I am trying to edit a linear dimension after it has already been placed, adding mtext. I understand that you can override the text on a linear dimension, but my goal is to be able to stack two numbers on top of each other under one dimension.
Use the escape code \X to stack two texts:
Upper\XLower
Probably the Dimension.Prefix property will do the trick here.
Related
I have the following DataFrame (only a part of it is shown):
I use it to generate the following plot in Altair. I generated this plot based on a modification of the code suggested in this post.
However, due to the fact that each of my Y labels has a different number of associated data points, the only way I could make the plot appear as desired was by using np.resize to repeat values. This works almost perfectly, but leads to the unfortunate issue that some of the marks in the plot appear darker than others, which can be misleading because it does not actually relate to the data in any way. Is there any way to get around this in Altair?
It sounds like you're asking about the opacity of the marks, which defaults to semi-transparent. You can adjust this with the opacity argument to mark_point(); for example:
alt.Chart(data).mark_point(opacity=1)
I'm working on a system to automatically take 2D profiles of components and assemble them into 3D shapes.
Imagine given these pieces:
You want to make this shape:
I'm highlighting one of the components to show how they fit together.
I'm open to any suggestions on how to go about doing this but the current approach I'm attempting first finds joints that may fit together just by looking at the 2D profile.
How could I go about identifying the "tabs" from the polyline profile?
The same technique should also work on assemblies like such:
see How to compare two shapes?
so you basically trying to find the "same" sequences in polylines encoded in the polar increment format (turn angle, line length) and then just check if relative position of matched sequences are the same in both shapes ...
Beware that the locks might have some gap between the joined shapes to ensure assembly is possible... in same case the gap might be even negative (overlap) depends on material and function so You need to compare the sequences with some margin ...
Also I would divide each shape into its sides to speed up the process as the lock is most likely not crossing sides ...
You may define the "code" for a tab. For example:
3,C,5,C,3 would mean: Three units length, then turn 90º counter-clockwise, then 5 units length, then turn 90º counter-clockwise, then 3 units length.
Of course more identifiers than C can be used, for different angles and so.
A tab in another piece that fits in the tab of the first piece has the same (or very similar) 3,C,5,C,3 code
So, finding same code in both pieces may be a fit. Check if adjacents codes in both pieces also fit, and you're done.
Notice that pieces can be rotated. This case doesn't change the code, but may change the order of adjacents codes.
I have been asked to create three dimensional vector embeddings for a series of words. Although I understand what an embedding is and that word2vec will be able to create the vector embeddings, I cannot find a resource that shows me how to create a three dimensional vector (all the resources show many more dimensions than this).
The format I have to create the file in is:
house 34444 0.3232 0.123213 1.231231
dog 14444 0.76762 0.76767 1.45454
which is in the format <token>\t<word_count>\t<vector_embedding_separated_by_spaces>
Can anyone point me towards a resource that will show me how to create the desired file format given some training text?
Once you've decided on a programming language, and word2vec library, its documentation will likely highlight a configurable parameter that lets you specify the dimensionality of the vectors it trains. So, you just need to change that parameter from its typical values , like 100 or 300, to 3.
(Note, though, that 3-dimensional word-vectors are unlikely to show the interesting & useful property of higher-dimensional vectors.)
Once you've used such a library to create the vectors-in-memory, writing them out in your specified format becomes just a file-IO problem, unrelated to word2vec itself. In typical languages, you'd open a new file for writing, loop over your data printing each line properly, then close the file.
(To get a more detailed answer from StackOverflow, you'd want to pick a specific language/library, show what you've already tried with actual code, and show how the results/errors achieved fall short of your goal.)
I am running into problems when computing the relative risk estimation (relrisk.ppp) of two point patterns: One with four marks in a rectangular region and the other with two marks in a circular region.
For the first pattern with four marks, I am able to get the relative risk and the resulting object in a large imlist with 4 elements corresponding to each mark.
However, for the second pattern, it gives a list of 10 elements, of which the first matrix v is empty with NA entries. I am breaking my head on what possibly could be wrong when the created point pattern objects seems to be identical. Any help will be appreciated. Thanks.
For your first dataset, the result is a list of image objects (a list of four objects of class im). For your second dataset, the result of relrisk.ppp is a single image (object of class im). This is the default behaviour when there are only two possible types of points (two possible mark values). See help(relrisk.ppp).
In all cases, you should just be able to plot and print the resulting object. You don't need to examine the internal data of the image.
More explanation: when there are only two possible types of points, the default behaviour of relrisk.ppp is to treat them as case-control data, where the points belonging to the first type are treated as controls (e.g. non-infected people), and the points of the second type are treated as cases (e.g. infected people). The ratio of intensities (cases divided by controls) is estimated as an image.
If you don't want this to happen, set the argument casecontrol=FALSE and then relrisk.ppp will always return a list of images, with one image for each possible mark. Each image gives the spatially-varying probability of that type of point.
It's all explained in help(relrisk.ppp) or in the book.
To learn some plotting in spatstat, I am trying to plot database mucosa using the split function to create a multivariate plot. I get two different subplots of mucosa, but by default they both have the same symbology.
library(spatstat)
plot(split(mucosa))
Now in the two subplots, I would like to customise each subplot in terms of colour, size, shape etc. How can I do this? please advice.
I tried to pass pch and cex and col as a vector of two elements (because I know it is two types), but I get error
plot(split(mucosa), pch=c(19,3))
Error in symbolmap(..., chars = chars, cols = cols) :
Argument ‘pch’ is neither a function nor a constant
It seems untraditional to plot the types with different plotting characters when they are split into different panels. Why do you want to do that?
If you plot them in the same single plot you can just do as you suggest:
plot(mucosa, pch = c(19, 3))
And here you can add cols, cex, ...
However, if you first split the point pattern the more complicated plot.listof is called and you can look at that help file for details. Also if you look at our book Baddeley, Rubak and Turner (2015) you may find multi-panel plots which may inspire you. On the companion website for the book you can find code to generate all the figures of the book (requires a bit of searching though).
Use the argument chars instead of pch to specify several plotting characters.
In the call to split, you need to specify the argument un=FALSE which ensures that each of the split point patterns retains its original mark information (i.e. the type of each point).
So you need
plot(split(mucosa, un=FALSE), chars=c(19,3))