fix price normalization

app.ipynb

@@ -18,13 +18,6 @@
    "id": "5d3ea548",
    "metadata": {},
    "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "plot_prices: date_range=[None, None]\n"
-     ]
-    },
     {
      "data": {
       "text/html": [
@@ -40,7 +33,7 @@
        "        "
       ],
       "text/plain": [
-       "<IPython.lib.display.IFrame at 0x7f69486ff1c0>"
+       "<IPython.lib.display.IFrame at 0x7fd23f91ee60>"
       ]
      },
      "metadata": {},
@@ -51,21 +44,7 @@
      "output_type": "stream",
      "text": [
       "Selected tickers: AAPL, GOOGL, MSFT\n",
-      "Selected tickers: AAPL, GOOGL, MSFT\n",
-      "plot_prices: date_range=['1980-12-12', '2025-01-31']\n",
-      "Selected tickers: AAPL, GOOGL, MSFT\n",
-      "plot_prices: date_range=['1991-02-08 09:20', '2025-01-31']\n",
-      "Selected tickers: AAPL, GOOGL, MSFT\n",
-      "plot_prices: date_range=['1991-04-13 08:40', '2025-01-31']\n",
-      "Selected tickers: AAPL, GOOGL, MSFT\n",
-      "plot_prices: date_range=['1991-04-13 08:40', '2009-10-25 01:46:40']\n",
-      "Selected tickers: AAPL, GOOGL, MSFT\n",
-      "plot_prices: date_range=['1998-04-16 20:54:30.1644', '2005-03-24 20:59:54.675']\n",
-      "Selected tickers: AAPL, GOOGL, MSFT\n",
-      "['2004-03-24', '2005-03-24 20:59:54.675']\n",
-      "plot_prices: date_range=['2004-03-24', '2005-03-24 20:59:54.675']\n",
-      "Selected tickers: AAPL, GOOGL, MSFT\n",
-      "['2004-03-24', '2005-03-24 20:59:54.675']\n"
+      "Selected tickers: AAPL, GOOGL, MSFT\n"
      ]
     }
    ],

src/dash_app.py

@@ -1,8 +1,4 @@
-from datetime import timedelta
-
-import numpy as np
 from dash import Dash, Input, Output, State, ctx, dcc, html
-from dateutil import parser  # type: ignore
 
 from src.prices import get_historical_prices
 from src.style_elements import (
@@ -10,13 +6,13 @@ from src.style_elements import (
     setup_interval_buttons,
     setup_ticker_selection,
 )
-from src.utils import date_to_idx_range, get_date_range
+from src.utils import adjust_date_range, date_to_idx_range, get_date_range
 
 
 class NormalizedAssetPricesApp:
 
-    # TODO: add initial interval
-    def __init__(self, initial_tickers=["AAPL", "GOOGL", "MSFT"]):
+    # TODO: add initial interval via self.idx_range
+    def __init__(self, initial_tickers=["AAPL", "GOOGL", "MSFT"], initial_interval="1y"):
 
         self.setup_env(initial_tickers)
 
@@ -34,31 +30,18 @@ class NormalizedAssetPricesApp:
         self.rolling_changes = self.percentage_changes.rolling(window=251, min_periods=1).sum()
         self.timestamps = self.prices.index
         self.idx_range = [0, -1]
-        self.normalize_prices()
-        # TODO: this is horrible, pls fix
-        self.fig = plot_prices(
-            self.timestamps, self.prices, self.prices_normalized, self.rolling_changes, [None, None]
-        )
 
-    def normalize_prices(self):
-        idx0, idx1 = self.idx_range
-        date0, date1 = self.timestamps[idx0], self.timestamps[idx1]
-        price = self.prices.loc[date0]
-        self.prices_normalized = np.nan * self.prices
-        self.prices_normalized.loc[date0:date1] = 100 * (self.prices[date0:date1] / price - 1)
+        self.fig = plot_prices(self.timestamps, self.prices, self.rolling_changes, self.idx_range)
 
     def update_figure(self, date_range=[None, None]):
         idx_range = date_to_idx_range(self.timestamps, date_range)
-        # do not update the figure if the range is unchanged
         if idx_range != self.idx_range:
             self.idx_range = idx_range
-            self.normalize_prices()
             self.fig = plot_prices(
                 self.timestamps,
                 self.prices,
-                self.prices_normalized,
                 self.rolling_changes,
-                date_range,
+                idx_range,
             )
         return self.fig
 
