diff --git a/.gitignore b/.gitignore
index 99026b4e..99955825 100644
--- a/.gitignore
+++ b/.gitignore
@@ -315,3 +315,4 @@ gmon.out
unsat.core
.gitignore
core.dimacs
+notebooks/saved-results/out
diff --git a/auxiliary_packages/funman_demo/src/funman_demo/generators/halfar.py b/auxiliary_packages/funman_demo/src/funman_demo/generators/halfar.py
new file mode 100644
index 00000000..4008a2ae
--- /dev/null
+++ b/auxiliary_packages/funman_demo/src/funman_demo/generators/halfar.py
@@ -0,0 +1,298 @@
+"""
+This script will generate instances of the Halfar ice model as Petrinet AMR models. The options control the number of discretization points.
+"""
+
+import argparse
+import os
+from decimal import Decimal
+from typing import Dict, List, Tuple
+
+from pydantic import AnyUrl, BaseModel
+
+from funman.model.generated_models.petrinet import (
+ Distribution,
+ Header,
+ Initial,
+ Model,
+ Model1,
+ OdeSemantics,
+ Parameter,
+ Properties,
+ Rate,
+ Semantics,
+ State,
+ Time,
+ Transition,
+ Unit,
+)
+from funman.representation.interval import Interval
+
+
+class HalfarModel(Model):
+ pass
+
+
+class Direction:
+ Negative: str = "negative"
+ Positive: str = "positive"
+
+
+class Coordinate(BaseModel):
+ """
+ Coordinates are N-D points in Cartesian space, as denoted by the vector attribute. The neighbors are coordinates that are at the next point in each direction.
+ """
+
+ vector: List[float]
+ id: str
+ neighbors: Dict[str, "Coordinate"] = {}
+
+
+class HalfarGenerator:
+ """
+ This generator class constructs the AMR instance. The coordinates are equally spaced across the range.
+ """
+
+ range: Interval = Interval(lb=-2.0, ub=2.0)
+
+ def coordinates(self, args) -> List[Coordinate]:
+ """
+ Generate coordinates for the range.
+ """
+ coords = []
+ step_size = value = self.range.width() / Decimal(
+ int(args.num_discretization_points) - 1
+ )
+ for i in range(args.num_discretization_points):
+ value = self.range.lb + float(step_size * i)
+ coords.append(Coordinate(vector=[value], id=str(i)))
+ for i, coord in enumerate(coords):
+ coord.neighbors[Direction.Negative] = (
+ coords[i - 1] if i > 0 else None
+ )
+ coord.neighbors[Direction.Positive] = (
+ coords[i + 1] if i < len(coords) - 1 else None
+ )
+ return coords
+
+ def transition_expression(
+ self, n1_name: str, n2_name: str, negative=False
+ ) -> str:
+ """
+ Custom rate change
+ """
+ prefix = "-1*" if negative else ""
+ gamma = "(2/(n+2))*A*(rho*g)**n"
+ return f"{prefix}{gamma}*(({n2_name}-{n1_name})**3)*({n1_name}**5)"
+
+ def neighbor_gradient(
+ self, coordinate: Coordinate, coordinates: List[Coordinate]
+ ) -> Tuple[List[Transition], List[Rate]]:
+ """
+ Find a triple of coordinates (n0, n1, n2) that are ordered so that dx = n2-n1 and dx = n1-n0 is positive
+ """
+ if (
+ coordinate.neighbors[Direction.Positive]
+ and coordinate.neighbors[Direction.Negative]
+ ):
+ n0 = coordinate.neighbors[Direction.Negative]
+ elif (
+ coordinate.neighbors[Direction.Positive]
+ and not coordinate.neighbors[Direction.Negative]
+ ):
+ n0 = coordinate
+ elif (
+ not coordinate.neighbors[Direction.Positive]
+ and coordinate.neighbors[Direction.Negative]
+ ):
+ n0 = coordinate.neighbors[Direction.Negative].neighbors[
+ Direction.Negative
+ ]
+ else:
+ raise Exception(
+ "Cannot determine the gradient of a coordinate with no neighbors"
+ )
+ n1 = n0.neighbors[Direction.Positive]
+ n2 = n1.neighbors[Direction.Positive]
