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Dual Momentum - Stocks, Bonds, Cash
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dual_momentum.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Dual Momentum Portfolio\n",
"This Notebook is designed to show a simple system which loops through daily data on three instruments: a stock, a bond and cash. Momentum is measured by a moving average crossover. The system invests in stocks if the short moving avearge of the stock's price is above the long moving average. If the stock momentum indicator shows no trend but the bond short moving average is above the bond long moving average, the system invests in bonds. If the both stocks and bonds fail the momentum test, the system invests in cash.\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## You will need to import the following Python packages into the Notebook"
]
},
{
"cell_type": "code",
"execution_count": 82,
"metadata": {},
"outputs": [],
"source": [
"import datetime\n",
"import logging\n",
"import os\n",
"import sys\n",
"import ffn\n",
"from collections import OrderedDict\n",
"from typing import Dict, List\n",
"import numpy as np\n",
"import pandas as pd\n",
"from numba import jit\n",
"import matplotlib.pyplot as plt\n",
"%matplotlib notebook"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## You may or may not find the following options useful."
]
},
{
"cell_type": "code",
"execution_count": 83,
"metadata": {},
"outputs": [],
"source": [
"pd.set_option(\"max_colwidth\", 100)\n",
"pd.set_option(\"display.max_rows\", 100000)\n",
"pd.set_option(\"display.max_columns\", 1000)\n",
"pd.set_option('precision', 6)\n",
"pd.options.display.float_format = '{:20,.6f}'.format"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Set up the built in Python logging facilty\n",
"Useful for de-bugging.\n",
"\n",
"Currently set to: logger.setLevel(logging.INFO)\n",
"\n",
"Set this to DEBUG if you want some verbose output: logger.setLevel(logging.DEBUG)\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 84,
"metadata": {},
"outputs": [],
"source": [
"logger = logging.getLogger(\"a_w\")\n",
"logger.setLevel(logging.INFO)\n",
"\n",
"# create a file handler\n",
"handler = logging.StreamHandler()\n",
"for handler in logger.handlers:\n",
" logger.removeHandler(handler)\n",
"handler.setLevel(logging.DEBUG)\n",
"\n",
"# create a logging format\n",
"formatter = logging.Formatter(\n",
" '%(asctime)s - %(name)s - %(levelname)s - %(message)s')\n",
"handler.setFormatter(formatter)\n",
"\n",
"# add the handlers to the logger\n",
"logger.addHandler(handler)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Initialise Variables\n",
"Make sure to set the directory to where your stock data is located. \n",
"\n",
"Change dates, allocations and stocks as desired"
]
},
{
"cell_type": "code",
"execution_count": 85,
"metadata": {},
"outputs": [],
"source": [
"start: datetime.date = '1900-01-01'\n",
"end = datetime.date.today()\n",
"\n",
"starting_capital: float() =100000\n",
"\n",
"stock_directory: str = '..\\\\data\\\\Stocks\\\\'\n",
"\n",
"stock: str = 'WillshireTRFed'\n",
"#bond: str = 'Fed5YR'\n",
"bond: str = '30YrBond'\n",
"money:str = '3mTBill'\n",
"\n",
"\n",
"sma_length: int= 10\n",
"lma_length: int=20\n",
"\n",
"\n",
"stock_tickers_list: List[str] = [stock, bond,money]\n",
"\n",
"\n",
"#list of files to be saved. Ensure you use your own directories and desired filenames\n",
"test: str = \"C:\\\\Users\\\\agarn\\\\OneDrive\\\\Documents\\\\Articles//DMtest.csv\"\n",
"drawdown: str = \"C:\\\\Users\\\\agarn\\\\OneDrive\\\\Documents\\\\Articles//DMdrawdown.csv\"\n",
"rebased: str = \"C:\\\\Users\\\\agarn\\\\OneDrive\\\\Documents\\Articles//DMrebased.csv\"\n",
"stats: str = \"C:\\\\Users\\\\agarn\\\\OneDrive\\\\Documents\\\\Articles//DMstats.csv\"\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 86,
"metadata": {},
"outputs": [],
"source": [
"#This function will calculate the VAMI each day from the return for that day\n",
"@jit()\n",
"def calculator(a):\n",
" res = np.empty(data.equity.shape)\n",
" res[0] = 100\n",
" for i in range(1, res.shape[0]):\n",
" res[i] = res[i-1] +(res[i-1]* a[i])\n",
" return res"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## The following function checks to ensure the stock directory is correct and the data files exist:"
]
},
{
"cell_type": "code",
