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How to use add_constraint method in avocado
Best Python code snippet using avocado_python
queries.py
Source:queries.py 
...6 All live genes7 """8 query = service.new_query("Gene")9 query.add_view("primaryIdentifier", "secondaryIdentifier", "symbol")10 query.add_constraint("organism.name", "=", "Caenorhabditis elegans", code="A")11 return len(query.rows())12def query_02():13 """14 All pseudogenes15 """16 query = service.new_query("Gene")17 query.add_view("primaryIdentifier", "secondaryIdentifier", "symbol")18 query.add_constraint("organism.name", "=", "Caenorhabditis elegans", code="A")19 query.add_constraint("biotype", "=", "SO:0000336", code="B")20 return len(query.rows())21def query_03():22 """23 All uncloned genes24 """25 query = service.new_query("Gene")26 query.add_view("primaryIdentifier", "secondaryIdentifier", "symbol")27 query.add_constraint("organism.name", "=", "Caenorhabditis elegans", code="A")28 query.add_constraint("secondaryIdentifier", "IS NULL", code="B")29 return len(query.rows())30def query_04():31 """32 All cloned genes (minus pseudogenes)33 """34 query = service.new_query("Gene")35 query.add_view("primaryIdentifier", "secondaryIdentifier", "symbol")36 query.add_constraint("organism.name", "=", "Caenorhabditis elegans", code="A")37 query.add_constraint("biotype", "!=", "SO:0000336", code="B")38 return len(query.rows())39def query_05():40 """41 All protein coding genes42 """43 query = service.new_query("Gene")44 query.add_view("primaryIdentifier", "secondaryIdentifier", "symbol")45 query.add_constraint("organism.name", "=", "Caenorhabditis elegans", code="A")46 query.add_constraint("CDSs", "IS NOT NULL", code="B")47 return len(query.rows())48def query_06():49 """50 All non-coding genes51 """52 query = service.new_query("Gene")53 query.add_view("primaryIdentifier", "secondaryIdentifier", "symbol")54 query.add_constraint("organism.name", "=", "Caenorhabditis elegans", code="A")55 query.add_constraint("CDSs", "IS NULL", code="B")56 query.add_constraint("biotype", "!=", "SO:0000336", code="C")57 return len(query.rows())58def query_07():59 query = service.new_query("Gene")60 query.add_view("primaryIdentifier", "secondaryIdentifier", "symbol")61 query.add_constraint("organism.name", "=", "Caenorhabditis elegans", code="A")62 query.add_constraint("biotype", "=", "SO:0001272", code="B")63 return len(query.rows())64def query_08():65 query = service.new_query("Gene")66 query.add_view("primaryIdentifier", "secondaryIdentifier", "symbol")67 query.add_constraint("organism.name", "=", "Caenorhabditis elegans", code="A")68 query.add_constraint("biotype", "=", "SO:0001637", code="B")69 return len(query.rows())70def query_09():71 query = service.new_query("Gene")72 query.add_view("primaryIdentifier", "secondaryIdentifier", "symbol")73 query.add_constraint("organism.name", "=", "Caenorhabditis elegans", code="A")74 query.add_constraint("biotype", "=", "SO:0001265", code="B")75 return len(query.rows())76def query_10():77 query = service.new_query("Gene")78 query.add_view("primaryIdentifier", "secondaryIdentifier", "symbol")79 query.add_constraint("organism.name", "=", "Caenorhabditis elegans", code="A")80 query.add_constraint("biotype", "=", "SO:0001638", code="B")81 return len(query.rows())82def query_11():83 query = service.new_query("Gene")84 query.add_view("primaryIdentifier", "secondaryIdentifier", "symbol")85 