+
+ w_p_name = f"w_p_{coordinate.id}"
+ w_n_name = f"w_n_{coordinate.id}"
+ n0_name = f"h_{n0.id}"
+ n1_name = f"h_{n1.id}"
+ n2_name = f"h_{n2.id}"
+ h_name = f"h_{coordinate.id}"
+
+ # tp is the gradient wrt. n2, n1
+ tp = Transition(
+ id=w_p_name,
+ input=[n2_name, n1_name],
+ output=[h_name],
+ properties=Properties(name=w_p_name),
+ )
+
+ # tn is the gradient wrt. n1, n0
+ tn = Transition(
+ id=w_n_name,
+ input=[n1_name, n0_name],
+ output=[h_name],
+ properties=Properties(name=w_n_name),
+ )
+
+ transitions = [tp, tn]
+
+ tpr = Rate(
+ target=w_p_name,
+ expression=self.transition_expression(n1_name, n2_name),
+ )
+ tnr = Rate(
+ target=w_n_name,
+ expression=self.transition_expression(
+ n0_name, n1_name, negative=True
+ ),
+ )
+
+ rates = [tpr, tnr]
+ return transitions, rates
+
+ def model(self, args) -> Tuple[Model1, Semantics]:
+ """
+ Generate the AMR Model
+ """
+ coordinates = self.coordinates(args)
+
+ # Create a height variable at each coordinate
+ states = [
+ State(id=f"h_{i}", name=f"h_{i}", description=f"height at {i}")
+ for i in range(len(coordinates))
+ ]
+
+ transitions = []
+ rates = []
+ for coordinate in coordinates[1:-1]:
+ coord_transitions, trans_rates = self.neighbor_gradient(
+ coordinate, coordinates
+ )
+ transitions += coord_transitions
+ rates += trans_rates
+
+ time = Time(
+ id="t",
+ units=Unit(expression="day", expression_mathml="day"),
+ )
+
+ initials = [
+ Initial(
+ target=f"h_{c.id}",
+ expression=(
+ "0.0"
+ if (c == coordinates[0] or c == coordinates[-1])
+ else f"{1.0/(1.0+abs(c.vector[0]))}"
+ ),
+ )
+ for c in coordinates
+ ]
+
+ parameters = [
+ Parameter(
+ id="n",
+ value=3.0,
+ distribution=Distribution(
+ type="StandardUniform1",
+ parameters={"minimum": 3.0, "maximum": 3.0},
+ ),
+ ),
+ Parameter(
+ id="rho",
+ value=910.0,
+ distribution=Distribution(
+ type="StandardUniform1",
+ parameters={"minimum": 910.0, "maximum": 910.0},
+ ),
+ ),
+ Parameter(
+ id="g",
+ value=9.8,
+ distribution=Distribution(
+ type="StandardUniform1",
+ parameters={"minimum": 9.8, "maximum": 9.8},
+ ),
+ ),
+ Parameter(
+ id="A",
+ value=1e-16,
+ distribution=Distribution(
+ type="StandardUniform1",
+ parameters={"minimum": 1e-20, "maximum": 1e-12},
+ ),
+ ),
+ ]
+
+ return Model1(states=states, transitions=transitions), Semantics(
+ ode=OdeSemantics(
+ rates=rates,
+ initials=initials,
+ parameters=parameters,
+ time=time,
+ )
+ )
+
+
+def get_args():
+ parser = argparse.ArgumentParser()
+ # parser.add_argument(
+ # "-d",
+ # "--dimensions",
+ # default=1,
+ # type=int,
+ # help=f"Number of spatial dimensions",
+ # )
+ parser.add_argument(
+ "-p",
+ "--num-discretization-points",
+ default=5,
+ type=int,
+ help=f"Number of discretization points",
+ )
+ parser.add_argument(
+ "-o",
+ "--outfile",
+ default="halfar.json",
+ help=f"Output filename",
+ )
+ return parser.parse_args()
+
+
+def header():
+ return Header(
+ name="Halfar Model",
+ schema_=AnyUrl(
+ "https://raw.githubusercontent.com/DARPA-ASKEM/Model-Representations/petrinet_v0.1/petrinet/petrinet_schema.json"
+ ),
+ schema_name="petrinet",
+ description="Halfar as Petrinet model created by Dan Bryce and Drisana Mosiphir",
+ model_version="0.1",
+ )
+
+
+def main():
+ args = get_args()
+
+ assert (
+ args.num_discretization_points > 2
+ ), "Need to have use at least 3 discretization points to properly define the gradients."
