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datautility.ipynb
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "DataUtility.ipynb",
"provenance": [],
"collapsed_sections": [],
"toc_visible": true,
"include_colab_link": true
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
}
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/nagishin/1677ffa401476e9e98191a04012ac189/datautility.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "fnwBE86nl5d-"
},
"source": [
"# DataUtility使い方\n",
"https://github.com/nagishin/DataUtility"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "DCiOQxGxl8uj"
},
"source": [
"## 1. インストール"
]
},
{
"cell_type": "code",
"metadata": {
"id": "pNmm50d1loaj"
},
"source": [
"!pip install -U git+https://github.com/nagishin/DataUtility.git"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "M_lSVEORSI1j"
},
"source": [
"## 2. Timeクラス\n",
"日付変換・加工をサポートするクラス\n",
" * UnixTime, datetime, 日付文字列のいずれかを設定してTimeオブジェクトを作成します.\n",
" * Timeオブジェクトは必要に応じてタイムゾーン変換や時刻計算・丸めが可能です.\n",
" * TimeオブジェクトからUnixTime, datetime, 日付文字列の形式で時刻を取得できます."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "CvNHHxaNSj9a"
},
"source": [
"### 2-1. Timeオブジェクト生成 / Timeオブジェクトから時刻取得"
]
},
{
"cell_type": "code",
"metadata": {
"id": "bAREqQTpSce2",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "9afe03d1-60df-4ed9-d088-46d24ef78b05"
},
"source": [
"import time\n",
"from datetime import datetime, timedelta\n",
"from dateutil.relativedelta import relativedelta\n",
"import DataUtility as du\n",
"\n",
"#-------------------------------------------------------------------------------\n",
"# Timeオブジェクト生成\n",
"#-------------------------------------------------------------------------------\n",
"# [params]\n",
"# value : 設定する日付オブジェクト (UnixTime, datetime, str)\n",
"# tz : 設定するタイムゾーンをhours(int)または'UTC'/'JST'で設定 (デフォルトはUTC)\n",
"# str_fmt : valueがstrの場合に適用する日付フォーマット (省略可)\n",
"#-------------------------------------------------------------------------------\n",
"# UnixTimeから\n",
"t = du.Time(time.time(), tz='UTC')\n",
"# datetimeから\n",
"t = du.Time(datetime.now(), tz='JST')\n",
"# 日付文字列から\n",
"t = du.Time('2021/03/15 10:10:22', tz=+9)\n",
"\n",
"#-------------------------------------------------------------------------------\n",
"# Timeオブジェクトから時刻取得\n",
"#-------------------------------------------------------------------------------\n",
"# UnixTime取得\n",
"ut = t.unixtime()\n",
"print(ut)\n",
"# datetime取得\n",
"dt = t.datetime()\n",
"print(dt)\n",
"# 日付文字列取得\n",
"st = t.str('%Y/%m/%d %H:%M:%S')\n",
"print(st)"
],
"execution_count": 1,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"1615770622.0\n",
"2021-03-15 10:10:22+09:00\n",
"2021/03/15 10:10:22\n"
]
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "Mvks-UbPS-Za"
},
"source": [
"### 2-2. タイムゾーン変換"
]
},
{
"cell_type": "code",
"metadata": {
"id": "wC29r4ewT7OW",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "b44ec51f-f011-4eae-e931-6ee7f65bda41"
},
"source": [
"# Timeオブジェクト生成\n",
"t = du.Time('2021/03/15 10:00:00', tz='UTC')\n",
"print(t.datetime())\n",
"\n",
"#-------------------------------------------------------------------------------\n",
"# タイムゾーン変換\n",
"#-------------------------------------------------------------------------------\n",
"# [params]\n",
"# tz : 変換するタイムゾーンをhours(int)または'UTC'/'JST'で設定 (デフォルトはUTC)\n",
"#-------------------------------------------------------------------------------\n",
"# UTC -> JST\n",
"t.convert_timezone('JST')\n",
"print(t.datetime())"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"2021-03-15 10:00:00+00:00\n",
"2021-03-15 19:00:00+09:00\n"
]
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "QSHf2Wx5UkOK"
},
"source": [
"### 2-3. 時刻計算"
]
},
{
"cell_type": "code",
"metadata": {
"id": "A3AGo3roUoYi",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "1629162f-a83e-4cde-e44e-ebae5fc45750"
},
"source": [
"# Timeオブジェクト生成\n",
"t = du.Time('2021/03/15 00:00:00', tz='JST')\n",
"print(t.datetime())\n",
"\n",
"#-------------------------------------------------------------------------------\n",
"# 時刻計算\n",
"#-------------------------------------------------------------------------------\n",
"# 1日 加算\n",
"t.add_days(1)\n",
"print(t.datetime())\n",
"\n",
"# 5時間 減算\n",
"t.add_hours(-5)\n",
"print(t.datetime())\n",
"\n",
"# 15分 加算\n",
"t.add_minutes(15)\n",
"print(t.datetime())\n",
"\n",
"# 30秒 減算\n",
"t.add_seconds(-30)\n",
"print(t.datetime())"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"2021-03-15 00:00:00+09:00\n",
"2021-03-16 00:00:00+09:00\n",
"2021-03-15 19:00:00+09:00\n",
"2021-03-15 19:15:00+09:00\n",
"2021-03-15 19:14:30+09:00\n"
]
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "VHPVFW-vX4ud"
},
"source": [
"### 2-4. 時刻丸め"
]
},
{
"cell_type": "code",
"metadata": {
"id": "DfqC_pdvX9tc",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "0f03270b-82d3-4764-845a-d4da56eb7e41"
},
"source": [
"# Timeオブジェクト生成\n",
"t = du.Time('2021/03/15 12:34:45.678')\n",
"print(t.datetime())\n",
"\n",
"#-------------------------------------------------------------------------------\n",
"# 時刻計算\n",
"#-------------------------------------------------------------------------------\n",
"# [params]\n",
"# is_down : True:切り捨て, False:切り上げ\n",
"#-------------------------------------------------------------------------------\n",
"# 10秒 切り捨て丸め\n",
"t.round_seconds(10)\n",
"print(t.datetime())\n",
"\n",
"# 15分 切り上げ丸め\n",
"t.round_minutes(15, is_down=False)\n",
"print(t.datetime())\n",
"\n",
"# 4時間 切り捨て丸め\n",
"t.round_hours(4)\n",
"print(t.datetime())\n",
"\n",
"# 1日 切り上げ丸め\n",
"t.round_days(1)\n",
"print(t.datetime())"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"2021-03-15 12:34:45.678000+00:00\n",
"2021-03-15 12:34:40+00:00\n",
"2021-03-15 12:45:00+00:00\n",
"2021-03-15 12:00:00+00:00\n",
"2021-03-15 00:00:00+00:00\n"
]
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "OHUl3WDUZF6t"
},
"source": [
"### 2-5. 応用\n",
"メソッドチェーンによる直感的な時刻操作<br>\n",
"Timeクラスの各関数はチェーン呼び出しができるため、変換・加工を連続的に実施できます."
]
},
{
"cell_type": "code",
"metadata": {
"id": "51HRwltuZSyl",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "31fa2086-ede6-4009-c127-00c740ee89a7"
},
"source": [
"#-------------------------------------------------------------------------------\n",
"# 日付文字列をUnixTimeに変換\n",
"#-------------------------------------------------------------------------------\n",
"ut = du.Time('2021/03/15 10:10:22', tz='JST').unixtime()\n",
"print(ut)\n",
"\n",
"#-------------------------------------------------------------------------------\n",
"# 現在時刻の4H足 開始時刻をdatetimeで取得\n",
"#-------------------------------------------------------------------------------\n",
"dt = du.Time(datetime.now(), tz='UTC').round_hours(4).datetime()\n",
"print(dt)\n",
"\n",
"#-------------------------------------------------------------------------------\n",
"# 現在時刻(JST)の8時間10分後の15m足 開始時刻をUTC日付文字列('%Y/%m/%d %H:%M')で取得\n",
"#-------------------------------------------------------------------------------\n",
"st = du.Time(datetime.now(), tz='JST') \\\n",
" .add_hours(8) \\\n",
" .add_minutes(10) \\\n",
" .round_minutes(15) \\\n",
" .convert_timezone('UTC') \\\n",
" .str('%Y/%m/%d %H:%M')\n",
"print(st)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"1615770622.0\n",
"2021-09-10 04:00:00+00:00\n",
"2021/09/10 13:30\n"
]
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "y0JpVGmRJjJ8"
},
"source": [
"### 2-6. 様々な時刻演算\n",
"TimeオブジェクトはTime / datetime / unixtimeと演算の互換性があります.<br>\n",
"また、日付加工特有の曜日や月初日、月末日etc.を容易に取得できます."
]
},
{
"cell_type": "code",
"metadata": {
"id": "jFZxGNaYKeSN",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "5ecd8f70-c664-43cb-cc1b-f801993924aa"
},
"source": [
"t = du.Time(datetime.now(), tz='JST')\n",
"print(f'[unixtime]:{t.unixtime()} [datetime]:{t.datetime()}')"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"[unixtime]:1631252526.39122 [datetime]:2021-09-10 14:42:06.391220+09:00\n"
]
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "cFHt_p68Mqt9",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "3291fd48-c230-4f74-ef1a-ea55cfdfb4dc"
},
"source": [
"# 設定時刻の年,月,日,時,分,秒,マイクロ秒をタプルで取得\n",
"print(t.date())\n",
"\n",
"# それぞれバラバラにも取得可能\n",
"print(t.year())\n",
"print(t.month())\n",
"print(t.day())\n",
"print(t.hour())\n",
"print(t.minute())\n",
"print(t.second())\n",
"print(t.microsecond())"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"(2021, 9, 10, 14, 42, 6, 391220)\n",
"2021\n",
"9\n",
"10\n",
"14\n",
"42\n",
"6\n",
"391220\n"
]
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "sqpcWXLpM2dz",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "0c9bec88-9d56-4193-f50f-c1ee056fbb60"
},
"source": [
"# 設定時刻の曜日を取得\n",
"print(t.weekday())\n",
"print(t.weekday_name())"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"4\n",
"Friday\n"
]
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "3G5YcJ8JM3xD",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "8905c28f-8026-4b8c-9c5b-5b4e8abe38c2"
},
"source": [
"# 設定時刻からみた月初日/月末日\n",
"print(t.month_first_day(), t.month_last_day())\n",
"# 設定時刻からみた年初日/年末日\n",
"print(t.year_first_day(), t.year_last_day())"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"2021-09-01 00:00:00+09:00 2021-09-30 00:00:00+09:00\n",
"2021-01-01 00:00:00+09:00 2021-12-31 00:00:00+09:00\n"
]
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "rTYfiEZ2NxFr",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "3bf9ffaf-1918-44a0-c617-12dac30ea70d"
},
"source": [
"# 設定時刻を年初日に設定\n",
"t.set_year_first_day()\n",
"print(f'[unixtime]:{t.unixtime()} [datetime]:{t.datetime()}')"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"[unixtime]:1609426800.0 [datetime]:2021-01-01 00:00:00+09:00\n"
]
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "wggKG6YsNaeT",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "0f3f60b2-fb88-4e23-eccf-74962e51ff4b"
},
"source": [
"# 任意期間を加算\n",
"t.add_date(years=1, months=2, days=3, hours=4, minutes=5, seconds=6, microseconds=7)\n",
"print(f'[unixtime]:{t.unixtime()} [datetime]:{t.datetime()}')\n",
"\n",
"# それぞれバラバラに加算も可能\n",
"#t.add_years(1)\n",
"#t.add_months(2)\n",
"#t.add_days(3)\n",
"#t.add_hours(4)\n",
"#t.add_minutes(5)\n",
"#t.add_seconds(6)\n",
"#t.add_microseconds(7)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"[unixtime]:1646334306.000007 [datetime]:2022-03-04 04:05:06.000007+09:00\n"
]
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "RE3kDtDWPbeb",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "b0108efe-1506-4387-d236-62e4cee37d66"
},
"source": [
"# 設定時刻を年初日に設定\n",
"t = du.Time(datetime.now(), tz='JST')\n",
"t.set_year_first_day()\n",
"print(f't : [unixtime]:{t.unixtime()} [datetime]:{t.datetime()}')"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"t : [unixtime]:1609426800.0 [datetime]:2021-01-01 00:00:00+09:00\n"
]
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "xkDFX139RBWz",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "5de505f8-76db-4a8d-d871-23402ce4a094"
},
"source": [
"# 加算(relativedelta)\n",
"ret = t + relativedelta(years=1)\n",
"print('ret = t + relativedelta(years=1)')\n",
"print(f'ret : [unixtime]:{ret.unixtime()} [datetime]:{ret.datetime()}\\n')\n",
"\n",
"# 比較(Time : Time)\n",
"print(f'[t] :{t.datetime()}')\n",
"print(f'[ret]:{ret.datetime()}')\n",
"print(f't==ret:{t == ret} t!=ret:{t != ret}')\n",
"print(f't< ret:{t < ret} t> ret:{t > ret}')\n",
"print(f't<=ret:{t <= ret} t>=ret:{t >= ret}')"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"ret = t + relativedelta(years=1)\n",
"ret : [unixtime]:1640962800.0 [datetime]:2022-01-01 00:00:00+09:00\n",
"\n",
"[t] :2021-01-01 00:00:00+09:00\n",
"[ret]:2022-01-01 00:00:00+09:00\n",
"t==ret:False t!=ret:True\n",
"t< ret:True t> ret:False\n",
"t<=ret:True t>=ret:False\n"
]
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "7t-Jf4xrS0Ez",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "e680c87a-4dac-4a43-bffe-2d3b5c753e30"
},
"source": [
"# 減算(unixtime)\n",
"ret = t - 3600\n",
"print('ret = t - 3600')\n",
"print(f'ret : [unixtime]:{ret.unixtime()} [datetime]:{ret.datetime()}\\n')\n",
"\n",
"# 比較(Time : datetime)\n",
"print(f'[t] :{t.datetime()}')\n",
"print(f'[ret]:{ret.datetime()}')\n",
"print(f't==ret:{t == ret.datetime()} t!=ret:{t != ret.datetime()}')\n",
"print(f't< ret:{t < ret.datetime()} t> ret:{t > ret.datetime()}')\n",
"print(f't<=ret:{t <= ret.datetime()} t>=ret:{t >= ret.datetime()}')"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"ret = t - 3600\n",
"ret : [unixtime]:1609423200.0 [datetime]:2020-12-31 23:00:00+09:00\n",
"\n",
"[t] :2021-01-01 00:00:00+09:00\n",
"[ret]:2020-12-31 23:00:00+09:00\n",
"t==ret:False t!=ret:True\n",
"t< ret:False t> ret:True\n",
"t<=ret:False t>=ret:True\n"
]
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "diMPPiqpmU0F"
},
"source": [
"## 3. Toolクラス\n",
"BitMEX, bybitのOHLCVや約定履歴の取得・加工をサポートするクラス<br>\n",
"DataFrameでよく行う加工や変換を簡単に行う機能を関数化"
]
},
{
"cell_type": "code",
"metadata": {
"id": "kqKKDUMalz3u",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "5dec6a76-00f7-4dda-e611-15bd93a09fd8"
},
"source": [
"# データ取得期間設定 (Unix Time指定)\n",
"start_ut = int(du.Time('2020/09/01 09:00:00', 'JST').unixtime())\n",
"end_ut = int(du.Time('2020/09/05 09:00:00', 'JST').unixtime())\n",
"\n",
"print(start_ut, end_ut)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"1598918400 1599264000\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "hgziAu-gmzE5"
},
"source": [
"## 3. データ取得"
]
},
{
"cell_type": "code",
"metadata": {
"id": "LRa7sdT5npTl"
},
"source": [
"import random\n",
"import numpy as np\n",
"import pandas as pd\n",
"import DataUtility as du"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "fJD0lEnomyEw",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 436
},
"outputId": "c14ece9b-6701-494a-ca79-1972147df825"
},
"source": [
"#-------------------------------------------------------------------------------\n",
"# bybit約定履歴を取得\n",
"# (https://public.bybit.com/trading/BTCUSD/ より)\n",
"#-------------------------------------------------------------------------------\n",
"# [params]\n",
"# start_ut / end_ut : UnixTimeで指定\n",
"# 取得可能期間 : 2019-10-01以降かつ前日まで\n",
"# symbol : 取得対象の通貨ペアシンボル名（デフォルトは BTCUSD）\n",
"# csv_path : 該当ファイルがあれば読み込んで対象期間をチェック\n",
"# ファイルがない or 期間を満たしていない場合はrequestで取得\n",
"# csvファイル保存 (None or 空文字は保存しない)\n",
"# progress_info : 処理途中経過をprint\n",
"# [return]\n",
"# DataFrame columns=['unixtime', 'side', 'size', 'price']\n",
"#-------------------------------------------------------------------------------\n",
"df_bybit_trades = du.Tool.get_trades_from_bybit(start_ut, end_ut, symbol='BTCUSD', csv_path='./bybit_trades.csv')\n",
"\n",
"display(df_bybit_trades)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"trades from request.\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
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" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>unixtime</th>\n",
" <th>side</th>\n",
" <th>size</th>\n",
" <th>price</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1.598918e+09</td>\n",
" <td>Sell</td>\n",
" <td>7000</td>\n",
" <td>11659.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1.598918e+09</td>\n",
" <td>Buy</td>\n",
" <td>40</td>\n",
" <td>11660.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>1.598918e+09</td>\n",
" <td>Buy</td>\n",
" <td>1</td>\n",
" <td>11660.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>1.598918e+09</td>\n",
" <td>Sell</td>\n",
" <td>50</td>\n",
" <td>11659.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>1.598918e+09</td>\n",
" <td>Sell</td>\n",
" <td>210</td>\n",
" <td>11659.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1293136</th>\n",
" <td>1.599264e+09</td>\n",
" <td>Sell</td>\n",
" <td>400</td>\n",
" <td>10454.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1293137</th>\n",
" <td>1.599264e+09</td>\n",
" <td>Buy</td>\n",
" <td>13</td>\n",
" <td>10455.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1293138</th>\n",
" <td>1.599264e+09</td>\n",
" <td>Sell</td>\n",
" <td>2000</td>\n",
" <td>10454.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1293139</th>\n",
" <td>1.599264e+09</td>\n",
" <td>Buy</td>\n",
" <td>11</td>\n",
" <td>10455.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1293140</th>\n",
" <td>1.599264e+09</td>\n",
" <td>Buy</td>\n",
" <td>500</td>\n",
" <td>10455.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>1293141 rows × 4 columns</p>\n",
"</div>"
],
"text/plain": [
" unixtime side size price\n",
"0 1.598918e+09 Sell 7000 11659.5\n",
"1 1.598918e+09 Buy 40 11660.0\n",
"2 1.598918e+09 Buy 1 11660.0\n",
"3 1.598918e+09 Sell 50 11659.5\n",
"4 1.598918e+09 Sell 210 11659.5\n",
"... ... ... ... ...\n",
"1293136 1.599264e+09 Sell 400 10454.5\n",
"1293137 1.599264e+09 Buy 13 10455.0\n",
"1293138 1.599264e+09 Sell 2000 10454.5\n",
"1293139 1.599264e+09 Buy 11 10455.0\n",
"1293140 1.599264e+09 Buy 500 10455.0\n",
"\n",
"[1293141 rows x 4 columns]"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "q5OLDlmunijd",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 450
},
"outputId": "e024dd63-d914-4641-d0a7-ca7a921ea2f8"
},
"source": [
"#-------------------------------------------------------------------------------\n",
"# 約定履歴をOHLCVにリサンプリング\n",
"#-------------------------------------------------------------------------------\n",
"# [params]\n",
"# df : DateTimeIndexとprice,size列を含むDataFrame\n",
"# period : リサンプルするタイムフレーム ex) '1S'(秒), '5T'(分), '4H'(時), '1D'(日)\n",
"# [return]\n",
"# DataFrame columns=['unixtime', 'open', 'high', 'low', 'close', 'volume']\n",
"#-------------------------------------------------------------------------------\n",
"df_bybit_ohlcv = du.Tool.trade_to_ohlcv(df_bybit_trades, period='1T')\n",
"\n",
"display(df_bybit_ohlcv)"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
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" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>unixtime</th>\n",
" <th>open</th>\n",
" <th>high</th>\n",
" <th>low</th>\n",
" <th>close</th>\n",
" <th>volume</th>\n",
" </tr>\n",
" <tr>\n",
" <th>datetime</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2020-09-01 00:00:00+00:00</th>\n",
" <td>1598918400</td>\n",
" <td>11659.5</td>\n",
" <td>11668.5</td>\n",
" <td>11657.5</td>\n",
" <td>11668.5</td>\n",
" <td>3335761</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 00:01:00+00:00</th>\n",
" <td>1598918460</td>\n",
" <td>11668.0</td>\n",
" <td>11674.5</td>\n",
" <td>11668.0</td>\n",
" <td>11674.5</td>\n",
" <td>919116</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 00:02:00+00:00</th>\n",
" <td>1598918520</td>\n",
" <td>11674.0</td>\n",
" <td>11675.0</td>\n",
" <td>11674.0</td>\n",
" <td>11674.5</td>\n",
" <td>222945</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 00:03:00+00:00</th>\n",
" <td>1598918580</td>\n",
" <td>11674.5</td>\n",
" <td>11675.0</td>\n",
" <td>11670.0</td>\n",
" <td>11670.0</td>\n",
" <td>859762</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 00:04:00+00:00</th>\n",
" <td>1598918640</td>\n",
" <td>11670.0</td>\n",
" <td>11670.0</td>\n",
" <td>11645.0</td>\n",
" <td>11656.5</td>\n",
" <td>1811631</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 23:55:00+00:00</th>\n",
" <td>1599263700</td>\n",
" <td>10472.5</td>\n",
" <td>10472.5</td>\n",
" <td>10472.0</td>\n",
" <td>10472.5</td>\n",
" <td>137364</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 23:56:00+00:00</th>\n",
" <td>1599263760</td>\n",
" <td>10472.5</td>\n",
" <td>10472.5</td>\n",
" <td>10470.0</td>\n",
" <td>10470.5</td>\n",
" <td>45541</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 23:57:00+00:00</th>\n",
" <td>1599263820</td>\n",
" <td>10470.0</td>\n",
" <td>10470.5</td>\n",
" <td>10470.0</td>\n",
" <td>10470.5</td>\n",
" <td>697</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 23:58:00+00:00</th>\n",
" <td>1599263880</td>\n",
" <td>10470.5</td>\n",
" <td>10470.5</td>\n",
" <td>10459.5</td>\n",
" <td>10459.5</td>\n",
" <td>678282</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 23:59:00+00:00</th>\n",
" <td>1599263940</td>\n",
" <td>10459.5</td>\n",
" <td>10460.0</td>\n",
" <td>10451.5</td>\n",
" <td>10455.0</td>\n",
" <td>393265</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5760 rows × 6 columns</p>\n",
"</div>"
],
"text/plain": [
" unixtime open ... close volume\n",
"datetime ... \n",
"2020-09-01 00:00:00+00:00 1598918400 11659.5 ... 11668.5 3335761\n",
"2020-09-01 00:01:00+00:00 1598918460 11668.0 ... 11674.5 919116\n",
"2020-09-01 00:02:00+00:00 1598918520 11674.0 ... 11674.5 222945\n",
"2020-09-01 00:03:00+00:00 1598918580 11674.5 ... 11670.0 859762\n",
"2020-09-01 00:04:00+00:00 1598918640 11670.0 ... 11656.5 1811631\n",
"... ... ... ... ... ...\n",
"2020-09-04 23:55:00+00:00 1599263700 10472.5 ... 10472.5 137364\n",
"2020-09-04 23:56:00+00:00 1599263760 10472.5 ... 10470.5 45541\n",
"2020-09-04 23:57:00+00:00 1599263820 10470.0 ... 10470.5 697\n",
"2020-09-04 23:58:00+00:00 1599263880 10470.5 ... 10459.5 678282\n",
"2020-09-04 23:59:00+00:00 1599263940 10459.5 ... 10455.0 393265\n",
"\n",
"[5760 rows x 6 columns]"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "BbiLdHhRn3nz",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 453
},
"outputId": "cdb21036-ad23-4a45-baa8-d5477ee64f8c"
},
"source": [
"#-------------------------------------------------------------------------------\n",
"# BitMEX OHLCVを取得\n",
"#-------------------------------------------------------------------------------\n",
"# [params]\n",
"# start_ut / end_ut : UnixTimeで指定\n",
"# period : 分を指定 (1 or 5 or 60 or 1D)\n",
"# symbol : 取得対象の通貨ペアシンボル名 (デフォルトはXBTUSD)\n",
"# csv_path : 該当ファイルがあれば読み込んで対象期間をチェック\n",
"# ファイルがない or 期間を満たしていない場合はrequestで取得\n",
"# csvファイル保存 (None or 空文字は保存しない)\n",
"# request_interval : 複数request時のsleep時間(sec)\n",
"# progress_info : 処理途中経過をprint\n",
"# [return]\n",
"# DataFrame columns=['unixtime', 'open', 'high', 'low', 'close', 'volume']\n",
"#-------------------------------------------------------------------------------\n",
"df_bitmex_ohlcv = du.Tool.get_ohlcv_from_bitmex(start_ut, end_ut, period=1, symbol='XBTUSD', csv_path='./bitmex_ohlcv.csv', request_interval=0.5)\n",
"\n",
"display(df_bitmex_ohlcv)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"save csv: 1598918400 - 1599263940 (len=5760)\n",
"get df : 1598918400 - 1599263940 (len=5760)\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
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" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>unixtime</th>\n",
" <th>open</th>\n",
" <th>high</th>\n",
" <th>low</th>\n",
" <th>close</th>\n",
" <th>volume</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1598918400</td>\n",
" <td>11658.0</td>\n",
" <td>11673.0</td>\n",
" <td>11657.5</td>\n",
" <td>11672.5</td>\n",
" <td>1503198</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1598918460</td>\n",
" <td>11672.5</td>\n",
" <td>11676.0</td>\n",
" <td>11671.0</td>\n",
" <td>11676.0</td>\n",
" <td>802489</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>1598918520</td>\n",
" <td>11676.0</td>\n",
" <td>11676.0</td>\n",
" <td>11675.5</td>\n",
" <td>11675.5</td>\n",
" <td>543199</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>1598918580</td>\n",
" <td>11675.5</td>\n",
" <td>11676.0</td>\n",
" <td>11669.5</td>\n",
" <td>11670.0</td>\n",
" <td>1193766</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>1598918640</td>\n",
" <td>11670.0</td>\n",
" <td>11670.0</td>\n",
" <td>11650.0</td>\n",
" <td>11654.5</td>\n",
" <td>4711547</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5755</th>\n",
" <td>1599263700</td>\n",
" <td>10478.0</td>\n",
" <td>10478.0</td>\n",
" <td>10473.0</td>\n",
" <td>10473.0</td>\n",
" <td>68195</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5756</th>\n",
" <td>1599263760</td>\n",
" <td>10473.0</td>\n",
" <td>10473.5</td>\n",
" <td>10471.0</td>\n",
" <td>10471.0</td>\n",
" <td>125138</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5757</th>\n",
" <td>1599263820</td>\n",
" <td>10471.0</td>\n",
" <td>10471.5</td>\n",
" <td>10471.0</td>\n",
" <td>10471.0</td>\n",
" <td>32447</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5758</th>\n",
" <td>1599263880</td>\n",
" <td>10471.0</td>\n",
" <td>10471.5</td>\n",
" <td>10462.0</td>\n",
" <td>10462.5</td>\n",
" <td>1160564</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5759</th>\n",
" <td>1599263940</td>\n",
" <td>10462.5</td>\n",
" <td>10462.5</td>\n",
" <td>10455.0</td>\n",
" <td>10455.0</td>\n",
" <td>843951</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5760 rows × 6 columns</p>\n",
"</div>"
],
"text/plain": [
" unixtime open high low close volume\n",
"0 1598918400 11658.0 11673.0 11657.5 11672.5 1503198\n",
"1 1598918460 11672.5 11676.0 11671.0 11676.0 802489\n",
"2 1598918520 11676.0 11676.0 11675.5 11675.5 543199\n",
"3 1598918580 11675.5 11676.0 11669.5 11670.0 1193766\n",
"4 1598918640 11670.0 11670.0 11650.0 11654.5 4711547\n",
"... ... ... ... ... ... ...\n",
"5755 1599263700 10478.0 10478.0 10473.0 10473.0 68195\n",
"5756 1599263760 10473.0 10473.5 10471.0 10471.0 125138\n",
"5757 1599263820 10471.0 10471.5 10471.0 10471.0 32447\n",
"5758 1599263880 10471.0 10471.5 10462.0 10462.5 1160564\n",
"5759 1599263940 10462.5 10462.5 10455.0 10455.0 843951\n",
"\n",
"[5760 rows x 6 columns]"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "MU4Scx3z6v_n",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 453
},
"outputId": "8541c863-90cf-4e86-b4ee-37c286e66655"
},
"source": [
"#---------------------------------------------------------------------------\n",
"# bybit OHLCVを取得\n",
"# (取得件数:200/requestとなるため, 大量取得時はRateLimit注意)\n",
"#---------------------------------------------------------------------------\n",
"# [params]\n",
"# start_ut / end_ut : UnixTimeで指定\n",
"# period : 期間指定 (1 3 5 15 30 60 120 240 360 720 'D' 'M' 'W')\n",
"# symbol : 取得対象の通貨ペアシンボル名 (デフォルトはBTCUSD)\n",
"# csv_path : 該当ファイルがあれば読み込んで対象期間をチェック\n",
"# ファイルがない or 期間を満たしていない場合はrequestで取得\n",
"# csvファイル保存 (None or 空文字は保存しない)\n",
"# request_interval : 複数request時のsleep時間(sec)\n",
"# ohlcv_kind : end point指定\n",
"# 'default':kline, 'mark':mark-price, 'index':index-price, 'premium':premium-index\n",
"# progress_info : 処理途中経過をprint\n",
"# [return]\n",
"# DataFrame columns=['unixtime', 'open', 'high', 'low', 'close', ('volume')]\n",
"#---------------------------------------------------------------------------\n",
"df_bybit_ohlcv = du.Tool.get_ohlcv_from_bybit(start_ut, end_ut, period=1, symbol='BTCUSD', csv_path='./bybit_ohlcv.csv', ohlcv_kind='default')\n",
"\n",
"display(df_bybit_ohlcv)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"save csv: 1598918400 - 1599263940 (len=5760)\n",
"get df : 1598918400 - 1599263940 (len=5760)\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
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"<style scoped>\n",
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"\n",
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"</style>\n",
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" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>unixtime</th>\n",
" <th>open</th>\n",
" <th>high</th>\n",
" <th>low</th>\n",
" <th>close</th>\n",
" <th>volume</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1598918400</td>\n",
" <td>11660.0</td>\n",
" <td>11668.5</td>\n",
" <td>11657.5</td>\n",
" <td>11668.5</td>\n",
" <td>3335761</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1598918460</td>\n",
" <td>11668.5</td>\n",
" <td>11674.5</td>\n",
" <td>11668.0</td>\n",
" <td>11674.5</td>\n",
" <td>919116</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>1598918520</td>\n",
" <td>11674.5</td>\n",
" <td>11675.0</td>\n",
" <td>11674.0</td>\n",
" <td>11674.5</td>\n",
" <td>222945</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>1598918580</td>\n",
" <td>11674.5</td>\n",
" <td>11675.0</td>\n",
" <td>11670.0</td>\n",
" <td>11670.0</td>\n",
" <td>859762</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>1598918640</td>\n",
" <td>11670.0</td>\n",
" <td>11670.0</td>\n",
" <td>11645.0</td>\n",
" <td>11656.5</td>\n",
" <td>1811631</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5755</th>\n",
" <td>1599263700</td>\n",
" <td>10473.0</td>\n",
" <td>10473.0</td>\n",
" <td>10472.0</td>\n",
" <td>10472.5</td>\n",
" <td>137364</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5756</th>\n",
" <td>1599263760</td>\n",
" <td>10472.5</td>\n",
" <td>10472.5</td>\n",
" <td>10470.0</td>\n",
" <td>10470.5</td>\n",
" <td>45541</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5757</th>\n",
" <td>1599263820</td>\n",
" <td>10470.5</td>\n",
" <td>10470.5</td>\n",
" <td>10470.0</td>\n",
" <td>10470.5</td>\n",
" <td>697</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5758</th>\n",
" <td>1599263880</td>\n",
" <td>10470.5</td>\n",
" <td>10470.5</td>\n",
" <td>10459.5</td>\n",
" <td>10459.5</td>\n",
" <td>678282</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5759</th>\n",
" <td>1599263940</td>\n",
" <td>10459.5</td>\n",
" <td>10460.0</td>\n",
" <td>10451.5</td>\n",
" <td>10455.0</td>\n",
" <td>393265</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5760 rows × 6 columns</p>\n",
"</div>"
],
"text/plain": [
" unixtime open high low close volume\n",
"0 1598918400 11660.0 11668.5 11657.5 11668.5 3335761\n",
"1 1598918460 11668.5 11674.5 11668.0 11674.5 919116\n",
"2 1598918520 11674.5 11675.0 11674.0 11674.5 222945\n",
"3 1598918580 11674.5 11675.0 11670.0 11670.0 859762\n",
"4 1598918640 11670.0 11670.0 11645.0 11656.5 1811631\n",
"... ... ... ... ... ... ...\n",
"5755 1599263700 10473.0 10473.0 10472.0 10472.5 137364\n",
"5756 1599263760 10472.5 10472.5 10470.0 10470.5 45541\n",
"5757 1599263820 10470.5 10470.5 10470.0 10470.5 697\n",
"5758 1599263880 10470.5 10470.5 10459.5 10459.5 678282\n",
"5759 1599263940 10459.5 10460.0 10451.5 10455.0 393265\n",
"\n",
"[5760 rows x 6 columns]"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "KuxDBeeP7Bb9",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 453
},
"outputId": "e9c54b16-c648-4b55-f8d6-987aad9f1cbc"
},
"source": [
"#---------------------------------------------------------------------------\n",
"# coinbase OHLCVを取得\n",
"# (取得件数:300/requestとなるため, 大量取得時はRateLimit注意)\n",
"#---------------------------------------------------------------------------\n",
"# [params]\n",
"# start_ut / end_ut : UnixTimeで指定\n",
"# period : 分を指定 (1 or 5 or 15 or 60 or 360 or 1440)\n",
"# symbol : 取得対象の通貨ペアシンボル名 (デフォルトはBTC-USD)\n",
"# csv_path : 該当ファイルがあれば読み込んで対象期間をチェック\n",
"# ファイルがない or 期間を満たしていない場合はrequestで取得\n",
"# csvファイル保存 (None or 空文字は保存しない)\n",
"# request_interval : 複数request時のsleep時間(sec)\n",
"# progress_info : 処理途中経過をprint\n",
"# [return]\n",
"# DataFrame columns=['unixtime', 'open', 'high', 'low', 'close', 'volume']\n",
"#---------------------------------------------------------------------------\n",
"df_coinbase_ohlcv = du.Tool.get_ohlcv_from_coinbase(start_ut, end_ut, period=1, symbol='BTC-USD', request_interval=0.5)\n",
"\n",
"display(df_coinbase_ohlcv)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"save csv: 1598918400 - 1599260040 (len=5695)\n",
"get df : 1598918400 - 1599260040 (len=5695)\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>unixtime</th>\n",
" <th>open</th>\n",
" <th>high</th>\n",
" <th>low</th>\n",
" <th>close</th>\n",
" <th>volume</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1598918400</td>\n",
" <td>11655.00</td>\n",
" <td>11667.95</td>\n",
" <td>11655.00</td>\n",
" <td>11665.93</td>\n",
" <td>18.618135</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1598918460</td>\n",
" <td>11665.93</td>\n",
" <td>11670.00</td>\n",
" <td>11665.93</td>\n",
" <td>11669.99</td>\n",
" <td>30.599364</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>1598918520</td>\n",
" <td>11668.65</td>\n",
" <td>11672.80</td>\n",
" <td>11669.99</td>\n",
" <td>11670.34</td>\n",
" <td>10.110813</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>1598918580</td>\n",
" <td>11665.93</td>\n",
" <td>11670.36</td>\n",
" <td>11670.34</td>\n",
" <td>11665.93</td>\n",
" <td>3.760857</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>1598918640</td>\n",
" <td>11650.00</td>\n",
" <td>11665.94</td>\n",
" <td>11665.93</td>\n",
" <td>11652.20</td>\n",
" <td>51.447611</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5690</th>\n",
" <td>1599259800</td>\n",
" <td>10505.00</td>\n",
" <td>10519.48</td>\n",
" <td>10519.48</td>\n",
" <td>10510.36</td>\n",
" <td>17.553535</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5691</th>\n",
" <td>1599259860</td>\n",
" <td>10488.54</td>\n",
" <td>10510.16</td>\n",
" <td>10510.16</td>\n",
" <td>10499.35</td>\n",
" <td>41.164017</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5692</th>\n",
" <td>1599259920</td>\n",
" <td>10446.58</td>\n",
" <td>10499.31</td>\n",
" <td>10499.31</td>\n",
" <td>10466.12</td>\n",
" <td>70.377604</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5693</th>\n",
" <td>1599259980</td>\n",
" <td>10465.93</td>\n",
" <td>10492.41</td>\n",
" <td>10465.93</td>\n",
" <td>10476.98</td>\n",
" <td>25.725507</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5694</th>\n",
" <td>1599260040</td>\n",
" <td>10475.71</td>\n",
" <td>10502.70</td>\n",
" <td>10476.58</td>\n",
" <td>10500.05</td>\n",
" <td>33.257904</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5695 rows × 6 columns</p>\n",
"</div>"
],
"text/plain": [
" unixtime open high low close volume\n",
"0 1598918400 11655.00 11667.95 11655.00 11665.93 18.618135\n",
"1 1598918460 11665.93 11670.00 11665.93 11669.99 30.599364\n",
"2 1598918520 11668.65 11672.80 11669.99 11670.34 10.110813\n",
"3 1598918580 11665.93 11670.36 11670.34 11665.93 3.760857\n",
"4 1598918640 11650.00 11665.94 11665.93 11652.20 51.447611\n",
"... ... ... ... ... ... ...\n",
"5690 1599259800 10505.00 10519.48 10519.48 10510.36 17.553535\n",
"5691 1599259860 10488.54 10510.16 10510.16 10499.35 41.164017\n",
"5692 1599259920 10446.58 10499.31 10499.31 10466.12 70.377604\n",
"5693 1599259980 10465.93 10492.41 10465.93 10476.98 25.725507\n",
"5694 1599260040 10475.71 10502.70 10476.58 10500.05 33.257904\n",
"\n",
"[5695 rows x 6 columns]"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "l0t3lUpdoCGW",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 450
},
"outputId": "5a51c79a-8b0e-4774-c408-0b98e160189f"
},
"source": [
"#-------------------------------------------------------------------------------\n",
"# OHLCVを上位時間足にリサンプリング\n",
"#-------------------------------------------------------------------------------\n",
"# [params]\n",
"# df : DateTimeIndexとopen,high,low,close,volume列を含むDataFrame\n",
"# period : リサンプルするタイムフレーム ex) '1S'(秒), '5T'(分), '4H'(時), '1D'(日)\n",
"# [return]\n",
"# DataFrame columns=['unixtime', 'open', 'high', 'low', 'close', 'volume']\n",
"#-------------------------------------------------------------------------------\n",
"df_bitmex_ohlcv_1h = du.Tool.downsample_ohlcv(df_bitmex_ohlcv, period='1H')\n",
"\n",
"display(df_bitmex_ohlcv_1h)"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
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" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>unixtime</th>\n",
" <th>open</th>\n",
" <th>high</th>\n",
" <th>low</th>\n",
" <th>close</th>\n",
" <th>volume</th>\n",
" </tr>\n",
" <tr>\n",
" <th>datetime</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2020-09-01 00:00:00+00:00</th>\n",
" <td>1598918400</td>\n",
" <td>11658.0</td>\n",
" <td>11676.0</td>\n",
" <td>11540.5</td>\n",
" <td>11612.0</td>\n",
" <td>146487313</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 01:00:00+00:00</th>\n",
" <td>1598922000</td>\n",
" <td>11612.0</td>\n",
" <td>11639.5</td>\n",
" <td>11590.0</td>\n",
" <td>11632.5</td>\n",
" <td>50427440</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 02:00:00+00:00</th>\n",
" <td>1598925600</td>\n",
" <td>11632.5</td>\n",
" <td>11646.0</td>\n",
" <td>11615.5</td>\n",
" <td>11634.0</td>\n",
" <td>29863693</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 03:00:00+00:00</th>\n",
" <td>1598929200</td>\n",
" <td>11634.0</td>\n",
" <td>11712.0</td>\n",
" <td>11623.0</td>\n",
" <td>11702.0</td>\n",
" <td>79328840</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 04:00:00+00:00</th>\n",
" <td>1598932800</td>\n",
" <td>11702.0</td>\n",
" <td>11725.5</td>\n",
" <td>11691.0</td>\n",
" <td>11701.5</td>\n",
" <td>61243223</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 19:00:00+00:00</th>\n",
" <td>1599246000</td>\n",
" <td>10521.0</td>\n",
" <td>10599.0</td>\n",
" <td>10479.0</td>\n",
" <td>10580.5</td>\n",
" <td>111885780</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 20:00:00+00:00</th>\n",
" <td>1599249600</td>\n",
" <td>10580.5</td>\n",
" <td>10605.0</td>\n",
" <td>10542.0</td>\n",
" <td>10590.0</td>\n",
" <td>69780831</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 21:00:00+00:00</th>\n",
" <td>1599253200</td>\n",
" <td>10590.0</td>\n",
" <td>10636.0</td>\n",
" <td>10543.0</td>\n",
" <td>10547.0</td>\n",
" <td>41345011</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 22:00:00+00:00</th>\n",
" <td>1599256800</td>\n",
" <td>10547.0</td>\n",
" <td>10575.0</td>\n",
" <td>10450.0</td>\n",
" <td>10467.5</td>\n",
" <td>56204053</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 23:00:00+00:00</th>\n",
" <td>1599260400</td>\n",
" <td>10467.5</td>\n",
" <td>10492.0</td>\n",
" <td>10440.0</td>\n",
" <td>10455.0</td>\n",
" <td>37420194</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>96 rows × 6 columns</p>\n",
"</div>"
],
"text/plain": [
" unixtime open ... close volume\n",
"datetime ... \n",
"2020-09-01 00:00:00+00:00 1598918400 11658.0 ... 11612.0 146487313\n",
"2020-09-01 01:00:00+00:00 1598922000 11612.0 ... 11632.5 50427440\n",
"2020-09-01 02:00:00+00:00 1598925600 11632.5 ... 11634.0 29863693\n",
"2020-09-01 03:00:00+00:00 1598929200 11634.0 ... 11702.0 79328840\n",
"2020-09-01 04:00:00+00:00 1598932800 11702.0 ... 11701.5 61243223\n",
"... ... ... ... ... ...\n",
"2020-09-04 19:00:00+00:00 1599246000 10521.0 ... 10580.5 111885780\n",
"2020-09-04 20:00:00+00:00 1599249600 10580.5 ... 10590.0 69780831\n",
"2020-09-04 21:00:00+00:00 1599253200 10590.0 ... 10547.0 41345011\n",
