How to get the sill height (height above the floor) of a Ifcwindow in ifc file
There is no solution to get the height above the floor directly. This is because the height above for depends on several factors, like how the wall is created in which the window resides, etc.
It could be that the sillHeight is exported by the original modelling software to a custom IFC property. You could check for that, but since there is no common standard for it, it's risky.
Your best bet is to look into the ObjectPlacement property which IfcWindow inherits from IfcProduct. The ObjectPlacement defines how a product is placed either in world space or relative to its host. See https://standards.buildingsmart.org/IFC/RELEASE/IFC4/ADD2/HTML/schema/templates/product-local-placement.htm for details.
You need to read the ObjectPlacement property, and check if there is a RelativeTo property, if so, you need to fill into that property as well, and check if it's the placement of a floor. If so, you can stop the looping, and perform a matrix calculation on all the placements you harvested to calculate the placement of window relative to floor.
(Maybe even more simple: calculate world placement of window and floor separately, than subtract the two vector z values to get the height of window from floor)
Related
There was a gif on the internet where someone used some sort of CAD and drew multiple vector pictures in it. On the first frame they zoom-in on a tiny dot, revealing there a whole new different vector picture just on a different scale, and then they proceed to zoom-in further on another tiny dot, revealing another detailed picture, repeating several times. here is the link to the gif
Or another similar example: imagine you have a time-series with a granularity of a millisecond per sample and you zoom out to reveal years-worth of data.
My questions are: how such a fine-detailed data, in the end, gets rendered, when a huge amount of data ends up getting aliased into a single pixel.
Do you have to go through the whole dataset to render that pixel (i.e. in case of time-series: go through million records to just average them out into 1 line or in case of CAD render whole vector picture and blur it into tiny dot), or there are certain level-of-detail optimizations that can be applied so that you don't have to do this?
If so, how do they work and where one can learn about it?
This is a very well known problem in games development. In the following I am assuming you are using a scene graph, a node-based tree of objects.
Typical solutions involve a mix of these techniques:
Level Of Detail (LOD): multiple resolutions of the same model, which are shown or hidden so that only one is "visible" at any time. When to hide and show is usually determined by the distance between camera and object, but you could also include the scale of the object as a factor. Modern 3d/CAD software will sometimes offer you automatic "simplification" of models, which can be used as the low res LOD models.
At the lowest level, you could even just use the object's bounding
box. Checking whether a bounding box is in view is only around 1-7 point checks depending on how you check. And you can utilise object parenting for transitive bounding boxes.
Clipping: if a polygon is not rendered in the view port at all, no need to render it. In the GIF you posted, when the camera zooms in on a new scene, what is left from the larger model is a single polygon in the background.
Re-scaling of world coordinates: as you zoom in, the coordinates for vertices become sub-zero floating point numbers. Given you want all coordinates as precise as possible and given modern CPUs can only handle floats with 64 bits precision (and often use only 32 for better performance), it's a good idea to reset the scaling of the visible objects. What I mean by that is that as your camera zooms in to say 1/1000 of the previous view, you can scale up the bigger objects by a factor of 1000, and at the same time adjust the camera position and focal length. Any newly attached small model would use its original scale, thus preserving its precision.
This transition would be invisible to the viewer, but allows you to stay within well-defined 3d coordinates while being able to zoom in infinitely.
On a higher level: As you zoom into something and the camera gets closer to an object, it appears as if the world grows bigger relative to the view. While normally the camera space is moving and the world gets multiplied by the camera's matrix, the same effect can be achieved by changing the world coordinates instead of the camera.
First, you can use caching. With tiles, like it's done in cartography. You'll still need to go over all the points, but after that you'll be able zoom-in/zoom-out quite rapidly.
But if you don't have extra memory for cache (not so much actually, much less than the data itself), or don't have time to go over all the points you can use probabilistic approach.
It can be as simple as peeking only every other point (or every 10th point or whatever suits you). It yields decent results for some data. Again in cartography it works quite well for shorelines, but not so well for houses or administrative boarders - anything with a lot of straight lines.
Or you can take a more hardcore probabilistic approach: randomly peek some points, and if, for example, there're 100 data points that hit pixel one and only 50 hit pixel two, then you can more or less safely assume that if you'll continue to peek points still pixel one will be twice as likely to be hit that pixel two. So you can just give up and draw pixel one with a twice more heavy color.
Also consider how much data you can and want to put in a pixel. If you'll draw a pixel in black and white, then there're only 256 variants of color. And you don't need to be more precise. Or if you're going to draw a pixel in full color then you still need to ask yourself: will anyone notice the difference between something like rgb(123,12,54) and rgb(123,11,54)?
I am not sure how to put this problem in a single sentence, sorry if the title is misleading.
I am currently developing a simple terrain editor with a circle-shaped brush size. The image below shows a few cases that represent my problem.
additional info: the square size is fixed and uniform and in the current version, my concern is only to find which one is hit and which one is not (the amount of region covered is important for weighting the hit, but probably not right now)
My current solution (which is not even correct for a certain condition) is: given a hit in a position (x, y) with radius r, loop through all square from (x-radius, y-radius) to (x+radius, y+radius) and apply 2-D box to circle collision detection. But I don't think this is optimal (or even correct IMO).
Can anyone help me with this one? Thank you
Since i can't add a simple comment due to bureaucracy on this website i have to type it out here.
Anyway you're in luck since i was trying to do this recently as well! The way i did it is i iterated through the vertex array and check if the current vertex falls inside the radius of the circle. But perhaps what you want is to check it against each quad center and if that center falls inside the radius then add the whole quad as it's being collided.