+
+ generator = HalfarGenerator()
+ model, semantics = generator.model(args)
+ halfar_model = HalfarModel(
+ header=header(),
+ model=model,
+ semantics=semantics,
+ )
+ j = halfar_model.model_dump_json(indent=4)
+
+ with open(args.outfile, "w") as f:
+ print(f"Writing {os.path.join(os.getcwd(), args.outfile)}")
+ f.write(j)
+
+
+if __name__ == "__main__":
+ main()
diff --git a/auxiliary_packages/funman_demo/src/funman_demo/parameter_space_plotter.py b/auxiliary_packages/funman_demo/src/funman_demo/parameter_space_plotter.py
index 54d09385..c8c788a4 100644
--- a/auxiliary_packages/funman_demo/src/funman_demo/parameter_space_plotter.py
+++ b/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
@@ -55,20 +56,30 @@ 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})
return box
- def initialize_figure(self):
+ def map_param_idx_to_plot_loc(self, i, j, plot_diagonal):
+ if plot_diagonal:
+ return i, j
+ elif i == 0 or j == self.dim - 1:
+ return None, None
+ else:
+ return i - 1, j
+
+ def initialize_figure(self, plot_diagonal):
if self.dim == 0:
return
+ dim_to_plot = self.dim if plot_diagonal else self.dim - 1
fig, axs = plt.subplots(
- self.dim,
- self.dim,
+ dim_to_plot,
+ dim_to_plot,
squeeze=False,
- dpi=600,
+ dpi=self.dpi,
figsize=(10, 10),
)
self.fig = fig
@@ -89,43 +100,74 @@ def initialize_figure(self):
self.fig.tight_layout(pad=3.0)
self.data = [[None] * self.dim] * self.dim
+
for i in range(self.dim):
for j in range(self.dim):
- if j > i:
- axs[i, j].axis("off")
+ i_coord, j_coord = self.map_param_idx_to_plot_loc(
+ i, j, plot_diagonal
+ )
+ if i_coord is None or j_coord is None:
+ continue
+
+ if j_coord > i_coord:
+ axs[i_coord, j_coord].axis("off")
else:
- (self.data[i][j],) = self.axs[i, j].plot([], [])
- axs[i, j].set_xlabel(f"{self.parameters[i]}")
- axs[i, j].set_ylabel(f"{self.parameters[j]}")
+ (self.data[i][j],) = self.axs[i_coord, j_coord].plot(
+ [], []
+ )
+ axs[i_coord, j_coord].set_xlabel(f"{self.parameters[i]}")
+ axs[i_coord, j_coord].set_ylabel(f"{self.parameters[j]}")
self.fig.suptitle(self.title)
plt.legend(self.custom_lines, ["true", "false"])
- def plot(self, show=False):
- self.initialize_figure()
+ def plot(self, show=False, plot_diagonal=False):
+ self.initialize_figure(plot_diagonal)
t = "true"
f = "false"
for b in self.ps.false_boxes:
- self.plotNDBox(b, self.color_map[f])
+ self.plotNDBox(b, self.color_map[f], plot_diagonal=plot_diagonal)
for b in self.ps.true_boxes:
- self.plotNDBox(b, self.color_map[t])
+ self.plotNDBox(b, self.color_map[t], plot_diagonal=plot_diagonal)
if self.plot_points:
for p in self.ps.false_points():
- self.plot_add_point(p, self.color_map[f], self.shape_map[f])
+ self.plot_add_point(
+ p,
+ self.color_map[f],
+ self.shape_map[f],
+ plot_diagonal=plot_diagonal,
+ )
true_points = self.ps.true_points()
for p in true_points:
- self.plot_add_point(p, self.color_map[t], self.shape_map[t])
+ self.plot_add_point(
+ p,
+ self.color_map[t],
+ self.shape_map[t],
+ plot_diagonal=plot_diagonal,
+ )
if show:
plt.show(block=False)
- def plot_add_point(self, point: Point, color="r", shape="x", alpha=0.9):
+ def plot_add_point(
+ self,
+ point: Point,
+ color="r",
+ shape="x",
+ alpha=0.9,
+ plot_diagonal=False,
+ ):
for i in range(self.dim):
for j in range(self.dim):
- if i < j:
+ i_coord, j_coord = self.map_param_idx_to_plot_loc(
+ i, j, plot_diagonal
+ )
+ if i_coord is None or j_coord is None:
+ continue
+ if j_coord > i_coord:
continue
yval = (
point.values[self.parameters[j]] if self.dim > 1 else 0.0
)
- self.axs[i, j].scatter(
+ self.axs[i_coord, j_coord].scatter(
