I have a simple graph created with dot which represents simple neural network.
I want to make this graph wider, i.e. make more space between layers by elongating edges. I tried to do it with size and ratio attributes but without success. Ratio works for height, but I want to increase width.
In case anyone needs this later, I have solved my problem with variable ranksep.
Have you tried the nodesep variable?
GraphViz documentation
From the documentation it says "In dot, this specifies the minimum space between two adjacent nodes in the same rank, in inches." So depending on how you have your ranks set up, this might help you. The the look of your graph (lacking the .gv file), I'd guess that you're using invisible top-to-bottom ranks to align the vertical columns. If this, the nodesep variable may work well for you. The default is quite small, 0.25 inch.
Related
I'm using FontForge. I'm modifying the lower case q to make a straight-stalked 9. The q has 2 logical parts, the stalk, and the 'c'. The 'c' is too big vertically. How can I scale it down vertically while keeping the vertical stroke widths the same (and not altering any of the horizontal dimensions)?
I'm a novice with FontForge, so please spell out your explanation and provide step-by-step instructions. Thanks for your help.
It sounds like you want to decrease the x-height of the 'q' without changing stroke widths.
Font-forge provides a built-in tool to achieve this: Element > Styles > Change X-Height. You might like to experiment with this, but in practice it gives you very little control over the results and I would rarely use it.
Instead I would achieve this by directly modifying the nodes of the paths.
First, I would ensure that InterpolateCPsOnMotion is enabled. Double-click the pointer tool in your toolbox to access this setting.
This will help ensure that curves scale correctly (rather than distort) as you move control points. Now, I would select the nodes at the top and sides of the bowl of the q:
and use the down arrow key to move them down about half the distance you wish to decrease the height by. Then I would deselect the nodes at the side of the bowl:
and lower the remaining nodes the rest of the distance:
You will need to check the resulting appearance and possibly make tweaks to get it perfect. Note that this or any scaling technique can subtly distort the axis of modulated strokes, which you may wish to correct.
This technique presupposes that nodes are sensibly placed at the vertical and horizontal extrema of the bowl, and that you don't have extra nodes between these extrema. If you are not in this happy situation, you can add extrema by ctrl-shift-x and you can remove surplus nodes by selecting them and ctrl-m. If you can't remove extra nodes without significantly changing the shape of the bowl, you'll just have to modify these nodes by eye.
Another point: you say you're working from a "c". I'm not sure whether you just mean the C-shape of the bowl of the q, or whether you mean you are copying the actual glyph 'c'. Note that it is rare that the bowl of a 'q' will have exactly the same shape and weight as a 'c'. Typically the stroke will be somewhat lighter to achieve the right visual grey, and especial care will be taken where it intersects the stem. Often the two shapes will differ substantially.
What options should I use for making my graph looking like an Elipse ? I was messing with the hierarchical option under the layout module, but I've not gotten nowhere near my desired shape.
My graph is left to right, left node group connects to middle one, and middle one connects to the right one. It can be perceived as this image below.
Can someone point me in the right direction ? Thanks for your expertise
As for the elliptic shape around the nodes and edges, you can either set a background image to your graph area or create a node of large size (but this way you may have troubles with node repulsion, though). Unfortunately, there's no way to make sure that all the nodes will always be inside the ellipse (unless you access the vis' canvas and deal with it on low level or do some other hackery).
Also AFAIK it is impossible to create those wavy edges, but for those rounded ones you may want to use repulsion physics instead of barnesHut. See also physicsConfiguration example.
Recently I had much fun with the Laplacian Pyramid algorithm (http://persci.mit.edu/pub_pdfs/pyramid83.pdf). But one big problem is that the original paper is limited to 2^m+1*2^n+1 images. My question is: What is the best way to deal with arbitrary w*h instead? I can think of a couple of options:
Up sample the input to the next 2^m+1,2^n+1 up front
Pad even lines. How exactly? Wouldn't it shift the signal?
Shift even lines by half a sample? Wouldn't it loose half a sample?
