symmetry | : ferris_wheel : Detect , analyze , and visualize protein | Machine Learning library

I'm trying to detect if two square tiles are symmetries of each other, by iterating over the 8 symmetries of the square, applying each of the symmetry transforms to one of the tiles, and comparing the result of that with the other tile.

All of the transforms have the same inputs and outputs. I'd like to loop over them.

I'm using the image crate, which exports the transforms I need, with signatures like this:

I have to solve the equality between 2 matrices 12x12 containing a lot of symbolic variables and with which I perform inversion of the matrix. There are only one unknown called SIGAM_O, and FISH_O_SYM(1,1), FISH_O_SYM(1,2) and FISH_O_SYM(2,2) (FISH_O_SYM(2,1) = FISH_O_SYM(1,2).

My system is solved fastly when I take for example 2 matrices 2x2, the inversion is pretty direct.

Now, with the case of 2 matrices 12x12, I need before actually to inverse a 31x31 matrix of symbolic variables (I marginalize after), since inversion takes a lot of time.

I would like to benefit from my GPU NVIDIA card to achieve this inversion faster but the GPU optimization is not supported currently for Symbolic arrays.

Below the script where you will find the line of inversion:

I have more than 20 images that I want to classify based on pixel correlation. I am able to perform all the procedures but the problem is just saving the image into the corresponding class. Suppose that the pixel correlation values are[0.48, 0.20, 0.57, 0.53, 0.06, 0.52, 0.55, 0.57, 0.51, 0.49, ..., 0.25]

And I want to use each index of the above values based on some thresholds to classify the images into Normal, Abnormal and Ambiguous classes. With this snippet below, I achieved the following results however, The saved images are in an unsupported format

Apologies in advance for my inefficient code, still learning! I'm trying to create a loop that (1) takes items from a list of semantic characters, copying the ones that are relevant into a new matrix, and (2) deleting the items I copy as I go. I achieved part 1, but cannot get part 2 to work. It only works for the first two rows and then I get a "Error in a[[n]] : subscript out of bounds".

Here is the code that achieves part 1:

I was trying to recreate a simplified version of the natural numbers, for learning purposes (as it involves inductive definitions, recursive functions, etc...). In that process however, I got stuck in something that I thought would be very trivial.

Basically, I have a definition for natural numbers 'natt' and a definition for the '<' relation:

I would like to test the simetry in the response of an observer to a contrast stimuli with different polarity, positive (white) and negative (black). I took the reaction time (RT) as dependent variable, along four different contrasts. It is known that the response time follows a Pieron curve whose asymptotas are placed (1) at observer threshold (Inf) and (2) at a base RT placed somewere between 250 and 450 msec. The knowledge allows us to linearize the relationship transforming the independent variable (effective contrast EC) as 1/EC^2 (tEC), so the equation linking RT to EC becomes:

RT = m * tEC + RT0

To test the symmetry I established the criteria: same slope and same intercept in the two polarities implies symmetry. To obtain the coefficients I made a linear model with interaction (coding trough a dummy variable for Polarity: Positive or Negative). The output of lm is clear to me, but some colegues prefer somthing more similar to an ANOVA output. So I decided to use emmeans to make the contrasts. With the slope is all right, but when computing the interceps starts the problem. The intercepts computed by lm are very different from the output of emmeans, and the conclusions are also different. In what follows I reproduce the example. The question is two fold: It is possible to use emmeans to solve my problem? If not, it is possible to make the contrasts through other packages (which one)?

I am, specifically concerned with obeying the symmetry part of the general contract established in Object#equals(Object) where, given two non-null objects x and y, the result of x.equals(y) and y.equals(x) should be the same.

Suppose you have two classes, PurchaseOrder and InternationalPurchaseOrder where the latter extends the former. In the basic case, it makes sense that comparing an instance of each against the other shall return consistently false for x.equals(y) and y.equals(x) simply because a PurchaseOrder is not always an InternationalPurchaseOrder and therefore, the additional fields in InternationalPurchaseOrder objects will not be present in instances of PurchaseOrder.

Now, suppose you upcast an instance of InternationalPurchaseOrder.

I am wondering what is an elegant and effective way of simplifying the following snippet of code. Since I have many more buttons and their mechanics all behave in the same way, the symmetry of the methods, and the alternation from color.green -> color.red suggests there may exist a way of simplifying this down to a function?

I have been scratching my head on this design problem for a while, the way I am coding it seems definitely wrong and cumbersome.

In a magic rectangle of dimensions m x n, every entry is the XOR of the row and column, zero-indexed. Example (8 x 5):