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This commit is contained in:
Dobromir Popov 2025-02-04 22:23:23 +02:00
parent f32f648bf0
commit 907468239a
1 changed files with 19 additions and 9 deletions
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28
crypto/brian/index-deep-new.py
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@ -22,6 +22,18 @@ import matplotlib.dates as mdates
from dotenv import load_dotenv
load_dotenv()
# --- Helper Function for Timestamp Conversion ---
def convert_timestamp(ts):
"""
Safely converts a timestamp to a datetime object.
If the timestamp is abnormally high (i.e. in milliseconds),
it is divided by 1000.
"""
ts = float(ts)
if ts > 1e10: # Likely in milliseconds
ts = ts / 1000.0
return datetime.fromtimestamp(ts)
# --- Directories ---
LAST_DIR = os.path.join("models", "last")
BEST_DIR = os.path.join("models", "best")
@ -219,11 +231,10 @@ def load_best_checkpoint(model, best_dir=BEST_DIR):
old_embed = old_state["timeframe_embed.weight"]
new_embed = new_state["timeframe_embed.weight"]
if old_embed.shape[0] < new_embed.shape[0]:
# Copy the available rows and keep the remaining as initialized.
new_embed[:old_embed.shape[0]] = old_embed
old_state["timeframe_embed.weight"] = new_embed
# For channel_branches, if there are missing keys, load_state_dict with strict=False.
# For channel_branches, missing keys are handled by strict=False.
model.load_state_dict(old_state, strict=False)
return checkpoint
@ -232,7 +243,7 @@ def update_live_html(candles, trade_history, epoch):
"""
Generate a chart image that uses actual timestamps on the x-axis
and shows a cumulative epoch PnL. The chart (with buy/sell markers and dotted lines)
is embedded in an HTML page that auto-refreshes every 10 seconds.
is embedded in an HTML page that auto-refreshes every 1 seconds.
"""
from io import BytesIO
import base64
@ -252,7 +263,7 @@ def update_live_html(candles, trade_history, epoch):
<html>
<head>
<meta charset="utf-8">
<meta http-equiv="refresh" content="10">
<meta http-equiv="refresh" content="1">
<title>Live Trading Chart - Epoch {epoch}</title>
<style>
body {{
@ -291,15 +302,15 @@ def update_live_chart(ax, candles, trade_history):
Mark BUY (green) and SELL (red) actions, and draw dotted lines between entry and exit.
"""
ax.clear()
# Convert timestamps to datetime objects.
times = [datetime.fromtimestamp(candle["timestamp"]) for candle in candles]
# Use the helper to convert timestamps safely.
times = [convert_timestamp(candle["timestamp"]) for candle in candles]
close_prices = [candle["close"] for candle in candles]
ax.plot(times, close_prices, label="Close Price", color="black", linewidth=1)
# Format x-axis date labels.
ax.xaxis.set_major_formatter(mdates.DateFormatter('%H:%M:%S'))
for trade in trade_history:
entry_time = datetime.fromtimestamp(candles[trade["entry_index"]]["timestamp"])
exit_time = datetime.fromtimestamp(candles[trade["exit_index"]]["timestamp"])
entry_time = convert_timestamp(candles[trade["entry_index"]]["timestamp"])
exit_time = convert_timestamp(candles[trade["exit_index"]]["timestamp"])
in_price = trade["entry_price"]
out_price = trade["exit_price"]
ax.plot(entry_time, in_price, marker="^", color="green", markersize=10, label="BUY")
@ -518,7 +529,6 @@ async def main():
except Exception as e:
print("Failed to load optimizer state due to:", e)
print("Deleting all checkpoints and starting fresh.")
# Delete checkpoint files.
for chk_dir in [LAST_DIR, BEST_DIR]:
for f in os.listdir(chk_dir):
os.remove(os.path.join(chk_dir, f))