From 39f72829a7075f358fd1d1f3e63ec78256064321 Mon Sep 17 00:00:00 2001
From: vintache-d <damien.vintache@univ-nantes.fr>
Date: Mon, 13 Nov 2017 17:49:24 +0100
Subject: [PATCH 1/2] pep8 Style Guide for Python Code
---
HelperClass.py | 198 +++++++++++++++++++++++-------------------
TestVLP.py | 15 ++--
TestVLP2.py | 200 ++++++++++++++++++++++---------------------
setup.py | 29 +++----
test_benpy.py | 2 +-
test_benpy_simple.py | 3 +-
6 files changed, 233 insertions(+), 214 deletions(-)
diff --git a/HelperClass.py b/HelperClass.py
index 8486303..36ead5d 100644
--- a/HelperClass.py
+++ b/HelperClass.py
@@ -5,10 +5,12 @@ Created on Thu May 4 15:35:50 2017
Construct Ecosystem system
@author: mbudinich
"""
-#import cobra
+# import cobra
import numpy as np
from scipy.sparse import lil_matrix, find
-#%%
+# %%
+
+
class VlpProblem:
def __init__(self, B=None, a=None, b=None, l=None, s=None, P=None, Y=None, Z=None, c=None, opt_dir=None):
self.B = B
@@ -22,15 +24,15 @@ class VlpProblem:
self.c = c
self.opt_dir = opt_dir
- def to_file(self,filename=None): #VLP is 1 based, constraint numbering starts at 1!!
+ def to_file(self, filename=None): # VLP is 1 based, constraint numbering starts at 1!!
def getlen(obj):
return 0 if obj is None else len(obj)
-
+
if filename is None:
raise RuntimeError("No filename given")
- if hasattr(self,'ub') and not hasattr(self,'s'):
+ if hasattr(self, 'ub') and not hasattr(self, 's'):
self.s = self.ub
- if hasattr(self,'lb') and not hasattr(self,'l'):
+ if hasattr(self, 'lb') and not hasattr(self, 'l'):
self.l = self.lb
if self.opt_dir is None:
self.opt_dir = 1
@@ -42,129 +44,138 @@ class VlpProblem:
# raise RuntimeError('Matrix B has no shape attribute')
# if not hasattr(self.P,'shape'):
# raise RuntimeError('Matrix P has no shape attribute')
- (m,n) = self.B.shape
- (q,p) = self.P.shape
+ (m, n) = self.B.shape
+ (q, p) = self.P.shape
if (n != p):
raise RuntimeError('B and P must have same number of columns')
- [A_rows,A_cols,A_vals]=find(lil_matrix(self.B))
- k=len(A_rows)
- [P_rows,P_cols,P_vals]=find(lil_matrix(self.P))
- k1=len(P_rows)
- kstr=''
+ [A_rows, A_cols, A_vals] = find(lil_matrix(self.B))
+ k = len(A_rows)
+ [P_rows, P_cols, P_vals] = find(lil_matrix(self.P))
+ k1 = len(P_rows)
+ kstr = ''
if self.Y is not None and self.Y.shape[1] > 0:
- [K_rows,K_cols,K_vals]=find(lil_matrix(self.Y))
- k2=len(K_rows)
- kstr=' cone {} {}'.format(self.Y.shape[1],k2)
+ [K_rows, K_cols, K_vals] = find(lil_matrix(self.Y))
+ k2 = len(K_rows)
+ kstr = ' cone {} {}'.format(self.Y.shape[1], k2)
elif self.Z is not None and self.Z.shape[1] > 0:
- [K_rows,K_cols,K_vals] = find(lil_matrix(self.Z))
+ [K_rows, K_cols, K_vals] = find(lil_matrix(self.Z))
k2 = len(K_rows)
- kstr=' dualcone {} {}'.format(self.Z.shape[1],k2)
+ kstr = ' dualcone {} {}'.format(self.Z.shape[1], k2)
else:
- k2=0
-
- opt_dir_str=''
- if self.opt_dir==1:
+ k2 = 0
+
+ opt_dir_str = ''
+ if self.opt_dir == 1:
opt_dir_str = 'min'
- elif self.opt_dir==-1:
+ elif self.opt_dir == -1:
opt_dir_str = 'max'
else:
- raise RuntimeError('Invalid value for opt_dir: use -1 or 1 for maximitation and minimization')