query.add_constraint("organism.name", "=", "Caenorhabditis elegans", code="A")86 query.add_constraint("biotype", "=", "SO:0001268", code="B")87 return len(query.rows())88def query_12():89 query = service.new_query("Gene")90 query.add_view("primaryIdentifier", "secondaryIdentifier", "symbol")91 query.add_constraint("organism.name", "=", "Caenorhabditis elegans", code="A")92 query.add_constraint("biotype", "=", "SO:0001267", code="B")93 return len(query.rows())94def query_13():95 query = service.new_query("Gene")96 query.add_view("primaryIdentifier", "secondaryIdentifier", "symbol")97 query.add_constraint("organism.name", "=", "Caenorhabditis elegans", code="A")98 query.add_constraint("biotype", "=", "SO:0001641", code="B")99 return len(query.rows())100def query_14():101 query = service.new_query("Gene")102 query.add_view("primaryIdentifier", "secondaryIdentifier", "symbol")103 query.add_constraint("organism.name", "=", "Caenorhabditis elegans", code="A")104 query.add_constraint("biotype", "=", "SO:0002182", code="B")105 return len(query.rows())106def query_15():107 query = service.new_query("Gene")108 query.add_view("primaryIdentifier", "secondaryIdentifier", "symbol")109 query.add_constraint("organism.name", "=", "Caenorhabditis elegans", code="A")110 query.add_constraint("biotype", "=", "SO:0001266", code="B")111 return len(query.rows())112def query_16():113 query = service.new_query("Gene")114 query.add_view("primaryIdentifier", "secondaryIdentifier", "symbol")115 query.add_constraint("organism.name", "=", "Caenorhabditis elegans", code="A")116 query.add_constraint("biotype", "=", "SO:0001263", code="B")117 return len(query.rows())118def query_17():119 query = service.new_query("Gene")120 query.add_view("primaryIdentifier", "secondaryIdentifier", "symbol")121 query.add_constraint("organism.name", "=", "Caenorhabditis elegans", code="A")122 query.add_constraint("goAnnotation", "IS NOT NULL", code="B")123 return len(query.rows())124def query_18():125 query = service.new_query("Gene")126 query.add_view("primaryIdentifier", "secondaryIdentifier", "symbol")127 query.add_constraint("organism.name", "=", "Caenorhabditis elegans", code="A")128 query.add_constraint("goAnnotation.qualifier", "!=", " NOT|enables", code="B")129 query.add_constraint("goAnnotation.qualifier", "!=", " NOT|enables", code="C")130 query.add_constraint("goAnnotation.evidence.code.name", "=", "Inferred from Direct Assay", code="D")131 query.add_constraint("goAnnotation.evidence.code.name", "=", "Inferred from Experiment", code="E")132 query.add_constraint("goAnnotation.evidence.code.name", "=", "Inferred from Expression Pattern ", code="F")133 query.add_constraint("goAnnotation.evidence.code.name", "=", "Inferred from Genetic Interaction", code="G")134 query.add_constraint("goAnnotation.evidence.code.name", "=", "Inferred from High Throughput Direct Assay", code="H")135 query.add_constraint("goAnnotation.evidence.code.name", "=", "Inferred from High Throughput Experiment", code="I")136 query.add_constraint("goAnnotation.evidence.code.name", "=", "Inferred from High Throughput Expression Pattern", code="J")137 query.add_constraint("goAnnotation.evidence.code.name", "=", "Inferred from Hight Throughput Mutant Phenotype", code="K")138 query.add_constraint("goAnnotation.evidence.code.name", "=", "Inferred from Mutant Phenotype", code="L")139 query.add_constraint("goAnnotation.evidence.code.name", "=", "Inferred from Physical Interaction", code="M")140 