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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