-
+ raise RuntimeError(
+ 'Invalid value for opt_dir: use -1 or 1 for maximitation and minimization')
+
try:
- file = open(filename,'w')
+ file = open(filename, 'w')
except OSError as e:
print("OS error: {0}".format(e))
raise
- #Write 'p', 'a', 'k' to file
- file.write("p vlp {} {} {} {} {} {}{}\n".format(opt_dir_str,m,n,k,q,k1,kstr))
+ # Write 'p', 'a', 'k' to file
+ file.write("p vlp {} {} {} {} {} {}{}\n".format(
+ opt_dir_str, m, n, k, q, k1, kstr))
for i in list(range(k)):
- file.write("a {} {} {}\n".format(A_rows[i]+1,A_cols[i]+1,A_vals[i]))
+ file.write("a {} {} {}\n".format(
+ A_rows[i] + 1, A_cols[i] + 1, A_vals[i]))
for i in list(range(k1)):
- file.write("o {} {} {}\n".format(P_rows[i]+1,P_cols[i]+1,P_vals[i]))
+ file.write("o {} {} {}\n".format(
+ P_rows[i] + 1, P_cols[i] + 1, P_vals[i]))
for i in list(range(k2)):
- file.write("k {} {} {}\n".format(K_rows[i]+1,K_cols[i]+1,K_vals[i]))
+ file.write("k {} {} {}\n".format(
+ K_rows[i] + 1, K_cols[i] + 1, K_vals[i]))
# duality parameter vector
-
+
if self.c is not None:
- if(len(np.array(self.c).shape) != 1 ) or (len(self.c)!=q) :
+ if(len(np.array(self.c).shape) != 1) or (len(self.c) != q):
raise RuntimeError('c has wrong dimension')
for i in range(q):
- file.write("k {} 0 {}\n".format(i+1,self.c[i]))
-
- #Write row
+ file.write("k {} 0 {}\n".format(i + 1, self.c[i]))
+
+ # Write row
if (len(np.array(self.a).shape) > 1):
raise RuntimeError('a has wrong dimension')
if (len(np.array(self.b).shape) > 1):
raise RuntimeError('b has wrong dimension')
- m1 = max(getlen(self.a),getlen(self.b))
+ m1 = max(getlen(self.a), getlen(self.b))
if self.a is None:
- aa = -np.inf*np.ones((m1,1))
+ aa = -np.inf * np.ones((m1, 1))
else:
aa = self.a
if self.b is None:
- bb = np.inf*np.ones((m1,1))
+ bb = np.inf * np.ones((m1, 1))
else:
bb = self.b
-
+
for i in list(range(m1)):
if aa[i] < bb[i]:
- ch = 2*np.isfinite(aa[i]) + np.isfinite(bb[i])
+ ch = 2 * np.isfinite(aa[i]) + np.isfinite(bb[i])
if ch == 0:
- file.write('i {} f \n'.format(i+1))
+ file.write('i {} f \n'.format(i + 1))
elif ch == 1:
- file.write('i {} u {}\n'.format(i+1,bb[i]))
+ file.write('i {} u {}\n'.format(i + 1, bb[i]))
elif ch == 2:
- file.write('i {} l {}\n'.format(i+1,aa[i]))
+ file.write('i {} l {}\n'.format(i + 1, aa[i]))
elif ch == 3:
- file.write('i {} d {} {}\n' .format(i+1,aa[i],bb[i]))
+ file.write('i {} d {} {}\n' .format(i + 1, aa[i], bb[i]))
else:
raise RuntimeError("Bad ch switch for constrains bounds")
elif aa[i] == bb[i] and np.isfinite(aa[i]):
- file.write('i %d s %g\n',i,aa[i])
+ file.write('i %d s %g\n', i, aa[i])
else:
- raise RuntimeError('Invalid constrsaints: a[{}]={}, b[{}]={}'.format(i+1,aa[i],i,bb[i]))
-
- #Write cols
+ raise RuntimeError(
+ 'Invalid constrsaints: a[{}]={}, b[{}]={}'.format(i + 1, aa[i], i, bb[i]))
+
+ # Write cols
if self.l is None:
- llb=-np.inf*np.ones((n,1))
+ llb = -np.inf * np.ones((n, 1))
else:
- llb=self.l
-
+ llb = self.l
+
if self.s is None:
- uub= np.inf*np.ones((n,1))
+ uub = np.inf * np.ones((n, 1))
else:
- uub= self.s
-
+ uub = self.s