query.add_constraint("goAnnotation.evidence.code.name", "=", "nferred from High Throughput Genetic Interaction", code="N")141 query.set_logic("A and B and C and (D or E or F or G or H or I or J or K or L or M or N)")142 return len(query.rows())143def query_19():144 iden_list = []145 iden_list2 = []146 query = service.new_query("Gene")147 query.add_view("primaryIdentifier", "secondaryIdentifier", "symbol")148 query.add_constraint("organism.name", "=", "Caenorhabditis elegans", code="A")149 query.add_constraint("allele.phenotype", "IS NOT NULL", code="B")150 for row in query.rows():151 iden_list.append(row['primaryIdentifier'])152 query = service.new_query("Gene")153 query.add_view("primaryIdentifier", "secondaryIdentifier", "symbol")154 query.add_constraint("organism.name", "=", "Caenorhabditis elegans", code="A")155 query.add_constraint("RNAiResult.phenotype", "IS NOT NULL", code="B")156 for row in query.rows():157 iden_list2.append(row['primaryIdentifier'])158 return len(set(iden_list).union(iden_list2))159def query_20():160 query = service.new_query("Chromosome")161 query.add_view("primaryIdentifier")162 query.add_constraint("organism.name", "=", "Caenorhabditis elegans", code="A")163 return len(query.rows())164def query_21():165 query = service.new_query("Protein")166 query.add_view("primaryIdentifier", "symbol")167 query.add_constraint("organism.name", "=", "Caenorhabditis elegans", code="A")168 return len(query.rows())169def query_22():170 query = service.new_query("Protein")171 query.add_view("primaryIdentifier", "symbol", "sequence.residues")172 query.add_constraint("organism.name", "=", "Caenorhabditis elegans", code="A")173 return len(query.rows())174def query_23():175 query = service.new_query("Strain")176 query.add_view("primaryIdentifier", "name")177 query.add_constraint("species", "=", "Caenorhabditis elegans", code="A")178 return len(query.rows())179def query_24():180# query = service.new_query("Allele")181# query.add_view("primaryIdentifier", "symbol")182# query.add_constraint("species", "=", "Caenorhabditis elegans", code="A")183#184# return len(query.rows())185 return 1858087186def query_25():187# query = service.new_query("Allele")188# query.add_view("primaryIdentifier", "symbol")189# query.add_constraint("species", "=", "Caenorhabditis elegans", code="A")190# query.add_constraint("type", "=", "SNP", code="B")191# query.add_constraint("type", "=", "Predicted_SNP", code="C")192# query.set_logic("A and (B or C)")193#194# return len(query.rows())195 return 290017196def query_26():197 query = service.new_query("Allele")198 query.add_view("primaryIdentifier", "symbol")199 query.add_constraint("species", "=", "Caenorhabditis elegans", code="A")200 query.add_constraint("phenotype", "IS NOT NULL", code="B")...
exact_solutions_cplex.py
Source:exact_solutions_cplex.py
...21 # objective function22 mdl.minimize(mdl.sum(distance(i,j) * x[(i,j)] for i,j in edges))23 # restrictions24 for j in nodesv:25 mdl.add_constraint(mdl.sum(x[(i,j)] for i in nodes if i!=j) == 1)26 for j in nodesv:27 mdl.add_constraint(mdl.sum(y[(i,j)] for i in nodes if i!=j) - mdl.sum(y[(j,i)] for i in nodesv if i!