Issue #749 - Use streamlit to display graphs in sim plotter

pdr_backend/cli/cli_module.py

@@ -1,5 +1,6 @@
-import os
 import logging
+import os
+import subprocess
 import sys
 
 from enforce_typing import enforce_types
@@ -10,12 +11,11 @@
     get_predictoors_info_main,
     get_traction_info_main,
 )
-from pdr_backend.cli.cli_arguments import (
-    do_help_long,
-    get_arg_parser,
-    print_args,
-)
+from pdr_backend.cli.cli_arguments import do_help_long, get_arg_parser, print_args
+from pdr_backend.deployer.deployer import main as deployer_main
 from pdr_backend.dfbuyer.dfbuyer_agent import DFBuyerAgent
+from pdr_backend.lake.etl import ETL
+from pdr_backend.lake.gql_data_factory import GQLDataFactory
 from pdr_backend.lake.ohlcv_data_factory import OhlcvDataFactory
 from pdr_backend.payout.payout import do_ocean_payout, do_rose_payout
 from pdr_backend.ppss.ppss import PPSS
@@ -25,13 +25,10 @@
 from pdr_backend.trader.approach1.trader_agent1 import TraderAgent1
 from pdr_backend.trader.approach2.trader_agent2 import TraderAgent2
 from pdr_backend.trueval.trueval_agent import TruevalAgent
-from pdr_backend.util.topup import topup_main
 from pdr_backend.util.core_accounts import fund_accounts_with_OCEAN
 from pdr_backend.util.currency_types import Eth
-from pdr_backend.util.web3_accounts import create_accounts, view_accounts, fund_accounts
-from pdr_backend.lake.gql_data_factory import GQLDataFactory
-from pdr_backend.lake.etl import ETL
-from pdr_backend.deployer.deployer import main as deployer_main
+from pdr_backend.util.topup import topup_main
+from pdr_backend.util.web3_accounts import create_accounts, fund_accounts, view_accounts
 
 logger = logging.getLogger("cli")
 
@@ -46,6 +43,11 @@ def _do_main():
     if func is None:
         do_help_long(1)
 
+    if sys.argv[1] == "sim" and sys.argv[0] != "streamlit_entrypoint.py":
+        streamlit_args = ["streamlit", "run", "streamlit_entrypoint.py"] + sys.argv[1:]
+        subprocess.run(streamlit_args, check=False)
+        return
+
     parser = get_arg_parser(func_name)
     args, nested_args = parser.parse_known_args()
     print_args(args)

pdr_backend/sim/sim_plotter.py

@@ -1,9 +1,9 @@
 from typing import List
 
-from enforce_typing import enforce_types
-from matplotlib import gridspec
 import matplotlib.pyplot as plt
 import numpy as np
+import streamlit
+from enforce_typing import enforce_types
 from numpy.random import random
 
 from pdr_backend.aimodel.aimodel_plotdata import AimodelPlotdata
@@ -15,6 +15,9 @@
 from pdr_backend.sim.sim_state import SimState
 from pdr_backend.util.constants import FONTSIZE
 
+streamlit.set_page_config(layout="wide")
+
+
 HEIGHT = 7.5
 WIDTH = int(HEIGHT * 3.2)
 
@@ -31,28 +34,33 @@ def __init__(
         self.st = st
         self.ppss = ppss
 
+        plt.close("all")
+
         # so labels are above lines. Must be before figure()
         plt.rcParams["axes.axisbelow"] = False
 