"2020-09-04 22:00:00+00:00 1599256800 10547.0 ... 10467.5 56204053\n",
"2020-09-04 23:00:00+00:00 1599260400 10467.5 ... 10455.0 37420194\n",
"\n",
"[96 rows x 6 columns]"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "qZntXb840fLN",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"outputId": "c99aa711-ce50-4514-c3d8-962a6e6b04ba"
},
"source": [
"#-------------------------------------------------------------------------------\n",
"# DataFrameの行を指定列の値範囲で絞り込み\n",
"#-------------------------------------------------------------------------------\n",
"# [params]\n",
"# df : column列を含むDataFrame\n",
"# column : 絞り込み判定を行う列名\n",
"# min_value : 絞り込み下限値\n",
"# max_value : 絞り込み上限値\n",
"#-------------------------------------------------------------------------------\n",
"divided_date = datetime.strptime('2020/09/03 09:00:00+0900', '%Y/%m/%d %H:%M:%S%z')\n",
"divided_ut = int(divided_date.timestamp())\n",
"\n",
"df_filtered1 = du.Tool.filter_df(df_bitmex_ohlcv_1h, column='unixtime', min_value=start_ut, max_value=divided_ut-1)\n",
"df_filtered2 = du.Tool.filter_df(df_bitmex_ohlcv_1h, column='unixtime', min_value=divided_ut, max_value=end_ut)\n",
"\n",
"display(df_filtered1)\n",
"display(df_filtered2)"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
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" }\n",
"\n",
" .dataframe thead th {\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>unixtime</th>\n",
" <th>open</th>\n",
" <th>high</th>\n",
" <th>low</th>\n",
" <th>close</th>\n",
" <th>volume</th>\n",
" </tr>\n",
" <tr>\n",
" <th>datetime</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2020-09-01 00:00:00+00:00</th>\n",
" <td>1598918400</td>\n",
" <td>11658.0</td>\n",
" <td>11676.0</td>\n",
" <td>11540.5</td>\n",
" <td>11612.0</td>\n",
" <td>146487313</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 01:00:00+00:00</th>\n",
" <td>1598922000</td>\n",
" <td>11612.0</td>\n",
" <td>11639.5</td>\n",
" <td>11590.0</td>\n",
" <td>11632.5</td>\n",
" <td>50427440</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 02:00:00+00:00</th>\n",
" <td>1598925600</td>\n",
" <td>11632.5</td>\n",
" <td>11646.0</td>\n",
" <td>11615.5</td>\n",
" <td>11634.0</td>\n",
" <td>29863693</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 03:00:00+00:00</th>\n",
" <td>1598929200</td>\n",
" <td>11634.0</td>\n",
" <td>11712.0</td>\n",
" <td>11623.0</td>\n",
" <td>11702.0</td>\n",
" <td>79328840</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 04:00:00+00:00</th>\n",
" <td>1598932800</td>\n",
" <td>11702.0</td>\n",
" <td>11725.5</td>\n",
" <td>11691.0</td>\n",
" <td>11701.5</td>\n",
" <td>61243223</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 05:00:00+00:00</th>\n",
" <td>1598936400</td>\n",
" <td>11701.5</td>\n",
" <td>11810.0</td>\n",
" <td>11695.0</td>\n",
" <td>11804.5</td>\n",
" <td>130499116</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 06:00:00+00:00</th>\n",
" <td>1598940000</td>\n",
" <td>11804.5</td>\n",
" <td>11888.0</td>\n",
" <td>11790.0</td>\n",
" <td>11881.0</td>\n",
" <td>179424996</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 07:00:00+00:00</th>\n",
" <td>1598943600</td>\n",
" <td>11881.0</td>\n",
" <td>11949.0</td>\n",
" <td>11881.0</td>\n",
" <td>11937.5</td>\n",
" <td>134870660</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 08:00:00+00:00</th>\n",
" <td>1598947200</td>\n",
" <td>11937.5</td>\n",
" <td>11956.5</td>\n",
" <td>11890.0</td>\n",
" <td>11931.5</td>\n",
" <td>83831279</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 09:00:00+00:00</th>\n",
" <td>1598950800</td>\n",
" <td>11931.5</td>\n",
" <td>11973.5</td>\n",
" <td>11892.0</td>\n",
" <td>11964.0</td>\n",
" <td>82907238</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 10:00:00+00:00</th>\n",
" <td>1598954400</td>\n",
" <td>11964.0</td>\n",
" <td>11969.0</td>\n",
" <td>11932.0</td>\n",
" <td>11941.0</td>\n",
" <td>41896180</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 11:00:00+00:00</th>\n",
" <td>1598958000</td>\n",
" <td>11941.0</td>\n",
" <td>11941.0</td>\n",
" <td>11873.0</td>\n",
" <td>11896.0</td>\n",
" <td>63505006</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 12:00:00+00:00</th>\n",
" <td>1598961600</td>\n",
" <td>11896.0</td>\n",
" <td>11937.5</td>\n",
" <td>11868.0</td>\n",
" <td>11917.0</td>\n",
" <td>65009012</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 13:00:00+00:00</th>\n",
" <td>1598965200</td>\n",
" <td>11917.0</td>\n",
" <td>11925.0</td>\n",
" <td>11875.0</td>\n",
" <td>11884.5</td>\n",
" <td>55867004</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 14:00:00+00:00</th>\n",
" <td>1598968800</td>\n",
" <td>11884.5</td>\n",
" <td>11910.0</td>\n",
" <td>11820.5</td>\n",
" <td>11910.0</td>\n",
" <td>124728061</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 15:00:00+00:00</th>\n",
" <td>1598972400</td>\n",
" <td>11910.0</td>\n",
" <td>12059.5</td>\n",
" <td>11909.5</td>\n",
" <td>12058.5</td>\n",
" <td>191655875</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 16:00:00+00:00</th>\n",
" <td>1598976000</td>\n",
" <td>12058.5</td>\n",
" <td>12071.0</td>\n",
" <td>12008.0</td>\n",
" <td>12021.0</td>\n",
" <td>90994921</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 17:00:00+00:00</th>\n",
" <td>1598979600</td>\n",
" <td>12021.0</td>\n",
" <td>12034.0</td>\n",
" <td>11967.0</td>\n",
" <td>11988.0</td>\n",
" <td>55304270</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 18:00:00+00:00</th>\n",
" <td>1598983200</td>\n",
" <td>11988.0</td>\n",
" <td>12025.5</td>\n",
" <td>11980.0</td>\n",
" <td>11999.5</td>\n",
" <td>28016949</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 19:00:00+00:00</th>\n",
" <td>1598986800</td>\n",
" <td>11999.5</td>\n",
" <td>12009.0</td>\n",
" <td>11980.0</td>\n",
" <td>11980.5</td>\n",
" <td>23976109</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 20:00:00+00:00</th>\n",
" <td>1598990400</td>\n",
" <td>11980.5</td>\n",
" <td>12038.0</td>\n",
" <td>11967.5</td>\n",
" <td>12027.5</td>\n",
" <td>37885458</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 21:00:00+00:00</th>\n",
" <td>1598994000</td>\n",
" <td>12027.5</td>\n",
" <td>12055.0</td>\n",
" <td>12020.0</td>\n",
" <td>12034.0</td>\n",
" <td>41656455</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 22:00:00+00:00</th>\n",
" <td>1598997600</td>\n",
" <td>12034.0</td>\n",
" <td>12068.0</td>\n",
" <td>11958.0</td>\n",
" <td>11985.0</td>\n",
" <td>76984509</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 23:00:00+00:00</th>\n",
" <td>1599001200</td>\n",
" <td>11985.0</td>\n",
" <td>12027.0</td>\n",
" <td>11860.0</td>\n",
" <td>11937.0</td>\n",
" <td>111380745</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-02 00:00:00+00:00</th>\n",
" <td>1599004800</td>\n",
" <td>11937.0</td>\n",
" <td>11957.5</td>\n",
" <td>11902.0</td>\n",
" <td>11913.0</td>\n",
" <td>84874533</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-02 01:00:00+00:00</th>\n",
" <td>1599008400</td>\n",
" <td>11913.0</td>\n",
" <td>11937.0</td>\n",
" <td>11881.0</td>\n",
" <td>11900.0</td>\n",
" <td>56156788</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-02 02:00:00+00:00</th>\n",
" <td>1599012000</td>\n",
" <td>11900.0</td>\n",
" <td>11919.5</td>\n",
" <td>11871.0</td>\n",
" <td>11871.0</td>\n",
" <td>45315462</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-02 03:00:00+00:00</th>\n",
" <td>1599015600</td>\n",
" <td>11871.0</td>\n",
" <td>11881.5</td>\n",
" <td>11843.0</td>\n",
" <td>11847.0</td>\n",
" <td>66922453</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-02 04:00:00+00:00</th>\n",
" <td>1599019200</td>\n",
" <td>11847.0</td>\n",
" <td>11900.0</td>\n",
" <td>11839.5</td>\n",
" <td>11877.5</td>\n",
" <td>49905902</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-02 05:00:00+00:00</th>\n",
" <td>1599022800</td>\n",
" <td>11877.5</td>\n",
" <td>11912.5</td>\n",
" <td>11870.5</td>\n",
" <td>11874.5</td>\n",
" <td>46808346</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-02 06:00:00+00:00</th>\n",
" <td>1599026400</td>\n",
" <td>11874.5</td>\n",
" <td>11875.0</td>\n",
" <td>11760.5</td>\n",
" <td>11800.0</td>\n",
" <td>170903796</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-02 07:00:00+00:00</th>\n",
" <td>1599030000</td>\n",
" <td>11800.0</td>\n",
" <td>11813.0</td>\n",
" <td>11720.5</td>\n",
" <td>11733.5</td>\n",
" <td>90973417</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-02 08:00:00+00:00</th>\n",
" <td>1599033600</td>\n",
" <td>11733.5</td>\n",
" <td>11751.0</td>\n",
" <td>11681.0</td>\n",
" <td>11718.5</td>\n",
" <td>126152126</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-02 09:00:00+00:00</th>\n",
" <td>1599037200</td>\n",
" <td>11718.5</td>\n",
" <td>11750.5</td>\n",
" <td>11713.0</td>\n",
" <td>11747.0</td>\n",
" <td>45479977</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-02 10:00:00+00:00</th>\n",
" <td>1599040800</td>\n",
" <td>11747.0</td>\n",
" <td>11747.5</td>\n",
" <td>11530.0</td>\n",
" <td>11582.5</td>\n",
" <td>241558337</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-02 11:00:00+00:00</th>\n",
" <td>1599044400</td>\n",
" <td>11582.5</td>\n",
" <td>11582.5</td>\n",
" <td>11165.0</td>\n",
" <td>11409.0</td>\n",
" <td>560435702</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-02 12:00:00+00:00</th>\n",
" <td>1599048000</td>\n",
" <td>11409.0</td>\n",
" <td>11496.5</td>\n",
" <td>11383.5</td>\n",
" <td>11437.0</td>\n",
" <td>143273498</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-02 13:00:00+00:00</th>\n",
" <td>1599051600</td>\n",
" <td>11437.0</td>\n",
" <td>11453.0</td>\n",
" <td>11320.0</td>\n",
" <td>11343.0</td>\n",
" <td>147839203</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-02 14:00:00+00:00</th>\n",
" <td>1599055200</td>\n",
" <td>11343.0</td>\n",
" <td>11367.0</td>\n",
" <td>11214.0</td>\n",
" <td>11248.0</td>\n",
" <td>158294946</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-02 15:00:00+00:00</th>\n",
" <td>1599058800</td>\n",
" <td>11248.0</td>\n",
" <td>11358.0</td>\n",
" <td>11247.0</td>\n",
" <td>11338.0</td>\n",
" <td>110231118</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-02 16:00:00+00:00</th>\n",
" <td>1599062400</td>\n",
" <td>11338.0</td>\n",
" <td>11360.0</td>\n",
" <td>11252.0</td>\n",
" <td>11311.0</td>\n",
" <td>98194648</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-02 17:00:00+00:00</th>\n",
" <td>1599066000</td>\n",
" <td>11311.0</td>\n",
" <td>11365.0</td>\n",
" <td>11296.5</td>\n",
" <td>11359.0</td>\n",
" <td>40512603</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-02 18:00:00+00:00</th>\n",
" <td>1599069600</td>\n",
" <td>11359.0</td>\n",
" <td>11402.5</td>\n",
" <td>11338.0</td>\n",
" <td>11402.0</td>\n",
" <td>41249849</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-02 19:00:00+00:00</th>\n",
" <td>1599073200</td>\n",
" <td>11402.0</td>\n",
" <td>11412.5</td>\n",
" <td>11354.0</td>\n",
" <td>11402.0</td>\n",
" <td>58722051</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-02 20:00:00+00:00</th>\n",
" <td>1599076800</td>\n",
" <td>11402.0</td>\n",
" <td>11402.0</td>\n",
" <td>11317.5</td>\n",
" <td>11370.5</td>\n",
" <td>59544791</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-02 21:00:00+00:00</th>\n",
" <td>1599080400</td>\n",
" <td>11370.5</td>\n",
" <td>11380.0</td>\n",
" <td>11356.0</td>\n",
" <td>11378.0</td>\n",
" <td>24094977</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-02 22:00:00+00:00</th>\n",
" <td>1599084000</td>\n",
" <td>11378.0</td>\n",
" <td>11442.5</td>\n",
" <td>11377.5</td>\n",
" <td>11437.0</td>\n",
" <td>50259086</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-02 23:00:00+00:00</th>\n",
" <td>1599087600</td>\n",
" <td>11437.0</td>\n",
" <td>11437.5</td>\n",
" <td>11393.0</td>\n",
" <td>11398.5</td>\n",
" <td>29682045</td>\n",
" </tr>\n",
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],
"text/plain": [
" unixtime open ... close volume\n",
"datetime ... \n",
"2020-09-01 00:00:00+00:00 1598918400 11658.0 ... 11612.0 146487313\n",
"2020-09-01 01:00:00+00:00 1598922000 11612.0 ... 11632.5 50427440\n",
"2020-09-01 02:00:00+00:00 1598925600 11632.5 ... 11634.0 29863693\n",
"2020-09-01 03:00:00+00:00 1598929200 11634.0 ... 11702.0 79328840\n",
"2020-09-01 04:00:00+00:00 1598932800 11702.0 ... 11701.5 61243223\n",
"2020-09-01 05:00:00+00:00 1598936400 11701.5 ... 11804.5 130499116\n",
"2020-09-01 06:00:00+00:00 1598940000 11804.5 ... 11881.0 179424996\n",
"2020-09-01 07:00:00+00:00 1598943600 11881.0 ... 11937.5 134870660\n",
"2020-09-01 08:00:00+00:00 1598947200 11937.5 ... 11931.5 83831279\n",
"2020-09-01 09:00:00+00:00 1598950800 11931.5 ... 11964.0 82907238\n",
"2020-09-01 10:00:00+00:00 1598954400 11964.0 ... 11941.0 41896180\n",
"2020-09-01 11:00:00+00:00 1598958000 11941.0 ... 11896.0 63505006\n",
"2020-09-01 12:00:00+00:00 1598961600 11896.0 ... 11917.0 65009012\n",
"2020-09-01 13:00:00+00:00 1598965200 11917.0 ... 11884.5 55867004\n",
"2020-09-01 14:00:00+00:00 1598968800 11884.5 ... 11910.0 124728061\n",
"2020-09-01 15:00:00+00:00 1598972400 11910.0 ... 12058.5 191655875\n",
"2020-09-01 16:00:00+00:00 1598976000 12058.5 ... 12021.0 90994921\n",
"2020-09-01 17:00:00+00:00 1598979600 12021.0 ... 11988.0 55304270\n",
"2020-09-01 18:00:00+00:00 1598983200 11988.0 ... 11999.5 28016949\n",
"2020-09-01 19:00:00+00:00 1598986800 11999.5 ... 11980.5 23976109\n",
"2020-09-01 20:00:00+00:00 1598990400 11980.5 ... 12027.5 37885458\n",
"2020-09-01 21:00:00+00:00 1598994000 12027.5 ... 12034.0 41656455\n",
"2020-09-01 22:00:00+00:00 1598997600 12034.0 ... 11985.0 76984509\n",
"2020-09-01 23:00:00+00:00 1599001200 11985.0 ... 11937.0 111380745\n",
"2020-09-02 00:00:00+00:00 1599004800 11937.0 ... 11913.0 84874533\n",
"2020-09-02 01:00:00+00:00 1599008400 11913.0 ... 11900.0 56156788\n",
"2020-09-02 02:00:00+00:00 1599012000 11900.0 ... 11871.0 45315462\n",
"2020-09-02 03:00:00+00:00 1599015600 11871.0 ... 11847.0 66922453\n",
"2020-09-02 04:00:00+00:00 1599019200 11847.0 ... 11877.5 49905902\n",
"2020-09-02 05:00:00+00:00 1599022800 11877.5 ... 11874.5 46808346\n",
"2020-09-02 06:00:00+00:00 1599026400 11874.5 ... 11800.0 170903796\n",
"2020-09-02 07:00:00+00:00 1599030000 11800.0 ... 11733.5 90973417\n",
"2020-09-02 08:00:00+00:00 1599033600 11733.5 ... 11718.5 126152126\n",
"2020-09-02 09:00:00+00:00 1599037200 11718.5 ... 11747.0 45479977\n",
"2020-09-02 10:00:00+00:00 1599040800 11747.0 ... 11582.5 241558337\n",
"2020-09-02 11:00:00+00:00 1599044400 11582.5 ... 11409.0 560435702\n",
"2020-09-02 12:00:00+00:00 1599048000 11409.0 ... 11437.0 143273498\n",
"2020-09-02 13:00:00+00:00 1599051600 11437.0 ... 11343.0 147839203\n",
"2020-09-02 14:00:00+00:00 1599055200 11343.0 ... 11248.0 158294946\n",
"2020-09-02 15:00:00+00:00 1599058800 11248.0 ... 11338.0 110231118\n",
"2020-09-02 16:00:00+00:00 1599062400 11338.0 ... 11311.0 98194648\n",
"2020-09-02 17:00:00+00:00 1599066000 11311.0 ... 11359.0 40512603\n",
"2020-09-02 18:00:00+00:00 1599069600 11359.0 ... 11402.0 41249849\n",
"2020-09-02 19:00:00+00:00 1599073200 11402.0 ... 11402.0 58722051\n",
"2020-09-02 20:00:00+00:00 1599076800 11402.0 ... 11370.5 59544791\n",
"2020-09-02 21:00:00+00:00 1599080400 11370.5 ... 11378.0 24094977\n",
"2020-09-02 22:00:00+00:00 1599084000 11378.0 ... 11437.0 50259086\n",
"2020-09-02 23:00:00+00:00 1599087600 11437.0 ... 11398.5 29682045\n",
"\n",
"[48 rows x 6 columns]"
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"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>unixtime</th>\n",
" <th>open</th>\n",
" <th>high</th>\n",
" <th>low</th>\n",
" <th>close</th>\n",
" <th>volume</th>\n",
" </tr>\n",
" <tr>\n",
" <th>datetime</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2020-09-03 00:00:00+00:00</th>\n",
" <td>1599091200</td>\n",
" <td>11398.5</td>\n",
" <td>11447.0</td>\n",
" <td>11378.0</td>\n",
" <td>11423.5</td>\n",
" <td>35167747</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-03 01:00:00+00:00</th>\n",
" <td>1599094800</td>\n",
" <td>11423.5</td>\n",
" <td>11437.0</td>\n",
" <td>11390.0</td>\n",
" <td>11436.5</td>\n",
" <td>22916932</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-03 02:00:00+00:00</th>\n",
" <td>1599098400</td>\n",
" <td>11436.5</td>\n",
" <td>11444.0</td>\n",
" <td>11410.0</td>\n",
" <td>11434.0</td>\n",
" <td>21863921</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-03 03:00:00+00:00</th>\n",
" <td>1599102000</td>\n",
" <td>11434.0</td>\n",
" <td>11442.5</td>\n",
" <td>11348.0</td>\n",
" <td>11364.5</td>\n",
" <td>47295024</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-03 04:00:00+00:00</th>\n",
" <td>1599105600</td>\n",
" <td>11364.5</td>\n",
" <td>11387.5</td>\n",
" <td>11279.5</td>\n",
" <td>11287.5</td>\n",
" <td>60063228</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-03 05:00:00+00:00</th>\n",
" <td>1599109200</td>\n",
" <td>11287.5</td>\n",
" <td>11350.0</td>\n",
" <td>11269.0</td>\n",
" <td>11292.0</td>\n",
" <td>68025443</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-03 06:00:00+00:00</th>\n",
" <td>1599112800</td>\n",
" <td>11292.0</td>\n",
" <td>11327.5</td>\n",
" <td>11261.0</td>\n",
" <td>11294.0</td>\n",
" <td>77589133</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-03 07:00:00+00:00</th>\n",
" <td>1599116400</td>\n",
" <td>11294.0</td>\n",
" <td>11438.0</td>\n",
" <td>11260.0</td>\n",
" <td>11414.5</td>\n",
" <td>96769077</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-03 08:00:00+00:00</th>\n",
" <td>1599120000</td>\n",
" <td>11414.5</td>\n",
" <td>11473.0</td>\n",
" <td>11362.5</td>\n",
" <td>11400.0</td>\n",
" <td>110657992</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-03 09:00:00+00:00</th>\n",
" <td>1599123600</td>\n",
" <td>11400.0</td>\n",
" <td>11411.0</td>\n",
" <td>11360.0</td>\n",
" <td>11363.0</td>\n",
" <td>41879703</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-03 10:00:00+00:00</th>\n",
" <td>1599127200</td>\n",
" <td>11363.0</td>\n",
" <td>11363.5</td>\n",
" <td>11222.0</td>\n",
" <td>11265.0</td>\n",
" <td>111907903</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-03 11:00:00+00:00</th>\n",
" <td>1599130800</td>\n",
" <td>11265.0</td>\n",
" <td>11302.0</td>\n",
" <td>11190.0</td>\n",
" <td>11225.5</td>\n",
" <td>171467766</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-03 12:00:00+00:00</th>\n",
" <td>1599134400</td>\n",
" <td>11225.5</td>\n",
" <td>11255.0</td>\n",
" <td>10625.5</td>\n",
" <td>10811.0</td>\n",
" <td>809626935</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-03 13:00:00+00:00</th>\n",
" <td>1599138000</td>\n",
" <td>10811.0</td>\n",
" <td>10917.0</td>\n",
" <td>10787.0</td>\n",
" <td>10915.0</td>\n",
" <td>129503868</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-03 14:00:00+00:00</th>\n",
" <td>1599141600</td>\n",
" <td>10915.0</td>\n",
" <td>10919.5</td>\n",
" <td>10822.0</td>\n",
" <td>10846.5</td>\n",
" <td>101114710</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-03 15:00:00+00:00</th>\n",
" <td>1599145200</td>\n",
" <td>10846.5</td>\n",
" <td>10846.5</td>\n",
" <td>10450.0</td>\n",
" <td>10672.5</td>\n",
" <td>480577808</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-03 16:00:00+00:00</th>\n",
" <td>1599148800</td>\n",
" <td>10672.5</td>\n",
" <td>10733.0</td>\n",
" <td>10560.5</td>\n",
" <td>10569.5</td>\n",
" <td>186827814</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-03 17:00:00+00:00</th>\n",
" <td>1599152400</td>\n",
" <td>10569.5</td>\n",
" <td>10767.0</td>\n",
" <td>10569.5</td>\n",
" <td>10695.5</td>\n",
" <td>121655544</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-03 18:00:00+00:00</th>\n",
" <td>1599156000</td>\n",
" <td>10695.5</td>\n",
" <td>10725.5</td>\n",
" <td>10630.0</td>\n",
" <td>10647.5</td>\n",
" <td>52220475</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-03 19:00:00+00:00</th>\n",
" <td>1599159600</td>\n",
" <td>10647.5</td>\n",
" <td>10705.5</td>\n",
" <td>10599.0</td>\n",
" <td>10680.0</td>\n",
" <td>49747830</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-03 20:00:00+00:00</th>\n",
" <td>1599163200</td>\n",
" <td>10680.0</td>\n",
" <td>10786.0</td>\n",
" <td>10676.0</td>\n",
" <td>10770.0</td>\n",
" <td>55878445</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-03 21:00:00+00:00</th>\n",
" <td>1599166800</td>\n",
" <td>10770.0</td>\n",
" <td>10784.0</td>\n",
" <td>10698.0</td>\n",
" <td>10729.0</td>\n",
" <td>33125192</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-03 22:00:00+00:00</th>\n",
" <td>1599170400</td>\n",
" <td>10729.0</td>\n",
" <td>10747.0</td>\n",
" <td>10650.0</td>\n",
" <td>10665.5</td>\n",
" <td>43643283</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-03 23:00:00+00:00</th>\n",
" <td>1599174000</td>\n",
" <td>10665.5</td>\n",
" <td>10671.5</td>\n",
" <td>9922.0</td>\n",
" <td>10144.0</td>\n",
" <td>653185338</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 00:00:00+00:00</th>\n",
" <td>1599177600</td>\n",
" <td>10144.0</td>\n",
" <td>10341.0</td>\n",
" <td>10086.5</td>\n",
" <td>10307.5</td>\n",
" <td>181953551</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 01:00:00+00:00</th>\n",
" <td>1599181200</td>\n",
" <td>10307.5</td>\n",
" <td>10313.5</td>\n",
" <td>10235.5</td>\n",
" <td>10262.0</td>\n",
" <td>57276752</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 02:00:00+00:00</th>\n",
" <td>1599184800</td>\n",
" <td>10262.0</td>\n",
" <td>10282.5</td>\n",
" <td>10175.0</td>\n",
" <td>10262.5</td>\n",
" <td>85363948</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 03:00:00+00:00</th>\n",
" <td>1599188400</td>\n",
" <td>10262.5</td>\n",
" <td>10290.5</td>\n",
" <td>10248.5</td>\n",
" <td>10267.5</td>\n",
" <td>34986791</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 04:00:00+00:00</th>\n",
" <td>1599192000</td>\n",
" <td>10267.5</td>\n",
" <td>10334.0</td>\n",
" <td>10232.5</td>\n",
" <td>10288.5</td>\n",
" <td>59655147</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 05:00:00+00:00</th>\n",
" <td>1599195600</td>\n",
" <td>10288.5</td>\n",
" <td>10302.5</td>\n",
" <td>10240.0</td>\n",
" <td>10293.0</td>\n",
" <td>32414658</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 06:00:00+00:00</th>\n",
" <td>1599199200</td>\n",
" <td>10293.0</td>\n",
" <td>10305.0</td>\n",
" <td>10236.0</td>\n",
" <td>10236.0</td>\n",
" <td>35527671</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 07:00:00+00:00</th>\n",
" <td>1599202800</td>\n",
" <td>10236.0</td>\n",
" <td>10334.0</td>\n",
" <td>10104.0</td>\n",
" <td>10308.0</td>\n",
" <td>142442103</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 08:00:00+00:00</th>\n",
" <td>1599206400</td>\n",
" <td>10308.0</td>\n",
" <td>10440.0</td>\n",
" <td>10307.5</td>\n",
" <td>10422.0</td>\n",
" <td>123949996</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 09:00:00+00:00</th>\n",
" <td>1599210000</td>\n",
" <td>10422.0</td>\n",
" <td>10534.0</td>\n",
" <td>10397.0</td>\n",
" <td>10528.0</td>\n",
" <td>118823160</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 10:00:00+00:00</th>\n",
" <td>1599213600</td>\n",
" <td>10528.0</td>\n",
" <td>10537.0</td>\n",
" <td>10472.5</td>\n",
" <td>10476.5</td>\n",
" <td>91629988</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 11:00:00+00:00</th>\n",
" <td>1599217200</td>\n",
" <td>10476.5</td>\n",
" <td>10487.5</td>\n",
" <td>10370.5</td>\n",
" <td>10436.0</td>\n",
" <td>105392760</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 12:00:00+00:00</th>\n",
" <td>1599220800</td>\n",
" <td>10436.0</td>\n",
" <td>10475.0</td>\n",
" <td>10393.0</td>\n",
" <td>10467.0</td>\n",
" <td>71084674</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 13:00:00+00:00</th>\n",
" <td>1599224400</td>\n",
" <td>10467.0</td>\n",
" <td>10506.5</td>\n",
" <td>10376.0</td>\n",
" <td>10378.0</td>\n",
" <td>98369762</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 14:00:00+00:00</th>\n",
" <td>1599228000</td>\n",
" <td>10378.0</td>\n",
" <td>10414.0</td>\n",
" <td>9880.0</td>\n",
" <td>10382.5</td>\n",
" <td>471965990</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 15:00:00+00:00</th>\n",
" <td>1599231600</td>\n",
" <td>10382.5</td>\n",
" <td>10459.5</td>\n",
" <td>10165.0</td>\n",
" <td>10432.0</td>\n",
" <td>217385889</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 16:00:00+00:00</th>\n",
" <td>1599235200</td>\n",
" <td>10432.0</td>\n",
" <td>10477.5</td>\n",
" <td>10319.0</td>\n",
" <td>10444.5</td>\n",
" <td>114461404</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 17:00:00+00:00</th>\n",
" <td>1599238800</td>\n",
" <td>10444.5</td>\n",
" <td>10452.5</td>\n",
" <td>10386.0</td>\n",
" <td>10419.0</td>\n",
" <td>49660778</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 18:00:00+00:00</th>\n",
" <td>1599242400</td>\n",
" <td>10419.0</td>\n",
" <td>10521.0</td>\n",
" <td>10352.0</td>\n",
" <td>10521.0</td>\n",
" <td>87123011</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 19:00:00+00:00</th>\n",
" <td>1599246000</td>\n",
" <td>10521.0</td>\n",
" <td>10599.0</td>\n",
" <td>10479.0</td>\n",
" <td>10580.5</td>\n",
" <td>111885780</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 20:00:00+00:00</th>\n",
" <td>1599249600</td>\n",
" <td>10580.5</td>\n",
" <td>10605.0</td>\n",
" <td>10542.0</td>\n",
" <td>10590.0</td>\n",
" <td>69780831</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 21:00:00+00:00</th>\n",
" <td>1599253200</td>\n",
" <td>10590.0</td>\n",
" <td>10636.0</td>\n",
" <td>10543.0</td>\n",
" <td>10547.0</td>\n",
" <td>41345011</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 22:00:00+00:00</th>\n",
" <td>1599256800</td>\n",
" <td>10547.0</td>\n",
" <td>10575.0</td>\n",
" <td>10450.0</td>\n",
" <td>10467.5</td>\n",
" <td>56204053</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-04 23:00:00+00:00</th>\n",
" <td>1599260400</td>\n",
" <td>10467.5</td>\n",
" <td>10492.0</td>\n",
" <td>10440.0</td>\n",
" <td>10455.0</td>\n",
" <td>37420194</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" unixtime open ... close volume\n",
"datetime ... \n",
"2020-09-03 00:00:00+00:00 1599091200 11398.5 ... 11423.5 35167747\n",
"2020-09-03 01:00:00+00:00 1599094800 11423.5 ... 11436.5 22916932\n",
"2020-09-03 02:00:00+00:00 1599098400 11436.5 ... 11434.0 21863921\n",
"2020-09-03 03:00:00+00:00 1599102000 11434.0 ... 11364.5 47295024\n",
"2020-09-03 04:00:00+00:00 1599105600 11364.5 ... 11287.5 60063228\n",
"2020-09-03 05:00:00+00:00 1599109200 11287.5 ... 11292.0 68025443\n",
"2020-09-03 06:00:00+00:00 1599112800 11292.0 ... 11294.0 77589133\n",
"2020-09-03 07:00:00+00:00 1599116400 11294.0 ... 11414.5 96769077\n",
"2020-09-03 08:00:00+00:00 1599120000 11414.5 ... 11400.0 110657992\n",
"2020-09-03 09:00:00+00:00 1599123600 11400.0 ... 11363.0 41879703\n",
"2020-09-03 10:00:00+00:00 1599127200 11363.0 ... 11265.0 111907903\n",
"2020-09-03 11:00:00+00:00 1599130800 11265.0 ... 11225.5 171467766\n",
"2020-09-03 12:00:00+00:00 1599134400 11225.5 ... 10811.0 809626935\n",
"2020-09-03 13:00:00+00:00 1599138000 10811.0 ... 10915.0 129503868\n",
"2020-09-03 14:00:00+00:00 1599141600 10915.0 ... 10846.5 101114710\n",
"2020-09-03 15:00:00+00:00 1599145200 10846.5 ... 10672.5 480577808\n",
"2020-09-03 16:00:00+00:00 1599148800 10672.5 ... 10569.5 186827814\n",
"2020-09-03 17:00:00+00:00 1599152400 10569.5 ... 10695.5 121655544\n",
"2020-09-03 18:00:00+00:00 1599156000 10695.5 ... 10647.5 52220475\n",
"2020-09-03 19:00:00+00:00 1599159600 10647.5 ... 10680.0 49747830\n",
"2020-09-03 20:00:00+00:00 1599163200 10680.0 ... 10770.0 55878445\n",
"2020-09-03 21:00:00+00:00 1599166800 10770.0 ... 10729.0 33125192\n",
"2020-09-03 22:00:00+00:00 1599170400 10729.0 ... 10665.5 43643283\n",
"2020-09-03 23:00:00+00:00 1599174000 10665.5 ... 10144.0 653185338\n",
"2020-09-04 00:00:00+00:00 1599177600 10144.0 ... 10307.5 181953551\n",
"2020-09-04 01:00:00+00:00 1599181200 10307.5 ... 10262.0 57276752\n",
"2020-09-04 02:00:00+00:00 1599184800 10262.0 ... 10262.5 85363948\n",
"2020-09-04 03:00:00+00:00 1599188400 10262.5 ... 10267.5 34986791\n",
"2020-09-04 04:00:00+00:00 1599192000 10267.5 ... 10288.5 59655147\n",
"2020-09-04 05:00:00+00:00 1599195600 10288.5 ... 10293.0 32414658\n",
"2020-09-04 06:00:00+00:00 1599199200 10293.0 ... 10236.0 35527671\n",
"2020-09-04 07:00:00+00:00 1599202800 10236.0 ... 10308.0 142442103\n",
"2020-09-04 08:00:00+00:00 1599206400 10308.0 ... 10422.0 123949996\n",
"2020-09-04 09:00:00+00:00 1599210000 10422.0 ... 10528.0 118823160\n",
"2020-09-04 10:00:00+00:00 1599213600 10528.0 ... 10476.5 91629988\n",
"2020-09-04 11:00:00+00:00 1599217200 10476.5 ... 10436.0 105392760\n",
"2020-09-04 12:00:00+00:00 1599220800 10436.0 ... 10467.0 71084674\n",
"2020-09-04 13:00:00+00:00 1599224400 10467.0 ... 10378.0 98369762\n",
"2020-09-04 14:00:00+00:00 1599228000 10378.0 ... 10382.5 471965990\n",
"2020-09-04 15:00:00+00:00 1599231600 10382.5 ... 10432.0 217385889\n",
"2020-09-04 16:00:00+00:00 1599235200 10432.0 ... 10444.5 114461404\n",
"2020-09-04 17:00:00+00:00 1599238800 10444.5 ... 10419.0 49660778\n",
"2020-09-04 18:00:00+00:00 1599242400 10419.0 ... 10521.0 87123011\n",
"2020-09-04 19:00:00+00:00 1599246000 10521.0 ... 10580.5 111885780\n",
"2020-09-04 20:00:00+00:00 1599249600 10580.5 ... 10590.0 69780831\n",
"2020-09-04 21:00:00+00:00 1599253200 10590.0 ... 10547.0 41345011\n",
"2020-09-04 22:00:00+00:00 1599256800 10547.0 ... 10467.5 56204053\n",
"2020-09-04 23:00:00+00:00 1599260400 10467.5 ... 10455.0 37420194\n",
"\n",
"[48 rows x 6 columns]"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "Z7ugwafn0ink",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 419
},
"outputId": "f3345b4a-5c2a-43a6-b869-4811419a074d"
},
"source": [
"#-------------------------------------------------------------------------------\n",
"# DataFrameを結合\n",
"#-------------------------------------------------------------------------------\n",
"# [params]\n",
"# concat_dfs : 結合するDataFrameリスト\n",
"# sort_column : 結合後にソートする列名\n",
"#-------------------------------------------------------------------------------\n",
"df_concat = du.Tool.concat_df([df_filtered1, df_filtered2], sort_column='unixtime')\n",
"\n",
"display(df_concat)"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>unixtime</th>\n",
" <th>open</th>\n",
" <th>high</th>\n",
" <th>low</th>\n",
" <th>close</th>\n",
" <th>volume</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1598918400</td>\n",
" <td>11658.0</td>\n",
" <td>11676.0</td>\n",
" <td>11540.5</td>\n",
" <td>11612.0</td>\n",
" <td>146487313</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1598922000</td>\n",
" <td>11612.0</td>\n",
" <td>11639.5</td>\n",
" <td>11590.0</td>\n",
" <td>11632.5</td>\n",
" <td>50427440</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>1598925600</td>\n",
" <td>11632.5</td>\n",
" <td>11646.0</td>\n",
" <td>11615.5</td>\n",
" <td>11634.0</td>\n",
" <td>29863693</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>1598929200</td>\n",
" <td>11634.0</td>\n",
" <td>11712.0</td>\n",
" <td>11623.0</td>\n",
" <td>11702.0</td>\n",
" <td>79328840</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>1598932800</td>\n",
" <td>11702.0</td>\n",
" <td>11725.5</td>\n",
" <td>11691.0</td>\n",
" <td>11701.5</td>\n",
" <td>61243223</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>91</th>\n",
" <td>1599246000</td>\n",
" <td>10521.0</td>\n",
" <td>10599.0</td>\n",
" <td>10479.0</td>\n",
" <td>10580.5</td>\n",
" <td>111885780</td>\n",
" </tr>\n",
" <tr>\n",
" <th>92</th>\n",
" <td>1599249600</td>\n",
" <td>10580.5</td>\n",
" <td>10605.0</td>\n",
" <td>10542.0</td>\n",
" <td>10590.0</td>\n",
" <td>69780831</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93</th>\n",
" <td>1599253200</td>\n",
" <td>10590.0</td>\n",
" <td>10636.0</td>\n",
" <td>10543.0</td>\n",
" <td>10547.0</td>\n",
" <td>41345011</td>\n",
" </tr>\n",
" <tr>\n",
" <th>94</th>\n",
" <td>1599256800</td>\n",
" <td>10547.0</td>\n",
" <td>10575.0</td>\n",
" <td>10450.0</td>\n",
" <td>10467.5</td>\n",
" <td>56204053</td>\n",
" </tr>\n",
" <tr>\n",
" <th>95</th>\n",
" <td>1599260400</td>\n",
" <td>10467.5</td>\n",
" <td>10492.0</td>\n",
" <td>10440.0</td>\n",
" <td>10455.0</td>\n",
" <td>37420194</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>96 rows × 6 columns</p>\n",
"</div>"
],
"text/plain": [
" unixtime open high low close volume\n",
"0 1598918400 11658.0 11676.0 11540.5 11612.0 146487313\n",
"1 1598922000 11612.0 11639.5 11590.0 11632.5 50427440\n",
"2 1598925600 11632.5 11646.0 11615.5 11634.0 29863693\n",
"3 1598929200 11634.0 11712.0 11623.0 11702.0 79328840\n",
"4 1598932800 11702.0 11725.5 11691.0 11701.5 61243223\n",
".. ... ... ... ... ... ...\n",
"91 1599246000 10521.0 10599.0 10479.0 10580.5 111885780\n",
"92 1599249600 10580.5 10605.0 10542.0 10590.0 69780831\n",
"93 1599253200 10590.0 10636.0 10543.0 10547.0 41345011\n",
"94 1599256800 10547.0 10575.0 10450.0 10467.5 56204053\n",
"95 1599260400 10467.5 10492.0 10440.0 10455.0 37420194\n",
"\n",
"[96 rows x 6 columns]"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "mGBq9IiwuS-u",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 700
},
"outputId": "38a03c3e-b25f-41fe-ed0d-a6671edbfda9"
},
"source": [
"#---------------------------------------------------------------------------\n",
"# 複数DataFrameを外部結合\n",
"#---------------------------------------------------------------------------\n",
"# [params]\n",
"# dfs : 結合するDataFrameリスト\n",
"# on_column : key列名\n",
"# join_column : 結合する列名\n",
"# fillna : 欠損値補間\n",
"# * None:しない\n",
"# * 数値 : 指定値で補間\n",
"# * 'ffill' : 前の値で補間\n",
"# * 'bfill' : 後の値で補間\n",
"# * 'linear' : 前後の値で線形補間\n",
"# sort_index : 結合したDataFrameをindexでソート(None:しない, True:昇順, False:降順)\n",
"# is_summary : 結合した列を合計(True:合計列のみ, False:各結合列)\n",
"# [return]\n",
"# DataFrame\n",
"#---------------------------------------------------------------------------\n",
"count = 10\n",
"df1 = pd.DataFrame({ 'no': range(0, count*2, 2), 'value': [random.randint(-1000, 1000) for i in range(count)], })\n",
"df2 = pd.DataFrame({ 'no': range(0, count*3, 3), 'value': [random.randint(-1000, 1000) for i in range(count)], })\n",
"df3 = pd.DataFrame({ 'no': range(0, count*4, 4), 'value': [random.randint(-1000, 1000) for i in range(count)], })\n",
"\n",
"dfs = [df1, df2, df3]\n",
"df_joined = du.Tool.outer_join_dfs(dfs, on_column='no', join_column='value', fillna=0, sort_index=True, is_summary=False)\n",
"\n",
"display(df_joined)"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>value_0</th>\n",
" <th>value_1</th>\n",
" <th>value_2</th>\n",
" </tr>\n",
" <tr>\n",
" <th>no</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>605.0</td>\n",
" <td>-236.0</td>\n",
" <td>732.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>733.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>0.0</td>\n",
" <td>-179.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>650.0</td>\n",
" <td>0.0</td>\n",
" <td>480.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>460.0</td>\n",
" <td>279.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>-673.0</td>\n",
" <td>0.0</td>\n",
" <td>-512.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>0.0</td>\n",
" <td>-20.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>160.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>-25.0</td>\n",
" <td>-205.0</td>\n",
" <td>760.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>707.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>0.0</td>\n",
" <td>-626.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>298.0</td>\n",
" <td>0.0</td>\n",
" <td>-607.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>736.0</td>\n",
" <td>-191.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>281.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>0.0</td>\n",
" <td>351.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>0.0</td>\n",
" <td>296.0</td>\n",
" <td>-46.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>0.0</td>\n",
" <td>-554.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>153.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>32</th>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>-148.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>36</th>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>-40.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" value_0 value_1 value_2\n",
"no \n",
"0 605.0 -236.0 732.0\n",
"2 733.0 0.0 0.0\n",
"3 0.0 -179.0 0.0\n",
"4 650.0 0.0 480.0\n",
"6 460.0 279.0 0.0\n",
"8 -673.0 0.0 -512.0\n",
"9 0.0 -20.0 0.0\n",
"10 160.0 0.0 0.0\n",
"12 -25.0 -205.0 760.0\n",
"14 707.0 0.0 0.0\n",
"15 0.0 -626.0 0.0\n",
"16 298.0 0.0 -607.0\n",
"18 736.0 -191.0 0.0\n",
"20 0.0 0.0 281.0\n",
"21 0.0 351.0 0.0\n",
"24 0.0 296.0 -46.0\n",
"27 0.0 -554.0 0.0\n",
"28 0.0 0.0 153.0\n",
"32 0.0 0.0 -148.0\n",
"36 0.0 0.0 -40.0"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "aa1jBQe_0VYm"
},
"source": [
"## 4. デバッグ出力"
]
},
{
"cell_type": "code",
"metadata": {
"id": "aLndnEEO0P3u"
},
"source": [
"#---------------------------------------------------------------------------\n",
"# デバッグ用 オブジェクト整形出力\n",
"#---------------------------------------------------------------------------\n",
"# [params]\n",
"# data : 表示するオブジェクト (int, float, str, list, dict, DataFrame, ndarray etc...)\n",
"# indent : 配列, リスト要素などを表示するインデント (str)\n",
"# print_limit : 配列, リストなどの表示上限数を指定 (0:全件表示)\n",
"# print_type : オブジェクトの型情報を出力するか (bool)\n",
"# print_len : 配列, リストなどの長さを出力するか (bool)\n",
"#---------------------------------------------------------------------------\n",
"du.Tool.debug_print(df_bitmex_ohlcv_1h, print_limit=5, print_type=False, print_len=True)"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "C9iTEU8p0ggf"
},
"source": [
"### 4.1 変数出力(int, float, str etc.)"
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "phu5JAAl0rEw",
"outputId": "09926f9b-a38d-4de8-bd37-863e01465215"
},
"source": [
"int_val = 1\n",
"du.Tool.debug_print(int_val)\n",
"\n",
"float_val = 0.5\n",
"du.Tool.debug_print(float_val)\n",
"\n",
"str_val = 'value'\n",
"du.Tool.debug_print(str_val)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"int_val = 1\n",
"float_val = 0.5\n",
"str_val = 'value'\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "Cv0aK9S_0wN_"
},