Of course depending on the size of your grid the performance will vary so it's good to try to iterate through as few quads as needed. Though accessing these quads from the array is something you have to figure out yourself.
I am new to the field of medical imaging - and trying to solve this (potentially basic problem). For a machine learning purpose, I am trying to standardize and normalize a library of DICOM images, to ensure that all images have the same rotation and are at the same scale (e.g. in mm). I have been playing around with the Mango viewer, and understand that one can create transformation matrices that might be helpful in this regard. I have however the following basic questions:
I would have thought that a scaling of the image would have changed the pixel spacing in the image header. Does this tag not provide the distance between pixels, and should this not change as a result of scaling?
What is the easiest way to standardize a library of images (ideally in python)? Is it possible and should one extract a mean pixel spacing across all images, and then scaling all images to match that mean? or is there a smarter way to ensure consistency in scaling and rotation?
Many thanks in advance, W
Does this tag not provide the distance between pixels, and should this
not change as a result of scaling?
Think of the image voxels as fixed units of space, which are sampling your image. When you apply your transform, you are translating/rotating/scaling your image around within these fixed units of space. That is, the size and shape of the voxels doesn't change. They just sample different parts of your image.
You can resample your image by making your voxels bigger or smaller or changing their shape (pixel spacing), but this can be independent of the transform you are applying to the image.
What is the easiest way to standardize a library of images (ideally in
python)?
One option is FSL-FLIRT, although it only accepts data in NIFTI format, so you'd have to convert your DICOMs to NIFTI. There is also this Python interface to FSL.
Is it possible and should one extract a mean pixel spacing across all
images, and then scaling all images to match that mean? or is there a
smarter way to ensure consistency in scaling and rotation?
I think you'd just to have pick a reference image to register all your other images too. There's no right answer: picking the highest resolution image/voxel dimensions or an average or some resampling into some other set of dimensions all sound reasonable.
A simple question as i am developing a java application based on dcm4che ...
I want to calculate/find the "position" of a dicom image into its sequence (series). By position i mean to find if this image is first, second etc. in its series. More specifically i would like to calculate/find:
Number of slices into a Sequence
Position of each slice (dicom image) into the Sequence
For the first question i know i can use tag 0020,1002 (however it is not always populated) ... For the second one?
If you are dealing with volumetric image series, best way to order your series is to use the Image Position (Patient) (0020, 0032). This is a required Type 1 tag (should always have value) and it is part of the image plane module. It will contain the X, Y and Z values coordinates representing the upper left corner of the image in mm. If the slices are parallel to each other, only one value should change between the slices.
Please note that the Slice Location (0020, 1041) is an optional (Type 3) element and it may not exist in the DICOM file.
We use the InstanceNumber tag (0x0020, 0x0013) as our first choice for the slice position. If there is no InstanceNumber, or if they are all the same, then we use the SliceLocation tag (0x0020, 0x1041). If neither tag is available, then we give up.
We check the InstanceNumber tag such that the Max(InstanceNumber) - Min(InstanceNumber) + 1 is equal to the number of slices we have in the sequence (just in case some manufacturers start counting at 0 or 1, or even some other number). We check the SliceLocation the same way.
This max - min + 1 is then the number of slices in the sequence (substitute for tag ImagesInAcquisition 0x0020, 0x1002).
Without the ImagesInAcquisition tag, we have no way of knowing in advance how many slices to expect...
I would argue that if the slice location is available, use that. It will be more consistent with the image acquisition. If it is not available, then you'll have to use or compute from the image position (patient) attribute. Part 3 section C.7.6.2.1 has details on these attributes.
The main issue comes when you have a series that is oblique. If you just use the z-value of the image position (patient), it may not change by the slice thickenss/spacing between slices attributes, while the slice location typically will. That can cause confusion to end users.
I've got an array of different sized images. I want to place these images on a canvas in a sort of automated collage.
Does anyone have an idea of how to work the logic behind this concept?
All my images have heights divisible by 36 pixels and widths divisible by 9 pixels. They have mouseDown functions that allow you to drag and drop. When dropped the image goes to the closest x point divisible by 9 and y point divisble by 36. There is a grid drawn on top of the canvas.
I've sorted the array of images based on height, then based on their widths.
imagesArray.sortOn("height", Array.NUMERIC | Array.DESCENDING);
imagesArray.sortOn("width", Array.NUMERIC | Array.DESCENDING);
I'd like to take the largest image ( imageArray[0] ) to put in corner x,y = 0,0. Then randomize the rest of the images and fit them into the collage canvas.
What you are trying to do sounds like treemapping.
I think this is what's known as a "Packing problem" or maybe a "2D bin packing problem". Googling those should find you some information, doing it efficiently is not a simple task. If you only have a small number of images, the easy methods would be:
Random...just randomly place images until no more can fit. Run this random placement 10..100..1000 or more times, and pick the best result (where "best" is determined by some criteria like least amount of wasted space, or most pictures fit, etc)
Brute force...try every single possible combination, one by one, and pick the "best" one. Downside to this method is that as number of items scale up, the amount of computation scales up very quickly.
I researched treemapping and packing problems.
.... and eventually decided to create an array of all the points on the canvas, then assign them a value of empty. I then looped through my array of images and placed them on the points that were "empty" and reassigned all the points it occupied with the source name of the image. It worked beautifully. But definitely takes time to create the array.
I did a different take on that I just fits all images to a tile size and tile the into a document.
Image are virturly center croped to the file size via a layer mask.
Paste Image Roll Script http://www.mouseprints.net/old/dpr/PasteImageRoll.html
http://www.mouseprints.net/old/dpr/PasteImageRoll.jsx