"execution_count": 87,
"metadata": {},
"outputs": [],
"source": [
"def check_data_files(ticker_list: List, target_directory: str):\n",
" logger = logging.getLogger(\"a_w.check_data_files\")\n",
"\n",
" if not os.path.exists(stock_directory):\n",
" logger.info('stockdirectory does not exist')\n",
" for ticker in stock_tickers_list:\n",
" filename = os.path.join(stock_directory, ticker + '.csv')\n",
" if not os.path.exists(filename):\n",
" logger.info('file does not exist in given directory:' + \" \" + ticker)"
]
},
{
"cell_type": "code",
"execution_count": 88,
"metadata": {},
"outputs": [],
"source": [
"check_data_files(stock_tickers_list,stock_directory)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## The next function returns a dictionary of dataframes for the stock data:\n",
"Reads the desired files from the relevant directory"
]
},
{
"cell_type": "code",
"execution_count": 89,
"metadata": {},
"outputs": [],
"source": [
"def get_dataframe_dictionary(ticker_list: List,\n",
" target_directory: str) -> Dict[str, pd.DataFrame]:\n",
" \"\"\"\n",
" Get a list of files and put into a dictionary of dataframes\n",
" :param ticker_list:\n",
" :param target_directory:\n",
" :return:\n",
" \"\"\"\n",
" ret = OrderedDict()\n",
" logger = logging.getLogger(\"a_w.get_dataframe_dictionary\")\n",
" logger.debug(\"get_dataframe_dictionary: %s\", ticker_list)\n",
" for ticker in ticker_list:\n",
" filename = os.path.join(target_directory, ticker + '.csv')\n",
" if os.path.exists(filename):\n",
" try:\n",
" ret[ticker] = pd.read_csv(filename, parse_dates=[\"Date\"])\n",
" except:\n",
" continue\n",
" return ret"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Merge the three separate time series into a single dataframe for back testing:"
]
},
{
"cell_type": "code",
"execution_count": 90,
"metadata": {},
"outputs": [],
"source": [
"def merge_data(stock_tickers_list: List[str], target_directory: str,\n",
" start: str, end: str) -> pd.DataFrame:\n",
" \"\"\"\n",
" take the dicts of stocks time series and create a dataframe to pass for backtesting\n",
" :param stock_tickers_list:\n",
" :param start: date like '2001-01-01' YYYY-MM-DD format\n",
" :param end: date like '2001-12-31' YYYY-MM-DD format\n",
" :return:\n",
" \"\"\"\n",
" logger = logging.getLogger('a_w.merge_data')\n",
" logger.debug(\"Running: stock_tickers_list: %d\", len(stock_tickers_list))\n",
" check_data_files(stock_tickers_list, target_directory)\n",
" stock_data = get_dataframe_dictionary(stock_tickers_list, target_directory)\n",
" logger.debug(\"Found Data: %d\", len(stock_tickers_list))\n",
" data = pd.DataFrame()\n",
"\n",
" for ticker in stock_tickers_list:\n",
" try:\n",
" if data.empty:\n",
" data = stock_data[ticker]\n",
" else:\n",
" a = stock_data[ticker]\n",
" data = data.merge(\n",
" a, how='left', left_on='Date',\n",
" right_on='Date').fillna(method='ffill')\n",
" data = data.dropna()\n",
" except:\n",
" continue\n",
" logger.debug(\"Cols:{}\".format(data.columns.values))\n",
" logger.debug(\"Now I have a datframe with shape: %s\", data.shape)\n",
"\n",
" if not data.empty:\n",
" new_index = pd.to_datetime(pd.Series(data['Date']))\n",
" data.set_index(new_index,drop=True,append=False,inplace=True,verify_integrity=False)\n",
" data.drop(['Date'], inplace=True, axis=1)\n",
" data = data.truncate(before=start, after=end, axis=0)\n",
" if len(data.columns) == 3:\n",
" data.columns = ['stock', 'bond','money']\n",
" data['stock_return']=data.stock.pct_change()\n",
" data['bond_return']=data.bond.pct_change()\n",
" data['money_return']=data.money.pct_change()\n",
" data['stock_test']=data.stock.rolling(sma_length).mean().shift(2)>data.stock.rolling(lma_length).mean().shift(2)\n",
" data['bond_test']=data.bond.rolling(sma_length).mean().shift(2)>data.bond.rolling(lma_length).mean().shift(2)\n",
" conditions=[data.stock_test==True,(data.stock_test==False) & (data.bond_test==False),data.stock_test==False,]\n",
" outputs=[data.stock_return,data.money_return,data.bond_return]\n",
" data['strategy_return']=np.select(conditions, outputs)\n",
" data.dropna(inplace=True)\n",
" data['equity']=0.0\n",
" #data['dual_momentum'] = calculator(*data[list(data.loc[:, ['strategy_return']])].values.T)\n",
" \n",
"\n",
" return data[lma_length:]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Call the functions listed so far and inspect the dataframe."
