Merge branch 'hackathon_fall_2023' of https://github.com/siftech/funman…

… into hackathon_fall_2023

auxiliary_packages/funman_demo/src/funman_demo/parameter_space_plotter.py

@@ -26,6 +26,7 @@ def __init__(
         alpha=0.2,
         plot_points=False,
         parameters=None,
+        dpi=100,
     ):
         if isinstance(parameter_space, ParameterSpace):
             self.ps = parameter_space
@@ -55,6 +56,7 @@ def __init__(
             Line2D([0], [0], color="g", lw=4, alpha=alpha),
             Line2D([0], [0], color="r", lw=4, alpha=alpha),
         ]
+        self.dpi = dpi
 
     def computeBounds(self, interval: Interval = Interval(lb=-2000, ub=2000)):
         box = Box(bounds={p: interval for p in self.parameters})
@@ -68,7 +70,7 @@ def initialize_figure(self):
             self.dim,
             self.dim,
             squeeze=False,
-            dpi=600,
+            dpi=self.dpi,
             figsize=(10, 10),
         )
         self.fig = fig

resources/cached/068cef77-839d-49be-9191-3502ee6d5240.json

@@ -361,7 +361,6 @@
             "num_steps": 2,
             "step_size": 1,
             "num_initial_boxes": 1,
-            "save_smtlib": "my.smt2",
             "dreal_precision": 0.001,
             "dreal_log_level": "off",
             "constraint_noise": 0.0,

scratch/hackathon/hackathon_fall_2023_demo_terarrium.py

@@ -64,8 +64,8 @@ def main():
                 "name": "epsilon",
                 "interval": {
                     "lb": 0.1368,
-                    #  "ub": 0.20520000000000002
-                    "ub": 0.18,
+                    "ub": 0.20520000000000002
+                    # "ub": 0.18,
                 },
                 "label": "all",
             },
@@ -109,8 +109,8 @@ def main():
                 "name": "theta",
                 "interval": {
                     "lb": 0.2968,
-                    #  "ub": 0.4452
-                    "ub": 0.4,
+                    "ub": 0.4452
+                    # "ub": 0.4,
                 },
                 "label": "all",
             },
@@ -180,7 +180,7 @@ def main():
             # {
             #     "name": "infected_maximum1",
             #     "variable": "Infected",
-            #     "interval": {"lb": 0.0, "ub":0.1},
+            #     "interval": {"lb": 1e-5},
             #     "timepoints": {"lb": 10, "ub": 10, "closed_upper_bound": True},
             # },
             # {
@@ -236,21 +236,21 @@ def main():
                             210,
                         ]
                     }
-                    # {"timepoints": [0, 10]}
+                    # {"timepoints": [0, 10, 20]}
                 ],
             }
         ],
         "config": {
             "use_compartmental_constraints": True,
             "normalization_constant": 1.0,
-            "tolerance": 0.1,
+            "tolerance": 0.2,
             "verbosity": 10,
             "dreal_mcts": True,
-            "save_smtlib": os.path.join(os.path.realpath(__file__), "./out"),
+            "save_smtlib": os.path.join(os.path.dirname(__file__), "./out"),
             "substitute_subformulas": False,
             "series_approximation_threshold": None,
-            "dreal_log_level": "info",
-            "dreal_precision": 1,
+            "dreal_log_level": "none",
+            "dreal_precision": 1e-1,
             "profile": False,
         },
     }
@@ -261,7 +261,7 @@ def main():
         request_dict,
         # REQUEST_PATH,
         description="SIDARTHE demo",
-        case_out_dir="./out",
+        case_out_dir=os.path.join(os.path.dirname(__file__), "./out"),
         dump_plot=True,
         parameters_to_plot=["theta", "epsilon", "timestep"],
         point_plot_config={

src/funman/api/run.py

@@ -256,15 +256,15 @@ def run_instance(
                 with open(outfile, "w") as f:
                     f.write(results.model_dump_json(by_alias=True))
                 if dump_plot:
-                    point_plot_filename = (
-                        f"{out_dir}/{work_unit.id}_points.png"
-                    )
-
                     points = results.parameter_space.points()
                     if len(points) > 0:
+                        point_plot_filename = (
+                            f"{out_dir}/{work_unit.id}_points.png"
+                        )
                         l.info(
-                        f"Creating plot of point trajectories: {point_plot_filename}"
+                            f"Creating plot of point trajectories: {point_plot_filename}"
                         )
+
                         points_to_plot = (
                             random.choices(
                                 points, k=min(len(points), num_points)
@@ -278,19 +278,21 @@ def run_instance(
                         plt.savefig(point_plot_filename)
                         plt.close()
 
-                    space_plot_filename = (
-                        f"{out_dir}/{work_unit.id}_parameter_space.png"
-                    )
-                    l.info(
-                        f"Creating plot of parameter space: {space_plot_filename}"
-                    )
-                    ParameterSpacePlotter(
-                        results.parameter_space,
-                        plot_points=False,
-                        parameters=parameters_to_plot,
-                    ).plot(show=True)
-                    plt.savefig(space_plot_filename)
-                    plt.close()
+                    boxes = results.parameter_space.boxes()
+                    if len(boxes) > 0:
+                        space_plot_filename = (
+                            f"{out_dir}/{work_unit.id}_parameter_space.png"
+                        )
+                        l.info(
+                            f"Creating plot of parameter space: {space_plot_filename}"
+                        )
+                        ParameterSpacePlotter(
+                            results.parameter_space,
+                            plot_points=False,
+                            parameters=parameters_to_plot,
+                        ).plot(show=False)
+                        plt.savefig(space_plot_filename)
+                        plt.close()
                 sleep(10)
             else:
                 results = self._worker.get_results(work_unit.id)

src/funman/config.py

@@ -3,6 +3,7 @@
 analysis.
 """
 import logging
+import os
 from typing import Optional, Union
 
 from pydantic import BaseModel, ConfigDict, field_validator, model_validator
@@ -106,4 +107,10 @@ def check_use_compartmental_constraints(self) -> "FUNMANConfig":
             assert (
                 self.normalization_constant
             ), "Need to set normalization_constant in configuration to enforce compartmental constraints.  The normalization_constant provides the population size used in the constraint upper bound."
+
+        if self.save_smtlib:
+            assert os.path.exists(
+                os.path.dirname(self.save_smtlib)
+            ), "save_smtlib option must be an existing path"
+
         return self