CoCalc Public Filessupport / nbgrader-r-kernel.ipynbOpen in with one click!
Author: William A. Stein
Description: Jupyter notebook support/2015-06-04-141749-bokeh.ipynb
Manually graded answer(1 point), ID: 62b50c
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foo <- function(a, b) { # Returns a + b ### BEGIN SOLUTION return(a + b) ### END SOLUTION }
Answer that will be automatically graded below, ID: 988a6c
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squares <- function(n) { # Compute the squares of the numbers from 1 to n. ### BEGIN SOLUTION # Put correct code here. This code is removed for the student version, but is # used to confirm that your tests are valid. if (n <= 0) { stop("n must be positive") } x <- 1:n return(x * x) ### END SOLUTION }
Test your code from above here(1 point), ID: 3c374e
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testthat::test_that("squares function works as expected", { # test the result is an integer vector of length 10 testthat::expect_vector(squares(10), ptype = integer(), size = 10) # check for a specific n=3 testthat::expect_equal(squares(3), c(1, 4, 9)) # use 'tolerance' when there are slight floating point errors testthat::expect_equal(squares(2), c(1, 4.000001), tolerance = 0.002) }) # make sure the error contains the word 'positive' for a negative n testthat::test_that("squares function raises errors", { testthat::expect_error(squares(-1), "*positive*", ignore.case = TRUE) }) ### BEGIN HIDDEN TESTS # students will NOT see this extra test testthat::expect_equal(squares(10), c(1, 4, 9, 16, 25, 36, 49, 64, 81, 100)) ### END HIDDEN TESTS
Readonly, ID: 8009f5
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Manually graded task(1 point), ID: 1db769

Describe the task here, e.g., "Process the data and create a plot to illustrate your results."

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Describe how you will grade the task here.

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