+
for j in range(n):
if llb[j] < uub[j]:
- ch = 2*np.isfinite(llb[j]) + np.isfinite(uub[j])
+ ch = 2 * np.isfinite(llb[j]) + np.isfinite(uub[j])
if ch == 0:
- file.write('j {} f \n'.format(j+1))
+ file.write('j {} f \n'.format(j + 1))
elif ch == 1:
- file.write('j {} u {}\n'.format(j+1,uub[j]))
+ file.write('j {} u {}\n'.format(j + 1, uub[j]))
elif ch == 2:
- file.write('j {} l {}\n'.format(j+1,llb[j]))
+ file.write('j {} l {}\n'.format(j + 1, llb[j]))
elif ch == 3:
- file.write('j {} d {} {}\n' .format(j+1,llb[j],uub[j]))
+ file.write('j {} d {} {}\n' .format(j + 1, llb[j], uub[j]))
else:
raise RuntimeError("Bad ch switch for variable bounds")
elif llb[j] == uub[j] and np.isfinite(llb[j]):
- file.write('i %d s %g\n',j+1,llb[j])
+ file.write('i %d s %g\n', j + 1, llb[j])
else:
- raise RuntimeError('Invalid constrsaints: l[{}]={}, s[{}]={}'.format(j+1,llb[j],i,uub[j]))
+ raise RuntimeError('Invalid constrsaints: l[{}]={}, s[{}]={}'.format(
+ j + 1, llb[j], i, uub[j]))
file.write('e ')
file.close()
-#%%
+# %%
+
+
class EcosystemModel:
- from scipy.sparse import lil_matrix, block_diag, eye
-
- def __init__(self,model_array=None,metabolic_dict=None):
+ from scipy.sparse import lil_matrix, block_diag, eye
+
+ def __init__(self, model_array=None, metabolic_dict=None):
"""Instatiate the EcosystemModel object
model_array is an array of cobra models to connect
metabolic_dict is a dicctionary where its keys correspond to metabolites id's and their values to the name equivalence"""
- self.models=model_array
+ self.models = model_array
self.metabolic_dict = metabolic_dict
self._pooldict = None
self.pool_ex_rxns = None
@@ -178,57 +189,64 @@ class EcosystemModel:
def construct_ecosystem_pool(self):
"""Check all metabolites used in import/export exchanges and construct the pool compartment"""
- pooldict=dict()
+ pooldict = dict()
for model in self.models:
for rxn_ex in model.exchanges:
for met_ex in rxn_ex.metabolites:
met_name = self.metabolic_dict[met_ex.id]
- if met_name not in pooldict:
- pooldict[met_name]=[(model,rxn_ex,rxn_ex.get_coefficient(met_ex.id))]
+ if met_name not in pooldict:
+ pooldict[met_name] = [
+ (model, rxn_ex, rxn_ex.get_coefficient(met_ex.id))]
else:
- pooldict[met_name].append((model,rxn_ex,rxn_ex.get_coefficient(met_ex.id)))
- self._pooldict = pooldict
+ pooldict[met_name].append(
+ (model, rxn_ex, rxn_ex.get_coefficient(met_ex.id)))
+ self._pooldict = pooldict
def populate_ecosystem_model(self):
"""Calculate the object attributes after pool construction"""
- self.pool_ex_rxns = ["EX_{}:pool".format(key) for key in self._pooldict.keys()]
- self.pool_ex_mets = ["{}:pool".format(key) for key in self._pooldict.keys()]
- self.sysreactions = ["{}:{}".format(r.id,model.id) for model in self.models for r in model.reactions]
- self.sysmetabolites = ["{}:{}".format(m.id,model.id) for model in self.models for m in model.metabolites]
+ self.pool_ex_rxns = ["EX_{}:pool".format(
+ key) for key in self._pooldict.keys()]
+ self.pool_ex_mets = ["{}:pool".format(
+ key) for key in self._pooldict.keys()]
+ self.sysreactions = ["{}:{}".format(