]
},
{
"cell_type": "code",
"execution_count": 91,
"metadata": {},
"outputs": [],
"source": [
"data=merge_data(stock_tickers_list, stock_directory,start,end)"
]
},
{
"cell_type": "code",
"execution_count": 92,
"metadata": {},
"outputs": [
{
"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>stock</th>\n",
" <th>bond</th>\n",
" <th>money</th>\n",
" <th>stock_return</th>\n",
" <th>bond_return</th>\n",
" <th>money_return</th>\n",
" <th>stock_test</th>\n",
" <th>bond_test</th>\n",
" <th>strategy_return</th>\n",
" <th>equity</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Date</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>1980-01-02</th>\n",
" <td>1.860000</td>\n",
" <td>29.500860</td>\n",
" <td>221.498467</td>\n",
" <td>-0.021053</td>\n",
" <td>0.005745</td>\n",
" <td>0.000333</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>-0.021053</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1980-01-04</th>\n",
" <td>1.880000</td>\n",
" <td>28.871750</td>\n",
" <td>221.645348</td>\n",
" <td>0.010753</td>\n",
" <td>-0.021325</td>\n",
" <td>0.000663</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>0.010753</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1980-01-07</th>\n",
" <td>1.890000</td>\n",
" <td>28.557190</td>\n",
" <td>221.717368</td>\n",
" <td>0.005319</td>\n",
" <td>-0.010895</td>\n",
" <td>0.000325</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>0.005319</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1980-01-08</th>\n",
" <td>1.930000</td>\n",
" <td>28.905450</td>\n",
" <td>221.788925</td>\n",
" <td>0.021164</td>\n",
" <td>0.012195</td>\n",
" <td>0.000323</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>0.021164</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1980-01-09</th>\n",
" <td>1.930000</td>\n",
" <td>29.141370</td>\n",
" <td>221.860383</td>\n",
" <td>0.000000</td>\n",
" <td>0.008162</td>\n",
" <td>0.000322</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>0.000322</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" stock bond money \\\n",
"Date \n",
"1980-01-02 1.860000 29.500860 221.498467 \n",
"1980-01-04 1.880000 28.871750 221.645348 \n",
"1980-01-07 1.890000 28.557190 221.717368 \n",
"1980-01-08 1.930000 28.905450 221.788925 \n",
"1980-01-09 1.930000 29.141370 221.860383 \n",
"\n",
" stock_return bond_return money_return \\\n",
"Date \n",
"1980-01-02 -0.021053 0.005745 0.000333 \n",
"1980-01-04 0.010753 -0.021325 0.000663 \n",
"1980-01-07 0.005319 -0.010895 0.000325 \n",
"1980-01-08 0.021164 0.012195 0.000323 \n",
"1980-01-09 0.000000 0.008162 0.000322 \n",
"\n",
" stock_test bond_test strategy_return equity \n",
"Date \n",
"1980-01-02 True False -0.021053 0.000000 \n",
"1980-01-04 True False 0.010753 0.000000 \n",
"1980-01-07 True False 0.005319 0.000000 \n",
"1980-01-08 True False 0.021164 0.000000 \n",
"1980-01-09 False False 0.000322 0.000000 "
]
},
"execution_count": 92,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"inspect_data = pd.DataFrame()\n",
"if not data.empty:\n",
" inspect_data = data\n",
" #inspect_data.to_csv(\"C:\\\\Users\\\\agarn\\\\OneDrive\\\\Documents\\Articles//DM_inspect_data.csv\") \n",
"else:\n",
" print('data loading failed see logging')\n",
