hamr: Handle All Missing Values

impute_missing()

| Condition | Test Function | | ---------------------------------------- | ---------------------------------------- | | "only NA and NaN are allowed for matrix, otherwise the input matrix is not numerical" | expect_error(impute_missing(matrix(c(1,2,3, 6,8,""), nrow = 3, ncol = 2, byrow = FALSE), "V2", "DIP", "")) | | "data format is not supported, expected a data frame or a matrix" | expect_error(impute_missing(list(1, 2, 2, NA), "V2", "MIP", NA)) | | "column name is not applicable, expected a string instead" | expect_error(impute_missing(data.frame("exp" = c(1, 2, 3), "res" = c(0, 10, NaN))) | | "the specified column name is not in the data frame" | expect_error(impute_missing(data.frame(exp = c(1, 2, 3), res = c(0, 10, "")), "dn", "CC", "")) | | "method is not applicable" | expect_error(impute_missing(data.frame(x = c(1, 2, 3), y = c(0, 10, NA)), "y", "multi_im", NA)) | | "output type is a dataframe" | assert isinstance(impute_missing(np.matrix([[1, 2], [3, np.nan], [5, 6]]), 'b', "CC", np.nan), pd.DataFrame) | | "missing value format is not supported, expected one of blank space, a question mark, NA and NaN" | expect_error(impute_missing(data.frame(x = c(1, 2, 3), y = c(0, 10, 0)), "y", "CC", 0) | | "the input is a data frame, method is CC and missing_val_char is NA" | expect_equal(impute_missing(data.frame(V1 = c(1, 2, 3), V2 = c(0, 10, NA)), "V2", "CC", NA), data.frame(V1 = c(1, 2), V2 = c(0, 10))) | | "the input is a matrix, method is CC and missing_val_char is NA" | expect_equal(impute_missing(matrix(c(1,2,3, 0,10, NA), nrow = 3, ncol = 2, byrow = FALSE), "V2", "CC", NA), data.frame(V1 = c(1, 2), V2 = c(0, 10))) | | "the input is a data frame, method is MIP and missing_val_char is a qeustion mark" | expect_equal(impute_missing(data.frame(x = c(1, 2, 3), y = c(0, 10, "?")), "y", "MIP", "?"), data.frame(x = c(1, 2, 3), y = c(0, 10, 5))) | | "the input is a data frame, method is MIP and missing_val_char is a blank space" | expect_equal(impute_missing(data.frame(x = c(1, 2, 3), y = c(0, 5, " ")), "y", "MIP", " "), data.frame(x = c(1, 2, 3), y = c(0.0, 5.0, 2.5))) | | "the input is a matrix, method is MIP and missing_val_char is NaN" | expect_equal(impute_missing(matrix(c(1,2,3, 0,10,NaN), nrow = 3, ncol = 2, byrow = FALSE), "V2", "MIP", NaN), data.frame(V1 = c(1, 2, 3), V2 = c(0, 10, 5))) | | "the input is a data frame, method is DIP and missing_val_char is a blank space" | expect_equal(impute_missing(data.frame(ex = c(1, 2, 3), bf = c(6, 8, "")), "bf", "DIP", ""), data.frame(ex = c(1, 2, 3), bf = c(6, 8, 7))) | | "the input is a matrix, method is DIP and missing_val_char is NA" | expect_equal(impute_missing(matrix(c(1,2,3, 6,8,NA), nrow = 3, ncol = 2, byrow = FALSE), "V2", "DIP", NA), data.frame(V1 = c(1, 2, 3), V2 = c(6, 8, 7))) |

compare_model()

| Condition | Test Function | | ---------------------------------------- | ---------------------------------------- | | Test that output type is a dataframe or a list | expect_match(typeof(result),"list") | | Test that output type is a dataframe or a list | expect_match(class(result),"data.frame") | | Test base case | expect_equal(test,result) | | Test that input is a dataframe or a list | expect_error(compare_model(list(1, 2, 2, NA), "V2", "MIP", "NA") | | Check column name is a string | expect_error(compare_model(data.frame("exp" = c(1, 2, 3), "res" = c(0, 10, NaN)) | | Check if the specified column name is in the data frame | expect_error(compare_model(data.frame(exp = c(1, 2, 3), res = c(0, 10, "")) | | Check if specified method is supported | expect_error(compare_model(data.frame(x = c(1, 2, 3), y = c(0, 10, NaN)), "y", "multi_im", "NaN") | | Check if missing value format issupported | expect_error(compare_model(data.frame(x = c(1, 2, 3), y = c(0, 10, 0)), "y", "CC", 0) |