array

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: I think that my issue should be really simple, yet I can not find any help on the Internet whatsoever. I am very new to Python, so it is possible that I am missing something very obvious. I have an array, S, like this [x x x] (one-dimensional) . I now create a diagonal matrix, sigma , with np.diag(S) - so far, so good. Now, I want to resize this new diagonal array so that I can multiply it by another array that I have. import numpy as np ... shape = np . shape (( 6 , 6 )) #This will be some pre-determined size sigma = np . diag ( S

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 was wondering about an initialization of the following form: int array[] = { v - 1, array[0] + 1 } ; In the initialization of the second element, the value of the first is used, but the entire array is not yet initialized. This happens to compile with g++, but I was unsure whether this is actually portable and a well defined construct? 回答1: See 3.3.2 Point of declaration: The point of declaration for a name is immediately after its complete declarator (Clause 8) and before its initializer (if any), except as noted below. [ Example: int x =

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: Say I construct two numpy arrays: a = np.array([np.NaN, np.NaN]) b = np.array([np.NaN, np.NaN, 3]) Now I find that np.mean returns nan for both a and b : >>> np.mean(a) nan >>> np.mean(b) nan Since numpy 1.8 (released 20 April 2016), we've been blessed with nanmean , which ignores nan values: >>> np.nanmean(b) 3.0 However, when the array has nothing but nan values, it raises a warning: >>> np.nanmean(a) nan C:\python-3.4.3\lib\site-packages\numpy\lib\nanfunctions.py:598: RuntimeWarning: Mean of empty slice warnings.warn("Mean of empty slice"

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: Say I construct two numpy arrays: a = np.array([np.NaN, np.NaN]) b = np.array([np.NaN, np.NaN, 3]) Now I find that np.mean returns nan for both a and b : >>> np.mean(a) nan >>> np.mean(b) nan Since numpy 1.8 (released 20 April 2016), we've been blessed with nanmean , which ignores nan values: >>> np.nanmean(b) 3.0 However, when the array has nothing but nan values, it raises a warning: >>> np.nanmean(a) nan C:\python-3.4.3\lib\site-packages\numpy\lib\nanfunctions.py:598: RuntimeWarning: Mean of empty slice warnings.warn("Mean of empty slice"

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'm sure this is trivial, but I've been banging my head against the desk for the last few hours. I'm trying to convert a string (i.e. "key1,key2:) to an array (i.e. ["key1","key2"]) before storing it in the database. I'm using a before_validation callback in my model and it doesn't seem to be firing. My model looks like this: class Product I'm getting a SerializationTypeMismatch error. Obviously, either the update_keywords method isn't being run or isn't properly returning the updated attributes. Any ideas? EDIT I'm using Rails 3.0.3, if

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 making a process pool and each of them need to write in different parts of a matrix that exists in the main program. There exists no fear of overwriting information as each process will work with different rows of the matrix. How can i make the matrix writable from within the processes?? The program is a matrix multiplier a professor assigned me and has to be multiprocessed. It will create a process for every core the computer has. The main program will send different parts of the matrix to the processes and they will compute them, then

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 want to convert an image into a NumPy array to a PySide QPixmap, so I can display it (EDIT: in my PySide UI). I already found this tool: qimage2ndarray , but it only works for PyQt4. I tried to change it to get it working with PySide, but I would have to change the C part of the tool and I have no experience with C. How can I do this or are there any alternatives? 回答1: One alternative is to just use PIL library. >>> import numpy as np >>> import Image >>> im = Image.fromarray(np.random.randint(0,256,size=(100,100,3)).astype(np.uint8)) >>>

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 NumPy array of values. I want to count how many of these values are in a specific range say x25. I have read about the counter, but it seems to only be valid for specif values not ranges of values. I have searched, but have not found anything regarding my specific problem. If someone could point me towards the proper documentation I would appreciate it. Thank you I have tried this X = array(X) for X in range(25, 100): print(X) But it just gives me the numbers in between 25 and 99. EDIT The data I am using was created by another

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'm currently working on recursion and i keep getting stuck at this question: Find the cheapest path through an array using recursion. for example, if i had an array [0,1,3,4,1] i start at the value 0. Now i have 2 options i could jump to index 2 or just move to index 1.In this case i would jump right to index 2 (value 3) then jump to index 4 (value 1) because 3+1= 4 and that would be the cheapest way through the array. I've tried to compare the move index value with the jump index value and see which is smallest but in this case that would

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: This question already has an answer here: Accessing an array out of bounds gives no error, why? 17 answers I alloced an int array of 3 elements, and thought of this code below: int a[3]; for(int i = -2; i < 3; ++i){ a[i] = i; cout<<a[i]<<" "; } Here's its output: -2 -1 0 1 2 It seems like array a has 5 alloced space, and a is at the middle of those space. Any ideas? 回答1: To explain how negative indexes work, you first have to learn (or remember) that for any array or pointer a and index i , the expression a[i] is equal to *(a + i) . That