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Fix issues NVIDIA#13, NVIDIA#14, and NVIDIA#15
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@miguelusque
miguelusque committed Aug 5, 2019
1 parent 867488f commit 801c7e8
Showing 1 changed file with 19 additions and 80 deletions.
99 changes: 19 additions & 80 deletions notebook/cuIndicator/indicator_demo.ipynb
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"cells": [
{
"cell_type": "code",
"execution_count": 5,
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import sys\n",
"sys.path.append('../..')\n",
"\n",
"import os\n",
"import pandas as pd\n",
"import cudf\n",
"import numpy as np\n",
Expand All @@ -27,14 +29,14 @@
},
{
"cell_type": "code",
"execution_count": 6,
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"node_csv = {\"id\": \"node_csvdata\",\n",
" \"type\": \"CsvStockLoader\",\n",
" \"conf\": {\n",
" \"path\": \"/Project/data/stocks/stock_price_hist.csv.gz\" \n",
" \"path\": \"../data/stock_price_hist.csv.gz\" \n",
" },\n",
" \"inputs\": []}\n",
"node_asset = {\"id\": \"node_assetFilter\",\n",
Expand All @@ -53,27 +55,19 @@
"node_stockSymbol = {\"id\": \"node_stockSymbol\",\n",
" \"type\": \"StockNameLoader\",\n",
" \"conf\": {\n",
" \"path\": \"/Project/data/stocks/security_master.csv.gz\" \n",
" \"path\": \"../data/security_master.csv.gz\" \n",
" },\n",
" \"inputs\": []} "
]
},
{
"cell_type": "code",
"execution_count": 7,
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/conda/envs/rapids/lib/python3.6/site-packages/cudf-0.7.2-py3.6-linux-x86_64.egg/cudf/io/hdf.py:13: UserWarning: Using CPU via Pandas to read HDF dataset, this may be GPU accelerated in the future\n",
" warnings.warn(\"Using CPU via Pandas to read HDF dataset, this may \"\n"
]
}
],
"outputs": [],
"source": [
"df = run([node_csv, node_sort], ['node_sort'], {'node_csvdata': {\"load\": True}})[0]\n",
"action = \"load\" if os.path.isfile('./.cache/node_csvdata.hdf5') else \"save\"\n",
"df = run([node_csv, node_sort], ['node_sort'], {'node_csvdata': {action: True}})[0]\n",
"\n",
"def one_stock(df, stock_id):\n",
" return df.query('asset==%s' % stock_id)\n",
Expand All @@ -96,26 +90,11 @@
},
{
"cell_type": "code",
"execution_count": 8,
"execution_count": null,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "73b8aa7061454eda8d6e680b9323fde5",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"VBox(children=(HBox(children=(Dropdown(description='Add stock', options=('MIDAX', 'MMELX', 'BBDO', 'BSAC', 'BI…"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"outputs": [],
"source": [
"add_stock_selector = widgets.Dropdown(options=list_stocks.keys(), value=None, description=\"Add stock\")\n",
"year_selector = widgets.IntSlider(description=\"All Year\", continuous_update=False)\n",
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},
{
"cell_type": "code",
"execution_count": 9,
"execution_count": null,
"metadata": {
"scrolled": false
},
"outputs": [
{
"ename": "KeyError",
"evalue": "'High'",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-9-e34775186425>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0moutput\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mci\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mppsr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'High'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Low'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Close'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mprint\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0moutput\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0moutput\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mR1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;31m#print (output[100:].fillna(0))\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~conda/envs/rapids/lib/python3.6/site-packages/cudf-0.7.2-py3.6-linux-x86_64.egg/cudf/dataframe/dataframe.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, arg)\u001b[0m\n\u001b[1;32m 221\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_column_major\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0marg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 222\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mstr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnumbers\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mNumber\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtuple\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 223\u001b[0;31m \u001b[0ms\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_cols\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0marg\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 224\u001b[0m \u001b[0ms\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mname\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0marg\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 225\u001b[0m \u001b[0ms\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mKeyError\u001b[0m: 'High'"
]
}
],
"outputs": [],
"source": [
"output = ci.ppsr(df['High'],df['Low'],df['Close'])\n",
"output = ci.ppsr(df['high'],df['low'],df['close'])\n",
"print (output)\n",
"print(output.R1)\n",
"#print (output[100:].fillna(0))"
Expand All @@ -1320,45 +1286,18 @@
},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": null,
"metadata": {},
"outputs": [
{
"ename": "NameError",
"evalue": "name 'get_parameters' is not defined",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-4-1e60258454fb>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mget_parameters\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstock_df\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;31mNameError\u001b[0m: name 'get_parameters' is not defined"
]
}
],
"outputs": [],
"source": [
"get_parameters(stock_df)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"execution_count": null,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "0bdf2053c4664866af48e1a060fc02af",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"Output(layout=Layout(border='1px solid black'))"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"outputs": [],
"source": [
"out"
]
Expand Down

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