+ r.id, model.id) for model in self.models for r in model.reactions]
+ self.sysmetabolites = ["{}:{}".format(
+ m.id, model.id) for model in self.models for m in model.metabolites]
self.sysreactions.extend(self.pool_ex_rxns)
self.sysmetabolites.extend(self.pool_ex_mets)
array_form = [model.to_array_based_model() for model in self.models]
self.Ssigma = block_diag([model.S for model in array_form])
- self.Ssigma = lil_matrix(block_diag([self.Ssigma,-eye(len(self.pool_ex_rxns))]))
+ self.Ssigma = lil_matrix(block_diag(
+ [self.Ssigma, -eye(len(self.pool_ex_rxns))]))
for met in self._pooldict.keys():
met_name = "{}:pool".format(met)
met_idx = self.sysmetabolites.index(met_name)
- for model,reaction,coeff in self._pooldict[met]:
- rxn_name = "{}:{}".format(reaction.id,model.id)
+ for model, reaction, coeff in self._pooldict[met]:
+ rxn_name = "{}:{}".format(reaction.id, model.id)
rxn_idx = self.sysreactions.index(rxn_name)
- self.Ssigma[met_idx,rxn_idx]=-coeff
-
- def add_comparment(self,model):
+ self.Ssigma[met_idx, rxn_idx] = -coeff
+
+ def add_comparment(self, model):
"""Utility function to add a new agent to models. Pretty ineficient, re-runs all the steps again for each addition"""
- self.__init__(self.model_array.add(model),self.metabolic_dict)
+ self.__init__(self.model_array.add(model), self.metabolic_dict)
self.construct_ecosystem_pool()
self.populate_ecosystem_model()
-
+
@staticmethod
def get_common_mets(model_list):
"""Naive implementation of getting common exchange metabolites, using their id's"""
- common_mets=dict()
+ common_mets = dict()
for model in model_list:
for rxn_ex in model.exchanges:
for met_ex in rxn_ex.metabolites:
if met_ex.id not in common_mets:
- common_mets[met_ex.id]=dict([(model,rxn_ex)])
+ common_mets[met_ex.id] = dict([(model, rxn_ex)])
else:
- common_mets[met_ex.id][model]=rxn_ex
+ common_mets[met_ex.id][model] = rxn_ex
return(common_mets)
-#%%
-
+# %%
+
-#%%
+# %%
diff --git a/TestVLP.py b/TestVLP.py
index 463150f..05416db 100644
--- a/TestVLP.py
+++ b/TestVLP.py
@@ -9,7 +9,7 @@ Created on Wed May 31 15:45:22 2017
# Example: MOLP with 2 objectives, simplest example
# min [x1 - x2; x1 + x2]
-#
+#
# 6 <= 2*x1 + x2
# 6 <= x1 + 2*x2
#
@@ -18,13 +18,13 @@ Created on Wed May 31 15:45:22 2017
import numpy as np
from benpy import solve as bensolve, vlpProblem, vlpSolution
-#%%
+# %%
vlp = vlpProblem()
-vlp.B=np.matrix([[2,1],[1,2]]) # coefficient matrix
-vlp.a=[6,6] # lower bounds
-vlp.P=np.matrix([[1,-1],[1,1]]); # objective matrix
-vlp.l=[0,0]; # lower variable bounds
+vlp.B = np.matrix([[2, 1], [1, 2]]) # coefficient matrix
+vlp.a = [6, 6] # lower bounds
+vlp.P = np.matrix([[1, -1], [1, 1]]) # objective matrix
+vlp.l = [0, 0] # lower variable bounds
vlp.default_options()
@@ -33,6 +33,3 @@ vlp.to_string()
vlp.to_file('test01.vlp')
sol = bensolve(vlp)
-
-
-
diff --git a/TestVLP2.py b/TestVLP2.py
index b81063c..95e2202 100644
--- a/TestVLP2.py
+++ b/TestVLP2.py
@@ -5,29 +5,29 @@ Created on Wed May 31 15:45:22 2017
Test VLP interfase with bensolve
@author: mbudinich
"""
-#%%
+# %%
