fix: correct plot oom (#591)

* fix: remove broken plotting tool

* fix: avoid empty legend warnings

* feat: add logging to plot calls

* fix: update error message for check tagged versions

scripts/check_tagged_versions.py

@@ -25,7 +25,9 @@ def check_versions():
             tagged_vega_versions.add(tag["name"][5:])
 
     if versions_to_check.difference(tagged_vega_versions):
-        raise Exception(f"Missing tags for vega versions: {versions_to_check}")
+        raise Exception(
+            f"Missing tags for vega versions: {versions_to_check - tagged_vega_versions}"
+        )
 
 
 if __name__ == "__main__":

vega_sim/tools/scenario_plots.py

@@ -28,6 +28,20 @@
 
 import numpy as np
 
+import logging
+from functools import wraps
+
+logger = logging.getLogger(__name__)
+
+
+def log_plotting_function(func):
+    @wraps(func)
+    def wrapped_fn(*args, **kwargs):
+        logger.info(f"Calling func {func.__name__}")
+        return func(*args, **kwargs)
+
+    return wrapped_fn
+
 
 TRADING_MODE_COLORS = {
     0: (200 / 255, 200 / 255, 200 / 255),
@@ -137,6 +151,7 @@ def _series_df_to_single_series(
     return df_clone.merge(selector, on=["time", "market_id"]).set_index("time")
 
 
+@log_plotting_function
 def plot_trading_summary(
     ax: Axes,
     trade_df: pd.DataFrame,
@@ -180,6 +195,7 @@ def plot_trading_summary(
     )
 
 
+@log_plotting_function
 def plot_total_traded_volume(ax: Axes, trades_df: pd.DataFrame) -> None:
     if trades_df.empty:
         return
@@ -191,13 +207,15 @@ def plot_total_traded_volume(ax: Axes, trades_df: pd.DataFrame) -> None:
     ax.plot(traded)
 
 
+@log_plotting_function
 def plot_open_interest(ax: Axes, market_data_df: pd.DataFrame):
     ax.set_title("Open Interest")
 
     _set_xticks(ax, market_data_df.index)
     ax.plot(market_data_df["open_interest"])
 
 
+@log_plotting_function
 def plot_open_notional(
     ax: Axes,
     market_data_df: pd.DataFrame,
@@ -211,6 +229,7 @@ def plot_open_notional(
     ax.plot(market_data_df["open_interest"] * price_df["price"])
 
 
+@log_plotting_function
 def plot_spread(ax: Axes, order_book_df: pd.DataFrame) -> None:
     if order_book_df.empty:
         return
@@ -229,6 +248,7 @@ def plot_spread(ax: Axes, order_book_df: pd.DataFrame) -> None:
     ax.plot(spread_df)
 
 
+@log_plotting_function
 def plot_margin_totals(ax: Axes, accounts_df: pd.DataFrame) -> None:
     if accounts_df.empty:
         return
@@ -243,6 +263,7 @@ def plot_margin_totals(ax: Axes, accounts_df: pd.DataFrame) -> None:
     ax.plot(grouped_df)
 
 
+@log_plotting_function
 def plot_target_stake(ax: Axes, market_data_df: pd.DataFrame) -> None:
     if market_data_df.empty:
         return
@@ -252,6 +273,7 @@ def plot_target_stake(ax: Axes, market_data_df: pd.DataFrame) -> None:
     ax.plot(market_data_df["target_stake"])
 
 
+@log_plotting_function
 def plot_run_outputs(run_name: Optional[str] = None) -> list[Figure]:
     order_df = load_order_book_df(run_name=run_name)
     trades_df = load_trades_df(run_name=run_name)
@@ -299,7 +321,7 @@ def plot_run_outputs(run_name: Optional[str] = None) -> list[Figure]:
         ax6 = plt.subplot(427)
         ax7 = plt.subplot(428)
 
-        plot_trading_summary(ax, market_trades_df, market_order_df, market_mid_df)
+        # plot_trading_summary(ax, market_trades_df, market_order_df, market_mid_df)
         plot_total_traded_volume(ax2, market_trades_df)
         plot_spread(ax3, order_book_df=market_order_df)
         plot_open_interest(ax4, market_data_df)
@@ -312,6 +334,7 @@ def plot_run_outputs(run_name: Optional[str] = None) -> list[Figure]:
     return figs
 
