v-if用法 and or

时间: 2023-11-10 18:00:47 浏览: 38
在Python中,v-if语法并不存在。v-if是Vue.js中的指令,用于条件性地渲染DOM元素。它的作用是根据指定的条件决定是否显示或隐藏某个元素。 在Python中,我们使用if语句来实现条件判断和分支执行的逻辑。if语句后面跟着一个条件表达式,该表达式的值为True或False。根据条件表达式的结果,决定是否执行相应的代码块。 在Python中,and和or是逻辑运算符。and运算符表示"与"的关系,只有当所有条件都为True时,整个表达式才为True。or运算符表示"或"的关系,只要有一个条件为True,整个表达式就为True。
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[root@localhost ~]# kubeadm init --image-repository registry.aliyuncs.com/google_containers --kubernetes-version v1.26.2 --apiserver-advertise-address 192.168.0.4 --pod-network-cidr=10.244.0.0/16 --token-ttl 0 [init] Using Kubernetes version: v1.26.2 [preflight] Running pre-flight checks error execution phase preflight: [preflight] Some fatal errors occurred: [ERROR KubeletVersion]: the kubelet version is higher than the control plane version. This is not a supported version skew and may lead to a malfunctional cluster. Kubelet version: "1.27.3" Control plane version: "1.26.2" [preflight] If you know what you are doing, you can make a check non-fatal with `--ignore-preflight-errors=...` To see the stack trace of this error execute with --v=5 or higher

根据您提供的日志信息,问题出现在 kubelet 版本与控制平面版本不匹配上。这是一个不支持的版本差异,可能导致集群功能异常。 在您的命令行中,kubelet 版本为 "1.27.3",而控制平面版本为 "1.26.2"。为了解决这个问题,您可以尝试以下步骤: 1. 升级控制平面版本:确保您的控制平面组件(kube-apiserver、kube-controller-manager、kube-scheduler)与 kubelet 版本匹配。您可以更新相应的组件版本,以使其与 kubelet 版本保持一致。 2. 降低 kubelet 版本:如果您希望继续使用当前的控制平面版本,您可以尝试将 kubelet 版本降低到与控制平面版本匹配的版本。 请注意,这是一个不支持的版本组合,可能会导致集群的稳定性和功能问题。建议您使用兼容的版本组合来确保集群的正常运行。 另外,您还可以使用 `--ignore-preflight-errors=KubeletVersion` 参数来忽略版本不匹配的警告,但这并不推荐,因为它可能导致集群不稳定。最好的解决方法是确保版本匹配。

用c++解决You surely know that there are N different currencies you can deal with in our city. Let us assign unique integer number from 1 to N to each currency. Then each exchange point can be described with 6 numbers: integer A and B - numbers of currencies it exchanges, and real RAB, CAB, RBA and CBA - exchange rates and commissions when exchanging A to B and B to A respectively. Nick has some money in currency S and wonders if he can somehow, after some exchange operations, increase his capital. Of course, he wants to have his money in currency S in the end. Help him to answer this difficult question. Nick must always have non-negative sum of money while making his operations. Input The first line contains four numbers: N - the number of currencies, M - the number of exchange points, S - the number of currency Nick has and V - the quantity of currency units he has. The following M lines contain 6 numbers each - the description of the corresponding exchange point - in specified above order. Numbers are separated by one or more spaces. 1 ≤ S ≤ N ≤ 100, 1 ≤ M ≤ 100, V is real number, 0 ≤ V ≤ 103. For each point exchange rates and commissions are real, given with at most two digits after the decimal point, 10-2 ≤ rate ≤ 102, 0 ≤ commission ≤ 102. Let us call some sequence of the exchange operations simple if no exchange point is used more than once in this sequence. You may assume that ratio of the numeric values of the sums at the end and at the beginning of any simple sequence of the exchange operations will be less than 104. Output If Nick can increase his wealth, output YES, in other case output NO.

