Conditional highlight on max in matrix

[learner03]

How can I do conditional highlight based on each row by product in this situation like, if Max quantity in the row in destination belongs to same state and max quantity belong to state in origin then do not highlight otherwise highlight both max in both (destintion & origin)

example-  max of product A is 1000 which belongs to y1 and max in origin is 1000which belongs to y1 so no highlight. Same for product B.

But for product C, Max in the destination is 1000 which belongs to x1 and max in origin is 1000 that belongs to Z1, so highlight both values here. 

In G, Max in destination  belongs to z1 which is 300 and max in origin belongs to y1 which is 343, so highlight both.

[Jihwan_Kim]

Hi,

I am not sure how your semantic model looks like, but I tried to create a sample pbix file like below.

Please check the below picture and the attached pbix file whether it suits your requirement.

INDEX function (DAX) - DAX | Microsoft Learn

color condition: =
VAR _destinationmaxstate =
    MAXX (
        INDEX (
            1,
            FILTER ( ALL ( State ), State[State Type] = "Destination" ),
            ORDERBY ( [Quantity:], DESC )
        ),
        State[State]
    )
VAR _originnmaxstate =
    MAXX (
        INDEX (
            1,
            FILTER ( ALL ( State ), State[State Type] = "Origin" ),
            ORDERBY ( [Quantity:], DESC )
        ),
        State[State]
    )
VAR _maxqty =
    CALCULATE (
        [Quantity:],
        INDEX (
            1,
            ALL ( State ),
            ORDERBY ( [Quantity:], DESC ),
            ,
            PARTITIONBY ( State[State Type] )
        )
    )
RETURN
    IF ( _destinationmaxstate <> _originnmaxstate && [Quantity:] = _maxqty, "red" )

[learner03]

@Jihwan_Kim it says "INDEX's Relation parameter may have duplicate rows. This is not allowed.".

my Model is below and I have pivotted state column.

Input

ProdInvc
P.Name	Origin State	Destination State	Qty	Amount
A	x1	z1	20	200
b	y1	w1	100	1000
c	z1	x1	1000	2000
e	w1	y1	300	2000
f	x1	z1	200	3000
g	y1	w1	43	200
h	z1	x1	200	1000
i	w1	y1	400	4000
j	x1	z1	400	5000
k	y1	z1	300	2000
l	z1	w1	200	3000
m	w1	x1	100	1000
A	y1	y1	1000	1000
b	z1	z1	300	2000
c	w1	w1	200	2000
e	x1	x1	43	3000
f	y1	y1	1000	200
g	y1	z1	300	1000
h	z1	w1	200	4000
i	w1	x1	43	1000
j	x1	y1	200	2000
k	y1	z1	43	2000
l	y1	w1	200	3000
m	z1	x1	400	200
c	w1	y1	400	1000
e	x1	z1	300	4000
f	y1	w1	200	2000

State

x1

y1

z1

w1