python-2.7

问题 I'm working with the "itemchanged" signal. How can I find out the row and column where the item was changed? I only found the same question for c++, but I'm using python. 回答1: The slot you connect to the itemChanged() signal receives a reference to the QTableWidgetItem that changed. You should be able to call the row() and column() functions of this object to determine the row/column. For example, the code to register your slot might look like this: self.imagesTable.itemChanged.connect(self

问题 I am given a string which is of this pattern: [blah blah blah] [more blah] some text I want to split the string into three parts: blah blah blah , more blah and some text . A crude way to do it is to use mystr.split('] ') , and then removes the lead [ from the first two elements. Is there a better and performant way (need to do this for thousands of strings very quickly). 回答1: You can use a regular expression to extract the text, if you know that it will be in that form. For efficiency, you

问题 I am given a string which is of this pattern: [blah blah blah] [more blah] some text I want to split the string into three parts: blah blah blah , more blah and some text . A crude way to do it is to use mystr.split('] ') , and then removes the lead [ from the first two elements. Is there a better and performant way (need to do this for thousands of strings very quickly). 回答1: You can use a regular expression to extract the text, if you know that it will be in that form. For efficiency, you

问题 I am trying to train a model to identify images containing fire VS images that contain forests. I am training the model on a remote server using Linode. I am using Python 2.7 and Ubuntu 16.04.5. When i run the following code locally or in Jupyter notebooks it will create 2 classes, but when i want to run it on the server it creates 3 classes. The code that classifies the model: def onehot(x): return np.array(OneHotEncoder().fit_transform(x.reshape(-1,1)).todense()) model = keras.applications

问题 I am trying to train a model to identify images containing fire VS images that contain forests. I am training the model on a remote server using Linode. I am using Python 2.7 and Ubuntu 16.04.5. When i run the following code locally or in Jupyter notebooks it will create 2 classes, but when i want to run it on the server it creates 3 classes. The code that classifies the model: def onehot(x): return np.array(OneHotEncoder().fit_transform(x.reshape(-1,1)).todense()) model = keras.applications

问题 I am trying to figure out how to aggregate groups in Pandas data frame by creating a percentage and summation on the new columns. For example, in the following data frame, I have columns A, B, C, and D. I would like to aggregate by groups in A, and C should be a percent of (frequency of '1' divided by frequency of non-missing value), and D should be a summation of non-missing values. For example, for 'foo' group, the resulting data frame should be A B C D foo 1.333 4 I am able to do some of

问题 I am trying to figure out how to aggregate groups in Pandas data frame by creating a percentage and summation on the new columns. For example, in the following data frame, I have columns A, B, C, and D. I would like to aggregate by groups in A, and C should be a percent of (frequency of '1' divided by frequency of non-missing value), and D should be a summation of non-missing values. For example, for 'foo' group, the resulting data frame should be A B C D foo 1.333 4 I am able to do some of

问题 Currently I am using odoov8, my problem is that I have created many filters from xml code as per my requirement and all are working fine ,but I can select only one filter at a time . so for example I want to apply any 3 Filters in tree view , then I need to select first one , then system loads the data , then I select 2nd and then 3rd filter , so system is loading after applying each filter . I want to achieve that if I can select all my filters at once and then I can apply search , so system

问题 Currently I am using odoov8, my problem is that I have created many filters from xml code as per my requirement and all are working fine ,but I can select only one filter at a time . so for example I want to apply any 3 Filters in tree view , then I need to select first one , then system loads the data , then I select 2nd and then 3rd filter , so system is loading after applying each filter . I want to achieve that if I can select all my filters at once and then I can apply search , so system

问题 I'm seeing non-deterministic behavior when trying to select a pseudo-random element from sets, even though the RNG is seeded (example code shown below). Why is this happening, and should I expect other Python data types to show similar behavior? Notes: I've only tested this on Python 2.7, but it's been reproducible on two different Windows computers. Similar Issue: The issue at Python random seed not working with Genetic Programming example code may be similar. Based on my testing, my