I'm looking to auto-generate a Bill Of Materials (BOM) in draw.io by using object ID's. This is because my plans contain many of the same or similar components making it difficult to visually count. So, ultimately I'd like to auto-generate a parts list. Firstly is this possible in draw.io? Secondly what would be the best method of execution?
Currently I'm converting my diagram to PDF and then using the find function to count the number of instances of the part number.
A point in the right direction would be most welcome.
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I am currently building a little search engine as part of a university project.
The search engine has to be able to perform searches on quite a lot of documents. 500k-1M I would say. The documents are pure .txt files and are not big (max 1MB).
I am writing the search engine in C++, but I am not quite sure how to store and access the documents efficiently (in memory).
I am using an inverted index, which stores for every term a list of document ids (pure integers) in which that term occurs.
I thought about creating a document class which takes into the constructor the filename of the document and creates a document object.
For example
Document d("25.txt");
The document class would also hold other information about the document, which I would present to the user, if the user decides to take a look at the document.
However, if I search for a term, that occurs in quite a lot of documents, for example "apple", then I would probably have to create hundreds or thousands of document objects. And when the queries get longer, that would blow up the heap (I guess?).
And I really need all of the potentially relevant documents in order to create a ranking.
What would be the right way to go here? Maybe somehow with serialization? Or using a DB? Or something else?
Please note, I can not use something like solr or Lucene, as this task is part of a university course.
i was messing around organizing my music files when i asked myself why windows nor linux offer a way to organize a folder by custom tags in a database-likle manner rather than hierarchically.
The problem i wanted to solve is the following:
I have music files
A titled "tempest" from Beethoven, classical music in a piano only version.
B titled "whatever" from Mozart, classical music orchestral
D titled "one winged angel" from Uematsu, classical style, game ost, orchestral
C titled "one winged angel" same as before, violin only, cover from Taylor Davis.
And whatever "main" information i use for grouping, makes listing files by any other category immpossible.
Hence i whished to save files in an hidden folder with a simple increasing number.format, and have a program in which i can add files, add categories, search by tags, and end up with a list of the files i want. E.g. today i want to listen to all piano only pieces independently of their composer-time period.
I started making a structure of vectors containing vectors (aka matrix) but indexing lines and column by string started getting complicated when i want to remove a column.
And searching files by tag would require me to have each tag as an object knowing all files that use it, and it starts becomming more similar to a 3d matrix.
I though it would be better to think of this as a database, started with sqllite but ended with the problem of being unable to remove columns (i know i can create a copy etcc, but i wanted to avoid messy workarounds).
Also an sql-like database wouldn't allow me to have an area dedicated to a list of random tags for each file without a definite category.
Is there any existing library that rather then working as an sql database offers me something similar to a search/insert optimized matrix for strings? I don't think i was the first one thinking about that, someone must have done something similar.
This is very similar to what i want to achieve (strictly speaking about functionality), but rather than having only a bunch of random tags, i'd like to have some categories AND a set of random tags.
The problem with random tags only is you can't use the same word when it refers to different things. For example if the title of a piece is A and there's a film named A with a piece titled B, filtering A in the mess of tags would give both, while with categories i could filter pieces titled A. But the random mess of additional tags without category is useful too, for information you don't want to fill in most of the files and that would take pointless space in a standard database.
I am new to quantlib, but I have relatively good understanding of C++. To put my question in some sort of context, I can inform you that I am actually trying to implement the portfolio CVA calculation method proposed by Giovanni Cesari (see link below) for a simple portfolio consisting of one interest rate swap (as a starting point).
I working with the Cheyette (quasi-Gaussian) interest rate model. The model has been implemented as a "new" stochastic process class and the simulated paths stored/generated as a multipath class.
However, as Cesari's method is based on LS-Monte Carlo, I need to write a code that can generate the resulting cash flow sequence from an interest rate swap under each scenario. I do not know if there is some efficient way to do this in quantlib, but I have a feeling that there is. I guess one should be able let the scenarios generated, populate Quantlib quotes which are linked to an instance of the quantlib term structures class. Hopefully I can use this together with the swap class in order to obtain the realized cash flows (basically the floating leg, as the fixed leg is deterministic) from the swap.
Any idea of how this can be done will be highly appreciated!
Link to Cesari's presentation (see page 21 to 26): http://sfi.epfl.ch/files/content/sites/sfi/files/shared/Swissquote%20Conference%202010/Cesari_talk.pdf
I want to create levels in my cocos2d game and I do not know how to do that with .plist files ... I searched the Internet but unfortunately I couldn't find significant information on how to implement these property lists. Can you please help out ?
Check out Tiled Map Editor. Tiled's TMX format is supported by Cocos2D.
As with any Apple technologies, the first place you should start searching for is the developer.apple.com website. In this case, here's the Property List (plist) Programming Guide.
However, I find property lists very awkward to work with, specifically if you want to create them manually and whenever they contain more than just a few entries. It certainly can't hurt to evaluate rolling out your own file format, text-based plain and simple. I would always rather work with simple text files like these rather than messing with property lists:
X=10;Y=10;Tile=30;
X=12;Y=11;Tile=28;
X=16;Y=19;Tile=22;
It's a different story if you actually design the data with a tool or within an app, where you'll be able to make use of the various collection convenience methods that save and load property lists, for example to and from a dictionary or array.
I'm working on a C++/Qt image retrieval system based on similarity that works as follows (I'll try to avoid irrelevant or off-topic details):
I take a collection of images and build an index from them using OpenCV functions. After that, for each image, I get a list of integer values representing important "classes" that each image belongs to. The more integers two images have in common, the more similar they are believed to be.
So, when I want to query the system, I just have to compute the list of integers representing the query image, perform a full-text search (or similar) and retrieve the X most similar images.
My question is, what's the best approach to permorm such a search?
I've heard about Lucene, Lemur and other indexing methods, but I don't know if this kind of full-text searchs are the best way, given the domain is reduced (only integers instead of words).
I'd like to know about the alternatives in terms of efficiency, accuracy or C++ friendliness.
Thanks!
It sounds to me like you have a vectorspace model, so Lucene or a similar product may work well for you. In general, an inverted-index model will be good if:
You don't know the number of classes in advance
There are a lot of classes relative to the number of images
If your problem doesn't fit these criteria, a normal relational DB might work better, as Thomas suggested. If it meets #1 but not #2, you could investigate one of the "column oriented" non-relational databases. I'm not familiar enough with these to tell you how well they would work, but my intuition is that you'll need to replicate a lot of the functionality in an IR toolkit yourself.
Lucene is written in Java and I don't know of any C++ ports. Solr exposes Lucene as a web service, so it's easy enough to access it that way from whatever language you choose.
I don't know much about Lemur, but it looks like it has a similar vectorspace model, and it's written in C++, so that might be easier for you to use.
You can take a look at Lucene for image retrieval (LIRE) here: http://www.semanticmetadata.net/2006/05/19/lire-lucene-image-retrieval-04-released/
If I'm mistaken, you are trying to implement a typical bag of words image retrieval am I correct? If so you are probably trying to build an inverted file index. Lucene on its own is not suitable as you probably have already realized as it index text instead of numbers. Using its classes for querying the index would also be a problem as it is not designed to "parse" (i.e. detect keypoints, extract descriptors then vector-quantize them) image into the query vector.
LIRE on the other hand have been modified to index feature vectors. However, it does not appear to work out of the box for bag of words model. Also, I think I've read on the author's website that it currently uses brute force matching rather than the inverted file index to retrieve the images but I would expect it to be easier to extend than Lucene itself for your purposes.
Hope this helps.