apply | 易学教程

Can inline CSS apply to child elements nested in the styled element?

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可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 由翻译强力驱动问题: This is the problem in a nutshell: I want to apply the style vertical-align: top to every <tr> in a table, without manually applying the style to every row. I have to use inline CSS because I'm on a wiki, so I can't edit the external style sheet, or edit the <head> to embed a style. When I add a style attribute to a <table> tag, it appears this style is not passed on to its child elements. (I can see how this is nearly always a good thing.) I can't use <style></style> , because that is not a permitted tag on MediaWiki

git: patch does not apply

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可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: I have a certain patch called my_pcc_branch.patch. When I try to apply it, I get following message: $ git apply --check my_pcc_branch.patch warning: src/main/java/.../AbstractedPanel.java has type 100644, expected 100755 error: patch failed: src/main/java/.../AbstractedPanel.java:13 error: src/main/java/.../AbstractedPanel.java: patch does not apply What does it mean? How can I fix this problem? 回答1: Johannes Sixt from the msysgit@googlegroups.com mailing list suggested using following command line arguments: git apply --ignore-space-change

TypeError: $scope.apply is not a function

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可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: I am trying to render the contacts list after retrieving it thru rdflib.js . It is loading properly and saving it in the list inside the scope. But I am not able to render sine the $scope doesn't update, it seems like I am calling $scope.apply() in the wrong place. The error occurs because I call it outside angular, but I am deliberately calling it inside the function that is outside angular context ( nowOrWhenFetched ), so not making sense for me. any help? $scope.load = function () { //$scope.getContactsList(); var g = $rdf.graph(); var f

Apply a function to every row of a matrix or a data frame

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可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: Suppose I have a n by 2 matrix and a function that takes a 2-vector as one of its arguments. I would like to apply the function to each row of the matrix and get a n-vector. How to do this in R? For example, I would like to compute the density of a 2D standard Normal distribution on three points: bivariate.density(x = c(0, 0), mu = c(0, 0), sigma = c(1, 1), rho = 0){ exp(-1/(2*(1-rho^2))*(x[1]^2/sigma[1]^2+x[2]^2/sigma[2]^2-2*rho*x[1]*x[2]/(sigma[1]*sigma[2]))) * 1/(2*pi*sigma[1]*sigma[2]*sqrt(1-rho^2)) } out How to apply the function to

three.js - apply different material to extruded shape

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可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: I have Three.Shape which I can apply Extrusion To get a plane I drew a square first and then apply extrusion var squareShape = new THREE.Shape(); squareShape.moveTo( 0,0 ); squareShape.lineTo( 0, sqLength ); squareShape.lineTo( sqLength, sqLength ); squareShape.lineTo( sqLength, 0 ); squareShape.lineTo( 0, 0 ); var geometry = new THREE.ExtrudeGeometry( squareShape,extrudeSettings); now a 3D square is appearing on my browser. Next I want to apply a image texture of 256x256 on its top face. How to do this? 回答1: If you look at src/extras

Apply over two data frames

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问题 I'm using R, and I have two data.frames, A and B . They both have 6 rows, but A has 25000 columns (genes), and B has 30 columns. I'd like to apply a function with two arguments f(x,y) where x is every column of A and y is every column of B . So far it looks like this: i = 1 for (x in A){ j = 1 for (y in B){ out[i,j] <- f(x,y) j = j + 1 } i = i + 1 } I have two issues with this: from my Python programming I associate keeping track of counters like this as crufty, and from my R programming I am

Python pandas apply function if a column value is not NULL

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问题 I have a dataframe (in Python 2.7, pandas 0.15.0): df= A B C 0 NaN 11 NaN 1 two NaN ['foo', 'bar'] 2 three 33 NaN I want to apply a simple function for rows that does not contain NULL values in a specific column. My function is as simple as possible: def my_func(row): print row And my apply code is the following: df[['A','B']].apply(lambda x: my_func(x) if(pd.notnull(x[0])) else x, axis = 1) It works perfectly. If I want to check column 'B' for NULL values the pd.notnull() works perfectly as

Apply function to each column in a data frame observing each columns existing data type

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问题 I'm trying to get the min/max for each column in a large data frame, as part of getting to know my data . My first try was: apply(t,2,max,na.rm=1) It treats everything as a character vector, because the first few columns are character types. So max of some of the numeric columns is coming out as " -99.5" . I then tried this: sapply(t,max,na.rm=1) but it complains about max not meaningful for factors . ( lapply is the same.) What is confusing me is that apply thought max was perfectly

How to apply summarise_each to all columns except one? [duplicate]

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可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 由翻译强力驱动问题: This question already has an answer here: Aggregate / summarize multiple variables per group (e.g. sum, mean) 4 answers I am analyzing a set of data with many columns (almost 30 columns). I want to group data based on two columns and apply sum and mean functions to all the columns except timestamp. How would I use summarise_each on all columns except timestamp? This is the draft code I have but it obviously not correct. Plus it generates and error because it can not apply Sum to POSIXt data type (Error: 'sum' not defined for

How to apply gradient clipping in TensorFlow?

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可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: Considering the example code . I would like to know How to apply gradient clipping on this network on the RNN where there is a possibility of exploding gradients. tf.clip_by_value(t, clip_value_min, clip_value_max, name=None) This is an example that could be used but where do I introduce this ? In the def of RNN lstm_cell = rnn_cell.BasicLSTMCell(n_hidden, forget_bias=1.0) # Split data because rnn cell needs a list of inputs for the RNN inner loop _X = tf.split(0, n_steps, _X) # n_steps tf.clip_by_value(_X, -1, 1, name=None) But this doesn't

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