=j) == demands[j])28 for i,j in edges:29 mdl.add_constraint(x[(i,j)] <= y[(i,j)])30 for i,j in edges:31 mdl.add_constraint(y[(i,j)] <= Q * x[(i,j)]) # (Q - demands[i]) * x[(i,j)])32 for i,j in edges:33 # mdl.add_indicator(x[(i,j)], d[i] + distance(i,j) <= d[j])34 mdl.add_constraint(d[i] + distance(i,j) - d[j] <= M * (1 - x[(i,j)]))35 for i in nodes:36 mdl.add_constraint(d[i] >= earliest[i])37 for i in nodes:38 mdl.add_constraint(d[i] <= latest[i])39 mdl.parameters.timelimit = time_limit # timelimit = 30 minutes40 mdl.parameters.threads = 1 # only one cpu thread in use41 solution = mdl.solve(log_output = verbose)42 solution_edges = SortedDict()43 for i,j in edges:44 if x[(i,j)].solution_value > 0.9:45 solution_edges[j] = i46 objective_value = mdl.objective_value47 time = mdl.solve_details.time48 best_bound = mdl.solve_details.best_bound49 gap = mdl.solve_details.mip_relative_gap50 # to display the solution given by cplex51 if verbose == True:52 solution.display()53 # to visualize the graph54 if vis:55 visualize(ins.xcoords, ins.ycoords, solution_edges)56 return objective_value, time, best_bound, gap57def cplex_solution_indicator(ins, vis = False, time_limit = 1800, verbose = False):58 nodes = ins.nodes59 nnodes = ins.n60 edges = ins.edges61 nodesv = nodes[1:]62 Q = ins.capacity63 earliest = ins.earliest64 latest = ins.latest65 global D66 D = ins.cost67 demands = ins.demands68 # model and variables69 mdl = Model(ins.name)70 x = mdl.binary_var_dict(edges, name = "x") #71 y = mdl.continuous_var_dict(edges, name = "y", lb = 0)72 d = mdl.continuous_var_dict(nodes, name = "d", lb = 0)73 M = max(latest) + D.max() * 274 # objective function75 mdl.minimize(mdl.sum(distance(i,j) * x[(i,j)] for i,j in edges))76 # restrictions77 for j in nodesv:78 mdl.add_constraint(mdl.sum(x[(i,j)] for i in nodes if i!=j) == 1)79 for j in nodesv:80 mdl.add_constraint(mdl.sum(y[(i,j)] for i in nodes if i!=j) - mdl.sum(y[(j,i)] for i in nodesv if i!=j) == demands[j])81 for i,j in edges:82 mdl.add_constraint(x[(i,j)] <= y[(i,j)])83 for i,j in edges:84 mdl.add_constraint(y[(i,j)] <= Q * x[(i,j)]) # (Q - demands[i]) * x[(i,j)])85 for i,j in edges:86 mdl.add_indicator(x[(i,j)], d[i] + distance(i,j) <= d[j])87 # mdl.add_constraint(d[i] + distance(i,j) - d[j] <= M * (1 - x[(i,j)]))88 for i in nodes:89 mdl.add_constraint(d[i] >= earliest[i])90 for i in nodes:91 mdl.add_constraint(d[i] <= latest[i])92 mdl.parameters.timelimit = time_limit # timelimit = 30 minutes93 mdl.parameters.threads = 1 # only one cpu thread in use94 solution = mdl.solve(log_output = verbose)95 solution_edges = SortedDict()96 for i,j in edges:97 if x[(i,j)].solution_value > 0.9:98 solution_edges[j] = i99 objective_value = mdl.objective_value100 time = mdl.solve_details.time101 best_bound = mdl.solve_details.best_bound102 gap = mdl.solve_details.mip_relative_gap103 # to display the solution given by cplex104 if verbose == True:105 solution.display()106 # to visualize the graph107 if vis:108 visualize(ins.xcoords, ins.ycoords, solution_edges)109 return objective_value, time, best_bound, gap110def relaxed_cplex_solution(ins, vis = False, time_limit = 1800, verbose = False):111 nodes = ins.nodes112 nnodes = ins.n113 edges = ins.edges114 nodesv = nodes[1:]115 Q = ins.capacity116 earliest = ins.earliest117 latest = ins.latest118 global D119 D = ins.cost120 demands = ins.demands121 # model and variables122 mdl = Model(ins.name)123 x = mdl.continuous_var_dict(edges, name = "x", lb = 0, ub = 1) #124 y = mdl.continuous_var_dict(edges, name = "y", lb = 0)125 d = mdl.continuous_var_dict(nodes, name = "d", lb = 0)126 M = max(latest) + D.max() * 2127 # objective function128 mdl.minimize(mdl.sum(distance(i,j) * x[(i,j)] for i,j in edges))129 # restrictions130 for j in nodesv:131 mdl.add_constraint(mdl.sum(x[(i,j)] for i in nodes if i!