My app is a simple blog app. I parse an XML, and build custom HTML code from the parsed parts, and load that HTML into a webview. Not everyone has the same quality of vision, so I am trying to add simple buttonsto add or decrease the font size. Currently, the HTML may look like:
font size=5 The Title.../font font size = 3 The body of text.../font
What I would like to do is take whatever number is listed, and increase or decrease by 1.
Any suggestions on how I can take just those 2 numbers (don't want to increase other numbers that may be in body of article) and increase or decrease incrementally?
I'd recommend stuffing the HTML you parsed out of the XML into a "NSMutableString" object and then hunt through the mutable string object looking for the ranges of all substrings that match the pattern "font size=".
Once you find those ranges, you should be able to get the font sizes and then put them into a "NSInteger" via something like [NSString integerValue] which you can then increment and put back into the mutable string object. Obviously there's some extra detail I'm not thinking too hard about, like how to replace a "9" in the mutable string with a "10" or to tell the difference between a font size of "10" and one that's "100". But at least this should be a good start for you.
Related
I'm trying to extract text information from a (digital) PDF by identifying content and location of each character and each word. For words, pdftotext --bbox from xpdf / poppler works quite well, but I cannot find an easy way to extract character location.
What I've tried
The solution I currently have is to convert the pdf to svg (via pdf2svg), and then parse the resulting svg to extract single character (= glyph) locations. In a third step, the resulting boxes are compared, each character is assigned to a word and hopefully the numbers match.
Problems
While the above works for most "basic" fonts, there are two (main) situations where this approach fails:
In script fonts (or some extreme italic fonts), bounding boxes are way larger than their content; as a result, words overlap significantly, and it can well happen that a character is entirely contained in two words. In this case, the mapping fails, because once I translate to svg I have no information on what character is contained in which glyph.
In many fonts multiple characters can be ligated, giving rise to a single glyph. In this case, the count of character boxes does not match the number of characters in the word, and matching each letter to a box is again problematic.
The second point (which is the main one for me) has a partial workaround by identifying the common ligatures and (if the counts don't match) splitting the corresponding bounding boxes into multiple pieces; but that cannot always work, because for example "ffi" is sometimes ligated to a single glyph, sometimes in two glyphs "ff" + "i", and sometimes in two glyphs "f" + "fi", depending on the font.
What I would hope
It is my understanding that pdf actually contain glyph information, and not words. If so, all the programs that extract text from pdf (like pdftotext) must first extract and locate the various characters, and then maybe group them into words/lines; so I am a bit surprised that I could not find options to output location for each single character. Converting to svg essentially gives me that, but in that conversion all information about the content (i.e. the mapping glyph-to-character, or glyph-to-characters, if there was a ligature) is lost, because there is no font anymore. And redoing the effort of matching each glyph to a character by looking at the font again feels like rewriting a pdf parser...
I would therefore be very grateful for any idea of how to solve this. The top answer here suggests that this might be doable with TET, but it's a paying option, and replacing my whole infrastructure to handle just one limit case seems a big overkill...
A PDF file doesn't necessarily specify the position of each character explicitly. Typically, it breaks a text into runs of characters (all using the same font, anything up to a line, I think) and then for each run, specifies the position of the bounding box that should contain the glyphs for those characters. So the exact position of each glyph will depend on metrics (mostly glyph-widths) of the font used to render it.
The Python package pdfminer has a script pdf2txt.py. Try invoking it with -t xml. The docs just say XML format. Provides the most information. But my notes indicate that it will apply the font-metrics and give you a <text> element for every single glyph, with font and bounding-box info.
There are various versions in various places (e.g. PyPI and github). If you need Python 3 support, look for pdfminer.six.
I know that PO / MO files are meant to be used for small strings like button names, labels, etc. Not long text like an About page, etc.
But lately I am encountering a lot of situations that are in the middle. For example, a two sentence call to action. Or a short paragraph.
Is there best practice or "rule of thumb" for when a string is too long to put in a PO file?
update
For "long" text I use partials and include the correct language version. My question is WHEN is it optimal to use one vs the other. I've heard that PO files are "inefficient" for "long" pieces of text. But what does that mean and when is it too "long"? Or is this not a concern?
Use one entry for a self-contained chunk of text; e.g. a sentence as you say.
Two sentences that belong together and don't make sense without each other should be one entry. Why? Because otherwise the translator wouldn't have the context necessary to translate it well. Same goes for a short paragraph, e.g. explaining a setting: if it's inseparable in the code, it should be one entry.
If you encounter a situation where you have lots of long texts regularly (e.g. entire pages or paragraphs of pages), that's usually a sign that you are using an ill-fitting tool. Some people do it, using Gettext for entire articles, but you're better off having separate documents in such cases. But that doesn't seem to be the case here.
We are using Jfreechart along with iText for generating pdf reports. For Japanese, we realized that in the rendered content for the graph legend, characters don't have any spaces between them. They basically overlap which makes it hard to read.
Do we need to use any special encoding?
Attached are images for expected and actual(generated by jfreechart), in that order
Below is a snippet of the graph generated with the legend
According to the PDF specification, a CIDFont dictionary contains an optional dictionary called DW and an optional array called W. DW is the default width for glyphs. If not set, it defaults to 1000.
