Improved detection of backends and solvers

README.md

@@ -19,7 +19,7 @@ conda activate corneto
 pip install git+https://github.com/saezlab/corneto.git@0.9.0-alpha.3
 ```
 
-Alternatively you can download the wheel file from https://github.com/saezlab/corneto/releases/download/0.9.0-alpha.3/corneto-0.9.0a3-py3-none-any.whl and install it with `pip install corneto-0.9.0a3-py3-none-any.whl`. 
+Alternatively you can download the wheel (.whl) file from https://github.com/saezlab/corneto/releases and install it with `pip install file.whl`. 
 
 > :warning: Please note that without any backend, you can't do much with CORNETO. There are two supported backends right now: [PICOS](https://picos-api.gitlab.io/picos/tutorial.html) and [CVXPY](https://www.cvxpy.org/). Both backends allow symbolic manipulation of expressions in matrix notation. 
 

corneto/__init__.py

@@ -1,5 +1,5 @@
 from corneto._constants import *
 from corneto._core import ReNet
-from corneto.backend import available_backends, DEFAULT_BACKEND
+from corneto.backend import available_backends, DEFAULT_BACKEND, DEFAULT_SOLVER
 
 __version__ = '0.9.0-alpha.4'

corneto/backend/__init__.py

@@ -1,3 +1,4 @@
+from importlib.util import find_spec
 from corneto.backend._base import Backend, VarType
 from corneto.backend._cvxpy_backend import CvxpyBackend
 from corneto.backend._picos_backend import PicosBackend
@@ -9,10 +10,31 @@
 def available_backends():
     return [b for b in supported_backends if b.is_available()]
 
+_cvxpy_solvers = ['gurobi', 'cplex', 'mosek', 'scip', 'cbc', 'glpk_mi']
+_picos_solvers = ['gurobi', 'cplex', 'mosek', 'scip', 'glpk']
+
 
 DEFAULT_BACKEND = available_backends()[0] if len(available_backends()) > 0 else None
+DEFAULT_SOLVER = None
 
 if not DEFAULT_BACKEND:
     s.LOGGER.warn(
         "None of the supported backends found. Please install CVXPY or PICOS to create and solve optimization problems."
     )
+else:
+    if isinstance(DEFAULT_BACKEND, CvxpyBackend):
+        from cvxpy import installed_solvers
+        available = [name.lower() for name in installed_solvers()]
+        for solver in _cvxpy_solvers:
+            if solver in available:
+                DEFAULT_SOLVER = solver
+                break
+    else:
+        import picos as pc
+        available = [name.lower() for name in pc.available_solvers()]
+        for solver in _picos_solvers:
+            if solver in available:
+                DEFAULT_BACKEND = solver
+                break
+    if not DEFAULT_SOLVER:
+        s.LOGGER.warn(f"MIP solver not found for {DEFAULT_BACKEND}")

corneto/backend/_base.py

@@ -2,10 +2,12 @@
 from turtle import pos
 import numpy as np
 import numbers
-from typing import Any, Dict, Iterable, Optional, Set, Tuple, Union, List
+from typing import Any, Dict, Iterable, Optional, Tuple, Union, List
+import corneto as cnt
 from corneto._constants import *
 from corneto._core import ReNet
 from corneto._decorators import _proxy
+#from corneto.backend import DEFAULT_SOLVER
 
 
 def _eq_shape(a: np.ndarray, b: np.ndarray) -> bool:
@@ -330,14 +332,16 @@ def get_symbols(self, *args) -> List[CtProxySymbol]:
 
     def solve(
         self,
-        solver: Solver = Solver.COIN_OR_CBC,
+        solver: Optional[Union[str, Solver]] = None,
         max_seconds: int = None,
         warm_start: bool = False,
         verbosity: int = 0,
         **options,
     ) -> Any:
         if self._backend is None:
             raise ValueError("No backend assigned.")