"inspect_data.head()"
]
},
{
"cell_type": "code",
"execution_count": 93,
"metadata": {},
"outputs": [
{
"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>stock</th>\n",
" <th>bond</th>\n",
" <th>money</th>\n",
" <th>stock_return</th>\n",
" <th>bond_return</th>\n",
" <th>money_return</th>\n",
" <th>stock_test</th>\n",
" <th>bond_test</th>\n",
" <th>strategy_return</th>\n",
" <th>equity</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Date</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>1980-01-02</th>\n",
" <td>1.860000</td>\n",
" <td>29.500860</td>\n",
" <td>221.498467</td>\n",
" <td>-0.021053</td>\n",
" <td>0.005745</td>\n",
" <td>0.000333</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>-0.021053</td>\n",
" <td>100.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1980-01-04</th>\n",
" <td>1.880000</td>\n",
" <td>28.871750</td>\n",
" <td>221.645348</td>\n",
" <td>0.010753</td>\n",
" <td>-0.021325</td>\n",
" <td>0.000663</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>0.010753</td>\n",
" <td>101.075269</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1980-01-07</th>\n",
" <td>1.890000</td>\n",
" <td>28.557190</td>\n",
" <td>221.717368</td>\n",
" <td>0.005319</td>\n",
" <td>-0.010895</td>\n",
" <td>0.000325</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>0.005319</td>\n",
" <td>101.612903</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1980-01-08</th>\n",
" <td>1.930000</td>\n",
" <td>28.905450</td>\n",
" <td>221.788925</td>\n",
" <td>0.021164</td>\n",
" <td>0.012195</td>\n",
" <td>0.000323</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>0.021164</td>\n",
" <td>103.763441</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1980-01-09</th>\n",
" <td>1.930000</td>\n",
" <td>29.141370</td>\n",
" <td>221.860383</td>\n",
" <td>0.000000</td>\n",
" <td>0.008162</td>\n",
" <td>0.000322</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>0.000322</td>\n",
" <td>103.796873</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" stock bond money \\\n",
"Date \n",
"1980-01-02 1.860000 29.500860 221.498467 \n",
"1980-01-04 1.880000 28.871750 221.645348 \n",
"1980-01-07 1.890000 28.557190 221.717368 \n",
"1980-01-08 1.930000 28.905450 221.788925 \n",
"1980-01-09 1.930000 29.141370 221.860383 \n",
"\n",
" stock_return bond_return money_return \\\n",
"Date \n",
"1980-01-02 -0.021053 0.005745 0.000333 \n",
"1980-01-04 0.010753 -0.021325 0.000663 \n",
"1980-01-07 0.005319 -0.010895 0.000325 \n",
"1980-01-08 0.021164 0.012195 0.000323 \n",
"1980-01-09 0.000000 0.008162 0.000322 \n",
"\n",
" stock_test bond_test strategy_return equity \n",
"Date \n",
"1980-01-02 True False -0.021053 100.000000 \n",
"1980-01-04 True False 0.010753 101.075269 \n",
"1980-01-07 True False 0.005319 101.612903 \n",
"1980-01-08 True False 0.021164 103.763441 \n",
"1980-01-09 False False 0.000322 103.796873 "
]
},
"execution_count": 93,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data['equity'] = calculator(*data[list(data.loc[:, ['strategy_return']])].values.T)\n",
"data.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Save backtest data to file for further inspection. Use FFN package to create charts and statistics for the backtest."