以下是使用C++解决该问题的代码示例: ``` #include <iostream> #include <vector> #include <cstdio> #include <cstring> using namespace std; const int MAXN = 110; const double INF = 1e9; struct Edge { int from, to; double rate, commission; Edge(int from, int to, double rate, double commission) : from(from), to(to), rate(rate), commission(commission) {} }; vector<Edge> edges; double dist[MAXN]; bool bellman_ford(int n, int m, int s, double v) { memset(dist, 0, sizeof(dist)); dist[s] = v; for (int i = 0; i < n - 1; i++) { bool updated = false; for (int j = 0; j < m; j++) { Edge e = edges[j]; if (dist[e.from] > e.commission && dist[e.from] * e.rate - e.commission > dist[e.to]) { dist[e.to] = dist[e.from] * e.rate - e.commission; updated = true; } } if (!updated) { break; } } for (int j = 0; j < m; j++) { Edge e = edges[j]; if (dist[e.from] > e.commission && dist[e.from] * e.rate - e.commission > dist[e.to]) { return true; } } return false; } int main() { int n, m, s; double v; scanf("%d%d%d%lf", &n, &m, &s, &v); for (int i = 0; i < m; i++) { int a, b; double rab, cab, rba, cba; scanf("%d%d%lf%lf%lf%lf", &a, &b, &rab, &cab, &rba, &cba); edges.push_back(Edge(a, b, rab, cab)); edges.push_back(Edge(b, a, rba, cba)); } if (bellman_ford(n, m * 2, s, v)) { printf("YES\n"); } else { printf("NO\n"); } return 0; } ``` 该代码使用了Bellman-Ford算法来判断是否可以增加资产。具体实现方法为:首先将起始点的资产赋值为v,其余点的资产赋值为0;然后进行n-1轮松弛操作,每次遍历所有边,如果满足条件(即当前点的资产大于手续费,且通过该边操作后能够得到更多的资产),则更新该点的资产;最后再进行一轮遍历,如果仍然满足条件,则说明可以增加资产,否则不能。

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UnZip 6.00 of 20 April 2009, by Info-ZIP. Maintained by C. Spieler. Send bug reports using http://www.info-zip.org/zip-bug.html; see README for details. Usage: unzip [-Z] [-opts[modifiers]] file[.zip] [list] [-x xlist] [-d exdir] Default action is to extract files in list, except those in xlist, to exdir; file[.zip] may be a wildcard. -Z => ZipInfo mode ("unzip -Z" for usage). -p extract files to pipe, no messages -l list files (short format) -f freshen existing files, create none -t test compressed archive data -u update files, create if necessary -z display archive comment only -v list verbosely/show version info -T timestamp archive to latest -x exclude files that follow (in xlist) -d extract files into exdir modifiers: -n never overwrite existing files -q quiet mode (-qq => quieter) -o overwrite files WITHOUT prompting -a auto-convert any text files -j junk paths (do not make directories) -aa treat ALL files as text -U use escapes for all non-ASCII Unicode -UU ignore any Unicode fields -C match filenames case-insensitively -L make (some) names lowercase -X restore UID/GID info -V retain VMS version numbers -K keep setuid/setgid/tacky permissions -M pipe through "more" pager -O CHARSET specify a character encoding for DOS, Windows and OS/2 archives -I CHARSET specify a character encoding for UNIX and other archives See "unzip -hh" or unzip.txt for more help. Examples: unzip data1 -x joe => extract all files except joe from zipfile data1.zip unzip -p foo | more => send contents of foo.zip via pipe into program more unzip -fo foo ReadMe => quietly replace existing ReadMe if archive file newer