point.values[self.parameters[i]],
yval,
color=color,
@@ -136,17 +178,23 @@ def plot_add_point(self, point: Point, color="r", shape="x", alpha=0.9):
# self.fig.canvas.draw()
# self.fig.canvas.flush_events()
- def plotNDBox(self, box, color="g", alpha=0.2):
+ def plotNDBox(self, box, color="g", alpha=0.2, plot_diagonal=False):
for i in range(self.dim):
for j in range(self.dim):
- if i < j:
+ i_coord, j_coord = self.map_param_idx_to_plot_loc(
+ i, j, plot_diagonal
+ )
+ if i_coord is None or j_coord is None:
continue
+ if j_coord > i_coord:
+ continue
+
x_limits = box.bounds[self.parameters[i]]
y_limits = box.bounds[self.parameters[j]]
if i == j:
# Plot a line segment
- self.axs[i, j].plot(
+ self.axs[i_coord, j_coord].plot(
[x_limits.lb, x_limits.ub],
[x_limits.lb, x_limits.ub],
color=color,
@@ -162,7 +210,7 @@ def plotNDBox(self, box, color="g", alpha=0.2):
x = np.linspace(
float(x_limits.lb), float(x_limits.ub), 1000
)
- self.axs[i, j].fill_between(
+ self.axs[i_coord, j_coord].fill_between(
x,
y_limits.lb,
y_limits.ub,
diff --git a/auxiliary_packages/funman_dreal/src/funman_dreal/converter.py b/auxiliary_packages/funman_dreal/src/funman_dreal/converter.py
index 05bce6e3..8a1322a1 100644
--- a/auxiliary_packages/funman_dreal/src/funman_dreal/converter.py
+++ b/auxiliary_packages/funman_dreal/src/funman_dreal/converter.py
@@ -1,12 +1,25 @@
import functools
+import logging
import re
from fractions import Fraction
from typing import List
import dreal
from pysmt.decorators import catch_conversion_error
+from pysmt.exceptions import UndefinedSymbolError
from pysmt.formula import FNode
-from pysmt.shortcuts import Symbol
+from pysmt.parsing import (
+ ClosePar,
+ Constant,
+ GrammarSymbol,
+ HRLexer,
+ Identifier,
+ InfixOpAdapter,
+ PrattParser,
+ Rule,
+ UnaryOpAdapter,
+)
+from pysmt.shortcuts import FALSE, Symbol
from pysmt.smtlib.parser import SmtLibParser, Tokenizer
from pysmt.solvers.solver import (
Converter,
@@ -17,9 +30,81 @@
)
from pysmt.walkers import DagWalker
+l = logging.getLogger(__name__)
+
+
+def CoreParser(env=None):
+ return PrattParser(CoreLexer)
+
+
+class BinaryLiteralExpr(GrammarSymbol):
+ """Adapter for unary operator."""
+
+ def __init__(self, operator, lbp):
+ GrammarSymbol.__init__(self)
+ self.operator = operator
+ self.lbp = lbp
+
+ def nud(self, parser):
+ # parser.advance() # OpenPar
+ parser.advance() # OpenPar
+ if type(parser.token) != ClosePar:
+ r = parser.expression()
+ if type(parser.token) != ClosePar:
+ raise SyntaxError("Expected ')'")
+ parser.advance() # ClosePar
+ if type(parser.token) != ClosePar:
+ raise SyntaxError("Expected ')'")
+ parser.advance() # ClosePar
+ return r
+
+ def __repr__(self):
+ return repr(self.operator)
+
+
+class CoreLexer(HRLexer):
+ def __init__(self, env=None):
+ super().__init__(env=env)
+
+ self.identifier_map = {"and": "&", "or": "|", "==": "="}
+
+ self.rules = [
+ Rule(r"(pow)", InfixOpAdapter(self.mgr.Pow, 80), False), # pow
+ Rule(
+ r"(and)", InfixOpAdapter(self.AndOrBVAnd, 40), False
+ ), # conjunction
+ Rule(
+ r"(or)", InfixOpAdapter(self.OrOrBVOr, 30), False
+ ), # disjunction
+ Rule(
+ r"(b\()", BinaryLiteralExpr(self.BinaryLiteral, 50), False
+ ), # b()
+ Rule(r"(==)", InfixOpAdapter(self.mgr.Equals, 60), False), # eq
+ Rule(
+ r"(-?\d+\.\d+e-?\d+)", self.real_constant, True
+ ), # decimals scientific
+ ] + self.rules
+ self.compile()
+
+ def BinaryLiteral(self, x):
+ return x
+
+ def int_constant(self, read):
+ return Constant(self.mgr.Real(int(read)))
+
+ def identifier(self, read):
+ r = self.identifier_map.get(read, read)