"source": [
"### 4.2 list出力"
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "RMo54AxF0u4u",
"outputId": "9f0929a9-1d3d-411a-d635-19bd4f820ca7"
},
"source": [
"lst_sample = [1, 2, 3, 4, 5]\n",
"du.Tool.debug_print(lst_sample, print_limit=3)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"lst_sample = \n",
"[\n",
" 1,\n",
" 2,\n",
" 3,\n",
" ...\n",
"], (len = 5)\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "DtPDwgh11hMv"
},
"source": [
"### 4.3 dict出力"
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "YwJ5mQ3P1Qqw",
"outputId": "1e3e254e-85be-4952-e5ed-872cadae2dbf"
},
"source": [
"dic_sample = {'int_val': 123, 'str_val': 'test', 'date': datetime.now()}\n",
"du.Tool.debug_print(dic_sample)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"dic_sample = \n",
"{\n",
" 'int_val' : 123,\n",
" 'str_val' : 'test',\n",
" 'date' : datetime.datetime(2021, 3, 8, 7, 55, 3, 829626),\n",
"},\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "4gjWdiFr2Yr-"
},
"source": [
"### 4.4 json出力"
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "irKkyMC62cpL",
"outputId": "97d761d2-a467-4845-91d5-645074eca4e3"
},
"source": [
"import requests\n",
"import json\n",
"import traceback\n",
"\n",
"symbol='BTCUSD'\n",
"period='5min'\n",
"url = 'https://api.bybit.com/v2/public/open-interest'\n",
"params = {\n",
" 'symbol':symbol,\n",
" 'period':period,\n",
" 'limit':200,\n",
"}\n",
"\n",
"res = requests.get(url, params, timeout=10)\n",
"result = res.json()\n",
"du.Tool.debug_print(result, print_limit=3)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"result = \n",
"{\n",
" 'ret_code' : 0,\n",
" 'ret_msg' : 'OK',\n",
" 'ext_code' : '',\n",
" 'ext_info' : '',\n",
" 'result' : \n",
" [\n",
" {\n",
" 'open_interest' : 2001029972,\n",
" 'timestamp' : 1615192200,\n",
" 'symbol' : 'BTCUSD',\n",
" },\n",
" {\n",
" 'open_interest' : 1995768024,\n",
" 'timestamp' : 1615191900,\n",
" 'symbol' : 'BTCUSD',\n",
" },\n",
" {\n",
" 'open_interest' : 1993416658,\n",
" 'timestamp' : 1615191600,\n",
" 'symbol' : 'BTCUSD',\n",
" },\n",
" ...\n",
" ], (len = 200)\n",
" 'time_now' : '1615192387.238645',\n",
"},\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "9WzM_fLk2U7G"
},
"source": [
"### 4.5 DataFrame出力"
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "McK7AjWB24ju",
"outputId": "fdf7b2ed-5a2a-41cf-ba05-c9ec66157484"
},
"source": [
"du.Tool.debug_print(df_bybit_trades, print_limit=5)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"df_bybit_trades = \n",
" unixtime side size price\n",
"0 1.598918e+09 Sell 7000 11659.5\n",
"1 1.598918e+09 Buy 40 11660.0\n",
"2 1.598918e+09 Buy 1 11660.0\n",
"3 1.598918e+09 Sell 50 11659.5\n",
"4 1.598918e+09 Sell 210 11659.5\n",
"...\n",
"(, table = row:1293141 * col:4)\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "xDQ-LZe72OIg"
},
"source": [
"### 4.6 Series/ndarray出力"
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "BDzl8uzC2Arw",
"outputId": "2ea54329-856f-4fc1-bcf3-bc72c4734908"
},
"source": [
"sr_unixtime = df_bybit_trades.unixtime\n",
"du.Tool.debug_print(sr_unixtime, print_limit=5, print_type=True)\n",
"\n",
"print()\n",
"\n",
"nd_unixtime = df_bybit_trades.unixtime.values\n",
"du.Tool.debug_print(nd_unixtime, print_limit=5, print_type=True)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"sr_unixtime = \n",
"0 1.598918e+09\n",
"1 1.598918e+09\n",
"2 1.598918e+09\n",
"3 1.598918e+09\n",
"4 1.598918e+09\n",
"Name: unixtime, dtype: float64\n",
"...\n",
" (type = <class 'pandas.core.series.Series'>, len = 1293141)\n",
"\n",
"nd_unixtime = \n",
"array([1.5989184e+09, 1.5989184e+09, 1.5989184e+09, 1.5989184e+09,\n",
" 1.5989184e+09])\n",
"...\n",
" (type = <class 'numpy.ndarray'>, len = 1293141)\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "nq7NfrcODNXF"
},
"source": [
"## 5. 指定値切り捨て/切り上げ"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "QzVqR6CTFhes"
},
"source": [
"### 5.1 値切り捨て/切り上げ"
]
},
{
"cell_type": "code",
"metadata": {
"id": "ClzG7y-KDL-e",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "7e87c1f6-6b94-4d99-d568-b87f649dc20f"
},
"source": [
"value = 22\n",
"print(f'value = {value}')\n",
"\n",
"#---------------------------------------------------------------------------\n",
"# 指定値切り捨て\n",
"#---------------------------------------------------------------------------\n",
"# [params]\n",
"# value : 切り捨てするオブジェクト (int, float, list, ndarray, Series, etc.)\n",
"# round_base : 切り捨てする基準値 (int)\n",
"# [return]\n",
"# valueを切り捨てしたオブジェクト (エラーの場合はNoneを返す)\n",
"#---------------------------------------------------------------------------\n",
"ret = du.Tool.round_down(value, round_base=5)\n",
"print(f'dound_down = {ret}')\n",
"\n",
"#---------------------------------------------------------------------------\n",
"# 指定値切り上げ\n",
"#---------------------------------------------------------------------------\n",
"# [params]\n",
"# value : 切り上げするオブジェクト (int, float, list, ndarray, Series, etc.)\n",
"# round_base : 切り上げする基準値 (int)\n",
"# [return]\n",
"# valueを切り上げしたオブジェクト (エラーの場合はNoneを返す)\n",
"#---------------------------------------------------------------------------\n",
"ret = du.Tool.round_up(value, round_base=10)\n",
"print(f'dound_up = {ret}')"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"value = 22\n",
"dound_down = 20\n",
"dound_up = 30\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "wWkq3_EUFSKV"
},
"source": [
"### 5.1 list切り捨て/切り上げ"
]
},
{
"cell_type": "code",
"metadata": {
"id": "4nyA0j25EPOv",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "a0497ebc-c6bb-4c31-c8a5-f39bbb14e99d"
},
"source": [
"lst_value = [1, 5, 10, 18, 1.5 ,20.58, 123, 54321, 0.5, 55.5, 33.0]\n",
"print(f'lst_value = {lst_value}')\n",
"\n",
"lst_ret = du.Tool.round_down(lst_value, 5)\n",
"print(f'round_down = {lst_ret}')\n",
"\n",
"lst_ret = du.Tool.round_up(lst_value, 10)\n",
"print(f'round_up = {lst_ret}')"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"lst_value = [1, 5, 10, 18, 1.5, 20.58, 123, 54321, 0.5, 55.5, 33.0]\n",
"round_down = [0, 5, 10, 15, 0, 20, 120, 54320, 0, 55, 30]\n",
"round_up = [10, 10, 20, 20, 10, 30, 130, 54330, 10, 60, 40]\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "C0h1KAlhFttM"
},
"source": [
"### 5.2 ndarray切り捨て/切り上げ"
]
},
{
"cell_type": "code",
"metadata": {
"id": "co1hKI8mFFPj",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "58807499-2099-4bda-80ca-8018b258ab95"
},
"source": [
"nd_value = np.array(lst_value)\n",
"print(f'nd_value = \\n', nd_value)\n",
"\n",
"nd_ret = du.Tool.round_down(nd_value, 5)\n",
"print(f'round_down = \\n', nd_ret)\n",
"\n",
"nd_ret = du.Tool.round_up(nd_value, 10)\n",
"print(f'round_up = \\n', nd_ret)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"nd_value = \n",
" [1.0000e+00 5.0000e+00 1.0000e+01 1.8000e+01 1.5000e+00 2.0580e+01\n",
" 1.2300e+02 5.4321e+04 5.0000e-01 5.5500e+01 3.3000e+01]\n",
"round_down = \n",
" [0 5 10 15 0 20 120 54320 0 55 30]\n",
"round_up = \n",
" [10 10 20 20 10 30 130 54330 10 60 40]\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "foy-iIsSHhRc"
},
"source": [
"### 5.3 Series切り捨て/切り上げ"
]
},
{
"cell_type": "code",
"metadata": {
"id": "vIyejjcMGNl4",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "1127e226-83eb-4d61-90b7-a0c5b834470a"
},
"source": [
"sr_value = pd.Series(lst_value)\n",
"print(f'sr_value = \\n', sr_value)\n",
"\n",
"sr_ret = du.Tool.round_down(sr_value, 5)\n",
"print(f'round_down = \\n', sr_ret)\n",
"\n",
"sr_ret = du.Tool.round_up(sr_value, 10)\n",
"print(f'round_up = \\n', sr_ret)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"sr_value = \n",
" 0 1.00\n",
"1 5.00\n",
"2 10.00\n",
"3 18.00\n",
"4 1.50\n",
"5 20.58\n",
"6 123.00\n",
"7 54321.00\n",
"8 0.50\n",
"9 55.50\n",
"10 33.00\n",
"dtype: float64\n",
"round_down = \n",
" 0 0\n",
"1 5\n",
"2 10\n",
"3 15\n",
"4 0\n",
"5 20\n",
"6 120\n",
"7 54320\n",
"8 0\n",
"9 55\n",
"10 30\n",
"dtype: int64\n",
"round_up = \n",
" 0 10\n",
"1 10\n",
"2 20\n",
"3 20\n",
"4 10\n",
"5 30\n",
"6 130\n",
"7 54330\n",
"8 10\n",
"9 60\n",
"10 40\n",
"dtype: int64\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "57Dx8draHqQl"
},
"source": [
"### 5.4 DatetimeIndex切り捨て/切り上げ"
]
},
{
"cell_type": "code",
"metadata": {
"id": "gVa4PAIfHMES",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "e1f0ae07-4db0-4a25-b484-64976ce33138"
},
"source": [
"df = df_bybit_trades.iloc[0:10,:].copy()\n",
"du.Tool.set_unixtime_to_dateindex(df)\n",
"print(f'df_index = \\n', df.index)\n",
"\n",
"dt_ret = du.Tool.round_down(df.index, 5)\n",
"print(f'round_down = \\n', dt_ret)\n",
"\n",
"dt_ret = du.Tool.round_up(df.index, 10)\n",
"print(f'round_up = \\n', dt_ret)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"df_index = \n",
" DatetimeIndex(['2020-09-01 00:00:00.672435045+00:00',\n",
" '2020-09-01 00:00:01.154071093+00:00',\n",
" '2020-09-01 00:00:01.825673103+00:00',\n",
" '2020-09-01 00:00:02.841267109+00:00',\n",
" '2020-09-01 00:00:02.950003862+00:00',\n",
" '2020-09-01 00:00:02.950003862+00:00',\n",
" '2020-09-01 00:00:02.950003862+00:00',\n",
" '2020-09-01 00:00:02.950003862+00:00',\n",
" '2020-09-01 00:00:02.950003862+00:00',\n",
" '2020-09-01 00:00:03.044623137+00:00'],\n",
" dtype='datetime64[ns, UTC]', name='datetime', freq=None)\n",
"round_down = \n",
" DatetimeIndex(['2020-09-01 00:00:00+00:00', '2020-09-01 00:00:00+00:00',\n",
" '2020-09-01 00:00:00+00:00', '2020-09-01 00:00:00+00:00',\n",
" '2020-09-01 00:00:00+00:00', '2020-09-01 00:00:00+00:00',\n",
" '2020-09-01 00:00:00+00:00', '2020-09-01 00:00:00+00:00',\n",
" '2020-09-01 00:00:00+00:00', '2020-09-01 00:00:00+00:00'],\n",
" dtype='datetime64[ns, UTC]', name='datetime', freq=None)\n",
"round_up = \n",
" DatetimeIndex(['2020-09-01 00:00:10+00:00', '2020-09-01 00:00:10+00:00',\n",
" '2020-09-01 00:00:10+00:00', '2020-09-01 00:00:10+00:00',\n",
" '2020-09-01 00:00:10+00:00', '2020-09-01 00:00:10+00:00',\n",
" '2020-09-01 00:00:10+00:00', '2020-09-01 00:00:10+00:00',\n",
" '2020-09-01 00:00:10+00:00', '2020-09-01 00:00:10+00:00'],\n",
" dtype='datetime64[ns, UTC]', name='datetime', freq=None)\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "jlfKqWx_JTwk"
},
"source": [
"## 6. datetime変換"
]
},
{
"cell_type": "code",
"metadata": {
"id": "G8NvX9MFIuDT",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "c0f880fe-5827-4f4b-86df-f43b9cda3ee8"
},
"source": [
"#---------------------------------------------------------------------------\n",
"# datetime変換\n",
"#---------------------------------------------------------------------------\n",
"# [params]\n",
"# value : datetime変換するオブジェクト (str, list, ndarray, Series, etc.)\n",
"# fmt : 日付フォーマット (str) 省略可\n",
"# [return]\n",
"# valueをdatetime変換したオブジェクト (エラーの場合はNoneを返す)\n",
"#---------------------------------------------------------------------------\n",
"dt = du.Tool.str_to_datetime('2020-09-01T10:10:10')\n",
"print(dt)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"2020-09-01 10:10:10\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "HqgDnZuGJw3z"
},
"source": [
"### 6.1 strをdatetime変換"
]
},
{
"cell_type": "code",
"metadata": {
"id": "qjZ_JtE_J46A",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "194d0663-052f-4680-ca36-f522818766f7"
},
"source": [
"str_date = [\n",
" '2020-09-01T10:10:10',\n",
" '2020-09-01T10:10:10+0900',\n",
" '2020-09-01T11:00:00.123Z',\n",
" '2020-09-01T11:00:00.123Z+0000',\n",
" '2020-09-01T12:00:00.123456',\n",
" '2020-09-01T12:00:00.123456+0900',\n",
" '2020/09/01 09:00:00',\n",
" '2020/09/01 09:00:00+0900',\n",
" '2020/09/01 09:00:00.123',\n",
" '2020/09/01 09:00:00.123+0900',\n",
" '2020/09/01 09:00:00.123456',\n",
" '2020/09/01 09:00:00.123456+0900',\n",
"]\n",
"\n",
"for i, s in enumerate(str_date):\n",
" dt = du.Tool.str_to_datetime(s)\n",
" print(i, s, ' => ', dt)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"0 2020-09-01T10:10:10 => 2020-09-01 10:10:10\n",
"1 2020-09-01T10:10:10+0900 => 2020-09-01 10:10:10+09:00\n",
"2 2020-09-01T11:00:00.123Z => 2020-09-01 11:00:00.123000\n",
"3 2020-09-01T11:00:00.123Z+0000 => 2020-09-01 11:00:00.123000+00:00\n",
"4 2020-09-01T12:00:00.123456 => 2020-09-01 12:00:00.123456\n",
"5 2020-09-01T12:00:00.123456+0900 => 2020-09-01 12:00:00.123456+09:00\n",
"6 2020/09/01 09:00:00 => 2020-09-01 09:00:00\n",
"7 2020/09/01 09:00:00+0900 => 2020-09-01 09:00:00+09:00\n",
"8 2020/09/01 09:00:00.123 => 2020-09-01 09:00:00.123000\n",
"9 2020/09/01 09:00:00.123+0900 => 2020-09-01 09:00:00.123000+09:00\n",
"10 2020/09/01 09:00:00.123456 => 2020-09-01 09:00:00.123456\n",
"11 2020/09/01 09:00:00.123456+0900 => 2020-09-01 09:00:00.123456+09:00\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "2PkGSUbmKSzi"
},
"source": [
"### 6.2 list要素をdatetime変換"
]
},
{
"cell_type": "code",
"metadata": {
"id": "-yQ3ZrFPKf3r",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "c215e1c7-d0b0-4f4e-e782-1cf53fbd375c"
},
"source": [
"du.Tool.debug_print(str_date)\n",
"\n",
"print()\n",
"\n",
"lst_ret = du.Tool.str_to_datetime(str_date)\n",
"du.Tool.debug_print(lst_ret)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"str_date = \n",
"[\n",
" '2020-09-01T10:10:10',\n",
" '2020-09-01T10:10:10+0900',\n",
" '2020-09-01T11:00:00.123Z',\n",
" '2020-09-01T11:00:00.123Z+0000',\n",
" '2020-09-01T12:00:00.123456',\n",
" '2020-09-01T12:00:00.123456+0900',\n",
" '2020/09/01 09:00:00',\n",
" '2020/09/01 09:00:00+0900',\n",
" '2020/09/01 09:00:00.123',\n",
" '2020/09/01 09:00:00.123+0900',\n",
" '2020/09/01 09:00:00.123456',\n",
" '2020/09/01 09:00:00.123456+0900',\n",
"], (len = 12)\n",
"\n",
"lst_ret = \n",
"[\n",
" datetime.datetime(2020, 9, 1, 10, 10, 10),\n",
" datetime.datetime(2020, 9, 1, 10, 10, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=32400))),\n",
" datetime.datetime(2020, 9, 1, 11, 0, 0, 123000),\n",
" datetime.datetime(2020, 9, 1, 11, 0, 0, 123000, tzinfo=datetime.timezone.utc),\n",
" datetime.datetime(2020, 9, 1, 12, 0, 0, 123456),\n",
" datetime.datetime(2020, 9, 1, 12, 0, 0, 123456, tzinfo=datetime.timezone(datetime.timedelta(seconds=32400))),\n",
" datetime.datetime(2020, 9, 1, 9, 0),\n",
" datetime.datetime(2020, 9, 1, 9, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=32400))),\n",
" datetime.datetime(2020, 9, 1, 9, 0, 0, 123000),\n",
" datetime.datetime(2020, 9, 1, 9, 0, 0, 123000, tzinfo=datetime.timezone(datetime.timedelta(seconds=32400))),\n",
" datetime.datetime(2020, 9, 1, 9, 0, 0, 123456),\n",
" datetime.datetime(2020, 9, 1, 9, 0, 0, 123456, tzinfo=datetime.timezone(datetime.timedelta(seconds=32400))),\n",
"], (len = 12)\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "HJ0enaJSK-b7"
},
"source": [
"### 6.3 ndarray要素をdatetime変換"
]
},
{
"cell_type": "code",
"metadata": {
"id": "uD7G8XHcLHWT",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "d3d58fa9-3101-4f6a-d89d-a8c3262c90e1"
},
"source": [
"nd_str_date = np.array(str_date)\n",
"du.Tool.debug_print(nd_str_date)\n",
"\n",
"print()\n",
"\n",
"nd_ret = du.Tool.str_to_datetime(nd_str_date)\n",
"du.Tool.debug_print(nd_ret)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"nd_str_date = \n",
"array(['2020-09-01T10:10:10', '2020-09-01T10:10:10+0900',\n",
" '2020-09-01T11:00:00.123Z', '2020-09-01T11:00:00.123Z+0000',\n",
" '2020-09-01T12:00:00.123456', '2020-09-01T12:00:00.123456+0900',\n",
" '2020/09/01 09:00:00', '2020/09/01 09:00:00+0900',\n",
" '2020/09/01 09:00:00.123', '2020/09/01 09:00:00.123+0900',\n",
" '2020/09/01 09:00:00.123456', '2020/09/01 09:00:00.123456+0900'],\n",
" dtype='<U31')\n",
" (len = 12)\n",
"\n",
"nd_ret = \n",
"array([datetime.datetime(2020, 9, 1, 10, 10, 10),\n",
" datetime.datetime(2020, 9, 1, 10, 10, 10, tzinfo=tzoffset(None, 32400)),\n",
" datetime.datetime(2020, 9, 1, 11, 0, 0, 123000, tzinfo=tzlocal()),\n",
" datetime.datetime(2020, 9, 1, 11, 0, 0, 123000, tzinfo=tzlocal()),\n",
" datetime.datetime(2020, 9, 1, 12, 0, 0, 123456),\n",
" datetime.datetime(2020, 9, 1, 12, 0, 0, 123456, tzinfo=tzoffset(None, 32400)),\n",
" datetime.datetime(2020, 9, 1, 9, 0),\n",
" datetime.datetime(2020, 9, 1, 9, 0, tzinfo=tzoffset(None, 32400)),\n",
" datetime.datetime(2020, 9, 1, 9, 0, 0, 123000),\n",
" datetime.datetime(2020, 9, 1, 9, 0, 0, 123000, tzinfo=tzoffset(None, 32400)),\n",
" datetime.datetime(2020, 9, 1, 9, 0, 0, 123456),\n",
" datetime.datetime(2020, 9, 1, 9, 0, 0, 123456, tzinfo=tzoffset(None, 32400))],\n",
" dtype=object)\n",
" (len = 12)\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "ImwERLuBPh8p"
},
"source": [
"### 6.4 Series要素をdatetime変換"
]
},
{
"cell_type": "code",
"metadata": {
"id": "Z7FKVH_tPm3R",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 699
},
"outputId": "184d3db7-f459-4a2a-e461-d30078bfb4a6"
},
"source": [
"df_str_dt = pd.DataFrame({'str_dt': str_date})\n",
"display(df_str_dt)\n",
"\n",
"print()\n",
"\n",
"sr_ret = du.Tool.str_to_datetime(df_str_dt.str_dt)\n",
"du.Tool.debug_print(sr_ret)"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>str_dt</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2020-09-01T10:10:10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2020-09-01T10:10:10+0900</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2020-09-01T11:00:00.123Z</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2020-09-01T11:00:00.123Z+0000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2020-09-01T12:00:00.123456</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>2020-09-01T12:00:00.123456+0900</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>2020/09/01 09:00:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>2020/09/01 09:00:00+0900</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>2020/09/01 09:00:00.123</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>2020/09/01 09:00:00.123+0900</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>2020/09/01 09:00:00.123456</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>2020/09/01 09:00:00.123456+0900</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" str_dt\n",
"0 2020-09-01T10:10:10\n",
"1 2020-09-01T10:10:10+0900\n",
"2 2020-09-01T11:00:00.123Z\n",
"3 2020-09-01T11:00:00.123Z+0000\n",
"4 2020-09-01T12:00:00.123456\n",
"5 2020-09-01T12:00:00.123456+0900\n",
"6 2020/09/01 09:00:00\n",
"7 2020/09/01 09:00:00+0900\n",
"8 2020/09/01 09:00:00.123\n",
"9 2020/09/01 09:00:00.123+0900\n",
"10 2020/09/01 09:00:00.123456\n",
"11 2020/09/01 09:00:00.123456+0900"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"\n",
"sr_ret = \n",
"0 2020-09-01 10:10:10\n",
"1 2020-09-01 10:10:10+09:00\n",
"2 2020-09-01 11:00:00.123000+00:00\n",
"3 2020-09-01 11:00:00.123000+00:00\n",
"4 2020-09-01 12:00:00.123456\n",
"5 2020-09-01 12:00:00.123456+09:00\n",
"6 2020-09-01 09:00:00\n",
"7 2020-09-01 09:00:00+09:00\n",
"8 2020-09-01 09:00:00.123000\n",
"9 2020-09-01 09:00:00.123000+09:00\n",
"10 2020-09-01 09:00:00.123456\n",
"11 2020-09-01 09:00:00.123456+09:00\n",
"Name: str_dt, dtype: object\n",
" (len = 12)\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "k2hXb53CJV5b"
},
"source": [
"## 7. unixtime変換"
]
},
{
"cell_type": "code",
"metadata": {
"id": "KFGLxpimJY1l",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "49d9fa72-a51d-49f9-fcfb-ebecfe3f2c86"
},
"source": [
"#---------------------------------------------------------------------------\n",
"# unixtime変換\n",
"#---------------------------------------------------------------------------\n",
"# [params]\n",
"# value : unixtime変換するオブジェクト (str, datetime, list, ndarray, Series, etc.)\n",
"# [return]\n",
"# valueをunixtime変換したオブジェクト (エラーの場合は0を返す)\n",
"#---------------------------------------------------------------------------\n",
"ut = du.Tool.to_unixtime('2020-09-01T10:10:10')\n",
"print(ut)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"1598955010.0\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "kqbiUv7ZQnKp"
},
"source": [
"### 7.1 値をunixtime変換"
]
},
{
"cell_type": "code",
"metadata": {
"id": "YoScw1jgQi46",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "c83aff09-e9e4-4184-beea-6745c2de9f4c"
},
"source": [
"# str => unixtime\n",
"str_date = '2020-09-01T10:10:10'\n",
"ret_ut = du.Tool.to_unixtime(str_date)\n",
"print(str_date, ' => ', ret_ut)\n",
"\n",
"# datetime => unixtime\n",
"dt_now = datetime.now()\n",
"ret_ut = du.Tool.to_unixtime(dt_now)\n",
"print(dt_now, ' => ', ret_ut)\n"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"2020-09-01T10:10:10 => 1598955010.0\n",
"2021-03-08 07:55:48.561367 => 1615190148.561367\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "EqqdPyqMRbxh"
},
"source": [
"### 7.2 list要素をunixtime変換"
]
},
{
"cell_type": "code",
"metadata": {
"id": "JWs21fC8Q_Pw",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "a1a89a84-a785-4c5e-f37e-be34e2a55a49"
},
"source": [
"str_date = [\n",
" '2020-09-01T10:10:10',\n",
" '2020-09-01T10:10:10+0900',\n",
" '2020-09-01T11:00:00.123Z',\n",
" '2020-09-01T11:00:00.123Z+0000',\n",
" '2020-09-01T12:00:00.123456',\n",
" '2020-09-01T12:00:00.123456+0900',\n",
" '2020/09/01 09:00:00',\n",
" '2020/09/01 09:00:00+0900',\n",
" '2020/09/01 09:00:00.123',\n",
" '2020/09/01 09:00:00.123+0900',\n",
" '2020/09/01 09:00:00.123456',\n",
" '2020/09/01 09:00:00.123456+0900',\n",
"]\n",
"du.Tool.debug_print(str_date)\n",
"\n",
"print()\n",
"\n",
"# listの各要素をunixtime変換\n",
"lst_ut = du.Tool.to_unixtime(str_date)\n",
"du.Tool.debug_print(lst_ut)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"str_date = \n",
"[\n",
" '2020-09-01T10:10:10',\n",
" '2020-09-01T10:10:10+0900',\n",
" '2020-09-01T11:00:00.123Z',\n",
" '2020-09-01T11:00:00.123Z+0000',\n",
" '2020-09-01T12:00:00.123456',\n",
" '2020-09-01T12:00:00.123456+0900',\n",
" '2020/09/01 09:00:00',\n",
" '2020/09/01 09:00:00+0900',\n",
" '2020/09/01 09:00:00.123',\n",
" '2020/09/01 09:00:00.123+0900',\n",
" '2020/09/01 09:00:00.123456',\n",
" '2020/09/01 09:00:00.123456+0900',\n",
"], (len = 12)\n",
"\n",
"lst_ut = \n",
"[\n",
" 1598955010.0,\n",
" 1598922610.0,\n",
" 1598958000.123,\n",
" 1598958000.123,\n",
" 1598961600.123456,\n",
" 1598929200.123456,\n",
" 1598950800.0,\n",
" 1598918400.0,\n",
" 1598950800.123,\n",
" 1598918400.123,\n",
" 1598950800.123456,\n",
" 1598918400.123456,\n",
"], (len = 12)\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "Gk9iXY1-SH8h"
},
"source": [
"### 7.3 ndarray要素をunixtime変換"
]
},
{
"cell_type": "code",
"metadata": {
"id": "phSgcsl2R3Cj",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "4db2a8c0-95db-4cd6-a0dd-1a865027a378"
},
"source": [
"nd_str_date = np.array(str_date)\n",
"du.Tool.debug_print(nd_str_date)\n",
"\n",
"print()\n",
"\n",
"nd_ret = du.Tool.to_unixtime(nd_str_date)\n",
"du.Tool.debug_print(nd_ret)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"nd_str_date = \n",
"array(['2020-09-01T10:10:10', '2020-09-01T10:10:10+0900',\n",
" '2020-09-01T11:00:00.123Z', '2020-09-01T11:00:00.123Z+0000',\n",
" '2020-09-01T12:00:00.123456', '2020-09-01T12:00:00.123456+0900',\n",
" '2020/09/01 09:00:00', '2020/09/01 09:00:00+0900',\n",
" '2020/09/01 09:00:00.123', '2020/09/01 09:00:00.123+0900',\n",
" '2020/09/01 09:00:00.123456', '2020/09/01 09:00:00.123456+0900'],\n",
" dtype='<U31')\n",
" (len = 12)\n",
"\n",
"nd_ret = \n",
"array([1.59895501e+09, 1.59892261e+09, 1.59895800e+09, 1.59895800e+09,\n",
" 1.59896160e+09, 1.59892920e+09, 1.59895080e+09, 1.59891840e+09,\n",
" 1.59895080e+09, 1.59891840e+09, 1.59895080e+09, 1.59891840e+09])\n",
" (len = 12)\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "Ks9Ay0OrUJM4"
},
"source": [
"### 7.4 Series要素をunixtimetime変換"
]
},
{
"cell_type": "code",
"metadata": {
"id": "wMmDWvTuSV8K",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 699
},
"outputId": "de9b1e5f-c63a-4a9b-bf97-4c09868a91af"
},
"source": [
"df_str_dt = pd.DataFrame({'str_dt': str_date})\n",
"display(df_str_dt)\n",
"\n",
"print()\n",
"\n",
"sr_ret = du.Tool.to_unixtime(df_str_dt.str_dt)\n",
"du.Tool.debug_print(sr_ret)"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>str_dt</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2020-09-01T10:10:10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2020-09-01T10:10:10+0900</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2020-09-01T11:00:00.123Z</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2020-09-01T11:00:00.123Z+0000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2020-09-01T12:00:00.123456</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>2020-09-01T12:00:00.123456+0900</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>2020/09/01 09:00:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>2020/09/01 09:00:00+0900</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>2020/09/01 09:00:00.123</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>2020/09/01 09:00:00.123+0900</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>2020/09/01 09:00:00.123456</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>2020/09/01 09:00:00.123456+0900</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" str_dt\n",
"0 2020-09-01T10:10:10\n",
"1 2020-09-01T10:10:10+0900\n",
"2 2020-09-01T11:00:00.123Z\n",
"3 2020-09-01T11:00:00.123Z+0000\n",
"4 2020-09-01T12:00:00.123456\n",
"5 2020-09-01T12:00:00.123456+0900\n",
"6 2020/09/01 09:00:00\n",
"7 2020/09/01 09:00:00+0900\n",
"8 2020/09/01 09:00:00.123\n",
"9 2020/09/01 09:00:00.123+0900\n",
"10 2020/09/01 09:00:00.123456\n",
"11 2020/09/01 09:00:00.123456+0900"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"\n",
"sr_ret = \n",
"0 1.598955e+09\n",
"1 1.598923e+09\n",
"2 1.598958e+09\n",
"3 1.598958e+09\n",
"4 1.598962e+09\n",
"5 1.598929e+09\n",
"6 1.598951e+09\n",
"7 1.598918e+09\n",
"8 1.598951e+09\n",
"9 1.598918e+09\n",
"10 1.598951e+09\n",
"11 1.598918e+09\n",
"Name: str_dt, dtype: float64\n",
" (len = 12)\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "RhpJl5d2UjRY"
},
"source": [
"### 7.5 DatetimeIndex要素をunixtime変換"
]
},
{
"cell_type": "code",
"metadata": {
"id": "Lmefk0D-UZSR",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 487
},
"outputId": "aa168a5b-c59d-4f7c-b1a7-91904355840c"
},
"source": [
"df = df_bybit_trades.iloc[0:10,:].copy()\n",
"du.Tool.set_unixtime_to_dateindex(df)\n",
"display(df)\n",
"\n",
"print()\n",
"\n",
"idx_ret = du.Tool.to_unixtime(df.index)\n",
"du.Tool.debug_print(idx_ret)"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>unixtime</th>\n",
" <th>side</th>\n",
" <th>size</th>\n",
" <th>price</th>\n",
" </tr>\n",
" <tr>\n",
" <th>datetime</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2020-09-01 00:00:00.672435045+00:00</th>\n",
" <td>1.598918e+09</td>\n",
" <td>Sell</td>\n",
" <td>7000</td>\n",
" <td>11659.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 00:00:01.154071093+00:00</th>\n",
" <td>1.598918e+09</td>\n",
" <td>Buy</td>\n",
" <td>40</td>\n",
" <td>11660.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 00:00:01.825673103+00:00</th>\n",
" <td>1.598918e+09</td>\n",
" <td>Buy</td>\n",
" <td>1</td>\n",
" <td>11660.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 00:00:02.841267109+00:00</th>\n",
" <td>1.598918e+09</td>\n",
" <td>Sell</td>\n",
" <td>50</td>\n",
" <td>11659.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 00:00:02.950003862+00:00</th>\n",
" <td>1.598918e+09</td>\n",
" <td>Sell</td>\n",
" <td>210</td>\n",
" <td>11659.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 00:00:02.950003862+00:00</th>\n",
" <td>1.598918e+09</td>\n",
" <td>Sell</td>\n",
" <td>900</td>\n",
" <td>11659.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 00:00:02.950003862+00:00</th>\n",
" <td>1.598918e+09</td>\n",
" <td>Sell</td>\n",
" <td>87</td>\n",
" <td>11659.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 00:00:02.950003862+00:00</th>\n",
" <td>1.598918e+09</td>\n",
" <td>Sell</td>\n",
" <td>192</td>\n",
" <td>11659.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 00:00:02.950003862+00:00</th>\n",
" <td>1.598918e+09</td>\n",
" <td>Sell</td>\n",
" <td>4254</td>\n",
" <td>11659.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020-09-01 00:00:03.044623137+00:00</th>\n",
" <td>1.598918e+09</td>\n",
" <td>Sell</td>\n",
" <td>982</td>\n",
" <td>11659.5</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" unixtime side size price\n",
"datetime \n",
"2020-09-01 00:00:00.672435045+00:00 1.598918e+09 Sell 7000 11659.5\n",
"2020-09-01 00:00:01.154071093+00:00 1.598918e+09 Buy 40 11660.0\n",
"2020-09-01 00:00:01.825673103+00:00 1.598918e+09 Buy 1 11660.0\n",
"2020-09-01 00:00:02.841267109+00:00 1.598918e+09 Sell 50 11659.5\n",
"2020-09-01 00:00:02.950003862+00:00 1.598918e+09 Sell 210 11659.5\n",
"2020-09-01 00:00:02.950003862+00:00 1.598918e+09 Sell 900 11659.5\n",
"2020-09-01 00:00:02.950003862+00:00 1.598918e+09 Sell 87 11659.5\n",
"2020-09-01 00:00:02.950003862+00:00 1.598918e+09 Sell 192 11659.5\n",
"2020-09-01 00:00:02.950003862+00:00 1.598918e+09 Sell 4254 11659.5\n",
"2020-09-01 00:00:03.044623137+00:00 1.598918e+09 Sell 982 11659.5"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"\n",
"idx_ret = Float64Index([1598918400.672435, 1598918401.154071, 1598918401.825673,\n",
" 1598918402.841267, 1598918402.950004, 1598918402.950004,\n",
" 1598918402.950004, 1598918402.950004, 1598918402.950004,\n",
" 1598918403.044623],\n",
" dtype='float64', name='datetime')\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "dEtxg20l2pNa"
},
"source": [
"## 8. bybitデータ取得"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "J254lkpv6p1w"
},
"source": [
"### 8.1 bybit状態取得"
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "L-D7OOpz1fNr",
"outputId": "5c010db5-9899-42f5-b6fe-c8d3f6da9d24"
},
"source": [
"#---------------------------------------------------------------------------\n",
"# bybit状態取得\n",
"#---------------------------------------------------------------------------\n",
"# [params]\n",
"# api_key / api_secret : API Key/SECRET\n",
"# testnet : 接続先(True:testnet, False:realnet)\n",
"# symbol : 取得対象の通貨ペアシンボル名（デフォルトは BTCUSD）\n",
"#---------------------------------------------------------------------------\n",
"api_key = 'your api key'\n",
"api_secret = 'your api secret'\n",
"du.Tool.print_status_from_bybit(api_key, api_secret, symbol='BTCUSD')"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"<STATUS> BTCUSD 2021/03/08 17:33:16\n",
"[price]\n",
" ltp : 49724.0\n",
" bid : 49723.5\n",
" ask : 49724.0\n",
" mark : 49711.50\n",
" index : 49671.31\n",
" vol_24 : 6,009,652,370\n",
" oi : 2,010,319,933\n",
" fr : 0.0869%\n",
"[position]\n",
" side : None\n",
" size : 0 (0.00000000)\n",
" avr_entry : 0.00 (+0.00)\n",
" stop_loss : 0.0\n",
" take_profit: 0.0\n",
" trailing : 0.0\n",
" liq_price : 0.0\n",
" unrealised : 0.00000000\n",
" leverage : 100.00\n",
"[balance]\n",
" wallet : 0.09963084\n",
" available : 0.09963084\n",
"\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "RhpmMF_86xaR"
},
"source": [
"### 8.2 bybit 自注文約定履歴に損益計算を付加して取得"
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 703
},
"id": "0SrRGGEf29Zg",
"outputId": "bb632089-1009-40a0-ab58-1983b9456337"
},
"source": [
"#---------------------------------------------------------------------------\n",
"# bybit 自注文約定履歴に損益計算を付加して取得\n",
"#---------------------------------------------------------------------------\n",
"# [params]\n",
"# api_key / api_secret : API Key/Secret\n",
"# testnet : 接続先(True:testnet, False:realnet)\n",
"# symbol : 取得対象の通貨ペアシンボル名（デフォルトは BTCUSD）\n",
"# from_ut : 取得開始UnixTime\n",
"# [return]\n",
"# 指定期間内の自約定履歴DataFrame (エラーの場合はNoneを返す)\n",
"#---------------------------------------------------------------------------\n",
"api_key = 'your api key'\n",
"api_secret = 'your api secret'\n",
"from_ut = du.Tool.to_unixtime('2021/03/05 00:00:00+0900')\n",
"df_execs = du.Tool.get_executions_from_bybit(api_key, api_secret, symbol='BTCUSD', from_ut=from_ut)\n",
"\n",
"display(df_execs)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"Success API request. last:1615108970.270892 execs:40 RateLimit:116/120 Reset:1615192492.205\n",
"Success API request. last:1615108970.270892 execs:80 RateLimit:115/120 Reset:1615192492.938\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>exec_time</th>\n",
" <th>exec_type</th>\n",
" <th>order_type</th>\n",
" <th>side</th>\n",
" <th>exec_price</th>\n",
" <th>exec_qty</th>\n",
" <th>exec_value</th>\n",
" <th>fee_rate</th>\n",
" <th>exec_fee</th>\n",
" <th>pos_size</th>\n",
" <th>val_per_qty</th>\n",
" <th>pl</th>\n",
" </tr>\n",
" <tr>\n",
" <th>datetime</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2021-03-05 01:00:00+09:00</th>\n",
" <td>1.614874e+09</td>\n",
" <td>Funding</td>\n",
" <td></td>\n",
" <td>Sell</td>\n",
" <td>49472.69</td>\n",
" <td>2000</td>\n",
" <td>0.040426</td>\n",
" <td>-0.000100</td>\n",
" <td>-0.000004</td>\n",
" <td>-2000</td>\n",
" <td>0.000020</td>\n",
" <td>0.000004</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-03-05 09:00:00+09:00</th>\n",
" <td>1.614902e+09</td>\n",
" <td>Funding</td>\n",
" <td></td>\n",
" <td>Sell</td>\n",
" <td>48399.37</td>\n",
" <td>2000</td>\n",
" <td>0.041323</td>\n",
" <td>-0.000388</td>\n",
" <td>-0.000016</td>\n",
" <td>-2000</td>\n",
" <td>0.000020</td>\n",
" <td>0.000016</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-03-05 09:14:01.627373934+09:00</th>\n",
" <td>1.614903e+09</td>\n",
" <td>Trade</td>\n",
" <td>Market</td>\n",
" <td>Buy</td>\n",
" <td>47203.50</td>\n",
" <td>2000</td>\n",
" <td>0.042370</td>\n",
" <td>0.000750</td>\n",
" <td>0.000032</td>\n",
" <td>0</td>\n",
" <td>0.000020</td>\n",
" <td>0.002616</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-03-05 09:15:18.942918062+09:00</th>\n",
" <td>1.614903e+09</td>\n",
" <td>Trade</td>\n",
" <td>Market</td>\n",
" <td>Sell</td>\n",
" <td>47301.00</td>\n",
" <td>19533</td>\n",
" <td>0.412951</td>\n",
" <td>0.000750</td>\n",
" <td>0.000310</td>\n",
" <td>-19533</td>\n",
" <td>0.000021</td>\n",
" <td>-0.000310</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-03-05 09:15:18.942918062+09:00</th>\n",
" <td>1.614903e+09</td>\n",
" <td>Trade</td>\n",
" <td>Market</td>\n",
" <td>Sell</td>\n",
" <td>47301.00</td>\n",
" <td>4190</td>\n",
" <td>0.088582</td>\n",
" <td>0.000750</td>\n",
" <td>0.000066</td>\n",
" <td>-23723</td>\n",
" <td>0.000021</td>\n",
" <td>-0.000066</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-03-05 17:00:00+09:00</th>\n",
" <td>1.614931e+09</td>\n",
" <td>Funding</td>\n",
" <td></td>\n",
" <td>Sell</td>\n",
" <td>47403.15</td>\n",
" <td>23723</td>\n",
" <td>0.500452</td>\n",
" <td>-0.000800</td>\n",
" <td>-0.000401</td>\n",
" <td>-23723</td>\n",
" <td>0.000021</td>\n",
" <td>0.000401</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-03-06 01:00:00+09:00</th>\n",
" <td>1.614960e+09</td>\n",
" <td>Funding</td>\n",
" <td></td>\n",
" <td>Sell</td>\n",
" <td>47860.75</td>\n",
" <td>23723</td>\n",
" <td>0.495667</td>\n",
" <td>-0.000100</td>\n",
" <td>-0.000050</td>\n",
" <td>-23723</td>\n",
" <td>0.000021</td>\n",
" <td>0.000050</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-03-06 09:00:00+09:00</th>\n",
" <td>1.614989e+09</td>\n",
" <td>Funding</td>\n",
" <td></td>\n",
" <td>Sell</td>\n",
" <td>48766.20</td>\n",
" <td>23723</td>\n",
" <td>0.486464</td>\n",
" <td>-0.000100</td>\n",
" <td>-0.000049</td>\n",
" <td>-23723</td>\n",
" <td>0.000021</td>\n",
" <td>0.000049</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-03-06 09:15:12.476167917+09:00</th>\n",
" <td>1.614990e+09</td>\n",
" <td>Trade</td>\n",
" <td>Market</td>\n",
" <td>Buy</td>\n",
" <td>49116.50</td>\n",
" <td>23723</td>\n",
" <td>0.482995</td>\n",
" <td>0.000750</td>\n",
" <td>0.000362</td>\n",
" <td>0</td>\n",
" <td>0.000021</td>\n",
" <td>-0.018900</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-03-06 09:47:32.023179054+09:00</th>\n",
" <td>1.614992e+09</td>\n",
" <td>Trade</td>\n",
" <td>Market</td>\n",
" <td>Sell</td>\n",
" <td>48900.00</td>\n",
" <td>10000</td>\n",
" <td>0.204499</td>\n",
" <td>0.000750</td>\n",
" <td>0.000153</td>\n",
" <td>-10000</td>\n",
" <td>0.000020</td>\n",
" <td>-0.000153</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-03-06 17:00:00+09:00</th>\n",
" <td>1.615018e+09</td>\n",
" <td>Funding</td>\n",
" <td></td>\n",
" <td>Sell</td>\n",
" <td>48836.44</td>\n",
" <td>10000</td>\n",
" <td>0.204765</td>\n",
" <td>-0.000100</td>\n",
" <td>-0.000020</td>\n",
" <td>-10000</td>\n",
" <td>0.000020</td>\n",
" <td>0.000020</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-03-06 23:32:39.405642033+09:00</th>\n",
" <td>1.615041e+09</td>\n",
" <td>Trade</td>\n",
" <td>Market</td>\n",
" <td>Buy</td>\n",
" <td>47361.00</td>\n",
" <td>10000</td>\n",
" <td>0.211144</td>\n",
" <td>0.000750</td>\n",
" <td>0.000158</td>\n",
" <td>0</td>\n",
" <td>0.000020</td>\n",
" <td>0.006487</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-03-07 09:26:04.758910894+09:00</th>\n",
" <td>1.615077e+09</td>\n",
" <td>Trade</td>\n",
" <td>Market</td>\n",
" <td>Buy</td>\n",
" <td>49300.50</td>\n",
" <td>5000</td>\n",
" <td>0.101419</td>\n",
" <td>0.000750</td>\n",
" <td>0.000076</td>\n",
" <td>5000</td>\n",
" <td>0.000020</td>\n",
" <td>-0.000076</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-03-07 17:00:00+09:00</th>\n",
" <td>1.615104e+09</td>\n",
" <td>Funding</td>\n",
" <td></td>\n",
" <td>Buy</td>\n",
" <td>50070.35</td>\n",
" <td>5000</td>\n",
" <td>0.099859</td>\n",
" <td>0.000100</td>\n",
" <td>0.000010</td>\n",
" <td>5000</td>\n",
" <td>0.000020</td>\n",
" <td>-0.000010</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-03-07 18:22:50.270891905+09:00</th>\n",
" <td>1.615109e+09</td>\n",
" <td>Trade</td>\n",
" <td>Limit</td>\n",
" <td>Sell</td>\n",
" <td>50900.00</td>\n",
" <td>5000</td>\n",
" <td>0.098232</td>\n",
" <td>-0.000250</td>\n",
" <td>-0.000025</td>\n",
" <td>0</td>\n",
" <td>0.000020</td>\n",
" <td>0.003212</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" exec_time ... pl\n",
"datetime ... \n",
"2021-03-05 01:00:00+09:00 1.614874e+09 ... 0.000004\n",
"2021-03-05 09:00:00+09:00 1.614902e+09 ... 0.000016\n",
"2021-03-05 09:14:01.627373934+09:00 1.614903e+09 ... 0.002616\n",
"2021-03-05 09:15:18.942918062+09:00 1.614903e+09 ... -0.000310\n",
"2021-03-05 09:15:18.942918062+09:00 1.614903e+09 ... -0.000066\n",
"2021-03-05 17:00:00+09:00 1.614931e+09 ... 0.000401\n",
"2021-03-06 01:00:00+09:00 1.614960e+09 ... 0.000050\n",
"2021-03-06 09:00:00+09:00 1.614989e+09 ... 0.000049\n",