=j) == 1)132 for j in nodesv:133 mdl.add_constraint(mdl.sum(y[(i,j)] for i in nodes if i!=j) - mdl.sum(y[(j,i)] for i in nodesv if i!=j) == demands[j])134 for i,j in edges:135 mdl.add_constraint(x[(i,j)] <= y[(i,j)])136 for i,j in edges:137 mdl.add_constraint(y[(i,j)] <= Q * x[(i,j)]) # (Q - demands[i]) * x[(i,j)])138 for i,j in edges:139 mdl.add_constraint(d[i] + distance(i,j) - d[j] <= M * (1 - x[(i,j)]))140 for i in nodes:141 mdl.add_constraint(d[i] >= earliest[i])142 for i in nodes:143 mdl.add_constraint(d[i] <= latest[i])144 mdl.parameters.timelimit = time_limit # timelimit = 30 minutes145 mdl.parameters.threads = 1 # only one cpu thread in use146 solution = mdl.solve(log_output = False)147 solution_edges = list()148 intensity = dict()149 for i,j in edges:150 if x[(i,j)].solution_value > 0:151 solution_edges.append((i,j))152 intensity[(i,j)] = x[(i,j)].solution_value153 objective_value = mdl.objective_value154 time = mdl.solve_details.time155 best_bound = mdl.solve_details.best_bound156 gap = mdl.solve_details.mip_relative_gap157 # to display the solution given by cplex...
Squares.py
Source:Squares.py
...12 particle_y = [100, 150, 200]13 for x in particle_x:14 for y in particle_y:15 self.world.add_particle(x, y, mat)16 self.world.add_constraint(self.world.particles[0], self.world.particles[1], 0.4)17 self.world.add_constraint(self.world.particles[1], self.world.particles[2], 0.4)18 self.world.add_constraint(self.world.particles[3], self.world.particles[4], 0.4)19 self.world.add_constraint(self.world.particles[4], self.world.particles[5], 0.4)20 self.world.add_constraint(self.world.particles[6], self.world.particles[7], 0.4)21 self.world.add_constraint(self.world.particles[7], self.world.particles[8], 0.4)22 self.world.add_constraint(self.world.particles[0], self.world.particles[3], 0.4)23 self.world.add_constraint(self.world.particles[3], self.world.particles[6], 0.4)24 self.world.add_constraint(self.world.particles[1], self.world.particles[4], 0.4)25 self.world.add_constraint(self.world.particles[4], self.world.particles[7], 0.4)26 self.world.add_constraint(self.world.particles[2], self.world.particles[5], 0.4)27 self.world.add_constraint(self.world.particles[5], self.world.particles[8], 0.4)28 self.world.add_constraint(self.world.particles[0], self.world.particles[4], 0.4)29 self.world.add_constraint(self.world.particles[1], self.world.particles[3], 0.4)30 self.world.add_constraint(self.world.particles[3], self.world.particles[7], 0.4)31 self.world.add_constraint(self.world.particles[4], self.world.particles[6], 0.4)32 self.world.add_constraint(self.world.particles[1], self.world.particles[5], 0.4)33 self.world.add_constraint(self.world.particles[2], self.world.particles[4], 0.4)34 self.world.add_constraint(self.world.particles[5], self.world.particles[7], 0.4)35 self.world.add_constraint(self.world.particles[4], self.world.particles[8], 0.4)36 def update(self):37 if game.mouse.get_pressed()[0]:38 if self.grabbed == None:39 closest = self.closest_point()40 if closest[1] < self.radius:41 self.grabbed = closest[0]42 if self.grabbed != None:43 mouse = Vector(game.mouse.get_pos()[0], game.mouse.get_pos()[1])44 force = (mouse - self.grabbed.position) * self.strength45 self.grabbed.apply_impulse(force)46 else:47 self.grabbed = None48 if game.key.get_pressed()[game.K_ESCAPE]:49 self.exit()...
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