Adding ohlcv and fixed point plots

lib/chainsync/bin/run_hyperdrive_dashboard.py

@@ -5,7 +5,15 @@
 
 import mplfinance as mpf
 import streamlit as st
-from chainsync.dashboard import build_leaderboard, build_ticker, get_user_lookup, plot_fixed_rate, plot_ohlcv
+from chainsync.dashboard import (
+    build_fixed_rate,
+    build_leaderboard,
+    build_ohlcv,
+    build_ticker,
+    get_user_lookup,
+    plot_fixed_rate,
+    plot_ohlcv,
+)
 from chainsync.db.base import get_user_map, initialize_session
 from chainsync.db.hyperdrive import get_all_traders, get_pool_analysis, get_pool_config, get_ticker, get_wallet_pnl
 from ethpy import build_eth_config
@@ -49,19 +57,20 @@
     # Adds user lookup to the ticker
     display_ticker = build_ticker(ticker, user_lookup)
 
-    # TODO get wallet pnl and calculate leaderboard
+    # get wallet pnl and calculate leaderboard
     wallet_pnl = get_wallet_pnl(session, start_block=-max_live_blocks, coerce_float=False)
     # Get the latest updated block
     latest_wallet_pnl = wallet_pnl[wallet_pnl["blockNumber"] == wallet_pnl["blockNumber"].max()]
-
     comb_rank, ind_rank = build_leaderboard(latest_wallet_pnl, user_lookup)
 
-    # TODO calculate ohlcv and volume
-    # ohlcv = calc_ohlcv(combined_data, config_data, freq="5T")
+    # build ohlcv and volume
+    ohlcv = build_ohlcv(pool_analysis, freq="5T")
+    # build fixed rate
+    fixed_rate = build_fixed_rate(pool_analysis)
 
     with ticker_placeholder.container():
         st.header("Ticker")
-        st.dataframe(ticker, height=200, use_container_width=True)
+        st.dataframe(display_ticker, height=200, use_container_width=True)
         st.header("Total Leaderboard")
         st.dataframe(comb_rank, height=500, use_container_width=True)
         st.header("Wallet Leaderboard")
@@ -74,7 +83,7 @@
         ax_fixed_rate.clear()
 
         plot_ohlcv(ohlcv, ax_ohlcv, ax_vol)
-        plot_fixed_rate(fixed_rate_x, fixed_rate_y, ax_fixed_rate)
+        plot_fixed_rate(fixed_rate, ax_fixed_rate)
 
         ax_ohlcv.tick_params(axis="both", which="both")
         ax_vol.tick_params(axis="both", which="both")

lib/chainsync/chainsync/dashboard/__init__.py

@@ -1,8 +1,10 @@
 """Dashboard utilities"""
 
+from .build_fixed_rate import build_fixed_rate
 from .build_leaderboard import build_leaderboard
+from .build_ohlcv import build_ohlcv
 from .build_ticker import build_ticker
 from .extract_data_logs import get_combined_data, read_json_to_pd
 from .plot_fixed_rate import plot_fixed_rate
-from .plot_ohlcv import calc_ohlcv, plot_ohlcv
+from .plot_ohlcv import plot_ohlcv
 from .usernames import address_to_username, combine_usernames, get_user_lookup

lib/chainsync/chainsync/dashboard/build_fixed_rate.py

@@ -0,0 +1,3 @@
+def build_fixed_rate(pool_analysis):
+    fixed_rate = pool_analysis[["timestamp", "fixed_rate"]]
+    return fixed_rate

lib/chainsync/chainsync/dashboard/build_ohlcv.py

@@ -0,0 +1,27 @@
+from decimal import Decimal
+
+import pandas as pd
+
+
+def build_ohlcv(pool_analysis, freq="D"):
+    """
+    freq var: https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases
+    """
+    # TODO get volume from pool_analysis
+    # fixme hacking it in for now
+    pool_analysis["trade_volume"] = Decimal(1)
+
+    spot_prices = pool_analysis[["timestamp", "spot_price", "trade_volume"]].copy()
+    spot_prices = spot_prices.set_index("timestamp")
+
+    # TODO this is filling groups without data with nans, is this desired?
+    ohlcv = spot_prices.groupby([pd.Grouper(freq=freq)]).agg(
+        {"spot_price": ["first", "last", "max", "min"], "trade_volume": "sum"}
+    )
+
+    ohlcv.columns = ["Open", "Close", "High", "Low", "Volume"]
+    ohlcv.index.name = "Date"
+    # ohlcv must be floats
+    ohlcv = ohlcv.astype(float)
+
+    return ohlcv

lib/chainsync/chainsync/dashboard/plot_fixed_rate.py

@@ -5,9 +5,9 @@
 from matplotlib import ticker as mpl_ticker
 
 
-def plot_fixed_rate(x_data, y_data, axes):
+def plot_fixed_rate(data, axes):
     """Returns the fixed rate plot"""
-    axes.plot(x_data, y_data)
+    axes.plot(data["timestamp"], data["fixed_rate"])
     # change y-axis unit format to 0.1%
     axes.yaxis.set_major_formatter(mpl_ticker.FuncFormatter(lambda x, p: format(x, "0.3%")))
     axes.yaxis.set_label_position("right")

lib/chainsync/chainsync/dashboard/plot_ohlcv.py

@@ -2,8 +2,6 @@
 from __future__ import annotations
 
 import mplfinance as mpf
-import pandas as pd
-from chainsync.analysis.calc_spot_price import calc_spot_price
 
 
 def plot_ohlcv(ohlcv, ohlcv_ax, vol_ax):
@@ -22,36 +20,4 @@ def plot_ohlcv(ohlcv, ohlcv_ax, vol_ax):
         vol_ax.yaxis.set_label_position("right")
         vol_ax.yaxis.tick_right()
 
-
-def calc_ohlcv(trade_data, config_data, freq="D"):
-    """
-    freq var: https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases
-    """
-    spot_prices = (
-        calc_spot_price(
-            trade_data["share_reserves"],
-            trade_data["bond_reserves"],
-            config_data["initialSharePrice"],
-            config_data["invTimeStretch"],
-        )
-        .to_frame()
-        .astype(float)
-    )
-
-    spot_prices.columns = ["spot_price"]
-    value = trade_data["value"]
-
-    spot_prices["value"] = value
-    spot_prices["timestamp"] = trade_data["timestamp"]
-    spot_prices = spot_prices.set_index("timestamp")
-
-    ohlcv = spot_prices.groupby([pd.Grouper(freq=freq)]).agg(
-        {"spot_price": ["first", "last", "max", "min"], "value": "sum"}
-    )
-
-    ohlcv.columns = ["Open", "Close", "High", "Low", "Volume"]
-    ohlcv.index.name = "Date"
-
-    return ohlcv
-
     # format x-axis as time

lib/chainsync/chainsync/db/hyperdrive/interface.py

@@ -683,7 +683,10 @@ def get_pool_analysis(
     DataFrame
         A DataFrame that consists of the queried pool info data
     """
-    query = session.query(PoolAnalysis)
+    if return_timestamp:
+        query = session.query(PoolInfo.timestamp, PoolAnalysis)
+    else:
+        query = session.query(PoolAnalysis)
 
     # Support for negative indices
     if (start_block is not None) and (start_block < 0):
@@ -698,6 +701,7 @@ def get_pool_analysis(
 
     if return_timestamp:
         # TODO query from PoolInfo the timestamp
+        query = query.join(PoolInfo, PoolAnalysis.blockNumber == PoolInfo.blockNumber)
         pass
 
     # Always sort by block in order