"2021-03-06 09:15:12.476167917+09:00 1.614990e+09 ... -0.018900\n",
"2021-03-06 09:47:32.023179054+09:00 1.614992e+09 ... -0.000153\n",
"2021-03-06 17:00:00+09:00 1.615018e+09 ... 0.000020\n",
"2021-03-06 23:32:39.405642033+09:00 1.615041e+09 ... 0.006487\n",
"2021-03-07 09:26:04.758910894+09:00 1.615077e+09 ... -0.000076\n",
"2021-03-07 17:00:00+09:00 1.615104e+09 ... -0.000010\n",
"2021-03-07 18:22:50.270891905+09:00 1.615109e+09 ... 0.003212\n",
"\n",
"[15 rows x 12 columns]"
]
},
"metadata": {
"tags": []
}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "KYZ_2r0b7Hl4"
},
"source": [
"### 8.3 約定履歴を日別にOHLCVにリサンプリングしてcsv出力"
]
},
{
"cell_type": "code",
"metadata": {
"id": "rYEmDr3L7Uno",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "6af28ed0-fe8a-4a3e-f3a8-dcc5f6932626"
},
"source": [
"#---------------------------------------------------------------------------\n",
"# bybit約定履歴を日別にOHLCVにリサンプリングしてcsv出力\n",
"# (https://public.bybit.com/trading/:symbol/ より)\n",
"#---------------------------------------------------------------------------\n",
"# [params]\n",
"# start_ymd / end_ymd : str(yyyy/mm/dd)で指定\n",
"# 取得可能期間 : 2019-10-01以降かつ前日まで\n",
"# symbol : 取得対象の通貨ペアシンボル名（デフォルトは BTCUSD）\n",
"# period : リサンプルするタイムフレーム ex) '1S'(秒), '5T'(分), '4H'(時), '1D'(日)\n",
"# output_dir : 日別csvを出力するディレクトリパス (Noneは'./bybit/{symbol}/ohlcv/{period}/')\n",
"# request_interval : 複数request時のsleep時間(sec)\n",
"# progress_info : 処理途中経過をprint\n",
"#---------------------------------------------------------------------------\n",
"start_ymd = '2021/08/01'\n",
"end_ymd = '2021/08/10'\n",
"symbol = 'BTCUSD'\n",
"period = '1S'\n",
"output_dir = None\n",
"request_interval = 0.0\n",
"progress_info = True\n",
"\n",
"du.Tool.save_daily_ohlcv_from_bybit_trading_gz(start_ymd, end_ymd, symbol, period, output_dir, request_interval, progress_info)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"output dir: ./bybit/BTCUSD/ohlcv/1S/ save term: 2021/08/01 -> 2021/08/10\n",
"Completed output 20210801.csv\n",
"Completed output 20210802.csv\n",
"Completed output 20210803.csv\n",
"Completed output 20210804.csv\n",
"Completed output 20210805.csv\n",
"Completed output 20210806.csv\n",
"Completed output 20210807.csv\n",
"Completed output 20210808.csv\n",
"Completed output 20210809.csv\n",
"Completed output 20210810.csv\n",
"Total output files: 10\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "-yog9tmdvIc6",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "7ab53c7b-cc03-4c23-a29d-1193218195cf"
},
"source": [
"# ---------------------------------------------------------------------------\n",
"# GMO約定履歴を日別にOHLCVにリサンプリングしてcsv出力\n",
"# (https://api.coin.z.com/data/trades/:symbol/ より)\n",
"# ---------------------------------------------------------------------------\n",
"# [params]\n",
"# start_ymd / end_ymd : str(yyyy/mm/dd)で指定\n",
"# 取得可能期間 : 2019-10-01以降かつ前日まで\n",
"# symbol : 取得対象の通貨ペアシンボル名（デフォルトは BTC_JPY）\n",
"# period : リサンプルするタイムフレーム ex) '1S'(秒), '5T'(分), '4H'(時), '1D'(日)\n",
"# output_dir : 日別csvを出力するディレクトリパス (Noneは'./gmo/{symbol}/ohlcv/{period}/')\n",
"# request_interval : 複数request時のsleep時間(sec)\n",
"# progress_info : 処理途中経過をprint\n",
"# ---------------------------------------------------------------------------\n",
"start_ymd = '2021/08/01'\n",
"end_ymd = '2021/08/10'\n",
"symbol = 'BTC_JPY'\n",
"period = '1S'\n",
"output_dir = None\n",
"request_interval = 0.0\n",
"progress_info = True\n",
"\n",
"du.Tool.save_daily_ohlcv_from_gmo_trading_gz(start_ymd, end_ymd, symbol, period, output_dir, request_interval, progress_info)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"output dir: ./gmo/BTC_JPY/ohlcv/1S/ save term: 2021/08/01 -> 2021/08/10\n",
"Completed output 20210801.csv\n",
"Completed output 20210802.csv\n",
"Completed output 20210803.csv\n",
"Completed output 20210804.csv\n",
"Completed output 20210805.csv\n",
"Completed output 20210806.csv\n",
"Completed output 20210807.csv\n",
"Completed output 20210808.csv\n",
"Completed output 20210809.csv\n",
"Completed output 20210810.csv\n",
"Total output files: 10\n"
]
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "zvhVgQWs721g"
},
"source": [
"### 8.4 ディレクトリ内の日別OHLCVをまとめて上位時間足にリサンプリングしてcsv出力"
]
},
{
"cell_type": "code",
"metadata": {
"id": "GQtqsUnf75go",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "e268f5eb-373c-443a-8957-1a8b67becf67"
},
"source": [
"#---------------------------------------------------------------------------\n",
"# ディレクトリ内の日別OHLCVをまとめて上位時間足にリサンプリングしてcsv出力\n",
"#---------------------------------------------------------------------------\n",
"# [params]\n",
"# input_dir : 日別csvの入力ディレクトリパス\n",
"# output_dir : 日別csvの出力ディレクトリパス\n",
"# period : リサンプルするタイムフレーム ex) '1S'(秒), '5T'(分), '4H'(時), '1D'(日)\n",
"# progress_info : 処理途中経過をprint\n",
"#---------------------------------------------------------------------------\n",
"input_dir = './bybit/BTCUSD/ohlcv/1S/'\n",
"output_dir = './bybit/BTCUSD/ohlcv/1T/'\n",
"period = '1T'\n",
"progress_info = True\n",
"\n",
"du.Tool.downsample_daily_ohlcv(input_dir, output_dir, period, progress_info)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"input dir: ./bybit/BTCUSD/ohlcv/1T/ -> output dir: ./bybit/BTCUSD/ohlcv/1T/ period: 1T\n",
"Completed output 20210809.csv\n",
"Completed output 20210804.csv\n",
"Completed output 20210807.csv\n",
"Completed output 20210801.csv\n",
"Completed output 20210803.csv\n",
"Completed output 20210808.csv\n",
"Completed output 20210810.csv\n",
"Completed output 20210802.csv\n",
"Completed output 20210805.csv\n",
"Completed output 20210806.csv\n",
"Total output files: 10\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "APkeQxJv8GnA"
},
"source": [
"### 8.5 日別OHLCV(csv)から指定期間のOHLCVを1つのDataFrameにまとめて取得"
]
},
{
"cell_type": "code",
"metadata": {
"id": "cIiAB4f48Ja4",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 422
},
"outputId": "b32b6eb3-d7a4-495b-ff90-bccd9952cf2b"
},
"source": [
"#---------------------------------------------------------------------------\n",
"# 日別OHLCV(csv)から指定期間のOHLCVを1つのDataFrameにまとめて取得\n",
"# (periodにてリサンプリング指定可能)\n",
"#---------------------------------------------------------------------------\n",
"# [params]\n",
"# start_ymd / end_ymd : str(yyyy/mm/dd)で指定\n",
"# csv_dir : 読み込む日別csvが格納されているディレクトリパス\n",
"# ignore_defect : 取得期間中に日別csvが存在しなかった場合に無視して継続するか (True:無視し継続, False:エラー)\n",
"# period : リサンプルするタイムフレーム ex) '1S'(秒), '5T'(分), '4H'(時), '1D'(日)\n",
"#---------------------------------------------------------------------------\n",
"start_ymd = '2021/08/01'\n",
"end_ymd = '2021/08/10'\n",
"csv_dir = './bybit/BTCUSD/ohlcv/1T/'\n",
"ignore_defect = False\n",
"period = '1H'\n",
"\n",
"df_ohlcv = du.Tool.get_ohlcv_from_daily_csv(start_ymd, end_ymd, csv_dir, ignore_defect, period)\n",
"display(df_ohlcv)"
],
"execution_count": null,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>unixtime</th>\n",
" <th>open</th>\n",
" <th>high</th>\n",
" <th>low</th>\n",
" <th>close</th>\n",
" <th>volume</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1627776000</td>\n",
" <td>41447.0</td>\n",
" <td>41758.0</td>\n",
" <td>41119.0</td>\n",
" <td>41734.5</td>\n",
" <td>189421227</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1627779600</td>\n",
" <td>41735.0</td>\n",
" <td>41944.0</td>\n",
" <td>41628.0</td>\n",
" <td>41710.0</td>\n",
" <td>119963612</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>1627783200</td>\n",
" <td>41710.0</td>\n",
" <td>41824.0</td>\n",
" <td>41654.0</td>\n",
" <td>41823.5</td>\n",
" <td>57383501</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>1627786800</td>\n",
" <td>41823.5</td>\n",
" <td>42605.5</td>\n",
" <td>41823.5</td>\n",
" <td>42455.5</td>\n",
" <td>334816976</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>1627790400</td>\n",
" <td>42455.5</td>\n",
" <td>42456.0</td>\n",
" <td>42050.0</td>\n",
" <td>42068.5</td>\n",
" <td>177368696</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>235</th>\n",
" <td>1628622000</td>\n",
" <td>45299.5</td>\n",
" <td>45586.5</td>\n",
" <td>45265.5</td>\n",
" <td>45507.0</td>\n",
" <td>110463368</td>\n",
" </tr>\n",
" <tr>\n",
" <th>236</th>\n",
" <td>1628625600</td>\n",
" <td>45507.0</td>\n",
" <td>45848.0</td>\n",
" <td>45351.0</td>\n",
" <td>45631.5</td>\n",
" <td>238544763</td>\n",
" </tr>\n",
" <tr>\n",
" <th>237</th>\n",
" <td>1628629200</td>\n",
" <td>45631.0</td>\n",
" <td>45970.5</td>\n",
" <td>45463.0</td>\n",
" <td>45705.0</td>\n",
" <td>217312875</td>\n",
" </tr>\n",
" <tr>\n",
" <th>238</th>\n",
" <td>1628632800</td>\n",
" <td>45705.0</td>\n",
" <td>45914.5</td>\n",
" <td>45450.0</td>\n",
" <td>45476.0</td>\n",
" <td>160539424</td>\n",
" </tr>\n",
" <tr>\n",
" <th>239</th>\n",
" <td>1628636400</td>\n",
" <td>45476.5</td>\n",
" <td>45640.0</td>\n",
" <td>45278.0</td>\n",
" <td>45598.0</td>\n",
" <td>139980409</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>240 rows × 6 columns</p>\n",
"</div>"
],
"text/plain": [
" unixtime open high low close volume\n",
"0 1627776000 41447.0 41758.0 41119.0 41734.5 189421227\n",
"1 1627779600 41735.0 41944.0 41628.0 41710.0 119963612\n",
"2 1627783200 41710.0 41824.0 41654.0 41823.5 57383501\n",
"3 1627786800 41823.5 42605.5 41823.5 42455.5 334816976\n",
"4 1627790400 42455.5 42456.0 42050.0 42068.5 177368696\n",
".. ... ... ... ... ... ...\n",
"235 1628622000 45299.5 45586.5 45265.5 45507.0 110463368\n",
"236 1628625600 45507.0 45848.0 45351.0 45631.5 238544763\n",
"237 1628629200 45631.0 45970.5 45463.0 45705.0 217312875\n",
"238 1628632800 45705.0 45914.5 45450.0 45476.0 160539424\n",
"239 1628636400 45476.5 45640.0 45278.0 45598.0 139980409\n",
"\n",
"[240 rows x 6 columns]"
]
},
"metadata": {}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "_ENRVsf9639I"
},
"source": [
"## 9. 損益 統計情報出力"
]
},
{
"cell_type": "code",
"metadata": {
"id": "wNfZeft1TFBQ",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "a5b24d2d-cdc7-4a17-c741-7e801bcb4d77"
},
"source": [
"#---------------------------------------------------------------------------\n",
"# 損益 統計情報出力\n",
"#---------------------------------------------------------------------------\n",
"# [params]\n",
"# lst_pnl : 各取引毎の損益額リスト ([注意] 累積損益ではない)\n",
"# start_balance : 開始時残高\n",
"# round_digits : 出力時の小数点以下桁数\n",
"# [output example]\n",
"# [Profit and loss statistics] PF: 2.00\n",
"# [Balance ] Result: 7,179.0 -> 55,518.0 (+673.35%) PnL: +48,339.0 Avr: +452.0\n",
"# [Trade ] Count: 107 PnL: +48,339.0 Avr: +452.0\n",
"# [Profit ] Count: 37 (34.58%) Sum: +96,696.0 Avr: +2,613.0 Max: +18,497.0 MaxLen: 4 (+1,316.0)\n",
"# [Loss ] Count: 70 (65.42%) Sum: -48,357.0 Avr: -691.0 Max: -3,477.0 MaxLen: 8 (-2,318.0)\n",
"# [Max risk] Drawdown: -37.82% (-3,930.0)\n",
"#---------------------------------------------------------------------------\n",
"lst_pnl = [random.randint(-800, 1000) for i in range(100)]\n",
"start_balance = 1000\n",
"du.Tool.print_pnl_statistics(lst_pnl, start_balance, round_digits=0)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"[Profit and loss statistics] PF: 1.29\n",
" [Balance ] Result: 1,000 -> 6,411 (+541.10%) PnL: +5,411 Avr: +54.0\n",
" [Trade ] Count: 100 PnL: +5,411 Avr: +54.0\n",
" [Profit ] Count: 51 (51.00%) Sum: +24,169 Avr: +474.0 Max: +998 MaxLen: 5 (+2,628)\n",
" [Loss ] Count: 49 (49.00%) Sum: -18,758 Avr: -383.0 Max: -791 MaxLen: 4 (-1,144)\n",
" [Max risk] Drawdown: -67.37% (-2,345)\n",
"\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "At8nz6In-B50"
},
"source": [
"## 9. Chartクラス\n",
"DataFrameからチャート作成をサポートするクラス<br>\n",
" * DataFrameからチャートを作成します.\n",
" * X軸同期したサブチャートを設定することができます.\n",
" * DataFrame列をシンプルな設定で可視化します.\n",
" * index walkするアニメーションチャートを作成できます."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "p6ymDsnF-mu2"
},
"source": [
"### 9-1. OHLCVデータ取得"
]
},
{
"cell_type": "code",
"metadata": {
"id": "W9B59LvD-es6",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 490
},
"outputId": "17fdac63-82bd-4d6b-9bbf-b10634e10ee6"
},
"source": [
"import DataUtility as du\n",
"\n",
"start_ut = int(du.Time('2021/01/01 09:00:00', 'JST').unixtime())\n",
"end_ut = int(du.Time('2021/05/25 09:00:00', 'JST').unixtime())\n",
"df_ohlcv = du.Tool.get_ohlcv_from_bitmex(start_ut, end_ut, period=1440, symbol='XBTUSD', csv_path='./bitmex_ohlcv_1d.csv')\n",
"du.Tool.set_unixtime_to_dateindex(df_ohlcv)\n",
"display(df_ohlcv)"
],
"execution_count": 2,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"read csv: 1609459200 - 1621814400 (len=144)\n",
"get df : 1609459200 - 1621814400 (len=144)\n"
]
},
{
"output_type": "display_data",
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>unixtime</th>\n",
" <th>open</th>\n",
" <th>high</th>\n",
" <th>low</th>\n",
" <th>close</th>\n",
" <th>volume</th>\n",
" </tr>\n",
" <tr>\n",
" <th>datetime</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2021-01-01 00:00:00+00:00</th>\n",
" <td>1609459200</td>\n",
" <td>28951.0</td>\n",
" <td>29717.0</td>\n",
" <td>28701.5</td>\n",
" <td>29402.5</td>\n",
" <td>1838861284</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-01-02 00:00:00+00:00</th>\n",
" <td>1609545600</td>\n",
" <td>29402.5</td>\n",
" <td>33430.0</td>\n",
" <td>29028.5</td>\n",
" <td>32185.0</td>\n",
" <td>4616478195</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-01-03 00:00:00+00:00</th>\n",
" <td>1609632000</td>\n",
" <td>32185.0</td>\n",
" <td>34896.0</td>\n",
" <td>31988.0</td>\n",
" <td>33062.5</td>\n",
" <td>4233140121</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-01-04 00:00:00+00:00</th>\n",
" <td>1609718400</td>\n",
" <td>33062.5</td>\n",
" <td>33670.0</td>\n",
" <td>27650.0</td>\n",
" <td>32044.5</td>\n",
" <td>5115041875</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-01-05 00:00:00+00:00</th>\n",
" <td>1609804800</td>\n",
" <td>32044.5</td>\n",
" <td>34600.0</td>\n",
" <td>29936.5</td>\n",
" <td>34107.5</td>\n",
" <td>3831661018</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-05-20 00:00:00+00:00</th>\n",
" <td>1621468800</td>\n",
" <td>36811.0</td>\n",
" <td>42444.0</td>\n",
" <td>34873.0</td>\n",
" <td>40620.5</td>\n",
" <td>3453752671</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-05-21 00:00:00+00:00</th>\n",
" <td>1621555200</td>\n",
" <td>40620.5</td>\n",
" <td>42327.0</td>\n",
" <td>33460.0</td>\n",
" <td>37301.0</td>\n",
" <td>3346306092</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-05-22 00:00:00+00:00</th>\n",
" <td>1621641600</td>\n",
" <td>37301.0</td>\n",
" <td>38885.0</td>\n",
" <td>35244.0</td>\n",
" <td>37446.5</td>\n",
" <td>1880503309</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-05-23 00:00:00+00:00</th>\n",
" <td>1621728000</td>\n",
" <td>37446.5</td>\n",
" <td>38270.5</td>\n",
" <td>31100.0</td>\n",
" <td>34711.0</td>\n",
" <td>2882564071</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-05-24 00:00:00+00:00</th>\n",
" <td>1621814400</td>\n",
" <td>34711.0</td>\n",
" <td>39920.0</td>\n",
" <td>34453.0</td>\n",
" <td>38842.5</td>\n",
" <td>1991029675</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>144 rows × 6 columns</p>\n",
"</div>"
],
"text/plain": [
" unixtime open ... close volume\n",
"datetime ... \n",
"2021-01-01 00:00:00+00:00 1609459200 28951.0 ... 29402.5 1838861284\n",
"2021-01-02 00:00:00+00:00 1609545600 29402.5 ... 32185.0 4616478195\n",
"2021-01-03 00:00:00+00:00 1609632000 32185.0 ... 33062.5 4233140121\n",
"2021-01-04 00:00:00+00:00 1609718400 33062.5 ... 32044.5 5115041875\n",
"2021-01-05 00:00:00+00:00 1609804800 32044.5 ... 34107.5 3831661018\n",
"... ... ... ... ... ...\n",
"2021-05-20 00:00:00+00:00 1621468800 36811.0 ... 40620.5 3453752671\n",
"2021-05-21 00:00:00+00:00 1621555200 40620.5 ... 37301.0 3346306092\n",
"2021-05-22 00:00:00+00:00 1621641600 37301.0 ... 37446.5 1880503309\n",
"2021-05-23 00:00:00+00:00 1621728000 37446.5 ... 34711.0 2882564071\n",
"2021-05-24 00:00:00+00:00 1621814400 34711.0 ... 38842.5 1991029675\n",
"\n",
"[144 rows x 6 columns]"
]
},
"metadata": {}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "I5AjGjtcAFfH"
},
"source": [
"### 9-2. キャンドルチャート表示"
]
},
{
"cell_type": "code",
"metadata": {
"id": "czW1U_Ls_DV-",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 761
},
"outputId": "7b514b34-3fba-4d03-f34d-b14edc9f0cd4"
},
"source": [
"#---------------------------------------------------------------------------\n",
"# Chartオブジェクト生成\n",
"#---------------------------------------------------------------------------\n",
"# [params]\n",
"# df : チャートを作成するDataFrame\n",
"#---------------------------------------------------------------------------\n",
"chart = du.Chart(df_ohlcv)\n",
"\n",
"#---------------------------------------------------------------------------\n",
"# タイトル設定\n",
"#---------------------------------------------------------------------------\n",
"# [params]\n",
"# title : チャートタイトル\n",
"# loc : タイトル位置('left', 'center', 'right')\n",
"# fontsize : タイトルフォントサイズ\n",
"#---------------------------------------------------------------------------\n",
"chart.set_title(title='BitMEX 1D ローソク足', loc='center', fontsize=16)\n",
"\n",
"#---------------------------------------------------------------------------\n",
"# チャートサイズ設定\n",
"#---------------------------------------------------------------------------\n",
"# [params]\n",
"# width : チャート幅\n",
"# height : チャート高さ\n",
"#---------------------------------------------------------------------------\n",
"chart.set_size(width=16, height=12)\n",
"\n",
"#---------------------------------------------------------------------------\n",
"# X軸設定\n",
"#---------------------------------------------------------------------------\n",
"# [params]\n",
"# col : X軸に使用する列名(Noneはindex)\n",
"# grid : X軸グリッド表示ON/OFF\n",
"# converter : X軸ラベルの変換関数\n",
"# format : X軸ラベルの日付変換フォーマット\n",
"#\n",
"# [X軸変換]\n",
"# UnixTimeやdatetimeを指定フォーマットでラベル設定する場合\n",
"# converterにto_date_format、formatに書式を指定する\n",
"# ex) set_x(col=None, grid=True, converter=Chart.to_date_format, format='%m/%d')\n",
"#\n",
"# また、任意の変換関数をconverterに設定することでX軸に適用可能\n",
"# ex) set_x(col=None, grid=True, converter=lambda x: f'{x} sec')\n",
"#---------------------------------------------------------------------------\n",
"chart.set_x(col=None, grid=True, converter=du.Chart.to_date_format, format='%m/%d')\n",
"\n",
"#---------------------------------------------------------------------------\n",
"# Y軸設定\n",
"#---------------------------------------------------------------------------\n",
"# [params]\n",
"# ax : チャート番号(0:メイン, 1～:サブチャート)\n",
"# title : Y軸タイトル\n",
"# grid : Y軸グリッド表示ON/OFF\n",
"# legend : 凡例表示ON/OFF\n",
"# gridspec : 複数チャート時の高さ配分\n",
"#\n",
"# [複数チャートの高さ調整]\n",
"# 各チャートのgridspec値の合計から各チャートの高さ比率が設定される\n",
"# ex) [ax0]gridspec=2, [ax1]gridspec=1, [ax2]gridspec=1の場合\n",
"# ax0 : ax1 : ax2の高さは 2:1:1 となる\n",
"#---------------------------------------------------------------------------\n",
"chart.set_y(ax=0, title='USD', grid=True, legend=False, gridspec=1)\n",
"\n",
"#---------------------------------------------------------------------------\n",
"# ロウソク足設定\n",
"#---------------------------------------------------------------------------\n",
"# [params]\n",
"# ax : チャート番号(0:メイン, 1～:サブチャート)\n",
"# open : open列名 (省略時は列名から自動検索)\n",
"# high : high列名 (省略時は列名から自動検索)\n",
"# low : low列名 (省略時は列名から自動検索)\n",
"# close : close列名 (省略時は列名から自動検索)\n",
"# upcolor : 陽線色\n",
"# downcolor : 陰線色\n",
"# width : バー幅\n",
"#---------------------------------------------------------------------------\n",
"chart.set_candlestick(ax=0, open='open', high='high', low='low', close='close')\n",
"\n",
"#---------------------------------------------------------------------------\n",
"# チャート表示\n",
"#---------------------------------------------------------------------------\n",
"# 設定した内容でチャートを表示する\n",
"# (jupyterなどで使用する場合は事前に「%matplotlib inline」を記述しておく)\n",
"#---------------------------------------------------------------------------\n",
"chart.plot()"
],
"execution_count": 3,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": 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"text/plain": [
"<Figure size 1600x1200 with 1 Axes>"
]
},
"metadata": {}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "_6HgQi86BD35"
},
"source": [
"### 9-3. サブチャートに出来高bar追加"
]
},
{
"cell_type": "code",
"metadata": {
"id": "veXCUSDCA_CM",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 761
},
"outputId": "73d25305-7153-4a2a-af3c-16e2b7c2038e"
},
"source": [
"# Chartオブジェクト生成\n",
"chart = du.Chart(df_ohlcv)\n",
"\n",
"# タイトル設定\n",
"chart.set_title(title='BitMEX 1D ローソク足', loc='center', fontsize=16)\n",
"\n",
"# チャートサイズ設定\n",
"chart.set_size(width=16, height=12)\n",
"\n",
"# X軸設定\n",
"chart.set_x(col=None, grid=True, converter=du.Chart.to_date_format, format='%m/%d')\n",
"\n",
"# メインチャートY軸設定(ax=0)\n",
"chart.set_y(ax=0, title='USD', grid=True, legend=False, gridspec=1)\n",
"\n",
"# ロウソク足設定(メインチャート : ax=0)\n",
"chart.set_candlestick(ax=0, open='open', high='high', low='low', close='close')\n",
"\n",
"#---------------------------------------------------------------------------\n",
"# サブチャートY軸設定(ax=1)\n",
"#---------------------------------------------------------------------------\n",
"chart.set_y(ax=1, title='Volume', grid=True, legend=False, gridspec=1)\n",
"\n",
"#---------------------------------------------------------------------------\n",
"# BAR設定\n",
"#---------------------------------------------------------------------------\n",
"# [params]\n",
"# ax : チャート番号(0:メイン, 1～:サブチャート)\n",
"# y : y列名\n",
"# color : バー色\n",
"# width : バー幅\n",
"# label : 見出し\n",
"#---------------------------------------------------------------------------\n",
"# サブチャート(ax=1)\n",
"chart.set_bar(ax=1, y='volume', color='orange', width=0.8, label='Volume')\n",
"\n",
"# チャート表示\n",
"chart.plot()"
],
"execution_count": 4,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": 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ef/zjHzFixAhs2bIF3/zmN7NaRiQSwWOPPYZx48bhkksuwYYNG6BpWq9JTSIiIqJ0OKFJRERElIUNGzYYP0ciERw+fBj79u1Da2srTjrpJKxduzaj5UydOhWjRo3C3/72N6xYsQKHDx/GrFmzcOutt/b7vAsvvBAbNmxANBrF97///az7v2PHDuzdu7fPx8855xyceuqpqKurM86NeOutt6acpJ05cyZ++tOf4uGHH8bKlSvxwgsvYOTIkVn3KRttbW1GBtFoFB0dHfjss8/wwQcfQFVVHHfccbj//vsHdaX5W265JePzTebLRWref/99PPjgg8YFdebMmYN77rln0BdFCgQCeOqpp7B161Y0NzfjS1/6EtatWzegq7f/13/9Fw4ePIhbbrkFP/3pT9Hc3IyNGzfipZdeyurCVkRERESc0CQiIiLKwiOPPGL87Ha7MWrUKMyePRvnnXceFi5cCKfTmdFyfD4f1q9fj7vvvhuvvPIKZs6cia997Wtpnzd69GjcfffdiEQiAzo0t68LrsSNHTsWp556Km6//XZ0dHTgjDPOwMUXX9xn++XLl+NPf/oTDh48iDVr1mDjxo1Z9ykbgUDAyEBRFJSUlKCiogLz58/Ht771LXz729+GyzWwj7hf/vKXceedd2Y1SXnbbbcN+UWZMvHpp5/itddew7hx43D99dfj0ksvTXmOymw9/PDDeOihh1BaWoqbb74ZP/nJTzJexxN98skn2LBhA6ZOnYrFixdDURSsWbMGs2fPxv33348HHngAQGz72rlzJ8rKyuDxeOByuaDrOiKRCMLhMLq7u3HxxRfjuuuuG/R7IyIiosKl6NmcuImIiIiIiPLSnj17cPrpp6OkpCRny9Q0DX/4wx/w3e9+N6NTKfTluuuuw549e/C73/0OX/7yl02PdXV14fXXX8e+ffuwf/9+1NXVobm5Gd3d3b2W43Q68eSTT+bNnrFERERkD05oEhERERHRkKqursZbb72FhQsXZvwcXdcRDocRjUbhdDrhcrkGtHcoERERFR9OaBIREREREREREVHBcNjdASIiIiIiIiIiIqJMcUKTiIiIiIiIiIiICgYnNImIiIiIiIiIiKhgcEKTiIiIiIiIiIiICobL7g4Ui0AggH/9618YM2YM3G633d0hIiIiIiIiIiIqKKqqoqmpCbNmzUJpaWmf7TihmSP/+te/8Pjjj9vdDSIiIiIiIiIiooL24x//GGeccUafj3NCM0fGjBkDAFi8eDEqKips7g0REREREREREVFhqa+vx/bt2415tr5wQjNH4oeZV1RUYPLkyabHwuEw6urqMH78eHg8Hju6RzZi/rIxf9mYv2zMXzbmLxvzl435y8b8ZWP+uZPudI68KJBFXC7OHUvG/GVj/rIxf9mYv2zMXzbmLxvzl435y8b8rcEqW8Dj8WDixIl2d4NswvxlY/6yMX/ZmL9szF825i8b85eN+cvG/K3DPTQtoOs6otEodF23uytkA+YvG/OXjfnLxvxlY/6yMX/ZmL9szF825m8dTmhaIBQKYf/+/QiFQnZ3hWzA/GVj/rIxf9mYv2zMXzbmLxvzl435y8b8rcMJTQu43W5MnDgx7QlNqTgxf9mYv2zMXzbmLxvzl435y8b8ZWP+sjF/6/AcmhZwOp0oKyuzuxtkE+YvG/OXjfnLxvxlY/6yMX/ZmL9szF825m8d7qFpgUgkgtbWVkQiEbu7QjZg/rIxf9mYv2zMXzbmLxvzl435y8b8ZWP+1uGEpgUikQjq6+u5QgvF/GVj/rIxf9mYv2zMXzbmLxvzl435y8b8rcNDzi3g8/lwwgkn2N0Nsgnzl435y8b8ZWP+sjF/2Zi/bMxfNuYvG/O3DvfQJCIiIiIiIiIiooLBCU0LhMNh1NTUIBwO290VsgHzl435y8b8ZWP+sjF/2Zi/bMxfNuYvG/O3Tl5NaFZXV+Paa6/FnDlzcOaZZ+IXv/gFGhoaAAD//Oc/MXv2bMydO9d0+/Of/2xaxs6dO7FgwQLMnTsXl1xyCf7+97/3ep10bTJZRrYURRn0MqhwMX/ZmL9szF825i8b85eN+cvG/GVj/rIxf2vkzTk029vbceWVV+Laa6/Fli1bEAqFsHLlSmzfvh033ngj6urqMGvWLDz99NN9LmPXrl2477778MQTT2D69Ol45ZVXcM011+DZZ5/F5MmTM2qTyTKy5fF4cOyxxw7ouVT4mL9szF825i8b85eN+cvG/GVj/rIxf9mYv3XyZg/Nxx9/HDNmzMCll14KRVHg8/mwbt063HjjjQCA+vp6TJgwod9lbN68GUuWLMH06dMBAPPnz8dpp52GJ598MuM2mSwjW7quQ9M06Lo+4GVQ4WL+sjF/2Zi/bMxfNuYvG/OXjfnLxvxlY/7WyZsJzVdffRVz5841/c7pdBo/p5vQPHz4MPx+P84++2zT7+fNm4c9e/Zk1CaTZaSTeJ6EUCgEVVURCoXw6aefor29HZqmAQAikQiCwaDpeaqqAohtAMFgENFotM+28ddJbhuNRhEMBo2NZ6BtASAYDCISiaRsq6pqn201TUMwGDTea7wGiXXJpm28Lsltk+uSqm1/NRzqesfr0tXVhU8//RRdXV2DqndiXXJV70gkkpN6D6aGua73QNbZeNu+aphtvRNr2N7ejk8//dTIYaD15hhRmGNEfPuPt8+mhhwjCn+MiP//39HRkXENOUYUzxgRzz8QCAxJDTlG5PcYEQgEjP//B/M5gmNE77aFMEYk5m/XOssxwr4xIj7+d3V1mdoOxXcNjhEDq+FQjhGJ8z/5MB9RqGNEJvJmQtPv92PEiBFYuXIl5s2bhwsuuABbtmwx3nh9fT3a29uxbNkynHvuuVi4cKHp8PP6+noAQHl5uWm55eXlxmPp2mSyjHTi5/wEgNraWjQ3N8PtdmPs2LGoq6szVsz29nZUV1cbbQ8fPoympiYAsZXH7/eju7sbANDR0YGqqirTez1y5AiA2Arh9/uNwTIQCMDv95v6k9gnv9+PQCAAIPZF2+/3GyvTkSNHTO+zqqrK+BLW3d0Nv99vbDhNTU04fPiw0ba6uhrt7e0AYiu33+83smtubkZtba3RtqamBq2trQBiK6zf7zc2pNbWVhw6dMhoe+jQIbS0tACIbRh+v99Y4dva2lBTU2OqYXNzs6mGfdW7rq7OqGFyvZNrWF9fj8bGRgCxAcTv96Ozs9PUNr6hNzY29qp3KBTC+PHjEYlEetW7rq4uZb2Ta9jU1GRqW1NTg7a2tpRtW1paetU7XsNwOGyqd0tLi6mGtbW1Rtt4f+M1TK53XV2dsc4mt01eZxPrnck6m1zv+Drb2dnZq96J62xi2+R1NrneqdbZeNvm5mbT+p1Y7/g6Gx9oW1paeq2z8fU7HA6jrq4OY8aMgdvtRmtra696x9fZ5BpyjCiOMSK+nrjdbgCpx4j+6s0xorDHCLfbjWHDhhnvDeg9RiSusxwjimuMcLvdGD9+PFpaWgb1OYJjRGGOEU1NTRg/fjzcbvegPkdwjOi73kM5RgRWrx/UGNHc3Ayfzwe32z3k3zU4RuTfGOF2u6EoipH5UH7X4BgRk0+fIzKZ/7FyPqJQx4hMKHqe7Ad78sknY/Lkybjjjjtw+umn48CBA7j++utx5plnYsWKFfjlL3+JpqYmrFq1CpMmTcIHH3yA6667DsuXL8eiRYvw4YcfYuHChXjvvfdQUlJiLPeNN97ADTfcgHfeeSdtm23btqVdRl+qqqpw77334vrrrzcOVw+FQnA4HHC73dA0DeFwGB6PBw6HA5FIBJFIBD6fD0AsWEVR4Ha7oes6QqEQ3G43nE5nyrZA7NwMyW2j0ShUVYXX64WiKANuC8RWTJfLBZfL1autqqrQdT1l2+T3qqoqNE2D1+s16uJ0OjNum2kNU7Xtr4ZDXe90Ncy23ol1yVW9I5EIotHooOs9mBpaVe/+1tl4275qmG29+6vhQOvNMYJjBMcIjhEcIzhGcIzgGMExwpoxouvODfCt/v84RnCM4BjBMYKfI2wYI+rq6rBhwwasWLECU6ZMQV/yZkJz/vz5+OEPf4grr7zS+N3//M//YM2aNdi3b1/K5zz88MPYvXs3duzYgSNHjuCb3/wm/vSnP6GystJo8/TTT+Oxxx7DSy+9lLbN9u3b0y6jL/EJzZtuuqnXxYOi0Sg6OzsxfPhw02H0JAPzl435y8b8ZWP+sjF/2Zh/YQusXo/SNbcM+PnMXzbmLxvzH7zq6uqMJjTz5pDz0047zXT8flx8tjjVvKumaVAUBQAwduxYzJw5E2+88Yapzd69ezFnzpyM2mSyjIFQVRWHDx/O6lwAVDyYv2zMXzbmLxvzl435y8b8ZWP+sjF/2Zi/dfJmQvPqq6/Gtm3b8NZbbwGInatg8+bNWLhwIQBg6dKlWLdunXFegQ8++ADbtm3DpZdeaizjqquuwqOPPooDBw4AAHbv3o0333wTV1xxRcZtMllGtrxeL77whS8Yu9GSLMxfNuYvG/OXjfnLxvxlY/6yMX/ZmL9szN86Lrs7EFdZWYmNGzfi17/+NWpqajB8+HBcdNFFuOaaawAAa9aswX333YfzzjsPqqqirKwMy5YtwyWXXGIsY8GCBQgEAli6dCk6OztRUVGBhx56yLSLaro2mSwjW4qiGHuSkjzMXzbmLxvzl435y8b8ZWP+sjF/2Zi/bMzfOnlzDs1C1985NMPhMBobGzFu3DjjEHqSg/nLxvxlY/6yMX/ZmL9szL+wDfYcmsxfNuYvG/MfvII7h2ax0zTN7i6QjZi/bMxfNuYvG/OXjfnLxvxlY/6yMX/ZmL818uaQ82Lm8Xh67bVJcjB/2Zi/bMxfNuYvG/OXjfnLxvxlY/6yMX/rcA9NIiIiIiIiIiIiKhic0LRAMBjExx9/jGAwaHdXyAbMXzbmLxvzl435y8b8ZWP+sjF/2Zi/bMzfOpzQtIDL5UJFRQVcLh7hLxHzl435y8b8ZWP+sjF/2Zh/8Vv77o4+H2P+sjF/2Zi/dTihaQGXy4VRo0ZxhRaK+cvG/GVj/rIxf9mYv2zMP7/1NxmZC8xfNuYvG/O3DitsgWg0iu7ubpSUlMDpdNrdHbIY85eN+cvG/GVj/rIxf9mYf35ZsneT6X4wGjb9buuc5WhbvDyhQdB8H8DI7eZl9If5y8b8ZWP+1uEemhZQVRWHDh2Cqqp2d4VswPxlY/6yMX/ZmL9szF825p9/ppaWGzef02P8nMg5bQqc06YAPp/xs3PalKxfS1VVdN25gfkLxe1fNuZvHe6haQGv14vp06dzdl4o5i8b85eN+cvG/GVj/rIxf9m8Xi9KSnzwer12d4VswO1fNuZvHU5oWkBRFJ4/QTDmLxvzl435y8b8ZWP+sjF/2RRFgaI4oCiK3V0hG3D7l435W4dVtoCqqjhy5AjGjh0Lt9ttd3fIYsxfNuYvG/OXjfnLxvxlY/7FJ7vzcOrQgyG0LV4GoGdSM5vzcFLh4vYvG/O3Dic0LaDrOlRVha7rdneFbMD8ZWP+sjF/2Zi/bMxfNuZfnBLPuXkw0GDcPxhoMH7vnDYFuq4hcqAKzqmToSixy1ZED1RZ21myDbd/2Zi/dTihaQGPx4MpU7I/mTQVB+YvG/OXjfnLxvxlY/6yMf/CZEw6BoMpJyATJy6D0bDpfiJFccChOIzJTJKF279szN86nNAkIiIiIiIi0RIPBw+sXo/SNbeYHt+a1H7tuzuw6pTLLOgZERGlwj8ZWSAYDOLTTz9FMBi0uytkA+YvG/OXjfnLxvxlY/6yMX/ZNC1q3Egebv+yMX/rcELTAi6XC2PGjOGVroRi/rIxf9mYv2zMXzbmLxvzly12lXOFVzkXitu/bMzfOqywBVwuF0aPHm13N8gmzF825i8b85eN+cvG/GVj/rIpR8+fyXNoysTtXzbmbx2OsBaIRqPo7OxENMpDDiRi/rIxf9mYv2zMXzbmLxvzl05PuPUtsHq9Jb0ha3H7l435W4cTmhZQVRU1NTVQVdXurpANmL9szF825i8b85eN+cvG/GXTNM24kTzc/mVj/tbhIecW8Hg8OO644+B0Ou3uCtmA+cvG/GVj/rIxf9mYv2zMXzaHwwHd4YDDwXvHjiUAACAASURBVP2HJOL2Lxvztw4nNC3g4H9mojF/2Zi/bMxfNuYvG/OXjflLpyTcSBpu/7Ixf+uwyhZQVRX19fXc5Vgo5i8b85eN+cvG/GVj/rIxf9l0XTNuJA+3f9mYv3U4oWkBTdPQ3d3Nc6gIxfxlY/6yMX/ZmL9szF825k+63v8Fgah4cfuXjflbh4ecW8Dr9WLq1Kl2d4NswvxlY/6yMX/ZmL9szF825l/8Vp1yWZ+PKYoDDocTisL9hyTi9i8b87cOR1giIiIiKipr391hdxeIiIiIaAhxQtMCwWAQ+/fvRzAYtLsrZAPmLxvzl435y8b8ZWP+sjF/2TQtatxIHm7/sjF/63BC0wIulwvHHHMMXC4e4S8R85eN+cvG/GVj/vkrsHr9kL8G85eN+Q9MsexdrSiKcSN5uP3LxvytwwpbwOVyYcyYMXZ3g2zC/GVj/rIxf9mYv2zMXzbmL5uiOIwbycPtXzbmbx1OaFpA0zSEQiF4vV44HPxPTRrmLxvzl435y8b8ZWP+sjF/uaIHqgDoQDCE6AE/gJ69NNsWLzc3DgZNvxu5fZM1naQhxe1fNuZvHVbXAuFwGFVVVQiHw3Z3hWzA/GVj/rIxf9mYv2zMXzbmbx8rTinRl5HbN2Hk9k3wPrIRocpJ8D6y0fhdfLLSOW2KcYPP1/MzFQ1u/7Ixf+twD00LeDweTJ06FW632+6ukA2Yv2zMXzbmLxvzt9aSvT17NgWjYdP9rXOWm/eMStorCsj9nlHMXzbmX9hK19wyqOd7PB6UlPjg8Xhy1CMqJNz+ZWP+1uGEpgUcDge8Xq/d3SCbMH/ZmL9szF825m+9qaXlAICDgQbTz3HxvaCiB6pMe0TFDhHNLeYvG/OXzeGInT+Th5vKxO1fNuZvHY6wFlBVFQ0NDVBV1e6ukA2Yv2zMXzbmLxvzl435y8b8ZVNVFaoaZv5CcfuXjflbhxOaFtA0DYFAAJqm2d0VsgHzl435y8b8ZWP+sjF/2Zi/bJqmIRqNMn+huP3Lxvytw0POLeD1enHcccfZ3Q2yCfOXjfnLxvxlY/6yMX/ZmL9sXq8Xqq+Eh50Kxe1fNuZvHe6hSURERERERERERAWDE5oWCIVC+PzzzxEKhezuCtmA+cvG/GVj/rIx/8IWWL1+UM9n/rIx/6Gx9t0ddnchI6FQCMFgN/MXitu/bMzfOpzQtIDD4UBZWRmvcicU85eN+cvG/GVj/rIxf9mYv2wOhwNOp5P5C8XtXzbmbx2eQ9MCbrcb48aNs7sbZBPmLxvzl435y8b8ZWP+sjF/2dxuN9xuD9xut91dIRtw+5eN+Vsnr6aMq6urce2112LOnDk488wz8Ytf/AINDQ3G4zt37sSCBQswd+5cXHLJJfj73//eaxm5aJPJMrKhaRqCwSCvciUU85eN+cvG/GVj/rIxf9mYv2yapkHTBn+V88Ge+oLswe1fNuZvnbyZ0Gxvb8eVV16JefPmYc+ePdi9ezdcLhe2b98OANi1axfuu+8+/OY3v8GePXtw1VVX4ZprrkF1dbWxjFy0yWQZ2QqHw/D7/QiHwwNeBhUu5i8b85eN+cvG/GVj/rJlmn+hnBOSshMOhxEMhrj9C8XxXzbmb528mdB8/PHHMWPGDFx66aVQFAU+nw/r1q3DjTfeCADYvHkzlixZgunTpwMA5s+fj9NOOw1PPvmksYxctMlkGdnyeDyYMmUKPB7PgJdBhYv5y8b8ZWP+sjF/2TLNn3tgFSdu/7J5PB74fF7mLxS3f9mYv3XyZkLz1Vdfxdy5c02/czqdAIDDhw/D7/fj7LPPNj0e35szV20yWUY6ibPwoVAIqqrC4XDA6/UiHA4bux1HIhEEg0HT81RVBQDouo5gMIhoNNpn2/jrJLeNRqMIBoPQdX1QbQEgGAwiEomkbKuqap9tk3exVlXVdIWvUCiUVdt4XZLbJtclVdv+ajjU9Y7XRdM0lJSUGM8daL0T65KrekcikZzUezA1zHW9B7LOxtv2VcNs651Yw3A4DK/XC4fDMah6c4wozDFC13UoigJFUbKuIceIwh8jHA4HXC6XUYdMasgxYnDrrK5rpkO8NE0Djr4moEPTogD0hLbRPuutadFBjREOhwMlJSWIRCL91lDTogOqIceI/B4jVFVFSUkJHA5Hv/XWdS2rGhb7GBHfPhPrvWTvJizZ8wCW7NmEj9pqsGRPz/0lezdBVVW0LV6GtsXL0bZ4OaL/+0nC/WWx5R4dBvobI3L5OSISiUBRFDgcjt51OeA/eqsCgkHjfryGsb4vS3ovPe+HY0T+jxEOhwOKohjvbSi/a0gbIwrhu0bi/E8+zEcU6hiRibyZ0PT7/RgxYgRWrlyJefPm4YILLsCWLVsQiURQX18PACgvLzc9p7y83HgsF20yWUY6ief8rK2tRXNzMyKRCBobG+H3+40Vs7293XQY++HDh9HU1AQgtvL4/X50d3cDADo6OlBVVWW0ra+vx5EjRwDEVgi/34+uri4AQCAQgN/vN/UnsU9+vx+BQAAA0NXVBb/fb6xMR44cMb3PqqoqdHR0AAC6u7vh9/uNDaepqQmHDx822lZXV6O9vR1AbOX2+/3GStvc3Iza2lqjbU1NDVpbWwHEVtjE3bFbW1tx6NAho+2hQ4fQ0tICILZh+P1+Y4Vva2tDTU2NqYbNzc2mGvZV77q6OqOGyfVOrmF9fT0aGxsBxAYQv9+Pzs5OU9v4ht7Y2Nir3u3t7Thy5Ag6Ojp61buuri5lvZNr2NTUZGpbU1ODtra2lG1bWlp61Ttew+Td31taWkw1rK2tNdpGIhFTDZPrXVdXZ6yzyW2T19nEemeyzibXO77OdnZ29qp34jqb2DZ5nU2ud6p1Nt62ubnZtH4n1ju+zsYH2paWll7rbHz9jte7oaEBkUgEra2tveodX2eTa8gxojjGiPb2dtN7TTVG9FdvjhGFPUZEIhHU1tamHSPi6yzHiMGPEWqKD8bx9SG27FDCh+ioqW3yGBEMhgY1RkQiEWO96u9zRDAY6vdzRCZjxNp3d3CMOMrKMWLNO/9lqmHiGFFbW4sjR44gEon0+zlCVSMcIxLqHd9ck8eIclcZjvUdA5/Tg8nDxqDcWYYpw8ca9dY0Dc5pU+CcNgWaxw1t0gQ4p00x+mRMlPYzRuTyc8Thw4eNL/GJ9R65fRP0B+5C3crrMXL7JjhPnIH2u1cgcO9tscd0PVavKcfG+u/zIlQxrue96To/RyD/x4hIJIKqqipjWx7q7xqSxohC+K6RyfyPlfMRhTpGZELREz/l2ejkk0/G5MmTcccdd+D000/HgQMHcP311+PMM8/EggULsHDhQrz33nsoKSkxnvPGG2/ghhtuwDvvvIMPP/xw0G22bduWdhl9qaqqwr333ovrr7/eOFw9FArB4XBA0zRUV1ejvLwcpaWlxp5akUgEPp8PQCxYRVHgdruh6zpCoRDcbjecTmfKtkBsV+bkttFoFKqqwuv1QlGUAbcFYiumy+WCy+Xq1VZVVei6nrJtfK80j8cDh8MBVVWhaRq8Xq9RF6fTmXFbh8MBt9vdq21yXVK17a+GQ13veF00TcPhw4cxYcIE4681A6l3Yl1yVe/4h6zB1nswNcx1vQeyzsbb9lXDbOudWMNAIICGhgZMnjzZeA8DqTfHiMIcI7q6ulBbW4tJkybB5/NlVUOOEYU/RqiqiurqalRUVKCsrCyjGnKMGPg6e9WbW1A5fCx0HajqOoKppeXQNA1VnY3YOvfnaFu8DErlJDgcDkQPVMMxdRJ0XYfD4UT0QBV8j240j9+r12H4f9wy4DFCURTU1NSgoqICHo+nzxp23rEeZWtXZF3DxLZr392Bm0+8kGOExWPE+n/twuqvXJ5yjAgGg2hoaMCkSbH1rK96r3nnKdw6+6K+P0esXofSNbeKGSN+/b+7sOqUy031XrJ3E6YMGwtFUeDvbETl8HHGERD+zkb8n69dg66f/gJA7GgIBIOAz3v0vg7vIxux7K1Hj96NffUNaip8To9xf+vcn+f0c0QgEEBdXR0mT54Mj8fTZ70Dq9fDs/IXphq2/2j50clYBdEDfmPcit8v2Xo/P0fk+RgRCoVQXV2NiRMnYtiwYUP6XYOfI/Lvu0bi/M/w4cNtn48oxDGirq4OGzZswIoVKzBlSuyPU6m4+nzEYhMmTMBll12GM844AwBw3HHH4brrrsOaNWvws5/9DEBsdr+ystJ4TkNDAyoqKgAA48ePH3SbTJaRTuJ5EuKhAMDxxx9vahcPP9Xz4ucQHUhbp9NpHKo/mLYA+m3rdrv7bOtwOEz3k9sm1mUwbZPrkk1bK+oN9NQlPsmdKB/qPZgaJrYdTA2Hot6p2vZXw6Gs94gRIzBixAjT++2rrd015BiR+3oPGzbMNP5nU8N8qDfHiOzbJtbF6/X2+v8/39fZQh8jFMWBo2d4MB7v+YUCh8PZZ9vk5TocPX0eaL2T//9PVUOHw2mcloJjROq2+TpGxHNL1dbtdht/yEiUap1NrEWq9TA2mVW8Y8SSvZuM3wWjYdP9rXOWA4j9kSL+uL+z0bQct9uNkds3G/cDq9ejdM0tpjZb5y433V/77g6sOuUy0+9yuX6Xlpaaxv9s6h2beU09bgGKqT3HiN7vNR/GiOT//wuh3vkwRoR/9Z+mbbeQv2vkw/wPUNhjRCby5pDz0047zXT8fpzH48HYsWMxc+ZMvPHGG6bH9u7dizlz5gBATtpksgwiIiIiIiLKnaml5ZhaWg6f02P8HLd1znLjNnPkJNP9+IRntpInM4locNa+u8PuLpBAeTOhefXVV2Pbtm146623AMTOVbB582YsXLgQAHDVVVfh0UcfxYEDBwAAu3fvxptvvokrrrjCWEYu2mSyjGyFQiEcOHDAdL4WkoP5y8b8ZWP+sjF/2Zi/bIWWf2D1eru7UFQyzT95T1IqDoW2/VNuMX/r5M0h55WVldi4cSN+/etfo6amBsOHD8dFF12Ea665BgCwYMECBAIBLF26FJ2dnaioqMBDDz1kOp4+F20yWUa2HA4Hhg0bZhwuQrIwf9mYv2zMXzbmL1uu8k91aCwNvcHW3eFwYORDT8Kx9tYc9ooKBcd/2Zi/bMzfOnkzoQkAZ5xxBp5++uk+H1+0aBEWLVrU7zJy0SaTZWTD7XZnfA5OKj7MXzbmLxvzl435y8b8ZXO73fB4PL3OJWYHTopbj9u/bMy/t1Tnti1WzN86eTWhWaw0TUMkEoHL5eIsvUDMXzbmLxvzl435y8b8ZdM0DbquQdM0W/Lv70I7AHDfwx+ZnxAMom1xz/koR243ty8k+TBpwu1fNuYvG/O3DqtrgXA4jAMHDqS86BEVP+YvG/OXjfnLxvxlY/6yhcNhdHcHbc0/1YV2Ei+245w2xbjB5+v5OY8Vyp6m3P5lY/6yMX/rcELTAh6PB5MnT4bH47G7K2QD5i8b85eN+cvG/GXzeDz4Q8c7zF8oj8cDn8/L/IXi+C8b85eN+VuHh5xbIH5SWJKJ+cvG/GVj/rIx//wTPVAV+yEY7Pk5QeIhtwM9BDf5UN+r3txi3N86Z7n5NQbxOpTfHA4HHA5nr8MNkw/9Tj4cvNc6krR+AIW7jkg6hx7Hf9lylX++n/+2v1NbFPNYlg63f+twQtMCkUgE7e3tGDFiBFwullwa5i8b85eN+cvG/PNLpl+c4ofcRg9UmX7OxtTScui6joMdDagcPg6KouBgoKHXawz2dcha2U1G6tCDIbQtXgZA6XnS1TNNh30fDDQY91OtI4nrR/w+5T+O/7JJyj9x/OJYFiMpf7uxuhaIRCJoamrCsGHDuEILxPxlY/6yMX/ZmL9suq5D1zXoug5FUdI/gWyXbm+j7Okpf5v4ZT8YDZvuU3Hg+C9bseWf73uK5ptiyz+fsboW8Pl8+MIXvmB3N8gmzF825i8b85eN+cvmcDjgcPY+5JjyW397GyVPaqb6kp+4J3CqQ6y3Jr1eoUwUSDpcPBc4/svG/GVj/tbhJywiIiIioiIWWL3e7i7QEFr77g67u0BERGQ5TmhaIBwOw+/3IxwO290VsgHzl435y1Zs+fNLc3aKLX/KjqZpxq0QSJv0HOrxLBwOIxgMcvsXiuO/bOFwGLf/323MXyhu/9bhhKYFFEWB1+vl+ZOEYv6yMX/ZmL9szF82RYldCobxy6QoChwOJe32XwiHm1P2OP7LFtv+HQWTv7Q/aA01bv/W4Tk0LeB2uzF+/Hi7u0E2Yf6yMX/ZmL9szH9gCuWcgukoigOKwwFF4f4DErndbng8Xrjd7pwvO5OrrQM95/7khYesx/Ffttj27xmS7b/QGFczDwZTXtm8bXHCuYmDQdP9xHMSFxJu/9bhhKYFdF1HNBqF0+nkLL1AzF825i8b85eN+Q+Nwrk4iX70Itc6Yvtq5k4mE1r9fUkECveLYqEY6qvcxy9YBKS/gFGqPxK0PTyQq7abpVoPfU6PcV/yesjxX7bY9q8P2fZfKNJdJC3OOW0KgNjkZ+LPhYrbv3U4oWmBUCgEv9+PyspK+Hw+u7tDFmP+sjF/2Zi/bMxfNk3ToWlRaJoOhyO7LzSJE0XJk5XZSPUlMX6fhlYoFEJ3dxDuUChvt3/TepBi76l0k5G4embaidVMFdvepBz/ZYtt/90I5fH2X6zy4Y+e3P6twwlNC7jdbhx77LHc5Vwo5i8b85eN+cvG/GVTFOXoIecD2zsjcWIoedIoce87oHgO0y8mbrcbXm/+HnKavGdkX5MAg50Uz2QPrXR7kxYijv/Fr791Nbb9pz/lRD5MvlHucfu3Dic0LeB0OlFaWmp3N8gmzF825i8b85eN+WemWA+fVhTFuJE8TqcTI++6ze5ukE04/suUvHf91X990PT4fQ9/ZH6CBeeMLJY/EhQSbv/W4YSmBSKRCDo6OlBWVgaXiyWXhvnLxvxlY/6yMf/MZXLYaqEdPm3lOdT4ZTX/cPsfmGJZl5l/8cn0YlwAYqdOjt+Shv/k/7+K4ZyRZMbt3zqsrgUikQgaGxtRUlLCFVog5i8b85et0PLnX/Fzq9Dyp9zSdR26NnQXhaHsWH1lcG7/vUk6tJb5F6dML8YVDAbxH39/Cnecush0DsVcXIyL8h+3f+uwuhbw+XyYMWOG3d0gmzB/2Zi/bMWQf7qLk6Q6fAoJH97z8VBgqxRD/jRwDocDDqcTDoej12PpLsYCFN9FUvLBYK8Mng1u/7JZmT/Pw5h/fD4fhg0bZtsFYQby2W2oD32XhOO/dTihSURERP3q7+IkAA+fosxxL+DMLsZSjBdJISIi6/CzG0nACU0LhMNh1NfXo6KiAh6Px+7ukMWYv2zMXzbmLxvzl03TNOOWai9NKxhfTFPsBZp8YSXuoZNbhbb9cw+/3Cq0/Cm3wuEwgqEgwuFwweafbi/PXJ+mo5hw+7cOJzQt4nQ67e4C2Yj5y8b8ZWP+sjH/3Olvci6OX6x6JE5IptoLtG3x8pzvocNDX824/cvG/GVTkq8GVIDS7eXJown6xu3fGpzQtIDH48HEiRPt7gbZhPnLxvxlY/6yMf/cSTc5B+TfFyuHw2HcSJ7Bbv/pJvATJ+w5gZ9/8mn8z4fxUBqPxwOv1zugvfN47vLCl0/bf7HjhKYFdF03DjfiVS7lYf6yMX/ZmL9szF86HdCP/lsEe+pQdgaz/aebwN+a1J4TVvmH479suq4bt4Hkz/NfFjZu/9bhhKYFQqEQ/H4/KisrbbvSGdmH+cvG/GVj/rIx/+KTvKdMMBqGz9mzB47pnGK6jmBUxcGOBoBfaArOYCcIuf3LxvxlC4VCuHz4lxEKhcTkzz+q9OD2bx1OaFrA7XZj4sSJcLvddneFbMD8ZWP+sjF/2Zh/cUreWyZxTxqgZ1IzGo1izbv/hdWnXN7vubR4zsnilKvtn+tHYeL4LxvzHzqFsEc687cOJzQt4HQ6UVZWZnc3yCbMXzbmLxvzl435y+Z0OuFyunhhgCLW35fqfNr+8/3LfzHKp/wzwQt65Vah5Z/PUh0Zkfi7rXOWo23x8oQGQfN9WH9eUeZvHU5oWiAajSIQCKC0tJQfagVi/rIxf9mYv2zMX7ZoNIpIJIJoNMr8c6gQ9s4BuP1Lx/xl6y9/03ku01z0ixf8ikl3ZAQA03lEk88xajVu/9bhhKYFVFVFXV0dKisruUILxPxlY/6yMX/ZmL9sqqoiHA5DVVXmb7F82NuM279szF+2vvJP3lMw5UW/5vTsXZjqDzhtD5v3PqT8w+3fOpzQtIDX68WMGTPs7gbZhPnLxvxly6f8C2WvpmKST/mT9bxeL4YNK4HX67W7K2QDbv+y2Z1/4iG5yYfoAsB9D39kfkLSYbpWH6JrtaH+o4fd+ZO9mL91OKFpAYVXthSN+cvG/GVj/rIxf9li+StcD4SyMnf+sSr/5MN2n3hYbvIhuwB6HZabeMguDU6u8h/KbZuHvg+dfNj+peCEpgXC4TAaGhpQXl4Oj8djd3fIYsxfNuYvG/OXjfnLFg6HEQqFEA6Hmb9A3P5lG2z+xuRSiomm5AueSNu7shDk+/afi0Pfs2X3aUCslO/5FxNOaBIRERER5SnufUckS+JkU6qJprbFy7l3JREROKFpCY/Hg0mTJtndDbIJ85eN+cvG/GVj/vbJh0lAj8cDr9fLvTOE4vYvG/OXjfnLxvytwwlNC+i6bvzM8ynIw/xlY/6y2Z1/uosCJJ5TC4idK2ntuzuM+/FJIZ5DaWDszj9fpFsPAZjWq2JZz2L569B1XXT+UhXL9t/foc9AcW67uVAs+dPAZJq/pMOwJeH2bx1OaFogFArB7/ejsrISPp/P7u6QxZi/bMxftnzIv7+LAiTvxZbqHEnpzqHU9nDSubzIkA/554v+1sPEdQzIzbm68kEoFEJXVzdCoVBR5G9nLukmxbfOWW4+r2AenFOwGLb/dIc+b01qXyzbbi4UQ/40cMw/O8X2hxPmbx1OaFrA7XZj/PjxcLvddneFbMD8ZWP+sjF/2Zi/bG63Gx6Ph/nnSLorNmfCyi/F3P5lY/6yMf/Mpf3DSQH+0ZP5W4cTmhZwOp0YOXKk3d0gmzB/2Zi/bMxfNuZfmHK1p4jT6YTL5YLT6RySfpJZvn0p5vYv21Dnbxqb0oxVhbBHW7Hh9i8b87cOJzQtEI1G0dXVhWHDhvFDrUDMXzbmLxvzl435F55cTopFo1FEohFEo1HmL5DE7T/f95qy0lDmn3wKhXRjFU8XYz2J2z/1YP7WcdjdAQlUVUVtbS1UVbW7K2QD5i8b85et2PLnl9XsFFv+lB1VVREOhZm/UNz+ZSu2/AOr19vdhYwlXtzQLsWWP2WH+Vsnb/bQ/Oc//4nLLrsMY8aMMf1+1apV+Pa3v5328bidO3fiscceQ3t7O8rLy/HLX/4Sp556quk56dpksoxseL1eHH/88XA4OH8sEfOXjfnLxvxlY/6yeb1elJSUwOv12t0VskGxbf+8GnN2ii1/yg7zl435WydvJjTr6uowa9YsPP300wN6HAB27dqF++67D0888QSmT5+OV155Bddccw2effZZTJ48OaM2mSwjW4qicFdjwZi/bMxfNuYvG/OXTVEU40bycPuXjfnLVmj5p/uDBY/QyU6h5V/I8mbKuL6+HhMmTBjw4wCwefNmLFmyBNOnTwcAzJ8/H6eddhqefPLJjNtksoxshcNh1NbWIhwOD3gZVLiYv2zMXzbmLxvzly0cDiMUCjH/LOXD4aK5wO1fNuZf2AZ7iD3zl435W6doJjQPHz4Mv9+Ps88+2/T7efPmYc+ePRm1yWQZ6SSutKFQyDhvQiQSQSgUgqZpxv1gMGh6XrytrusIBoOIRqN9to2/TnLbaDSKYDAIXdcH1RYAgsEgIpFIyraqqvbZVtM0BINB472qqopQKGSqSzZt43VJbptcl1Rt+6vhUNc7XpdoNGrcBlPvxLrkqt7x9XKw9R5MDXNd74Gss/G2fdUw23on1jCx/oOpN8eIwh0jVFUdUA1zNUbouh6rSawpdF0zapRc73j/sxkj4guOLTdqtNV1LeEx2WNEX58Ncjkm5/sYYayHRyWvh8lt+6u3rmuWjBGaFh30GKFDN60DuVxns2nrXXVDr3XWGBSgH912e7blnsey+xyh61rW9V6yd1PstucBLNmzCR+11WDJnqP3926KLxgHO+pxMNAQu2JzRz0OdjTErtyso1c2sfdg7xgRDoeN1x3M5wgpYwQ/R6SuIaCnrWF8fc+m3snbPaAby0lVb02L5vV3jdj4ERszYmNIbDxZsncTIpEI2hYvQ9vi5UdvyxD930+Mn9sWL+u1zsbrklxDTdOM+kLH0b6nXmdVVe213Fx81zBnpSfcYvcT