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帮我翻译代码:def splitRoutes(node_id_list,model):V={i:[] for i in model.demand_id_list} V[-1]=[[0]*(len(model.vehicle_type_list)+4)] V[-1][0][0]=1 V[-1][0][1]=1 number_of_lables=1 for i in range(model.number_of_demands): n_1=node_id_list[i] j=i load=0 distance={v_type:0 for v_type in model.vehicle_type_list} while True: n_2=node_id_list[j] load=load+model.demand_dict[n_2].demand stop = False for k,v_type in enumerate(model.vehicle_type_list): vehicle=model.vehicle_dict[v_type] if i == j: distance[v_type]=model.distance_matrix[v_type,n_1]+model.distance_matrix[n_1,v_type] else: n_3=node_id_list[j-1] distance[v_type]=distance[v_type]-model.distance_matrix[n_3,v_type]+model.distance_matrix[n_3,n_2]\ +model.distance_matrix[n_2,v_type] route=node_id_list[i:j+1] route.insert(0,v_type) route.append(v_type) "检查时间窗口。只有在满足时间窗口时才能生成新标签。否则,跳过“" if not checkTimeWindow(route,model,vehicle): continue for id,label in enumerate(V[i-1]): if load<=vehicle.capacity and label[k+4]<vehicle.numbers: stop=True if model.opt_type==0: cost=vehicle.fixed_cost+distance[v_type]vehicle.variable_cost else: cost=vehicle.fixed_cost+distance[v_type]/vehicle.free_speedvehicle.variable_cost W=copy.deepcopy(label) "set the previous label id " W[1]=V[i-1][id][0] "set the vehicle type" W[2]=v_type "update travel cost" W[3]=W[3]+cost "update the number of vehicles used" W[k+4]=W[k+4]+1 if checkResidualCapacity(node_id_list[j+1:],W,model): label_list,number_of_lables=updateNodeLabels(V[j],W,number_of_lables) V[j]=label_list j+=1 if j>=len(node_id_list) or stop==False: break if len(V[model.number_of_demands-1])>0: route_list=extractRoutes(V, node_id_list, model) return route_list else: print("由于容量不足,无法拆分节点id列表") return None

class SVDRecommender: def __init__(self, k=50, ncv=None, tol=0, which='LM', v0=None, maxiter=None, return_singular_vectors=True, solver='arpack'): self.k = k self.ncv = ncv self.tol = tol self.which = which self.v0 = v0 self.maxiter = maxiter self.return_singular_vectors = return_singular_vectors self.solver = solver def svds(self, A): if self.which == 'LM': largest = True elif self.which == 'SM': largest = False else: raise ValueError("which must be either 'LM' or 'SM'.") if not (isinstance(A, LinearOperator) or isspmatrix(A) or is_pydata_spmatrix(A)): A = np.asarray(A) n, m = A.shape if self.k <= 0 or self.k >= min(n, m): raise ValueError("k must be between 1 and min(A.shape), k=%d" % self.k) if isinstance(A, LinearOperator): if n > m: X_dot = A.matvec X_matmat = A.matmat XH_dot = A.rmatvec XH_mat = A.rmatmat else: X_dot = A.rmatvec X_matmat = A.rmatmat XH_dot = A.matvec XH_mat = A.matmat dtype = getattr(A, 'dtype', None) if dtype is None: dtype = A.dot(np.zeros([m, 1])).dtype else: if n > m: X_dot = X_matmat = A.dot XH_dot = XH_mat = _herm(A).dot else: XH_dot = XH_mat = A.dot X_dot = X_matmat = _herm(A).dot def matvec_XH_X(x): return XH_dot(X_dot(x)) def matmat_XH_X(x): return XH_mat(X_matmat(x)) XH_X = LinearOperator(matvec=matvec_XH_X, dtype=A.dtype, matmat=matmat_XH_X, shape=(min(A.shape), min(A.shape))) #获得隐式定义的格拉米矩阵的低秩近似。 eigvals, eigvec = eigsh(XH_X, k=self.k, tol=self.tol ** 2, maxiter=self.maxiter, ncv=self.ncv, which=self.which, v0=self.v0) #格拉米矩阵有实非负特征值。 eigvals = np.maximum(eigvals.real, 0) #使用来自pinvh的小特征值的复数检测。 t = eigvec.dtype.char.lower() factor = {'f': 1E3, 'd': 1E6} cond = factor[t] * np.finfo(t).eps cutoff = cond * np.max(eigvals) #获得一个指示哪些本征对不是简并微小的掩码, #并为阈值奇异值创建一个重新排序数组。 above_cutoff = (eigvals > cutoff) nlarge = above_cutoff.sum() nsmall = self.k - nlarge slarge = np.sqrt(eigvals[above_cutoff]) s = np.zeros_like(eigvals) s[:nlarge] = slarge if not self.return_singular_vectors: return np.sort(s) if n > m: vlarge = eigvec[:, above_cutoff] ularge = X_matmat(vlarge) / slarge if self.return_singular_vectors != 'vh' else None vhlarge = _herm(vlarge) else: ularge = eigvec[:, above_cutoff] vhlarge = _herm(X_matmat(ularge) / slarge) if self.return_singular_vectors != 'u' else None u = _augmented_orthonormal_cols(ularge, nsmall) if ularge is not None else None vh = _augmented_orthonormal_rows(vhlarge, nsmall) if vhlarge is not None else None indexes_sorted = np.argsort(s) s = s[indexes_sorted] if u is not None: u = u[:, indexes_sorted] if vh is not None: vh = vh[indexes_sorted] return u, s, vh def _augmented_orthonormal_cols(U, n): if U.shape[0] <= n: return U Q, R = np.linalg.qr(U) return Q[:, :n] def _augmented_orthonormal_rows(V, n): if V.shape[1] <= n: return V Q, R = np.linalg.qr(V.T) return Q[:, :n].T def _herm(x): return np.conjugate(x.T) 将上述代码修改为使用LM,迭代器使用arpack

