add code for analysis of data

1 files changed, 22 insertions, 68 deletions

diff --git a/app.py b/app.py
index e3bc2b7..4032592 100644
--- a/app.py
+++ b/app.py
@@ -4,6 +4,7 @@ import json
 from datetime import datetime, timedelta
 from ema_algo import Ema_Algo
 from api import fetch_chart_data_yahoo
+from analysis import compute_results
 import pytz
 
 app = Dash(__name__)
@@ -25,29 +26,10 @@ app = Dash(__name__)
 #     intersected_x.append(x)
 #     intersected_y.append(y)
 
-app.layout = html.Div([
-    html.H4('Backtesting using the EMA method (5 vs 13) [ALPHA VERSION 0.0.2]'),
-    html.Div(
-        [
-            html.Label("Ticker ", htmlFor="ticker"),
-            dcc.Input(id="ticker", value="SPY", type="text"),
-            html.Br(),
-            html.Label("Period ", htmlFor="period_dropdown"),
-            dcc.Dropdown(
-                id="period_dropdown",
-                options=["1d","5d","1mo","3mo","6mo","1y","2y","5y","10y","ytd","max"],
-                value = "1y"),
-            html.Br(),
-            html.Label("Interval ", htmlFor="interval_dropdown"),
-            dcc.Dropdown(
-                id="interval_dropdown",
-                options=["1m", "2m", "5m", "15m", "30m", "60m", "90m", "1h", "4h", "1d", "5d", "1wk", "1mo", "3mo"],
-                value = "1d",
-            ),
-            html.P(id='error_message'),
-        ],
-        id='input_params'
-    ),
+app.layout = html.Div(
+    html.H4('Backtesting using EMA algos [ALPHA VERSION 0.0.5]'),
+    dcc.table(id="results_table")
+    dcc.Input(id="file_id", value="SPY", type="text"),
     html.Hr(),
     dcc.Graph(id="graph"),
     html.P("If bought and sold on these signals, the percent gain/loss would be:"),
@@ -56,54 +38,26 @@ app.layout = html.Div([
 ])
 
 @app.callback(
+    Output("results_table", "figure"),
     Output("graph", "figure"),
-    Output("percent_gain", "children"),
-    Output("input_params", "style"),
     Output("error_message", "children"),
-    Input("ticker", "value"),
-    Input("period_dropdown", "value"),
-    Input("interval_dropdown", "value")
+    Input("file_id", "value"),
     )
-def display_color(ticker, period, interval):
-        fd = open('bt-recent.json', 'r')
-        raw_data = fd.read()
-        trial_data = json.loads(raw_data)
-        fd.close()
-
-        chart_data = trial_data['chart_data']
-        backtest_results = trial_data['backtest_results']
-        url_params = trial_data['url_params']
-
-        percent_gain = backtest_results['percent_gain']
-        error_style = {"color" : "red"}
-        error_message = "False error"
-
-        # Code to execute no matter what (optional)
-
-        raw_timestamps = chart_data['timestamps']
-        timestamps = [datetime.fromtimestamp(t).astimezone(pytz.timezone('US/Eastern')) for t in raw_timestamps]
-        prices = chart_data['prices']
-
-        # test to see if graphc works, TODO make it abstracted
-        algoEMA = Ema_Algo()
-        algo_graph_data = backtest_results['algo_graph_data']
-        algo_graphs = algoEMA.export_graph(algo_graph_data)
-
-        buy_indices = backtest_results['buy_indices']
-        sell_indices = backtest_results['sell_indices']
-
-        buy_prices, buy_times = [], []
-        for i in buy_indices:
-                buy_prices.append(prices[i])
-                buy_times.append(timestamps[i])
-        sell_prices, sell_times = [], []
-        for i in sell_indices:
-                sell_prices.append(prices[i])
-                sell_times.append(timestamps[i])
-        buy_sell_scatters = [
-                go.Scatter(name='Buys', x=buy_times, y=buy_prices, line=dict(color='rgb(0, 0, 255)'), mode='markers', marker_size=10),
-                go.Scatter(name='Sells', x=sell_times, y=sell_prices, line=dict(color='rgb(255, 255, 0)'), mode='markers', marker_size=10)
-        ]
+def display_color(file_id):
+        # compute the results to show in the table
+        path = 'test-1-ema'
+        result_summary = compute_results(path, file_id)
+        if not result_summary:
+            return go.Figure(), go.Figure(), "No results found for the given file ID."
+        
+        print(result_summary)
+
+        table = go.Figure(
+                data = [go.Table(
+                        header=dict(values=["algo name", "algo params", "avg percent gain", "best stock order"]),
+                        cells=dict(values=result_summary)
+                )]
+        )
         data = fetch_chart_data_yahoo('XRP-USD', '1d', None, timedelta(weeks=52))
         times = [datetime.fromtimestamp(t).astimezone(pytz.timezone('US/Eastern')) for t in data['timestamps']]
         comp_scatter = go.Scatter(name='Price (yahoo)', x=times, y=data['prices'], line=dict(color='rgb(255, 0, 0)'), mode='lines')