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Coursera course "R Programming" - Programming Assignment 2: Lexical Scoping

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Programming Assignment 2: Lexical Scoping

For the Coursera course R Programming

The following code demonstrates how to use the assessment3.R R script.

Lines starting with # are simple comments, lines starting with #> are things printed in the output.

# read the R script
# replace the "path/to/file" with the directory you save the file into
# or you can read the file directly from the web
source("path/to/file/assessment3.R")

# create a *square* matrix (because `solve` only handles square matrices)
# create the matrix during the call of makeCacheMatrix()
a <- makeCacheMatrix( matrix(c(1,2,12,13), nrow = 2, ncol = 2) );

summary(a);
#>              Length Class  Mode    
#> setMatrix    1      -none- function
#> getMatrix    1      -none- function
#> cacheInverse 1      -none- function
#> getInverse   1      -none- function

a$getMatrix();
#>      [,1] [,2]
#> [1,]    1   12
#> [2,]    2   13

cacheSolve(a)
#> [,1]        [,2]
#> [1,] -1.1818182  1.09090909
#> [2,]  0.1818182 -0.09090909

# the 2nd time we run the function,we get the cached value
cacheSolve(a)
#> getting cached data
#> [,1]        [,2]
#> [1,] -1.1818182  1.09090909
#> [2,]  0.1818182 -0.09090909

Alternatively, the matrix can be created after calling a makeCacheMatrix without arguments.

# read the R script
# replace the "path/to/file" with the directory you save the file into
# or you can read the file directly from the web
source("path/to/file/assessment3.R")

# call makeCacheMatrix without arguments
a <- makeCacheMatrix();
summary(a);
#>              Length Class  Mode    
#> setMatrix    1      -none- function
#> getMatrix    1      -none- function
#> cacheInverse 1      -none- function
#> getInverse   1      -none- function

# create a square matrix (reason `solve` only handles square matrices )
a$setMatrix( matrix(c(1,2,12,13), nrow = 2, ncol = 2) );
a$getMatrix();
#>      [,1] [,2]
#> [1,]    1   12
#> [2,]    2   13

cacheSolve(a)
#> [,1]        [,2]
#> [1,] -1.1818182  1.09090909
#> [2,]  0.1818182 -0.09090909

# the 2nd time we run the function, we get the cached value
cacheSolve(a)
#> getting cached data
#> [,1]        [,2]
#> [1,] -1.1818182  1.09090909
#> [2,]  0.1818182 -0.09090909

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Coursera course "R Programming" - Programming Assignment 2: Lexical Scoping


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