]
},
{
"cell_type": "code",
"execution_count": 94,
"metadata": {},
"outputs": [],
"source": [
" def show_stats(backtest: pd.DataFrame):\n",
" if backtest is not None and not backtest.empty:\n",
" logger = logging.getLogger('a_w.charts')\n",
" res = backtest.equity.astype(np.float64)\n",
" benchmarked = pd.concat(\n",
" [res, backtest.stock, backtest.bond], sort=False, axis=1) \n",
" log = True\n",
" benchmarked.rebase().plot(figsize=(7, 6), logy=log, title='All Weather Portfolio')\n",
" benchmarked.calc_stats().display()\n",
" benchmarked.to_drawdown_series().plot(figsize=(8, 6))\n",
"\n",
" def save_1():backtest.to_csv(test)\n",
" def save_2():benchmarked.rebase().to_csv(rebased)\n",
" def save_3():benchmarked.calc_stats().to_csv(sep=', ', path=stats)\n",
" def save_4():benchmarked.to_drawdown_series().to_csv(drawdown)\n",
" save_files=[save_1,save_2,save_3,save_4]\n",
" for s in save_files:\n",
" try:\n",
" s()\n",
" except IOError:\n",
" print('file open - close file ',s) \n",
" continue\n",
"\n",
" else:\n",
" print('backtest failed see logging')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Call the show-backtest function"
]
},
{
"cell_type": "code",
"execution_count": 95,
"metadata": {},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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\" 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]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Stat equity stock bond\n",
"------------------- ---------- ---------- ----------\n",
"Start 1980-01-02 1980-01-02 1980-01-02\n",
"End 2019-03-29 2019-03-29 2019-03-29\n",
"Risk-free rate 0.00% 0.00% 0.00%\n",
"\n",
"Total Return 3302.05% 7087.63% 407.82%\n",
"Daily Sharpe 0.81 0.73 0.41\n",
"Daily Sortino 1.27 1.14 0.68\n",
"CAGR 9.41% 11.51% 4.23%\n",
"Max Drawdown -21.39% -55.39% -39.66%\n",
"Calmar Ratio 0.44 0.21 0.11\n",
"\n",
"MTD 1.73% 1.50% 3.36%\n",
"3m 9.81% 15.10% 3.72%\n",
"6m 6.39% -2.19% 7.49%\n",
"YTD 9.36% 14.11% 3.29%\n",
"1Y 9.19% 8.93% 4.89%\n",
"3Y (ann.) 9.57% 13.71% -0.04%\n",
"5Y (ann.) 5.27% 10.53% 3.28%\n",
"10Y (ann.) 9.18% 16.16% 3.71%\n",
"Since Incep. (ann.) 9.41% 11.51% 4.23%\n",
"\n",
"Daily Sharpe 0.81 0.73 0.41\n",
"Daily Sortino 1.27 1.14 0.68\n",
"Daily Mean (ann.) 9.71% 12.33% 4.86%\n",
"Daily Vol (ann.) 12.03% 16.93% 11.98%\n",
"Daily Skew -0.25 -0.61 0.14\n",
"Daily Kurt 6.73 15.47 3.71\n",
"Best Day 7.10% 11.36% 5.38%\n",
"Worst Day -6.55% -17.31% -6.02%\n",
"\n",
"Monthly Sharpe 0.83 0.79 0.45\n",
"Monthly Sortino 1.57 1.32 0.86\n",
"Monthly Mean (ann.) 9.48% 11.91% 5.02%\n",
"Monthly Vol (ann.) 11.39% 15.16% 11.11%\n",
"Monthly Skew -0.10 -0.77 0.47\n",
"Monthly Kurt 0.98 2.60 2.47\n",
"Best Month 11.89% 12.87% 14.82%\n",
"Worst Month -10.44% -22.81% -10.75%\n",
"\n",
"Yearly Sharpe 0.84 0.74 0.46\n",
"Yearly Sortino 4.00 1.69 1.15\n",
"Yearly Mean 9.28% 11.99% 5.32%\n",
"Yearly Vol 11.07% 16.30% 11.66%\n",
"Yearly Skew 0.50 -0.81 0.12\n",
"Yearly Kurt -0.03 0.86 -0.54\n",
"Best Year 35.52% 36.40% 26.44%\n",
"Worst Year -8.44% -37.23% -17.95%\n",
"\n",
"Avg. Drawdown -2.07% -2.01% -2.96%\n",
"Avg. Drawdown Days 38.11 27.77 85.75\n",
"Avg. Up Month 2.75% 3.46% 2.60%\n",
"Avg. Down Month -2.31% -3.49% -2.19%\n",
"Win Year % 79.49% 79.49% 66.67%\n",
"Win 12m % 80.43% 80.00% 67.61%\n"
]
},
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
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\" width=\"799.9999826604674\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"show_stats(data)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## This is my Python version\n",
"from platform import python_version\n",
"\n",
"python_version()\n",
"\n",
"'3.6.8'"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Anaconda Version and System Info\n",
"\n",
"sys.version,sys.version_info\n",
"\n",
"('3.6.8 |Anaconda custom (64-bit)| (default, Feb 21 2019, 18:30:04) [MSC v.1916 64 bit (AMD64)]',\n",
" sys.version_info(major=3, minor=6, micro=8, releaselevel='final', serial=0))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Version of the Imports\n",
"\n",
"import pip\n",
"\n",
"%pip list\n",
"\n",
"Package Version \n",
"---------------------------------- --------\n",
"ffn 0.3.4 \n",
"numpy 1.16.2 \n",
"pandas 0.24.2 \n",
" \n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.3"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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