Compute the Discrete Cosine Transform of every row in the H2OFrame
h2o.dct(data, destination_frame, dimensions, inverse = FALSE)
data | An H2OFrame object representing the dataset to transform |
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destination_frame | A frame ID for the result |
dimensions | An array containing the 3 integer values for height, width, depth of each sample. The product of HxWxD must total up to less than the number of columns. For 1D, use c(L,1,1), for 2D, use C(N,M,1). |
inverse | Whether to perform the inverse transform |
Returns an H2OFrame object.
# NOT RUN { library(h2o) h2o.init() df <- h2o.createFrame(rows = 1000, cols = 8 * 16 * 24, categorical_fraction = 0, integer_fraction = 0, missing_fraction = 0) df1 <- h2o.dct(data = df, dimensions = c(8 * 16 * 24, 1, 1)) df2 <- h2o.dct(data = df1, dimensions = c(8 * 16 * 24, 1, 1), inverse = TRUE) max(abs(df1 - df2)) df1 <- h2o.dct(data = df, dimensions = c(8 * 16, 24, 1)) df2 <- h2o.dct(data = df1, dimensions = c(8 * 16, 24, 1), inverse = TRUE) max(abs(df1 - df2)) df1 <- h2o.dct(data = df, dimensions = c(8, 16, 24)) df2 <- h2o.dct(data = df1, dimensions = c(8, 16, 24), inverse = TRUE) max(abs(df1 - df2)) # }