28Y+//V8Fkv8PJiPY4Sua2nHiL7qrWlRU10S1287xoj4up8P8xFD/V1jqOYjMpFXE5rt7e1YtmwZzj33XCxcuNB0eHkmjwNAeXm5abnl5eXGY+naZLKMdBoaGoyfa2tr0dzcDI/Hg/Hjx6O2ttZYMdvb21FdXW20PXz4MJqamgDEVh6/34/u7m4AQEdHB6qqqkzv9ciRIwBiK4Tf70dXVxcAIBAIwO/3m/qT2Ce/349AIAAA6Orqgt/vN1amI0eOmN5nVVUVOjo6AADd3d3w+/3GhtPU1ITDhw8bbaurq9He3g4gtnL7/X5jpW1ubkZtba3RtqamBq2trQBiK6zf7zc2pNbWVhw6dMhoe+jQIbS0tACIbRh+v99Y4dva2lBTU2OqYXNzs6mGfdW7rq7OqGFyvZNrWF9fj8bGRgCxAcTv96Ozs9PUNr6hNzY29qp3KBTC5MmTEYlEetW7rq4uZb2Ta9jU1GRqW1NTg7a2tpRtW1paetU7XsNwOGyqd0tLi6mGtbW1Rtt4f+M1TK53XV2dsc4mt01eZxPrnck6m1zv+Drb2dnZq96J62xi2+R1NrneqdbZeNvm5mbTU3RSHgAAIABJREFU+p1Y7/g6Gx9oW1paeq2z8fU7/te5cePGwePxoLW1tVe94+tscg05RhTHGBEOhxEMBuF2uwGkHiP6q3cuxojkiUdVjSAUDpnaxmsY7382Y0RcJBJN+kASNrZVqWOEx+NBSUmJKfPkMSJxnS3EMeLafQ/hZ3s3Y8neTbjm//4f/OTNTcYE1bX7HjLW2YOBBhzsqEcwEj7689HJqBT1jveprzEiGAxZMkYEg6FBjREejwc+rw/Nzc2D+hwxVGNE/DVjY0TPthuJREyTzdl8jgiFQgP6HFE5fCzKnWWYPGwMfE4Pji05BuXOMqPtHVP/DWuPX4itc5bjhBHH4paK7+A/T7kSW+csx8aTr+i1zobDPV8S7Rojjhw5gsmTJ8Pj8Qzqc0ShjxFSP0fEvwN6PJ5BfY6IP7e/MSJes2zGiFgdQwkTSTpCoZ6JjeTvGsFgKK+/a2i6jgmeUZhaWg6fw4NyZxkmDRtt1FvTNDinTYFz2hREJlZA83qM+5qm9Roj4pLHiMSJJN2YbEavens8HoTDYSPzXH7X0DTzH/Xit3iOpjE5bM44GAxCP/p5MB/HCFVV044R8XonjxGJk4fx/9fi793qMcLj8WDChAn9zv9YOR8x1N81hmo+IhN5cw5NRVHQ1NSEVatWYdKkSfjggw9w3XXXIRqNYtGiRWkfd7libyX5xKuKohjhpmuTyTLSSZwMnThxorEsl8uFyspKeDweAMCIESMwbNgwo+2ECROMcyw5nU5UVlYaX4DLyspQUlJitK2oqDB+djgcpralpaWorKxM2R8AprbDhg1DZWWl0cexY8ea2k6ZMsWoSUlJCSorK41zQYwZM8ZUk8mTJxttfT4fKisrjfujR4/GqFGjjLaTJk0yluP1ek11GTVqFEaMGGG0PfbYY43+ud1uU9uRI0di+PDhphrG2ybXMLne48eP77PepaWl8Pl8KeutKErKeseXNW7cuF71jtchm3on13DMmDGmLxeTJk3qs+0xxxyDkSNHpqy3x+Mx1fCYY44x1bu/dTa53uPHj+/Vtq91dvz48cbPqdbZxHonrrPJ9R4+fHjG9U5eZ8eOHZt2nY23HT16dJ/1jq+z8T4l1ztxnU2u96hRo1BW1vMFjWMExwgrxgiHwxHrb2fgaJ1ccOkuINLRq97x/mczRsSnQVwuJ5xOh7GPgNfrgXb0fXOMKN4xwuFwYGrZOAAKNE1DVWcjppbGnnOwox5lZWXYOme5sbfyr/93F1adcrmx53L8/STWO96nvsYIn8+LkqP3h3KM8Pm8xrrX5xhRV7hjROjoa8bGCK+x7bpcLmgJn4WNMaIm/ecIr9cL3zHHGMvJ6HPEp7G6+Hw+ow4upwtOnxPoChhte2qItGNEyONOWe/EMWLVKZf1OhyQY0QMP0fkz+eI+HP7GyPUo++1z3o39a53rI5eY7mKosDr9ZhqmFjviM+b1981HIpiPAYFpvGktLQUnQ4HogdiE3Iu6EAofPS+DofDgdLSUrQtXg5Ax3gA0WAIbYuXo/ToyNgGBbh6pmm5CuLjFox6WzFGOBwOOBL+v9QdDqNOiqJg0qRJwNG5JK/HC0Xtydjn80E5+nkwH8cIt9ttWnaqMUL53/cA9B4jvN7Y+qyh5/+1+Psp5jEiH75rDMV8ROLkaX/yZkLznnvuMd0/+eST8aMf/Qg7d+7EokWL0j4e/6DT0NBg2oAaGhqMFSBdm0yWkU48GADGVS2DwSCqqqowZcoU06Cc+B9K4vPig01cNm2dTqfpBLQDbQug37bGfxgp2hpfnvtom3i1z8G0Ta5LNm2tqDcQq0swGMTnn3+OKVOmmJ6bD/UeTA0T2w6mhrmud19t+6vhUNYbAPbv32/kn8/rLMeI3NdbVVVj/Pf5fFnVMFf1Ni5KosTvO4wP30B223KqGoYQ/6AcW27UWJYDgPlDdF/LLdYxIvH//7h8X2ezHSNiK1PPxJhp5VIU43V7lht7PN062992X7Z2hfHzUI4RDkdPLQZS72AwiK6uLmiaZjyey3V2sOt3fNsFFDgcTkQTtmVjwEhRl/5qqCgO47WyqXesDz2vmXwxJfN7Tb9+h5WeL/d2jRHBYBCffPJJr89/hf7/Gj9HZNZW0zTT//8DrXfy+p6qhhGlZwIl03rHt/vE+4riSNk2Ph4mTuokyofvGlAU005JiT+7XC6M3L7Z1OfA6vUpL4TjnBabA4geqIJzWs//3fHJUNOOT4r5fmJdEv//d7lcOV2/zVkpCbfY/V7fRRImrRM/D+bjGKEoDlP71G1Tf45IXp8T71s9RiTmP5jPEZm0tfNzRNxQjbOZyJtDzlPtAalpmvFhJt3jY8eOxcyZM/HGG2+Y2uzduxdz5szJqE0myxgIl8uFcePGmQddEoP5y8b8ZWP+sjF/2VwuF9weN/O3Qbor9lqB279szF825i8b87dO3kxoLl26FOvWrTPOG/DBBx9g27ZtuPTSSzN6HACuuuoqPProozhw4AAAYPfu3XjzzTdxxRVXZNwmk2Vky+Vy4ZhjjuEKLRTzl435y8b8ZWP+srlcLrhdnNCUitu/bMxfNuYvG/O3Tt5UeM2aNbjvvvtw3nnnQVVVlJWVYdmyZbjkkksyehwAFixYgEAggKVLl6KzsxMVFRV46KGHTId6pWuTyTKyFY1G0d3djZKSEtNuuyQD85eN+cvG/GVj/rJFo1Hjxvzl4fYvG/OXjfnLxvytkzcTmhUVFVi3bt2AH49btGgRFi1aNKg2mSwjG6qq4tChQ6YTAZMczF825i8b85eN+Re2wR62rKoqQqEQVFUt2PyX7N1k/ByMhk33AeC+hz8yPyEYPHphjZiR283tJeH2LxvzHzpr392BVadcZnc3+sX8h06+Zw8wfyvlzYRmMfN6vZg+fTpXZqGYv2zMXzbm31tfJ+IvRsx/YArhy0omvF4vSkpKsj7Bfb4xrlofaDB+jt8H0OvCGfH78YtoSMXtXzYr85fyf2oh4fYvG/O3Dic0LaAkXOWT5GH+sjF/2aTkb5q4CAZ7TWQk7rGVvAcXULx7cUnJn1KLX1E28WrdJAe3f9mYv2zMXzbmbx1W2QKqqqKpqQljxozpdQl7Kn7MXzbmL5uE/JMnI/vaAzNxr63kPbqKlYT8qW+qquKqCXOhqmre5p/ujxFAz56YwWjY+JnS4/YvG/PPneRTXSSf/mLrnNgfSfNprGL+sjF/63BC0wK6riMUCkHXdbu7QjZg/rIxf9mYv2zMX7Z8zz+TP0bEJwqA1Oeta3vYvLe1FQrllAT5nj8NLeafW8mnu0g8FQaQfqyyGvOXjflbhxOaFvB4PKisrLS7G2QT5i8b85et0PK3+wtAsSm0/Cm3mL9szF+2Qsifp4sZOoWQPw0d5m8dTmgSERERERERCSH9dDG8kFJ+Yi6ULYfdHZAgGAzi008/RTAYtLsrZAPmLxvzl435y8b8ZSu0/PlFMrcKLX/KLeYvG/OXjflbh3toWsDlcmHMmDG80pVQzF825i8b85eN+cvG/GVj/rIVWv78g0aMsedpmoukAf1ffKjQ8qfcYv7WYYUt4HK5MHr0aLu7QTZh/rIxf9mYv2zMXzbmLxvzl435F57Ew/BTXiQtqX1/Fx9i/rIxf+vwkHMLaJqGrq4uaJpmd1fIBsxfNuYvG/OXjfnLxvxlY/6y5VP+vOCf9fIpf7Ie87cOJzQtEA6HUV1djXA4bHdXyAbMXzbmLxvzl435y8b8ewusXm93FyzD/GVj/rINdf7RA1XGLX54fPIh8gcDDTgYaDAOjY/faOhx+7cODzm3gMfjwbRp03gOBaGYv2zMXzbmLxvzL3797fnE/GVj/rIxf/vkwx6pQ5l/Jleo3zpnufFzf4fG09Dg9m8dVtgCDocDHo/H7m6QTZi/bMxfNuYvG/OXjfnLxvxlY/6yMX/ZmL91eMi5BVRVRX19PVRVtbsrZAPmLxvzl435y8b8ZSu2/LmHT3aKLX/KDvMvfv2NiVbmzyvU5x9u/9bhhKYFeFJY2Zi/bMxfNuYvG/PvTdKkGPOXjfnLxvxlY/6yMX/rcELTAl6vF9OmTYPX67W7K2QD5i8b85ctV/mvfXdHjnpEVuL2Lxvzl435y8b8Zcun/CX9ITFf5FP+xY4TmkREREVA0tWDiw0nrImIiIiIssMJTQuEQiF89tlnCIVCdneFbMD8ZWP+sjF/2Zi/bMxfNuYvG/OXjfnLxvytw6ucW8DpdGLkyJFwOp12d4VswPxlY/6yMX/ZiiH/JXs3GT8Ho2H4nL2v2nkw0GBqk3hfsmLInwaO+cvG/GVj/rIxf+twQtMCLpcLY8eOtbsbZBPmLxvzl435y1Ys+U8tLQcQm7iM/xy/v3XOclPbte/u4Pm6jiqW/GlgmL9szF825i8b87cOJzQtoGkaQqEQvF4vHA4e5S8N85eN+cs2mPyT94xLvL91znK0LTZPJCEYNP1u5PZNIHtx+5dNSv7RA1U9d4JB833APFYljVMAgKtnDmHv7CMlf0qN+Re20jW3DOr5zF825m8dVtcC4XAYVVVVCIfDdneFbMD8ZWP+sg02/6ml5ZhaWg6f02P8nMg5bYpxg8/X83ORK5QLIHH7l01C/iO3bzLdnCfOMN2PSzVOFftYJSF/6pvE/Avl/2YrSMyfejB/63BC0wIejweVlZXweHqfd4qKH/OXjfnLxvxlY/6yMX/ZmL9szF825i8b87cODzm3gMPhgM/ns7sbZBPmLxvzl435yyYxf54/s4fE/KkH85eN+cvG/GVj/tbhHpoWUFUVjY2NUFXV7q6QDZi/bMxfNuYvG/OXjfnLxvxlY/6yMX/ZmL91uIemBTRNQ0dHB0aMGGF3V8gGzF825i8b85ctV/kHVq8f9AUKyHrc/mVj/rIVS/7GRb7SXfDraBtenDCmWPKngWH+1uGEpgW8Xi+OO+44u7tBNmH+sjF/2YY6/3RXFwaAg4GG2MPRsPEzWYPbv2wS8+fEew+J+VOPYsg/cUIy1R/W2hYvN13cK3qgyrif6vOIJMWQPw0c87cOJzSJiIgKUPKeD6m+bGyd07OnxNp3d/D8htQvriNEREQkHT8PFQ6eQ9MCoVAIn3/+OUKhkN1dIRswf9mYv2zMf2DWvrvD7i7kBPOXjfnLxvxlY/6yMX/ZmL91uIemBRwOB0pLS+FwcP5YIuYvG/OXjfnLxvxlY/49+jsPHwDT6TCK5fQYzF825i8b889vQ70HJvO3Dic0LeB2u1FeXm53N8gmzF825i8b85eN+cvG/GPSnYdva1L7YjnUj/nLxvxlY/6yMX/rcELTApqmQVVVuN1uztILxPxlY/6yMX/ZmL9szH9gimEyE2D+0knJP93FCU1XQg8GAZ/P9HixXgldSv6UGvO3Dic0LRAOh+H3+1FZWQlf0iBOxY/5y8b8ZWP+suV7/kv2mr9IBqNh0+/iF5WKH/5bLIcCWyXf86ehxfxlk5B/JhcnBGC68vn/z967B8lRn3e/3+65rrTS6rLaFWi1qwsgfAm2Y97kmNeyMcTgSqjk5EBRSp3Am5SCwZYMRiE2BEu2JZ8XoWAlx4j4hQB5gVBxcB0pHLtcRZlUImTi5D1l5ER2YhvMalZ7X+19dtWX6e7zx6h7p+eyO7M70z0zz/dTpdL0zjO9v3k+v36255m+5N8VvVmR4J+Uhv6Dgw3NAIjH4+ju7kY8Hg97KCQE6F829C+bcv03yymWxE8jbP/bWhdOiTqfHvWW3cal29QEOE8rpRH8k9pB/7Khf9nQv2zoPzjY0AwAVVXR0tIS9jBISNC/bOhfNkH6L3ZUBAkXbv+yoX/Z0L9s6F829C8b+g8OntAfAJlMBuPj48hkMmEPhYQA/cuG/mVD/7Khf9nQv2zoXzbV8s8vKxsTbv+yof/gYEMzADKZDCYnJzmhhUL/sqF/2dSTf54qHDz15J8ED/3Lhv5lQ//LI33oWNhDqAr03/wsNlfpPzh4ynkAJJNJXHXVVWEPg4QE/cuG/mVD/7Khf9nQv2zoXzb0Lxv6lw39B0fdHKH505/+FO973/vwsY99zPfv+9//vhdz8uRJ3HbbbfjYxz6GO+64Az/60Y8K1lONmHLWQQghhBBCCCGENDs89Z0QUo/UzRGaw8PDeO9734tvf/vbRZ9/9dVXcfz4cbzwwgvYuXMnXnvtNdx77704deoUtm7dWrWYctZRKbquY2hoCFdccQUSicTyEkQaFvqXDf3Lhv5lU8r/3jMnfHGaZfh+9tzu/Zi+a39OgOZfBtD2kn8dpP7g9l+IpKYI/cuG/mVD/7Kh/+ComyM0R0ZGcMUVV5R8/qmnnsLevXuxc+dOAMCtt96K66+/Hi+//HJVY8pZR6W4d7lS1bpJNwkQ+pcN/cuG/mWjqirW/o+/Kep/W2uH9y8ZiXuPc4ls70ZkezeQTHqPI9u7gxo+WSHc/mVD/7Khf9nQv2zoPzjqJsOLNTSHhoaQSqVw4403+n5+00034Y033qhaTDnrWArDMLzHuq7DNE3EYjFs2rQJlmXBtm0A2QvFaprme51pmgAAx3GgaRosyyoZ6/6e/FjLsqBpGhzHWVEsAGia5l3INj/WNM2SsbZtQ9M0772apgld1315qSTWzUt+bH5eisUulsNa59vNi6Io6OzshKqqK8p3bl6qle9MJlOVfK8kh9XO93LmrBtbKoeV5js3h5ZlYdOmTYjFYivKN2tEY9YIVVXR1taGaDRacQ7hON57ccfsPtdoNQJwYNsWAOfyW7MvLxfPobvtlMq349hF811vNSIWiyEWi/o86roOOG4eLjv2lDvec26e3Pean8NqzdnsehfmlpM37/JjWSPKz3csFkNnZyccx6lJneV+RH3vR9i2jc7OTsRisRXtR1Qr39yPCLZGOI6DDRs2IBaLhTZn66FGAA6s3hSs3j5A0y4/vrx8+W/K9F37MH3XfkzftQ/Wf/7i8uPssn8/ory/VfVQI2KxGNra2qAoii+2Fp81WCNw+f1ZJfeZ8nNo2/ai+c7fb6u0RuT2f+qhH1HPNWKxOVsOddXQnJmZwb59+3DzzTfj9ttv904/HxkZAQB0dPiPXOjo6PCeq0ZMOetYitHRUe/x4OAgJiYmPGmpVMqbmDMzM7hw4YIXOzQ0hPHxcQDZyZNKpXDp0iUAwOzsLPr6+rzYkZERXLx4EUB2QqRSKczPzwMA0uk0UqmUbzy5Y0qlUkin0wCA+fl5pFIpbzJdvHjR9z77+vowOzsLALh06RJSqZS34YyPj2NoaMiLvXDhAmZmZgDAe6/upJ2YmMDg4KAX29/fj6mpKQDZCZtKpbwNaWpqCgMDA17swMAAJicnAWQ3jFQq5U346elp9Pf3+3I4MTHhy2GpfA8PD3s5zM93fg5HRkYwNjYGIFtAUqkU5ubmfLHuhj42NlaQ79nZWZimibm5uYJ8Dw8PF813fg7Hx8d9sf39/Zieni4aOzk5WZBvN4eGYfjyPTk56cvh4OCgF5vJZHw5zM/38PCwN2fzY/PnbG6+y5mz+fl256ybw9x8587Z3Nj8OZuf72Jz1o2dmJjwze/cfLtz1i20k5OTBXPWnd9uvufm5mDbNqampgry7c7Z/ByyRjRHjZidnfXlpViNKJVvO6cJ4uYtY2WK5rDea0R2HLr33izL8u285NcITdMWnbOGsbADWM81wrZtmKZZMGdzP5Bl87fQpLTthYZmdqcukxO7kMNq1QjHyb4/y/bvGOfmmzVieTXC9b/S/YjF8s39iPrej3DrwEr3I9w5y/2IxqkRQ0NDGB0d9b6gq+VnjXquEcbxr+DiVw6g7aUTiLznGkwcfgj617+MtpdOoOW5P/fyENneDbvrStjxmHc2gm073px1/156TRDL3/Cptxph2zb6+voKclirzxqsEdm8uc9l9yV1z2N+jdB1fdEakbuPupwaUU7/J8h+RD3XiMX2I8qhbq6hqSgKxsfHcfDgQXR1deHcuXP47Gc/C8uy8P73vx8ACg7ZVRTFE+ce/bKSmHLWsRS5zdArr7wSqqrCMAxcuHABmzdvRjKZBACsXbsWq1at8mKvuOIK7xucSCSCnp4exGIxAMCaNWvQ0tLixXZ2dnqPVVX1xba2tqKnp6foeAD4YletWoWenh7v/ba3t/tiu7u7vZy0tLSgp6cHkUgEALBx40ZfTrZu3erFJpNJ9PT0eMsbNmzAunXrvNiuri5vPYlEAj09PYjH4wCAdevWYe3atV7sli1bvPHFYjFfbFtbG1avXu3LoRubn8P8fG/evLlkvltbWz1P+flWFKVovt11bdq0qSDflmXh3XffRVdXV9n5zs/hxo0bfd8UdXV1lYxdv3492traiuY7Ho/7crh+/Xpfvt05C2S3l8XyvXnz5oLYUnN28+bN3uNiczY337lzNj/fq1evXjLfpeZse3v7knPWjd2wYUPJfLtz1h1Tfr5z52w8HsfmzZsxODiInp4erFu3DmvWrCkr36wRjVEjjpx9BV983//uvS5/zrr/m6aJaDS66JzNz7eqKN57cfPmjqmea0QmJ4e5f0+TyQRUVYV1Oae5z+XXiGQy6fkoViP0eKxovuutRhiGgUzG8m07W7ZsgdKveONPJpPAXNrLqaoqXqx73SXbi13IYVVqxC8BRfHPrUgkkh3TfNrLd34OWSPKqxHuTvuVV17puVzOfkSpGsH9iPrej9A0De+++y56enpWtB+RP7+5H9EYNWLDhg0YHByEYRgFzqv9WaNeaoSG5dUIt3UUjUZg5+wbqKqCjRs3Am8v/L108xCNRBFJRry/VfVWI7Jnkzje763lZw3WCHh5UxQFNtx9yYT3fvJrRCKR8JbdfO/7X88CCgDHgWaZC9c2v/w7jv/xzwE42AzAAABNR/Tzh7AJwDQUtL10wqsR5fR/guxH1EuNAMqvEbnN08Wom4bmY4895lu+7rrrcPfdd+PkyZP4jd/4DQDZ7n7uxjE6OurJdYvYSmLKWcdS5H74dHdeVVVFV1cXksmkr6C4wvNf533AuUwlsZFIxJssK4kFsGisuwEVi3U/jJaKzb0w7kpi8/NSSWwQ+QayebEsy/Nfb/leSQ5zY1eSw2rnu1TsYjmsZb5bW1vR1dWFWCyGSCRS13OWNaL6+U4mk+jq6vJiKskhFMXX9Mt9XM81Il0kFlCgqgvjVRQVykLfriCHqqp6769Yvg1F9WLDrhFHzr6Cgx+601vOzUssFkMymfB9IE4kEnDfvKIo2R1QZeG95yZGUXK/YPXnsFpzNrtexfdaJWcM+bGsEYXvtVS+i/39r+acrYd8cz+idKy7/+/+/Xep5zlbTiz3I8qLXbVqlec/rDlbD/kuJ4c63L+JKrw/iNmf5Pyu8v9W1UONiMViXv1fKjZ/vawRC1QyZ3P3kfL3mQpjVe/9eHlR4F3L/Hx61Hdd8/Pp7BGPke0LPSKrt8+7rnn2Egr+/s8VL53E6q9+YdH92VJ5YY0on7ppaDqO4ytKQPZQYUVR0N7ejmuvvRanT5/G3Xff7T1/5swZ7N69GwCqElPOOpZDJBLxfZghsqB/2dC/bOi/PJr1rt/ZI1HzGtVEDNz+ZUP/sqF/2dB/fVHOfiaw0LjULMN7vBy4/xccddPQvO+++7Bjxw7cf//9aGlpwblz5/Diiy/iwIEDAIB77rkHx44dw+7du7F9+3a8/vrrePPNN3Hq1ClvHdWIKWcdlZLJZDAzM4O1a9f6us9EBvQvG/qXDf2XT/434bnfkrvkfhOee7dv95vxIKis+erA0XRM37UP7lEn9dh4JbWB279s6F829C8b+q8/ltrPdJuaQOHZNwAw/Yz/i/TFyGQyyGRMZDIZ+q8xdZPdw4cP4/jx4/jUpz4F0zSxZs0a7Nu3D3fccQcA4LbbbkM6ncZ9992Hubk5dHZ24umnn0Z398IHmmrElLOOSslkMhgfH8eqVas4oQVC/7Khf9nQf3NSbvPVti3YvX1Qe7qgqpFAG68kfLj9y4b+ZUP/sqH/4PH2sTSt6P5W7j7aSo/AXIpMJgPTZEMzCOomu52dnXj88ccXjdmzZw/27NlT85hy1lEJyWQSV199ddXWRxoL+pcN/cuG/mWjqhE4aiTvuk61odjRBCRcuP3Lhv5lQ/+yof9gyT37JX3oGFoPf8H3/HN58bXeZ0omk8i0rPJdK5LUBnXpEEIIIYQQQgghhBBCCKkP6uYIzWbGMAwMDw9j8+bNBXeSIs0P/cuG/uuXYt/gVptS/oO+ODkJB8exYTs2VMfOu2N58FTjaAQeAVoZrP+yoX/Z0L9s6F82hmFA1zXEDYP+awwbmgGgKApisVjBXdyJDOhfNvQvG0VR0PqXL0A58nDBcyu9ODlpDLjly4X1Xzb0Lxv6r4x6uv5hNaB/2SiK4v0jtYUNzQCIxWK44oorwh4GCQn6lw39yyYWiyEeTyAWi4U9FBICiqJ6/4g8WP9lQ/+yof/yWfL6h7v9d5duhC956V823P8PDjY0A8BxHFiWhUgkwi69QOhfNvQvG8dx4Dg2HMcR77/Zjr4oDyfnX/D+cy9jkH9ZA5fmzHt9wPovG/qXDf3Lhv5lw/3/4GBDMwB0XUcqlUJPTw/vdCUQ+pcN/YdHPXyDr+s6Ll3SENP1FfkP+32slHq7+2RQ2LYN27ah2HbV73Re7nVYF6OcGLJ8WP9lQ/+yoX/Z0H9js9J90Grt/5OlYUMzAGKxGLZs2cJDjoVC/7Kh/+ZjqaPentu9H9N3uY0iBwlNh37PH0O/fIRebnOPNDeqqsJRVahqbU4553VY6xvWf9nQv2zov3Y0wt8y+pdNLBZDIhGn/wBgQzMAIpEIWltbwx4GCQn6lw39Nye5jaP8ppJLZHs3gOyp1rmPiSSUnH9EGqz/sqF/2dB/IflnZzQz9C+bSCSCSCSKSKS6Z+eQQtjQDIBMJoN0Oo3W1lZEo0y5NOhfNvQvm+ytrgBRAAAgAElEQVT1c7L/eGMYWWSb1w4cTYfVm0J+U5PXrmx+WP9lQ/+yoX/Z0L9sMpkMMhkTmUyG/msMsxsAmUwGIyMjSCaTnNACoX/Z0L9sshcFdy5fFDzs0cii2LU6K3l+JbiXFdA0DTNfOoq1X3vYdw2lRrxjK6kc1n/Z0L9s6F829B8e9XAkcCaTgWGwoRkEzG4AJJNJ7Nq1K+xhkJCgf9nQ//KolwbPSpteqhqBo0aqfkMY0hgkk0lkVq1a9gXhZd4Zvnlg/ZcN/cuG/mVD/7JZ6f4fKR82NAkhhBBC6gypd4YnhBBCCCGkHNjQDADDMDAyMoLOzk7E4/Gwh0MChv5lQ//BkX+38fw7kPvvPg5A0/zLqP4dyB3Hhu3YUHkNTZEYhgFd1xA3DG7/AmH9lw39y4b+ZUP/suH+X3CwoRkQqsoPspKhf9nQf3Dk33E8927kLsXuPu4uVxP3pjCKbsA+fwG8KYxUlr54Ko+sbF5Y/2VD/7Khf9nQv3R48fwgYEMzAOLxOLZs2RL2MEhI0L9s6F8mS54uzJvCiCAejyORSPDbeaGw/suG/mVD/7Khf9lw/y84+LVBADiOA9u24ThO2EMhIUD/sqF/2WS9O/QvFPqXDeu/bOhfNvQvG/qXDff/goMNzQDQdR1vv/02dF0PeygkBOhfNvQvG13XMT9/if6FQv+yYf2XDf3Lhv5lQ/+y4f5fcCz7lPNz587hP/7jPzA+Pg5VVbF+/Xq8//3vx/ve975qjq8piMViuOKKKxCLxcIeCgkB+pcN/csmFoshkYjTv1DoXzas/7Khf9nQv2zoXzbc/wuOihuas7OzePrpp9Hb24vVq1ejvb0dAPDuu+/ijTfewM6dO7F37160tbVVfbCNSiQSwdq1a8MeBgkJ+pcN/deGYtelLBfv5j+aVvRGQIvdCb3Su6BHIhFEIlFEIpFljbURWa6XZkSif7IA679s6F829C8b+pcN9/+Co6KGpmVZOHHiBAzDwAMPPIBrrrnG9/zPf/5z/O3f/i2++c1v4k/+5E8o8DKWZSGdTqO1tZU5EQj9y4b+64ulbtbjUuxO6Mu5C7plWbCsDCzLon+BVMs/m8SNCeu/bOhfNhL982/VAhL9kwW4/x8cFV1D84c//CEmJydx4MCBgmYmAOzatQuf//znMT4+jrNnz1ZtkI2OaZoYHh6GaZphD4WEAP3Lhv4bE6u3L9vAvHwUZ34z83x6FOfTo9Asw3t8Pj1asB7TNKHrBv0Lhf5lw/ovG/qXDf3Lhv5lw/2/4KjoCM233noLu3fvxpo1a0rGrFu3Dh/96Efxr//6r7j++utXPMBmIJFI4Oqrr4aiKGEPhYQA/cuG/huPpY7ifG73winoR86+goMfurPkuhKJBFatakEikaj+QEndQ/+yYf2XDf3Lhv5lQ/+y4f5fcFTU0BwYGMAtt9yyZNw111yDt956a9mDajYURWExEwz9y4b+ZZN1zzlQLRa7/qnv2qeXY1Zy/dNqQP+yYf2XDf3Lhv5lQ/+y4f5fcFTU0Jyfny/r4rZtbW2Ynp5e9qCaDcMwMDY2hk2bNiEej4c9HBIw9C8b+m9uFjs6E8j613UdccNY1P9S6yFLHzk7fdd+73qnwMqvf1oNDMPA9L3/55L+g4BzLHhY/2VD/7Khf9nQv2zK3f8nK6eia2jatl3WRU0jkQivF5CH4zhhD4GECP3Lhv79HDn7SthDCBj6r5Rmar5x+5cN/cuG/mVD/5XTTDcWon/p0H8QVHSEJgCkUinMzMwsGjMxMbHsATUj8XgcXV1dYQ+DhAT9y4b+ZROPx5FIJPntrFC4/cuG/mVD/7Khf9nQf3PiO+NnicsfRTUNl/YewKWc58O4/FGzU3FD84UXXqjFOAghhBBCCCGEEEIIqSvym5HFLn8EwHe5o/xLIeVTah2kfCpqaD7wwAO1GkdTo2kaUqkUenp6kEwmwx4OCRj6lw39y0bTNMzPzyOqafRfRYLa+Vvpjia3f9nQv2zoXzb0Lxv6l41tW7BtC4ptQVWXvmQjWT4VNTSvueaaWo2jqYlGo+js7EQ0WvEBsaQJoH/Z0H957D3j/9ZTswzfz57bvd9/F+u8O1gDAD59bS2HuCyi0Sji8Rj9C4Xbv2zoXzb0Lxv6lw39Nz+LfeHt3uWedzmvPVXbwizLwuDgIFpaWtDe3l6t1TYF0WgU69atC3sYJCToXzb0nyW3OZnfrKyESk7jqAei0SiiUTY0pcLtXzb0Lxv6lw39y4b+5eJ+JlF0A/b5ft9zBQdj5B2gwWtsVk5Fn7Bs28azzz6LX/3VX8X111/v/fz8+fN49tlnMTk5CQC47rrrsHfvXn6Au4xlWZifn8eqVavKuks8aS7oXzb0v8C21g4AwPn0qPfYXX5ut/8P/JGzrzTFna4ty4JlZWBZlnj/QVDJxdqLHeVb7R1Jbv+yoX/Z0L9s6F829C8Tdz/SsiykDz2O1sNf9Pmfvmt/wQEZuQdrkMqpqOP4T//0T/jP//xPfPzjH/d+ZhgGnnnmGaiqij/4gz+Apmn4+7//e/zDP/wDbr311qoPuBExTRODg4Po6elhQRMI/cuG/hublV6r0TRN6LqBhGnSf40p92LtS7FY07PShmeQ238zfAHQbLD+y4b+ZUP/sqF/2XD/Pzgqamj+y7/8C37rt34Lu3bt8n525swZzM7O4pFHHsGVV14JAFBVlQ3NHBKJBK666iqoqhr2UEgI0L9s6L9+CeLGMolEAqtWtSCRSNT8d5GlyW1ILtbwLHZpg+V8c87tXzb0Lxv6lw39y4b+ZcP9/+CoqKE5Ojrqa2YC2YbmBz/4Qa+ZCQA9PT2YmJiozgibAEVR2JkXDP3Lhv5lk70YOC8KLhVu/7Khf9nQv2zoXzb0Lxvu/wdHRV8ZrFq1CnNzc97yuXPnMDY2ho9+9KO+uJmZGXajczAMA4ODgzAMI+yhkBCgf9nQv2wMw4Bh6PQvFG7/sqF/2dC/bOhfNvQvG+7/B0dFDc2rrroK3/nOdzA1NYWLFy/i1KlT6OrqKnrU5vbt26s60EYnk8mEPQQSIvQvG/qXjeM4YQ+BhAi3f9nQv2zoXzb0Lxv6l0019v/Th45VYSTNTUWnnP/O7/wOvv71r+PRRx8FkL02wIEDB3wxr732Gv793/8dDz74YPVG2eDE43F0d3cvHUiaEvqXDf3LJh6PI5FIIh6Phz0UEgLc/mVD/7Khf9nQv2zoXzbc/w+OihqaGzduxJe+9CX827/9GzRNwwc/+EGsX7/eF3PNNdfgjjvuwFVXXVXVgRJCCCGNSBA3HyKEEEIIIYQQSVR8261Vq1bhIx/5CD7xiU8UNDMBYPv27fjEJz5RlcE1C5qm4Re/+AU0TQt7KCQE6F829C8b+pcN/cuG/mVD/7Khf9nQv2w0TcOlS/P0HwAVHaF58ODBks+pqop169bhPe95D2666aYVHV47PDyM3/7t38ZNN92Eo0ePAgB++tOf4s4778TGjRsLxvTJT37SWz558iSef/55zMzMoKOjA4888gg+/OEP+16zVEw566iEaDSKTZs2IRqtKN2kSaB/2dC/bOhfNvQvG/qXDf3Lhv5lQ/+yiUajiMVi9B8AFWX46quvLvmcbduYmJjAd7/7XZw9exYHDhxY1p3OHcfBF7/4RXR2dvp+Pjw8jPe+97349re/XfK1r776Ko4fP44XXngBO3fuxGuvvYZ7770Xp06dwtatW8uKKWcdlRKNRosezUpkQP+yoX/Z0L9s6F829C8b+pcN/cuG/mUTjUYRjbKhGQQVZfjuu+9eMmZgYABPPvkkvv/97+O2226reEDPP/88otEobrnlFgwMDHg/HxkZwRVXXLHoa5966ins3bsXO3fuBADceuutOHXqFF5++WU8/PDDZcWUs45KsSwLmqYhmUwiEoksax2kcaF/2dC/bOi/MbF6+7IPNG3hcQ7n06PeY80yfMu+9dC/aOhfNvQvG/qXDf3LxrIs2LYFy7Lov8ZUfA3NpdiyZQt+8zd/E2+99VbFr/3Zz36GZ555Bl/5ylcKnluqoTk0NIRUKoUbb7zR9/ObbroJb7zxRlkx5axjKQzD8B7rug7TNGGaJvr7+5FOp2HbNgAgk8n4rqlgGAZM0wSQPUpV0zRYllUy1v09+bFu8XQcZ0WxQPbaD5lMpmisaZolY23bhqZp3ns1TRO6rvvyUkmsm5f82Py8FItdLIe1zrebF03T0N/f7z1ebr5z81KtfGcymarkeyU5rHa+lzNn3dhSOaw037k5TKfT6O/vh2maK8p3o9cIOI73HJzs+11Ydgry4j6XnxfHseE4ds5qc5YL1gvvdaXyXesa4W7/7vOV5JA1orY1AnCKztm2l06g7aUTSPzVE1CvvQptL51A6//8v5H4qydg2zae270f/+N/uxd/+Wv34Lnd+3FtWxee+i9/hKc/ch+e273flxf37//c3FzZOZRaI5pxP8L1Pz8/X5McskbU937E/Py89/d/JfsRrBGFsY1QI3L9hzVnWSPCqxFu/Xd/by0/a7BGVJ5D27ZrWiOydV9HOp325RBwvNjs5xd32QHgsEbk5bscqt7QBIAdO3ZgfHy8otfouo6HHnoIDz30UNFTu0dGRjAzM4N9+/bh5ptvxu233+47/XxkZAQA0NHR4XtdR0eH99xSMeWsYylGRxeO0hgcHMTExAQSiQS2bt2K4eFhb2LOzMzgwoULXuzQ0JCXM8uykEqlcOnSJQDA7Ows+voWjhAZGRnBxYsXAWQnRCqVwvz8PAAgnU4jlUr5xpM7plQqhXQ6DSD7hzaVSnmT6eLFi7732dfXh9nZWQDApUuXkEqlvA1nfHwcQ0NDXuyFCxcwMzMDIDu5U6mUN2knJiYwODjoxfb392NqagpA1nsqlfI2pKmpKd+RuQMDA5icnASQ3TBSqZQ34aenp9Hf3+/L4cTEhC+HpfI9PDzs5TA/3/k5HBkZwdjYGIBsAUmlUt6HUzfW3dDHxsYK8m2aJnbs2OH9ntx8Dw8PF813fg7Hx8d9sf39/Zieni4aOzk5WZBvN4eGYfjyPTk56cvh4OCgF5vJZHw5zM/38PCwN2fzY/PnbG6+y5mz+fl25+zc3FxBvnPnbG5s/pzNz3exOevGTkxM+OZ3br7dOesW2snJyYI5685vwzAwPDyMK6+8EolEAlNTUwX5dudsfg6brUbk7jg4eY0kx3EK5uxnu2/25duds8X+6BU2qGxvvbmxYdQId2zudaWL1YjF8s0aUbsa4XpdrEbkNqaXUyMSiQTa2tq89wYU1ojcv2uSa0Qz7kckEgns2LEDU1NTK9qPYI1ozP2I8fFx7NixA4lEYkX7EawRpfNdzzViYmICra2tSCQSNf+swRpRfzUikUhAURRvLtXyswZrRJZKaoSu6zWtEYlEAslkoqD/k3ughWEYvs9Ctm2zRsBfI8pBcbxDWapHb28vnnzySRw/frzs13zta1/DwMAAvvnNbwIAnnzySQwMDHg3BXrkkUcwPj6OgwcPoqurC+fOncNnP/tZ7N+/H3v27MFPfvIT3H777fjxj3+MlpYWb72nT5/Ggw8+iLfeemvJmBdffHHJdZSir68PR48exf333++drq7rOlRVRSwWg23bMAwD8Xgcqqoik8kgk8kgmUwCyIpVFAWxWMz7EB6LxRCJRIrGAtkPyPmxlmV5H6IURVl2LJCdmNnrP0QLYt1vG4vF5r9X0zRh27Z3TVVd1xGJRMqOLTeHxWIXy2Gt871UDivNd25eqpXvTCYDy7JWnO+V5DCofC82Z93YUjmsNN+L5XC5+W70GrH3jSfR09oBRVFwfnYU3avboSjK5eUR/OWvf3rJOTv73+6H902mpgPJ5MIyFBy459rLywqgAFrGQDISAxQFAPCXv3YPa0Qd1IhLX/06kocO1LxGzH35zxD/0udXVCPM/+svsObIw6wRAdQI7kewRnA/gjWCNYI1gjWCNSKIGvHVH30Lj37gjprWiPShxxH90wd8OZz7wwcQ2d4DIHuEpn3+wuVlB1ZvH1r/5zd8+c7892+g9fAXRNaI4eFhPPHEE3j44YfR3d2NUtTkKqXnzp3DlVdeWXb8D37wA3zve9/Dd77znZIxjz32mG/5uuuuw913342TJ09iz5492Lx5M4DsNwA9PT1e3OjoqHeDoaViylnHUuTe3d2VYpomxsfHsXHjRqhq9qBYV36x1ymK4m0UlcZGIhHfdRqWGwtg0dhYLFYyVlVV33J+bO7NolYSm5+XSmKDyDeQzYtpmhgeHsbGjRt9r62HfK8kh7mxK8lhtfNdKnaxHNYy35FIBKOjo9i4cWPB3e7qbc7WMt+43LzMPoZXC93ncnNRKi9tL53wfp4+dAyth7/g+xXP+X8jjpx9BQc/dCeKEVS+bdvG1NSU57+SHLJGVB5b7RxmFLXsWJfcvOT+/Xdp5L9r3I+oLN+5/t1xVTOH9ZBv6TVisdhS+3/1PGfLiWWNKC9WURTf9h/GnK2HfEutEaZpevt/S8Xmr5c1YoFazVlVVb33U4t8u6fDJ3LGnI1TvFhFUXOWFQCKLzYajSJ9+VmpNaIcqnrKuW3bOHPmDF5//XXccMMNZb/u9OnTGB8fxw033IBdu3Zh165dOHHiBE6dOoVdu3bhn//5nxeuiZb3+9wPyO3t7bj22mtx+vRpX8yZM2ewe/fusmLKWcdysG0buq77DjEmcqB/2dC/bOi/kPxGdDND/7Khf9nQv2zoXzb0LxvbtmHbDv0HQEVHaB48eLDkc47jYGZmBpZl4dd//dcramg++uijePTRR30/yz/l/N5778WOHTtw//33o6WlBefOncOLL76IAwcOeK+55557cOzYMezevRvbt2/H66+/jjfffBOnTp0qO6acdVRKIpHwHfFJZEH/sqF/2dC/bOhfNvQvG/qXDf3Lhv5lk0gkYCaTFR9tSCqnoobm1VdfXfI5RVGwbt06XHvttYvGLZfDhw/j+PHj+NSnPgXTNLFmzRrs27cPd9xxhxdz2223IZ1O47777sPc3Bw6Ozvx9NNP+865XyqmnHUQQgghhBBCCCGEkMai1CWpSONRUUPz7rvvrtU4Cvjc5z7nW+7s7MTjjz++5Ov27NmDPXv2rCimnHVUgqZp6O/vR1dXl+96AUQG9C8b+pcN/cuG/mVD/7Khf9nQv2zoXzaapuHSpXlENY3+a0xVr6FJihONRrF+/XrfxU6JHOhfNvQvG/qXDf3Lhv5lQ/+yoX/Z0L9ssje6idF/ADDDARCNRn13OCWyoH/Z0L9s6F829C8b+pcN/cuG/mVD/7KJRqOIxdjQDAIeoRkAtm1jfn6ed7kSCv3Lhv5lQ/+yoX/Z0L9s6F829C8b+pdN9i7nFv0HABuaAWAYBi5cuADDMMIeCgkB+pcN/YdHPVzwm/7Do/XwF8IeAv0Lh/5lQ/+yoX/Z0L9sDMOApun0HwA8BjYA4vE4tm/fzkOOhUL/sqF/2dC/bOhfNvQvG/qXDf3Lhv5lE4/H0dKSRDweD3soTQ+3sABQVZWTWTD0Lxv6lw39y4b+ZUP/sqF/2dC/bOhfNqqqYs2Rh8Mehgh4ynkAmKaJ0dFRmKYZ9lBICNC/bOi/NtTD6cTlQP+yoX/Z0L9s6F829C8b+pcN/QcHj9AMANu2MTc3h7a2trCHQkKA/mVD/7Khf9nQv2zoXzb0Lxv6lw39y2Yx/1Zv38KCpvmXAUzftd/3vG8ZQNtLJ3zL6UPHGuZAj1rAhmYAJBIJbN++PexhkJCgf9nQv2zoXzb0Lxv6lw39y4b+ZUP/sinlv9xmZGR7N4Bs89N97C4TPzzlnBBCCCGEEEIIIYQQ0jCwoRkAuq7jl7/8JXRdD3soJAToXzb0Lxv6lw39y4b+ZUP/sqF/2dC/bOg/ONjQDIBIJIK1a9ciEomEPRQSAvQvG/qXDf3Lhv5lQ/+yoX/Z0L9s6F829B8cvIZmAESjUWzatCnsYZCQoH/Z0L9s6F829C8b+pcN/cuG/mVD/7Kh/+DgEZoBYNs2NE2DbdthD4WEAP3Lhv5lQ/+NzUrvGkn/sqF/2dC/bOhfNvQvG/oPDh6hGQCGYSCVSqGnpwfJZDLs4ZCAoX/Z0L9s6F829C8b+pcN/cuG/mVD/7JZqX/vbuaaVnBn8+m79vuDNc33s/w7qTc7bGgGQDweR09PD+LxeNhDISFA/7Khf9nQv2zoXzb0Lxv6lw39y4b+ZbMS/7kNyfShYwVnC03ftR+R7d3estXb5y3nNz8lwIZmAKiqym9mBEP/sqF/2dC/bOhfNvQvG/qXDf3Lhv5lQ//BwWtoBkAmk8HY2BgymUzYQyEhQP+yoX/Z0L9s6F829C8b+pcN/cuG/mVD/8HBhmYAWJaFmZkZWJYV9lBICNC/bOhfNvQvG/qXDf3Lhv5lQ/+yoX/Z1JP/I2dfCXsINYUNzQBIJBLYuXMnEolE2EMhIUD/sqF/2dC/bOhfNvQvG/qXDf3Lhv5l02j+04eOhT2EZcOGJiGEEEIIIYQQQgghpGFgQzMAdF1Hb28vdF0PeygkBOhfNvQvG/qXDf3Lhv5lQ/+yoX/Z0L9squU//w7npBA2NANAVVWsXr0aqion3c1+rYZKkOifLED/sqF/2dC/bOhfNvQvG/qXDf3Lplz/bFiunGjYA5BALBZDR0dH2MMgIUH/sqF/2dC/bOhfNvQvG/qXDf3Lhv5lQ//Bwa8MAsC2bRiGAdu2wx4KCQH6lw39y4b+ZUP/sqF/2dC/bOhfNvQvG/oPDjY0A8AwDPT29sIwjLCHQkKA/mVD/7Khf9nQv2zoXzb0Lxv6lw39y4b+g4MNzQCIx+PYunUr4vF42EMhIUD/sqF/2dC/bOhfNvQvG/qXDf3Lhv5lQ//BwYZmAKiqilWrVvGiwBWSPnQs7CFUBfqXDf3Lhv5lQ/+yoX/Z0L9s6F829C8b+g8OZjgAMpkMxsfHkclkwh5K3dAszcpyoH/Z0L9s6F829C8b+pcN/cuG/mVD/7Kh/+BgQzMAMpkMJicnOaGFQv+yoX/Z0L9s6F829C8b+pcN/cuG/mVD/8ERDXsAEkgmk7jqqqvCHgYJCfqXDf3Lhv5lQ/+yoX/Z0L9s6F829C8b+g8OHqFJCCGEEEIIIYQQQghpGNjQDABd15FKpaDrethDISFA/7JpNv9Hzr4S9hAaimbzTyqD/mVD/7Khf9nQv2zoXzb0HxxsaAaAqqpIJBK8y5VQ6F829C8b+pcN/cuG/mVD/7Khf9nQv2zoPzh4Dc0AiMVi2Lx5c9jDICFB/7Khf9nQv2zoXzb0Lxv6lw39y4b+ZUP/wcGWcQA4jgPTNOE4TthDISFA/7Khf9nQv2zoXzb0Lxv6lw39y4b+ZUP/wcEjNAPAvYZCT08Pkslk2MMhAUP/sqF/2dC/bOhfNvQvG/qXDf3Lhv5lE7b/vWdOeI81y/AtA8Bzu/dj+q79Cz/QNN9y20v++HqGDc0AiMVi6OrqQiwWC3soVeHI2Vdw8EN3+n6Wv5HkbzhLbTRAY204ldBs/kll0L9s6F829C8b+pcN/cuG/mVD/7KpB//bWjsAAOfTo95jd9klsr0bAGD19vkeNxJsaAZAJBLB6tWrwx5GzcnfUHI3IpdiG4273KxI8U+KQ/+yoX/Z0L9s6F829C8b+pcN/cuG/oOjLq+hOTw8jF/7tV/Dww8/7Pv5yZMncdttt+FjH/sY7rjjDvzoRz8qeG01YspZRyVkMhlMTk4ik8msaD2kMaF/2dC/bOhfNvQvG/qXDf3Lhv5lQ/+yof/gqLsjNB3HwRe/+EV0dnb6fv7qq6/i+PHjeOGFF7Bz50689tpruPfee3Hq1Cls3bq1ajHlrKNSMpkMxsbG0NLSgmi07lIeKN6RmJpWcFRm/inojXwth1zoXzb0Lxv6lw39y4b+ZUP/sqF/2dC/bOg/OOruCM3nn38e0WgUt9xyi+/nTz31FPbu3YudO3cCAG699VZcf/31ePnll6saU846KiWZTOKaa64Rf0HgtpdOeP8i77nGt+w2KyPbu71/SCYXHofIkbOvrOj19C8b+pcN/cuG/mVD/7Khf9nQv2zoXzb0Hxx11dD82c9+hmeeeQZf+cpXfD8fGhpCKpXCjTfe6Pv5TTfdhDfeeKNqMeWsYykMw/Ae67oO0zQBALZtQ9M02LYNINu11zTN9zo31nEcaJoGy7JKxrq/Jz/WsixomgbHcVYUCwCapnmHSefHmqbpi4XjeM85juNbhuNA13VfXhzHLpoXx7G95/KXl8phsXwvlsNy823bdk1yWGm+c3OYG5ufl/xYXddLxmYymYLYcudsbuxK5my15nc5OVwqtlQOK833Yjlcbr7rpUa446s03/6akH2/i9WIauU7iBpRqznLGsEa0Yg1ohr5XsmcZY1gjWCNYI1gjWCNYI2oPN+sEY1RIwAHtm0BcIouG4YBuJ+xsisv2afJ773krqceakQ51E1DU9d1PPTQQ3jooYcKTu0eGRkBAHR0dPh+3tHR4T1XjZhy1rEUo6MLN8AZHBzExMQEDMNAX18fUqmUNzFnZmZw4cIFL3ZoaAjj4+MAspMnlUrh0qVLAIDZ2Vn09S2cnj0yMoKLFy8CyE6IVCqF+fl5AEA6nUYqlfKNJ3dMqVQK6XQaADA/P49UKuVNposXL/reZ19fH2ZnZwEAly5dQiqV8jay8fFxDA0NebG2bfsmaW6zwnEcDA4OerH9/f1erK7rSKVS3gZabEK7saZpIpVKec9PT0+jv7/fl8OJiQlfDkvle3h42Mthfr7zc2iYBsbGxrz3kkqlMDc354t13+vY2FhBvqenp9HX14eZmZmCfA8PDxfNt6ZpSKVS3nsfHx/3xfb392N6erpo7OTkZEG+Jycns+/FMHz5npyc9OVwcHDQi81kMr4c5ud7eHjYm7P5sflzNjff5czZ/Hy7c5zXJtkAACAASURBVHZubq4g37lzNjc2f87m5/vChQuYmZnx5dCNnZiY8M3v3Hy7c9YttJOTkxgYGPBiBwYGMDU15ct3X18fDMPA1NRUQb7dOZufw3qtEYa5sOOw3BrhwPH9gSxWI9wc5teIqampgny7czasGjEyMlKyRkxPT/vGX6xGLJZv1ojGrhHu3/+laoQ7Z5uhRix3P6JYvt05OzEx0ZA1wvU/PDy8ov0I1ojGrBGDg4Pe3/+V7kewRjRejRgcHPR+70r2I1gjGrNGuHlw32utP2uwRtRXjSin/7PczxrZ96d7eXCXXcbGxmDnNDRt215oINuW16tx30/+AXnu3K9FjThy9pWKakQ5KI6T274Nj6997WsYGBjAN7/5TQDAk08+iYGBARw9ehQ/+clPcPvtt+PHP/4xWlpavNecPn0aDz74IN56662qxLz44otLrqMUfX19OHr0KO6//37vdHVd16GqKhzHwdjYGNauXYvVq1dDVVVkMhlkMhnvMGTDMKAoCmKxGJzLRyvFYjFEIpGisQAQj8cLYi3LgmmaSCQSUBRl2bFAdmJGo1FEo1Ff7Nd+/G08/P7fheM4XuzeN55ET2sHFEXJ/mFIj3rL52dH8Je//mkkEgkvL8bX/hxrjjzsHf0Yj8cx+9/uh7qtCwCgKCqs3j5v2T7fjzUvfMOLLZZDN9+xWMxb72I5LDffX/3Rt/DIr/wfy86h4ziYnJzE+vXroShKxflWFAWmacK2bS+HubG5OVRVtSBW13VEIpGisZlMBpZl+WLzc1hOvlcyZ6s1v8vJYe6cLRZbKoeV5js3h3Nzc5iZmcGmTZugquqy810vNeKxcyfx5Q/vWTTfc1/+MyQOPliyRpyfHUX36nYoilKyRpSas0vlO4wasVgOL126hIsXL6KjowOJRKKiOcsa0fg1IpPJYHR0FOvWrUNra2tZOWz0GlGNfK9kztZTjVBVFRcvXkRbWxtisVjVc8gaUd81Qtd1zMzMoL29HbZtL3s/gjWiMWtEOp3G1NQUOjo6EIvFQpmzrBHh1QjDMDAyMoL29na0tLTU9LMGa0T91Yjc/s+qVauq+llj+q59UHq6oKoqAAVWb8pbtnovoOW54/jMvzyNbWuy96Q5PztS0Kd5dvd+zNz9OV+vJbK9G7ZtwUn1o+2lp2pSIx47dxKPfuCOsubs8PAwnnjiCTz88MPo7i59CcK6uELpD37wA3zve9/Dd77znaLPb968GUC2u9/T0+P9fHR01Lt5UDViylnHUrgbFABPCgBs2bLFF+fKL/Y6RVF811uoJDYSiSASiaw4FsCisbFYzBeLy40J9/fkLuNyE88lkUjAVLIHB6uq6vs9iuI/aDh3OT82Py+5v2Op2EryraqqF18sh5e++nUkD3+hYL3AQg5zG+TFxpAb6653sXznxua/1/zYSvKy3NiVzNlqzW9g+TmsZb7XrFmDNWvW+N5vqdiwc1hObPaPZ5bl1ggo8K2nWI1wCWt+VyvfLS0tvrMOKpmzrBGVx9ZbjYjH4+jq6vLF1vucDWs/olpztt5qxJVXXukbTzVzWA/5Zo0oHRuLxbwvMnKp9zm7VCxrRHmxra2tPv9hzNl6yLfUGhGPx337f42Qb9aIymMXy3et+j+AAlWNlFyOx+OA+5kru/KSfZr83ouqRmAh+1w9zNlyqItTzk+fPo3x8XHccMMN2LVrF3bt2oUTJ07g1KlT2LVrF37xi1/g2muvxenTp32vO3PmDHbv3g0AaG9vX3FMOetYDo7jwLIs7/BdIgv6lw39y4b+ZUP/sqF/2dC/bOhfNvQvG/oPjrpoaD766KP4+c9/7vu3f/9+/O7v/i5+/vOf44YbbsA999yDZ599Fr29vQCA119/HW+++SZ+//d/31tPNWLKWUel6LqOd955x3dtSCIH+pcN/cuG/mVD/7Khf9nQv2zoXzb0Lxv6D466OOW8HG677Tak02ncd999mJubQ2dnJ55++mnf+fTViClnHZUSi8Vw5ZVXFp6C2UDsPXPCe6xZhm/Z5Xx61BeTuyyZZvBPlg/9y4b+ZUP/sqF/2dC/bOhfNvQvG/oPjrptaH7uc58r+NmePXuwZ8+eRV9XjZhy1lEJkUjEdw29RmVba/bu7+fTo95jd/m53ft9sUfOvoKDH7oz0PHVK83inyyPZvC/1Bcax5/5mf8FmobpuxZqQttLhV+ASKEZ/JPlQ/+yoX/Z0L9s6F829C8b+g+OujjlvNnJZDKYmprybmNPZEH/smkW/9taO7CttQPJSNx7nPvFRmR7t/cPyeTCY+E0i3+yPOhfNvQvG/qXDf3Lhv5lQ//BUbdHaDYTmUwGIyMjSCaTvjs4kfok/+iz/CPSntu933f0Wf7RaID/iDT6lw39y4b+ZUP/sqF/2dC/bOhfNvQvG/oPDmY3AJLJJHbt2hX2MEgF5J9Sn3u6vYt79JnV2+c7Es3q7fOti/5lQ/+yoX/Z0L9s6F829C8b+pcN/cuG/oODDU1CCCErxtfI17SCxj6w8IUAbxpGCCGEEEIIIWQlsKEZAIZhYHR0FB0dHYjH42EPhwQM/cumnvynDx1D6+EvVH29+Tf9KfZ7cm8cJummYfXknwQP/cuG/mVD/7Khf9nQv2yazf9yP7uVcym/lcKbAgWEoihhD4GECP03LkfOvrLiddC/bOhfNvQvG/qXDf3Lhv5lQ/+yof8suTeTzb25bLXgEZoBEI/HsWXLlrCHUVfU4iixeoX+ZUP/sqF/2dC/bOhfNvQvG/qXDf3Lhv6Dg0doBoDjOLBtG47jhD0UEgL0Lxv6lw39y4b+ZUP/sqF/2dC/bOhfNvQfHGxoBoCu63j77beh63rYQyEhQP+yaTT/1TjFnizQaP5JdaF/2dC/bOhfNvQvG/qXDf0HB085D4BYLIbNmzcjFouFPRQSAvQvm3r3X+7FmnmH8uVR7/5JbaF/2dC/bOhfNvQvG/qXDf0HBxuaARCJRNDW1hb2MBoCq7dvYUHT/MsApu/a73seyaTv+fy7LdcD9C+bRvCfe2Hm8+lRb9ltXEq9Q3k1aAT/pHbQv2zoXzb0Lxv6lw39y0ai//ShY6HcJ4UNzQCwLAtzc3NYvXo1IpFI2MOpW/KbkaU2isj2bgDZ5qf72F2uR+hfNs3mn83Mymg2/6Qy6F829C8b+pcN/cuG/mVD/8HBa2gGgGmaGBoagmmaYQ+FhAD9y4b+ZUP/sqF/2dC/bOhfNvQvG/qXDf0HBxuaAZBIJHD11VcjkUiEPRQSAolEAlte/vtA/KcPHav57yCVwe2/EElHedK/bOhfNvQvG/qXDf3Lhv5lQ//BwYZmACiKAlVVoShK2EMheQRxR+esd4X+hcLtXzb0Lxv6lw39y4b+ZUP/sqF/2dB/cPAamgFgGAbGxsawadMmxOPxsIdDAsYwDOi6jrhh0L9Aarn9F7tDeTKy8Due272/4EZavmUA+PS1VR0T8cP6Lxv6lw39y4b+ZUP/sqF/2dB/cLChGRC2bYc9BBIqTtgDICFSy+1/qTuUA413I61mg/VfNvQvG/qXDf3Lhv5lQ/+yof9g4CnnARCPx7F161Z254USj8eRSCRX7D+I0+NJ9eH2Lxv6lw39y4b+ZUP/sqF/2dC/bOg/OHiEJhFH7mm6mmUUnLYL+I9u0yzDt0wIIYQQQgghhBDSjCzVM1nq0mZtLxX2WGoBG5oBoGkaUqkUenp6kEwmwx4OAXyn5eafsvvcbv81Bo+cfWVFd2XWNA3z8/OIahr9C0Ti9t96+AthD6FukOifLED/sqF/2dC/bOhfNvQvm0bx711+TNOWfSmyYpc2C/KyZmxoBkA0GkVnZyeiUaZbItFoFPF4jP6Fwu1fNvQvG/qXDf3Lhv5lQ/+yoX/ZNIL/3CMo04eOFRyQknuQ10oP8Kol9ZvhJiIajWLdunVhD4OERDQaRTTKhqZUuP3Lhv5lQ/+yoX/Z0L9s6F829C8b+g8O3hQoACzLQjqdhmVZYQ+lLHjzmepiWRYsK9Mw/kl1qYft3+rtyx76f/l0Am/5MufTo94/95qxvG5sdagH/yQ86F829C8b+pcN/cuG/mVD/8HBQ8YCwDRNDAwMoKenB5FIJOzhkIAxTRO6biBhmvQvkLC3/yVPJ8iLr+dTChqRsP2TcKF/2dC/bOhfNvQvG/qXDf0HBxuaAZBIJLBz5866ncz5d6zKv4uVe/0E94gt3vW7MhKJBFpakkgkEiVjijWaSHNQ79s/qS30Lxv6lw39y4b+ZUP/sqF/2dTav++mOyVu6COld8OGZgAoilL310/Mv9N37l3Agca5KGyQLHVXsOm7cu6WrmmYuftz3mLuUXOLkdtYLtZo9v2Oy78n92fl/h5SOxph+ye1g/5lQ/+yoX/Z0L9s6F829C+bWvrP/3zfyDf0qQbcygLANE1cvHgR7e3tiMViYQ9HFNU48rFYAVjqNF6XyPZuOI4Nq7cPkW1dUBS1aPNzMXKby/mNZvd3uFi9fd5ypb+H1AZu/7Khf9nQv2zoXzb0Lxv6lw39y4b+g4M3BQoAx3FgmiYcxwl7KIHRzN8CLAc55kk+jbb9c9utLo3mn1QX+pcN/cuG/mVD/7Khf9nQf3CwoRkA8Xgc3d3diMfjYQ+FhICiqFAVFYoS/uaWPnQs7CGIg9u/bOhfNvQvG/qXDf3Lhv5lQ/+yof/gCL/DQhoOHsFFCCGEEEIIIYQQQsKCDc0A0DQNb7/9NjRNC3soJARs2/L+EXlw+5cN/cuG/mVD/7Khf9nQv2zoXzb0HxxsaAZANBrFxo0beaczoSiK4v0j8qin7X+lN8gilVNP/knw0L9s6F829C8b+pcN/cuG/oODGQ6AaDSKDRs2hD0MEgLuncYV3YB9vt/33PRd+xcWNM2/DP+d1EnjUq3t/8jZV3i5hwaE9V829C8b+pcN/cuG/mVD/7Kh/+BgQzMALMuCpmlIJpOIRCJhD4cEhNuQtCwLc18+htVf/UKB/8j27mxMb5/32F0uF1+sphW8drHGKZumtYfbv2zoXzb0Lxv6lw39y4b+ZUP/sqH/4GBDMwBM00R/fz96eno4oQVimiY0TUfcNAv8e83HIo1Il/Pp0WyIZXiPXfIbkulDx4qeVlyscVpJ05QsH27/sqF/2dC/bOhfNvQvG/qXDf3Lhv6Dgw3NAIjH49ixYwcns1Di8ThaWpKIx+O+n+c2I0s1Ip/bvXA0ZTmnHPMaifUHt3/Z0L9s6F829C8b+pcN/cuG/mVD/8HBmwIFgKqqiMViUFWmWyKqqkJR1Ibxnz50LOwhNBXc/mVD/7Khf9nQv2zoXzb0Lxv6lw39BweP0AwA0zQxMTGBDRs2IBaLhT0cEjCmacIwDJimGZr/xU5tz78ZEa+zWV1Wsv3vPbOQe80yfMvu0bu5lyEodlkCEi6s/7Khf9nQv2zoXzb0Lxv6lw39B0fdNDTT6TSeeOIJnD59GrZtY8OGDfjMZz6DW265BQDw05/+FHfeeSc2btzoe93BgwfxyU9+0ls+efIknn/+eczMzKCjowOPPPIIPvzhD/tes1RMOeuoBNu2cenSJdi2vex1kAUarTln2zZs2wrNfzmntuffkIjX2aweK93+t7V2AMg2LnMfA/5LEgC8E3o9wvovG/qXDf3Lhv5lQ/+yoX/Z0H9w1E1D8/Of/zza29vx3e9+F6tXr8YPf/hDfOYzn8HmzZtx3XXXYXh4GO9973vx7W9/u+Q6Xn31VRw/fhwvvPACdu7ciddeew333nsvTp06ha1bt5YVU846KiWRSGDbtm3Lei3xs1Rzbvqu/XXXnEskEkgc+3Iov5uET5DbP5uZ9Qfrv2zoXzb0Lxv6lw39y4b+ZUP/wVE3J/UfO3YMhw8fxurVqwEAH/nIR9Dd3Y233noLADAyMoIrrrhi0XU89dRT2Lt3L3bu3AkAuPXWW3H99dfj5ZdfLjumnHUQQgghhBBCCCGEEELCoW4amhs2bPDuAq3rOr71rW/h3Xff9U71XqqhOTQ0hFQqhRtvvNH385tuuglvvPFGWTHlrGMpDMPwHuu6DtM0oWka3n77bUxPT3uHHWcyGWia5nudaZoAAMdxoGkaLMsqGev+nvxYy7KgaRocxyk71iV7arTtW0Z2NQXrda8L6aJpGjKZjPc6TdO8dZmmCV3XfXmpJNbNS36s49i+8Wdfd3nAcGDblrfsOHbOc9l1ZX/mxtree6s037ZtFc23m5e5uTm88847mJubK+kmP4fF8p3rZrn5BhxfbPbnC3nx58nxclMsL7luVjJnqzW/y8nhUrGlclhpvnPn7PT0NN5++21vHeXO70wmAzgLbuA4OXMWgdaIauc7qBqx2Jx1YxfLYTXm99zcHN5++21cunSp4hxWmu+VzNlSsZXOWdYIf17cv/8zMzNl53C5+Q5zP4I1oni+NU3DO++8g9nZ2ZrkkDWivmvE7Ows3nnnHW8uVGvOskY0Ro2YnZ319v/CmrOsEeHVCPfv/9zcnC+2Fp81WCOWl8Na1gjX//T0dM0/a7if70vl0LbtFdeIgx+6s+icze8b5C7nxub2WhzH8fWZFpuz5VA3DU2Xj3/84/jABz6Ab33rW/jGN76BX/mVXwGQbWjOzMxg3759uPnmm3H77bf7Tj8fGRkBAHR0dPjW19HR4T23VEw561iK0dGFG3IMDg5iYmIC0WgUbW1tGB4e9ibmzMwMLly44MUODQ1hfHwcQHbypFIp7wPw7Ows+voWTpceGRnBxYsXAWQnRyqVwvz8PIDstUhTqZRvPLljSqVSSKfTAID5+fls7OXJZJomDNM/oZ3LT166dAmpVMrbcMbHxzE0NOTFXrhwwfvApmkaUqmUtzFMTExgcHDQi+3v78fU1BSA7IRNpVLehjQ1NYWBgQEvdmBgAJOTk974UqmUN+EzGQv9/f2+HOZuKJq2sGFkG48LzSDDMGB4BQS+wpSfw5GREYyNjXnrTaVS3h+ndDoNTdO93zs2NlaQb13XsX79em/87u+5ePEihoeHvdi+vj7Mzs4WzeH4+Liv2PT392N6erpo7OTkZEG+3Ry688Vd1+TkpC8vuq4XFBt3zk5PT/vyPTw87M3ZTCaDVCrlxebP2eHh4YrmbH6+3Tk7NzeHVCrly3futpkbmz9n8/NdbM66sRMTE775nZtvd866hXZycrJgzrrz2zAMDA8PY82aNYhGo5iamvLl0K0RxXI4MzPj/4LBcWCalxvTDgKtEblzNjffuXO2HmtE/pwdGhry8u3W2VI1OXfO5tfkSmqEYRiwbRvRaPYKL8VqxGL5rqRG5MYut0YYhlFQI/LnrBubP2dZIwprRDQaRSKR8N4bUFgjcudspTWiXvYjWCOK14hoNIr169djcnJy0f2I/DnLGtEcNeLixYtYv349otHoivYjWCNK57uea8TExARisRii0eiK9iNYIxqzRkSjUTiO4zmv5WcN1ogs9VQjyun/VOuzhvvaUjVC07Sa1Qj3d7oHxuX2EXLzres6zIy/ees2oRarEeWgOO5vrSNmZmbw13/91/jlL3+Jo0ePYtWqVXjkkUcwPj6OgwcPoqurC+fOncNnP/tZ7N+/H3v27MFPfvIT3H777fjxj3+MlpYWb12nT5/Ggw8+iLfeemvJmBdffHHJdZSir68PR48exf333++drq7rOlRVRSwWg23bMAwD8Xgcqqoik8kgk8kgmUwCyBYjRVEQi8XgONmOdiwWQyQS8WL/7D//Xxz80J3exhaPxwtiLcuCaZpIJBJQFKWs2H3/37PY1trhTey++Yvect/cRTz3sf0F6zVNE47jeEfVapqGaDSKaDRa8F7dowsTiYSXl0gksmRs+tAxxB59oGQOZw8eRezRz3s51HUd2h8dQGR7D7yjLlP9iGzvgePYsM9fQNtLT2HvmRPoXtUORQFScxexrXUTbNuBoihIzY3h6Y/cV+BmsRzOffkY1hx5uCDf+XlZzE360DFE//T+krGmaeK///v/gy9/eM+K8p0+9Diif/qAbx7O/eEDl3MGL09uDq3ePqx54cmiczZ3fpeas+XksFSs8bW/wOqv/knZ83upfC82Z93YYjk8cvYV/Ml7frtkvg+/9S188X2/68v3Ytu9ZVllx977z9/EtjWdAIDzsyPoad0ERVFxPj2Kp/7LHy0r38upEdXOd7VqRKV1tljsYjlcqiavNN+V1Ihy8p2bl2rlu9I5G2SNCHLOLlYjlpPvatWIoOcsawRrBGsEawRrBGsEawRrBGtE/dQI9/N9qRx+9UffwqMfuGPRGmF87S/QevgLFdcI/Z4/9vUNsvcuUWD1ppB89jg++7/+yusrub2WntWb4DiO12cqNWeHh4fxxBNP4OGHH0Z398I9UvKpm5sC5bJ27Vo88MAD2LNnD/7mb/4Gn/70p/HYY4/5Yq677jrcfffdOHnyJPbs2YPNmzcDyH4D0NPT48WNjo6iszPbEFgqppx1LIU7cQB4Umzbhq7rSCQSUNXsQbHuRCn2OkVRvMlbaWwkEkEkEllWrDs237JSPDYWi/lic9erqqpvOT/WzctSsfk3/MmPVRT/ciKRgOYOGApUNQLr8rKiqPDeTMF7VaCqC89Vmm9VjUBRlIJYIJsX287e5SyRSPheWyw2d735+c4d83LzDRTOrdy8+POkIJub4nM2d70rmbOlYo0isYvNb2DpHFYjttg8zM1F/vyOx+Pe9r9YDvPXG41GAWXBDRTlsp/CMQVVI6qV72rViKViK813LWqyoihwHAeOk/3SpJIc1kO+V5LDWteIYrH1ViPc03wWqxH1NmdZI8qLLSffxfb/qpnDesg3a0Tp2FL7f/U8Z8uJZY0oLzYajXpNk5W4YY3I0mg1wj1aza39jZBv1ojKY0vlO8j+T/7n+/wcugdEAaXz7Z4HWmm+9by+QW4fIT9vueNXFMULXWzOlkNdnHJu2zb+8R//seDn69at8x1aW+x1biOpvb0d1157LU6fPu2LOXPmDHbv3l1WTDnrWA6GYaCvr893yjCRQ7X88w7WjUk5/o+cfSXAEZEgYf2XDf3Lhv5lQ/+yoX/Z0L9sJPm3evtg9fYBmrbwOIfz6VHvn2YZ3uNqURdHaE5MTOBLX/oSfu/3fg+f/vSnEY/HcebMGfzgBz/A008/DQC47777sGPHDtx///1oaWnBuXPn8OKLL+LAgQPeeu655x4cO3YMu3fvxvbt2/H666/jzTffxKlTp8qOKWcdlRKPx7Ft27aCrnYYHDn7ChtjAVNP/knw0L9s6F829C8b+pcN/cuG/mVD/7KR4r/tpRPe4/ShYwVn2D63e79vuRa9qLpoaLa3t+Pv/u7v8PWvfx0333wzHMdBe3s7jh49iv/6X/8rAODw4cM4fvw4PvWpT8E0TaxZswb79u3DHXfc4a3ntttuQzqdxn333Ye5uTl0dnbi6aef9p1zv1RMOeuoFFVVKz50ljQP9C8b+pcN/cuG/mVD/7Khf9nQv2zoXzb0Hxx10dAEgK6uLvz5n/95yec7Ozvx+OOPL7mePXv2YM+ePSuKKWcdlWCaJiYnJ7F+/fqm79KTQuhfNvQvG/qXDf3Lhv5lQ/+yoX/Z0L9s6D846qah2czYto10Oo22trawh0JCgP6bj71nFg6v1yzDtwxkD6+fvss9xN5BXNMwn0zCvfpx7uH5pLnh9i8b+pcN/cuG/mVD/7Khf9nQf3FqcelDNjQDIJFIYMeOHWEPg9SI/GtF5EP/jUV+czK/YZl/LZDFiGzPXqrC6u3zPSZy4PYvG/qXDf3Lhv5lQ/+yoX/Z0H9wsKEpgMWOJnObM7l3mnLvPkWIVLa1dniPz6dHvWV3u8htavJGW4QQQgghhBBCSLCwoRkAuq5jYGAAW7ZsCe3isLkNmcWaM0DjN2h8R8BpWtEj4tz3HkTzth78k/BwHBu2bUF1bCiKGvZwSMBw+5cN/cuG/mVD/7Khf9nQv2zoPzjY0AwAVVWxZs0aqCqbGbUm/9qE6UPHCk4JD/roOvoniqKEPQQSEtz+ZUP/sqF/2dC/bOhfNvQvG/oPDmY4AGKxGDZt2sQ7XAml2fwfOftK2EOoGkG8F0VRvX9EHs22/ZPKoH/Z0L9s6F829C8b+pcN/QcHP2EHgG3b0DQNtm3X9PekDx2r6frJ8ijH/1I3FiKNjJPzj0gjqPpP6hP6lw39y4b+ZUP/sqF/2dB/cLChGQCGYSCVSsEwjLCHQkKA/mVj27b3j8iD279s6F829C8b+pcN/cuG/mVD/8HBa2gGQDweR3d3N+LxeNhDISEg0X+xa5dKRVVVOKpacA2VvWcWrveqWYZvGVi41muQN7Ai1Ufi9k8WoH/Z0L9s6F829C8b+pcN/QcHG5oBoKoqWlpaFo1p9DuLk9KU458Ex1KNRAC+xuHKG4lKzj8/21o7vN/nPs79/UHfwIpUH27/sqF/2dC/bOhfNvQvG/qXDf0HBxuaAZDJZDA1NYV169YhGq3/lLNpUl0azb8EFmsk5jYRgZU3Eh3H9v6t5MZA3C4bE27/sqF/2dC/bOhfNvQvG/qXTaP5b+QzK3kNzQCwLAvT09OwLCvsoZAQqCf/jVysGhnH4Q2BpFJP2z8JHvqXDf3Lhv5lQ/+yoX/Z0H9w1H+7uAlIJBLYuXPnsl672Omxz+3ej+m7co4m0zT/MoC2lwpPpyXBshL/zYqU06et3j4AgGqYsM/3FzzP62M2P9z+ZUP/sqF/2dC/bOhfNvQvG/oPDjY0G4Bip8fmNj8i27sBZJsn7mN3mZBqsNR1J48/8zP/C/Ka6xIb67nvudhNknh9TEIIIYQQQgghZHnwlPMA0HUdvb290HU97KGQEGgW/9taO7CttQPJSNx7nHv9ycj2bu8fksmFxzXiyNlXarbuaqLrOjTtUsP7J8ujWbZ/sjzoXzb0Lxv6lw39y4b+ZUP/wcGGZgCoqopVq1ZBVZluR3pqRQAAIABJREFUidC/bFRVhapG6F8o3P5lQ/+yoX/Z0L9s6F829C8b+g8OnnIeALFYDJ2dnWEPg4QE/Tc3S50qHovFEI/HEYvFAhoRqSe4/cuG/mVD/7Khf9nQv2zoXzb0HxxsGQeAbdswDAO2bYc9FBIC9B8e6UPHwh4CbNuG49j0LxRu/7Khf9nQv2zoXzb0Lxv6lw39BweP0AwAwzCQSqXQ09ODZDIZ9nBEkX8jljCg/+rRiDcnMgwDly5piBkG/QuE279s6F829C8b+pcN/cuG/mVD/8HBhmYAxONxbN26FfF4POyhkBCg/+ri3ojofHrUd1Oi8+lRAPDdiMjq7fOWrd6+AEe5QDweRzKZoH+hcPuXDf3Lhv5lQ/+yoX/Z0L9s6D842NAMAPeisKT+WOr6h9WA/rM04tGV1YA3BZINt3/Z0L9s6F829C8b+pcN/cuG/oODDc0AyGQymJmZwdq1axGNLqR8qQbPc7uzzRz3yDPNMrzHpHEo5V8iSx1dWQ6Ntj1kMhlkMiYymUxJ/0E01kk4cPuXDf3Lhv5lQ/+yoX/Z0L9s6D84mN0AyGQyGB8fx6pVqwom9FINHrepCQBHzr7CxkcDspj/ZsJ3SremFT3Fe7FmZP4RmOlDxwqugbrU9jD9zH7UG5lMBmN/eCeSizQ0SfMiZfsnxaF/2dC/bOhfNvQvG/qXDf0HB7MbAMlkEldffXXN1u81jko0kYDGO6qtmai1/3qgGs3IZkWCf1Ia+pcN/cuG/mVD/7Khf9nQv2zoPzjY0GwgijWAchtJxZpIgNxGEiHVgNsLIYQQQgghhBBSX/AuFQFgGAZSqRQMwwh7KCQE6H95FGvONyL0Lxv6lw39y4b+ZUP/sqF/2dC/bOg/ONjQDABFUZBIJKAoSthDISFA/7Khf9nQv2zoXzb0Lxv6lw39y4b+ZUP/wcFTzgMgFoth8+bNYQ+DhAT9y4b+ZUP/sqF/2dC/bOhfNvQvG/qXDf0HB4/QDADHcZDJZOA4TthDISFA/7Khf9nQv2zoXzb0Lxv6lw39y4b+ZUP/wcGGZgDouo5f/vKX0HU97KGQEKB/2dC/bOhfNvQvG/qXDf3Lhv5lQ/+yof/gYEMzAGKx2P/P3r0HSXYW5v1/+nJ6Znf2rr1qb1rJkSOQwQhBQBLGyLaQYhnKcYEpyziJEWAhAiKmfigEcJBxlTAQZAOJETYIS3Iwgtgy2LJdQCJBVhaqkghWEMLoMrs79/t9uvt09++PdbemZ+fSc3tP9zzfT9VW7e6c7Xnn/Z55t+ed02d0+PBhRVGU9FCQAMf+m+UH+qwHx/54Hv290d8b/b3R3xv9vdHfG/3D4R6aAWQyGW3bti3pYSAh9PdGf2/090Z/b/T3Rn9v9PdGf2/0D4crNAOI41gjIyOK4zjpoSAB9PdGf2/090Z/b/T3Rn9v9PdGf2/0D4cNzQDiONbAwAAntCn6e6O/N/p7o783+nujvzf6e6O/N8f+Sd1yjpecB9De3q6LL7446WEgIfT3Rn9v9PdGf2/090Z/b/T3Rn9v9A+HDU0AKj176vk/zM7W//mfPTfZf/bNpULt96v1wZe8cU3/HgAAAAAA+GJDM4BCoaC+vj4dOHBAuVwu6eEgsGbvv/PuT9f9efJDv3/OJeN/8qp31n7/u49/uSk2JJthDI1o9v7YWPT3Rn9v9PdGf2/090Z/b/QPh3toBpLJZJIeAhJEf2/090Z/b/T3Rn9v9PdGf2/090b/MLhCM4BcLqfzzz8/6WEgIfT3Rn9v9PdGf2/090Z/b/T3Rn9v9A+naTY0Jycn9fGPf1wPPvigyuWy9uzZo5tuuknXXHNN7Zj/+T//pz7/+c9rfHxc+/fv13/6T/9JL33pS+seZz2OaeQxVqJSqahcLiudTiuVSq36cdCa6B9W6PuBLof+3ujvjf7e6O+N/t7o743+3ugfTtNsaN5yyy3au3evvv71r6ujo0MPP/ywbrrpJh08eFAvetGLdP/99+u//tf/qi9+8Yu66KKL9Hd/93d6+9vfrr/4i7/Q0aNHJWldjmnkMVYqn8+rs7NTx48fV3t7+7rNmbv593lsVvQPpxnvB0p/b/T3Rn9v9PdGf2/090Z/b/QPp2nuofn7v//7uu2229TR0SFJeuUrX6ljx47psccekyR95jOf0Vve8hZddNFFkqTXvva1uvzyy3XvvffWHmM9jmnkMVYqiiKdf/75iqJo1Y+B1kV/b/T3Rn9v9PdGf2/090Z/b/T3Rv9wmmZDc8+ePbWfAJXP5/WlL31JzzzzjF760peqp6dHnZ2d+tmf/dm6f3P11VfroYcekqR1OaaRx1hOoVCo/T6fz6tYLCqTyaijo0PFYlHlclmSFMexVKk8/w8rFVUq5eofpEpFpVKpduzs7Gzd+6i+n0qlotnZ2dqxpVJJs7OzqvzzY88/tlwuN3SsJM3Ozp4d5wLHFovFRY8tl8uanZ2tfazFYlH5fL5uXlZybLFYXPDY+fOy0LFLzWH12PlzuF7zXZ2XSqWi7du31/15NfM9d17Wa77jOD7n2Op5uJL5Xsscrvd8z53Dcrm05DlbfVv1cRebw5XO99zzsFgsqqOjQ5lMZsH5bvT8DnHOrnW+WSPOPVY6+6QmnU6veA6bdY1YzXw36xrR6Dm72jUik8movb299rZG5pA1YvOsEZlMRtu3b1epVNqQOWSNaO41Io5jbd++XZlMZk3PI1gjzj22FdaIUqmk9vZ2ZTKZxM5Z1ojk1ohMJqMoioJ8rcEasbo53Mg1Yu7+z8Z/rVHZtGtEI5pmQ7Pq1a9+tV784hfrS1/6kv7wD/9QP/VTP6W+vj5J0v79++uO3b9/f+1t63FMI4+xnP7+5+/H193dreHhYZVKJY2MjKizs7N2Yo6Pj9ciSlK5UlGxeDZypXI29MzMjCRpYmJCp049fx/Avr4+DQ4Onv135bI6Ozs1PT0t6ey9SDs7O+vGM3dMs7OzmpyclCRNT0+rs7OzNo7BwcG6j/PUqVOamJiQJM3MzKizs7P2iTM0NKSenp7asadPn9b4+HjtfXR2dtZO2uHhYXV3d9eOPXPmjEZHRyU9fzl29RNpdHRUXV1dtWO7uro0MjIi6ewnRmdnZ+2EHxsb05kzZ2rH9vT0aHh4WNLZT8D583369Onasb29vbU5rB5bne/5c9jX16eBgYF/blNRZ2enpqam6o6tfqIPDAzUzXdnZ6fGx8c1NjZWO3bufPf29i443/PncGhoqO7YM2fOaGxsbMFjR0ZGzpnv6hwWCoW6+R4ZGambw+7u7trjxHFcN4fz57u3t1dDQ0MLHjv/nJ07342cs/Pnu3rOTk1NnTPfc8/ZucfOzMxodjZfO2fnz/fp06drH2t1DqvHDg8P153fc+e7es5WF9qRkZFzztnq+V2d7+o6MDo6es58V8/Z+XM4/5zt6empzff8c3Y914i5c8gasfY1YmJiom5eFlojlprvZlwjqsduhjVibpuF1oj55+xK14hSqaTe3t5l14jqOcsasbnWiFKppLGxMfX29q7peQRrROuuEWNjYyqVSmt+HsEa0XprRE9Pj7q7u1UqlTb8aw3WiOZbI0qlkk6dOlU7Dzf6aw3WiOZaIxbb/9mIrzWq/3YzrhGNSFWqH3kTGR8f1xe+8AU9/fTTuv322/XMM8/oV37lV/S9731PW7ZsqR334IMP6j3veY8ee+wxPfHEE2s+5k//9E+XfYzFnDp1Srfffrve9a531V6uns/nlU6nayfZwYMHtX37dqXTacVxrLef/O+6YPsBSdJzE306vm2fUqm0pIqem+jXnVe+o3ZVVxzHtfsvVOPncjlVKhXl83lFUaSZD39CW37nt1UsFtXW1qZUKrXosZlMRqVSadFjpbMnZjabVTabPefYYrGoSqWy4LHlclmFQkG5XE7pdLp2ZWpbW1ttXjKZTMPHptNpRVF0zrHz52WhY6sf60JzmEqlat85mzsvjc53o3NYfSJ75MgRZTKZVc/33HlZr/mO41ilUmlF8/2xJ/9KH3zJG+uOXcscrvd8z53Dqd/5fW3/3VsXPWd//wf360OX/WrtcRebw5XO99w5nJiYUG9vr44fP14b12rO7xDnLGvE+s/31NSUzpw5o2PHjmnLli0rmsNWXSMWmu9mXSMaPWdXu0ZUn7QdOnRIO3bsaGgOWSM2zxohnf1C4vzzz1dbW9u6zyFrRHOvEbOzs+ru7tbx48cladXPI1gjWnONmJiYqPVva2tL5JxljUhujahu8Bw5ckQdHR0b+rUGa0TzrRFz93+2bdu2oV9rTH7oo8q+/92bbo3o7e3Vxz/+cd166606duyYFtOUG5pVb3rTm3T11Vfr3/ybf6Mrr7xSf//3f197UiBJ9913nz7/+c/rgQce0ODg4JqPufvuu5d9jMVUNzTf+973nvPDg+ZO8dyfcvWWb39aF2w7ezXoc5P9td9X/zz3h5c0YqEfgILkLda/VYX4QTrrpRk+JzZbf6wM/b3R3xv9vdHfG/290d9byP7N8PXuRjh9+nRDG5pN8ZLzcrms//W//tc5f79r1y4NDAxo7969+pf/8l/qwQcfrHv7t7/9bb3qVa+SpHU5ppHHWI1UKqWPfO8+FjNTqVSq9gt+6O+N/t7o743+3ujvjf7e6O+N/uE0xYbm8PCwPvCBD+jTn/507bLXb3/72/rOd75T+wE9b33rW/XHf/zHevbZZyVJ3/jGN/R//s//0a//+q/XHmc9jmnkMVaqUCgon8/X3XAVPgqFgs6cOUN/U/T3Rn9v9PdGf2/090Z/b/T3Rv9wskkPQDp75eSf//mf6xOf+IR+7ud+TpVKRXv37tXtt9+uK6+8UpJ0/fXXa3JyUr/1W7+lqakpHThwQJ/97GfrLj9dj2MaeQwAAAAAAAAAyWiKDU1JOnLkiD75yU8uecyb3vQmvelNb9rwYxp5jOW85dufrvvzbKmgmx65s/bn6v0xn5vsr729+ntsLrlcTkeOHEl6GEgI/b3R3xv9vdHfG/290d8b/b3RP5ym2dDcjJ7/IT8VPTc5oAu27ZOUqm1czv2hP630g1awMtwU2hv9vdHfG/290d8b/b3R3xv9vdE/nKa4h+ZmVy5XVC6VVC4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"text/plain": [