The W array describes individual widths for characters in the font (if not specified they default to the value of DW). For many Japanese fonts, I've seen the value set to lower than 1000, but in this case it might be too low.
You can take a look at these values using Acrobat's "preflight>browse internal structure" tool. If these seem off, you make be using the wrong encoding. Setting encoding to "UniJIS-UCS2-H" should help resolve this issue.
I'd like to add an automatic page break to a libHaru PDF in iOS.
I do have several text fields in the app which contain the user filled data. when i generate the pdf i first measure the expected size of the text-rect going to be created. if it exceeds the remaining space i trigger a hpdf_new_page event and put the text on an new page. i'd like to have this just in part automatically. so if the text exceeds the space on the current page it should split and continue on a new page without me checking or doing anything.
unfortunately i can't find anything like this in the documentation.
Line counting using fgets() may help. When your print program opens a file to print, each line can be copied to the pdf file and checked for a form feed character
or
if the line count has reached a limit.
Another possible solution is to use a character count limit with "while(getc(file) != EOF)".
This link uses libharu to print basic text files with PCL commands to change the font.
https://github.com/DaDaDadeo/GetCycle/blob/master/pcl_to_pdf.c
The form feed character '\f' (ascii 12) and 61 lines will trigger a new page. There are other conditions in the program to restrict a new page but the general idea is illustrated.
The results are the same as a printer using telnet raw 9100 protocol. The pcl commands are limited to just a couple of font changes so it is not too complicated.
Libharu is rather low-level library, and I could not even expect of appearing such automatic page splitting in newer versions due to number of reasons. Hereafter I state two of them:
There is no good, preferred strategy how to place remaining of non-fitting text on the next page. In some cases it could be even impossible at all.
There is no good, preferred strategy for text splitting.
Why?
Consider your font is extremely large, and just one letter (for instance, wide one as "W") does not fit into the page. Where we are supposed to place it? On the next page? Ok, we add new page... oops, it does not fit this page too - as soon as all our pages have the same size. Dead-end without any good, straightforward way out.
In other words, there should be a user-defined strategy for these cases. Almosy every naive implementation will have such a corner cases.
libharu does not know where it should split your text automatically. It does not know hyphenation rules of your language, it does not know whether it should respect spaces or not (wrap whole words only or not), and so on. It's up to you to specify these rules.
So, you should call HPDF_Font_MeasureText for some part of your text string, decide if it fits into your page (excluding margins, footers - which also out of libharu's internal knowledge) and render it. And note that there is no simple formula for text size depending on its length. String "wwww" is more than twice wider than "iiii", of course if your font is not mono-spaced.
I'm thinking this may be impossible to do resonably, but I figured I would take a shot at it. So lets say I have two NSStrings. One is #"Singin' In The Rain" and the other is #"Singing In The Rain". These strings are very similar, but have a small difference. I'm trying to find a way where I could write something like the following:
NSString *stringOne = #"Singin' In The Rain";
NSString *stringTwo = #"Singing In The Rain";
float dif = [stringOne differenceFrom:stringTwo];
//dif = .9634 or something like that
One project that I did find similar to this was taken from the previous similar question on Stack Overflow: Check if two NSStrings are similar. However, this simply returns a BOOL which isn't as accurate as I need it to be. I also tried looking into the compare: documentation for NSString but it all looked too basic. Another similar thing I found is at https://gist.github.com/iloveitaly/1515464. However, this gives varying results, even saying two of the same string are different occasionally. Any advice would be much appreciated.
The question is a little vague, but I would assume that the most satisfactory results will come from using NSLinguisticTagger. If you parse each for tags with the NSLinguisticTagSchemeLexicalClass scheme then your string will be broken down into verbs, nouns, adjectives, etc. In your example, even if you weren't spotting that singin' and singing are the same, you'd spot the other three words are the same and that the thing at the end is a noun, so they're both about doing something in the same thing.
It'd probably be wise to use something like a BK-Tree to compare individual words where you suspect there may be a match (a noun obviously doesn't match an adverb but two nouns may match even if spellings differ).
Another off the wall suggestion:
The source, and hence the algorithm, for diff and similar programs is easily available. These compare input on a line-by-line basis and detect insertions, deletions and changes.
When comparing text strings for "closeness" then the insertion, deletion or changing of words seems as good a measure as any.
So:
Break each string into "words" (white space separated should be sufficient).
Compare the two lists using the diff algorithm, treating each "word" as a "line", use a re-sync length of 1 (the number of "lines" that need to be the same to treat the two inputs as back in sync)
Calculate the "closeness" as the number of insertions/deletions/changes compared to the total word count.
For the two example strings this would give 1:4 changes or 75% similar.
If you want greater granularity for each change split the two words into characters and repeat the algorithm giving you a fraction the word is similar by (as opposed to the whole word).
For the two example strings this would give 3 6/7 words out of 4, or 96% similar.
I'd recommend dynamic time warping for such comparisons:
http://en.wikipedia.org/wiki/Dynamic_time_warping
This will however return distance between two strings (so you'll get 0 for identical), but this the best starting point I can think of.