+        if not solver:
+            solver = cnt.DEFAULT_SOLVER
         return self._backend.solve(
             self,
             solver=solver,
@@ -492,12 +496,14 @@ def Problem(
     def solve(
         self,
         p: ProblemDef,
-        solver: Solver = Solver.COIN_OR_CBC,
+        solver: Optional[Union[str, Solver]] = None,
         max_seconds: int = None,
         warm_start: bool = False,
         verbosity: int = 0,
         **options,
     ):
+        if not solver:
+            solver = cnt.DEFAULT_SOLVER
         o: Optional[CtProxyExpression]
         if p.objectives is not None and len(p.objectives) > 1:
             if len(p.weights) != len(p.objectives):
@@ -526,7 +532,7 @@ def _solve(
         self,
         p: ProblemDef,
         objective: Optional[CtProxyExpression] = None,
-        solver: Solver = Solver.COIN_OR_CBC,
+        solver: Optional[Union[str, Solver]] = None,
         max_seconds: int = None,
         warm_start: bool = False,
         verbosity: int = 0,

corneto/backend/_cvxpy_backend.py

@@ -1,3 +1,4 @@
+from multiprocessing.sharedctypes import Value
 from typing import Any, List, Optional, Tuple, Union
 from corneto.backend._base import (
     CtProxyExpression,
@@ -8,7 +9,8 @@
 )
 import numpy as np
 from corneto._constants import *
-import warnings
+from corneto._settings import LOGGER
+
 
 try:
     import cvxpy as cp
@@ -49,6 +51,9 @@ def _load(self):
 
         cvxpy
 
+    def __str__(self) -> str:
+        return "CVXPY Backend"
+
     def Variable(
         self,
         name: Optional[str] = None,
@@ -75,15 +80,17 @@ def _solve(
         self,
         p: ProblemDef,
         objective: Optional[CtProxyExpression] = None,
-        solver: Solver = Solver.COIN_OR_CBC,
+        solver: Optional[Union[str, Solver]] = None,
         max_seconds: int = None,
         warm_start: bool = False,
         verbosity: int = 0,
         **options,
     ) -> Any:
+        if not solver:
+            raise ValueError("A solver must be provided")
         o: Union[cp.Minimize, cp.Maximize]
         if objective is not None:
-            obj = objective.e if hasattr(objective, '_expr') else objective
+            obj = objective.e if hasattr(objective, "_expr") else objective
             if p._direction == Direction.MIN:
                 o = cp.Minimize(obj)
             elif p._direction == Direction.MAX:
@@ -117,12 +124,12 @@ def _solve(
             elif s == "CPLEX":
                 options["cplex_params"] = {"timelimit": max_seconds}
             elif s == "GLPK_MI":
-                warnings.warn("Timelimit for GLPK_MI is not supported")
+                LOGGER.warn("Timelimit for GLPK_MI is not supported")
             elif s == "SCIP":
                 # https://www.scipopt.org/doc/html/PARAMETERS.php
                 options["scip_params"] = {"limits/time": max_seconds}
             elif s == "MOSEK":
                 # https://docs.mosek.com/latest/cxxfusion/parameters.html
                 options["mosek_params"] = {"mioMaxTime": max_seconds}
         P.solve(solver=s, verbose=verbosity > 0, warm_start=warm_start, **options)
-        return P
+        return P

corneto/backend/_picos_backend.py

@@ -43,7 +43,7 @@ def __init__(
         ub: Optional[Union[float, np.ndarray]] = None,
         vartype: VarType = VarType.CONTINUOUS,
     ) -> None:
-        super().__init__(expr, name, lb, ub, vartype)       
+        super().__init__(expr, name, lb, ub, vartype)
 
 
 class PicosBackend(Backend):
@@ -52,6 +52,9 @@ def _load(self):
 
         picos
 
+    def __str__(self) -> str:
+        return "PICOS Backend"
+
     def Variable(
         self,
         name: Optional[str] = None,
@@ -76,23 +79,26 @@ def _solve(
         self,
         p: ProblemDef,
         objective: Optional[CtProxyExpression] = None,
-        solver: Solver = Solver.GLPK_MI,
+        solver: Optional[Union[str, Solver]] = None,
         max_seconds: int = None,
         warm_start: bool = False,
         verbosity: int = 0,
         **options,
     ):
+        if not solver:
+            raise ValueError("A solver must be provided")
         P = pc.Problem()
         for c in p.constraints:
             P += c.e
         if objective is not None:
-            obj = objective.e if hasattr(objective, '_expr') else objective
+            obj = objective.e if hasattr(objective, "_expr") else objective
             if p._direction == Direction.MIN:
                 P.minimize = obj
             else:
                 P.maximize = obj
         if warm_start:
             from corneto._settings import LOGGER
+
             LOGGER.warn("warm_start is not supported yet, ignored")
         P.solve(
             timelimit=max_seconds,