+ try:
+ return Identifier(r, env=self.env)
+ except UndefinedSymbolError as e:
+ l.exception(
+ f"Could not resolve parsed identifier: {r}, because:\n{e}"
+ )
+
class DRealConverter(Converter, DagWalker):
def __init__(self, environment):
+ # self.__setattr__("walk_abs", walk_abs)
DagWalker.__init__(self, environment)
self.backconversion = {}
self.mgr = environment.formula_manager
@@ -59,10 +144,14 @@ def rewrite_dreal_formula(self, formula: dreal.Formula) -> str:
# str_formula = str_formula.replace("pow(beta, 2.0)", "beta^2.0")
str_formula = re.sub(
- r"pow\([a-z]+\, [0-9.]+\)",
- lambda x: x.group().split(",")[0].split("(")[1]
+ r"pow\([\(\)\-a-z0-9\_\+\*\.\^ ]+\, [\-0-9a-z.]+\)",
+ lambda x: "("
+ + x.group().split(",")[0].split("(", 1)[1]
+ + ")"
+ "^"
- + x.group().split(",")[1].split(")")[0].strip(),
+ + "("
+ + x.group().split(",")[1].split(")")[0].strip()
+ + ")",
str_formula,
)
@@ -77,12 +166,13 @@ def create_dreal_symbols(self, rewritten_formula: str) -> List[Symbol]:
return symbols
def back(self, dreal_formula: dreal.Formula) -> FNode:
- from pysmt.parsing import parse
-
try:
- rewritten_formula = self.rewrite_dreal_formula(dreal_formula)
- new_symbols = self.create_dreal_symbols(rewritten_formula)
- formula = parse(rewritten_formula)
+ # rewritten_formula = self.rewrite_dreal_formula(dreal_formula)
+ l.debug(
+ f"Extracting dreal unsat core expression: {str(dreal_formula)}"
+ )
+ new_symbols = self.create_dreal_symbols(str(dreal_formula))
+ formula = CoreParser().parse(str(dreal_formula))
except Exception as e:
raise e
return formula
@@ -159,6 +249,10 @@ def walk_pow(self, formula, args, **kwargs):
res = dreal.pow(args[0], exponent)
return res
+ def walk_abs(self, formula, args, **kwargs):
+ res = abs(args[0])
+ return res
+
def bool_to_formula(self, value):
if isinstance(value, bool):
value = dreal.Formula.TRUE() if value else dreal.Formula.FALSE()
diff --git a/notebooks/funman_results.ipynb b/notebooks/funman_results.ipynb
new file mode 100644
index 00000000..22364ceb
--- /dev/null
+++ b/notebooks/funman_results.ipynb
@@ -0,0 +1,476 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# This notebook illustrates example outputs from Funman, and how to work with the ParameterSpace object it creates.\n",
+ "\n",
+ "# Import funman related code\n",
+ "\n",
+ "from pathlib import Path\n",
+ "from funman import FunmanResults\n",
+ "import json\n",
+ "from funman import Point, Box, Parameter\n",
+ "from typing import List, Dict\n",
+ "\n",
+ "# %load_ext autoreload\n",
+ "# %autoreload 2"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Model has the symbols: ['Susceptible', 'Diagnosed', 'Infected', 'Ailing', 'Recognized', 'Healed', 'Threatened', 'Extinct', 'beta', 'gamma', 'delta', 'alpha', 'epsilon', 'zeta', 'lambda', 'eta', 'rho', 'theta', 'kappa', 'mu', 'nu', 'xi', 'tau', 'sigma', 't']\n"
+ ]
+ }
+ ],
+ "source": [
+ "SAVED_RESULTS_DIR = Path(\"saved-results\").resolve()\n",
+ "SAVED_RESULT_FILES = [\n",
+ " # \"a8749b58-59ac-476f-848a-486c5ef54010.json\" # Only constrain the parameters\n",
+ " \"66f19967-f4fb-4b7b-82dd-65176bf41c44.json\"# 60-80: I in [0.1, 0.2)\n",
+ "]\n",
+ "SAVED_RESULT_TO_USE = SAVED_RESULTS_DIR / SAVED_RESULT_FILES[0]\n",
+ "\n",
+ "with open(SAVED_RESULT_TO_USE, \"r\") as f:\n",
+ " # Create a FunmanResults object\n",
+ " results: FunmanResults = FunmanResults.model_validate(json.load(f))\n",
+ "\n",
+ "print(f\"Model has the symbols: {results.model._symbols()}\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 4,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "