n_neighbors=15, n_pcs=20) computing neighbors using 'X_pca' with = 20 finished: added to `.uns ', 'total_counts', 'highly_variable', 'means', 'dispersions', 'dispersions_norm', 'mean', 'std' uns ', connectivities subtree (adata.uns) (0:00:00) sc.pl.paga(adata_new, color=['cell type','CXCL14']) --> added 'pos', the PAGA positions (adata.uns['paga']) #adata_new.uns['iroot'] = np.flatnonzero(adata_new.obs positions (adata.uns['paga']) 下面我又做了作者没有做的所有细胞类型的拟时序分析!
fprintf(fid,'depth= %d; \n',depth); fprintf(fid,'width= %d; \n',width); fprintf(fid,'address_radix=uns ;\n'); fprintf(fid,'data_radix = uns;\n'); fprintf(fid,'Content Begin \n'); for(k=1:depth) fprintf 图3 log函数图 部分Rom表: depth= 256; %数据深度 width= 8; %数据位宽 address_radix=uns; data_radix = uns; Content
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5025 × 1000 obs: 'n_counts_all', 'leiden' var: 'gene_ids', 'feature_types', 'n_counts' uns adjacency Sparse adjacency matrix of the graph, defaults to `adata.uns['neighbors'][' ) 'paga/connectivities_tree', connectivities subtree (adata.uns) (0:00:00) adata.var_names Out[304 Requires that `adata.uns` contains a directed single-cell graph with key `['velocity_graph']` **connectivities_tree** : :class:`scipy.sparse.csr_matrix` (adata.uns['connectivities_tree'])
选择 File > Mesh >Save Mesh As… ,我们这里保存已生成的网格为 1.uns ,后面组装的时候要 用到此文件。 3 、按照相同的步骤对模型 2 与模型 3 进行网格文件,同时保存网格文件为 2.uns 与 3.uns 。
n_vars = 2638 × 1838 obs: 'n_genes', 'percent_mito', 'n_counts', 'louvain' var: 'n_cells' uns ', 'louvain' var: 'n_counts', 'means', 'dispersions', 'dispersions_norm', 'highly_variable' uns 2638 × 208 obs: 'n_genes', 'percent_mito', 'n_counts', 'louvain', 'leiden' var: 'n_cells' uns sc.tl.ingest(adata, adata_ref, obs='louvain') adata.uns['louvain_colors'] = adata_ref.uns['louvain_colors , 'n_counts-new', 'means-new', 'dispersions-new', 'dispersions_norm-new', 'highly_variable-new' uns
dominant cell type to the adata.obs slot with the same key as the cell type scores added to the adata.uns spot_mixtures.index.values==data.obs_names.values)) # NOTE: using the same key in data.obs & data.uns data.obs['cell_type'] = data.obs['cell_type'].astype('category') # Adding the cell type scores data.uns ['lr_summary']中的行名一样且顺序一致 LR结果的summary在data.uns['lr_summary']中: 3.P-value矫正 可以使用不同的方法矫正 p 值; p 值已经通过运行 p_adjs, -log10(p_adjs), lr_sig_scores # Just choosing one of the top from lr_summary best_lr = data.uns
# 如果值是 65535,则表示使用uns2标准,即:2个字节表示 # 如果值是 1114111,则表示使用uns4标准,即:4个字节表示 8、查看Python默认的编码格式。
obs: 'clusters_coarse', 'clusters', 'S_score', 'G2M_score' var: 'highly_variable_genes' uns layers: 'spliced', 'unspliced' scVelo 是基于adata,存储了数据矩阵adata.X、观测注释adata.obs、变量adata.var和非结构化注释的对象adata.uns finished (0:00:10) --> added 'velocity_graph', sparse matrix with cosine correlations (adata.uns [12]: scv.tl.rank_velocity_genes(adata, groupby='clusters', min_corr=.3) df = scv.DataFrame(adata.uns subtree (adata.uns) [22]: reads从左/行到右/列读取,例如分配了从Ductal到Ngn3 low EP的可信过渡。
for (int i = 0; i < utxos.Count; i++) { ListUnspentResponse uns = utxos[i]; GetTransactionResponse response = rpc.GetTransaction(uns.TxId); // response.BlockTime // uns.Amount.ToString("0.00000000 ") // uns.Confirmations // uns.Address } 构建交易 比特币的一条交易由输入和输出构成,用下面语句构成: CreateRawTransactionRequest
下面使用一个简单的.mif文件举例: width=14; %存储器的位宽 横向宽度 depth =1024; %存储器的深度 总共有多少个数据 address_radix=uns sine.mif','wt'); fprintf(fid,'width=14;\n'); fprintf(fid,'depth =1024;\n'); fprintf(fid,'address_radix=uns
所以,这张表.X的对象cell相关的信息记录在.obs中,属性gene的信息记录在.var中,其他的信息在.uns中。那么每一部分是什么呢? length #observations. var Key-indexed one-dimensional variables annotation of length #variables. uns adjacency Sparse adjacency matrix of the graph, defaults to `adata.uns['neighbors'][' key_added The key in `adata.uns` information is saved to. **pvals** : structured `np.ndarray` (`.uns['rank_genes_groups']`) p-values.
obs: 'clusters_coarse', 'clusters', 'S_score', 'G2M_score' var: 'highly_variable_genes' uns finished (0:00:12) --> added 'velocity_graph', sparse matrix with cosine correlations (adata.uns finished (0:00:07) --> added 'velocity_graph', sparse matrix with cosine correlations (adata.uns object with n_obs × n_vars = 2930 × 13913 obs: 'clusters', 'age(days)', 'clusters_enlarged' uns , arrow_size=1.5) [11]: scv.tl.rank_velocity_genes(adata, groupby='clusters') scv.DataFrame(adata.uns
AagLS84uNS~5@@u#dKrNxHC"); }); options.ConfigureHttpsDefaults(co => { co.SslProtocols AagLS84uNS~5@@u#dKrNxHC"); }); }); 那只能说明代码有问题,既然已经设置了,但是未生效,so,那说明放的顺序有问题,那我将上述设置协议放在监听HTTPS AagLS84uNS~5@@u#dKrNxHC"); }); options.Listen(IPAddress.Any, 5000); }); 没啥可总结的 ,大意失荆州,一度怀疑配置了
array_col', 'sum_counts', 'imagecol', 'imagerow' var: 'gene_ids', 'feature_types', 'genome' uns 'imagerow', 'louvain' var: 'gene_ids', 'feature_types', 'genome', 'n_cells', 'mean', 'std' uns sub_cluster_labels', 'dpt_pseudotime' var: 'gene_ids', 'feature_types', 'genome', 'n_cells', 'mean', 'std' uns sub_cluster_labels', 'dpt_pseudotime' var: 'gene_ids', 'feature_types', 'genome', 'n_cells', 'mean', 'std' uns layers: 'raw_count', 'normal_count', 'scale_count' obsp: 'distances', 'connectivities' data.uns
obs: 'in_tissue', 'array_row', 'array_col' var: 'gene_ids', 'feature_types', 'genome' uns array_row', 'array_col', 'mt_frac', 'total_counts' var: 'gene_ids', 'feature_types', 'genome' uns : 'images', 'scalefactors' obsm: 'X_spatial' adata.uns['images']['hires'][1] Out[24]: array([[ ..., [ 7594, 18294], [ 7190, 14730], [10484, 5709]], dtype=int64) adata.uns feature_types', 'genome', 'n_cells', 'highly_variable', 'means', 'dispersions', 'dispersions_norm' uns
NL80211_CMD_SET_STATION, .doit = nl80211_set_station, .policy = nl80211_policy, .flags = GENL_UNS_ADMIN_PERM NL80211_CMD_NEW_STATION, .doit = nl80211_new_station, .policy = nl80211_policy, .flags = GENL_UNS_ADMIN_PERM NL80211_CMD_DEL_STATION, .doit = nl80211_del_station, .policy = nl80211_policy, .flags = GENL_UNS_ADMIN_PERM
知识的掌握程度用UNS表示,它有4个水平,即Very Low、Low、Middle、High。 file.choose()) Test <- read.csv(file = file.choose()) #加载CART算法所需的扩展包,并构建模型 library(rpart) fit <- rpart(UNS fit2 = rpart(UNS ~ ., data = Train, parms = list(loss = cost)) Pred2 = predict(fit2, Test[,-6], type
Service Segment包括: Envelopes (UNB-UNZ, UNG-UNE, UNH-UNT) Delimiter String Advice (UNA) Section Separator (UNS 4567890123456::9′ 名称和地址 收货地GLN LIN+1++4123456789012:EN’ 订单行明细 GTIN QTY+21:10:PCE’ 数量 订购数量 PRI+AAA:9.99′ 价格明细 净价 UNS
utm_source=LCUS&utm_medium=ip_redirect_q_uns&utm_campaign=transfer2china [2] 【Leetcode】罗马数字转整数: https utm_source=LCUS&utm_medium=ip_redirect_q_uns&utm_campaign=transfer2china
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