@@ -107,22 +90,14 @@ class NormalizedAssetPricesApp:
             date_range = get_date_range(current_figure["layout"])
             triggered_id = ctx.triggered_id
             if triggered_id in self.interval_buttons_ids:
-                date_range = self.adjust_date_range(date_range, triggered_id)
-                print(date_range)
+                date_range = adjust_date_range(
+                    self.timestamps, self.interval_offsets, date_range, triggered_id
+                )
+                print(f"interval update: {date_range=}")
 
             fig = self.update_figure(date_range)
             return fig
 
-    # TODO: filter date_range=[None, None]
-    # UPD: might have fixed it by setting the initial idx range to [0, -1]
-    def adjust_date_range(self, date_range, button_id):
-        start_date, end_date = date_range
-        start_date = max(
-            parser.parse(end_date) - timedelta(days=self.interval_offsets[button_id]),
-            self.timestamps[0],
-        ).strftime("%Y-%m-%d")
-        return [start_date, end_date]
-
     def run(self, **kwargs):
         self.app.run_server(**kwargs)
 

src/style_elements.py

@@ -5,6 +5,7 @@ import plotly.graph_objects as go
 from dash import dcc, html
 
 from src.prices import get_available_tickers
+from src.utils import normalize_prices
 
 
 def setup_ticker_selection(initial_tickers):
@@ -64,8 +65,11 @@ def setup_interval_buttons():
     return interval_buttons_html, interval_buttons_ids, interval_offsets
 
 
-def plot_prices(timestamps, prices, prices_normalized, rolling_changes, date_range):
-    print(f"plot_prices: {date_range=}")
+def plot_prices(timestamps, prices, rolling_changes, idx_range):
+    idx0, idx1 = idx_range
+    date_range = [timestamps[idx0], timestamps[idx1]]
+    prices_normalized = normalize_prices(prices, date_range)
+
     fig = go.Figure()
 
     # rangeslider plot
@@ -88,7 +92,7 @@ def plot_prices(timestamps, prices, prices_normalized, rolling_changes, date_ran
         fig.add_trace(
             go.Scatter(
                 x=timestamps,
-                y=prices_normalized[asset],
+                y=100 * prices_normalized[asset],
                 line=dict(width=3, color=next(colors)),
                 name=asset,
                 xaxis="x2",
@@ -111,11 +115,11 @@ def plot_prices(timestamps, prices, prices_normalized, rolling_changes, date_ran
     # configure axes
     xaxis1_dict = dict(rangeslider=dict(visible=True, thickness=0.1), tickangle=-30, nticks=20)
     xaxis2_dict = dict(matches="x1", showticklabels=False)
-    if all(date_range):
-        xaxis1_dict["range"] = date_range
-        xaxis2_dict["range"] = date_range
+    xaxis1_dict["range"] = date_range
+    xaxis2_dict["range"] = date_range
     yaxis1_dict = dict(showticklabels=False)
     yaxis2_dict = dict(
+        autorange=True,
         title="relative price change",
         nticks=12,
         tickformat=".0f",

src/utils.py

@@ -1,3 +1,9 @@
+from datetime import timedelta
+
+import numpy as np
+from dateutil import parser  # type: ignore
+
+
 def date_to_idx_range(timestamps, date_range):
     idx_range = (
         timestamps.get_indexer(date_range, method="nearest").tolist()
@@ -18,3 +24,19 @@ def get_date_range(figure_layout):
     # else:
     #     print(figure_layout)
     return date_range
+
+
+def adjust_date_range(timestamps, interval_offsets, date_range, button_id):
+    start_date, end_date = date_range
+    start_date = max(
+        parser.parse(end_date) - timedelta(days=interval_offsets[button_id]),
+        timestamps[0],
+    ).strftime("%Y-%m-%d")
+    return [start_date, end_date]
+
+
+def normalize_prices(prices, date_range):
+    date0, date1 = date_range
+    prices_normalized = np.nan * prices
+    prices_normalized.loc[date0:date1] = prices[date0:date1] / prices.loc[date0] - 1
+    return prices_normalized