from numpy import transpose, ones, zeros, eye, matrix, loadtxt, append, hstack, vstack, inf
from HelperClass import VlpProblem
-#%%
+# %%
# Example: MOLP with 2 objectives, simplest example
# min [x1 - x2; x1 + x2]
-#
+#
# 6 <= 2*x1 + x2
# 6 <= x1 + 2*x2
#
# x1 >= 0
# x2 >= 0
-vlp = VlpProblem();
+vlp = VlpProblem()
-vlp.B=matrix([[2,1],[1,2]]) # coefficient matrix
-vlp.a=[6,6] # lower bounds
-vlp.P=matrix([[1,-1],[1,1]]) # objective matrix
-vlp.l=[0,0] # lower variable bounds
+vlp.B = matrix([[2, 1], [1, 2]]) # coefficient matrix
+vlp.a = [6, 6] # lower bounds
+vlp.P = matrix([[1, -1], [1, 1]]) # objective matrix
+vlp.l = [0, 0] # lower variable bounds
-vlp.to_file('ex01.vlp');
-#%%
+vlp.to_file('ex01.vlp')
+# %%
# Example: MOLP with 2 objectives which is infeasible
# v-min [x1;x2]
@@ -36,15 +36,15 @@ vlp.to_file('ex01.vlp');
# 0 <= x1 + 2*x2 <= 1
# 1 <= x1 + x2 <= 2
-vlp = VlpProblem();
+vlp = VlpProblem()
-vlp.B=matrix([[3,1],[1,2],[1,1]])
-vlp.b=[1, 1, 2]
-vlp.a=[0, 0, 1]
-vlp.P=matrix([[1,0],[0,1]])
+vlp.B = matrix([[3, 1], [1, 2], [1, 1]])
+vlp.b = [1, 1, 2]
+vlp.a = [0, 0, 1]
+vlp.P = matrix([[1, 0], [0, 1]])
-vlp.to_file('ex02.vlp');
-#%%
+vlp.to_file('ex02.vlp')
+# %%
# Example: MOLP with 2 objectives the upper image of which has no vertex
# v-min [x1;x2]
@@ -52,14 +52,14 @@ vlp.to_file('ex02.vlp');
# 1 <= x1 + x2 + x3
# 1 <= x1 + x2 - x3
-vlp = VlpProblem();
+vlp = VlpProblem()
-vlp.B=matrix([[1,1,1],[1,1,-1]])
-vlp.a=[1,1]
-vlp.P=matrix([[1,0,0], [0,1,0]])
+vlp.B = matrix([[1, 1, 1], [1, 1, -1]])
+vlp.a = [1, 1]
+vlp.P = matrix([[1, 0, 0], [0, 1, 0]])
-vlp.to_file('ex03.vlp');
-#%%
+vlp.to_file('ex03.vlp')
+# %%
# Example: MOLP with 2 objectives, which is totally unbounded
# v-min [x1;x2]
@@ -67,27 +67,28 @@ vlp.to_file('ex03.vlp');
# 1 <= x1 + x2 + x3
# 1 <= x1 + x2 + 2*x3
-vlp = VlpProblem();
+vlp = VlpProblem()
-vlp.B=matrix([[1,1,1],[1,1,2]]);
-vlp.a=[1,1]
-vlp.P=matrix([[1,0,0], [0,1,0]]);
+vlp.B = matrix([[1, 1, 1], [1, 1, 2]])
+vlp.a = [1, 1]
+vlp.P = matrix([[1, 0, 0], [0, 1, 0]])
-vlp.to_file('ex04.vlp');
-#%%
+vlp.to_file('ex04.vlp')
+# %%
# Example: VLP with q = 3 and 4 generating vectors of C
# see http://bensolve.org/demo.html
-vlp = VlpProblem();
+vlp = VlpProblem()
-vlp.B=matrix([ones((1,3)).tolist()[0],[1,2,2],[2,2,1],[2,1,2]]) # coefficient matrix
-vlp.a=[1,3/2,3/2,3/2]; # lhs of constraints
-vlp.P=matrix([[1,0,1],[1,1,0],[0,1,1]]) # objective matrix
-vlp.l=[0,0,0] # lower variable bounds
+vlp.B = matrix([ones((1, 3)).tolist()[0], [1, 2, 2], [
+ 2, 2, 1], [2, 1, 2]]) # coefficient matrix
+vlp.a = [1, 3 / 2, 3 / 2, 3 / 2] # lhs of constraints
+vlp.P = matrix([[1, 0, 1], [1, 1, 0], [0, 1, 1]]) # objective matrix
+vlp.l = [0, 0, 0] # lower variable bounds
# generating vectors of ordering cone C
-vlp.Y=transpose(matrix([[1,0,0], [0,1,0], [-1,0,2], [0,-1,2]]))
+vlp.Y = transpose(matrix([[1, 0, 0], [0, 1, 0], [-1, 0, 2], [0, -1, 2]]))
# alternative variant: generating vectors of the dual of the ordering cone C
# vlp.Z=[2 2 1 ; 2 0 1 ; 0 0 1 ; 0 2 1]';
@@ -95,59 +96,61 @@ vlp.Y=transpose(matrix([[1,0,0], [0,1,0], [-1,0,2], [0,-1,2]]))
