blob: e566bcbc68b252e473e2c17a51520feb28266606 [file] [log] [blame]
#-------------------------------------------------------------
#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
#
#-------------------------------------------------------------
# Fix invalid lengths
#
# INPUT:
# ------------------------
# X ---
# mask ---
# ql ---
# qu ---
# ------------------------
#
# OUTPUT:
# ------------------------
# out ---
# M ---
# ------------------------
s_fixInvalidLengthsApply = function(Frame[Unknown] X, Matrix[Double] mask, Matrix[Double] qLow, Matrix[Double] qUp)
return (Frame[Unknown] X)
{
length = map(X, "x -> x.length()")
length = as.matrix(length)
length = replace(target = (length * mask), pattern = NaN, replacement = 0)
M = ( length < qLow | length > qUp)
# # # check if mask vector has 1 in more than one column
# # # this indicates that two values are being swapped and can be fixed
rowCountSwap = rowSums(M) >= 2
rowCountDangling = rowSums(M) > 0 & rowSums(M) < 2
if(sum(rowCountSwap) > 0)
{
countTotalSwaps = sum(rowCountSwap)
# # get the row index for swapping
rowIds = rowCountSwap * seq(1, nrow(rowCountSwap))
rowIds = removeEmpty(target=rowIds, margin="rows")
colIds = M * t(seq(1, ncol(M)))
for(i in 1:countTotalSwaps)
{
rowIdx = as.scalar(rowIds[i, 1])
colIdx = removeEmpty(target = colIds[rowIdx], margin="cols")
id1 = as.scalar(colIdx[1, 1])
id2 = as.scalar(colIdx[1, 2])
tmp = X[rowIdx, id1]
X[rowIdx, id1] = X[rowIdx, id2]
X[rowIdx, id2] = tmp
# # remove the mask for fixed entries
M[rowIdx, id1] = 0
M[rowIdx, id2] = 0
}
}
if(sum(rowCountDangling) > 0) # no swaps just invalid lengths
{
countTotalInvalids = sum(rowCountDangling)
# # get the row index for swapping
rowIds = rowCountDangling * seq(1, nrow(rowCountDangling))
rowIds = removeEmpty(target=rowIds, margin="rows")
colIds = M * t(seq(1, ncol(M)))
for(i in 1:countTotalInvalids)
{
rowIdx = as.scalar(rowIds[i, 1])
colIdx = removeEmpty(target = colIds[rowIdx], margin="cols")
id1 = as.scalar(colIdx[1, 1])
X[rowIdx, id1] = ""
# # remove the mask for fixed entries
M[rowIdx, id1] = 0
}
}
M = replace(target = M, pattern = 1, replacement = NaN)
}