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## Power BI Matrix sum totalling %ages incorrectly Tag : sql , By : user106284 Date : November 29 2020, 04:01 AM

Any of those help It seems like the purpose of your Measure2 is to show [Actual Y.T.D] as a percentage of [Full Year Budget], and to only show that if you are in the context of a single [KPI group].
The reason you aren't getting the result you expect is probably because you are using SUMX() where you shouldn't, SUMX() will calculate the percentage once for each row of the 'CPP' table and then add all of those together.
``````Measure 2 =
IF(
HASONEVALUE(CPP[KPI Group]),
DIVIDE(
SUM(CPP[Actual Y.T.D]),
SUM('Corporate Planning Project'[Full Year Budget]),
0
)
)
``````

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## Cognos Crosstab Report Calculated Column Totalling Incorrectly

Tag : development , By : johntynan
Date : March 29 2020, 07:55 AM
may help you . Try to customize Solve Order for your calculations. Default behavior is Total(Value1/Value2). You need to archive Total(Value1)/Total(Value2) (Don't change your formulas, just set Solve Order for calculations)

## R - Given a matrix and a power, produce multiple matrices containing all combinations of matrix columns

Tag : r , By : Gilmar Souza Jr.
Date : March 29 2020, 07:55 AM
I hope this helps . Given a matrix mat (of size N by M) and a power, p (e.g., 4), produce p matrices, where each p-th matrix contains all possible combinations of the columns in mat at that degree. , You can do something like this
``````N = 5
M = 3
p = 4
mat = matrix(1:(N*M),N,M)

res_mat <- list()
res_mat[[1]] <- mat
for(i in 2:p) {
res_mat[[i]] <- t(sapply(1:N, function(j) tcrossprod(res_mat[[i-1]][j, ], res_mat[[1]][j, ])))
}
``````

## R - Given a matrix and a power, produce multiple matrices containing all unique combinations of matrix columns

Tag : r , By : niel
Date : March 29 2020, 07:55 AM
like below fixes the issue Based on my related question linked below (see @Aleh solution): I am looking to calculate only unique products between columns in a matrix for a given power. , If I understand you correctly, then this is what you are looking for:
``````# all combinations of p elements out of M with repetiton
# c.f. http://www.mathsisfun.com/combinatorics/combinations-permutations.html
comb_rep <- function(p, M) {
combn(M + p - 1, p) - 0:(p - 1)
}

# use cols from mat to form a new matrix
# take row products
col_prod <- function(cols, mat) {
apply(mat[ ,cols], 1, prod)
}

N <- 5
M <- 3
p <- 3
mat <- matrix(1:(N*M),N,M)

col_comb <- lapply(2:p, comb_rep, M)
col_comb
#> [[1]]
#>      [,1] [,2] [,3] [,4] [,5] [,6]
#> [1,]    1    1    1    2    2    3
#> [2,]    1    2    3    2    3    3
#>
#> [[2]]
#>      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
#> [1,]    1    1    1    1    1    1    2    2    2     3
#> [2,]    1    1    1    2    2    3    2    2    3     3
#> [3,]    1    2    3    2    3    3    2    3    3     3

# prepend original matrix
res_mat <- list()
res_mat[[1]] <- mat
c(res_mat,
lapply(col_comb, function(cols) apply(cols, 2, col_prod, mat)))
#> [[1]]
#>      [,1] [,2] [,3]
#> [1,]    1    6   11
#> [2,]    2    7   12
#> [3,]    3    8   13
#> [4,]    4    9   14
#> [5,]    5   10   15
#>
#> [[2]]
#>      [,1] [,2] [,3] [,4] [,5] [,6]
#> [1,]    1    6   11   36   66  121
#> [2,]    4   14   24   49   84  144
#> [3,]    9   24   39   64  104  169
#> [4,]   16   36   56   81  126  196
#> [5,]   25   50   75  100  150  225
#>
#> [[3]]
#>      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
#> [1,]    1    6   11   36   66  121  216  396  726  1331
#> [2,]    8   28   48   98  168  288  343  588 1008  1728
#> [3,]   27   72  117  192  312  507  512  832 1352  2197
#> [4,]   64  144  224  324  504  784  729 1134 1764  2744
#> [5,]  125  250  375  500  750 1125 1000 1500 2250  3375
``````
``````# original function from @Moody_Mudskipper's answer
fun <- function(mat,p) {
mat <- as.data.frame(mat)
combs <- do.call(expand.grid,rep(list(seq(ncol(mat))),p)) # all combinations including permutations of same values
combs <- combs[!apply(combs,1,is.unsorted),]              # "unique" permutations only
rownames(combs) <- apply(combs,1,paste,collapse="-")      # Just for display of output, we keep info of combinations in rownames
combs <- combs[order(rownames(combs)),]                   # sort to have desired column order on output
apply(combs,1,function(x) Reduce(`*`,mat[,x]))            # multiply the relevant columns
}
combined <- function(mat, p) {
mat <- as.data.frame(mat)
combs <- combn(ncol(mat) + p - 1, p) - 0:(p - 1)          # all combinations with repetition
colnames(combs) <- apply(combs, 2, paste, collapse = "-") # Just for display of output, we keep info of combinations in colnames
apply(combs, 2, function(x) Reduce(`*`, mat[ ,x]))        # multiply the relevant columns
}
N <- 10000
M <- 25
p <- 4
mat <- matrix(runif(N*M),N,M)
microbenchmark::microbenchmark(
fun(mat, p),
combined(mat, p),
times = 10
)
#> Unit: seconds
#>              expr      min       lq     mean   median       uq      max neval
#>       fun(mat, p) 3.456853 3.698680 4.067995 4.032647 4.341944 4.869527    10
#>  combined(mat, p) 2.543994 2.738313 2.870446 2.793768 3.090498 3.254232    10
``````

## Total/Sum working incorrectly in Power Bi

Tag : powerbi , By : ponchopilate
Date : March 29 2020, 07:55 AM

## np.power (raised to power 2) of matrix is not resulting in elements^2

Tag : python , By : Brian
Date : March 29 2020, 07:55 AM
may help you . The element in your matrix are of type 8-bit unsigned integer (uint8) which means they are restricted between 0 and 255. So (252**2) % 256 = 16
You can change your array type using:
``````m = m.astype(np.uint16)
``````