@@ -47,9 +47,9 @@ setMethod(f="model_apply",

         smeta=D$sample_meta

         x=D$data

-        coeff = apply(x,MARGIN = 2,FUN = function(z) sqrt(sum(z, na.rm = TRUE)))

-        normalised = apply(x,MARGIN = 2,FUN = function(z) z/sqrt(sum(z, na.rm=TRUE)))

-        D$data = as.data.frame(normalised)

+        coeff = apply(x,MARGIN = 1,FUN = function(z) sqrt(sum(z*z, na.rm = TRUE)))

+        normalised = apply(x,MARGIN = 1,FUN = function(z) z/sqrt(sum(z*z, na.rm=TRUE)))

+        D$data = as.data.frame(t(normalised))

         output_value(M,'normalised') = D

         output_value(M,'coeff') = data.frame('coeff'=coeff)

@@ -7,5 +7,8 @@ test_that('vecnorm',{

   M = vec_norm()

   # apply

   M = model_apply(M,D)

-  expect_equal(M$normalised$data[1,1],0.172,tolerance=0.001)

+  expect_equal(sum(M$normalised$data[1,]^2),1,tolerance=0.00001)

+  expect_equal(sum(M$normalised$data[5,]^2),1,tolerance=0.00001)

+  expect_equal(sum(M$normalised$data[25,]^2),1,tolerance=0.00001)

+  expect_equal(predicted(M)$data[1,1],0.8037,tolerance=0.0001)

 })