# duality parameter vector (must belong to interior of C)
# if not given, it is computed automatically
# dual problem depends on c
-vlp.c=[1,1,1]
+vlp.c = [1, 1, 1]
vlp.to_file('ex05.vlp')
-#%%
+# %%
# Example: VLP with 2 objectives
# max [x1 - x2; x1 + x2]
#
# w.r.t. cone C ={(y1,y2) | 2 y1 -y2 >= 0, -y1 + 2 y2 >= 0}
-#
-# 1 <= x1 + x2 <= 2
+#
+# 1 <= x1 + x2 <= 2
#
# 0 <= x1 <= 1
# 0 <= x2
-vlp = VlpProblem();
+vlp = VlpProblem()
-vlp.opt_dir=-1 # maximization
-vlp.Z=matrix([[2,-1], [-1,2]]) # generators of dual of ordering cone
-vlp.c=[1,1] # geometric duality parameter vector (belongs to interior of C)
+vlp.opt_dir = -1 # maximization
+vlp.Z = matrix([[2, -1], [-1, 2]]) # generators of dual of ordering cone
+vlp.c = [1, 1] # geometric duality parameter vector (belongs to interior of C)
-vlp.B=matrix([1,1]) # coefficient matrix
-vlp.a=[1] # lhs
-vlp.b=[2] # rhs
-vlp.l=[0,0] # lower bounds
-vlp.s=[1,inf] # upper bounds
-vlp.P=matrix([[1,-1],[1,1]]) # objective matrix
+vlp.B = matrix([1, 1]) # coefficient matrix
+vlp.a = [1] # lhs
+vlp.b = [2] # rhs
+vlp.l = [0, 0] # lower bounds
+vlp.s = [1, inf] # upper bounds
+vlp.P = matrix([[1, -1], [1, 1]]) # objective matrix
-vlp.to_file('ex06.vlp');
-#%%
+vlp.to_file('ex06.vlp')
+# %%
# Example: MOLP with 3 objectives, 1211 constraints and 1143 variables
#
# Example (PL) in
-#
+#
# Shao, L., Ehrgott, M.: Approximately solving multiobjective linear programmes in objective space and
# an application in radiotherapy treatment planning. Math. Methods Oper. Res. 68(2), 257Ð276 (2008)
#
# enlarge epsilon in phase 2 and use primal simplex algorithm, for instance, run
# ./bensolve ex/ex07.vlp -m 2 -e 0.05 -l primal_simplex
-vlp = VlpProblem();
+vlp = VlpProblem()
-vlp.B=loadtxt('example07.txt');
-vlp.P = -1*matrix([append(zeros((1,1140)),[-1,0,0]),append(zeros((1,1140)),[0,-1,0]),append(zeros((1,1140)),[0,0,-1])])
-vlp.l = append(zeros((1140,1)),[0,-45,0])
-vlp.s = append(inf*ones((1140,1)),[17.07,12,90.64])
-vlp.b = vstack((90.64*ones((67,1)),-85.3601*ones((67,1)),60*ones((37,1)),45*ones((8,1)),60*ones((46,1)),ones((986,1))))
+vlp.B = loadtxt('example07.txt')
+vlp.P = -1 * matrix([append(zeros((1, 1140)), [-1, 0, 0]), append(
+ zeros((1, 1140)), [0, -1, 0]), append(zeros((1, 1140)), [0, 0, -1])])
+vlp.l = append(zeros((1140, 1)), [0, -45, 0])
+vlp.s = append(inf * ones((1140, 1)), [17.07, 12, 90.64])
+vlp.b = vstack((90.64 * ones((67, 1)), -85.3601 * ones((67, 1)), 60 *
+ ones((37, 1)), 45 * ones((8, 1)), 60 * ones((46, 1)), ones((986, 1))))
vlp.b = vlp.b.T.tolist()[0]
-vlp.to_file('ex07.vlp');
-#%%
+vlp.to_file('ex07.vlp')
+# %%
# Example: VLP with 2 objectives, which is unbounded (but not totally unbounded)
#
-# its the solution consists of feasible points and feasible directions
+# its the solution consists of feasible points and feasible directions
# min_C [x1;x2]
#
@@ -155,22 +158,22 @@ vlp.to_file('ex07.vlp');
#
# duality parameter c is set to [0;1], which is an interior point of C
#
-# 0 <= 3*x1 + x2
-# 0 <= x1 + 2*x2
-# 1 <= x1 + x2
+# 0 <= 3*x1 + x2
+# 0 <= x1 + 2*x2
+# 1 <= x1 + x2
-vlp = VlpProblem();
+vlp = VlpProblem()
-vlp.B=matrix([3,1],[1,2],[1,1])
-vlp.a=[0, 0, 1]
-vlp.P=[[1,0] , [0,1]];
+vlp.B = matrix([3, 1], [1, 2], [1, 1])
+vlp.a = [0, 0, 1]
+vlp.P = [[1, 0], [0, 1]]
# generating vectors of ordering cone C
-vlp.Y=matrix([[-1,3], [3/2,-1]])
-vlp.c=[0,1]
+vlp.Y = matrix([[-1, 3], [3 / 2, -1]])
+vlp.c = [0, 1]
-vlp.to_file('ex08.vlp');
-#%%
+vlp.to_file('ex08.vlp')
+# %%
# VLP with 3 objectives, 4608 constrains and 36939 variables
#
# Example 6.6 in
@@ -180,7 +183,7 @@ vlp.to_file('ex08.vlp');
# special options are necessary to run example:
#
# For instance, run
- # ./bensolve ex/ex09.vlp -e 1e-2 -m 3 -L primal_simplex -l primal_simplex -p
+# ./bensolve ex/ex09.vlp -e 1e-2 -m 3 -L primal_simplex -l primal_simplex -p
#
# (-e: set epsilon in Phase 2)
# (-m set message level to have more output on screen)
@@ -196,11 +199,11 @@ vlp.to_file('ex08.vlp');
# (-a use dual Benson algorithm in Phase 2)
# (-p generate graphics files)
-#vlp = VlpProblem();
-#load('example09');
-#vlp.c=[1,1,1]
-#vlp.to_file('ex09.vlp');
-#%%
+# vlp = VlpProblem();
+# load('example09');
+# vlp.c=[1,1,1]
+# vlp.to_file('ex09.vlp');
+# %%
# The 'bensolvehedron', see the titlepage of the reference manual
#
# MOLP with q objectives, n=(q+2*m)^q variables and constraints
@@ -213,36 +216,37 @@ vlp.to_file('ex08.vlp');
# add green color (!)
# adapt q and m to generate other (larger) problems
-#q=3;
-#m=2;
+# q=3;
+# m=2;
-#n=(q+2*m)^q;
+# n=(q+2*m)^q;
-#vlp = VlpProblem();
+# vlp = VlpProblem();
# feasible set is n dimensional hyper cube
-#vlp.B=eye(n)
-#vlp.a=zeros((n,1))
-#vlp.b=ones((n,1))
+# vlp.B=eye(n)
+# vlp.a=zeros((n,1))
+# vlp.b=ones((n,1))
# objective map
-#P=zeros(n,q);
-#for i in range(n):
-# line = dec2base(i-1,q+2*m,q)-'0';
-# line = line - (q+2*m-1)/2;
-# P[i,:] = line
+# P=zeros(n,q);
+# for i in range(n):
+# line = dec2base(i-1,q+2*m,q)-'0';
+# line = line - (q+2*m-1)/2;
+# P[i,:] = line
-#vlp.P = transpose(P)
+# vlp.P = transpose(P)
-#vlp.to_file('ex10.vlp');
-#%%
+# vlp.to_file('ex10.vlp');
+# %%
# Example: MOLP with q=5, unbounded,
# recession cone of upper image has 22 extreme directions (main effort in phase 1)
-vlp = VlpProblem();
+vlp = VlpProblem()
-vlp.B=matrix([[1,1,1,1,1],[2,1,1,1,1],[1,2,1,1,1],[1,1,2,1,1],[1,1,1,2,1],[1,1,1,1,2],[2,2,1,1,1],[2,1,2,1,1],[2,1,1,2,1],[2,1,1,1,2],[1,2,2,1,1],[1,2,1,2,1],[1,2,1,1,2],[1,1,2,2,1],[1,1,2,1,2],[1,1,1,2,2],[2,2,2,1,1],[2,2,1,2,1],[2,2,1,1,2],[2,1,2,1,2],[2,1,1,2,2],[1,2,2,2,1],[1,2,1,2,2],[1,2,2,1,2],[1,2,2,2,1],[1,1,2,2,2],[1,2,2,2,2],[2,1,2,2,2],[2,2,1,2,2],[2,2,2,1,2],[2,2,2,2,1]])
-vlp.a=append(1,zeros((30, 1)))
-vlp.P=eye((5,5));
+vlp.B = matrix([[1, 1, 1, 1, 1], [2, 1, 1, 1, 1], [1, 2, 1, 1, 1], [1, 1, 2, 1, 1], [1, 1, 1, 2, 1], [1, 1, 1, 1, 2], [2, 2, 1, 1, 1], [2, 1, 2, 1, 1], [2, 1, 1, 2, 1], [2, 1, 1, 1, 2], [1, 2, 2, 1, 1], [1, 2, 1, 2, 1], [1, 2, 1, 1, 2], [1, 1, 2, 2, 1], [1, 1, 2, 1, 2], [
+ 1, 1, 1, 2, 2], [2, 2, 2, 1, 1], [2, 2, 1, 2, 1], [2, 2, 1, 1, 2], [2, 1, 2, 1, 2], [2, 1, 1, 2, 2], [1, 2, 2, 2, 1], [1, 2, 1, 2, 2], [1, 2, 2, 1, 2], [1, 2, 2, 2, 1], [1, 1, 2, 2, 2], [1, 2, 2, 2, 2], [2, 1, 2, 2, 2], [2, 2, 1, 2, 2], [2, 2, 2, 1, 2], [2, 2, 2, 2, 1]])
