boundary

How to restrict app usability to a certain geographical area ANDROID

半腔热情 提交于 2019-12-10 14:48:25
问题 I want to define a geographical boundary outside of which, the app will refuse to work. I already know how to do this with a square bound by two lat/long pairs: if ((dLAT.doubleValue() > 35.309171) || (dLAT.doubleValue() < 35.226442) || (dLON.doubleValue() < -92.790165) || (dLON.doubleValue() > -92.707081)) { LocalBroadcastManager localBroadcastManager = LocalBroadcastManager.getInstance(this); localBroadcastManager.sendBroadcast(new Intent("killapp")); } I also know about geofencing... or

How to set my own boundary on multipart/form-data using XMLHttpRequest and FormData object

隐身守侯 提交于 2019-12-08 19:39:32
问题 I have been trying to find out a way to set my own boundary on an XMLHttpRequest object when using the FormData object to append files to a request. I've seen multiple posts on this and everyone says "just don't set the boundary and it will automatically generate for you." This is NOT what I want. Let me explain what I need so I don't get these kinds of responses. I have a web service endpoint to which I send a multipart/form-data request with two images and some json data. Since WCF doesn't

relabeling pixels based on distance between object's centerline and boundary

怎甘沉沦 提交于 2019-12-08 02:53:56
问题 I've a binary image containing an object as illustrated in the figure below. The centerline of the object is depicted in red . For each pixel belonging to the object, I would like to relabel it with a color. For instance, pixels whose orthogonal distance to the centerline are half of the distance to the object boundary from the centerline, should be labeled blue , otherwise green . An illustration is given below. Any ideas? Also, how could I fit a 1D gaussian centered in the object centerline

Python: regex match across file chunk boundaries

孤街醉人 提交于 2019-12-07 03:14:57
问题 Huge plain-text data file I read a huge file in chunks using python. Then I apply a regex on that chunk. Based on an identifier tag, I want to extract the corresponding value. Due to the chunk size, data is missing at the chunk boundaries. Requirements: The file must be read in chunks. The chunk sizes must be smaller than or equal to 1 GiB. Python code example identifier_pattern = re.compile(r'Identifier: (.*?)\n') with open('huge_file', 'r') as f: data_chunk = f.read(1024*1024*1024) m = re

relabeling pixels based on distance between object's centerline and boundary

旧街凉风 提交于 2019-12-06 11:51:23
I've a binary image containing an object as illustrated in the figure below. The centerline of the object is depicted in red . For each pixel belonging to the object, I would like to relabel it with a color. For instance, pixels whose orthogonal distance to the centerline are half of the distance to the object boundary from the centerline, should be labeled blue , otherwise green . An illustration is given below. Any ideas? Also, how could I fit a 1D gaussian centered in the object centerline and orthogonal to it? The image in full resolution can be found under: http://imgur.com/AUK9Hs9 Here

Placing a boundary around a series of points in ggplot2

烈酒焚心 提交于 2019-12-06 05:23:41
问题 I have a series of points that I want to place a boundary around. How can I go about this? These are my points: I tried geom_line but that was obviously wrong since it produced this! Thanks 回答1: Use geom_path instead of geom_line . Here is an example: i <- seq(0, 2*pi, length.out=50) dat <- data.frame(x=cos(i), y=sin(i)) library(ggplot2) ggplot(dat, aes(x, y)) + geom_line() ggplot(dat, aes(x, y)) + geom_path() 来源: https://stackoverflow.com/questions/12603006/placing-a-boundary-around-a-series

Python: regex match across file chunk boundaries

两盒软妹~` 提交于 2019-12-05 08:09:12
Huge plain-text data file I read a huge file in chunks using python. Then I apply a regex on that chunk. Based on an identifier tag, I want to extract the corresponding value. Due to the chunk size, data is missing at the chunk boundaries. Requirements: The file must be read in chunks. The chunk sizes must be smaller than or equal to 1 GiB. Python code example identifier_pattern = re.compile(r'Identifier: (.*?)\n') with open('huge_file', 'r') as f: data_chunk = f.read(1024*1024*1024) m = re.findall(identifier_pattern, data_chunk) Chunk data examples Good: number of tags equivalent to number of

Size and position of one image in another via PHP

蓝咒 提交于 2019-12-05 05:36:31
问题 I have two images(small and big). Big one contains a small one. Like if the small one is a photo and a big one is a page from the photo album. How do I get coordinates of that small image in the big one using PHP? And also I need to know the size of that image in big one...so just a(x,y) coordinate of any angle and sizes of sides of that presentation of the small image... (x,y, width, height) I've already asked the question like that and got a brilliant answer (here) but I've forgot to

Size and position of one image in another via PHP

女生的网名这么多〃 提交于 2019-12-03 21:16:24
I have two images(small and big). Big one contains a small one. Like if the small one is a photo and a big one is a page from the photo album. How do I get coordinates of that small image in the big one using PHP? And also I need to know the size of that image in big one...so just a(x,y) coordinate of any angle and sizes of sides of that presentation of the small image... (x,y, width, height) I've already asked the question like that and got a brilliant answer ( here ) but I've forgot to mention over there that the size of a small image could be different from the the size of that image in the

Python curve_fit choice of bounds and initial condition affect the result

拥有回忆 提交于 2019-12-03 20:33:35
问题 I have a data set that is described by two free parameters which I want to determine using optimalization.curve_fit . The model is defined as follows def func(x, a, b,): return a*x*np.sqrt(1-b*x) And the fitting part as popt, pcov = opt.curve_fit(f = func, xdata = x_data, ydata= y_data, p0 = init_guess, bounds = ([a_min, b_min], [a_max, b_max])) The outcome of the solutions for a and b depends quite strong on my choice of init_guess , i.e. the initial guess and also on the choice of the