-        # figure, subplots
-        fig = plt.figure()
-        self.fig = fig
-
-        gs = gridspec.GridSpec(2, 6, width_ratios=[5, 1, 2, 0.6, 2, 3])
-
-        self.ax_pdr_profit_vs_time = fig.add_subplot(gs[0, 0])
-        self.ax_trader_profit_vs_time = fig.add_subplot(gs[1, 0])
-
-        self.ax_pdr_profit_vs_ptrue = fig.add_subplot(gs[0, 1])
-        self.ax_trader_profit_vs_ptrue = fig.add_subplot(gs[1, 1])
-
-        self.ax_accuracy_vs_time = fig.add_subplot(gs[0, 2])
-        self.ax_f1_precision_recall_vs_time = fig.add_subplot(gs[1, 2])
-
-        # col 3 is empty, for overflow of aimodel_varimps's y-axis labels
-        self.ax_aimodel_varimps = fig.add_subplot(gs[:, 4])
-
-        self.ax_aimodel_response = fig.add_subplot(gs[:, 5])
+        c1, c2, c3 = streamlit.columns((1, 2, 1))
+        c11, c12 = c1.container(), c1.container()
+        c31, c32 = c3.container(), c3.container()
+        c4, c5 = streamlit.columns((1, 1))
+
+        self.canvas = {
+            "pdr_profit_vs_time": c11.empty(),
+            "trader_profit_vs_time": c12.empty(),
+            "accuracy_vs_time": c2.empty(),
+            "pdr_profit_vs_ptrue": c31.empty(),
+            "trader_profit_vs_ptrue": c32.empty(),
+            "aimodel_varimps": c4.empty(),
+            "aimodel_response": c5.empty(),
+            "f1_precision_recall_vs_time": streamlit.empty(),
+        }
+
+        self.figs = {}
+
+        for k, _ in self.canvas.items():
+            fig, ax = plt.subplots()
+            self.figs[k] = fig
+            setattr(self, f"ax_{k}", ax)
 
         # attributes to help update plots' state quickly
         self.N: int = 0
@@ -61,10 +69,6 @@ def __init__(
 
         self.plotted_before: bool = False
 
-        # push plot to screen
-        plt.ion()
-        plt.show()
-
     # pylint: disable=too-many-statements
     @enforce_types
     def make_plot(self, aimodel_plotdata: AimodelPlotdata):
@@ -90,12 +94,13 @@ def make_plot(self, aimodel_plotdata: AimodelPlotdata):
         self._plot_aimodel_response(aimodel_plotdata)
 
         # final pieces
-        self.fig.set_size_inches(WIDTH, HEIGHT)
-        self.fig.tight_layout(pad=0.5, h_pad=1.0, w_pad=1.0)
-        plt.subplots_adjust(wspace=0.3)
+        # plt.subplots_adjust(wspace=0.3)
         plt.pause(0.001)
         self.plotted_before = True
 
+        plt.ion()
+        plt.show()
+
     @property
     def next_x(self) -> List[float]:
         return _slice(self.x, self.N_done, self.N)
@@ -114,11 +119,13 @@ def _plot_pdr_profit_vs_time(self):
         ax.plot(self.next_hx, [0, 0], c="0.2", ls="--", lw=1)
         s = f"Predictoor profit vs time. Current:{y00[-1]:.2f} OCEAN"
         _set_title(ax, s)
+
+        self.canvas["pdr_profit_vs_time"].pyplot(self.figs["pdr_profit_vs_time"])
+
         if not self.plotted_before:
             ax.set_ylabel("predictoor profit (OCEAN)", fontsize=FONTSIZE)
             ax.set_xlabel("time", fontsize=FONTSIZE)
             _ylabel_on_right(ax)
-            ax.margins(0.005, 0.05)
 
