The region setting will not effect the memory consumption of this module. The number of subranges in case of value range calculation or the number of equal value groups effect the memory consumption and the calculation time. The user can expect a huge time consumption to calculate the equal value groups (flag -e) if large region settings occur for maps which have many equal value groups (> 100000).
num | value | volume | perc | count 1 1.000000 300822000.000 50.13700 50137 2 2.000000 101400000.000 16.90000 16900 3 3.000000 197778000.000 32.96300 32963 4 * 0.000 0.00000 0 Number of groups with equal values: 3 Sum of non Null cells: Volume = 600000000.000 Percentage = 100.000 Count = 100000 Sum of all cells: Volume = 600000000.000 Percentage = 100.000 Count = 100000
#create a small 3D region g.region n=1000 s=0 e=2000 w=0 t=300 b=0 res3=100 #create a raster3D map with row() and null values r3.mapcalc "volmap = if(row() == 5, null(), row())" #run r3.stats with a subrange of 10 r3.stats input=volmap nsteps=10 #the result should look like this num | minimum <= value | value < maximum | volume | perc | cell count 1 1.000000000 1.900000000 60000000.000 10.00000 60 2 1.900000000 2.800000000 60000000.000 10.00000 60 3 2.800000000 3.700000000 60000000.000 10.00000 60 4 3.700000000 4.600000000 60000000.000 10.00000 60 5 4.600000000 5.500000000 0.000 0.00000 0 6 5.500000000 6.400000000 60000000.000 10.00000 60 7 6.400000000 7.300000000 60000000.000 10.00000 60 8 7.300000000 8.200000000 60000000.000 10.00000 60 9 8.200000000 9.100000000 60000000.000 10.00000 60 10 9.100000000 10.000000001 60000000.000 10.00000 60 11 * * 60000000.000 10.00000 60 Sum of non Null cells: Volume = 540000000.000 Percentage = 90.000 Cell count = 540 Sum of all cells: Volume = 600000000.000 Percentage = 100.000 Cell count = 600
Available at: r3.stats source code (history)
Latest change: Thursday Jan 26 14:10:26 2023 in commit: cdd84c130cea04b204479e2efdc75c742efc4843
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