr1+vJ554wnq+bds2bd++XbNmzbLajDFKS0vToUOHVKtWLW3evFnjxo3Ttm3bdPbsWWuOx9GjRxUaGqo9e/aoWbNmTvsJCwu7aX3BwcEqXry49TwwMNC6FPfbb7/p8uXLatq0qbXc19dXNWrUuOE2//rrLxUtWtSpbc+ePapQoYKCgoKuW9+2bdt04MABp3okKTk5WQcPHlRiYqLi4+Od6nF1dVWjRo0yzHlp1KhRhm2vWLFC3t7eGeo9ePCgLl++rIsXL+ree+91Wnbp0iU1bNhQkjRw4EB1797dOhvTtWtXNW/e/IbHIjPX1rZnzx6FhYVZl7AkqUWLFjp//rx+//13VaxYUZJUr149p3GXKlVKdevWtdr8/f0lKcOl1Kxwd3d32n5W7NixQ6mpqapevbpTe0pKikqVKnXDda/el5eXl3x8fKy6s3o8rj2ON3Kj93m6YsWKSdJ1z7AB1yIQAbfAy8tLVatWdWr7/fffnZ6fP39eTz/9tIYMGZJh/YoVK+rChQuKiIhQRESEZs2apTJlyujo0aOKiIi47cmkbm5uTs8dDsdtT6gtXbq0zp49e8vrnT9/Xo0aNXIKhunKlClzS9vy8vLKsO0HHnhAb7zxRoa+gYGB2rlzpyTp+++/V7ly5ZyWe3h4SJI6deqkI0eOaNGiRYqJiVH79u01aNAgvfXWW7dVW1Zl9lpd3ZYeILLz+hUrVswpgEiSi4uLjDFObZcvX7b+fP78ebm6umrz5s1ydXV16pdZ8LxaTrzvbuU4ZmV/6ZfsbvW9BvsiEAE57K677tLu3bszBKd0O3bs0J9//qkJEyaoQoUKkqRNmzY59alVq1aGiak///zzbdVVuXJlubm5aePGjdb/yhMTE/Xrr7+qdevW112vYcOGiouL09mzZ1WiRAmrvmPHjunkyZMKDAzMtL677rpLX331lcqWLSsfH59Mt+3v76+NGzda+09NTdWWLVtu+j0zd911l7755hsFBwdnerfX1ZOJ27Rpc93tlClTRpGRkYqMjFSrVq00YsSIWw5E16pVq5a++eYbGWOsULJ27VoVL15c5cuXv61tX8vd3V2pqalZ6lumTBmneUapqanauXOn2rVrJ+nv1zk1NVWnTp1Sq1atcqzG2zkebm5uWR7ftXbu3Kny5ctfd14YcC0mVQM5bOTIkVq3bp2ioqK0detW7d+/X/Pnz7cmVVesWFHu7u6aPHmyfvvtNy1YsECvvPKK0zaeeeYZ7d+/XyNGjNC+ffs0e/ZszZgx47bqKl68uCIjIzVixAitWLFCu3btUr9+/eTi4pLhbMLVGjZsqNKlS2vt2rVWW3h4uKpXr67IyEht27ZNP/30k/7v//7Pab2ePXuqdOnS6tKli3766ScdOnRIK1eu1JAhQ6yzaoMHD1Z0dLTmz5+vffv26bnnntPZs2dvWI8kDRo0SGfOnNFjjz2mjRs36uDBg/rhhx/Ut29fpaamqnjx4nr++ec1bNgwzZw5UwcPHtSWLVs0efJkzZw5U5I0ZswYzZ8/XwcOHNCuXbu0cOFCp4nj2fXss8/q2LFjGjx4sPbu3av58+dr7NixGj58eI5/bUFwcLBWr16t48ePO91hl5l77rlH33//vb7//nvt3btXAwcOdPrurOrVq6tnz57q3bu3vv32Wx06dEgbNmxQdHS0vv/++2zXeDvHIzg4WMuWLbMC+a346aef1KFDh2zXDfshEAE5rF69elq1apV+/fVXtWrVSg0bNtSYMWOs+TZlypTRjBkzNGfOHIWGhmrChAkZzkpUrFhR33zzjebNm6f69etr2rRpev3112+7tnfeeUdhYWG6//77FR4erhYtWqhWrVoZ5ghdzdXVVX379nW69OXi4qK5c+fqr7/+UtOmTfXUU0/ptddec1rP09NTq1evVsWKFdWtWzfVqlVL/fr1U3JysnXGaOTIkXrsscfUu3dvhYWFydvbWxERETesR5KCgoK0du1apaamqkOHDqpbt66GDh0qPz8/60P2lVde0ejRoxUdHa1atWqpY8eO+v777xUSEiLp77Mro0aNUr169dS6dWu5urrmyG3a5cqV06JFi7RhwwbVr19fzzzzjPr166eXXnrptrd9rfHjx+vw4cOqUqXKTS8NPfnkk4qMjFTv3r3Vpk0bVa5c2To7lG769Onq3bu3/vnPf6pGjRrq2rWr0xnF7Lid4/H2228rJiZGFSpUsOZ+ZUVycrLmzZun/v37Z7tu2I/DXHtRGYBtXLhwQeXKldPbb7+tfv36XbdfXFycateurS1btqhSpUq5Vk9aWppq1aqlRx55JMNZMyCrpk6dqrlz52rp0qX5XQoKEeYQATbyyy+/aO/evWratKkSExM1fvx4SVKXLl1uuF5AQID+85//6OjRozkaiI4cOaKlS5eqTZs2SklJ0QcffKBDhw7p8ccfz7F9wH7c3Nw0efLk/C4DhQxniAAb+eWXX/TUU09p3759cnd3V6NGjfTOO+843e6dl44dO6YePXpo586dMsaoTp06mjBhwg0neQNAbiAQAQAA22NSNQAAsD0CEQAAsD0CEQAAsD0CEQAAsD0CEQAAsD0CEQAAsD0CEQAAsD0CEQAAsD0CEQAAsL3/DyfpDQ/HU9UkAAAAAElFTkSuQmCC", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Heading histogram\n", - "\n", - "n, bins, patches = plt.hist(headings, 30, density=False, facecolor='g', alpha=0.5)\n", - "\n", - "\n", - "plt.xlabel('Heading (degrees from true north)')\n", - "plt.ylabel('Count')\n", - "plt.title('Ship Heading Distribution (Full)')\n", - "plt.grid(False)\n", - "plt.show()\n" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3.10.7 ('.env': venv)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.7" - }, - "orig_nbformat": 4, - "vscode": { - "interpreter": { - "hash": "2bb7a2c41c651f73b682b7367306edacd511b29193c16df337c21b7907a04bb5" - } - } - }, - "nbformat": 4, - "nbformat_minor": 2 -}