+vlp.a = append(1, zeros((30, 1)))
+vlp.P = eye((5, 5))
-vlp.to_file('ex11.vlp');
\ No newline at end of file
+vlp.to_file('ex11.vlp')
diff --git a/setup.py b/setup.py
index faa535f..84251ce 100644
--- a/setup.py
+++ b/setup.py
@@ -2,20 +2,19 @@ from distutils.core import setup, Extension
from Cython.Build import cythonize
import numpy
-ext = Extension("benpy",sources=["benpy.pyx",
- "bensolve-mod/bslv_main.c",
- "bensolve-mod/bslv_vlp.c",
- "bensolve-mod/bslv_algs.c",
- "bensolve-mod/bslv_lists.c",
- "bensolve-mod/bslv_poly.c",
- "bensolve-mod/bslv_lp.c"
- ],
- libraries=['glpk','m'],
- extra_compile_args=['-std=c99','-O3']
- )
+ext = Extension("benpy", sources=["benpy.pyx",
+ "bensolve-mod/bslv_main.c",
+ "bensolve-mod/bslv_vlp.c",
+ "bensolve-mod/bslv_algs.c",
+ "bensolve-mod/bslv_lists.c",
+ "bensolve-mod/bslv_poly.c",
+ "bensolve-mod/bslv_lp.c"
+ ],
+ libraries=['glpk', 'm'],
+ extra_compile_args=['-std=c99', '-O3']
+ )
setup(
- name="benpy",
- ext_modules = cythonize([ext]),
- include_dirs=[numpy.get_include()]
+ name="benpy",
+ ext_modules=cythonize([ext]),
+ include_dirs=[numpy.get_include()]
)
-
diff --git a/test_benpy.py b/test_benpy.py
index c56f5ee..e6c3bad 100644
--- a/test_benpy.py
+++ b/test_benpy.py
@@ -2,7 +2,7 @@ import benpy
problem = benpy.vlpProblem()
problem.filename = "ex01.vlp"
-problem.options={'message_level':3}
+problem.options = {'message_level': 3}
sol = benpy.solve(problem)
problem2 = benpy.vlpProblem()
diff --git a/test_benpy_simple.py b/test_benpy_simple.py
index 0a69066..3244ba0 100644
--- a/test_benpy_simple.py
+++ b/test_benpy_simple.py
@@ -1,3 +1,4 @@
import benpy
-problem = benpy.vlpProblem(filename = "ex01.vlp", options = {'message_level':3, 'solution':True, 'logfile':False})
+problem = benpy.vlpProblem(filename="ex01.vlp", options={
+ 'message_level': 3, 'solution': True, 'logfile': False})
sol = benpy.solve(problem)
--
GitLab
From e974fc51259bd79c8159a4eabd34b39bb8c9102a Mon Sep 17 00:00:00 2001
From: vintache-d <damien.vintache@univ-nantes.fr>
Date: Tue, 14 Nov 2017 09:13:18 +0100
Subject: [PATCH 2/2] unused import
---
TestVLP.py | 2 +-
TestVLP2.py | 2 +-
2 files changed, 2 insertions(+), 2 deletions(-)
diff --git a/TestVLP.py b/TestVLP.py
index 05416db..e82d17c 100644
--- a/TestVLP.py
+++ b/TestVLP.py
@@ -17,7 +17,7 @@ Created on Wed May 31 15:45:22 2017
# x2 >= 0
import numpy as np
-from benpy import solve as bensolve, vlpProblem, vlpSolution
+from benpy import solve as bensolve, vlpProblem
# %%
vlp = vlpProblem()
diff --git a/TestVLP2.py b/TestVLP2.py
index 95e2202..a634788 100644
--- a/TestVLP2.py
+++ b/TestVLP2.py
@@ -6,7 +6,7 @@ Test VLP interfase with bensolve
@author: mbudinich
"""
# %%
-from numpy import transpose, ones, zeros, eye, matrix, loadtxt, append, hstack, vstack, inf
+from numpy import transpose, ones, zeros, eye, matrix, loadtxt, append, vstack, inf
from HelperClass import VlpProblem
# %%
# Example: MOLP with 2 objectives, simplest example
--
GitLab