Does anybody have experience with this? What is the most practical and efficient approach? Also any pointers to papers dealing with this would be very welcome.
One approach is to create an image with a width and height equal to the next 2^m+1,2^n+1, but instead of up-sampling the image to fill the expanded dimensions, just place it in the top-left corner and fill the empty space to the right and below with a constant value (the average value for the image is a good choice for this). Then encode in the normal way, storing the original image dimensions along with the pyramid. When decoding, decode and then crop to the original size.
This won't introduce any visual artifacts or degradation because you aren't stretching or offsetting the image in any way.
Because the empty space to the right and below the original image is a constant value, the high-pass bands at each level in the image pyramid will be all zero in this area. So if you are using a compression scheme like run length encoding to store each level this will be automatically taken care off and these areas will be compressed to almost nothing. If not then you can simply store the top-left (potentially non-zero) area of each level and then fill out the rest with zeros when decoding.
You could find the min and max x and y bounding rectangle of the non-zero values for each level and store this along with the level, cropped to include only non-zero values. The decoder could also be optimized so that areas of the image that are going to be cropped away are not actually decoded in the first place, by only processing the top-left of each level.
Here's an illustration of the technique:
Instead of just filling the lower-right area with a flat color, you could fill it with horizontally and vertically mirrored copies of the image to the right and below, and a copy mirrored in both directions to the bottom-right, like this:
This will avoid the discontinuities of the first technique, although there will be a discontinuity in dx (e.g. if the value was gradually increasing from left to right it will suddenly be decreasing). Choosing a mirror that keeps dx constant and ddx zero will avoid this second-order discontinuity by linearly extrapolating the values.
Another technique, which is similar to what some JPEG encoders do to pad out an image to a whole number of MCU blocks, is to take the last pixel value of each row and repeat it, and likewise for columns, with the bottom-right-most pixel of the image used to fill the bottom-right area:
This last technique could easily be modified to extrapolate the gradient of values or even the gradient of gradients instead of just repeating the same value for the remainder of the row or column.
I have a graph like:
I would like to generate a set of (x,y) pairs that correspond to points of this graph.
Maybe one for each horizontal pixel.
How would I go about doing this?
If I had the image in uncompressed bitmap format, maybe cropped to the actual graph, I could examine each vertical strip for the blackest point...
I would prefer to work in Python, but I'm interested in any technique.
I answered a question like this a while back. It should be fairly easy to detect the grid, from there you can get the pixel's coordinates relatively to the grid. However, it wasn't clear how to extract the numbers, which you need to do in order to get the the scale of the grid. Although, it might be possible fairly easily if you can match the font and font size (which might be possible via scaling). Otherwise, you'd have to enter the numbers manually.
To extract the grid, you'd start from the top right and move diagonally until you find the start of the grid. From there you can follow the vertical and horizontal lines (of the grid) until they end. This should allow you to say with fairly high probability where the outer rectangle of the grid is and what the x and y intervals of the grid are in terms of pixels. The blackest parts within the grid should do for finding the curve, but it may require some interpolation depending on how many data points you need/want.
It also may be useful to look into techniques for reversing anti-aliasing effects. Although, the uncompressed bitmap image may not need it.
I have some kind of a shape consisting of vertical, horizontal and diagonal lines. I have starting X,Y and ending X,Y (this is my input - just 2 points defining a line) of each line and I would like to make the whole shape scalable (just by changing the value of a scale ratio variable), so that I can still preserve the proper connection of the lines and the proportions as well. Just for getting a better idea of what I mean: it'd be as if I had the same lines in a vector editor.
Would that be possible with an algorithm, and could you please, give me another possible solution if there is no such algorithm ?
Thank you very much in advance!
what point do you want it to scale about? You could scale relative to the first point, the center, or some other arbitrary location. Typically, you subtract out an offset (for instance the first point in your input), multiply by a scale factor, and then add back the offset.
A more systematic approach in computer graphics would be to use a transformation matrix... although thats probably overkill in your case.