"<Figure size 1600x1200 with 2 Axes>"
]
},
"metadata": {}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "pNQ5KQr4CtL2"
},
"source": [
"### 9-4. メインチャート/サブチャートの高さを調整(gridspec)"
]
},
{
"cell_type": "code",
"metadata": {
"id": "Rb90nUI5A5FJ",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 761
},
"outputId": "823a7944-00c4-4b74-de7e-8fccfe06ffdb"
},
"source": [
"# Chartオブジェクト生成\n",
"chart = du.Chart(df_ohlcv)\n",
"\n",
"# タイトル設定\n",
"chart.set_title(title='BitMEX 1D ローソク足', loc='center', fontsize=16)\n",
"\n",
"# チャートサイズ設定\n",
"chart.set_size(width=16, height=12)\n",
"\n",
"# X軸設定\n",
"chart.set_x(col=None, grid=True, converter=du.Chart.to_date_format, format='%m/%d')\n",
"\n",
"#---------------------------------------------------------------------------\n",
"# メインチャートY軸設定(ax=0)\n",
"#---------------------------------------------------------------------------\n",
"# gridspec=3\n",
"chart.set_y(ax=0, title='USD', grid=True, legend=False, gridspec=3)\n",
"\n",
"# ロウソク足設定(メインチャート : ax=0)\n",
"chart.set_candlestick(ax=0, open='open', high='high', low='low', close='close')\n",
"\n",
"#---------------------------------------------------------------------------\n",
"# サブチャートY軸設定(ax=1)\n",
"#---------------------------------------------------------------------------\n",
"# gridspec=1\n",
"chart.set_y(ax=1, title='Volume', grid=True, legend=False, gridspec=1)\n",
"\n",
"# BAR設定(サブチャート : ax=1)\n",
"chart.set_bar(ax=1, y='volume', color='orange', width=0.8, label='Volume')\n",
"\n",
"# チャート表示\n",
"chart.plot()"
],
"execution_count": 5,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": 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Ys2YNfv/732PEiBG4//778ZWvfCWrbcRiMTz66KMYN24cLrnkEqxduxaWZXUrahIRERH1hwVNIiIioiysXbvW+ToWi2Hfvn3YtWsXWlpacOKJJ2LlypUZbWfq1KkYNWoU/vKXv2DJkiXYt28fZsyYgdtuu63P91144YVYu3Yt4vE4vv3tb2fd/y1btmDnzp29vn7uuefitNNOQ11dnXNtxNtuu63HIu3xxx+PH/7wh3jooYewdOlSPP/88xg5cmTWfcpGa2urk0E8Hkd7ezs+++wzvP/++zBNE0cddRTuueeeQd1p/tZbb834epP5cpOa9957Dw888IBzQ53Zs2fjl7/85aBvihSJRPDkk09i48aNaGpqwsknn4zVq1cP6O7t//mf/4k9e/bg1ltvxQ9/+EM0NTVh3bp1ePHFF7O6sRURERERC5pEREREWXj44Yedr/1+P0aNGoWZM2fiG9/4BubPnw9N0zLaTigUwpo1a7Bq1Sq8/PLLOP744/HFL36x3/eNHj0aq1atQiwWG9Cpub3dcCVh7NixOO2003DHHXegvb0ds2bNwsUXX9xr+8WLF+MPf/gD9uzZgxUrVmDdunVZ9ykbkUjEyUBRFJSUlKCiogJz587FV7/6VXzta1+Dzzewj7if//zn8bOf/SyrIuXtt98+5DdlysQnn3yCV199FePGjcONN96ISy+9tMdrVGbroYcewoMPPoiysjLccsst+MEPfpDxPp7s448/xtq1azF16lQsXLgQiqJgxYoVmDlzJu655x7cd999ALrm19atWzF8+HAEAgH4fD7Yto1YLAbDMNDZ2YmLL74Y119//aB/NiIiIipcip3NhZuIiIiIiCgv7dixA2eccQZKSkpytk3LsvC73/0O3/zmNzO6lEJvrr/+euzYsQO/+c1v8PnPfz7ltY6ODrz22mvYtWsXPv30U9TV1aGpqQmdnZ3dtqNpGp544om8OTKWiIiIvMGCJhERERERDanq6mq8+eabmD9/fsbvsW0bhmEgHo9D0zT4fL4BHR1KRERExYcFTSIiIiIiIiIiIioYqtcdICIiIiIiIiIiIsoUC5pERERERERERERUMFjQJCIiIiIiIiIiooLBgiYREREREREREREVDJ/XHSgWkUgE//jHPzBmzBj4/X6vu0NERERERERERFRQTNNEY2MjZsyYgbKysl7bsaCZI//4xz/w2GOPed0NIiIiIiIiIiKigvb9738fs2bN6vV1FjRzZMyYMQCAhQsXoqKiIuW1WCyG9vZ2DB8+HD4fh1wa5i8b85eN+cvG/GVj/rIxf9mYv2zMXzbmP3j19fXYvHmzU2frDUc3RxKnmVdUVGDy5Mke94aIiIiIiIiIiKgw9Xc5R94UyAWWZUHXdViW5XVXyAPMXzbmLxvzl435y8b8ZWP+sjF/2Zi/bMzfPSxousAwDITDYRiG4XVXyAPMXzbmLxvzl435y8b8ZWP+sjF/2Zi/bMzfPSxouiAQCGDKlCkIBAJed4U8wPxlY/6yMX/ZmL9szF825i8b85eN+cvG/N3Da2i6QFVVlJSUeN0N8gjzl435y8b8ZWP+sjF/2Zi/bMxfNuYvG/N3D4/QdEEsFsOBAwcQi8W87gp5gPnLxvxlY/6yMX/ZmL9szF825i8b85eN+buHBU0XxONxtLa2Ih6Pe90V8gDzl435y8b8ZWP+sjF/2Zi/bMxfNuYvG/N3D085d0EwGMT06dO97gZ5hPnLxvxlY/6yMX/ZmL9szF825i8b85eN+buHR2gSERERERERERFRwWBB0wXRaBS7d+9GNBr1uivkAeYvG/OXjfnLxvxlY/6yMX/ZmL9szF825u8eFjRdoKoqSktLoaocbomYv2zMXzbmLxvzl435y8b8ZWP+sjF/2Zi/e3gNTRf4/X5UVFR43Q3yCPOXjfnLxvxlY/6yMX/ZmL9szF825i8b83cPS8YusCwLhmHAsiyvu0IeYP6yMX/ZmL9szF825i8b85eN+cvG/GVj/u5hQdMFhmFg9+7dMAzD666QB5i/bMxfNuYvG/OXjfnLxvxlY/6yMX/ZmL97WNB0QSAQwOTJkxEIBLzuCnmA+cvG/GVj/rIxf9mYv2zMXzbmLxvzl435u4fX0HRB4qKwJBPzl435y8b8ZWP+sjF/2Zi/bMxfNuYvG/N3D4/QdEEsFkNTUxNisZjXXSEPMH/ZmL9szF825i8b85eN+cvG/GVj/rIxf/ewoOmCWCyGxsZG7tBCMX/ZmL9szF825i8b85eN+cvG/GVj/rIxf/fwlHMXhEIhHHPMMV53gzzC/GVj/rIxf9mYv2zMXzbmLxvzl435y8b83cMjNImIiIiIiIiIiKhgsKDpAsMwEA6HYRiG110hDzB/2Zi/bMxfNuYvG/OXjfnLxvxlY/6yMX/3sKDpAkVREAwGoSiK110hDzB/2Zi/bMxfNuYvG/OXjfnLxvxlY/6yMX/35NU1NKurq7Fq1Sp88MEHsG0bp59+Om6//XaUl5fj73//Oy677DKMGTMm5T3Lli3D1772Nef51q1b8eijj6KtrQ3l5eX46U9/itNOOy3lPf21yWQb2fD7/TjyyCMH/H4qbMxfNuYvG/OXjfnLxvxlY/6yMX/ZmL9szN89eXOEZltbG6688krMmTMHO3bswPbt2+Hz+bB582YAQF1dHWbMmIEdO3akPJKLmdu2bcPdd9+Ne++9Fzt27MDVV1+Na6+9FtXV1Rm3yWQb2bJtG7FYDLZtD3gbVLiYv2zMXzbmLxvzl435y8b8ZWP+sjF/2Zi/e/KmoPnYY4/h2GOPxaWXXgpFURAKhbB69Wr85Cc/AQDU19dj/PjxfW5jw4YNWLRoEaZPnw4AmDt3Lk4//XQ88cQTGbfJZBvZikaj+OyzzxCNRge8DSpczF825i8b85eN+cvG/GVj/rIxf9mYv2zM3z15U9B85ZVXcNZZZ6X8m6Zpztf9FTT37duHcDiMc845J+XfE0d8ZtImk230J/nCr9FoFKZpwu/3Y8KECYjH47AsCwAQi8Wg63rK+0zTBNBV0dd1HfF4vNe2ie+T3jYej0PXdeevAQNtCwC6riMWi/XY1jTNXttalgVd152f1TTNlMkcjUazapsYl/S26ePSU9u+xnCoxzsxLqqqYuLEiVBVdVDjnTwuuRrvWCyWk/EezBjmerwHss8m2vY2htmOd/IYxuNxjB8/Hn6/f1DjzTWiMNcIVVUxbtw4+Hy+rMeQa0ThrxGJU44S78tkDLlGFM8a4ff7MXHiRNi2PSRjyDUiv9cI27YxceJE+P3+QX2O4BrRvW0hrBG2baOiogJ+v9+zfZZrhHdrhN/vx7hx45xrKA7l7xpcIwY2hkO5RiTXf/KhHlGoa0Qm8qagGQ6HMWLECCxduhRz5szBBRdcgPvvv9/5wevr69HW1oYbbrgB5513HubPn4+nnnrKeX99fT0AoLy8PGW75eXlzmv9tclkG/3Zv3+/83VtbS2ampqgaRqCwSBqamqcHbOtrS3lNPZ9+/ahsbERQNfOEw6H0dnZCQBob29HVVVVys964MABAF07RDgcRkdHBwAgEokgHA6n9Ce5T+FwGJFIBADQ0dGBcDjs7EwHDhxI+TmrqqrQ3t4OAOjs7EQ4HHYmTmNjI/bt2+e0ra6uRltbG4CunTscDjvZNTU1oba21mlbU1ODlpYWAF07bPIdwFpaWrB3716n7d69e9Hc3Ayga2KEw2Fnh29tbUVNTU3KGDY1NaWMYW/jXVdX54xh+ninj2F9fT0aGhoAdC0g4XAYBw8eTGmbmOgNDQ3dxrujowNlZWXOz5o83nV1dT2Od/oYNjY2prStqalBa2trj22bm5u7jXdiDNPvuNbc3JwyhrW1tU7bWCyWMobp411XV+fss+lt0/fZ5PHOZJ9NH+/EPnvw4MFu4528zya3Td9n08e7p3020bapqSll/04e70SOiYW2ubm52z6b2L8Nw0BNTQ38fj80TUNLS0u38U7ss+ljyDWiONaIzs5ONDQ0QFW7/nfb0xrR13hzjSjsNULTNESj0ZTtpq8Ryfss14jiWiM0TUNZWRkOHDgwqM8RXCMKc42or69HWVkZNE0b1OcIrhG9j/dQrhGR5WsGtUY0NDSgs7MTmqYN+e8aXCPyb43QNA2NjY1OjkP5uwbXiC759DlC0zSEQqE+6z9u1iMKdY3IhGLnyYn9J510EiZPnow777wTZ5xxBnbv3o0bb7wRZ555JpYsWYKf/vSnaGxsxLJlyzBp0iS8//77uP7667F48WIsWLAAH3zwAebPn493330XJSUlznZff/113HTTTXj77bf7bbNp06Z+t9Gbqqoq3HXXXbjxxhud09Wj0ShUVYWiKGhra0MwGERJSQlUVUUsFkMsFkMoFALQFayiKM5f8aLRqFME6aktAAQCgW5t4/E4TNN07qo10LZA147p8/ng8/m6tU385bmntpZlwTAMBAIBqKoK0zRhWRaCwaAzLpqmZdxWVVX4/f5ubdPHpae2fY3hUI93YlwURUFHRwdKS0th2/aAxzt5XHI13rFYDPF4fNDjPZgxzPV4D2SfTbTtbQyzHe/kMezs7EQ0GsWIESMAYMDjzTWiMNeIaDSK1tZWHHHEEfD7/VmNIdeIwl8jLMtCS0sLSktLUVpamtEYco0onjXC5/Ohvb0dwWAQPp8v52PINSK/14jEESrDhw939odc7LNcI9xZIzp+thah5f/fgNeIjo4OdHR0YNSoUc7nAbf3Wa4R3q0RsVgMTU1NGDFiBEKh0JD+rsE1Iv8+RyTXf0KhkOf1iEJcI+rq6rB27VosWbIEU6ZMQW/ypqA5d+5cfPe738WVV17p/Nt///d/Y8WKFdi1a1eP73nooYewfft2bNmyBQcOHMBXvvIV/OEPf0BlZaXT5qmnnsKjjz6KF198sd82mzdv7ncbvUkUNG+++WZMnjw55TVd11FVVYUpU6Y4OyXJwfxlY/6yMX/ZmL9szF825l/YIsvXoGzFrQN+P/OXjfnLxvwHr7q6OqOCZt6ccn766aennL+fkKgW91R3tSzLuS7F2LFjcfzxx+P1119PabNz507Mnj07ozaZbGMgQqEQjj32WO7MQjF/2Zi/bMxfNuYvG/OXjfnLxvxlY/6yMX/35E1B85prrsGmTZvw5ptvAui6VsGGDRswf/58AMB1112H1atXO9cVeP/997Fp0yZceumlzjauvvpqPPLII9i9ezcAYPv27XjjjTdwxRVXZNwmk20QERERERERERGRN3xedyChsrIS69atw69+9SvU1NRg2LBhuOiii3DttdcCAFasWIG7774b3/jGN2CaJoYPH44bbrgBl1xyibONefPmIRKJ4LrrrsPBgwdRUVGBBx98MOUQ1f7aZLKNbBmGgfr6elRUVDhHnJIczF825i8b85eN+cvG/GVj/rIxf9mYv2zM3z15U9AEgFmzZqXcuTxZRUUFVq9e3e82FixYgAULFgyqTSbbyJamaTndHhUW5i8b85eN+cvG/GVj/rIxf9mYv2zMXzbm7468KmgWq0AggAkTJnjdDfII85eN+cvG/GVj/rIxf9mYv2zMXzbmLxvzd0/eXEOzmNm2jXg83uONjaj4MX/ZmL9szF825i8b85eN+cvG/GVj/rIxf/ewoOmCaDSKTz/9FNFo1OuukAeYv2zMXzbmLxvzl435y8b8ZWP+sjF/2Zi/e1jQdIHf78eECRPg9/u97gp5gPnLxvxlY/6yMX/ZmL9szF825i8b85eN+buH19B0gaZpGD58uNfdII8wf9mYv2zMXzbmLxvzl435y8b8ZWP+sjF/9/AITRfE43G0trYiHo973RXyAPOXjfnLxvxlY/6yMX/ZmL9szF825i8b83cPC5ouME0TdXV1ME3T666QB5i/bMxfNuYvG/OXjfnLxvxlY/6yMX/ZmL97eMq5C4LBII499livu0EeYf6yMX/ZmL9szF825i8b85eN+cvG/GVj/u7hEZouUBTFeZA8zF825i8b85eN+cvG/GVj/sVv5Ttben2N+cvG/GVj/u5hQdMFhmGgpqYGhmF43RXyAPOXjfnLxvxlY/6yMX/ZmL9szF825i8b83cPC5pEREREREQkRt12D+EAACAASURBVF9HVxIRUWHgNTRdEAgEMGnSJK+7QR5h/rIxf9mYv2zMXzbmLxvzl435y8b8ZWP+7mFB0wW2bTtf8zoK8jB/2Zi/bMxfNuYvG/OXjfnnl0U716c81+NGyr9tnL0YrQsXJzXQU58DGLk5dRt9Yf6yMX/ZmL97eMq5C6LRKD7++GNEo1Gvu0IeYP6yMX/ZmL9szF825i8b888/U8vKnUdICzhfJ9OmTYE2bQoQCjlfa9OmZP29mL9szF825u8eFjRd4Pf7ceSRR8Lv93vdFfIA85eN+cvG/GVj/rIxf9mYv2x+vx9Hbvo98xeK81825u8ennLuAk3TMHLkSK+7QR5h/rIxf9mYv2zMXzbmLxvzl03TNGiaD5qmed0V8gDnv2zM3z08QtMF8Xgc7e3tiMfjXneFPMD8ZWP+sjF/2Zi/bMxfNuYvWzweRzweY/5Ccf7Lxvzdw4KmC0zTRG1tLUzT9Lor5AHmLxvzl435y8b8ZWP+sjF/2UzTRDRqMH+hOP9lY/7u4SnnLggGgzj66KOhqqwfS8T8ZWP+sjF/2Zi/bMxfNuZffLK7U7qNoB5F9OqfIIrDdznO5k7pVLg4/2Vj/u5hQdMFiqLw+imCMX/ZmL9szF825i8b85eN+Ren5Lui74nsd57viex3/j1xV/T47qqUO6THd1e51EvyGue/bMzfPSwZu8AwDNTW1sIwDK+7Qh5g/rIxf9mYv2zMXzbmLxvzl822LedB8nD+y8b83cMjNF3CC8LKxvxlY/6yMX/ZmL9szF825l94nKModb3HIyqTj8TU40bK83R2zntHhYTzXzbm7w4WNF0QCAQwefJkr7tBHmH+sjF/2Zi/bMxfNuYvG/MvPMnXt4wsX4OyFbemvL4xrf3Kd7Zg2SmX9bgtRVGhKioUhSdESsT5Lxvzdw9XWCIiIiIiIiIiIioYLGi6QNd1fPzxx9B13euukAeYv2zMXzbmLxvzl435y8b8ZbOsuPMgeTj/ZWP+7mFB0wU+nw/jxo2Dz8cz/CVi/rIxf9mYv2zMXzbmLxvzl01RFOdB8nD+y8b83cMRdoHP58MRRxzhdTfII8xfNuYvG/OXjfnLxvxlY/6yKYeun8lraMrE+S8b83cPV1gXxONxRCIR3ulKKOYvG/OXjfnLxvxlY/6yMX/p7KQHScP5Lxvzdw8Lmi4wTRN79+6FaZped4U8wPxlY/6yMX/ZmL9szF825i+bZVnOoy+R5Wtc6hG5ifNfNubvHp5y7oJgMIjp06dD0zSvu0IeYP6yMX/ZmL9szF825i8b85dNVVXYqgpV5fFDEnH+y8b83cOCpgsUReEFYQVj/rIxf9mYv2zMXzbmLxvzl05JepA0nP+yMX/38E9GLjBNE3V1dTzkWCjmLxvzl435y8b8ZWP+sjF/2Wzbch4kD+e/bMzfPSxousC2bUSjUdg2LwotEfOXjfnLxvxlY/6yMX/ZmD8xerk4/2Vj/u7hcbAuCAQCqKys9Lob5BHmLxvzl435y8b8ZWP+sjF/2RSl6/qZisLjhyTi/JeN+buHKywREREREREREREVDBY0XaDrOj755BPouu51V8gDzF825i8b85eN+cvG/GVj/rJZVtx5kDyc/7Ixf/ewoOkCn8+HMWPG8E5XQjF/2Zi/bMxfNuYvG/OXjfkXv2WnXNbra4qiOA+Sh/NfNubvHo6wC3w+H0aPHu11N8gjzF825i8b85eN+cvG/GVj/rIpiuo8SB7Of9mYv3u4wrrAsix0dHTAsiyvu0IeYP6yMX/ZmL9szF825i8b85fOTnqQNJz/sjF/97Cg6QLDMFBdXQ3DMLzuCnmA+cvG/GVj/rIxf++sfGeL111g/sIxf9ksy3IeJA/nv2zM3z085dwFgUAA06ZN4zUUhGL+sjF/2Zi/bMxfNuYvG/OXTVVV2KoKVeXxQxJx/svG/N3DEXaBqqoIBAJed4M8wvxlY/6yMX/ZmL9szF825i+dkvQgaTj/ZWP+7uGfjFxgmibq6+thmqbXXSEPMH/ZmL9szF825p+/IsvXDPn3YP6yMf+ByYfLReSCbVvOg+Th/JeN+buHBU0X8KKwsjF/2Zi/bMxfNuYvG/OXjfmTbfOGQFJx/svG/N3DU85dEAwGMW3aNK+7QR5h/rIxf9mYv2zMXzbmLxvzl01RVKiqBkXh8UMScf7Lxvzdw4ImERERERERUQ7Ed1d1faHrh78+pHXh4tTGup7ybyM3rx/q7hERFQ3+ycgF0WgUn332GaLRqNddIQ8wf9mYv2zMXzbmLxvzl435e8eNa+T2ZuTm9Ri5eT1Cj6yDMXUyQo+sc/4tUazUpk1xHgiFDn9NRYPzXzbm7x4WNF2gaRpGjhwJTdO87gp5gPnLxvxlY/6yMX/ZmL9szF82TdPg82nMXyjOf9mYv3t4yrkLfD4fxo4d63U3yCPMXzbmLxvzl435u2vRzsOnaupxI+X5xtmLU0/1TDvNE8j9qZ7MXzbmX9jKVtw6qPf7fD74/QH4fPx1WyLOf9mYv3t4hKYLLMtCZ2cn73IlFPOXjfnLxvxlY/7um1pWjqll5QhpAefrZD2d5jlUp3oyf9mYv2yWZcGy4sxfKM5/2Zi/e1jQdIFhGKiqqoJhGF53hTzA/GVj/rIxf9mYv2zMXzbmL5thGND1KPMXivNfNubvHhY0XRAIBFBZWYlAIOB1V8gDzF825i8b85eN+cvG/GVj/rIFAgGEQkHmLxTnv2zM3z28qIcLVFVFKBTyuhvkEeYvG/OXjfnLxvxlY/6yMX/ZVFWFqmpQVR4/JBHnv2zM3z1cYV1gmiYaGhpgmqbXXSEPMH/ZmL9szF825i8b85eN+ctmmiZM02D+QnH+y8b83cOCpgssy0J7ezsvCisU85eN+cvG/GVj/rIxf9mYv2yWZSEe502BpOL8l435u4ennLsgGAziqKOO8rob5BHmLxvzl435y8b8ZWP+sjF/2YLBIMxQCYLBoNddIQ9w/svG/N3DIzSJiIiIiIiIiIioYLCg6YJoNIp//vOfiEajXneFPMD8ZWP+sjF/2Zh/YYssXzOo9zN/2Zj/0Fj5zhavu5CRaDQKXe9k/kJx/svG/N3DgqYLVFVFWVkZ73InFPOXjfnLxvxlY/6yMX/ZmL9sqqpC03iXc6k4/2Vj/u7hNTRd4Pf7UV5e7nU3yCPMXzbmLxvzl435y8b8ZWP+svn9fvj9Afj9fq+7Qh7g/JeN+buHJWMXWJaFaDTKu1wJxfxlY/6yMX/ZmL9szF825i+bZVmwbYv5C8X5Lxvzdw8Lmi4wDAN79uyBYRhed4U8wPxlY/6yMX/ZmL9szF825i+bYRjo7NQHnf9gr+VL3uD8l435u4cFTRcEAgFMmTIFgUDA666QB5i/bMxfNuYvG/OXjfnLlmn+hXKTG8pOIBBAKBTk/BeK679szN89eVXQrK6uxo9+9CPMnj0bZ555Jv7t3/4N+/fvd17funUr5s2bh7POOguXXHIJ/vrXv3bbRi7aZLKNbKiqipKSEl4UVijmLxvzl435y8b8ZWP+sjF/2VRVharypkBScf7Lxvzdkzcj3NbWhiuvvBJz5szBjh07sH37dvh8PmzevBkAsG3bNtx999249957sWPHDlx99dW49tprUV1d7WwjF20y2Ua2YrEYGhsbEYvFBrwNKlzMXzbmLxvzl435y5Zp/jyltDhx/ssWi8VgmibzF4rzXzbm7568KWg+9thjOPbYY3HppZdCURSEQiGsXr0aP/nJTwAAGzZswKJFizB9+nQAwNy5c3H66afjiSeecLaRizaZbCNbsVgMzc3N3KGFYv6yMX/ZmL9szF825i8b85ctFoshFuu5oBnfXeU8oOuHvz6kdeFi5xH/349TnrcuXOzmj0EDxPkvG/N3T94UNF955RWcddZZKf+maRoAYN++fQiHwzjnnHNSXk8czZmrNplsoz/JF36NRqMwTROhUAhHHXUUADh3uorFYtB1PeV9pmkCAGzbhq7riMfjvbZNfJ/0tvF4HLquw7btQbUFAF3XnUmY3tY0zV7bWpYFXdedn9U0TUSj0ZRxyaZtYlzS26aPS09t+xrDoR7vxLj4fD4cffTR8Pv9gxrv5HHJ1XjHYrGcjPdgxjDX4z2QfTbRtrcxzHa8k8cQAI466iiEQqFBjTfXiMJcI/x+PyZNmoRgMJj1GHKNKPw1IhQKobKyEoqiZDyGXCMGt8+m31XYsizg0PcEbFhWHICd1Dbe63hbVnxQa0QoFMLRRx8NVVX7HEPLig9oDLlG5PcaoSgKjj76aIRCoT7H27atrMaw2NeIxPxMHu9FO9dj0Y77sGjHenzYWoNFOw4/X7RzPUzTROvCG9KKgInnN3Rt99Ay0NcakcvPEaqqIhQKIRQKpYzLyM3rMez//geCD6/FyM3roZ1wLEo23o2SjXdj5Ob1h8bKhjZtMrRpU4BQEErlxMPPYXON6KFtvq0RoVAIkyZNgs/nS2k7FL9rSFsjCuF3jeT6Tz7UIwp1jchE3hQ0w+EwRowYgaVLl2LOnDm44IILcP/99yMWi6G+vh4AUF5envKe8vJy57VctMlkG/1JvuZnbW0tmpqaAHQFFQ6HnR2zra0t5TT2ffv2obGxEUDXzhMOh9HZ2QkAaG9vR1XV4b/a1dfX48CBAwC6dohwOIyOjg4AQCQSQTgcTulPcp/C4TAikQgAoKOjA+Fw2NmZDhw4kPJzVlVVob29HQDQ2dmJcDjsTJzGxkbs27fPaVtdXY22tjYAXTt3OBx2dtqmpibU1tY6bWtqatDS0gKga4cNh8PORGppacHevXudtnv37kVzczOArokRDoedHb61tRU1NTUpY5gY78QY9jbedXV1zhimj3f6GNbX16OhoQFA1wISDodx8ODBlLaJid7Q0JDVeNfV1fU43ulj2NjYmNK2pqYGra2tPbZtbm7uNt6JMTQMI2W8m5ubU8awtrbWaZu+z6aPd11dnbPPprdN32eTxzuTfTZ9vBNjePDgwW7jnbzPJrdN32fTx7unfTbRtqmpKWX/Th7vxD6bWGibm5u77bOJ/Tsx3ol9tqWlpdt4c43gGsE1gmsE14jcrRFmDx+ME/tD17ajSR+i4ylt09cIXY+6skboenTQa8TKd7ZwjTik0NYI04xxjUga78R0TV8jyn3DMTF0BEJaAJNLx6BcG44pw8Y6421ZFrRpU6BNmwIr4Ic1afyhAiAO9ffQL+V9rBG5/hyRyDjbNcKyLGdfArrWrQTLtvk5ArLWCH6O4O8aUn/XyIRiJ3/K89BJJ52EyZMn484778QZZ5yB3bt348Ybb8SZZ56JefPmYf78+Xj33XdRUlLivOf111/HTTfdhLfffhsffPDBoNts2rSp3230pqqqCnfddRduvPFG53T1aDQKVVVhWRZqa2sxZswYlJWVQVXVQ6chxBAKhQB0BasoCvx+P2zbRjQahd/vh6ZpPbYFuu6eld42Ho/DNE0Eg0EoijLgtsDhowt9Pl+3tqZpwrbtHttalgXDMBAIBKCqKkzThGVZzhFK0WgUmqZl3FZVVfj9/m5t08elp7Z9jeFQj3diXCzLwv79+1FeXg5VVQc83snjkqvxjsViiMfjgx7vwYxhrsd7IPtsom1vY5jteCePYSQSQWNjIyZMmOD8DAMZb64RhblGdHR0oK6uDhMmTEAoFMpqDLlGFP4aYZomamtrMXbsWAwfPjyjMeQaMfB99uo37kflsLGwbaCq4wCmlpXDsixUHWzAxrN+jNaFN0CpnARVVRHfXQ116iTYtg1V1RDfXYXQI+tS1+/lqzHs328d8BqhKAr27duHsWPHIhAI9DqGB+9cg+Erl2Q9hsltV76zBbeccCHXCJfXiDX/2Iblp17e4xqh6zoaGxsxfvx42Lbd63ivePtJ3Dbzot4/RyxfjbIVt4lZI371v9uw7JTLU8Z70c71mFI6FoqiIHywAZXDxsG2bef5//nitej44b9Bm1YJAIjvDkOdOhmKoiK+O4zgw+tww5uPYOrwcti21esakcvPEZFIBA0NDZgwYQICgUCv4x1ZvgaBpf+WMoZt31t8qBirIL477KxbieclG+/h54g8XyOi0Sj27t2LI488EqWlpUP6uwY/R+Tf7xrJ9Z9hw4Z5Xo8oxDWirq4Oa9euxZIlSzBlStcfp3ri6/UVl40fPx6XXXYZZs2aBaDrFM3rr78eK1aswFVXXQWgq7pfWVnpvGf//v2oqKgAABx55JGDbpPJNvqT2BkAOKGYponS0tKUO10lwu/pfYlriCZk01bTNOdU/cG0BdBnW7/f32vbxCkWvbVNjMtg26aPSzZt3RhvoGtcTNNESUkJ/H5/ys+XD+M9mDFMbjuYMcz1ePfWtq8xHMrxLikpQWlpKVRVzft9lmtE7sfb7/c7H2TS2wJ9j2E+jDfXiOzbJo+LqqooLS1NeT3f99lCXyMURUXSGf5dn7ucf1CgqlqvbdO3q6qH+zyQ8U78/z8YDDo/Q09jqKqac1kCrhE9t83XNSKRW29tE5/9k9/b0z6bPBY97Ye9/f5QnGtE15imj3fy3YIVRUm5lEdXW+XwdSj1KKw9iSN+DvVJAfZEDh+1pMeNw88PbSvX+3fi81+24901Bj2vW4CS0p5rRPefNR/WCFVVMWzYMOffCmG8C2eN6JLPv2sk138G8zkik7aDGcN8GO++9tlM5E1B8/TTT085fz8hEAhg7NixOP744/H666/je9/7nvPazp07MXv2bADISZtMtjEQfr8/44IoFR/mLxvzl435y8b8ZWP+sjH/zC3aud75Wo8bKc83zu66CU6i+JhSiEwycvPh90SWr0HZiltTXk9sJ2HlO1uw7JTLBt/5XjB/2Zj/wPQ0dwsR83dP3hQ0r7nmGlxxxRU4+eSTMWvWLOzduxcbNmzA/PnzAQBXX3011qxZg9mzZ2PatGnYvn073njjDTzzzDPONnLRJpNtZCtxHZSuv8LnzWVLySXMXzbmLxvzl435y8b8ZWP+2Zla1nUPgz2R/SlfA6nFyFwVIoeymAkwf+mYv2zM3z15U9CsrKzEunXr8Ktf/Qo1NTUYNmwYLrroIlx77bUAgHnz5iESieC6667DwYMHUVFRgQcffDDlfPpctMlkG9lKXPi0srIy5fBakoH5y8b8ZWP+sjF/2Zi/bMxfNuYvm8T8h/qo50IiMX+v5E1BEwBmzZqFp556qtfXFyxYgAULFvS5jVy0yWQb2fD7/Zg0aVK3awmQDMxfNuYvG/OXjfnLxvxlK7T8i+VUz3yRaf4c8+JUaPOfcov5u4fHv7pA07SUm0KQLMxfNuYvG/OXjfnLlqv8V76zJUc9IjdpmgZ79QbOf6G4/svG/GVj/u5hQdMFsVgMTU1NiMViXneFPMD8ZWP+sjF/2Zi/bMy/sA22kByLxRCLmcxfKM5/2Zi/bMzfPSxouiAWi6GxsZE7tFDMXzbmLxvzl435y8b8ZYvFYjBNFjS9kA+ncXP+y8b8ZWP+7smra2gWq1AohGOOOcbrbpBHmL9szF825i8b85eN+csWCoUQKyn17IYQi3aud77W4wZCWiDl9bsf+jD1DbqO1oWH7yY+cvN60MBx/svG/LuTdJ1e5u8eFjSJiIiIiIiKzNSycgDAnsh+5+vEcwDQpk1x/i2+u8p5Ht9d5WIviYiIBoannLvAMAxUVVXBMAyvu0IeYP6yMX/ZmL9szF825i+bYRiIRnXmn2PLTrnM6y5khPNfNuYvG/N3DwuaLlAUBX6/H4qieN0V8gDzl435y8b8ZWP+sjF/2RRFcR4kD+e/bMxfNubvHhY0XeD3+zF+/Hj4/X6vu0IeYP6yMX/ZmL9szF82v9+PR+p2Mn+h/H4/AoEg8xeK679sucp/5TtbctQjchPnv3t4DU0X2LaNeDwOTdNYpReI+cvG/GVj/rIx//zjXBtQ13u8TmDyTVEGepOUlJuxxIyU5xtnL079HoP4PpTfbNuGbVuwbTtl/ifvD0DXDXv63EfS9g+A+0gh4Povm5T8028+xrWsi5T88wELmi6IRqMIh8OorKz07E6H5B3mLxvzl435y8b880umvzgl3xhloDdJmVpWDsuysKe9HlNKx0JVVedGLMnfY7Dfh/JXNBpFZ6cOfzTabf6n36An+eY9CT3th4nnhUrSXY65/ssmKf+ebj5W7GtZfyTl7zUWNF3g9/sxceJEHnIsFPOXjfnLxvxlY/6yKYoCRVV5dEYRye7oShtBPYro1T9BFEn7wDXHu9BT8hrXf9mYv2zM3z0saLpA0zSUlZV53Q3yCPOXjfnLxvxlY/6y8aYwhae/0yezo6T997Dko5f0uJHynIoD13/Zii3/le9swbJTLvO6GwWj2PLPZyxouiAWiyESiaCsrAw+H4dcGuYvG/OXjfnLxvxl67qGot3tGoqU3/o6fTK9qNnTL/mJSxvEYjFElq9G2YrbUub/xrTvx0JBceL6Lxvzl435u4d3OXdBLBZDfX09YrGY110hDzB/2Zi/bMxfNuYvm23bsK2um8KQPLFYDIZhFs38jyxf43UXCgrXf9mYv2zM3z0saLogFArhuOOO4wVhhWL+sjF/2Zi/bMxfNlVVoWoaVNX7j9ssRrkvFAqhtLTUlfm/8p0tQ/49KDtc/2Vj/rIxf/d4/wmLiIiIiIg8xaInEVHu8A8NREOPBU0XGIaB6upqGIbhdVfIA8xfNuYvW7Hlzw/n2Sm2/Ck7lmU5D8o/Q72eGYaBaFTn/BeK679shmFAL6D5zz9o5Rbnv3tY0HRJPpxuRN5h/rIxf9mYv2zMn0iy/m8GxRsCFS+u/7IpGcx/Kl6c/+7gLZdcEAgEMHHiRK+7QR5h/rIxf9mYv2zMf2CK5a7Pqqo6D5InEAggGAwiEAh43RXyANd/2Tj/D4vvrur6QtcPf52kdeHiw090PeX5yM3rh7p7Q4Lz3z0saLrAtm3Ytg1FUaAo/EuNNMxfNuYvG/OXjflLZwP2of/ySB1xuu5uf3gNyKVFO1N/ydfjRsq/bZzdVRDYE9nvvJ74mtzB9V+2RP5DMf8LSXJBMrJ8DcpW3NpjO23aFABdxc/krwsV5797+CdjF0SjUXzyySeIRqNed4U8wPxlY/6yMX/ZmP/QKJRrfVmWDcuKw7Jsr7tCHohGo+jo6Byy+T+1rNx5hLSA83XCxtmLncfxIyelPE8UPHON11k+jOu/bNFoFJ2dQzf/Kb9x/ruHR2i6wO/3Y/z48fD7/V53hTzA/GVj/rIxf9mYv2yKokBR1SE5OiOTI/T6Oo0PKNxT+QqF3+9HMBgo6vmfyX6Y/AeI+O6qbn+QSByxVWxHk3L9l83v9yMQKO75T73j/HcPC5ou0DQNI0aM8Lob5BHmLxvzl435y8b8ZUucajaQgmZyUSi9SJSNnk7jSzynoaVpGjTNB03TvO5Kr1L2gx6ub9dfURzXHJ9yVOieyH7neaIomXyKaW+nnCYfMVos19Dl+i+bpmnw+fJ7/hervk5tdwvnv3tY0HRBPB5HJBJBWVkZFzWBmL9szF825i8b85dtsNdQSy4MpReN0k8ZLpYiUDGJx+OIx2OIx+N5Of/Tj9DtrQjAovjAcP0vfn2tu/F4HLFY//M/H4pvlHuc/+5hQdMFpmmirq4OlZWV3KEFYv6yMX/ZmL9szD8zxXr6tG3bsC1L/E0hpDJNE3Xfm49K0+T8F4jrv2ymacIwDJh5MP/5By/3cf67hwVNFwSDQRxzzDH8MCsU85eN+cvG/GVj/pnr77RVoPCOFFNVBaqqQVWZv0Sc/wNTLIUX5i9TyuVCYgZu+J9HUl6/+6EPU9+Q9ge6fPzjHGWP8989LGi6YKDXT6LiwPxlY/6yMX/ZmL90CqAc+u8QK5YiUDHh/JeN+cvV1+VCAHT7g1zyH+uoOHD+u4cFTRcYhoGGhgaMGzcOgUDA6+6Qy5i/bMxfNuYvG/OXzbIs56GqqtfdIZdx/svG/ItPJpdHAQ4VLm0betzEnvZ6gIUtcTj/3cOCpkts2/a6C+Qh5i8b85etkPLndZZyr5DyJypmWRUjDr2efMmDgeD8TyXt5ifMv/j0d3mUxDpiGAZWvP2fWH7q5SkFrdaHUq//TMWL898dLGi6IBAIYNKkSV53gzzC/GVj/rJJzJ937DxMYv50mKqqziNdyqmFut7jqYa5LKxRl0yLEcDg/8DD+S+bm/nz/7v5JxAIIBgMenZ0Xsq1PNP+eAPwWp5Djeu/e1jQJCIiol7xQzFRbqXPiZ6KEbksrBERkTy8lidJwIKmC3RdRzgcRmVlJUKhkNfdIZcxf9mYv2zFkj8/FA9MseSfS5KKc5ZlwYrHPb2GpjMHezgKNPkPD4k2/GNE7nD+y8b8ZdN1HR0dHdB1vWDz7+8P2kNxmY5iwfnvHhY0XeDz+VBRUQGfj8MtEfOXjfnLxvxlY/6yKYoCRVU9u9NpckGyp6NAWxcu5h8jhlChzX+espxbhZY/5ZbP50MgECj4/Pv7gzbPJugZ5797OMIu8Pl8GDVqlNfdII8wf9mYv2zMXzbmn1t9HW2YkE9HiiiK4jxIHs5/2Zi/bD6fz3mQPJz/7uEMc0E8HkdHRwdKS0uhaZrX3SGXMX/ZmL9szF825p87/R1tCOTfkSK2bTsPKUVN3pzkMM5/2Zi/bPF4HLF4DPF4nPkLxPnvHhY0XWCaJmpra1FZWckdWiDmLxvzl435y8b8ZbNtG7ZliSpo0mGc/7Ixf9lM04QRNWCaZtb5D+RmjEi6TiOvf+w9zn/3sKDpgmAwiKOPPtqzC8KTt5i/bMxfNuYvG/OXTVUVqKoGVWUxU6LBzv/+LrGQfEmFfLjEAqXKp/U/H45YlyYYDKKkpATBYHBA7+fNGAtbPs3/YseCpgsURWFlXjDmLxvzl435y8b8pVMA5dB/qeAMtgA0mPnf3yUWNqa1Z8Eq/3D9l01RgS5EFgAAIABJREFUFCw/9XKvu0Ee4fx3DwuaLjAMAwcOHMDYsWMRCAS87g65jPnLxvxlY/6yMf/ik37qnx43ENIOZ5u4jueeyH7AtqHHTexprwd4yrk4nP+yMX/ZJObPP6ocJjF/r7Cg6ZJYLOZ1F8hDzF825i8b85eN+Ref9NP/kk8NBA4XNQ3DwL//9UncedqCPn+h4U10ilcu5j/3j8LF9V825j80CuWIdObvDhY0XRAIBDBlypT+G1JRYv6yMX/ZmL9szF+2QCCAUCjEozOKWF+/VHP+y8b8ZWP+sjF/97CgSUREREREVKQK4Wgm8lZP12olygc9Xeol+d82zl6M1oWLkxroqc/BO78XM952yQW6ruPjjz+Gruted4U8wPxlY/6yMX/ZmL9suq6jo6OD+efYyne2eN2FjHD+y8b8ZWP+uTW1rNx5hLSA83UybdqUrru9h0LO18l3g3cT83cPj9B0gc/nw7hx4+DzcbglYv6yMX/ZmL9szF82n88Hf8DP/IXi/JeN+cvWV/7x3VWHn+h66vNDEtdk1uOG8zUVDs5/93CEXeDz+XDEEUd43Q3yCPOXjfnLxvxlY/6y+Xw++H0saHohH06f5fyXjfnL1lv+6ac+97RWJW4sB/R8A5zWh1JPp6b8w/nvHn7CckE8Hoeu6wiFQtA0zevukMuYv2zMXzbmLxvzly0ejzsP5i8P579sXueffI3B9GsOAsDdD32Y+oa06w4W+zUHh/qPHl7nT95i/u7hNTRdYJomampqYJqm110hDzB/2Zi/bPmUf6Fcd66Y5FP+5D7TNBGNRpm/UG7Of970J//kw/rf0zUHk687mHKdwaTrDtLg5Sr/oZzb8d1VziNx6nv66e97IvuxJ7LfOfU98aC+5cP8l4JHaLogGAziqKOO4ilHQjF/2Zi/bMxfNuYvWzAYRElJCMFg0OuukAc4/2Vj/rLle/65OPWdepfv+RcTjrALFEWB3+/3uhvkEeYvG/OXjfnLxvxlUxQFiqJCURSvu0Ie4PyXjfnLxvy78/q6xm5i/u5hQdMFpmmisbERY8aM4Y4tEPOXjfnLxvxlY/6ymaYJwzBgmibzF4jzX7bB5u+c+tvDXbCTr3WZaCPp+peFgPNfNubvHhY0XWBZFqLRKCzL8ror5AHmLxvzl435y8b8ZbMsy3kMBk/zK0yc/7INJv/kgmRPpwK3Llyccq3L+O4q53l68ZO8wfkvG/N3DwuaLggGg6isrPS6G+QR5i8b85eN+cvG/GULBoMIhXgNTak4/2Vj/rIxf9mYv3t4l3MiIiIiKio8qpGIiPKdpOtKEg0FHqHpAl3XUVNTg0mTJiEUCnndHXIZ85eN+cvG/GVj/l0W7Tx8+qQeN1KeJ+yJ7E9pk/y8UOm6js7OTui6Ljp/qTj/ZWP+sjF/2Zi/e1jQdIHP58MRRxwBn4/DLRHzl435y+Z1/v0VkqaWlac83xPZj5XvbHGeJ45ySxSXiqXQ5Bav888niX1tT2R/yn63J7IfG2en3uBi5TtbiuIIS5/P5zxInmKZ/33dnAYozj9G5EKx5E8Dw/yzU2zrDPN3D0fYBT6fD2PGjPG6G+QR5i8b85ctH/Lvq5CUXjTqqZCUXGzq6fXWh9LutkqOfMifvOPz+eD3+4vmFxovC839/XFm4+zFqXd+zoO7PhfD/O/v5jQb09oXyx8jcqEY8qeBY/6Z63edKcA/ejJ/9xTHJ6w8Z1mWc7qRqvKypdIwf9mYv2zMXzbmL5tlWYjH47Asi/nnQF9/nMmUm0f5cP7LxvxlY/6yMX/3sKDpAsMwUF1djcrKSl5DQSDmLxvzl435y8b8ZTMMA9FoFIZhMH8X5NtRPpz/sg11/imn5fZzmm4hnKJbbDj/ZWP+7mFB0wWBQADTpk0rmlOOKDvMXzbmLxvzl435F6ZcXcsrEAggFAohEAgMST8pv0mc//l+GqibhjL/9Eso9FfA5+Vi3Cdx/tNhzN89HGEXqKrKD7OCMX/ZmL9szF825l94cnmUn6qqzoPk4fyXjfnLxvxlY/7u4ScsF5imif3798M0Ta+7Qh5g/rIxf9mKLX8efZOdYsufsmOaJgzDYP5Ccf7LVmz5R5av8boLGVv5zhavu1B0+VN2mL97WNB0gWVZOHjwICzL8ror5AHmLxvzl435y8b8ZbMsC3ErzvyFKrb5n360MvWt2PKn7DB/2Zi/e3jKuQuCwSCmTZvmdTfII8xfNuYvG/OXjfnLFgwGURIqQTAY9Lor5AHOf9mYv2zMXzbm7x4eoUlEREREREREJBCPwKZClTcFzb///e+YOXMmzjrrrJTHH//4x4xeT9i6dSvmzZuHs846C5dccgn++te/dvte/bXJZBvZiEaj+OyzzxCNRge1HSpMzF825i8b85eN+csWjUbR2dnJ/IXi/JeN+ctWbPnzGurZKbb881nenHJeV1eHGTNm4KmnnhrQ6wCwbds23H333Xj88ccxffp0vPzyy7j22mvxzDPPYPLkyRm1yWQb2dI0DSNGjICmaQN6PxU25i8b85eN+cvG/GXTNA2aT2P+QnH+y8b8C1tk+ZpBHbXI/GVj/u7Jm4JmfX09xo8fP+DXAWDDhg1YtGgRpk+fDgCYO3cunnnmGTzxxBNYsmRJRm0y2Ua2fD4fxo0bN6D3UuFj/rIxf9mYv2zMXzafz4eAPwCfL28+buelRTvXpzzX4wZCWsB5vnH2YgDAnsh+5/XE1/mM81825i8b85eN+bsnb045H2xBc9++fQiHwzjnnHNS/n3OnDnYsWNHRm0y2UZ/DMNwvo5GozBNE5ZlobOzEx0dHc6drmKxGHRdT3mfaZoAANu2oes64vF4r20T3ye9bTweh67rsG17UG0BQNd1xGKxHtuaptlrW8uyoOu687OapplyuHU0Gs2qbWJc0tumj0tPbfsaw6Ee78S4mKaZ8t+BjnfyuORqvGOxWE7GezBjmOvxHsg+m2jb2xhmO97JY9jR0eHM/cGMN9eIwlwjTNNEa2ur8zybMczVGmHbdteYdDWFbVspd11MHu9E/7NZIxIb7tpu3Glr21bSazLXCMuyEIlE0NnZ2ecY5mJNzvc1wtkPD0nfD9Pb9jXetm25skZYVnxQa0RiH9B1fUj22WzaBpfd1G2fdRYF2Ifm7uG5fPi17D5H2LY1oPGeWjYOU0rHonLYOIS0ACqHdT1PeOAL1+CBL1yDjbMX4/iRE7HhjKvw0Jd/hI2zF+PBL13XLZuun8HbNULXdeffBvM5QsoaUWyfI3RdRyQSgWVZgxpvwO53DBP7ezbjnT7vAdvZTk/jbVnxvP5dY9GO+7oeO9fjw9aaQ8/XY9HO9YjFYmhdeANaFy4+9LgB8f/92Pm6deEN3fbZxLikj2Eiz0NDdqjv3fdZy7LQ1tbmPM/l7xqpWdlJj67nyW27Pv8d/iyW/HkwH9cI27b6XSN6Gu+unzWeMi7J+7fba0Ry/Scf6hFD/bvGUNUjMpFXBc22tjbccMMNOO+88zB//vyU08szeR0AysvLU7ZbXl7uvNZfm0y20Z/9+w//xbi2thZNTU0wDANVVVWorq52dsy2tjZUV1c7bfft24fGxkYAXTtPOBx2fgFqb29HVVVVys964MABAF07RDgcRkdHBwAgEokgHA6n9Ce5T+FwGJFIBADQ0dGBcDjs7EwHDhxI+TmrqqrQ3t4OAOjs7EQ4HHYmTmNjI/bt2+e0ra6uRltbG4CunTscDjs7bVNTE2pra522NTU1aGlpAdC1w4bDYWcitbS0YO/evU7bvXv3orm5GUDXxAiHw84O39raipqampQxbGpqShnD3sa7rq7OGcP08U4fw/r6ejQ0NADoWkDC4TAOHjyY0jYx0RsaGrqNd0tLC8LhMNrb27uNd11dXY/jnT6GjY2NKW1ramrQ2traY9vm5uZu450YQ8MwUsa7ubk5ZQxra2udtrFYLGUM08e7rq7O2WfT26bvs8njnck+mz7eiX324MGD3cY7eZ9Nbpu+z6aPd0/7bKJtU1NTyv6dPN6JfTax0DY3N3fbZxP7t2EYqK6uRnV1NQzDQEtLS7fxTuyz6WPINaI41ojW1lbU1dU5/e9pjehrvHOxRqQXHk0zhqgRTWmbGMNE/7NZIxJisXjaBxLDmatS1wjDMLB3796U/Tt9jUjeZwtxjfjRrgdx1c4NWLRzPa79f/8HP3ij6xfIRTvX40e7HnT22T2R/djTXg89Zhz6en/KUXbJ453oU29rhK5HXVkjdD06qDXCMAzouj7ozxFDtUYkvmfXGnF47sZisZRiczafI6LR6IA+R3T7Y0o89Ze55PG2bfS7zxrG4V8SvVwjEmM1mM8Rhb5GSP4csXfvXhiGMajPEYn39rVGJMYsmzWiaxyjSYUkG9Ho4cJG+u8auh7N6981LNvG+MAoTC0rR0gNoFwbjkmlo53xtiwL2rQp0KZNQWxCBaxgwHme+OMjcHiNSEhfI5ILSbZTbEa38TYMA/v27XP2w1z+rpE4SCLxdeKRyDFlTTZSM9Z1Hfahz4P5uEaYptnvGpEY7/Q1IhqNOuOb+P9a4md3e43IpP7jZj1iqH/XGKp6RCby5hwYRVHQ2NiIZcuWYdKkSXj//fdx/fXXIx6PY8GCBf2+njidR1XVbttNhNtfm0y20Z/kYuiECROgqio0TcOUKVNg2zZCoRAAYMSIESgtLXXajh8/HoqiAOi65kJlZSX8fj8AYPjw4SgpKfn/2bv32DjO+27035ndnV1KlClZF8qWREqWZblJTt6mMU5RI0oDNze0boqcOK4OjuX0heDGb6xcmqa5nFROavec2E7q90WjNLBh+z2OEfSFA9gNUgQw4gKxFffyR+KgaprYTkItJUq8iKQo3nZndmbOH6sd7iyX5C65fGa53+8HELDDfTh6+PvOPJx9OJeobW9vb/Tatu1Y2+7ubvT399ftD4BY202bNqG/vz/6eXfs2BFr29fXF9Wkq6sL/f390X0gtm/fHqvJvn37ora5XA79/f3R8rXXXoutW7dGbffu3RutJ5vNor+/H45TvrRo69atuOaaa6K2e/bsifqXyWRibXt6erB58+ZYDStta2tYW+/du3cvWe/u7u4op9p6W5ZVt96VddWeWl6p2ZYtW5BKpbBp06aG6l1bw+3bt8c+XOzdu3fJttu2bUNPT0/dejuOE6vhtm3bYvWubLNAeX9Zrt67d+9e1HapbXb37t3R63rbbHW9q7fZ2npv3rx5xXovtc3u2LFjxW220vbaa69dst6VbbbSp9p6V2+zjuNE9951HAdbt27Fli1bGqq3xojOGCN6enqQyWSiPi23zTZT72bGCNu2y/2dnblapzTSYRooTS+qd6X/zYwRlWmQdDqFVMqOzhHIZh0EV2vIPEbs2bMndg+l2jGidvveaGOEbdvYv2UnAAtBEGBwdgz7u8vfc3Z6BFu2bMGTR07A9314noev/vy7OPm2P4bneQjDMPp5qutd6dNSY0Qul0XX1eX1HCNyueySx23RGDG89BjhOA5yuRx6e3uj9a7mOGK9xoji1f+zPEZko303nU4jqDoWjsaI8ysfR2SzWeS2bYvW09BxxBvluuRyuagO6VQaqVwKmJuJ2lZYFlYcI4pOpm69q8eIk2+7M3ZmSm291zpGVI4NHMdZ03HERh8jmI8jSqUSHMepu983ehxR+X+WGyO8qz/rkvUeX1zvch2z0Xoty0I2u3Crh9rPGqVctq0/a9iWFb0HC7HxpLu7G7O2DX+gPCGXRggU3avLIWzbRnd3N6aOnQAQYjcAv1DE1LET6L46Mk7BAv705th6LVTGLUT1rmyzjuPguuuui3Ju5WcN27ZhV/2+DG079jtm7969wNW5pKyTheUtZJzL5WBdPR5sxzEik8nE1l1vjLB+/lMAi8eIbLa8PQdY+L1W+XlMjxHV8z/ZbLZuvU3OR6z3Z431mI+onjxdTttMaH7lK1+JLb/1rW/F3Xffjeeeew5Hjx5d8f3Kgc7o6GhsBxodHY02gJXaNLKOlVSCARBtvABiAwBQHpSrf6FUf19lsFlN21QqfvP51bYFsGzb6BdGnbbRh+cl2lbXZS1ta+vSTFsT9QYW6lL5uap/vnao91pqWN12LTVcj3rXa7tcDdez3tW/uGzbbuttVmNE6+udyWRiv9CbqWGr6m1ZVvkgx6os29HBN9DcvlyvhkVUDpTL6/WjddkA4gfRS623k8eI7u7uWNt232abHSPKG9PCxFhs47Ks6P9dWG/5/ZW22eX2e8taGEvXc4yw7YVarLbetf9nK7fZtW7flX0XsGDbKfhV+3I0YKC5GlqWHf1fzdS73IeF/zMat+r+rCtv36618OE+qTGiun07HLfpOKL5tmupd/V7tcvN1Lt2e69Xw5K1MMnaaL0r+331smXZddtWxsPqSZ1q7fBZA5YVOymp+nU6nUbPM9+I9Xmph/6kDpTnAPyBQaQO9EVfr0yGxk58suLL1XWxbTs2SdPK7TuelVX1r7xcW+PK7+Xa48F2HCMsy461r9+2/nFE7fZcvZzEGNEO8z+Amc8a61XDRrTNJef1zoAMgiA6mFnp/R07duDmm2/GSy+9FGtz+vRpHDlypKE2jaxjNUqlEsbGxqruWSJMlD835c9N+XNT/utjLU+eNalUKsH1XOVPSvs/N+XPTflzU/7mtM2E5r333ouHH344um/AmTNn8K1vfQsf/vCHG3ofAO655x488cQTGBgYAAC8+OKLeOWVV3DXXXc13KaRdTTL931cuXKl6ubOwkT5c1P+3JQ/N+XPzfd9+CVf+SegHSa9tf9zU/7clD835W9O21xy/sADD+DRRx/F+9//fniehy1btuC+++7DHXfc0dD7AHD77bdjZmYG9957L2ZnZ9Hb24vHHnsMfX19DbdpZB3NymazOHjw4Kq/XzY25c9N+XNT/tyUP7dsNouurq6mL5+SzqD9n5vy56b8uSl/c9pmQrO3txcPP/zwqt+vOHr0KI4ePbqmNo2sQ0RERERERERERMxrm0vOO1mxWMTAwACKxeLKjaXjKH9uyp+b8uem/LkVi0XMF+aVPynt/9yUPzflz035m6MJTQNs28bmzZvjT0UTGsqfm/Lnpvy5Kf+Nba33YbRtG6mqJwMLF+3/3JQ/N+W/fk6+7c6ku7Ai5W9O21xy3skymQx27dqVdDckIcqfm/Lnpvy5KX9umUwGjuMgk8kk3ZVVO376VPS64LuxZQB49PFfxL+hUMDUsRPRYs8z8fZMtP9zU/7r58FXn237SS3lz035m6MJTQOCIECpVEI6ndYsPSHlz035c1P+3JQ/tyAIon8bOf/93eUPZWdnRqPXlWUASB1YeHCmPzAYLfsDgwZ72X60/3Mzmf9azyaX1tP+z035m6PqGuC6LgYGBuC6btJdkQQof27Kn5vyX2zm/keS7oIxyn912v3Mm0a5rotCoaD8SWn/56b8uSl/bsrfHE1oGuA4Dvbt2wfHcZLuiiRA+XNT/tyUPzflz81xHGSzWeVPSvs/N+XPTflzU/7m6JJzA2zbxqZNm5LuhiRE+XNT/txY8o9dWlooLLrUtPqeerX32AM69z57LPlLfbZt48u3/J9Jd2NZK+27wMKl5QXfjV7LyrT/c1P+3JQ/N+VvjiY0DSiVSpiamkJPTw/SaZWcjfLnpvy5MeRfOxk5c/8jde/nVX1fvdp77nUqhvxlae2efyP77pNHFv74UO9BHFOPx/84IQvaPX9ZX8q/dWofRlb7gLLKONVOf3xR/tyUvzmqrgGlUgmTk5PYvHmzNmhCyp+b8uem/Lkpf27Kf31slHusKn9uyr+1ah9IVv2wMmDlP76Ypvy5KX9zVF0DcrkcbrzxxqS7IQlR/tyUP7eNln/SHwA6zUbLX1pL+XNT/tyUPzflz035m6MJTREREREREREizPe/rndrHBHZeDShaUCxWMTw8DB2796NbDabdHfEMOXPTflzU/7clD835c9N+XNr9/x1/+v11e75t6tOmWhW/ubYSXeAgW3byGazsG2Vm5Hy56b8uSl/bsqf20bLv1M+SLaLjZa/tJby56b8uSl/c3SGpgGZTAa7d+9OuhuSEOXPTflzU/7clD835c9N+XPbaPnrDxqttdHyl9ZS/uZoytiAMAzheR7CMEy6K5IA5c9N+XNT/tyUPzflz035c1P+3JQ/N+VvjiY0DSgWi/j1r3+NYrGYdFckAcqfm/Lnpvy5KX9uyp+b8uem/Dcmf2CwfH/Qqw9JipavOjszGv0r+G70upby56b8zdEl5wZkMhns3bsXmUwm6a5IApQ/N+XPTflzU/7clD835c9N+W881Q9KqveQpCdr2j/46rM4+bY7665L+XNT/uZoQtOAVCqFzZs3J90NSYjy56b8uSl/bsqfm/Lnpvy5tVP+S026yfppp/zFPOVvjiY0DSiVSpiensaWLVuQTqvkbJQ/N+XPTflzU/7clD835c9N+XNb7/yrL4OvXB5fq3IpfOXSeDFH+785qq4BpVIJY2Nj6Orq0gZNSPlzU/7clD835d/5ljvzSfkvVu8yzk6l/Lkp/+S0wxmp65l/9aXxwBKXxx85Eb1e7tJ4WR/a/81RdQ3I5XK46aabku6GJET5c1P+3JQ/N+XPTflzU/7clD835c9N+Zujp5yLiIiIiIiIiIjIhqEJTQNc18Xg4CBc1026K5IA5c9N+XNT/tyUPzflz035c1P+nW+5y7hN5s9yG4+NRPu/OZrQNET3TuCm/Lkpf27Kn5vy59ZJ+esebM3rpPylecqfm/LnpvzNUJUNcBwH119/fdLdkIQof27Kn5vy56b8F2OaFFP+3JQ/N+XPTflzU/7m6AxNA8IwhO/7CMMw6a5IApQ/N+XPTflzU/7clD835c9N+XNrp/yZ/pDYLtop/06nCU0DisUifvnLX6JYLCbdFUmA8uem/Lm1Kv8HX322RT0Sk7T/c1P+3JQ/N+XPTflzU/7maELTgEwmg+uvvx6ZTCbprkgClD835c9N+XNrNH9NWHcm7f/clD835c9N+XNT/uZoQtOAVCqFLVu2IJVKJd0VSYDy56b8uZnMf+b+R9b9/5DmaP/npvy5KX9uyp+b8uem/M3RhKYBpVIJly9fRqlUSrorkgDlz035c1P+3JQ/N+XPTflzU/7clD835W+OnnJuQKlUwsjICHK5HNJplZyN8uem/Lkpf26dkP/x06ei1wXfRS7lLGpzdmY01qZ6mVkn5C+rp/y5KX9uyp+b8jdH1TUgl8vh8OHDSXdDEqL8uSl/bsqfW6fkv797F4DyxGXldWX5ySMnYm0ffPVZPVH1qk7JX1ZH+XNT/tyUPzflb44uORcREREREREREZENQxOaBriui/Pnz8N13aS7IglQ/tyUPzflz035c1P+3JQ/N+W/sXU/8Nk1fb/y56b8zdEl54ZYlpV0FyRByp+b8ue22vxr711YvfzkkROYOha/1BeFQuxrPc+cgiRP+z83hvz9gcGFhUIhvgzEx6qacQoA8Kc3r2PvksWQvyxN+XNT/tyUvxma0DTAcRzs2bMn6W5IQpQ/N+XPba3517t3YfUDV1IH+qLX/sBgtFw7odBpZu5/ZM1nT5ig/Z8bQ/61fzhZat+sHptqx61OxZC/LI0x/43yu9kExvxlgfI3R5ecGxCGIYIgQBiGSXdFEqD8uSl/bsqfm/Lnpvy5KX9uyp+b8uem/M3RhKYBxWIRb7zxBorFYtJdkQQof27Kn5vy56b8uSl/bsqfm/Lnpvy5KX9zNKFpQCaTwe7du5HJZJLuiiRA+XNT/tyUPzfG/E++7c6ku9A2GPOXBcqfm/Lnpvy5KX9zdA9NA1KpFHp6epLuhiRE+XNT/tyUPzflz035c1P+3JQ/N+XPTfmbozM0DfB9H1euXIHv+0l3RRKg/Lkpf27Kn5vy56b8uSl/bsqfm/LnpvzN0RmaBnieh4sXL6K/vx+pVCrp7ohhyp+b8uem/Lm1Kn89OXZj0v7PTflz65T8/YHB8otCYeH1VVPHTsQbFwqxr/U8c2q9u9e2OiV/WR3lb44mNA3IZrM4dOgQLMtKuiuSAOXPTflzU/7clD83xvw18b6AMX9Z0An5V09I1vvD2tSxE0gd6IuW/YHBaLl28pNNJ+Qvq6f8zdGEpgGWZWljJqb8uSl/buudf+wDQ52zJwDg7Mxo+W3fjV6LGdr/uSl/bsqfm/Lnpvy5KX9zNKFpgOu6GBsbw86dO+E4TtLdEcOUPzflz20986+9lKve2RNPHlm49OvBV5/VE6gN0/7PTflzU/7clD835b+xrfWYWfmbo4cCGRIEQdJdkAQpf27Kn5vy57aR8n/w1WeT7kLH2Uj5S+spf27Kn5vy56b8zdCEpgGO42Dfvn2anSel/Lkpf27Kf3U6ZWJN+XNT/tyUPzflz035c1P+5uiScxERERERWTfLPSkZQOz+vrrfr4iIrCfdhqlzaELTgEKhgHw+j/7+fuRyuaS7I4Ypf27Kn5vy56b8uSn/spWelPxkTftO+aCp/Lkpf27Kn5vyN0eXnBuQTqfR29uLdFrzx4yUPzflz035c1P+3JT/6nTCZCag/Nkpf27Kn5vyN0cVNiCdTmPr1q1Jd0MSovy5KX9uyp+b8uem/Lkpf24s+cduIVHnlhJTx07E3kfN2WrVZ3B3Epb8pT7lb44mNA3wfR/z8/Po6upCKpVKujtimPLnpvy5KX9uyp+b8uem/Lkx5F87GVnvlhIAkDrQB6A8+Vl5XVnuVAz5y9KUvzma0DTA8zwMDQ2hv79fGzQh5c9N+XNrNP9OuWecxLX7/n/8dPzDaMF3Y1978kj5zJrKA1r0sJbmtHv+sr6UPzflz035c1P+5mhC04BsNouDBw9qYyal/Lkpf27Kn9tGyH9/967o9dmZ0Wi5MnFZmdQENPHerI2Qv6wf5c9N+XNT/txm3X2PAAAgAElEQVSUvzma0DTAsizdEJaY8uem/LmZzL/eZV6SLO3/3JQ/N+XPTflzU/7clL85esq5AZ7n4eLFi/A8L+muSAKUPzflz035c1P+3JQ/N+XPrVX564+VG5P2f27K3xxNaBoQhiE8z0MYhkl3RRKg/Lkpf27Kn5vy56b8uSl/bsqfm/LnpvzN0YSmAY7joK+vD47jJN0VSYDy56b8ubVT/rr3oXntlL+Yp/y5KX9uyp+b8u98M/c/suR7yt8cTWiKiIiIiIiISKKWmyQSEamlCU0DCoUC3njjDRQKhaS7IglQ/tyUPzflz035c1P+3JQ/N+XPTflzU/7maELTgHQ6je3bt+tJV6SUPzflz035c1P+3JQ/N+XPrdPy18OJmtNp+UtzlL85qrAB6XQa1157bdLdkIQof27Kn5vy56b8uSn/xZgmRZQ/N+XPTflzU/7maELTAN/3USgUkMvlkEqlku6OGKb8uSl/bsqf21L5Hz99Ktau4Luxrz155ASmjp2oalCILwPoeSa+Dmk/2v+5KX9uyp+b8uem/M1pm0vOf/azn+HNb34z3vnOd8b+/eAHP4jaPPfcc7j99tvxzne+E3fccQd+/OMfL1pPK9o0so5meJ6H8+fPw/O8Na1HNiblz035c1P+3DzPw+yXvlo3//3du6J/uZQTva6WOtCH1IE+IJeLXqcO9JnqvqyR9n9uyp+b8uem/Lkpf3Pa5gzN4eFhvOlNb8J3vvOduu9/97vfxaOPPoqnn34aBw8exAsvvICPfvSjeP7557Fv376WtWlkHc1yHAc33HCDZudJKX9uyp+b8ufmOA66unJwHCfprkgCtP9zU/7clD835c9N+ZvTNmdojoyM4Lrrrlvy/W984xs4fvw4Dh48CAB43/veh1tuuQXf/va3W9qmkXU0y7ZtZDIZ2HbblFsMUv7clD835c/Ntm1Ylq38SWn/56b8uSn/Bf7AIPyBQaBQiF77A4PR+1PHTkT//J+/HlveqJQ/N+VvTttUeLkJzYsXLyKfz+Nd73pX7Ou33XYbXn755Za1aWQdK3FdN3pdLBbheR48z8Pw8DBmZmYQBAEAoFQqoVAoxL6vckpyGIYoFArwfX/JtpX/p7Zt5X4NYRiuqS0AFAoFlEqlum09z1uybRAEKBQK0c/qeR6KxWKsLs20rdSltm1tXeq1Xa6G613vSl0KhQJGRkai16utd3VdWlXvUqnUknqvpYatrvdqttlK26Vq2Gy9q2s4MzOD4eFheJ63pnprjNiYY0ShUMDQ0FD0fjM1RBhGP0ulz5X3NtoYAYQIAh9AePVHC64u169hEATL1jsMg7r1brcxorzOImZnZ2N1QVipw9WMo8jD6L1KnSo/a20NW7XNlte7sG2FNdtdbVuNEY3X2/M8jIyMYG5ubl3GWR1HtPdxxOzsLEZGRuB53pqOI1pVbx1HmB0jZmdnceHCBXiel9g22w5jxOb/+T+Qe+Jv0PPMKaR+4ybknvgbbHrqv6PnmVPY8vTfXq1DiNSBPtj79wK5bNXtVcKa44jGfle1wxjheR6GhoYwPz8fa7senzU0RuDqz+cvecxUW8MgCJatd/W2tZoxonr+px3mI9p5jFhum21EW01oXrlyBffddx9+7/d+Dx/60Ieiy89HRkYAALt2xe8ttWvXrui9VrRpZB0rGR0djV5fuHABExMTCIIA8/PzGBoaijbMK1eu4Ny5c1HbixcvYnx8HEB548nn89EAOD09jcHBhb9ijYyM4NKlSwDKG0Q+n8fc3BwAYGZmBvl8Ptaf6j7l83nMzMwAAObm5pDP56ON6dKlS7Gfc3BwENPT0wCA+fl55PP5aMcZHx/HxYsXo7bnzp3DlStXAJQ37nw+H220ExMTuHDhQtT2/PnzuHz5MoDyBpvP56Md6fLlyxgaGoraDg0NYXJyEkB5x8jn89EGPzU1hfPnz8dqODExEavhUvUeHh6Oalhb79oajoyMYGxsDEB5AMnn89GH00rbyo4+NjZWt97z8/N16z08PFy33rU1HB8fj7U9f/48pqam6radnJxcVO9KDV3XjdV7cnIyVsMLFy5EbUulUqyGtfUeHh6OttnatrXbbHW9G9lma+td2WZnZ2cX1bt6m61uW7vN1ta73jZbaTsxMRHbvqvrXdlmKwPt5OTkom22sn27rouhoSHMzc0hCAJcvnx5Ub0r22xtDTVGdMYYMTs7G/tj1lJjRL16B2G4+CDDL9WtYbuPEeV+FKOfzff92MFL7RhRKBSW3WZdd+EAsJ3HiMrEbPV6h4aGYh/IKh/mKjUNgoUJzfJBXamq7UINWzVGhGH55/OD+IFxdb01RqxujKgc/42Nja35OGKpeus4on2PI0ZHRzE/P48gCNZ0HFG9zeo4YuOMEWNjY5idnY1+D6z3Z42l6r0RxoiKUsmv+UNuGG2zld+X0SSIH5/wabcxonJSQ2291+OzhsYIRHWrvFc+lixGOdaOEcVicdkxovoYdTVjRCPzP6bnI5aqdzuPEY1om3toWpaF8fFxnDx5Env37sWZM2fwsY99DL7v4y1veQsALDpl17KsKLh0Or3mNo2sYyXVk6HXX399dLpxf38/XNeN7qN1zTXXYNOmTVHb6667DpZlAQBSqRT6+/uRyWQAAFu2bEFXV1fUtre3N3pt23asbXd3N/r7++v2B0Cs7aZNm9Df3x/9vDt27Ii17evri2rS1dWF/v7+6D4Q27dvj9Vk3759UdtcLof+/v5o+dprr8XWrVujtnv37o3Wk81m0d/fH9Vl69atuOaaa6K2e/bsifpXqWOlbU9PDzZv3hyrYaVtbQ1r67179+4l693d3Y1cLle33pZl1a13ZV07d+5cVO90Oo0dO3bA931s2rSpoXrX1nD79u2xX/B79+5dsu22bdvQ09NTt96O48RquG3btli9K9ssUN5flqv37t27F7VdapvdvXt39LreNltd7+pttrbemzdvbqjewOJtdseOHStus5W211577ZL1rmyzlT7V1rt6m62ut23bSKVS2LJlS0P11hjRGWPE1q1bsXnzZmSzWQDLb7O19bYtK3bvxVwuF/WpnceIUlUNq3+f5nJZ2LYN/2pNq9+rHSNyuVyUR70xouhk6ta73caIys9yzd69Uds9e/bAOm9F/c/lcsDsTFRT27aitpXtJojaLtSwJWPErwDLim9bqVSq3Ke5majetTXUGNHYGJHNZrF///7YHyZWexzRbL3beYyormEnH0ds3bo12odbcRwBlLdvHUdsjDHi+uuvh2VZyGQyCMNw3T9rNFvv9RgjCljdGFGZOkqnUwiqjg1s28L27duBNxZ+X1bqkE6lkcqlot9V7TZGVLY7k581AO4xIpvNwrIsBKgcS2ajn6d2jMhms9FyvTGiMnbX1rt6jJjD0mNE9fxPu8xHNFvvpI8jqidPl9M2E5pf+cpXYstvfetbcffdd+O5557Du9/9bgDl2f3qnWN0dDQKtzKIraVNI+tYSfWHz+odofKhpiKdTkeB135f9AFnFW1TqVTs5rOrbQtg2baVHahe29qftbbtcnVppm1tXdqt3sDyNWyHeq+lhtVt11JDU/VeroYbod4aI5pva6LeD776LE6+7c4l266lhrCs2KRf9et23mZn6rQFLNj2Qn8ty4a1MG+3qN6VPwDU64PjOHAtO2qb9BhRuw3U1sWy7FgtstksKj+8ZVnlA1Br4WevLoxlVf+BNV7DVo0R5fVase+1qvpQ21ZjxOKfVccROo7YCPXWcUTzbdu93kBnjBFFVH4n2oh+IZa/UvV/Nf67SmNE+26z61nv6mOk2mOmxW3t6Oep1OX46VPR+wXfjS0DwKOP/yJ6XQSAQgGz//VT0XLPM6fart7Axh4jGtE2l5zXOwMyCAJYloUdO3bg5ptvxksvvRR7//Tp0zhy5AgAtKRNI+tYjUKhgF/+8pex0+KFh/Lnpvy5KX9uhUIB8/Nzyp+U9n9uyp+b8uem/Dem/d27sL97F3IpJ3q9v3vhDNPK/V1TB/qAXK7qfq9xhUIBY3/xZeVvQNucoXnvvffihhtuwCc+8Ql0dXXhzJkz+Na3voVPf/rTAIB77rkHjzzyCI4cOYIDBw7gxRdfxCuvvILnn38+Wkcr2jSyjmal02ls27YtNvMsPJQ/N+XPTflzK//VOaP8SWn/56b8uSl/bsq/vdSebVl7BuaTR04AAM7OjEbvV16vho7/zGmbCj/wwAN49NFH8f73vx+e52HLli247777cMcddwAAbr/9dszMzODee+/F7Owsent78dhjj6Gvb2FGvBVtGllHs9LpdPn+H0JJ+XNT/tyUf2MaOdCcOnaiqkEhvozypT4mNNtXu+qSJMBcPyV52v+5KX9uyp+b8m8/1Wdanp0ZjZYrE5eVSU1g8e2EAGDq8fhx53LS6TQyGU1omtA2Fe7t7cXDDz+8bJujR4/i6NGj696mkXU0IwgCFItFZLPZRQ8cks6n/Lkpf27Kv3ErHWgCiC7r8QcGY5f4+AMLT940ofG+hlf7ug+AZbyfkizt/9yUPzflz035cwuCAEHgIwgC5b/OVF0DXNfF4OBg7CmXwkP5c1P+3JQ/t/IBbRB7KqTw0P7PTflzU/7clD8313VRKBSVvwFtc4ZmJ3McB/v371/0tCfhoPy5KX9uyp+bbdsIbdvIX+frXR4lydL+z035c1P+3JS/edFVMIVC3Stiqq+iWes9MlfiOA66unKLniIuracJTQNs22768fPSOZQ/N+XPTfmzs6r+CRvt/9yUPzflz035m1V9f/KZ+x9B9wOfjb3/ZE379f4jsG3bsCwzf9Bmpwob4HkeRkdH4Xle0l2RBCh/bsqfm/LnFoZB9E/4aP/npvy5KX9uyp+b53nwPFf5G6AJTQOCIMDMzIzuoUVK+XNT/tyUv4RhmHQXWkaXtDdH+z835c9N+XNT/tyCIIDv+8rfAF1ybkA2m8UNN9yQdDckIcqfm/JvX/UuSWm1pfI/fvpUbLngu7GvPXnkBICF+/2s971+ZH2ULzdKwbKS//ux7rFpnsZ/bsqfm/Lnpvy5ZbNZeLku3XbAAE1oioiIJGB/967o9dmZ0Wi5MnFZmdQENBklIiIiIiJSLflTBggUi0X8+te/RrFYTLorkgDlz035cysWi7j02b9S/qTCMEAQ+LqHJimN/9yUPzfl3xx/YLD8ZOqrT6iufUr12ZnR6F/lqpV2vnJF+XMrFosoFOaVvwE6Q9MA27axZcsWPeWKlPLnpvy52baNVCql/IlZlp5wzkrjPzflz035N27FJ1RXXbECbIyrVpQ/Nx3/m6MJTQMymQx27tyZdDckIcqfm/LnlslkkMk4yGQySXclcdHZFlfPvqhVfaZFp9wz1LLs6F8Squ/LWnuf1opOrHu70PjPTflzU/7clD83Hf+bowlNA4IggOu6cBxHs/SElD835Z+cdvgLfhCULzkOgmBN+Sf9c6zVimdf1LRvh+xaI6z6l8yZmtX3Zq29b2vtWS/SWhr/uSl/bsqfm/Ln1qrjf1mZJjQNcF0X+Xwe/f39yOVySXdHDFP+3JQ/N9d1USgU4biu8idUPqANYAUBbDvV0nXXnm1ZewZmZbKycsalzr40T+M/N+XPTflzU/4b21r/qK7jf3M0oWmA4zjo6+uD4zhJd0USoPy5KX9ujuMgl8sqf1K2bSO07XX763ztGZfVZ2MC8fuOdc5ZrxuHxn9uyp+b8l8/G+F3mfLnpuN/czShaYBt2+jq6kq6G5IQ5c9N+Xeele5L+OSRE5g6VnUpb6GA6Y98IlqsvvxaOp1V9U/YaPznpvy5Kf/Fam8308mUPzfbtmHbeiiQCaqwAaVSCZcuXUKpVEq6K5IA5c9N+Xem/d27sL97F3IpJ3pdfbYcAKQO9MHevxdh1oG9fy9SB/oS6q0kJQyD6J/w0fjPTflzU/7clD+3UqkEz3OVvwGa0DTA931MTU3B9/2kuyIJUP7clL+EYZh0FyRByp+Xxn9uyp+b8uem/Ln5vo9SyVf+BuiScwOy2SwOHjyYdDckIcqfm/LnZlnlS04sS38/NK3e09RN8gcGAQC26yE4e37R+9UP6NEDezqTxn9uyp+b8uem/JPTDrc2yGaz6OrqQjabTborHU8TmiIiIkJnPSc8q++TWu//qX5YD6AH9oiIiIiINEunjBhQLBYxMDCAYrGYdFckAcqfm/Lf2Gbuf2RN3x+GAYLA1z0USRWLRRQK86ve//2BwfKZnoVC9Lpy5idQPsuz8q9ylqfO9GwfGv+5KX9uyp+b8ue21uM/aZzO0DTAtm1s2rRJT7kipfy5Kf/V6aQz1ixLT7hmtZanXK54lmdN+07aZzqFxn9uyp+b8uem/LnpKefmaELTgEwmg97e3qS7IQlR/tyUPzfLsqN/wieTycBxHGQymaS7IgnQ+M9N+XNT/tyUPzcd/5mjT1gGBEEA13URBLrkkJHy56b82YVV/4RNEARXbzuw/P6vMys7k8Z/bsqfm/Lnpvy5NXr8J2unMzQNcF0X+Xwe/f39yOVySXdHDFP+3JS/OcdPn4otF3w39rUnj5zA1LGqh7EUCvFlxC/zbYUgKB/MWEEA2061dN3S/lzXxfx8ARnX1f5PSOM/N+XPTflzU/7cdPxnjiY0DXAcB/v27YPjOEl3RRKg/Lkpf7P2d++KXp+dGY2Wqx+UkjrQB6D8wJXK68pyK5XXF8J2PYT58/ARv5dmdZ8qD3SRzuI4DnK5rPZ/Uhr/uSl/bsqfm/LnpuM/czShaUDlpsDCSflzU/6cVnygy5H4maF6oEtn0k3huWn856b8uSl/bsqfm47/zFGFDSiVSpiYmECpVEq6K5IA5c9N+XMrlUoolTzlT0r5c9P4z035c1P+3JQ/Nx3/maMJTQNKpRLGx8e1QZNS/tyUP7dSqQTP0wENK+XPTeM/N+XPTflzU/7cdPxnji45NyCXy+HQoUNJd0MSovy5KX9uuVwOpa5NuiE4KeXPTeM/N+XPTflzU/7cdPxnjs7QFBERERERERERkQ1DE5oGuK6LfD4P13WT7ookQPlzU/7cXNdFoVBQ/qSUPzeN/9yUPzflz035c9Pxnzm65NwAy7KQzWZhWVbSXZEEKH9uyn991HtyeKP8gcHyi0Jh4XWVqWNVTyAvFGLL1U8vb4RlWbBtiyr/1ebSiRjzlwUa/7kpf27Kn5vy56bjP3M0oWlAJpPB7t27k+6GJET5c1P+7aV6QnK5SdHUgT4A5cnP6tfNymQycJwsMpnMKnorG53y56bxn5vy58aYv/6guYAxf1mg4z9zdMm5AWEYolQqIQzDpLsiCVD+3JQ/tzAMEYaB8ifVqvz1IXFj0vjPTflzU/7clD83Hf+bowlNA4rFIn71q1+hWCwm3RVJgPLnpvy5FYtFzM8XlD8p5c9N4z835c9N+XNT/tx0/GeOLjk3IJPJYM+ePTrlmJTy56b8N6aV7rN5dma0/LbvRq/ryWQyyGYd5U9K+XPT+M9N+XNT/tyUPzcd/5mz6gnNM2fO4D//8z8xPj4O27axbds2vOUtb8Gb3/zmVvavI6RSKXR3dyfdDUmI8uem/Deele6z+eSRhYcEPfjqszj5tjuXXFcqlUIqlUYqlWp9R6XtKX9uGv+5KX9uyp+b8uem4z9zmp7QnJ6exmOPPYaBgQFs3rwZO3bsAAD8+te/xssvv4yDBw/i+PHj6OnpaXlnN6pSqYTp6Wls2bIF6bROimWj/Lkpf26lUgmlkodSqaT8W2C5M2djT6e/2mYtT6hvBeXPTeM/N+XPTflzU/7cdPxnTlPV9X0fp06dguu6+OQnP4mbbrop9v5rr72Gv//7v8c3v/lN/MVf/IVmpK8qlUoYGxtDV1eXNmhCyp+b8u9sy52dCZTz97yVD2hWWo+sfObs1LET0RPpgbU/ob4VSqUSRv/kw8i1wQGttjHzNP5zU/7clD835c+t0eN/WbumHgr0L//yL5icnMSnP/3pRZOZAHD48GF86lOfwvj4OF599dWWdXKjy+VyuOmmm5DL5ZLuiiRA+XNT/txyuRy6ujYpf1La/7kpf27Kn5vy56b8uen435ymJjR/8pOf4MiRI9iyZcuSbbZu3Yp3vOMd+Ld/+7c1d05ERDrPg68+m3QXpM3pbEIRERE+tVdfiIgsp6kJzaGhIRw6dGjFdjfddBNGR5d+6isb13Vx7tw5uK6bdFckAcqfm/Ln5rouisWC8iel/Z+b8uem/Lkpf27Kn5uO/81p6oL+ubk5XHPNNSu26+npwdTU1Ko71Yl0P1Fuyp+b8udmWVbSXZAEaf/npvy5KX9uyp+b8u88sXuyL/uAyhCpQhHzx/8M81j4HJDEAyo7XVMTmkEQNLRjplIpeJ636k51GsdxcP311yfdDUmI8uem/Lk5jgPHycJxnKS7IgnQ/s9N+XNT/tyUPzfl33lqJyPrPaASQOyBlLUPq5TWa/qRS/l8HleuXFm2zcTExKo71InCMEQQBLBtW2fqEFL+3JQ/tzAMAYQIw1D5t5Cpe2wtdbDaKO3/3JQ/N+XPTflzU/7swqp/S+e/1uNMWcWE5tNPP70e/ehoxWIR+Xwe/f39etIVIeXPTflzKxaLmJubR7pYVP6EtP9zU/7clD835c9N+XMLggBBEMAKAti2bj2wnpqa0PzkJz+5Xv3oaJlMBtdffz0ymUzSXZEEKH9uyr8xx0/HL+Mo+G7sa08eOVF1XxoAhUJ8GQD+9Ob17OKqZDIZZLOO8iel/Z+b8uem/Lkpf27Kv/Mtd2albdsIbRu23dQzuGUVmprQvOmmm9arHx0tlUphy5YtSXdDEqL8uSn/surJydrJymZstPvSpFIppFJp3RielPZ/bsqfm/Lnpvy5KX9e0WeSQhH+wLnYe4tOxqg5QUMPDWpe05ecL8X3fVy4cAFdXV3YsWNHq1bbEXzfx8zMDLq7u/WhlpDy56b8F+zv3gUAODszGr2uLD95JP4L/sFXn8XJt91ptH/rwfd9+H4Jvu/T589I+z835c9N+XNT/tyUP6fKhKTv+5i5/2F0P/C5WP5Tx04sOiGj+mQNaV7TTzl/4okn8Fu/9Vu45ZZboq+fPXsWTzzxBCYnJwEAb33rW3H8+HGk0y2bL93QPM/D8PAw+vv7NaARUv7clD83z/NQLLrIep7yNyB2MFgoLDo4XOm2Ba3+y7j2f27Kn5vy56b8uSl/bjr+N6epGccf/vCH+PnPf47f/d3fjb7mui4ef/xx2LaNP/mTP0GhUMA//MM/4J/+6Z/wvve9r+Ud3oiy2awu1yem/Lkpf27ZbBabNnUhm80m3ZWOVzsZudSTI03etkD7Pzflz035c1P+3JQ/Nx3/m9PUhOa//uu/4g/+4A9w+PDh6GunT5/G9PQ0vvCFL+D6668HUL4JqiY0F1iWlXQXJEHKn5vyb1/L3cy7mTbLKedvaTtoIwv3Nlp8Biew/FmczZ7BaTL3TrhFQ6fRfs9N+XNT/tyUPzcd/5vT1ITm6OhobDITKE9o/uZv/mY0mQkA/f39mJiYaE0PO4DruhgdHcWuXbvgOE7S3RHDlD835c/NdV0UiwU4rqv820D1hORSZ3AC9c/iXM0ZnNr/uSl/bsqfm/Lnpvy56fjfnKaeI79p0ybMzs5Gy2fOnMHY2Bje8Y53xNpduXJFp9eKiIiIiIiIiIhIyzV1huaNN96I733ve9i9ezdKpRKef/557N27t+5ZmwcOHGhpRzcyx3Gwd+/epLshCVH+3JQ/N8dxkM3m9NdZUtr/uSl/bsqfm/Lnpvy56fjfnKbO0PyjP/ojTE5O4otf/CK+9KUv4fLlyzh27FiszQsvvIB///d/x7vf/e6WdnQjC8Mw+id8lD835c+tnLvyZ6X9n5vy56b8uSl/bsqfm47/zWlqQnP79u34y7/8S9x111244447cPLkyUV/ebjppptwxx134MYbb2xpRzeyYrGI119/HcViMemuSAKUPzflz61YLGJubl75k9L+z035c1P+3JQ/N+XPTcf/5jR1yTlQvo/m7/zO7yz5/oEDB3S5eY1MJoPdu3cjk8kk3RVJgPLnpvy5ZTIZZLOO8iel/Z+b8uem/Lkpf27Kn1urjv+Xe4CllDU1oXny5Mkl37NtG1u3bsVv/MZv4LbbbtP9AqqkUin09PQk3Q1JiPLnpvy5pVIppFJppFKppLsiCdD+z035c1P+3JQ/N+XPTcf/5jQ1oXno0KEl3wuCABMTE/jHf/xHvPrqq/j0pz+tJ51f5fs+5ubmsGnTJm3UhJQ/N+XPzfd9hH/x3+D7vvInpP2fm/Lnpvy5KX9uyp+b7/vw/ZKO/w1oakLz7rvvXrHN0NAQvv71r+MHP/gBbr/99lV3rJN4nocLFy6gv79fGzQh5c9N+XNT/tyUPzflz035c1P+3JQ/N8/zUCy6yHqe8l9nTT0UqBF79uzB7//+7+MnP/lJq1e9YWWzWdx44406Y5WU8uem/Lkpf27Kn5vy56b8uSl/bsqfWzabxaZNXcrfgJZPaALADTfcgPHx8fVY9YZkWRZSqRQsy0q6K5IA5c9N+XNT/tyUPzflz035c1P+3JQ/t3LulvI3YF0mND2dWhvjui4uXLgA13WT7ookQPlzU/7clD835c9N+XNT/tyUPzflz811XbhuUfkbsC4TmmfOnMH111+/HqvesHzfT7oLkiDlz035c1P+3JQ/N+XPTflzU/7clD+3MAyT7gKFph4KtJIgCPDKK6/gxRdfxNGjR1e9nuHhYXzgAx/AbbfdhoceeggA8LOf/Qx33nkntm/fHmt78uRJvOc974mWn3vuOTz11FO4cuUKdu3ahS984Qt4+9vfHvueldo0so5mOI6Dffv2rfr7ZWNT/tyUPzflvzH5A4PlF4XCwusqZ2dGo9cF340tV1P+3JQ/N+XPTflzU/7cHMdBNnOFqVsAACAASURBVJuD4zhJd6XjNTWhefLkySXfC8MQV65cge/7+O3f/m3ceuutq+pQGIb43Oc+h97e3tjXh4eH8aY3vQnf+c53lvze7373u3j00Ufx9NNP4+DBg3jhhRfw0Y9+FM8//3w0oKzUppF1iIiISGfqeeZU9Hrm/kfQ/cBnY+8/eeREbPnBV5/FybfdaaRvIiIiIiJS1tQl54cOHVry3+HDh/Ge97wHn/rUp3D33XevukNPPfUU0uk03vve98a+PjIyguuuu27Z7/3GN76B48eP4+DBgwCA973vfbjlllvw7W9/u+E2jaxjOdX3SSgWi/A8D4VCAa+99hqmpqYQBAEAoFQqoVAoxL7P8zwA5UndQqEQnaZer23l/6lt6/s+CoVCdIrzatsCQKFQQKlUqtvW87wl2wZBgEKhEP2snuehWCzG6tJM20pdatvW1qVe2+VquN71rtRldnYWr7/+OmZnZ9dU7+q6tKrepVKpJfVeSw1bXe/VbLOVtkvVsNl6V9dwamoKr732WrSO1dZ7o48RCMOFSy/C8s+7sBwuqkvlvdq6hGGAMAyqVlu1vGi9iL5vqXqv9xgxOzuL1157DfPz803XUGPE+o4RQLjiGFHZtlY7RlR+/1+5cqXhGrKOEZ14HFEoFPD6669jenp6XWqoMaK9jyOmp6fx+uuvR9tCq7ZZjREbY4yYnp6Ojv+S2mY1RiQ3RlR+/8/OzsbarsdnDY0RzdcwCIJ1HSMKhQLm5uYwNTUVqyGwcBl6+RizshwCCDVG1NS7EU1NaN59991L/jt27Bj+8A//EIcOHWpmlTG/+MUv8Pjjj+PLX/7yovdWmtC8ePEi8vk83vWud8W+ftttt+Hll19uqE0j61jJ6OjCZWcXLlzAxMQE0uk0rr32WgwPD0cb5pUrV3Du3LlY/ytPhvd9H/l8PvoAPD09jcHBhUveRkZGcOnSJQDlDSKfz2Nubg4AMDMzg3w+H+tPdZ/y+TxmZmYAAHNzc8jn89HGdOnSJYyMjERtBwcHMT09DQCYn59HPp+Pdpzx8XFcvHgxanvu3LnoA1uhUEA+n4822omJCVy4cCFqe/78eVy+fBlAeYPN5/PRjnT58mUMDQ1FbYeGhjA5OQmgvGPk8/log5+amsL58+djNZyYmIjVcKl6Dw8PRzWsrXdtDUdGRjA2NgagPIDk8/nol1OlbWVHHxsbW1TvYrGInTt3Rv2vrvfw8HDdetfWcHx8PNb2/PnzmJqaqtt2cnJyUb0rNXRdN1bvycnJWA0vXLgQtS2VSrEa1tZ7eHg42mZr29Zus9X1bmSbra13ZZudnZ1dVO/qbba6be02W1vvettspe3ExERs+66ud2WbrQy0k5OTi7bZyvbtui6Gh4exbds2pNNpXL58eVG9K9tsbQ07bYyoPnAIayaSwjBctM1+rO/3YvWubLP1fuktnqAKovVWt01ijKj0O50uXxBRb4xYrt4aI9ZvjKjkutwYUXlvtWNEOp3Gpk2bop8NWDxGVP9eYx4jOvE4Ip1OY+fOnZicnFzTcYTGiI15HHHp0iXs3LkT6XR6TccRGiOWrnc7jxETExPI5XJIp9Pr/llDY0T7jRHpdBqWZUWZr+dnDY0RZc2MEcVicV3HiHQ6jUwmvWj+p/pEC9d1Y5+FgiDQGIH4GNEIK2yTu5UWi0V86EMfwkc+8hF8+MMfxte//nUMDQ1F99D8/Oc/D8uycOXKFfziF7/A1q1bcfToUXz4wx8GAPz0pz/FH//xH+MnP/kJNm/eHK33hz/8If78z/8cP/7xj1ds8+STT664jqUMDg7ioYcewic+8Yno7M5isQjbtpHJZBAEAVzXheM4sG0bpVIJpVIJuVwOQDlYy7KQyWSiD+GZTAapVKpuW6B8b4batr7vw/M8ZLNZWJa16rZAecNMp9PRL+Lqtp7nIQzDum1rf1bP8xAEAbLZbFSXVCrVcNtGa1iv7XI1XO96r1TDZutdXZdW1btUKsH3/TXXey01NFXv5bbZStulathsvZer4WrrvdHHiOMvfx393btgWRbOTo+ib/MOWJZ1dXkEf/fbf7riNjv9kU/A3r8XABCcPY/Ugb5o8jI4ex6fvufmmvWW/x/btnF2ZhR/97/fozGiDcaI+b/6G+Tu//S6jxGzX/oqnL/81JrGCO//+R/Y8uDnNUYYHpN1HME9Rug4QmOExgiNERojNEas5xjxVz/+X/jif7ljXceImfsfRvr//mSshrP/9ZNIHegHUD5DMzh77upyCH9gEN3/39/G6l36f/8W3Q98lnKMGB4exte+9jV8/vOfR19fH5bS0ocCrcVXv/pV7Nu3L5qgrGVZFsbHx3Hy5Ens3bsXZ86cwcc+9jH4vo+jR49GZ7/Ytr3o+ypztiu1aWQdK6m+8WslFN/3MT8/j66urmjdlfDrfZ9lWdFO0WzbVCqFVCq15rYAlm2byWSWbGvbdmy5tm2lLmttW1uXZtqaqDdQrovv+5iZmUFXV1fse9uh3mupYXXbtdSw1fVequ1yNVzPemcyGczNzaGrq6vtt9n1rDeuTjKWX9eMs5YVq8VydQnOXv0LXqHOw1osYHBu4Uy4QuDGlpOoN1D+i3jloKOZGmqMaL5tq2tYsuyG21ZU18X3fRSLRXR1dUXvb+TfazqOaK7e1cd/lZ+9lTVsh3qzjxHLtV3q+K+dt9lG2mqMaKxtKpXC/Pw8bNtGKpVKZJtth3qzjhG+70fHfyu1rV2vxogF67XN2rYdm/tpdb1934fv++i6evxfaQtYUVvLsquWLQBWrG06ncbM1XdZx4hGtMWE5o9+9CN8//vfx/e+970l23zlK1+JLb/1rW/F3Xffjeeeew5Hjx7F7t27AZRPae7v74/ajY6ORg8YWqlNI+tYDc/zMDQ0hP7+/thGIRyUPzfl3zorPqylpn07PKxF+XNT/tyUPzflz035c1P+3Mr3kHSR9Tzlv86auofmennppZcwPj6OW2+9FYcPH8bhw4dx6tQpPP/88zh8+DD++Z//ue4ZkkEQRGf87NixAzfffDNeeumlWJvTp0/jyJEjDbVpZB2rkc1mcfDgwaZnm6UzKH9uyp+b8l+sdiK6kyl/bsqfm/Lnpvy5KX9u2WwWXV055W9AW0xofvGLX8Rrr70W+3fixAl88IMfxGuvvYZbb70V9957Lx5++OHoRqlnzpzBt771rdgl6vfccw+eeOIJDAwMAABefPFFvPLKK7jrrrsabtPIOpplWRbS6fTC5ZZCRflzU/7clD835c9N+XNT/tyUPzflz618P39b+RvQFpecN+KBBx7Ao48+ive///3wPA9btmzBfffdhzvuuCNqc/vtt2NmZgb33nsvZmdn0dvbi8ceeyx2E9GV2jSyjmZ5nofx8XFs37598X3lpOMpf27Kn5vy56b8uSl/bsqfm/Lnpvy5eZ4H1y3C8zzlv87adkLz4x//eGy5t7cXDz/88Irfd/ToURw9enRNbRpZRzMqT6JqkwfKi2HKn5vy56b8uSl/bsqfm/Lnpvy5Kf/2tt732A/DEEEQKn8D2nZCs5M4jhN7yJBwUf7clD835c9N+XNT/tyUPzflz035c3McB7lcbtFTxKX12uIemiIiIiIiIiIiIiKN0ISmAYVCAW+88QYKhULSXZEEKH9uyp+b8uem/Lkpf27Kn5vy56b8uRUKBczPzyl/AzShaUA6ncb27duRTusKf0bKn5vy56b8uSl/bsqfm/Lnpvy5KX9u6XQamUxG+RugChuQTqdx7bXXJt0NSYjy56b8uSl/bsqfm/Lnpvy5KX9uyp9bOp1GOq0JTRN0hqYBQRBgbm4OQRAk3RVJgPLnpvy5KX9uyp+b8uem/Lkpf27Kn1sQBAgCX/kboAlNA1zXxblz5+C6btJdkQQof27Kn5vy56b8uSl/bsqfm/Lnpvy5ua6LQqGo/A3QObAGOI6DAwcO6JRjUsqfm/LnpvyT0/3AZ5PugvInp/y5KX9uyp+b8ufmOA66unJwHCfprnQ87WEG2LatjZmY8uem/JNz8m13Jt0F5U9O+XNT/tyUPzflz035c7NtG5Zlw7Z1QfR6U4UN8DwPIyMj8Dwv6a5IApQ/N+XPTflzU/7clD835c9N+XNT/tw8z4PrusrfAE1oGqCbAnNT/tyUPzflz035c1P+3JQ/N+XPTflzC4IAUx/9v5S/Abrk3IBsNosDBw4k3Q1JiPLnpvzXRzvcH7ERyp+b8uem/Lkpf27Kn5vy56b8zdEZmiIiIiIiIiIiIrJhaELTgGKxiF/96lcoFotJd0USoPy5KX9uyp+b8uem/Lkpf27Kn5vy52Yy/5n7H1n3/6Od6ZJzA1KpFHp6epBKpZLuiiRA+XNT/tyUPzflz035c1P+3JQ/N+XPbbn8/YHBhYVCIb4MYOrYidj7sWUAPc+camlfNzpNaBqQTqexY8eOpLshCVH+3JQ/N+XPTflzU/7clD835c9N+XNbKv/ayciZ+x+p+1yA1IE+AOXJz8rryrLE6ZJzA4IgwPz8vJ5yRUr5c1P+3JQ/N+XPTflzU/7clD835c9N+ZujCU0DXNfF4OAgXNdNuiuSAOXPTflzU/7clD835c9N+XNT/tyUPzflb44mNA1wHAf9/f1wHCfprkgClD835c9N+XNT/tyUPzflz035c1P+3JS/ObqHpgG2bSOXyyXdDUmI8uem/Lkpf27Kn5vy56b8uSl/bsqfm/I3R2doGuB5HsbGxuB5XtJdkQQof27Kn5vy56b8uSl/bsqfm/Lnpvy5KX9zNKFpQBAEmJ6e1k1hSSl/bsqfm/Lnpvy5KX9uyp+b8uem/Lkpf3N0ybkB2WwWN9xwQ9LdkIQof27Kn5vy56b8uSl/bsqfm/Lnpvy5KX9zdIamiIiISB3dD3w26S6IiIiIiEgdOkPTgGKxiKGhIezZswfZbDbp7ohhyp+b8uem/Lkpf27Kn5vy56b8uSl/bmvN3x8YLL8oFBZeXzV17ES8caEQ+1rPM6ea/v82Mk1oGmDbNrq7u2HbOiGWkfLnpvy5KX9uyp+b8uem/Lkpf27Kn9ta8q+ekJy5/5FFVwtNHTuB1IG+aNkfGIyWayc/GWhC04BMJoNdu3Yl3Q1JiPLnpvy5KX9uyp+b8uem/Lkpf27Kn5vyN0d/MjAgCAIUi0U95YqU8uem/Lkpf27Kn5vy56b8uSl/bsqfm/I3RxOaBriui7Nnz8J13aS7IglQ/tyUPzflz035c1P+3JQ/N+XPTflzU/7maELTAMdx0NfXB8dxku6KJED5c1P+3JQ/N+XPTflzU/7clD835c9N+Zuje2gaYNs2urq6ku6GJET5c1P+3JQ/N+XPTflzU/7clD835c9N+ZujMzQNKJVKGB8fR6lUSrorkgDlz035c1P+3JQ/N+XPTflzU/7clD+3dsr/wVefTboL60oTmgaUSiVMTk62xQYt5il/bsqfm/Lnpvy5KX9uyp+b8uem/LlttPxn7n8k6S6smi45NyCXy+HGG29MuhuSEOXPTflzU/7clD835c9N+XNT/tyUPzflb47O0BQREREREREREWkT3Q98NukutD1NaBpQLBZx9uxZFIvFpLsiCVD+3JQ/N+XPTflzU/7clD835c9N+XNT/uZoQtOAylOubJun3J1+89lmMOYvC5Q/N+XPTflzU/7clD835c9N+XNrNH+dgbl2uoemAZlMBr29vUl3QxKi/Lkpf27Kn5vy56b8uSl/bsqfm/LnpvzN0Z8MDAiCAJ7nIQiCpLsiCVD+3JQ/N+XPTflzU/7clD835c9N+XNT/uZoQtMA13Xx61//Gq7rJt0VSYDy56b8uSl/bsqfm/Lnpvy5KX9uyp+b8jdHE5oGZDIZ7N27F5lMJumuSAKUPzflz035c1P+3JQ/N+XPTflzU/7clL85uoemAalUCps3b066G5IQ5c9N+XNT/tyUPzflz035c1P+3JQ/N+Vvjs7QNKBUKmFiYgKlUinprkgClD835c9N+XNT/tyUPzflz035c1P+3JS/OZrQNKBUKmF8fFwbNCnlz035c1P+3JQ/N+XPTflzU/7clD835W+OJjQNyOVyOHToEHK5XNJd2VBm7n8k6S60hPLnpvy5KX9uyp+b8uem/Lkpf27Kn5vyN0cTmpKITpmsFBERERERERERszShaYDruhgcHITrukl3RRKg/Lkpf27Kn5vy56b8uSl/bsqfm/LnpvzN0YSmAZZlIZPJwLKspLsiCVD+3JQ/N+XPTflzU/7clD835c9N+XNT/uakk+4Ag0wmg+uuuy7pbkhClD835c9N+XNT/tyUPzflz035c1P+3JS/OTpD04AwDFEqlRCGYdJdkQQof27Kn5vy56b8uSl/bsqfm/Lnpvy5KX9zNKFpQLFYxK9+9SsUi8WkuyIJUP7clD835c9N+XNT/tyUPzflz035c1P+5mhC04BMJoM9e/Ygk8kk3RVJgPLnpvy5KX9uyp+b8uem/Lkpf27Kn5vyN0cTmgakUil0d3cjlUol3RVJgPLn1mn5P/jqs0l3YUPptPylOcqfm/Lnpvy5KX9uyp+b8jdHE5oGlEolXL58GaVSKemuSAKUPzflz035c1P+3JQ/N+XPTflzU/7clL85mtA0oFQqYWRkRBs0KeXPTflzU/7clD835c9N+XNT/tyUPzflb0466Q4wyOVyOHz4cNLdkIQof27Kn5vy56b8uSl/bsqfm/Lnpvy5KX9zdIamiIiIiIiIiIiIbBia0DTAdV2cO3cOrusm3RVJgPLnpvy5KX9uyp+b8uem/Lkpf27Kn5vyN0eXnBti2509d3z89KnYcsF3Y1978sgJTB07UdWgEF8G0PNMfB2dpNPzl+Upf27Kn5vy56b8uSl/bsqfm/LnlmT+1fMwtfMywMpzMxtpXkYTmgY4joM9e/Yk3Y2WefDVZ3HybXcu+vr+7l3R67Mzo9Hy2ZnR6OupA30AAH9gMHpdWe5UnZa/NEf5c1P+3JQ/N+XPTflzU/7clD+3dsi/ei6mdp6mot7czEabl9GfDQwIwxBBECAMw6S7IglQ/tyUPzflz035c1P+3JQ/N+XPTflzU/7maELTgGKxiDfeeAPFYjHprkgClD835c9N+XNT/tyUPzflz035c1P+3JS/OZrQNCCTyeC6665DJpNJuiuSAOXPTflzU/7clD835c9N+XNT/tyUPzflb05b3kNzeHgYH/jAB3DbbbfhoYceir7+3HPP4amnnsKVK1ewa9cufOELX8Db3/722Pe2ok0j62hGKpXCNddcs+rv7yTRPRkKhUX3Z6h9SNBGvjltNeXPTflzU/7clD835c9N+XNT/tyUPzflb07bTWiGYYjPfe5z6O3tjX39u9/9Lh599FE8/fTTOHjwIF544QV89KMfxfPPP499+/a1rE0j62iW7/uYmZlBd3c3UqnU2gq0gVVPSM7c/wi6H/hs7P2pYycWPShoo96ctpry56b8uSl/bsqfm/Lnpvy5KX9uyp+b8jen7S45f+qpp5BOp/He97439vVvfOMbOH78OA4ePAgAeN/73odbbrkF3/72t1vappF1NMvzPAwPD8PzvFWvQ5Lz4KvPrun7lT835c9N+XNT/tyUPzflz035c1P+3JS/OW01ofmLX/wCjz/+OL785S/Hvn7x4kXk83m8613vin39tttuw8svv9yyNo2sYyWu60avi8UiPM9DNpvFwYMHo6ddAUCpVEKhUIh9X2WDD8MQhUIBvu8v2bby/9S29X0fhUIheqLWatsCQKFQQKlUqtvW87xYW4Rh9F4YhrFlhGHshrjFYhFhWK5DEAQoFApRXcIwiN6rXa5tW1uXSr2r2y5Xw0brHQTBmmqYTqdx6NAhpNPpNdW7uobVbWvrUtu2WCwu2bZUKi1qW1vDRuq9lm22Vdt3IzVcqe1SNWy23tU1DMMQBw8eRDabXVO922WMqPSv2XrHxwTEn/xXZ4xYbb2TGCOWq2E6nca+ffvgOM6itivVUGPExh8jstks9u/fj2or1XCjjxGtqPdattl2GiOy2SwOHToEy7LWpYYaI9p7jACAQ4cOIZvNruk4QmPE4rYbYYywLAv79+9HNptNbJvVGJHcGJHNZtHX1xednbeenzU0Rqyuhus5RlTP/7T6swYQIgh8AGHdZdd1geqnqy8zT1M791K9nnYYIxrRNhOaxWIRn/nMZ/CZz3xm0aXdIyMjAIBdu3bFvr5r167ovVa0aWQdKxkdHY1eX7hwARMTE7AsC0EQYHBwMNowr1y5gnPnzkVtL168iPHxcQDljSefz2N+fh4AMD09jcHBhUuuR0ZGcOnSJQDlDSKfz2Nubg4AMDMzg3w+H+tPdZ/y+TxmZmYAAHNzc8jn89HGdOnSpdjPOTg4iOnpaQDA/Pw88vl8tJONj4/j4sWLUdsgCGIbafVkRRiGuHDhQtT2/PnzUdtisYh8Ph/toPU26Epbz/OQz+ej96empnD+/PlYDScmJmI1XKrew8PDUQ1r611bQ9dzMTY2Fv0s+Xwes7OzsbaVn3VsbKxuvW3bjmpYXe/h4eG69S4UCsjn89HPPj4+Hmt7/vx5TE1N1W07OTm5qN6Tk5Pln8V1Y/WenJyM1fDChQtR21KpFKthbb2Hh4ejbba2be02W13vRrbZ2npXttnZ2dlF9a7eZqvb1m6ztfU+d+4crly5Eqthpe3ExERs+66ud2WbrQy0k5OTGBoaitoODQ3h8uXLUb0HBwfheR4sy8Lly5cX1buyzdbWsF3HCNdbOHBY7RgRIoz9gqw3RlRqWDtGXL58eVG9K9tsUmPEyMjIkmPE7OxsbL1LjRFL1VtjxMYeIyzLwtTUVKzetWNE9TbbCWPEao8j6tW7ss1OTExsyDHCsizYtl13m232OGKpemuMaN8xYnh4GLZtw7KsNR1HaIxYut7tPEaMjIxEnwPXchyhMWJjjhGV/b623uvxWUNjRFk7jRGWZSEMw2Xnf1b7WaP88xWjOlSWK8bGxhBUTWgGQbAwgRz40VxN5eepPSGvsu23wxjRCCsMq6dvk/PXf/3XGBoawje/+U0AwNe//nUMDQ3hoYcewn/8x3/gQx/6EH7605+iq6sr+p6XXnoJf/Znf4af/OQnLWnzrW99a8V1LGVwcBAPPfQQPvGJT0SXqxeLRdi2jTAMMTo6ip6eHmzevBm2baNUKqFUKiGXywEoB2tZFjKZDMKrZytlMhmkUqm6bQHAcZxFbX3fj/4qUH1GQLNtgYWzC9PpdKztX//0O/j8Wz6IMAyjtsdf/jr6u3dFO29+ZjRaPjs9gr/77T9FNpuN6uL+9X/Hlgc/H5396DgOpj/yCdj79wIALMuGPzAYLQdnz2PL038bta1Xw0q9M5lMtN7lathovf/qx/8LX/jf/o9V1zAMQ0xMTODaa6+FZVlN19uyLHieF53tU9u2uoa2bS9qWywWkUql6rYtlUrwfT/WtraGjdR7Ldtsq7bvRmpYvc3Wa7tUDZutd3UNZ2dnMTU1hV27dsG27VXXu13GiK+ceQ5fevvRputdPUacnR5F3+YdsCxryTFiqW12pXonMUYsV8P5+XmMjY2ht7cX2Wy2qW1WY8TGHyNKpRJGRkawbds2dHd3N1TDjT5GtKLea9lm22mMsG0bY2Nj2Lp1KzKZTMtrqDGivceIYrGIqakp7Ny5E0EQrPo4QmPExhwjZmZmMDk5id7eXmQymUS2WY0RyY0RrutieHgYO3fuRFdX17p+1tAY0X5jRPX8z6ZNm1r6WWPq2H2w+vfCtm0AFvyBfLTsD5xD15OP4r/962PYv6X8TJqz0yOL5mmeOHICV+7+eGyuJXWgD0HgI8yfR88z31iXMeIrZ57DF//LHQ1ts8PDw/ja176Gz3/+8+jrW3jOSq22eCjQj370I3z/+9/H9773vbrv7969G0B5dr+/vz/6+ujoaPTwoFa0aWQdK6nsUACiUKpPPS9veIjCr/d9lmVFG2+zbVOpVOzGs6ttC2DZtplMJv6DX52YqPw/1cu4OolXkc1m4VnlOti2Hft/LCt+0nD1cm3b2rpU/x8rtW2m3rZtR+1XU0PXdRGGIVKpVOz9tdS7um3tz1rbtpm6rLbtWrbZVm3fwOpruJ71rl42tc2u5xhRGcOA1Y8RsBBbT70xoiKp7buV9a6coVPbFli+hhojmm/bjmOEZVl1jw3qtW2XbTaJ44hWbbPtNEZUfv9XJjPrtV1LDduh3hojlm4bVl3W1w711hjRfNu11rv6s1ES22w71Jt5jLBtO3p/I9RbY0TzbZeqd/X8T6XPrao3YMG2U0suO44DVD5zlVe+5DxN7dyLbafgo/xeO2yzjWiLS85feukljI+P49Zbb8Xhw4dx+PBhnDp1Cs8//zwOHz6M119/HTfffDNeeuml2PedPn0aR44cAQDs2LFjzW0aWcdqOI6DvXv3LtpBhYPy58aY/8z9jyTdhbbBmL8sUP7clD835c9N+XNT/tyUvzltMaH5xS9+Ea+99lrs34kTJ/DBD34Qr732Gm699Vbcc889eOKJJzAwMAAAePHFF/HKK6/grrvuitbTijaNrEOkmiZvRERERERERETMaYtLzhtx++23Y2ZmBvfeey9mZ2fR29uLxx57LHY9fSvaNLKOZlVuktrf3x87vVY4KH9uyp+b8uem/Lkpf27Kn5vy56b8uSl/c9p2QvPjH//4oq8dPXoUR48eXfb7WtGmkXU0I51Oo7e3N3ZvAOGh/Lkpf27Kn5vy56b8uSl/bsqfm/LnpvzNUYUNSKfT2Lp1a9LdkIQof27Kn5vy56b8uSl/bsqfm/Lnpvy5KX9zNKFpgO/7mJubw6ZNm2JPitpIjp8+Fb0u+G5sueLszGisTfUys07IX1ZP+XNT/tyUPzflz035c1P+3JQ/N+VvjiY0DfA8DxcuXEB/f/+G3qD3d+8CUJ64rLyuFwMfdQAAIABJREFULD955ESs7YOvPouTb7vTaP/aVafkL6uj/Lkpf27Kn5vy56b8uSl/bsqfm/I3RxOaBmSzWdx4442w7bZ4qLwYpvy5dUL+K52h/ejjv4h/Q6GAqWMLf+ToeWbxGd0sOiF/WT3lz035c1P+3JQ/N+XPTfmbowlNAyzL0sw8MeXPrVPyX+4MbQBIHeiLvuYPDEbL/sCgwV62n07JX1ZH+XNT/tyUPzflz035c1P+5mjK2ADXdXHhwgW4rpt0VyQByp+b8uem/Lkpf27Kn5vy56b8uSl/bsrfHJ2haUip9P+zd+9BkpWF/f8/53Sf7tkbyy57c5nd2WUN3hBvmPIGKKYUK5iUieImgsk3QEQhQGL9dMsAyvI1WfarYBSNoEQUSCHGC99opSQkCqtSfi3BCiTe2e3Zmdm57Nx7ZrrP9ffHcM529/TM9Fz6OT3z+byqpmpm55meM8/7nIeZh774aR+CNKj24bS1D7G95/xrqx5OW/vwWmDmQ2zVn5v6c1N/burPTf25qT839eem/tzU3wxtaBqQy+Wwe/fu+QdKy6h9SG3lw21jlQ+prX24bSX156b+3NSfm/pzU39u6s9N/bmpPzf1N0cPORcREREREREREZEVQxuaBpRKJfzqV79CqVRK+1AkBerPjaV/cLQzeUOpdOr9CseK/ThW7EcpcJP3K+/1vBqx9Jf61J+b+nNTf27qz039uam/OXrIuQHZbBZbt25FNqvpZqT+3Fqpf/Hmw1h/8EPLfru1zxlb7/vcc/6p55m99amHcNMrLl3242hFrdRfzFN/burPTf25qT839ee22vov9m+3Rl6bZKlWxwy3uGw2i02bNqV9GJIS9eem/tzUn5v6c1N/burPTf25qT839T+lkdcmWQo95NyAIAgwMTGBIAjSPpSW0Yx7ibUq9V/Zbn3qoSV9vfpzU39u6s9N/bmpPzf156b+3NTfHG1oGuB5Hrq6uuB5XtqHIilQf27qz039uak/N/Xnpv7c1J+b+nNTf3P0kHMD8vk8zjrrrFXzHAqyMOrPTf25qT839eem/tzUn5v6c1N/bupvjmbYAMuy4DhO2ochKVF/burPTf25qT839eem/tzUn5v6c1N/c/SQcwM8z0Nvb6/uckxK/bmpPzf156b+3NSfm/pzU39u6s9N/c3RPTQNCMMQ5XIZYRimfSiSAvXn1ur9rzhyZ9XHpcBFWyaXfHzP+dcCOPVKdKXAXbZXpWPQ6v2ludSfm/pzU39u6s9N/bmpvzna0DQgn8+jo6Mj7cNYdYo3H14Rr5au/txWQv8967cl7x8r9icfxxuX8aYmMP2q7ze94lKzB7iCrYT+0jzqz039uak/N/Xnpv7c1N8cbWhKSwmOdp76oFSq/hjA6OXXVn2+6mMAG++rvreZiCwvbWaKiIiIiIhILK07m2lD04BSqYSuri60t7ejra0t7cNpWbWbkbNdFJm9uwFMb37G78cftyL156b+3NSfm/pzU39u6s9N/bmpPzf1N0cvCmRANpvFpk2bkM1q/5iR+nNTf27qz039uak/N/Xnpv7c1J+b+pujGTYgm83ijDPOSPswJCXqz039uak/N/Xnpv7c1J+b+nNTf27qb47uoWlAGIaYnJzUq1yRCsMQYzf+vfqT0vU/E9PzcKo/N/Xnpv7c1J+b+nNTf27qb442NA1wXRfHjx+H67ppH4qkwHVdlEplI/2LNx9u+veQhdH1z039uak/N/Xnpv7c1J+b+nNTf3P0kHMDcrkc9u7dq+dQIJXL5bBmTRtyuVzahyIp0PXPTf25qT839eem/tzUn5v6c1N/c3QPTQNs20Yul4Nta7pbza1PPdT072HbNizLVn9SJq9/E+ezLIzWf27qz039uak/N/Xnpv7c1N8cbRkb4HkehoeHsWnTJjiOk/bhiGGe58HzXHiep/6Emnn9X3HkzqqPS4Fb9W/3nH8tRi+/tmJAqfpjAPjLFy7rMUk1rf/c1J+b+nNTf27qz039uam/OdoyNiAMQ0xMTOhJYUmFYYggCNSfVLOv/z3rtyVvbZlc8n6lzN7dyOzdDbS1Je9n9u5uyvFINa3/3NSfm/pzU39u6s9N/bmpvzm6h6YB+Xwee/fuTfswJCX5fB5e2xrk8/m0D0VSoOufm/pzU39u6s9N/bmpPzf156b+5ugemiIrhJ4fUURERERERERE99A0olwuo6urC+3t7bqXHqFyuYypqSk45bL6E9L1z039uak/N/Xnpv7c1J+b+nNbDf0rX5eh9nUagPlfq2HjfdXjm0UbmgZkMhmcdtppyGQyaR+KYP6LEwCOFfurxlR+vFCZTAbZbEb9Sen656b+3NSfm/pzU39u6s9N/bmtlv7x6zIcK/ZXvUZD5d5I/LoMwdHOqvdN0YamAdlsFlu3bk37MKTCXBfnPedXvwr0rU89hJtecemiv1c2m4Xj5JDN6nJjxHj9rz/4obQPoWUw9pdT1J+b+nNTf27qz039ua2U/snGY6lUdxMy3rhc6h28mkk7LAaEYQjXdZHL5WDbetpSNmEYIgynX+Vc/fno+uem/tzUn5v6c1N/burPTf25rYT+lQ8JL958eMYdUirv5LXUO3g1U2vO7irjui4KhQJc1037UCQFruuiVCqrPyld/9zUn5v6c1N/burPTf25qT839TdHG5oG5HI5dHR0IJfLpX0okoJcLoe2trz6k9L1z039uak/N/Xnpv7c1J+b+nNTf3P0kHMDbNtGW1tb2ofRsFa+S/FKZNs2bDvTsnc3l+Zqheu/0edHAVr7OVJWolboL+lRf27qz039uak/N/Xnpv7maEPTAN/3MTw8jE2bNumFYQj5vg/Pc+H7vvoTSvv6n/f5UWrG639oLK+0+0u61J+b+nNTf27qz039uam/OZpdA4IgwNjYGE477bSWPKGvOHJn1celwK36t/gJYVfCq1y1oiAI4PsBgiBoyf7SXK1+/UtzqT839eem/tzUn5v6c1N/bupvjmbXgHw+j3379qV9GHPas35b8v6xYn/ycbxxuVJe5aoV5fN5rFmzBvl8ftYx9e45J6vDSrj+pXnUn5v6c1N/burPTf25qT+3ZvevegqxeZ5SbLXfGU0bmiIiIiIiIiIiIi2s8unEgFmeUozozmja0DSgXC6jp6cHO3funPNeetKaZlsA5nuhldHL44UkQlQqYfTyawBYAGYuRLOpfOh/vacCOPU94kGlqn9r9PtI8+j656b+3NSfm/pzU39u6s9N/bmpvzna0DTAtm2sW7dOr3KdgmY9lHu+F1qJZfbuRhSFCI52wt6zC5Zl1938nEvlw/9rnwog/h6x4Ghn8vFCv480h65/burPTf25qT839eem/tzUn5v6m6MNTQMcx8G2bdvmHyirkmXZyZvw0fXPTf25qT839eem/tzUn5v6c1N/c7TDYkAYhnBdF2EYpn0oxqzm52lYuKjiTdistOtf1+7yWmn9ZXmpPzf156b+3NSfm/pzU39ztKFpgOu6OHr0KFzXTftQJAVhGCZvwkfXPzf156b+3NSfm/pzU39u6s9N/c3RhqYBuVwOu3btQi6XS/tQJAW2bSdvaSvefDjtQ6Cj65+b+nNTf27qz039uak/N/Xnpv7m6Dk0DbBtG2vXrk37MJaNHpK6UFbFm7BZbde/LIz6c1N/burPTf25qT839eem/uakf5cxAr7vY3BwEL7vp30okoIoCpM34aPrn5v6c1N/burPTf25qT839eem/uZoQ9MA3/cxPDysE5pUFEXJm/Bppet//cEPpX0IdFqpv5in/tzUn5v6c1N/burPTf3N0UPODWhra8Pzn//8tA9DUmLbGUR2BradSftQJAW6/rmpPzf156b+3NSfm/pzU39u6m+ONjRFmig42jn9Tql06v3njF5+7akPSqXqjwFsvO/OZh+erCC3PvWQnr9WREREREREBNrQNKJcLqO3txc7duxAPp9P+3DEkHhDslwuY/ym27Dh1g/P6J/ZuxvA9MZn/H78sawOuv65qT839eem/tzUn5v6c1N/bupvjjY0DbBtG/l8HratpyxlZNs2bNuq23+ue3DGjhX7p4cEbvJ+3duY5Xbmuieo7gXafLr+uak/N/Xnpv7c1J+b+nNTf27qb442NA1wHAc7duxI+zAkJY7jIJfLw3Gcqn+v3Ews3ny47gu23HP+qc3Heg85rt2QnO126t0TVPcCNUPXPzf156b+3NSfm/pzU39u6s9N/c3RlrEBURTB8zy9yjWp6Vc4D43016tYtx5d/9zUn5v6c1N/burPTf25qT839TdHG5oGlMtlPPvssyiXy2kfiqSgXC5jaqqk/qR0/XNTf27qz039uak/N/Xnpv7c1N8cbWga4DgO2tvbZzzkWDg4joO2tpkPORcOuv65qT839eem/tzUn5v6c1N/bupvjp5D04BMJoN169alfRiSkkwmA9vOIJPJpH0oDZnteThlcZZy/V9x5NRzpJYCt+rj+PlVK18oarYXjpL0aP3npv7c1J+b+nNTf27qz039zdGGpgG+72N8fBwbNmxANqspZ+P7Pnzfg+/7qfWf69XUq14F/bkxeiX05bPU63/P+m0ApjcuK98Hql80Cqj/wlGSLq3/3NSfm/pzU39u6s9N/bmpvzmaXQN838fAwADWrFmjE5qQ7/vwvPQ2NBt5NfX4lc8BvRL6ctP1z039uak/N/Xnpv7c1J+b+nNTf3M0uwa0tbXh7LPPTvswVo2Vdm/DtrY2tP2fjxn/vtIaTF7/undm69H6z039uak/N/Xnpv7c1J+b+pujDU1ZUea7t+Ho5dfq3oYiIiIiIiIiIqtYy7zKebFYxMc+9jG86U1vwoUXXoh3vOMdeOSRR5LP//d//zde8pKX4IILLqh6+/d///eq2/nGN76BSy65BBdccAHe+c534qc//emM7zXfmEZuYyFc10VnZydc113S7cjKpP7c1J+b+nNTf27qz039uak/N/Xnpv7mtMw9NG+44QZs2bIF3/72t7Fu3To88cQTeP/7348dO3bg3HPPRW9vL1784hfja1/72qy38fDDD+P222/Hl7/8Zezbtw/f/e538b73vQ/f/OY3sWvXrobGNHIbi6HnTuCm/tzUn5v6c1N/burPTf25qT839ee2mvq38tOatcw9NA8fPoyDBw8mL2//2te+Frt378aTTz4JAOjr68Pznve8OW/js5/9LK644grs27cPAPDWt74V5513Hh544IGGxzRyG3Op3IUvl8vwPA+5XA47duxAGIYIwxDA9BPFlkqlqq/zPA8AEEURSqUSgiCYdWz8fWrHBkGAUqmEKIoaHhurPL74Y0zfzIzb9Tyv6mctlUrwfT/5ulKplNyW53kol8tV87KQsfG81I6NorDq+Ke/7rkDRoQwDJKPoyis+Nz0bU3/Wzw2TH62hc53GAZ15zueF9u2sXPnTmQymVnb1M5hvfmubLPY+QaiqrHT/35qXqrnKUrmpt68VLZZyjm7XOd3I3M439jZ5nCh8115zoZhiB07diCXy8H3/YbPb9/3gehUG0RRxTkLo2vEcs+3qTVirnM2HjvXHC7H+Z3JZLB582Y4jrPgOVzofC/lnJ1t7ELPWa0R1fOSy+WwdevW5Hs0MoeLne80f4/QGlF/vnO5HHbu3JmMX+451BrR2mtEFEXYuXMncrnckn6P0Boxc+xKWCMAYOvWrcjlcqmds1oj0lsjcrkcNm/eDNu2q8Y2428NrRGLm8NmrhGV+z/N/lsj/vt+tjkMw7Bpa0TtvkHlx5VjK/daoiiq2mea65xtRMtsaG7evBm5XA7A9A/x4IMP4tlnn8WrXvUqAPNvaJ44cQKFQgFvfOMbq/79oosuwuOPP97QmEZuYz79/f3J+z09PRgaGkIUTQctFArJiTk2Nobjx49XHf/g4CCA6ZOnUChgamoKADA+Po7OzlPP/9jX14eTJ08CmD45CoUCJicnAUw/dL9QKFQdT+UxFQoFFItFAMDk5OT02OdOJs/z4HrVJ3T03CenpqZQKBSSC2dwcBAnTpxIxh4/fhxjY2PJ1xUKheRiGBoaQk9PTzK2q6sLIyMjAJDMS3whjYyMoLu7Oxnb3d2N4eHh5PgKhUJywvt+gK6urqo5rLxQSqVTF8b0xuOpzSDXdeEmCwiqFqbaOezr68PAwEByu4VCARMTE8nYUqmcfN+BgYG68x0EASYmJlAoFJLvc/LkSfT29iZjOzs7MT4+XncOBwcHqxabrq4ujI6O1h07PDw8Y77jOYzPl/i2hoeHq+alXC7PWGzic3Z0dLRqvnt7e5Nz1vf9qvO79pzt7e1d0DlbO9/xORvPYeV89/X1zZhvYOY5Wzvf9c7ZeOzQ0FDV+V053/E5Gy+0w8PDM87Z+Px2XTe5lqMowsjISNUcxmtEvTkcGxur/h8MUQTPe25jOoLRNaLynK2c78pzthXXiNpz9sSJE8l8x+vsbGty5TlbuyYvdI2onMPZ1ojZ5nsha0Tl2MWuEfE5W7lG1J6z8djac1ZrxMw1IooiDA0NzbtGxOfsQteIVvk9QmtE/TUiiiIEQdDQGjHf7xGzzbfWiNZeI4Jg+n96L/X3CK0RK2+NOHHiBAYGBpJ1YKm/R2iNWFlrRBRF6OzsNPa3htaI1lojoihK2jT7b434a2dbI0qlUtPWiPh7xnfiqdxHqJzvcrkMz6/evI03oeZaIxphRZV3G2gBF154Ifr6+vDCF74Q1113HS666CIAwIEDB2BZFsbGxvCLX/wCp59+Ovbv3493vetdAICf/exnePe7340nn3wyuZcnAHz/+9/HBz/4Qfz0pz+dd8w999wz723MprOzE4cOHcJ1112X3LuzXC7Dtu3kJNuxYwc2bNgA27bh+z5830dbWxuA6cXIsiw4jpNsgDqOg0wmU3csgOT/+FWODYIAnuchn8/DsqyGxl7zky9iz/ptyYndOXky+bhz4iTuueDaGbcb/6EWb0KXSiVks1lks1mEYQjXdZHL5WDbdnLvwnw+n8xLJpOZd2zx5sNw/vZ62LYNx3FmjB2/6RCcv70hmZdyuYzSlX+DzN4OJPe6LHQhs7cDURQiPHYcG+/7LK44cid2r90CywIKEyexZ/1WhGEEy7JQmBjAXa+9ekHzPfHRw9hw64EZ8x3PSxBMb7y2t7cjk8nUbVO8+TCyH7kumcN68/13//V1fPRV+5c038Wbb0P2I9cnY33fx8T/uv65OUMyT/EcBkc7seHLn6l7zsbn91LP2eU6v2vnZSHnbDy23hze+tRD+P9e9AcLmu/Kc3Z8fBy9vb3o6OhIvtdsYytv1/d9vO9H/4g9G7YDAI6N96Fj/VZYlo1jxX589tVXGlsjlnu+l2uNaGQOZztn47FzzeFyrMkTExPo6urC7t27sWbNmgXN4ULnu3Jelmu+fd9f0DnLuEbMNd/xL7PPe97zcNpppzU0h4ud7zR/j9AaUX++gek/3Hbu3Il8Pr/sc6g1orXXiFKphJ6eHnR0TP+OtdjfI7RGrMw1Ynx8POmfz+dTOWe1RqS3RsSbQe3t7Vi3bt2if4/QGrEy14jK/Z/169c39W+N+O/72ebwlp8+iL992TvnXCPc//0prD/4oQWvEeWrPli1bzD9YswWgqMFtH3xdnzg/30h2VeK91o61k0/cineZ5rtnO3t7cUnPvEJHDhwALt3n3rR51ot98D+xx57DGNjY/jSl76Eb33rW3jNa16DtWvXwrIsDA4O4qabbkJ7ezuefvppfOADH0AQBNi/f3/yHAXx3bpjlmUlO8XzjWnkNuYTnzgAkijxQ47Xrl2b3HZ8otT7OsuykpO3cuytTz2Em15x6ZxjM5kMMplMQ7dbO7b257ZtG7Dqj40fPhmrvF3btqs+rh0bz8tSx1pW9cf5fB6l+IBhwbYzCJ772LJsJD/MjJ/Vgm2f+txC2mQyGdh2BpZlzRgLTM9LEATYuXMn2traZm0Tj6283dr5rjzmxc43MPPcqpyX6nmyMD039c/Zytud7Zyt97M2OjZ+FftGz29g/jlcjrG1833omW9WPa9I7Tm7fv167Ny5M/mPzmxzWHu72WwWsE61gWU912fmMS30nF3sGrFc821qjZjrnJ1v7GLO2Xpj29rakocc1o6NPx9rxfleyhw2e42oN7bV1gjHcZL//sda/ZzVGtHY2EbmO/7v/9q1a5OffTnnsBXmW2vE7GPj3//j//7HWvmcbWSs1ojGxq5duzbpn9Y52wrzzbpGxP/9j8evhPnWGrHwsbPNd+X+T3zMzZrv2r/va+fQtu3ktmab7/hxoAud73LNvkHlPkLtvFUev2VZydC5ztlGtMxDziuddtppuP7669Hf34/7778fAPD3f//3uPvuu7Fr1y5YloVzzz0X733ve/GNb3wDALBjxw4A1Q/5jj/evn17Q2MauY3FyGQy2LBhQ9UJIfNbf/BDaR/CslB/burPTf25qT839eem/tzUn5v6c2ul/q38gj7LoSU2NMMwxPe+970Z/3766adXPVdAva+L7xm3ZcsWvPCFL8Rjjz1WNebIkSM4//zzGxrTyG0shu/7GBkZSR5+JFzUn1sj/W996iGDRyQm6frnpv7c1J+b+nNTf27qz039zWmJDc2hoSHceOONuPPOO5PH8R85cgQ/+MEPkhfoufrqq3HbbbclT5T69NNP4ytf+UryHJoAcNVVV+GLX/wijh49CgB49NFH8cMf/hCXXXZZw2MauY2F8n0ffX19OqFJLVf/1f5/V1YrXf/c1J+b+nNTf27qz039uak/N6b+wdFOBEc7gVLp1PsVjhX7k7dS4CbvL5eWeA7NLVu24Ktf/So++clP4s1vfjOiKMKWLVtw6NAhvP71rwcAHDx4ELfffjsuvvhieJ6HDRs24JprrsE73/nO5HYuueQSFItFXH311ZiYmMD27dtx1113VT2J6HxjGrmNhWpra8MLXvCCRX/9coqfh1PMaaX+Yp76c1N/burPTf25qT839eem/txY+m+8787k/fj1Lyrdc/61VR83Yy+qJTY0AaC9vR133HHHrJ/fvn07brvttnlvZ//+/di/f/+SxjRyGyIiIiIiIiIiImJeSzzkfLVzXRddXV3Jw+mFi/pzU39u6s9N/bmpPzf156b+3NSfm/qbow1NQ+IXLxJO6s9N/bmpPzf156b+3NSfm/pzU39u6m+GNjQNyOVyOPPMM5HL5dI+FEmB+nPL5XLYeNcD6k9K1z839eem/tzUn5v6c1N/bupfXzNey6VlnkNzNYuiCFEUwbIs7dSvQrVPfltL/VefK46cegLkUuBWfQxMPwHy6OXxkyBHQKmM0cuvATDdv/IJlGV10/XPTf25qT839eem/tzUn5v6m6MNTQPK5TIKhQI6OjrQ1taW9uGIYeq/stRuTtZuWNa+WttcMnt3IwwDBEc7keloh21nEBztXLZjldan65+b+nNTf27qz039uak/N/U3RxuaBjiOgx07dsBxnLQPRVKg/ivPnvXbkvePFfuTj48V+wFUb2re+tRDc9593rZtRLYN29YzfDDS9c9N/bmpPzf156b+3NSfm/qbow1NAzKZDDZu3Jja95/r4bHxxky8UROPqfxYlibt/pI2q+JN2Oj656b+3NSfm/pzU39u6s9N/c3RhqYBQRBgYmIC69atQyaTSeUYKu9hNte9zYD573HW6qoe0lsq1X2Ib/yzm9i8bYX+kqao4k2bmmx0/XNTf27qz039uak/N/Xnpv7maEPTAM/zcOLECXR0dOiEbrLaF1sp3nx4xov2LOThwstB/bmFYYgwDGGFIWxb/dno+uem/tzUn5v6c1N/burPTf3N0YamAfl8Hr/zO7+jV7gipf7c9Bya3HT9c1N/burPTf25qT839eem/uboL2wDLMuCbds6oUk10r/2XqSt7NanHkr7EJaNmZ9Fz6HJTOs/N/Xnpv7c1J+b+nNTf27qb442NA1wXRfd3d1wXTftQ5EUqD+3KAoRRiGiKEz7UCQFuv65qT839eem/tzUn5v6c1N/c7ShaUgYNn8zo3jz4aZ/D1kcE/1FpDXp+uem/tzUn5v6c1N/burPTf3N0HNoGpDL5bBr1660D0NSov7cLMuGbdmwLP3/I0a6/rmpPzf156b+3NSfm/pzU39ztKEpIpKCK47cmbxfCtyqjwHgnvOvBQAcK/YnY+L3RURERERERJhpQ9OAUqmEQqGAjo4OtLW1pX04Yhhj/+LNh1fUCx01UxgGCMMAVhjAtjNVn9uzfhuA6U3L+P34Y+DUpiYw/QJGN73iUgNHLMuJ8fqXU9Sfm/pzU39u6s9N/bmpvzna0DQgm81i+/btyGZnn25tVqxejfQXc+a7ZySAqntCLvWekZZlJW/CR9c/N/Xnpv7c1J+b+nNTf24rrf9KviPSypjhFS6bzeL0009P+zAapo3V5bXS+jOY656RlfeKBJb+Pxus554/c6nPoanrcmXS9c9N/bmpPzf156b+3NSfm/qbo1epMCAIAhSLRQRBkPahSApaqf9K/r8vK1dU8SZsWun6F/PUn5v6c1N/burPTf25qb852tA0wPM8dHd3w/O8tA9FUqD+3MIwTN6Ej65/burPTf25qT839eem/tzU3xxtaBqQz+exb98+5PP5tA9FUqD+M9361ENpH4Ixtm0nb8JH1z839eem/tzUn5v6c1N/bupvjp5D0wDLshb9hLBzvYDJPedfi9HLK57vr1Sq/hjAxvtmvuCJmLWU/rKyBUc7p98plREcPT7j8/GLDS31hYekden656b+3NSfm/pzU39u6s9N/c3RLBvgeR5OnjyJLVu2wHGcBX99vRcwqdz8yOzdDWB68yR+P/5Y0rfU/q1gvlcGv/3uX1R/Qc3mOuPGevwze56H8ZsOYcOtB6r6V7740FJfeEha12q4/mXx1J+b+nNTf27qz00/RA9PAAAgAElEQVT9uam/OXoMpAFRFMHzPESRXhSE0Wrpv2f9NuxZvw1tmVzyfuUrhGf27k7e0NZ26v0mWSkPW4+iKHkTPqvl+pfFUX9u6s9N/bmpPzf156b+5ugemgbkcjns3t28jR1pberPLZfLIZ9vQy6XS/tQJAW6/rmpPzf156b+3NSfm/pzU39zdA9NERERERERERERWTG0oWlAqVTCr3/9a5RKpbQPRVKg/txKpRKmpibVn5Suf27qz039uak/N/Xnpv7c1N8cbWgakM1mccYZZ+iVrkip/+o234v5ZLNZOI6j/qR0/XNTf27qz039uak/N/Xnpv7maIYNyGaz2Lx5c9qHISlRf27ZbBbZrDY0Wen656b+3NSfm/pzU39u6s9N/c3RPTQNCIIAExMTCIIg7UORFKh/eoo3H077EBAEAcIwUH9Suv65qT839eem/tzUn5v6c1N/c3SXIQM8z0NXVxc6OjqQyWTSPhwq6w9+KO1DUP9ldMWRO5P3S4Fb9TEA3H73L6q/oFTC6OXXJh9uvK96vAme56FUKiPneepPSNc/N/Xnpv7c1J+b+nNTf27qb442NA3I5XI466yzdDKTUv/ltWf9NgDAsWJ/8n78MQBk9u5O/i042pl8HBztNHiUp+RyOaxZ04ZcLpfK95d06frnpv7c1J+b+nNTf27qz039zdGGpgG2bcO29eh+VurPzbZtWJbOAVa6/rmpPzf156b+3NSfm/pzU39ztKFpgOd5GBoawubNm+E4TtqHIxXme4Xq5aD+01biw8WXg+d5cF0XnufN2t/EeSjp0PXPTf25qT839eem/tzUn5v6m6MNTQPCMMTU1BTCMKz69/k2eO45f3ozJ34obSlwk/dl5ZitP6P5Hi7eiJV2PYRhiDAM1J+Urn9u6s9N/bmpPzf156b+3NTfHG1oGpDP57Fnz566n5tvgyfe1ASAW596SPfkWoHm6i+n1N4Ds3jz4Rkv6jTf9TB697VoNfl8Hl7bGuTz+bQPRVKg65+b+nNTf27qz039uak/N/U3Rxuaq0DyYiel0qwvfLLS7tUmK0/VuTfLuch6HtZuzIqIiIiIiIjI4mlD04BSqYSuri60t7ejra1tWW+78l5t9e7RBuhenmlrZv9WsRz3rlytGPrL7NSfm/pzU39u6s9N/bmpPzf1N0cvvWRANpvFpk2bkM0ubf+YZQNotVmu/pKOpV536s9N/bmpPzf156b+3NSfm/pzU39zNMMGZLNZnHHGGWkfhqRE/RdntTxMW/25qT839eem/tzUn5v6c1N/bupvju6haYBe5Yqb+nNTf27qz039uak/N/Xnpv7c1J+b+pujDU0DXNdFZ2cnXNdN+1AkBerPTf25qT839eem/tzUn5v6c1N/bupvjh5ybkAul8OePXvgOE7ahyIpUH9u6s9N/bmpPzf156b+3NSfm/pzU39ztKFpgG3byOfzaR+GpET9uak/N/Xnpv7c1J+b+nNTf27qz039zdFDzg3wPA/9/f3wPC/tQ5EUqD839eem/tzUn5v6c1N/burPTf25qb852tA0IAxDFItFPSksKfXnpv7c1J+b+nNTf27qz039uak/N/U3Rw85NyCfz+Oss85K+zAkJerPTf25qT839eem/tzUn5v6c1N/bupvju6hKSLLbv3BD6V9CCIiIiIiIiKySmlD04ByuYxnn30W5XI57UORFKg/N/Xnpv7c1J+b+nNTf27qz039uam/OdrQNMC2bWzYsAG2relmpP7c1J+b+nNTf27qz039uak/N/Xnpv7m6Dk0DXAcB1u3bk37MCQl6s9N/bmpPzf156b+3NSfm/pzU39u6m+OtowNCMMQpVJJr3JFSv25qT839eem/tzUn5v6c1N/burPTf3N0YamAa7rolAowHXdtA9FUqD+3NSfm/pzU39u6s9N/bmpPzf158bYP60XBdaGpgG5XA67d+9GLpdL+1AkBerPTf25qT839eem/tzUn5v6c1N/bupvjp5D0wDbtrFmzZq0D0NSov4z3fSKS9M+BGPUn5v6c1N/burPTf25qT839eem/uZoQ9MA3/cxMjKC008/HdmsppzNSugfHO089UGpVP3xc44V+6c/HbjJ+zK/ldBfmkf9uak/N/Xnpv7c1J+b+nNTf3M0uwYEQYDR0VFs2LBBJzShVu+/8b47qz4u3nx4xnNg3HP+tcn7tz71UEvcw7IVjqERrd5fmkv9uak/N/Xnpv7c1J+b+nNTf3M0uwbk83ns27cv7cOQlKg/N/Xnpv7c1J+b+nNTf27qz039uam/OXpRIBEREREREREREVkxtKFpQLlcxtGjR1Eul9M+FEmB+nNTf27qz039uak/N/Xnpv7c1J+b+pujDU0DbNvG2rVrYduabkbqz039uak/N/Xnpv7c1J+b+nNTf27qb46eQ9MAx3Gwffv2tA9DUqL+ZrXaK7arPzf156b+3NSfm/pzU39u6s9N/c3RhqYBYRjC931ks1nt0i+j2lfiblXqb04rvmK7+nNTf27qz039uak/N/Xnpv7c1N+clpndYrGIj33sY3jTm96ECy+8EO94xzvwyCOPVI35xje+gUsuuQQXXHAB3vnOd+KnP/3pjNtZjjGN3MZCuK6Lo0ePwnXdJd2OrEzqz039uak/N/Xnpv7c1J+b+nNTf27qb07L3EPzhhtuwJYtW/Dtb38b69atwxNPPIH3v//92LFjB84991w8/PDDuP322/HlL38Z+/btw3e/+128733vwze/+U3s2rULAJZlTCO3sVC5XA67du1CLpdbtvmSlUP9uak/N/Xnpv7c1J+b+nNTf27qz039zWmZe2gePnwYBw8exLp16wAAr33ta7F79248+eSTAIDPfvazuOKKK7Bv3z4AwFvf+lacd955eOCBB5LbWI4xjdzGQulJYbmpPzf156b+3NSfm/pzU39u6s9N/bmpvzktM8ObN29OdrDL5TIefPBBPPvss3jVq16FEydOoFAo4I1vfGPV11x00UV4/PHHAWBZxjRyG/OpvFtxuVyG53nwfR+Dg4OYmJhAGIYAAN/3gSg69YVRhCgK4w+AKEIQBMnYUqlU9T3i7xNFEUqlUjI2CAKUSiVEz9127dgwDBsaCwClUmn6OOuM9Txv1rFhGKJUKiU/q+d5KJfLVfOykLGe59UdWzsv9cbONYfx2No5XK75juelXC5jaGgI5XJ5SfNdOS/LNd++788YG5+HC5nvpczhcs935RyGYTDnORt/Lr7d2eZwofNdeR5OTExgcHAQvu/Xne9Gz28T5+xS51trxMyx5XIZfX19yW0tZA5bdY1YzHy36hrR6Dm72DXC930MDAxgcnKy4TnUGrF61gjf9zE0NITJycmmzKHWiNZeIyYnJzE0NFR1PjQ631ojVv4aMTk5iYGBAfi+n9o5qzUivTXC93309/cn37eZf2tojVjcHDZzjajc/2n23xpAtGrXiEa0zIZm7MILL8TLXvYyPPjgg/j0pz+Nl770pejr6wMAbNu2rWrstm3bks8tx5hGbmM+/f2nXjG5p6cn+UVmcHAQXV1dyYk5NjaWRASAMIrgedORo2g69NTUFABgfHwcnZ2nXqm5r68PJ0+enP66MEShUEj+WCoWiygUClXHU3lMpVIJxWIRwPR/aAuFQnIcJ0+erPo5Ozs7MT4+DgCYmppCoVBILpzBwUGcOHEiGXv8+HGMjY0l36NQKCQn7dDQEHp6epKxXV1dGBkZATB9whYKheRCGhkZQXd3dzK2u7sbw8PDAKYvjEKhkJzwo6Oj6OrqSsaeOHECQ0NDAKYvwEKhUDXfx48fT8b29vYmcxiPjee7dg77+vowMDDwXJsIhUIBExMTVWPjC31gYKBqvguFAsbGxpIFrXa+e3t768537RwODg5Wje3q6sLo6GjdscPDwzPmO55D13Wr5nt4eLhqDnt6epLb8X2/ag5r57u3txeDg4N1x9aes5Xz3cg5Wzvf8Tkbz2HlfFees5Vjp6amUCqVk3O2dr6PHz+e/KzxHMZjh4aGqs7vyvmOz9l4oR0eHp5xzsbnt+u66OrqSjY0R0ZGZsx3fM7WzmHtOXvixIlkvmvP2eVcIyrnUGvE0teI8fFxjIyMJD9rvTVirvluxTUiHrsa1ojKc7beGlF7zi50jYg3tCrH1q4Rlees1ojVtUbEv/8NDAws6fcIrRErc43o6+tL/vu/lN8jtEbMPt+tvEb09/cnfwc2+28NrRGtt0b4vo/h4eEl/x4Rz6HWiJW1Rsy2/9OMvzXir12Na0QjrCj+yVvI2NgYvvSlL+G3v/0tDh06hGeffRZ//Md/jJ/97GdYs2ZNMu6xxx7DX//1X+PJJ5/EM888s+QxX/nKV+a9jdl0dnbi0KFDuO6665KHq5fLZdi2DcdxEIYhXNdFLpeDbdvwfR/v+9E/Ys+G7QCAY+N96Fi/FZZlA4hwbLwfd7/+A8hkMsk9u9ra2gCcuhdoLpdDFEUol8twHAdTt3wSaz76QXieh3w+D8uyZow9+ORXcePL34VMJoMgCGYdC0yfmNlsFtlsdsZYz/MQRVHdsbU/q+d5CMMQ+Xw+mZdMJtPw2LnmsHJe6o11HGfWObQsC47jVM3hQuZ7qXO40PmunJflmu/4l6zKse7/vgMbbj0w63z/n5//X9z0ikur5nspc9jM+Z746GFsuPXArOfs4f95GDe/8t3J7c42hwud77nO2dr5bvT8NnHOLuf5rTVi9a4Ri5nvVl0jGj1ntUZojdAaoTVCa4TWCK0RWiO0RmiNaLU1onjzbch+5PpVt0b09vbiE5/4BA4cOIDdu3djNi3zokCVTjvtNFx//fXYv38/7r//fvzRH/0RgOnd/Y6OjmRcf38/tm+f3hDcsWPHksc0chvzqXzi1zgKMP08CvEJCQDZbBawrFNfaFnPbWYCgAVYFjKZTDI2mz2VqvJ7WJZVdbuZTCb5unpjP/qq/Q2NBTDn7TqOM+vY2p+1duxc87KQsbXzspCxc83hcs03MPcctsJ815vD/K0HGh4bW8ocNnO+bTsD67nrrN4cxp9Lc74bHWtiDpfz/NYaMW01rhGLGduqa0Sjc7gS5ltrxMLHtvp8A1oj6v2sWiNa95zVGtFa52wrzLfWiIWPXc3nrNaI5Z9voPrj1bRGNKIlHnIehiG+973vzfj3008/HQMDA9iyZQte+MIX4rHHHqv6/JEjR3D++ecDwLKMaeQ2FqP2brXCRf1b102vuLTp30P9uak/N/Xnpv7c1J+b+nNTf27qb05LbGgODQ3hxhtvxJ133plEP3LkCH7wgx8kL9Bz1VVX4Ytf/CKOHj0KAHj00Ufxwx/+EJdddllyO8sxppHbWCjLsvDF3iPJvcGEi2VZyV21hY/6c1N/burPTf25qT839eem/tzU35yWeMj5li1b8NWvfhWf/OQn8eY3vxlRFGHLli04dOgQXv/61wMALrnkEhSLRVx99dWYmJjA9u3bcdddd1U9nn45xjRyGwvlOA5yudyMu94KB8dxkqczED7qz039uak/N/Xnpv7c1J+b+nNTf3NaYkMTANrb23HHHXfMOWb//v3Yv39/08c0chsLEUVR8qZdej5RFCEIAmQyGfUnpP7c1J+b+nNTf27qz039uak/N/U3pyUecr7alctlTE1NoVwup30okoJyuYzf/va36k9K/bmpPzf156b+3NSfm/pzU39u6m+ONjQNcBwH+XxeDzkn5TgOzjzzTPUnpf7c1J+b+nNTf27qz039uak/N/U3p2Uecr7aXHHkzqqPS4GLv/zRPyYf33P+tQCAY8X+5PPx+7K6ZDIZrF+/Pu3DkJSoPzf156b+3NSfm/pzU39u6s9N/c3RhmYT7Vm/DcD0cygcK/ajY91WWJaVbFzGm5oAcOtTD+GmV1yaynFKc/m+j/HxcWzYsAHZrC45NurPTf25qT839eem/tzUn5v6c1N/c/SQcwOiKEIUhoiiKO1DkRT4vo+BgQH4vp/2oUgK1J+b+nNTf27qz039uak/N/Xnpv7maLvYANu2YWcysG3tHzNqa2vD2WefnfZhUFp/8ENpH4L6k1N/burPTf25qT839eem/tzU3xztsImIiIiIiIiIiMiKoQ1NA8IwTN6Ej+u6OH78OFzXTftQJAXqz039uak/N/Xnpv7c1J+b+nNTf3O0odki9IJAq1smk0n7ECRF6s9N/bmpPzf156b+3NSfm/pzU38z9ByaTRS/mjkAuJGPzsmTKR6NpCWXy2Hnzp1pH4akRP25qT839eem/tzUn5v6c1N/bupvjjY0m+Se869N3o+iCLc+9RBuesWlsCwrxaOSNERRhDAMYdu2+hNSf27qz039uak/N/Xnpv7c1J+b+pujh5wbUC6XMTU1hXK5nPahSArK5TJ+85vfqD8p9eem/tzUn5v6c1N/burPTf25qb852tA0wHEc5PI5OI6T9qFIChzHwc6dO1dNfz3f68Kstv6yMOrPTf25qT839eem/tzUn5v6m6OHnBuQyWRwy3l/mvZhSEoymQw2bNiQ9mFIStSfm/pzU39u6s9N/bmpPzf156b+5ugemgYEQYDR0VEEQZD2oUgK1J+b+nNTf27qz039uak/N/Xnpv7c1N8cbWga4Hkeent74Xle2ociKVB/burPTf25qT839eem/tzUn5v6c1N/c/SQcwPy+TzOPvvstA9DUqL+3NSfm/pzU39u6s9N/bmpPzf156b+5mhD0wDLstI+BEmR+nNTf27qz039uak/N/Xnpv7c1J+b+pujh5wb4Louurq64Lpu2ociKVB/burPTf25qT839eem/tzUn5v6c1N/c7ShKSIiIiIiIiIiIiuGHnJuQC6XQ3t7e9qHISlRf27qz039uak/N/Xnpv7c1J+b+nNTf3O0oWlAFEXJ+3o+BT7qz039uak/N/Xnpv7c1J+b+nNTf24m+68/+KGm3n6r00PODSiXy/jVr36Fcrmc9qFICtSfm/pzU39u6s9N/bmpPzf156b+3NTfHG1oGuA4Dnbs2AHHcdI+FEmB+nNTf27qz039uak/N/Xnpv7c1J+b+pujh5wbkMlksHHjxrQPQ1Ki/tzUn5v6c1N/burPTf25qT839eem/uboHpoGBEGA8fFxBEGQ9qFICtSfm/pzU39u6s9N/bmpPzf156b+3NTfHG1oGuB5Hnp6euB5XtqHIilQf27qz039uak/N/Xnpv7c1J+b+nNTf3P0kHMD8vk8nv/858O2tX/MSP25qT839eem/tzUn5v6c1N/burPTf3N0YamAZZlIZPJpH0YkhL156b+3NSfm/pzU39u6s9N/bmpPzf1N0dbxga4rouenh64rtvU77P+4IeaevuyOKb6S2tSf27qz039uak/N/Xnpv7c1J+b+pujDU1D9ISw3NSfm/pzU39u6s9N/bmpPzf156b+3NTfDD3k3IBcLoddu3alfRiSEvXnpv7c1J+b+nNTf27qz039uak/N/U3R/fQFBERERERERERkRVDG5oGlEol/OpXv0KpVEr7UCQF6s9N/bmpPzf156b+3NSfm/pzU39u6m+ONjQNyGaz2Lp1K7JZPcKfkfpzU39u6s9N/bmpPzf156b+3NSfm/qboxk2IJvNYtOmTWkfhqRE/bmpPzf156b+3NSfm/pzU39u6s9N/c3RPTQNCIIAxWJRr3RFSv25qT839eem/tzUn5v6c1N/burPTf3N0YamAZ7nobu7G57npX0okgL156b+3NSfm/pzU39u6s9N/bmpPzf1N0cPOTcgn89j3759yGQyRr7f17/+dTz44IOwLAsve9nLcODAAWPfW2Yy3V9ai/pzU39u6s9N/bmpPzf156b+3NTfHN1D0wDLspDNZmFZVtO/17Fjx3Dvvffi3nvvxUMPPYR8Po+vfe1rTf++MjuT/aX1qD839eem/tzUn5v6c1N/burPTf3N0YamAZ7nobe3d867HJ88eRL/8i//gne/+914y1veMuu4Z555BldeeSVe85rX4I1vfCM+8YlPwHXd5PO//OUv8fKXvxzr1q0DAFxyySV49NFHl++HkQVrpL+sXurPTf25qT839eem/tzUn5v6c1N/c7Sh2SS/+c1v0NnZCQCIogjlchlRFAEAfvKTn2BsbCwZ+8QTT+Atb3kLvv3tbyObnf1ZAH7+85/jz//8z/HqV78ajzzyCD73uc/h+9//Pm666aZkzAte8AI8+eSTGBwcRBRF+Nd//Vf09fU16aeURtT2Fy7qz039uak/N/Xnpv7c1J+b+nNTf3O0odkkn//853HllVfixIkTyOVy6OjoQC6Xw09+8hO8//3vx8MPP5yMfeUrX4kf/OAHuPfee/G6171u1tv81Kc+hZe//OV43/veh9NOOw0vfvGLcfDgQXznO9/Bb3/7WwDAnj178Fd/9Ve4/vrr8Zd/+ZfYu3dvcm9NSUdlf+Gj/tzUn5v6c1N/burPTf25qT839TdHG5pNcsstt2DTpk246qqrMDg4CAB4+umnce211+Liiy/GZZddlozN5/NYu3btnLc3OTmJH//4x3j7299e9e+vfOUr0d7ejn/7t39L/u3iiy/G/fffjy984Qt43vOeh46OjmX8yURERERERERERNKjDc0mWbduHe666y5ks1lcddVV+Na3voWrr74ar3/963HLLbcs+AliOzs74fs+9uzZM+NzHR0dOH78OIDp5+K88847EUURgiDA/fffj3e9613L8SPJIpVKJfz6179GqVRK+1AkBerPTf25qT839eem/tzUn5v6c1N/c7Sh2USnn346vvCFL2Bqago33ngjzjnnHNx2223IZDILvq2pqankNut9n+HhYQDA5s2bUSwW8Yd/+Ie49NJL8drXvhbnnXfe0n4QWZJsNoszzjhjzudHldVL/bmpPzf156b+3NSfm/pzU39u6m+OZrjJXNeF67qwbRvlchlBEMBxnAXfzubNmwGg6sWEYuPj49i0aRMAwLZtHDhwYGkHLcsqm80m/YSP+nNTf27qz039uak/N/Xnpv7c1N8c3UOziQYGBnDllVdix44d+PKXv4xjx47hhhtugOd5C76t7du3w3EcFAqFGZ979tlnsWvXruU4ZGmCMAwxOTmJMAzTPhRJgfpzU39u6s9N/bmpPzf156b+3NTfHG1oNsnIyAiuuuoqrF+/Hp/61Kewdu1afPazn8UzzzyDD3/4wwiCYEG319bWhje96U34zne+U/XvzzzzDLq6uvC2t71tOQ9flpHrujh+/Dhc1037UCQF6s9N/bmpPzf156b+3NSfm/pzU39ztKHZJAcPHkQYhrj77rtxxhlnYO/evXjRi16Eu+66C0888QTuv//+Bd/mlVdeiR//+Mf4whe+gPHxcfziF7/ARz7yEbz1rW/Fvn37mvBTyHLI5XLYu3cvcrlc2ociKVB/burPTf25qT839eem/tzUn5v6m6Pn0GySv/mbv0Eul0ue2zI+mV/ykpfgn/7pn+q+Wvl8XvziF+Puu+/GHXfcgc9//vPYsGEDfv/3fx/XXXfdch66LDPbtrWYEVN/burPTf25qT839eem/tzUn5v6m6MNzSZpb29P3vc8D0NDQ9i8eTMcx8GLXvSiWb/ummuuwTXXXDPr58877zw88MADy3qs0ly1/YWL+nNTf27qz039uak/N/Xnpv7c1N8cPeTcAD0pLDf156b+3NSfm/pzU39u6s9N/bmpPzf1N0f30DQgn89j7969aR+GpET9uak/N/Xnpv7c1J+b+nNTf27qz039zdE9NEVERERERERERGTF0D00l8no6CgA4Omnn0ZfX1/V5/QcCtzUn5v6c1N/burPTf25qT839eem/tzUf+n6+/sBnNpnm402NJfJM888AwD47ne/m/KRiIiIiIiIiIiIrFzPPPMMXvrSl876eW1oLpNzzjkHR44cwZ/+6Z9i27ZtVZ9zXRcDAwPYunUrcrlcSkcoaVF/burPTf25qT839eem/tzUn5v6c1P/pevv78c///M/45xzzplznDY0l8nGjRsBANu2bUN7e3vV56IoQkdHB2zbhmVZaRyepEj9uak/N/Xnpv7c1J+b+nNTf27qz039l0+8zzYbbWgaYFkWMplM2ochKVF/burPTf25qT839eem/tzUn5v6c1N/c/Qq5wZ4nof+/n54npf2oUgK1J+b+nNTf27qz039uak/N/Xnpv7c1N8cbWgaEEURfN9HFEVpH4qkQP25qT839eem/tzUn5v6c1N/burPTf3N0UPODcjlcti5c2fahyEpUX9u6s9N/bmpPzf156b+3NSfm/pzU39zdA9NERERERERERERWTG0oWlAuVzG0aNHUS6X0z4USYH6c1N/burPTf25qT839eem/tzUn1sz+1uWNecbGz3k3IBsNovNmzcjm9V0M1J/burPTf25qT839eem/tzUn5v6c2tWf8uy0JZ3YNn1bzcKfZTKHtVzd+oKMyCTyWDjxo1pH4akRP25qT839eem/tzUn5v6c1N/burPrZn9LTsL/Og9wOjPqz+x8UWwXvcAAK5XVteGpgFhGKJUKqGtrQ22rUf5s1F/burPTf25qT839eem/tzUn5v6c2t6/9GfA8NPLf/trkC6ugzwPA+9vb3wPK7dcpmm/tzUn5v6c1N/burPTf25qT839eem/uboHpoG5HI57N69G5lMJu1DkRSoPzf156b+3NSfm/pzU39u6s9N/bmpvzna0DTAsiw9ITAx9eem/tzUn5v6c1N/burPTf25qT839TdHDzk3wPd9DAwMwPf9tA9FUqD+3NSfm/pzU39u6s9N/bmpPzf156b+5mhD04AwDOG6LsIwTPtQJAXqz039uak/N/Xnpv7c1J+b+nNTf27qb47uB2tALpfDmWeemfZhSErUn5v6c1N/burPTf25qT839eem/tzU32/8K2kAACAASURBVBzdQ1NERERERERERERWDG1oGlAul3Hs2DGUy+W0D2XFsyxrzrdWpP7c1J+b+nNTf27qz039uak/N/Xnpv7m6CHndUxMTOAzn/kMHnnkEfi+jw0bNuBP/uRPcNllly3q9jKZDDZu3IhMJrPMR8rFsiy05R1Ydv3TNgp9lMoeoigyfGRzU39u6s9N/bmpPzf156b+3NSfm/pzU39ztKFZx4c//GFMTk7i61//OjZt2oRf/vKXuPLKKxGGId773vcu+Pay2Sw2bdrUhCPlY9lZ4EfvAUZ/Xv2JjS+C9boHAHipHNdc1J+b+nNTf27qz039uak/N/Xnpv7c1N8cPeS8jscffxzvec97kpPwBS94Ad72trfhRz/60aJuLwxDlEolvcrVchn9OTD8VPVb7QZnC1F/burPTf25qT839eem/tzUn5v6c1N/c7ShWcc555yD//iP/0hOwImJCfz4xz/Gq1/96nm/1vNO3UPQdV34vg/P89DT04OJiYnkNn3fr3pOBdd1k6+NogjlcjkZGwRB1VjP82aMDYKgamz8sOvFjgVQNTYMwxljXdetGuv7ftXYyp+1cmw8Lwsd28hDyePjrZ3DRua7dl6WOt/xvJRKJfT09KBcLs87h7PNd+28mJjvemNr57CyzVznrMn5nmvsfHPYjPmemJhAT08PPM9b8nxrjWjeOdusNaJcLqOnpyc55qWes1ojVtYaEf/3f3Jy0sh8a41orTUi7j81NWXsnNUa0TprxOTkZPLf/1aZb60R5taIyv6tdM5qjTAz3/H6XyqVVtR8a41YnnN2sfs/jZyz84m/f705XGlrRCO0oVnHP/zDP2B8fBx/8Ad/gJtvvhmXX3459u/fj7/4i7+Y92tPnjyZvN/f34+RkRE4joMdO3ZgYGAgOTGLxSJOnDiRjB0YGMDIyAiA6ROtu7s7WQCLxSK6u7urvsfQ0BCA6ZO/u7sbU1NTAKb/41k5dnBwEIODg8nH3d3dyR9WU1NT6O7uTk7SoaGhquPv7u5GsVgEAJRKJXR3dycn+MjICAYGBpKxJ06cSMaWy+UZY/v7+6vGjo2NAZg+Ybu7u5OLbmxsDL29vcnYvr4+jI6OJvMyn/HxcQDTF0btHPb09CTjBgYGMDw8DGD6oqocOzExsaT5rp1Dz/PQ3t6eHFN88Q4PD1eN7enpmXW+h4eHZ8x3/LPGcxhf+KOjo+jr60vG9vb2JvPteV7D8x0fb7zAjI+Pzzhn4zmsd85WzvfJkycXNN9LOWcnJiaq5rByvivnsN58x3NYe8729vYuer4HBgawbds2OI6DsbGxqjmM14jKOdQasfg1ot45Wzm2cr5NrRHxcTuOk8z3Qs5ZrREre41wHAfr169Pzo/Z5jueQ60Rq2uNcBwH7e3tGB0dXdLvEVojVuYaMTIygvb2djiOs6TfI7RGTFtpa8To6CjWrl0Lx3Ga/reG1ojWWyMcx4FlWcn12My/NbRGTGulNaJy/2e5/9aYz+jo6KpZIxphRa32Ciot4H/+539w8OBBnH322XjZy16Ghx9+GLlcDh//+Mexffv2ul/T2dmJQ4cO4ZprrsHevXsBTIe1bRvZbDa5p4bjOLBtG77vIwgC5PP5ZKxlWXAcB1EUwXXdZGwQBPB9Pxlb+QdyPDabzSKTySRjc7kcLMta9FhgeiGIx8bHXzk2iiLkcrlkbCaTmfVnDcMwGTvfvMw2FgDWrl0L/Nsrpx9mXmnTK4C3PYlisQjbtmfMYSPzXTsvS53v2jmsN7Z2Dmeb79p5MTHfjZyz8dj5ztlWne/aOWz1+dYa0bxzVmuE1gitEVojtEa0znxrjdAaoTVCa4TWCK0RWiOq5zuXy2HNmjVz7oeMj48jDMMVv0b09vbiU5/6FA4cOIDdu3djNtrQrFEsFvHmN78ZH//4x/F7v/d7yb/fcsst+M1vfoP77ruv7tfFG5o33HAD2tvbqz7n+z5GR0excePGZGNOFs6yrHkv4KmpKbTaKa3+3NSfm/pzU39u6s9N/bmpPzf159as/it1P2Qxurq6GtrQ1EPOazz77LMYGRnB7/7u71b9+xve8Ab813/916JuMwxDTE5OJnftFS7qz039uak/N/Xnpv7c1J+b+nNTf27qb442NGvs27cPZ5xxBj796U8nzwPR3d2Nu+++G+eff/6ibjOXy2HXrl3J3WiFi/pzU39u6s9N/bmpPzf156b+3NSfm/qbo/s/11i3bh3uv/9+fOYzn8HFF1+MIAjQ1taGiy++GB/4wAfSPjwRERERERERERFq2tCs46yzzsIdd9yxbLfnui56e3uxY8cO7dITUn9u6s9N/bmpPzf156b+3NSfm/pzU39z9JBzA2zbxvr162Hbmm5G6s9N/bmpPzf156b+3NSfm/pzU39u6m+O7qFpQDabxebNm9M+DEmJ+nNTf27qz039uak/N/Xnpv7c1J+b+pujLWMDwjBEuVzWq1yRUn9u6s9N/bmpPzf156b+3NSfm/pzU39ztKFpgOd56O7uhud5aR+KpED9uak/N/Xnpv7c1J+b+nNTf27qz039zdGGpgGO4+DMM8+E4zhpH4qkQP25qT839eem/tzUn5v6c1N/burPTf3N0XNoGmDbNvL5fNqHISlRf27qz039uak/N/Xnpv7c1J+b+nNTf3N0D00DfN/H0NAQfN9P+1AkBerPTf25qT839eem/tzUn5v6c1N/bupvjjY0DQjDEMViUU8KS0r9uak/N/Xnpv7c1J+b+nNTf27qz039zdFDzg3I5XLYvXt32ochKVF/burPTf2nWZY15+ejKDJ0JGapPzf156b+3NSfm/pzU39ztKEpIiIiTWNZFtryDiy7/q8cUeijVPZW7aamiIiIiIgsPz3k3ADXdXH8+HG4rpv2oUgK1J+b+nNT/2mWnQV+9B7g315Z/faj98y60bkaqD839eem/tzUn5v6c1N/c1bvXxEtxLZtrF27Frat/WNG6s9N/bmpf4XRnwPDT6V9FEapPzf156b+3NSfm/pzU39ztKFpQDabxRlnnJH2YUhK1J+b+nNTf27qz039uak/N/Xnpv7c1N8cbRkbEIYhXNfVq1yRUn9u6s9N/bmpPzf156b+3NSfm/pzU39ztKFpgOd56Orqgud5aR+KpED9uak/N/Xnpv7c1J+b+nNTf27qz039zdGGpgGO42Dnzp1wHCftQ5EUqD839eem/tzUn5v6c1N/burPTf25qb85eg5NA2zbRltbW9qHISlRf27qz039uak/N/Xnpv7c1J+b+nNTf3N0D00DfN/H8PAwfN9P+1AkBerPTf25qT839eem/tzUn5v6c1N/bupvjjY0DQiCAKOjowiCIO1DkRSoPzf156b+3NSfm/pzU39u6s9N/bmpvzl6yLkB+Xwee/bsSfswJCXqz039uak/N/Xnpv7c1J+b+nNTf27qb47uoSkiIiIiIiIiIiIrhjY0DXBdF93d3XBdN+1DkRSoPzf156b+3NSfm/pzU39u6s9N/bmpvzna0DTAtm3kcjnYtqabkfpzU39u6s9N/bmpPzf156b+3NSfm/qbo+fQNCCbzWLr1q1pH4akRP25qT839eem/tzUn5v6c1N/burPTf3N0ZaxAVEUwfd9RFGU9qFICtR/ZbEsa863hVJ/burPTf25qT839eem/tzUn5v6m6MNTQNc10VnZ6eeQ4GU+q8clmWhLe9gzZo1dd/a8s6CNzXVn5v6c1N/burPTf25qT839eem/uboIecGOI6DHTt2wHGctA9FUqD+K4tlZ4EfvQcY/Xn1Jza+CNbrHgDgLej21J8bQ//F3HOZBUN/mZ36c1N/burPTf25qb852tA0wLZtrF27Nu3DkJSo/wo0+nNg+KlluSn157ba+8f3arbs+r9ORKGPsusbPqrWsdr7y9zUn5v6c1N/burPTf3N0YamAUEQoFgsYv369chkMmkfjhim/tzUnxtD//nv1cy7ocnQX2an/tzUn5v6c1N/bupvjjY0DfB9H0NDQ2hra9MJTUj9uak/N5r+y3iv5tWEpr/Upf7c1J+b+nNTf27qb442NA3I5/PYu3dv2ochKVF/burPTf25qT839eem/tzUn5v6c1N/c7ShKSIiIiIiItIC5nuxvSiKDB2JiEhrs9M+AAau66Knpweu66Z9KJIC9eem/tzUn5v6c1N/burPbbH94xfbW7NmTd23trwz74anpE/XPzf1N0f30DTAsixks1n9x4eU+nNTf27qz039uak/N/XntpT+87/Ynrc8BylNo+ufm/qbow3NWRw/fhx/93d/h2eeeQZRFOG8887DRz7yEWzbtm3Bt+U4zqK+TlYH9eem/tzUn5v6c1N/burPbcn99WJ7K5quf27qb44ecl7H2NgY/uzP/gwXXXQRHn/8cTz66KPIZrO47777FnV7URQhCAI93wkp9eem/tzUn5v6c1N/burPTf25qT839TdHG5p13HvvvTj77LPxrne9a/p5TNracNttt+GDH/zgom7PdV0UCgU9hwIp9eem/tzUn5v6c1N/burPTf25qT839TdHG5p1/Od//icuuOCCqn/LZDINfa3nnXpOE9d14fs+stkstm3bhiAIEIYhAMD3fZTL5aqx8ddGUYRyuZyMDYKgaqzneTPGBkFQNTb+vwGLHQugamwYhjPGVl6g5XIZvu9Xja38WSvHxvOy0LGN/B+O+Hhr57CR+a6dl6XOdzwvlmVh+/btsCxr3jmcbb5r58XEfNcbWzuHlW3mOmdNzvdcY+ebw0bUO7fmmsMgCLBt2zZks9klz7fWiOads81aIyzLwubNm5P/hiz1nG21NaLyZ1kK3/dXxBqx0PnOZrPYsmVLMp9Ac89vrRGttUZks1ls374dURQZO2dbbY1g+z2icr6jKML27duRzWZbZr61RphbI6IowpYtW5DNZhd0zjYiPobaOdQa0TprRDabxebNm5PnUFwp8601YnnO2cXu/yzHGlH5O3XtHK60NaIR2tCso1Ao4LTTTsONN96Iiy66CG9/+9vxuc99rqGJPXnyZPJ+f38/RkZGkMlkkM/n0dvbm5yYxWIRJ06cSMYODAxgZGQEwPSJ1t3djVKplIzt7u6u+h5DQ0MApk/+7u5uTE1NAQAmJyerxg4ODmJwcDD5uLu7G5OTkwCAqakpdHd3Jyfp0NBQ1fF3d3ejWCwCAEqlErq7u5MTfGRkBAMDA8nYEydOJGPL5fKMsf39/VVjx8bGAEyfsN3d3clFNzY2ht7e3mRsX18fRkdHk3mZz/j4OIDpC6N2Dnt6epJxAwMDGB4eBjB9UVWOnZiYWNJ8185hqVTCunXr4Hkeuru7k4t3eHi4amxPT8+s8z08PDxjvuOfNZ7D+PwcHR1FX19fMra3tzeZ7/gYGpnveA7jBWZ8fHzGORvPYb1ztnK+T548uaD5Xso5OzExUTWHlfNdOYf15ruRazyew0bnu7e3F9lsFplMBmNjY1VzGK8RlXOoNWLxa0S9c7ZybOV8m1ojyuUyhoaGkg3NemvEXOdsq68Rld2WYmRkZEWtEbXnbG9vb935zmQy8Dyv6hjqzXd8zmqNWF1rRCaTwbp16zA8PLyk3yNW8hrB+nvEyMgITp48iXXr1iGTycy6RjQ631ojVt4aMTg4iFKphEwms+DfI+YTH0M8h1ojWm+NyGQyGB4eTm53sb9HNDrfWiNaa42o3P9Z7r815jM6Orpqfo9ohBXpgf0znHvuudi1axc++tGP4tWvfjWOHj2K6667Dm94wxtw4MCBul/T2dmJQ4cO4ZprrsHevXsBTIe1bRuWZaFYLMJxHLS1tcG2bfi+jyAIkM/nk7GWZcFxHERRBNd14TgObNtGEAT4/9u78yA3qgN/4N+WWtLMeE57xh4jMDaHIUBlwRhz2Mbg4oiJOQPlijHEQIG9xaaAxRSHQyUkYSF4oWKObGANmBgnVeEwDhTHBijsBAM2EMhymsOLjcbjuTz3jKSW+vfH/NRIGkndkvrU+36qpsoe9bSe3rff69dPfSiKoi2bCj992dSESWrZYDAISZJKXhaAdnZBakccj8czllVVFcFgUFvW7/dDlmVt2VT5FUVBMpnUlk3VS7HLAkBNTQ3w0qzxN8luOg5Y9D4GBwfh8/nG1aGR+s6ul3LrO1UvkiRhdHQUVVVVWp3lq8N89Z1dL3bUd65ls+swtazeNmtnfRdaVm+braqqQnV1dcFtbHh4GNFo1HAdjo6OIh6Po7a2FqqqllXf7COs22at6iNisRgGBwdRX18PWZbL3mbd1kckk0nU19cXbDOp/q/QMgMDA0gmk67vI4qtb1VV0d/f/13fYvH2zT7CXX2ELMsYGhpCMBiE3++3ZZt1Wx8h2jgivb5TZ51MmDBB+4LD6fpmH2FfHzE6OoqRkRHU19fD5/MZ3mYlSdIdiw4MDGhflLKPcGcfkUgk0NfXh9raWgSDQc/UN/sIc7bZUud/9LbZYDBoqH9Ijam93Ee0t7fjt7/9LW655RZMmzYN+XBCM4ezzz4bS5cuxU9+8hPtdy+++CJ++ctf4u233875N6kJzeuvvx4HHnhgxmupbwjC4bC2UVLxjOzgR0ZGDH2zaSfm7x1WbGPMX2yVnr+RNmNkQtONfbcZKj1/Koz5i435i63U/L16vEOZ2P7FZlX+IvUP3377raEJTdnGMnnG7NmzM67jT0nNGhcrFArhkEMOKbdY5FHMX2zMX2zMX2zMX2zMX2zMX2zMX2zMX2zM3z68h2YO11xzDf7whz9g+/btAMbuO/DQQw/hRz/6kcMlIyIiIiIiIiIiElvFTGj29/fj008/1W5yOzQ0ZOghMrkcfPDBuPfee7FmzRqcfPLJ+MlPfoJzzjkH1157bUnri8fj2Lt3r+EnU1FlYf5iY/5iY/5iY/5iY/5iY/5iY/5iY/5iY/728fwl58lkEk8//TS2bt0KVVXxs5/9DFOnTsVTTz2F9vZ2XH/99WP37irSnDlz8NRTT5lWTkmSTFsXeQ/zFxvzFxvzFxvzFxvzFxvzFxvzFxvzFxvzt4fnz9DcsmULduzYgSuvvDJjo1m6dCkCgQA2b97sYOnGBAIBtLa2ak+aIrEwf7Exf7Exf7Exf7Exf7Exf7Exf7Exf7Exf/t4fkLz73//Oy688ELMmjUr4/fBYBDnnHMOPvjgA4dK9h1VVbUfEg/zFxvzFxvzFxvzFxvzFxvzFxvzFxvzFxvzt4/nJzS7urpw0EEH5XwtEAhgeHjY5hKNF4vFsGvXrpxPTqfKx/zFxvzFxvzFxvzFxvzFxvzFxvzFxvzFxvzt4/kJzaamJuzZsyfna9u2bcPkyZNtLtF4siyjpaUFsuz5W5ZSCZi/2Ji/2Ji/2Ji/2Ji/2Ji/2Ji/2Ji/2Ji/fTxfwwsWLMBf/vIXTJo0CZIkIRqNYs+ePXj11Vfx7rvv4sc//rHTRYTf70ddXZ3TxSCHMH+xMX+xMX+xMX+xMX+xMX+xMX+xMX+xMX/7eH5C8/TTT0d/fz8eeOABqKqKNWvWABh7qtSZZ56JefPmOVxCIJFIYGRkBNXV1fD7/U4Xh2zG/MXG/MXG/MXG/MXG/MXG/MXG/MXG/MXG/O3j+QlNADj//PMxb948fPbZZxgYGMCECRPwve99D83NzU4XDQCgKAo6OjoQDoe5QQuI+YuN+YuN+YuN+YuN+YuN+YuN+YuN+YuN+dunIiY0AWDSpEmYO3eu08XIKRgMYvr06ZAkyemiWEbvs4n8hC8R8qf8mL/YmL/YmL/YmL/YmL/YmL/YmL/YmL99KmJCU1EUfPXVV+jv70cikRj3+kknneRAqb4jSVJFb8ySJKEqFIDky705qUkFo9G4sJOalZ4/Fcb8xcb8xcb8xcb8xcb8xcb8xcb8xcb87eP5Cc2vvvoK69atQ39/f95lnJ7QjMfj6OnpwcSJExEIBBwti1UknwxsuxTo+zTzhYbvQTplI4C4I+VyAxHyp/yYv9iYv9iYv9iYv9iYv9iYv9iYv9iYv308P6H5pz/9CS0tLbjiiiswceJE186EJ5NJp4tgvb5Pgf3/cLoUriRE/pQX8xcb8xcb8xcb8xcb8xcb8xcb8xcb87eH5yc0Ozs7ccMNN2D69OlOFyWvQCCAqVOnOl0McgjzFxvzFxvzFxvzFxvzFxvzFxvzFxvzFxvzt4/P6QKUa8aMGfjqq6+cLoZjUvdnyPdDRERERERERERUSTx/huZll12GRx55BH19fTj66KPh842foz388MMdKNl3otEoIpEIwuEwQqGQaevlw3i8war8yRuYv9iYv9iYv9iYv9iYv9iYv9iYv9iYv308P6E5MjKCRCKB1157Da+99lrOZR566CGbS5VJlmU0NzdDls2vbj6Mx/2szJ/cj/mLjfmLjfmLjfmLjfmLjfmLjfmLjfnbx/M1vGHDBvh8Plx++eVobGx05WXWfr8f9fX11r0BH8bjapbnT67G/MXG/MXG/MXG/MXG/MXG/MXG/MXG/O3j+QnNffv24brrrsOMGTOcLkpeiUQCo6OjqKqqgt/vd7o4ZDPmLzbmLzbmLzbmLzbmLzbmLzbmLzbmLzbmb5+KeCjQrl27nC5GQYqiYN++fVAUxemilIwPHypdJeRPpWP+YmP+YmP+YmP+YmP+YmP+YmP+YmP+9vH8GZqLFi3CH//4R+zfvx9HH310zhlwpx8KFAwGcfDBB+d8YJEXGHn4EOXn9vz1JqT5UKnyuD1/shbzFxvzFxvzFxvz9x4zx8TMX2zMX2zM3z6en9Bcu3YtAOD111/H66+/nnMZpx8KJEmS50811n/4EOXj5vyNTFaPRuOc1CyDm/Mn6zF/sTF/sTF/sTF/bzF7TMz8xcb83cXuE3iYv308P6F53XXXOV0EXfF4HPv370dTUxMCgYDTxSkdHz5UErfnrz9ZHXekXJXC7fmTtZi/2Ji/2Ji/2Ji/95g5Jmb+YmP+7uHECTzM3z6en9CcOXOm00XQpaoq4nGe5SYqT+TPyWrLeCJ/G4h6awPmLzbmLzbmLzbm71EmjYmZv9iYv7vYfQIP87eP5yc0vSAYDCIcDjtdDHII8xcb8xf71gbMX2zMX2zMX2zMX2zMX2zM34VsPIGH+dvH8xOav/3tb3WXuf76620oSfFEPWOJiMTDWxsQERERERGRWTz/2CVVVcf9jIyM4IsvvsDAwADq6+udLiKi0Sh27dqFaDSq/S51xlJ1dXXOn6pQQHfCk7whV/4kDuafJvXNaPpP9gRnhWH+YmP+YmP+YmP+YmP+YmP+YmP+9vH8GZo33HBDzt/v3LkTGzZswOmnn25zicbz+/1oamoa96QrnrEkhnz5kxiYv9iYv9iYv9iYv9iYv9iYv9iYv9iYv308P6GZz8yZM3HuuefimWeewapVqxwtiyzLaGxszP0iH8ZS8QrmTxWP+YuN+YuN+YuN+YuN+YuN+YuN+YuN+dvH85ecFzJlyhTs2bPH6WIgmUxieHgYyWTS6aKQA5i/2Ji/2Ji/2Ji/2Ji/2Ji/2ETIX5Kkgj8iEyF/yo/526diJzR7enrw8ssvo6mpyemiIB6Po729HfE4LyG3mht3rMxfbMxfbMxfbMxfbMxfbMxfbJWeP58HUVil50+FMX/7eP6S82uvvTbva7Is46qrrrKxNLkFg0EcdNBBkGV3Vncl7WxCQXns3qQ5qEkFo9G4KU+PL+YJ9W7Pn6zF/MXG/MXG/MXG/MXG/MUmQv58HkR+IuRP+TF/+3i+hhctWjRucsnn86G+vh7HHHMMGhoaHCrZdyRJQiAQcLoYOaW+XSs0CRiNKTaXqnR27FiN1Fn6xKmb8yfrMX+xMX+xMX+xMX+xMX+xCZM/nweRkzD5U07M3z6en9BcvHix00XQpSgKent70djYWPQsvR1nT+pPAtozoWnaZ7Vhx1rMxGk5+ZP3MX+xMX+xMX/vKTQWKfYKD+YvNuYvNuYvNuYvNuZvH9auDZLJJEZHR4u+KawkSXkvoTb9zEmHv13z5JmiBuus1PypMjB/sTF/sTF/byk0FinltjXMX2zMX2zMX2zMX2zM3z6em9DcsGFD0X9z2WWXWVAS44LBIA488MCS/jbnmYA2nzlpF7ecKWq2cvIn72P+YmP+YmP+3lN43FXcbWuYv9iYv9iYv9iYv9jy5V/MczjIGM9NaH7++ee2PcSmvb0d5513HhYuXIi7777blvfMSaR7k4j0WYmIiMh9OBYhAsCDbyIisxT7HA4yxnMTmr/+9a9teR9VVXHzzTdjypQpZa8rGo2ivb0dra2tCIVCJpSOvIT5i435i435i435i435i83r+fPguzxez5/Kw/zFli9/Ox5gLBrPTWja5bHHHoMsyzjrrLMQiUTKWpff70d9fT38fr9JpSMvqYT8+Q196Sohfyod8xcb8xcb8xdbJeTPg+/SVUT+Bcb/dl0x6VWVkD+VrmD+vArEVD6nC2CW999/H3/4wx/w4IMP4vHHH8eOHTtKnmT57LPP8Mgjj+AXv/hF0X8bj3+3Y4/FYlAUBbIso6GhAYlEQrsxbCKR0F2XGZNEiqJoZVJVFdFoVHvvRCKRUV4rKcp3979M1QswdsPcaDRq6LOaOWkWi8UK1ks0GtWWjcfjGcsWU2fRaBSSJKGpqQmSJGV81ng8jlgslrFsqgzZ9aIoyrhls+swtW1lL5urvovZDgGgKhRAdXV1zp+qUEArU/p60+uwnPrOtWx6HabnobesXh0akSqT0fpOJBJoaGiALMtFZaMoim4d5qvvUuuwnPrO3maz61uPXh9Ryvadqw5Ty+bK0YptVpIk1NTUaAOacrdZu/sIvWXN2ofo7avc0kcUW9+yLKOuri7jpvBWbt9e7iPs2mYL1WF6P5RL9hhPr15kWUZTU1PG2MHqbdZtfUSpfbJXxxHp9Z1MJtHU1ARZll1T38X0EVp7IBRX6QAAIABJREFUSB18p/+kTXBWUh+hR1EUw+OIZDKJ2tpayLJc1DZrtBwpVvURsVis4Pg/FDR2XpSofYQsy6ipqdH+zit9cqWOI/TE43FT92uyLKOxsbHo+R8j9a0nfUwNeHscYYTnJzQVRcGDDz6IRx99FJ988gmGh4fx+eefY/369XjggQeKqgxgLJhVq1Zh1apVOOigg4ouT1dXl/bvjo4O9Pb2IplMYnh4GJFIRNswR0ZGdNdlxoFiX18furu7tf9HIhEMDw9rZejo6Cj7PYzo6enR/r1371709/cDGNtgI5GIoZzMfEpYZ2cn9u/fr603EolgdHQUADA0NJRxVm5XV5dWflVVi6qzSCSCwcFBjI6OattA6nPs378/Y3tpa2vD4OAgAGB0dBSRSETrUPbv34/Ozk5t2b1792JgYADA+Drs6+vDvn37tGXb29u1+o7H44hEItq2NTQ0pPsZFEX57hv6l2Zl/my7FJJPHleHg4ODaGtry6jDYuq70DYbiUS0jrWnpyejDiORiPaZUnWYXt/pdZirvo1sh6k6LKa+BwcHkUwm0d/fj71792rLpvoIYGwHk95HDA4OZizb2dk5btn0+i60zUYiEa3PSW2HKd3d3WXVd75ttre3N6O+9ej1Ealttr+/H+3t7dqy+/btQ19fH4CxbTUSiWg7xYGBgYxl0+s7tWy+bbacPiK9vlPLprbD7u7uorZZp/sIvfo2ax/S29vrqT6it7c347O3t7fnrO9kMonu7u6MOsxV36ltVuQ+Yu/evdqy0Wh03LLp9W1VH5HeD+WSXl4jfUTqKaednZ1F1Xcl9RHZ9Z29zabqMNc26+VxRGqbTT3lNl8fYbS+negjUmXQU0l9hJ6enp6ixhFdXV1IJpNFjyP0pMoAWNdH9PT06I7/jRC1j0gmk2hra9PafanjCMC9fYSXxhF6Ojo6TD3WSCaT2naXqkMj8z+p9RbqI/T09fVVzDjCCM9fcv7SSy/hm2++wTXXXIN/+Zd/0X7/z3/+Exs2bMCLL76I8847z/D61qxZg4MOOgiXXHJJSeVpbm7W/j158mT4fD7E43F0dHSgpaVFu4dCdXW17roCgUBJZUjX0NCQMREYDochy7JWhqqqqrLfw4iJEydq/546dSp8vrG59GAwmFGmQlJ/Y4aWlhbtUgmfz5dRhgkTJmTc6yI9U0mSMHnyZMPvEw6HkUgk0NbWhqlTpyIcDmufI3XWRsoBBxyglaGqqgrhcFg7q6upqSkjx6lTp2qvZddhQ0MD6urqtGVbW1u19wwEAgiHw9q2NWHCBN3PoGVT4PR4v9+fsd7a2tqMbau5ubmk+gbGb7PhcFhbV/p2lb1sqg4L1XeqDlPLGtkOU3VotL5bWlrQ2dmJUCiE+vp61NbWasum+oh8dZjeT6Rvs0bqO0WSpIzy1tTUIBwOa69PmjQpbx2WUt+pOm1sbCzqrGq9PiL1WbPrcMqUKdqysixnLFtXV5fx7Xh6fWcvW6i+i+0j0pdNrT8ej8Pv9xesbyPbrN19hF59F9MfFtLY2KiV3wt9RHp5gbE6zFXf8XgcQ0NDGfVUTH2L1Eekb7OhUGjcstnbtxV9RHb5s7W0tGT8W6+PiMfjaGtrw5QpUxAMBgGUV99e7CMK1XdLS0vB7dvL44jGxkaMjo6ira0N4XA4bx9Rbn1b2UcYHXdXUh+hZ+LEiVqZ9MYRDQ0N2iRJduZ64wg9jY2N2r+t6iO0MpV5eayofUQ8PnZ/2dT7ljqOANzbR6R4YRyhJ72ezDjWSJ//SdWbkfmf1FhBb5stpND8j5fGEUYmgIEKmNDcvn07zj///IzJTAD4/ve/j/PPPx8vv/yy4QnNv//973jxxRfx/PPPl1ye9EnI1Abp8/lw4IEHQpbljA5Fjxn3JkmfoJEkKaMjMjJ5Y5bU5RbAd/UCjNVNKBQy9FnNvFdLehkkScroMPx+f0Y+6ZlKklTURHMoFEIymRyXf/Z6U8umpOolJTurYpbNVd8pZm6HheqwnPo2uqxeGYqp70Kyy6RX36kdUnb+uZbNXm/6uu2ow3LqO7v8xX4ho9dHpC+Xzqw6tKq+Q6GQ1v6zl029bmS92cva1UfoLWvWvaHS8/dCH2G0vgOBQEb+gDPbtxf6CLu22UJ1qDcuCgQCOfupfPWSa//v9m0217Ju2Ga9No5IXW6aa/znhfoOBAKGx3+V1EfoKbSvyq7v9PyLrZdiymFVH2HGiTW51itKH5G9/6+0Ptlr4wg96ft3M+qw1Pkfn88HVVXL6iPS+wfA2+MIIzw/odnX14dp06blfG3atGmGL5cAgC1btqC7uxunnHLKuNc2bdqExx9/POdrenw+X9HBmEWSJISCcs7LAtSkgmisuEvyqXhO5k/OY/5iY/5iY/5iY/5iY/5iY/5iY/5iY/728fyE5sSJE/HFF1/knNT88ssvdS8fSrd69WqsXr0643cPPPAAIpEI7r777pLLqCgK+vr6tAeD2C3nEwq1pxNyQtNqTudPzmL+YmP+YmP+YmP+YmP+Ykqd2ZpIJDA4OIja2tqMM6LMfMgpuRfbv9iYv308X7tz587FCy+8AFmWccoppyAQCEBRFGzbtg3PP/88fvCDHzhdRO2hQOn3EbBdmfc/odK5In9yDPMXG/O3j97lkU4cRDJ/sTF/sTF/8UiShKpQQLsyLv2+cMDY1XGj0TgnNQXA9i825m8fz09onnHGGWhvb8ef//xnPPXUU6itrcXg4CBUVcUJJ5yAs846q6z1//SnPy27jMFgsKQnplNlYP5iY/5iY/72yD6IzObUQSTzFxvzFxvzF1POK+OAtKvj4o6Ui+zF9i825m8fT05obtu2DbNnz0YwGIQkSbjsssswb948/POf/9RO7T/66KNx2GGHOV1UIiKyiRvP0CP78CCSiIhcgVfGERHZwpMTmhs3bsQzzzyDOXPmYN68eQiHw5gxYwZmzJjhdNFyisViaG9vR2trK28OKyDmLzbmb0y5k5FuPUMvX/6cfLWIyw4i2f7FJkL+7MvyEyF/IsqN7d9ehfZFevspKzB/+3hyQnPVqlV46623sGPHDmzduhXTp0/H/Pnzcfzxxxf1SHu7+Hw+1NbWwufzOV0UcgDzFxvzNyYUlMuejHTjGXq58nfr5CuZj+1fbJWev9G+TE+l9nWVnj8R5cf2bx8j+yK7MX/7eHJCM3U25iWXXIIPP/wQb7/9Np588kk8/fTTOPHEEzFv3jxMnTrV6WJqZFku6mnrZC27zyZg/mJj/saYNhnpsjP08uXvxslXMh/bv9hEyF+vL5MkxZQvrLxIhPyJKDe2f3vpj6vtxfzt48kJzZRAIIDZs2dj9uzZ6O3txTvvvIPt27fjjTfewCGHHIL58+dj1qxZkGVnP2YymUQ8HkcgEOAsvcMkSbJ9YM38xcb8i+CyyUgzFMy/Aj8vZWL7F5sw+ev0ZaJ+gSNM/kQ0Dtu/A1w0rnY6f5FuB+PpCc10jY2NOPvss3H22Wejra0Nr7zyCp544gk8/fTTuOeeexwtWzweRyQSQTgcRigUcrQsZP/AmvmLjfmLjfmLjfmLjfmncdGBpl2YP5G42P7F5mT+TpzA5aSKmdAEgIGBAezYsQPbt2/Hnj170NjYiJNPPtnpYiEQCOCAAw5w5f09hWXjwJr5i435i435i435i435i435E4mL7V9sTudv5ASuQmdxemmy0/MTmslkEh999BHeeustfPzxx1BVFccccwwWL16Mo446yhWnePt8PlRVVTldDHII8xcb8xcb8xcb8xcb8xcb8ycSF9u/2FyRf4ETuAqdxem1Mzg9O6HZ1tamPel8YGAALS0tWLx4MU466STU19c7XbwMiqKgv78f9fX1jt/Pk+zH/MXG/MXG/MXG/MXG/CtPMfclY/7uopcdkZnY/o2rlDMF03kh/5xncXrw3tburF0dv/nNb7B7927Isoxjjz0Wc+fOxcyZM50uVl7JZBIDAwOora11uihkgNkDHuYvNuYvNuYvNuY/ptz9qlcPaJh/ZZEkCVWhgOH7kjF/9zCSXTSm2FwqqmRs/8YUapteO1MQ+G68I0kS4vGxy7rTf+c6FXB/a09OaCqKgosvvhgnnngiampqnC6OrmAwiIMPPtjpYpBBejfRLXbAw/zt48YnujF/sTF/sTF/YxMJACry5vXMv/IU82BJ5u8u+tlxQpPMw/ZvXKWcKZg93qmrq8t4PTXeIXN5ckJz9erVTheBKlilDXhc+W2QBYo9c4KIiOyhv1+F4Ukip7nxizOyWQWc0eI2tl1yyuyI3KlC2qah8Q6ZypMTml4Ti8XQ0dGByZMnIxgMOl0cMsLETtXJ/PVO46+0y2uKOXPCLmz/YmP+YmP+afT2qzqvu2EisdBN9IHxX5wxf7Exf2Mq7ZJTIoDtX2gVMjnrFZzQtEHqKVdueOI62c/p/Aufxu+eCU3TDlZdthNxOn9yFvMXG/M3R7ETiZaWpYgvzpi/2Ji/cZVyyambuOFLIJGx/RPZgxOaNpBlGc3NzU4XgxziivxdNsmXrZIvF3dF/uQY5i825m8eV52Bb3CfyvzFVk7+Qk5GuXys6iWVPK72Cvb/RPbghKYNkskkEokE/H4/v6UREPM3xlUHqyZyOv9KOigq9Fnceq9Y5m8eu/I3815uTudfcTw24cH8xVZq/pyMIj1G9nmVOq72Cvb/RPbghKYN4vE4IpEIwuEwQqGQ08VxjBcnI8zA/IvgsYNVI5zMv5IOioxccupG5eRf7sSal/I3sg8w8qRsM8ph5r3c2P/by7YHixjE/MVWVv/PySgqQG88pN0jvwLH1V7B/p/IHpzQtEEgEMDUqVMRCAScLopjvDoZYQbmLzan86+kgyIvPjmw1PwL9ZnFTKx5JX8jB2d25W/mvdycbv8iMavNmIn5i63s/DkZRXno7w8r97jKK9j/kwjc8EUyJzRt4PP5UF1d7XQxHOfFyQgzMH+xuSL/SjooKvOz2H0Jdjn5mzaxVqDO3HJJuuGDM7u2ZZPexxXtXyBuebBIql35/X7U1NRkvOaGM6LJHmz/ZKlKGttVILZ/qnRmX9VUKk5o2kBRFAwODqK2thayLHiVC7jzzZe/WyYSvMSLty1g+3cPJ56UXHb+FveZbnlyNICK3D+w/TvA4e3IjWeKkjPY/onExfZPInDDF8lsXTZIJBLo7e1FdXU1OzQB5crfS/e2cwuv3ragEtp/JU2+230Jttvz98ol6V7l9vzJGm4Y4JPz2P6JxMX2T8Jw+Itkti4bhEIhTJ8+3elikM1Sk0BVVVWYMWPG+Nc5kVA0L962wOvtvyIn323c8Xoi/wo8M9Itysm/kr5IEJIH2hW3MWt5ov8nIkuw/VOpvHhFopM4oUlkAb1Lzsx6+qCQnZoHDhLtYlf+nHwnsldFfpFAriLiNsYJ3ExCjiGJiFzMq1ckOokTmjaIxWLo7OxES0sLgsGg08UhmxS+5Kz8zsjIwYg2cUqOsar9255/GQ+WqTRGDopTyyiKgv3796OpqYmXHAmonPav90WCJBVu36JNzniJWybWRPqyyokJXDeP/zmGJLKWle3fLfsQsoYXr0h0Eo+ubCBJEoLBoHAH/QTLzyY0/GRgcoyV7d8t+et9k1hJB0VGDwLT66Surm7c6ySGstt/gX2Iqx7oRIY58XCygnTGKZV06ZvdE7huH/+7ZQxBpMeLE3hWtX8Rz64XEq9INIwTmjYIBAJoaWlxuhjkQYZ2guzwXM3y9u+C/EU7KDLyea0+Q5u8wcr2L9LZdZXGSHZuOICvyEvfbNxn5mv/rprgdMEYgqgQr07gcf9PZA9OaNpAVVUkEgn4/X53DWLI1Qzfh5NcTZj2L9pBkZHPK1qd0DiWt39uY96lcxsPt5zFyUvfSper/fNSb3ILL41JvTiBx/0/kT04oWmDWCyGSCSCcDiMUCjkdHHIQ3iWl/ex/ROJK1/799KBJDnDVQfwPHAuSd72L9hVDeROnrtdkMf6IY7/iezBCU0bBAIBtLa2IhAIOF0U8iKP7cDdzu77gbH9E4krV/vnGVpkGPf/npQaS4RCIW0yI/0MTQC2ZFtJ9z8l83Fi3Voc/xPZgxOaNvD5fKipqXG6GETCc+J+YGz/ROLK1/55IEl24ISW/bLHGdnt3677jhr54oSIX5pYh+N/IntwQtMGiUQCg4ODqK2thd/vd7o4REKz+35gbP/kdZwUKV3B9s8DSbIQJ7Sc45b7jrqlHEQicnr874YHy1UajnndiROaNlAUBd3d3aiqquKEBlUkz+00bZxIYPsnL6vIpxzbSIT276UBvpfKagavTGh5bgxhhFu+sHBLOSqEGX2IaP2QqJzc/7vpwXKVgrcLci9OaNogFArhkEMOcboYRJYRbadZzMFXOe2fg15yA69MirhRpe//vTTAN3KA55aymsoDE1qijSHMwPGBM8zoQ4TshwTk9P7fVQ+WqxC8XZA7cUKTiMom0k7Trm89C00UcMBLgM0HtB6YFCFr6N1ywEsDfC+VVU8lTWgZGUNU5FmcZeCkmDPM6EMqqR8il+PYzXysU9fhhGYeTz31FNavX4/+/n7U1tZi+fLlWLJkSUnrisfj6OrqQnNzM590RpVLoA6+mAncctp/zvfhgJcg8NlmLmBkYiW1jKIo6O3tRWNjI2TZe0Muw/dh9FL/76WyFlBx7b9ALrx8cjxOijnIjD6kQvohyo/H/0T28N7o2gbPPfccHnzwQaxbtw6HH344vvrqK1x++eWYMGECFi9eXNI6fT6fyaUkIkcVMRjN1f4Nn13DQa/tvHLmEw9o7Wd0Ijl9mbq6unGvewlvOeBOorV/ka4EMYzjgwxe2XeTOHj8T2Q9Tmjm8OGHH+Kmm27C4YcfDgA49NBDce655+Lll18uaUIzEAhgypQpZheTiDwgV/v30n3nRFNowsqVufCA1nZGJpIq7uxqbmfuJFouNnxeTop5E2/TQ27D43/zsF+mQjihmcPPf/7zcb/buXMnJk+erPu38fh33xDHYjH4fD74/X4kEgkoioJgMAifz4dEIqG7LjMundF7H0WxZwdv5PPqcculRHbVmd77JJPJst/DyDrMqHdFUZBMJhEIBKCqKmKxGGRZ1tqGqqqorq4u+3302LUdJhIJ+Hw+JJPJcZ81mUwiFArpTookk7GC72HWduiWbPTY0R+mlDsZpZeNXduhXX2EHcza3qPRaMb2ndovS5KEeDxu/GyKAhMrWjZ5ljEjfyNSnyc15lAUBaFQSHsNQN52n14v5TKj7dq1r+KYyXx21Vk8Htdu65Br+w4Gg7rr0PtCa2h41NxC52FXH6HHSDkkSdIyTq9/v98Pn88HRVHG9bMAtEtwo9GooWxSy/r9fsiyjGQyiXg8jkAgoPVxkq86775bUezJzq7t3Q5mjzNTOaeOj3PlqCgKEomEtq9K7ZuMiMVikCSp4H6tlH1grm220LKqqiIYDEJVVYyOjiIQCGR81tSy2fVSaPvOXlaP0babOi5Jfbb0tpw6hklvY2bUYfayevt3RVFQO6Ha8pNA0sdMubZZu24bZOfxjh69bTYejxc8RlQURas3RVEgSRL8fj9UVYWiKPD7/TnXm+ojjOJ50Dri8Th+9atf4R//+AeuvPJK3eW7urq0f3d0dKC3txexWAy7d+9GW1sbotEoAGBkZMTQe5drcHCw4Ov79+8v+z2M6O/vL3sdbjmwtqvO9N5ndLT8wZmR7dCMAU1vb6/2eZLJJCKRiFb+oaEhdHR0lP0eRpixHRqpj6GhIQBjbbitrQ27d+9GLBZDf38/9u7d+92CqQmP9J//PxBP9RX5mLUd9vX1obu7W/t/JBLB8PAwgLHtw65s9Jixcy4q/+xssieeC9DLZmBgwHg58jCyf7Crj7CDWdt7JBLR2ufo6CgikYi2b9m/f7/u+xjZDvX6iN7eXoOlLU9HR4e2DQwODiISiWivdXV1oaenB8DY4DkSiWhZDw8PZyxbLjO2w1RmhdjRR5ixHRo5WLGrj7CDXWOm9H1VV1fXuP2a0e1Q+0LrpVnf/Wy7FJJPNtQfmrEd2tVH6DHS7kJBGXV1dairq0N1dTWqq6tRX1+PCRMmoCoUQDQaRSQS0bb7np6ejGOl9DGHnr1792rHNan1pupbazN59t1uGbsbYcaEhhnrMGs77O/vR3t7u/b/ffv2oa+vD8DY/jISiSAWG/sSf2BgIGOc3NnZabg/7OrqKniskb0PLDT21dtmC40jOjs7AYxNyuzdu1erx9SyqTFCb29vRr/V3t6ufdZYLJaxbF9fH/bt22eoHlLr1hMKyqitrUV9fb3WdlNtuSoUGFeH+cYRkiRBkiR0d3cjHh97gFssFtM+myRJGBgYwMDAACRJgs/nQ3d3tzYBrXe809vbm7tfTuubzdDR0aHtN3Nts3pzKmaxY/4HMNZHpLbZVD+bvn0DmfNeufT29qIqFNC2rdraWlRXV6Ompgb19fWoqQ5BkqSCfYQRPEOzgLa2Nlx//fUYHBzEn/70J8ycOVP3b5qbm7V/T548GT6fD5IkoaWlBX6/X/tWw8gZT2bcQLi2trbg601NTWW/hxH19fVlr8Mt9yGxq8703qeqqqrs9zCyHZrxjVRjY6P2oAxZljFt2jTtW5m6ujpMmDCh7Pcwwozt0Eh9pD5PIBBAa2srEokEZFlGfX29bptMSfUV+Zi1HTY0NGR8WRAOh7XPWF1dbcp2Zga/31/2OszI3wi9bNLvqVgqI/sHu/oIO5i1vadv31VVVQiHw9q+pampSXc/Y2Q71OsjGhsbDZa2PKkxCDA2FkjfHtLHKpIkZdRLTU0NwuGwaeUwYzs0so+wo48wYzs0ctarXX2EHewaM6VfRZW+fQNj7d7omU0A8p5dXVNTo/unZmyHdvUReoy0O72rTaqrqxEOh7XtfuLEiRmLFZPN1KlTtfoNhUIIh8Pa//XajFvG7kaYcWa8GeswazvMHvtOmTJF2zfJsoxwOKz1V3V1dRntrKWlxfBxSHNzs/a5fT5fxn5twoQJGePqXH1E+thXb5stNI5ITRTJsoympiatHaWWTf1tY2Njxvi7tbVV256DwWDGsg0NDUXtF4xkp9d2s7PJNY5Iv9XDYYcdpr1WXV2NiU0NGI3GURUK4MADD8x4i9SyalLRnVjT2pTFtxxJHzPl2mbtOkPTjvkfwFgfUV1djWnTpmllmjRpUsaDL7PbUbaJEycauv91vj7C6EkVnNDM46OPPsI111yD888/HzfccIPhnW0qcEmSMjrO7EGykQGPGTsjvfexq3GaMcBzy/0z7KozvfcxY4LXyDrMqPdAIJBxGVf2JIn2pFyL2bUdpk6n9/l8hg6ActHLxqztUJZlbTCR3W+lJp3dwI7+0Cx62di1HdrVR9jBrO09fTAuy3LGeoua8ChALxu7tsPUpV2p90x/3/QBc652b2YZzWi7du2rOGYynxMHgeltWZIk076Ys6vt2vU+egyXo8BEg8/ny+hfsg/WQ6GQoW01O8fsfsotbdeu97GDmePMdOntM3v7yLVfNtqXZbf7Qvu1YvaB2csWGkekL+v3+zMmuHN91nTpr+ktq8eMtgsYGzMVuk2TJOW5p3jaMj5f4WNAO/ch6ZPR6cy6BY8RbjnekSRp7AzKApf6Gx7v6mxnhfoIIyqn1zVRW1sbrrnmGtx+++1YtGhR0X/PB34QjSfqk3ITiQSGh4dRU1PjmoOUdG456CWymtEnlBOR93jugW5kGPtub9MbZ9p1v99yy2Hk+H40GtfW4/bxv56i2p3e2ZOiPcCuQhh5CKYbcEIzh5///OdYunRpSZOZKV7ZAIhsJeAOTVEUdHZ2Zlwa5SY8SCCRcN+ciV9oUCUp94FuZA1TLqFm3+1JRibF0icBrSxHMZOReddj4PLZlHLG/4XajJ37bbY78sKxOyc0c9i6dSs+/vhj/PnPf875mmEe2ACIyFrBYBAzZsxwuhh5cbBCwuG+GQCvJqEKxfbtKqaeXclsPcnIJKAdk3TllkN7zeB2WOr438i+2VZsd+RynNDM4fPPP3e6CERUITxxBhQHK0RC4hcaRGQ19jNUaJxp6+0iSixHqizFKGf8L+ptuohKwQlNIiILpAYyiqKgr68PDQ0NFXWzeCKqEPxCg4isxn6GCnDL7SLMnEiMx+Po7u7GpEmTSntyNdsMkSE8uiYiMln2t7x1dXXaa7yMk4iIiIgojVsm8NxSDiIyhBOaREQWcMu3zUREREREZJ9AIIDW1lani0FFcMvDmKg4nNAkIrIKv+UlIiIiIhJK+hPTORnmfmbfQ5XswwlNIiIiIiIiIvIkt00axmIxRCIRhMNhhEIhp4tDBvBhTN7ECU0iIiKiCsTLp4iIqNLZ+qR0g2RZRktLCx8I6jW8us5z2MKIiIiIKgwvnyIiIlG47d71fr8/46GgRGQNTmgSERERVSBePkVERMJw0dl1iUQCIyMjqK6uht/vd7o4RBWLE5pERERElcpFB3hEREQiUBQFHR0dCIfDnNAkshAnNImIiIiIiIiITBAMBjF9+nTer5rIYpzQJCIiIiIiIiIygSRJnMwksoHP6QIQEREREREREXlZaiIzkUhg//79SCQS2u+M/BBRcXiGJhERERERERFRiSRJQigojz2QDxj3lHM1Ofa09dTr2dSkgmjM/ieyE3kZJzSJiIiIiIiIiMog+WRg26VjD+RL1/A9SKdsHPt3wdc5oUlUDE5oEhERERERERGVq+9TYP8/Sn+diAzjPTSJiIiIiIiIiIjIMzihSURERERERERERJ7BCU0iIiIiIiIiIiLyDE5oEhERERERERERkWdwQpOIiIiIiIiIiIg8gxOaRERERERERERE5Bmc0CQiIiIiIiIiIiLP4IQmEREREREREREReQYnNImIiIiIiIiIiMgzOKFJREREREREREREnsEJTSJo42h2AAAQcUlEQVQiIiIiIiIiIvIMTmgSERERERERERGRZ3BCk4iIiIiIiIiIiDyDE5pERERERERERETkGZzQJCIiIiIiIiIiIs/ghCYRERERERERERF5Bic0iYiIiIiIiIiIyDM4oUlERERERERERESewQlNIiIiIiIiIiIi8gxOaObx7LPPYvHixTj11FNx8cUX47333nO6SERERERERERERMLjhGYOmzdvxn333Ye1a9di69atuPrqq7FixQrs2bPH6aIREREREREREREJjROaOTz00EO46qqrcOihhwIAzj77bMyePRsbN250uGRERERERERERERik50ugNvs3bsX33zzDU477bSM3y9cuBDr16/HLbfckvPv4vE4AKCtrQ2SJCEUCgHK0YBUk7mgMgPYvRujo6OoqqoquEw0Gs29nv//eiwWQzAYLLiOkZERVFdX513H8PAwampqCq7DyPuM/buEchSxjrz1UcQ6zPgsZdVZEeXI+z5FbEN65ShrOyyizszI30vbYd56LeKz6K3DrrZr5H301mFGOezaDu1ou2aUo6ztsIg6M2MdXtoO9faZRtaht+8uK38X1pneOsxouxUxZjKjHDbXu5e2Q71+10h96GVnV9sVbcxkRtvlmMm7n8WO452ytsMiPm8ltV23jJlEa7uiHe9Eo1EoioJkMolAIABgbF7N5/Ohu7tb+38hkqqqasElBPPBBx9gyZIleP/99zFhwgTt92+88QZuvPHGvPfS3L59O9avX29TKYmIiIiIiIiIiCrT8uXLMWfOnLyv8wzNLLI8ViU+X+bV+JIkodDc71FHHYXly5dj0qRJ2uwyERERERERERERGROPx9Hd3Y2jjjqq4HKc0MzS2toKAOjo6MDBBx+s/b6jowNTpkzJ+3e1tbUFZ46JiIiIiIiIiIiosNQzbQrhQ4GyNDc348gjj8SWLVsyfv+3v/0N8+fPd6hUREREREREREREBHBCM6err74a69atw65duwAAr776Kt58800sW7bM4ZIRERERERERERGJjZec57B48WIMDg5i5cqVGBoawpQpU/Dwww9j2rRpTheNiIiIiIiIiIhIaHzKuY0SiQT8fr/TxSCHMH+xMX+xMX+xMX+xMX+xMX+xMX+xMX+xMX/r8ZJzHc8++ywWL16MU089FRdffDHee+897bXR0VG88cYbuOGGG3DMMcfg22+/Lbiu//qv/8KHH36o/X/fvn24/vrrsXDhQsyfPx933XUXYrFYxt/83//9H9atW4ezzjoLt9xyi7kfjnRZmX9PTw82bdqESy+9FAsXLsz5NyMjI/j1r3+N0047DfPmzcOPf/zjjHWQtazM/4033sAll1yCBQsWYOHChbjtttuwf//+jL9h+3dWofxjsRjuuecerf9esmQJ3n333bzrKqX9z5o1C/PmzcOpp56q/dxzzz3mfUAqqFD+X3/9NVasWIEFCxZgwYIFuOqqq/DZZ5/lXVcp+/93330Xl156KebPn4+FCxfirrvuwujoqPkflHKyMn+99r9kyZKMdn/qqadi9uzZ+P73v2/uh6S8CuWf7o033sARRxyBZ599Nu+6OP73Hivz5/jf/Qrl//jjj+O4444b10d3dnbmXBfbv/dYmT/bvwVUyuu5555T586dq3755Zeqqqrqyy+/rB5//PHq7t27VVVV1dWrV6tXXnmlumbNGnXmzJnqnj178q4rkUiol19+uZpMJlVVVdVoNKouWrRIvfvuu1VFUdS+vj512bJl6h133KH9za5du9QzzzxT/cUvfqEuWbJEvfnmmy38tJTNyvxVVVXPO+889YYbblBvvPFG9fTTT8/5dytWrFBXr16tjoyMqMlkUt2wYYO6ZMkSNZFImPhJKRcr83///ffVOXPmqNu3b1dVVVUHBwfVa6+9Vr3mmmu0v2H7d5Ze/rfeeqt6xRVXqD09Pdrrxx57rPrNN9+MW1cp7X9gYECdOXOmOjIyYsXHIx2F8h8YGFBPOeUU9cknn1QTiYSqKIr68MMPqyeffLI6PDw8bl2l7P+//PJL9fjjj1dfeeUVVVVVtbe3V122bJl6++232/Dpycr8VdXY/j/b5Zdfrt53333mfEAqSK//T+nq6lIXLlyonnHGGeozzzyTc10c/3uPlfmrKsf/bqeX/3/8x3+o99xzj6F1sf17j5X5qyrbvxU4oVnAmWeeqT722GMZv1uxYoV61113Zfxuz549uhMaW7ZsUR9++GHt/5s3b1bnzJmjxmIx7XcfffSReswxx6jd3d3j/v7mm29mh2YzK/NP98wzz+Ts0N566y31xBNPVKPRaMbvFUUx+hGoDFbn397envH///mf/1FnzZqV8+/Z/u1XKP9oNKpefPHFaiQSyXj9wgsvVJ944olx6yql/X/55ZfqnDlzyvgEVA699p/dfnt7e9WZM2eqH3/88bh1lbL/37Rpk3rnnXdmrOe1115TTzjhhPI+GBliZf7p8rX/XOuYO3euOjg4aPQjUBmM7v9XrFihPvzww+qyZcvyTmhx/O89VuafjuN/d9LL/7rrrlM3bNhgaF1s/95jZf7p2P7Nw0vO89i7dy+++eYbnHbaaRm/X7hwIbZu3Vr0+jZt2oSLLrpI+//bb7+NefPmIRAIaL87+uij0dDQgLfffrvkcpM5rM7fiNdffx0nnXQSgsFgxu95Hw7r2ZH/lClTtH9//fXXePTRRzFnzpySykvm0ss/GAziqaeewgEHHKC9Njg4iEgkgtra2nHrK6X9t7e3Z6yf7GOk/ae3356eHtx7771oaWnBjBkzxq2vlP3/BRdcgNtuuy1jPTt37sy5fZG5rM6/FPfddx9WrlyJCRMmlLUe0md0///HP/4R7e3tuOKKKwquj+N/b7E6fyM4/neOkfzb29sxdepUQ+tj+/cWq/M3gu2/eJzQzGPfvn0AgMmTJ2f8fvLkydprRnV3d0NVVTQ3N2esP3vdwNgguaOjo4QSk5mszt+Ib775BlOnTsUjjzyCH/7whzjjjDNw2223oaenp6j1UPHsyn/9+vWYNWsWLrjgAhx11FH4zW9+U3qhyTTF5t/d3Y0VK1agubkZ55xzzrjXSmn/+/btQygUwh133IFFixbhnHPOwb333ouRkZEiPw0Vy2j+H3zwAU4++WScfPLJ6OjowPr161FdXZ3xN2bt/5977jk8+OCD+Ld/+7eSPxcZY3X+xdqyZQv27duHiy++uOR1kHFG8v/666+xdu1arFmzJmNiIhvH/95jdf5GcPzvHCP5d3R04JNPPsHSpUuxcOFCLF++POc9Vtn+vcfq/I1g+y8eJzTzkGUZAODzZVaRJElQi3ww/KZNm3DhhRdm/C4QCECSpHHLlrJ+Mp/V+RuRSCSwefNmNDQ04LnnnsMzzzyDoaEhXH311Ugmk0Wvj4yzK//ly5fj3XffxRNPPIGdO3dix44dpRWYTFVM/m+//TbOP/981NXV4cknn0RVVVXG66W2/3g8jqGhIZx33nl44YUX8Nhjj+GDDz7A6tWri14XFcdo/sceeyzeeustvPrqq6iursbLL788bl3l7v9HR0dx66234s4778Q999xT9pl+pM/q/Iv1yCOPYOnSpeP6FrKGXv7xeByrVq3CypUrcfjhhxdcF8f/3mN1/kZw/O8cI/1/IBDA6Ogofve73+Gvf/0rLrroIlx55ZXjHgzH9u89VudvBNt/8TihmUdraysAjPu2pKOjI+NSIyPefPNNzJ8/P+N3+b6JKWX9ZD6r8zfigAMOwHHHHYclS5YgEAigoaEBt99+Oz766CN89dVXRa+PjLMzf5/Ph+OOOw4rV67ETTfdhHg8XnyByVRG83/66adx3XXX4d///d/x+9//Hk1NTePWVWr7X7JkCZ5//nkcd9xx8Pv9aG1txapVq/DSSy9heHi46PWRccW2/4MOOgh33nknfv/73497CmU5+//e3l4sXboUnZ2deOGFF8ad/UvWsDr/YuzcuRPvvfde2ZOiZJxe/g888ABqa2uxfPly3XVx/O89VudvBMf/zjHS/7/yyiu46aab0NjYCL/fj/POOw8nnHACXnjhhYy/Yfv3HqvzN4Ltv3ic0MyjubkZRx55JLZs2ZLx+7/97W9FbZw7duzArFmzxs30z58/H9u2bYOiKNrvvvjiC/T09OCkk04qr/BUNqvzN+L4449HLBbL+Vr2fTXIXFbnv3v3bnz55ZcZv2tqasLQ0BAnq1zASP6vv/461q5di40bN+Y9a66c9g9g3DexiUQCwPhvjslcevkPDg7inXfeyXituroaoVAInZ2d2u/K2f/H43GsXLkSxx9/PP77v/+bBzo2sjr/Yjz99NOYPXs2DjzwwJLXQcXRy3/Lli145513cOSRR+KII47AEUccge3bt+PWW2/FEUccobVrjv+9yer8jeD43zlGxn+5zpJLJpMZZ16y/XuT1fkbwfZfPB4VFXD11Vdj3bp12LVrFwDg1VdfxZtvvolly5YZXsezzz6LH/3oR+N+f9ppp2HixIlYu3YtEokEBgYG8Ktf/QoXXXQRJk6caNpnoNJZmb8RP/zhD/Htt99i48aNSCQSGB4exq9//WuccMIJmDZtWknrJOOszH/z5s249tprsXPnTgBjD5R54IEHMGvWLDQ0NJjzAagshfIfGhrCz372M9x777047LDD8q6jnPb/6KOP4sorr8y4Z8+aNWtw7rnn8tJTGxTK/3//93/xr//6r/jrX/8KYGyi+aGHHoLf78esWbO0dZSz/1+/fj1CoRBuu+22nJenkbWszN8oVVXx0ksvYcGCBeV9GCpaofw3b96Mzz//PONnzpw5uOuuu/D5559rlyxy/O9dVuZvBMf/ziqUf39/P8466yz85S9/QTKZhKqq2LRpE959911ccMEF2jrY/r3LyvyNYPsvnux0Adxs8eLFGBwcxMqVKzE0NIQpU6bg4YcfNrwx9ff3Y3BwMOeTamVZxrp163DHHXdgwYIF8Pl8+MEPfoBVq1aZ/TGoRFbmb4Qsy3j00Udx5513agdLc+fOxf33388DXBtYmf9Pf/pTtLS04MYbb0Rvby/8fj9OPPFE/PKXvzT7Y1CJCuW/fft29PT05Oyvjz32WNx///1lt/9ly5ZhYGAAl112GUZGRqCqKvcRNiqU/7Rp0/C73/0ODz30kNZmDz30UDz66KPaAUm5+/+tW7fi008/zTmZtXbtWhx33HEWfXICrM3fqE8++QQdHR045ZRTTPlMZBzH/2Lj+F9sevn/53/+J+6//36sWbMGsVgM06dPxyOPPIJDDz0UANu/11mZvxFs/8WTVN6B1jIbN25ES0sLzjrrLKeLQg5g/mJj/mJj/mJj/mJj/mJj/mJj/mJj/mJj/vbjJecW6urqwumnn+50McghzF9szF9szF9szF9szF9szF9szF9szF9szN9+PEOTiIiIiIiIiIiIPINnaBIREREREREREZFncEKTiIiIiIiIiIiIPIMTmkREREREREREROQZnNAkIiIiIiIiIiIiz+CEJhEREREREREREXkGJzSJiIiIiIiIiIjIMzihSURERERERERERJ7BCU0iIiIiIiIiIiLyDE5oEhERERERERERkWf8P+ydFcljN3vxAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 1600x1200 with 2 Axes>"
]
},
"metadata": {}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "I02xwq4pEnzf"
},
"source": [
"### 9-5. 実践的なチャートサンプル\n",
"* メインチャート ： ローソクバー＋ボリンジャーバンド＋SMA\n",
"* サブチャート１ ： RSI\n",
"* サブチャート２ ： MACD"
]
},
{
"cell_type": "code",
"metadata": {
"id": "cVK2AHkSDS1Y",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 701
},
"outputId": "03a09d9d-8eb1-40a6-bf7b-13f1524320ef"
},
"source": [
"# 指標計算のため、再度OHLCVを取得(期間長めに)\n",
"start_ut = int(du.Time('2021/01/01 09:00:00', 'JST').unixtime())\n",
"end_ut = int(du.Time('2021/05/25 09:00:00', 'JST').unixtime())\n",
"df = du.Tool.get_ohlcv_from_bitmex(start_ut-100*86400, end_ut, period=1440, symbol='XBTUSD', csv_path='./bitmex_ohlcv_1d.csv')\n",
"du.Tool.set_unixtime_to_dateindex(df)\n",
"\n",
"# 単純移動平均\n",
"df['sma'] = df['close'].rolling(window=10).mean()\n",
"\n",
"# ボリンジャーバンド\n",
"df['middle'] = df['close'].rolling(window=14).mean()\n",
"rolling_std = df['close'].rolling(window=14).std()\n",
"df['upper'] = df['middle'] + (rolling_std * 2)\n",
"df['lower'] = df['middle'] - (rolling_std * 2)\n",
"\n",
"# RSI\n",
"diff = df['close'].diff()\n",
"diff = diff[1:]\n",
"up, down = diff.copy(), diff.copy()\n",
"up[up < 0] = 0\n",
"down[down > 0] = 0\n",
"up_sma_14 = up.rolling(window=14, center=False).mean()\n",
"down_sma_14 = down.abs().rolling(window=14, center=False).mean()\n",
"rs = up_sma_14 / down_sma_14\n",
"df['rsi'] = 100.0 - (100.0 / (1.0 + rs))\n",
"\n",
"# MACD(先行:12, 遅行:26, シグナル:9)\n",
"ema12 = df['close'].ewm(span=12).mean()\n",
"ema26 = df['close'].ewm(span=26).mean()\n",
"df['macd'] = ema12 - ema26\n",
"df['signal'] = df['macd'].ewm(span=9).mean()\n",
"df['hist'] = df['macd'] - df['signal']\n",
"\n",
"# チャート表示用に絞り込み\n",
"df = du.Tool.filter_df(df, 'unixtime', start_ut, end_ut)\n",
"\n",
"display(df)"
],
"execution_count": 6,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"read csv: 1609459200 - 1621814400 (len=144)\n",
"save csv: 1600819200 - 1621814400 (len=244)\n",
"get df : 1600819200 - 1621814400 (len=244)\n"
]
},
{
"output_type": "display_data",
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>unixtime</th>\n",
" <th>open</th>\n",
" <th>high</th>\n",
" <th>low</th>\n",
" <th>close</th>\n",
" <th>volume</th>\n",
" <th>sma</th>\n",
" <th>middle</th>\n",
" <th>upper</th>\n",
" <th>lower</th>\n",
" <th>rsi</th>\n",
" <th>macd</th>\n",
" <th>signal</th>\n",
" <th>hist</th>\n",
" </tr>\n",
" <tr>\n",
" <th>datetime</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2021-01-01 00:00:00+00:00</th>\n",
" <td>1609459200</td>\n",
" <td>28951.0</td>\n",
" <td>29717.0</td>\n",
" <td>28701.5</td>\n",
" <td>29402.5</td>\n",
" <td>1838861284</td>\n",
" <td>26613.35</td>\n",
" <td>25719.678571</td>\n",
" <td>30406.199679</td>\n",
" <td>21033.157464</td>\n",
" <td>80.743575</td>\n",
" <td>2516.636197</td>\n",
" <td>2075.220438</td>\n",
" <td>441.415759</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-01-02 00:00:00+00:00</th>\n",
" <td>1609545600</td>\n",
" <td>29402.5</td>\n",
" <td>33430.0</td>\n",
" <td>29028.5</td>\n",
" <td>32185.0</td>\n",
" <td>4616478195</td>\n",
" <td>27507.75</td>\n",
" <td>26313.285714</td>\n",
" <td>31993.042896</td>\n",
" <td>20633.528532</td>\n",
" <td>83.957831</td>\n",
" <td>2786.936606</td>\n",
" <td>2217.563671</td>\n",
" <td>569.372934</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-01-03 00:00:00+00:00</th>\n",
" <td>1609632000</td>\n",
" <td>32185.0</td>\n",
" <td>34896.0</td>\n",
" <td>31988.0</td>\n",
" <td>33062.5</td>\n",
" <td>4233140121</td>\n",
" <td>28440.00</td>\n",
" <td>26996.964286</td>\n",
" <td>33463.127165</td>\n",
" <td>20530.801407</td>\n",
" <td>87.592789</td>\n",
" <td>3036.924350</td>\n",
" <td>2381.435807</td>\n",
" <td>655.488543</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-01-04 00:00:00+00:00</th>\n",
" <td>1609718400</td>\n",
" <td>33062.5</td>\n",
" <td>33670.0</td>\n",
" <td>27650.0</td>\n",
" <td>32044.5</td>\n",
" <td>5115041875</td>\n",
" <td>29171.60</td>\n",
" <td>27661.464286</td>\n",
" <td>34155.802642</td>\n",
" <td>21167.125929</td>\n",
" <td>85.783522</td>\n",
" <td>3116.989551</td>\n",
" <td>2528.546556</td>\n",
" <td>588.442995</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-01-05 00:00:00+00:00</th>\n",
" <td>1609804800</td>\n",
" <td>32044.5</td>\n",
" <td>34600.0</td>\n",
" <td>29936.5</td>\n",
" <td>34107.5</td>\n",
" <td>3831661018</td>\n",
" <td>29933.35</td>\n",
" <td>28395.214286</td>\n",
" <td>35333.303146</td>\n",
" <td>21457.125425</td>\n",
" <td>86.770233</td>\n",
" <td>3308.718067</td>\n",
" <td>2684.580858</td>\n",
" <td>624.137209</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-05-20 00:00:00+00:00</th>\n",
" <td>1621468800</td>\n",
" <td>36811.0</td>\n",
" <td>42444.0</td>\n",
" <td>34873.0</td>\n",
" <td>40620.5</td>\n",
" <td>3453752671</td>\n",
" <td>46290.60</td>\n",
" <td>49538.571429</td>\n",
" <td>63793.920561</td>\n",
" <td>35283.222296</td>\n",
" <td>24.582857</td>\n",
" <td>-3990.253366</td>\n",
" <td>-2395.916032</td>\n",
" <td>-1594.337334</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-05-21 00:00:00+00:00</th>\n",
" <td>1621555200</td>\n",
" <td>40620.5</td>\n",
" <td>42327.0</td>\n",
" <td>33460.0</td>\n",
" <td>37301.0</td>\n",
" <td>3346306092</td>\n",
" <td>44344.30</td>\n",
" <td>48101.357143</td>\n",
" <td>62976.635563</td>\n",
" <td>33226.078723</td>\n",
" <td>19.868819</td>\n",
" <td>-4420.546353</td>\n",
" <td>-2800.842096</td>\n",
" <td>-1619.704257</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-05-22 00:00:00+00:00</th>\n",
" <td>1621641600</td>\n",
" <td>37301.0</td>\n",
" <td>38885.0</td>\n",
" <td>35244.0</td>\n",
" <td>37446.5</td>\n",
" <td>1880503309</td>\n",
" <td>43139.65</td>\n",
" <td>46561.821429</td>\n",
" <td>61034.112011</td>\n",
" <td>32089.530846</td>\n",
" <td>16.276814</td>\n",
" <td>-4695.687055</td>\n",
" <td>-3179.811088</td>\n",
" <td>-1515.875967</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-05-23 00:00:00+00:00</th>\n",
" <td>1621728000</td>\n",
" <td>37446.5</td>\n",
" <td>38270.5</td>\n",
" <td>31100.0</td>\n",
" <td>34711.0</td>\n",
" <td>2882564071</td>\n",
" <td>41640.75</td>\n",
" <td>44876.928571</td>\n",
" <td>58949.576979</td>\n",
" <td>30804.280164</td>\n",
" <td>15.302355</td>\n",
" <td>-5075.957550</td>\n",
" <td>-3559.040380</td>\n",
" <td>-1516.917170</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021-05-24 00:00:00+00:00</th>\n",
" <td>1621814400</td>\n",
" <td>34711.0</td>\n",
" <td>39920.0</td>\n",
" <td>34453.0</td>\n",
" <td>38842.5</td>\n",
" <td>1991029675</td>\n",
" <td>40536.20</td>\n",
" <td>43657.642857</td>\n",
" <td>56517.185165</td>\n",
" <td>30798.100549</td>\n",
" <td>26.116521</td>\n",
" <td>-4986.466259</td>\n",
" <td>-3844.525556</td>\n",
" <td>-1141.940703</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>144 rows × 14 columns</p>\n",
"</div>"
],
"text/plain": [
" unixtime open ... signal hist\n",
"datetime ... \n",
"2021-01-01 00:00:00+00:00 1609459200 28951.0 ... 2075.220438 441.415759\n",
"2021-01-02 00:00:00+00:00 1609545600 29402.5 ... 2217.563671 569.372934\n",
"2021-01-03 00:00:00+00:00 1609632000 32185.0 ... 2381.435807 655.488543\n",
"2021-01-04 00:00:00+00:00 1609718400 33062.5 ... 2528.546556 588.442995\n",
"2021-01-05 00:00:00+00:00 1609804800 32044.5 ... 2684.580858 624.137209\n",
"... ... ... ... ... ...\n",
"2021-05-20 00:00:00+00:00 1621468800 36811.0 ... -2395.916032 -1594.337334\n",
"2021-05-21 00:00:00+00:00 1621555200 40620.5 ... -2800.842096 -1619.704257\n",
"2021-05-22 00:00:00+00:00 1621641600 37301.0 ... -3179.811088 -1515.875967\n",
"2021-05-23 00:00:00+00:00 1621728000 37446.5 ... -3559.040380 -1516.917170\n",
"2021-05-24 00:00:00+00:00 1621814400 34711.0 ... -3844.525556 -1141.940703\n",
"\n",
"[144 rows x 14 columns]"
]
},
"metadata": {}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "tLib1sNiGOEv",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 760
},
"outputId": "45a75981-b16d-4415-b60b-b8f0205ae153"
},
"source": [
"# Chartオブジェクト生成\n",
"chart = du.Chart(df)\n",
"\n",
"# タイトル設定\n",
"chart.set_title(title='BitMEX 1D ローソク足', loc='center', fontsize=16)\n",
"\n",
"# チャートサイズ設定\n",
"chart.set_size(width=16, height=12)\n",
"\n",
"# X軸設定\n",
"chart.set_x(col=None, grid=True, converter=du.Chart.to_date_format, format='%m/%d')\n",
"\n",
"# メインチャートY軸設定(ax=0)\n",
"chart.set_y(ax=0, title='USD', grid=True, legend=False, gridspec=4)\n",
"\n",
"# ロウソク足設定(メインチャート : ax=0)\n",
"chart.set_candlestick(ax=0, open='open', high='high', low='low', close='close')\n",
"\n",
"#---------------------------------------------------------------------------\n",
"# BAND設定\n",
"#---------------------------------------------------------------------------\n",
"# [params]\n",
"# ax : チャート番号(0:メイン, 1～:サブチャート)\n",
"# y1 : y1列名\n",
"# y2 : y2列名\n",
"# linewidth : 線幅\n",
"# linecolor : 線色\n",
"# upcolor : y1 > y2 色\n",
"# downcolor : y1 < y2 色\n",
"# label : 見出し\n",
"#---------------------------------------------------------------------------\n",
"# ボリンジャーバンド(メインチャート : ax=0)\n",
"chart.set_band(ax=0, y1='upper', y2='lower', linewidth=0.5, linecolor='cyan', upcolor='skyblue', downcolor='pink', alpha=0.05, label='BB')\n",
"\n",
"#---------------------------------------------------------------------------\n",
"# LINE設定\n",
"#---------------------------------------------------------------------------\n",
"# [params]\n",
"# ax : チャート番号(0:メイン, 1～:サブチャート)\n",
"# y : y列名\n",
"# linewidth : 線幅\n",
"# linestyle : 線種('solid', 'dashed', 'dashdot', 'dotted', etc.)\n",
"# color : 線色\n",
"# label : 見出し\n",
"#---------------------------------------------------------------------------\n",
"# ボリンジャーバンド(メインチャート : ax=0)\n",
"chart.set_line(ax=0, y='middle', linewidth=0.5, linestyle='solid', color='cyan', label='BB middle')\n",
"\n",
"# SMA設定\n",
"chart.set_line(ax=0, y='sma', linewidth=1.0, linestyle='solid', color='red', label='SMA')\n",
"\n",
"#---------------------------------------------------------------------------\n",
"# VolumeサブチャートY軸設定(ax=1)\n",
"#---------------------------------------------------------------------------\n",
"chart.set_y(ax=1, title='Volume', grid=True, legend=False, gridspec=1)\n",
"\n",
"# BAR設定(サブチャート : ax=1)\n",
"chart.set_bar(ax=1, y='volume', color='orange', width=0.8, label='Volume')\n",
"\n",
"#---------------------------------------------------------------------------\n",
"# RSIサブチャートY軸設定(ax=2)\n",
"#---------------------------------------------------------------------------\n",
"chart.set_y(ax=2, title='RSI', grid=True, legend=True, gridspec=2)\n",
"\n",
"# RSI設定\n",
"chart.set_line(ax=2, y='rsi', linewidth=1.0, linestyle='solid', color='red', label='RSI')\n",
"\n",
"#---------------------------------------------------------------------------\n",
"# MACDサブチャートY軸設定(ax=3)\n",
"#---------------------------------------------------------------------------\n",
"chart.set_y(ax=3, title='MACD', grid=True, legend=True, gridspec=2)\n",
"\n",
"# MACD設定\n",
"chart.set_line(ax=3, y='macd', linewidth=1.0, linestyle='solid', color='red', label='MACD')\n",
"chart.set_line(ax=3, y='signal', linewidth=1.0, linestyle='solid', color='cyan', label='Signal')\n",
"chart.set_bar(ax=3, y='hist', color='orange', width=0.8, label='Hist')\n",
"\n",
"# チャート表示\n",
"chart.plot()"
],
"execution_count": 7,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1600x1200 with 4 Axes>"
]
},
"metadata": {}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "D5sCVEUlK3A6"
},
"source": [
"### 9-6. メソッドチェーン記法"
]
},
{
"cell_type": "code",
"metadata": {
"id": "OZa0g6HUJJjh",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 760
},
"outputId": "df48250f-8649-4fcd-df88-f1cf16dad70d"
},
"source": [
"# Chartオブジェクト生成\n",
"chart = (\n",
" du.Chart(df)\n",
" .set_title(title='BitMEX 1D ローソク足', loc='center', fontsize=16) # タイトル設定\n",
" .set_size(width=16, height=12) # チャートサイズ設定\n",
" .set_x(col=None, grid=True, converter=du.Chart.to_date_format, format='%m/%d') # X軸設定\n",
" # メインチャート(ax=0)\n",
" .set_y(ax=0, title='USD', grid=True, legend=False, gridspec=4) # Y軸設定\n",
" .set_candlestick(ax=0, open='open', high='high', low='low', close='close') # ロウソク足設定\n",
" .set_band(ax=0, y1='upper', y2='lower', linewidth=0.5, linecolor='cyan', upcolor='skyblue', downcolor='pink', alpha=0.05, label='BB') # ボリンジャーバンド\n",
" .set_line(ax=0, y='middle', linewidth=0.5, linestyle='solid', color='cyan', label='BB middle') # ボリンジャーバンドmiddle\n",
" .set_line(ax=0, y='sma', linewidth=1.0, linestyle='solid', color='red', label='SMA') # SMA設定\n",
" # サブチャート(ax=1)\n",
" .set_y(ax=1, title='Volume', grid=True, legend=False, gridspec=1) # Y軸設定\n",
" .set_bar(ax=1, y='volume', color='orange', width=0.8, label='Volume') # BAR設定(Volume)\n",
" # サブチャート(ax=2)\n",
" .set_y(ax=2, title='RSI', grid=True, legend=True, gridspec=2) # Y軸設定\n",
" .set_line(ax=2, y='rsi', linewidth=1.0, linestyle='solid', color='red', label='RSI') # RSI設定\n",
" # サブチャート(ax=3)\n",
" .set_y(ax=3, title='MACD', grid=True, legend=True, gridspec=2) # Y軸設定\n",
" .set_line(ax=3, y='macd', linewidth=1.0, linestyle='solid', color='red', label='MACD') # MACD設定\n",
" .set_line(ax=3, y='signal', linewidth=1.0, linestyle='solid', color='cyan', label='Signal') # MACD Signal設定\n",
" .set_bar(ax=3, y='hist', color='orange', width=0.8, label='Hist') # MACD Hist設定\n",
")\n",
"\n",
"# チャート表示\n",
"chart.plot()"
],
"execution_count": 27,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": 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