class svd_recommender_py(): #svd矩阵推荐 def svds(A, ncv=None, tol=0, which='LM', v0=None, maxiter=None, return_singular_vectors=True, solver='arpack'): if which == 'LM': largest = True elif which == 'SM': largest = False else: raise ValueError("which must be either 'LM' or 'SM'.") if not (isinstance(A, LinearOperator) or isspmatrix(A) or is_pydata_spmatrix(A)): A = np.asarray(A) n, m = A.shape if k <= 0 or k >= min(n, m): raise ValueError("k must be between 1 and min(A.shape), k=%d" % k) if isinstance(A, LinearOperator): if n > m: X_dot = A.matvec X_matmat = A.matmat XH_dot = A.rmatvec XH_mat = A.rmatmat else: X_dot = A.rmatvec X_matmat = A.rmatmat XH_dot = A.matvec XH_mat = A.matmat dtype = getattr(A, 'dtype', None) if dtype is None: dtype = A.dot(np.zeros([m, 1])).dtype else: if n > m: X_dot = X_matmat = A.dot XH_dot = XH_mat = _herm(A).dot else: XH_dot = XH_mat = A.dot X_dot = X_matmat = _herm(A).dot def matvec_XH_X(x): return XH_dot(X_dot(x)) def matmat_XH_X(x): return XH_mat(X_matmat(x)) XH_X = LinearOperator(matvec=matvec_XH_X, dtype=A.dtype, matmat=matmat_XH_X, shape=(min(A.shape), min(A.shape))) # Get a low rank approximation of the implicitly defined gramian matrix. #获得隐式定义的格拉米矩阵的低秩近似。 #这不是解决问题的稳定方法。 solver == 'arpack' eigvals, eigvec = eigsh(XH_X, k=k, tol=tol ** 2, maxiter=maxiter, ncv=ncv, which=which, v0=v0) #格拉米矩阵具有实非负特征值。 eigvals = np.maximum(eigvals.real, 0) #使用来自pinvh的小特征值的复杂检测。 t = eigvec.dtype.char.lower() factor = {'f': 1E3, 'd': 1E6} cond = factor[t] * np.finfo(t).eps cutoff = cond * np.max(eigvals) #得到一个指示哪些本征对不是退化微小的掩码, #并创建阈值奇异值的重新排序数组。 above_cutoff = (eigvals > cutoff) nlarge = above_cutoff.sum() nsmall = k - nlarge slarge = np.sqrt(eigvals[above_cutoff]) s = np.zeros_like(eigvals) s[:nlarge] = slarge if not return_singular_vectors: return np.sort(s) if n > m: vlarge = eigvec[:, above_cutoff] ularge = X_matmat(vlarge) / slarge if return_singular_vectors != 'vh' else None vhlarge = _herm(vlarge) else: ularge = eigvec[:, above_cutoff] vhlarge = _herm(X_matmat(ularge) / slarge) if return_singular_vectors != 'u' else None u = _augmented_orthonormal_cols(ularge, nsmall) if ularge is not None else None vh = _augmented_orthonormal_rows(vhlarge, nsmall) if vhlarge is not None else None indexes_sorted = np.argsort(s) s = s[indexes_sorted] if u is not None: u = u[:, indexes_sorted] if vh is not None: vh = vh[indexes_sorted] return u, s, vh这段代码主要是为了将scipy包中的SVD计算方法封装成一个自定义类,是否封装合适?如果不合适,给出修改后的完整代码

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