indexing

问题 I would like to set bits of a std_logic_vector separately in order to easily set comments for individual bits or group of bits. Here is what I have: signal DataOut : std_logic_vector(7 downto 0); ... DataOut <= ( 5=>'1', -- Instruction defined 4=>'1', -- Data length control bit, high=8bit bus mode selected 3=>'1', -- Display Line Number ctrl bit, high & N3 option pin to VDD=3 lines display 2=>'0', -- Double height font type control byte, not selected 1 downto 0=>"01", -- Select Instruction

问题 A common problem of mine is the following: As input I have ( n is some int >1 ) W = numpy.array(...) L = list(...) where len(W) == n >> true shape(L)[0] == n >> true And I want to sort the list L regarding the values of W and a comparator. My idea was to do the following: def my_zip_sort(W,L): srt = argsort(W) return zip(L[srt],W[srt]) This should work like this: a = ['a', 'b', 'c', 'd'] b = zeros(4) b[0]=3;b[1]=2;b[2]=[1];b[3]=4 my_zip_sort(a,b) >> [(c,1)(b,2)(a,3)(d,4)] But this does not,

问题 I have 2 tables: products and categories . Each category has many products, and a product can belong to many categories. products product_id - int primary auto increment name - unique etc. categories category_id - int primary auto increment name - unique etc. I have a 3rd table for manyTomany relations. products_categories product_id -> foreign key: products.product_id category_id -> foreign key: category.category_id My question is: should I create indexes for product_id and category_id in

问题 I have a large image A and a smaller image B , both expressed as 2-D numpy arrays. I want to use A as the canvas, and write translated copies of B all over it, packed in a hexagonal arrangement. The part I can't get my head around is how to handle it such that the image wraps both vertically and horizontally—essentially what I want is regular tessellation of a (padded, as necessary) sub-image onto a torus. I've seen the discussion of numpy.take and numpy.roll at wrapping around slices in

问题 in the process of using Lucene, I am a bit disapointed. I do not see or understand how i should proceed to feed any Lucene analyzers with something that is already and directly indexable. Or how i should proceed to create my own analyzer... for example, if i have a List<MyCustomToken> , which already contains many tokens (and actually many more informations about capitalization, etc. that i would also like to index as features on each of MyCustomToken) if i understand well what i have read, i

问题 Wondering which would be the more efficient technique for indexing my document's various timestamps that I need to keep track of, keeping in mind my application is fairly heavy on writing, but heavy enough on reading that without the indexes, the queries are too slow. Is it better to have a field for each timestamp, and index each field, or store the timestamps and their associated type in an array field, and index each field of that array? First option, separate fields, and an index for each

问题 Simple question: does SQLite support FULL-TEXT searches? If not, is there any way I can implement that feature? 回答1: Yes, it does. 来源： https://stackoverflow.com/questions/2000398/full-text-search-in-sqlite

问题 I'm considering CQEngine for a project where I need to handle lots of real time events and execute some queries from time to time. It works well for returning the results but I noticed that the larger the collection gets the slower it becomes to add or remove elements to/from it. I have a few simple indexes added on the collection so I'm assuming the delay is because on each event added/removed the indexes are updated. I also get an OutOfMemoryError on large numbers of events, from the

问题 I have a MySQL indexing question for you guys. I've got a very large table (~100Million Records) in MySQL that contains information about files. Most of the Queries I do on it involve substring operations on the file path column. Here's the table ddl: CREATE TABLE `filesystem_data`.`$tablename` ( `file_id` INT( 14 ) NOT NULL AUTO_INCREMENT PRIMARY KEY , `file_name` VARCHAR( 256 ) NOT NULL , `file_share_name` VARCHAR ( 100 ) NOT NULL, `file_path` VARCHAR( 900 ) NOT NULL , `file_size` BIGINT(

问题 I have a dataframe with one column that contains several hundreds of dates in Date format e.g.: as.Date(c("2011-08-13","2011-09-13","2010-06-12","2012-09-13","2010-09-13","2012-05-26","2012-07-20")) Now I'd like to select only the rows where 15.03 < date < 15.8 (all Dates between 15th march and 15th october, disregarding the year). Is there a simple way to select (index) in such a way? I slightly modified the answer I accepted, as below: a <- as.Date(c("2011-08-13","2011-09-13","2010-06-12",