 
+@log_plotting_function
 def plot_trading_mode(
     fig: Figure, data_df: pd.DataFrame, ss: Optional[SubplotSpec] = None
 ):
@@ -391,6 +414,7 @@ def plot_trading_mode(
     ax1.legend(labels=names, loc="lower right")
 
 
+@log_plotting_function
 def plot_price_comparison(
     fig: Figure,
     data_df: pd.DataFrame,
@@ -450,6 +474,7 @@ def plot_price_comparison(
     ax0.legend(labels=["external price", "mark price"])
 
 
+@log_plotting_function
 def plot_risky_close_outs(
     fig: Figure,
     accounts_df: pd.DataFrame,
@@ -547,6 +572,7 @@ def plot_risky_close_outs(
     ax1r.ticklabel_format(axis="y", style="sci", scilimits=(0, 0))
 
 
+@log_plotting_function
 def fuzz_plots(run_name: Optional[str] = None) -> Figure:
     data_df = load_market_data_df(run_name=run_name)
     accounts_df = load_accounts_df(run_name=run_name)
@@ -606,6 +632,7 @@ def fuzz_plots(run_name: Optional[str] = None) -> Figure:
     return figs
 
 
+@log_plotting_function
 def account_plots(run_name: Optional[str] = None, agent_types: Optional[list] = None):
     accounts_df = load_accounts_df(run_name=run_name)
     agents_df = load_agents_df(run_name=run_name)
@@ -657,6 +684,7 @@ def account_plots(run_name: Optional[str] = None, agent_types: Optional[list] =
     return fig
 
 
+@log_plotting_function
 def plot_price_monitoring(
     run_name: Optional[str] = None,
     fig: Optional[Figure] = None,
@@ -815,6 +843,7 @@ def plot_price_monitoring(
     return figs
 
 
+@log_plotting_function
 def resource_monitoring_plot(run_name: Optional[str] = None):
     resource_df = load_resource_df(
         run_name=run_name,
@@ -878,6 +907,7 @@ def resource_monitoring_plot(run_name: Optional[str] = None):
     return fig
 
 
+@log_plotting_function
 def reward_plots(run_name: Optional[str] = None):
     accounts_df = load_accounts_df(run_name=run_name)
     assets_df = load_assets_df(run_name=run_name)
@@ -966,6 +996,8 @@ def reward_plots(run_name: Optional[str] = None):
         axs[-1].set_title(f"Asset: {plot[2]}")
         accounts_for_asset = joined_df[joined_df.symbol == str(plot[2])]
         grouped = accounts_for_asset.groupby(["agent_type", "time"])["balance"].sum()
+        if len(grouped.index.get_level_values(0).unique().values) == 1:
+            continue
         for index in grouped.index.get_level_values(0).unique():
             if index == "RewardFunder":
                 continue
@@ -978,6 +1010,7 @@ def reward_plots(run_name: Optional[str] = None):
     return fig
 
 
+@log_plotting_function
 def plot_account_by_party(
     run_name: Optional[str] = None,
     fig: Optional[Figure] = None,
@@ -1059,6 +1092,7 @@ def plot_account_by_party(
     axs[-1].legend()
 
 
+@log_plotting_function
 def sla_plot(run_name: Optional[str] = None):
     accounts_df = load_accounts_df(run_name=run_name)
     ledger_entries_df = load_ledger_entries_df(run_name=run_name)
@@ -1205,6 +1239,7 @@ def determine_poi(row):
     return fig
 
 
+@log_plotting_function
 def price_series_plot(
     run_name: Optional[str] = None,
     fig: Optional[Figure] = None,
@@ -1296,6 +1331,7 @@ def price_series_plot(
     return fig
 
 
+@log_plotting_function
 def liquidation_plot(
     run_name: Optional[str] = None,
     fig: Optional[Figure] = None,
@@ -1448,6 +1484,7 @@ def liquidation_plot(
     return fig
 
 
+@log_plotting_function
 def plot_overlay_auctions(ax: Axes, chained_market_data: pd.DataFrame):
     twinx = ax.twinx()
     twinx.set_ylim(0, 1)
@@ -1548,5 +1585,4 @@ def plot_overlay_auctions(ax: Axes, chained_market_data: pd.DataFrame):
             fig.savefig(f"{dir}/price.jpg")
 
     if args.show:
-        plt.ion()
         plt.show()