Logical indexing is a compact and expressive notation that's very useful for many image processing operations. Let's talk about the basic rules of logical indexing, and then we'll reexamine the expression B (isnan (B)). If C and D are matrices, then C (D) is a logical indexing expression if C and D are the same size, and D is a logical matrix.
Matrices are the R objects in which the elements are arranged in a two-dimensional rectangular layout. They contain elements of the same atomic types. Though we can create a matrix containing only characters or only logical values, they are not of much use. We use matrices containing numeric elements to be used in mathematical calculations.
In a data frame the columns contain different types of data, but in a matrix all the elements are the same type of data. A matrix in R is like a mathematical matrix, containing all the same type of thing (usually numbers). R often but not always lets these be used interchangably.
Latent semantic indexing (LSI) is an indexing and retrieval method that uses a mathematical technique called singular value decomposition (SVD) to identify patterns in the relationships between the terms and concepts contained in an unstructured collection of text. LSI is based on the principle that words that are used in the same contexts tend to have similar meanings.
When you index a vector with a logical vector, R will return values of the vector for which the indexing vector is TRUE. If that was confusing, think about it this way: a logical vector, combined with the brackets ( ), acts as a filter for the vector it is indexing.
Logical indexing on the left assigns these values to the elements that were singled out in column major order. So it scans the first column up here, looking for a negative number. It finds one here on the third row, and it assigns the first value from the right, which was 101.
Help needed vectorizing layer-wise 3d logical. Learn more about vectorization, logical indexing, parallel computing.
This section will discuss Python matrix indexing. In order to select specific items, Python matrix indexing must be used. Lets start with the basics, just like in a list, indexing is done with the square brackets () with the index reference numbers inputted inside. However, we have to remember that since a matrix is two dimensional (a mix of rows and columns), our indexing code should also.