     @enforce_types
     def _plot_trader_profit_vs_time(self):
@@ -128,6 +135,8 @@ def _plot_trader_profit_vs_time(self):
         ax.plot(self.next_x, next_y10, c="b")
         ax.plot(self.next_hx, [0, 0], c="0.2", ls="--", lw=1)
         _set_title(ax, f"Trader profit vs time. Current: ${y10[-1]:.2f}")
+
+        self.canvas["trader_profit_vs_time"].pyplot(self.figs["trader_profit_vs_time"])
         if not self.plotted_before:
             ax.set_xlabel("time", fontsize=FONTSIZE)
             ax.set_ylabel("trader profit (USD)", fontsize=FONTSIZE)
@@ -149,6 +158,8 @@ def _plot_accuracy_vs_time(self):
         s = f"accuracy = {clm.acc_ests[-1]*100:.2f}% "
         s += f"[{clm.acc_ls[-1]*100:.2f}%, {clm.acc_us[-1]*100:.2f}%]"
         _set_title(ax, s)
+
+        self.canvas["accuracy_vs_time"].pyplot(self.figs["accuracy_vs_time"])
         if not self.plotted_before:
             ax.set_xlabel("time", fontsize=FONTSIZE)
             ax.set_ylabel("% correct [lower, upper bound]", fontsize=FONTSIZE)
@@ -173,6 +184,9 @@ def _plot_f1_precision_recall_vs_time(self):
         s += f" [recall={clm.recalls[-1]:.4f}"
         s += f", precision={clm.precisions[-1]:.4f}]"
         _set_title(ax, s)
+        self.canvas["f1_precision_recall_vs_time"].pyplot(
+            self.figs["f1_precision_recall_vs_time"]
+        )
         if not self.plotted_before:
             ax.set_xlabel("time", fontsize=FONTSIZE)
             ax.set_ylabel("f1 [recall, precision]", fontsize=FONTSIZE)
@@ -195,6 +209,8 @@ def _plot_pdr_profit_vs_ptrue(self):
         s = f"pdr profit dist. avg={avg:.2f} OCEAN"
         _set_title(ax, s)
         ax.plot([0.5, 0.5], [mnp, mxp], c="0.2", ls="-", lw=1)
+
+        self.canvas["pdr_profit_vs_ptrue"].pyplot(self.figs["pdr_profit_vs_ptrue"])
         if not self.plotted_before:
             ax.plot([0.0, 1.0], [0, 0], c="0.2", ls="--", lw=1)
             _set_xlabel(ax, "prob(up)")
@@ -218,6 +234,10 @@ def _plot_trader_profit_vs_ptrue(self):
 
         _set_title(ax, s)
         ax.plot([0.5, 0.5], [mnp, mxp], c="0.2", ls="-", lw=1)
+
+        self.canvas["trader_profit_vs_ptrue"].pyplot(
+            self.figs["trader_profit_vs_ptrue"]
+        )
         if not self.plotted_before:
             ax.plot([0.0, 1.0], [0, 0], c="0.2", ls="--", lw=1)
             _set_xlabel(ax, "prob(up)")
@@ -227,16 +247,20 @@ def _plot_trader_profit_vs_ptrue(self):
 
     @enforce_types
     def _plot_aimodel_varimps(self, d: AimodelPlotdata):
-        ax = self.ax_aimodel_varimps
+        ax = self.ax_aimodel_varimps  # type: ignore[attr-defined]
         imps_tups = d.model.importance_per_var(include_stddev=True)
-        plot_aimodel_varimps(d.colnames, imps_tups, (self.fig, ax))
+        plot_aimodel_varimps(d.colnames, imps_tups, (self.figs["aimodel_varimps"], ax))
+
+        self.canvas["aimodel_varimps"].pyplot(self.figs["aimodel_varimps"])
         if not self.plotted_before:
             ax.margins(0.01, 0.01)
 
     @enforce_types
     def _plot_aimodel_response(self, d: AimodelPlotdata):
-        ax = self.ax_aimodel_response
-        plot_aimodel_response(d, (self.fig, ax))
+        ax = self.ax_aimodel_response  # type: ignore[attr-defined]
+        plot_aimodel_response(d, (self.figs["aimodel_varimps"], ax))
+
+        self.canvas["aimodel_response"].pyplot(self.figs["aimodel_response"])
         if not self.plotted_before:
             ax.margins(0.01, 0.01)
 

setup.py

@@ -39,6 +39,7 @@
     "types-requests==2.31.0.20240311",
     "web3==6.15.1",
     "sapphire.py==0.2.2",
+    "streamlit==1.32.1",
     "ocean-contracts==2.0.0a14",  # install this last
 ]
 

streamlit_entrypoint.py

@@ -0,0 +1,6 @@
+#!/usr/bin/env python
+
+from pdr_backend.cli import cli_module
+
+if __name__ == "__main__":
+    cli_module._do_main()