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# Copyright 2013 Google Inc. All Rights Reserved.
#
# Licensed 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.
#
# Author: mstokely@google.com (Murray Stokely)
HistToEcdf <- function(h, method="constant", f=0, inverse=FALSE) {
# Compute an empirical cumulative distribution function from a histogram.
#
# Args:
# h: An S3 histogram object.
# method: specifies the interpolation method to be used in call to
# approxfun(). Choices are "linear" or "constant".
# f: for method="constant" a number between 0 and 1 inclusive,
# indicating a compromise between left- and right-continuous
# step functions. See ?approxfun
# inverse: If TRUE, return the inverse function.
#
# Returns:
# An empirical cumulative distribution function (see ?ecdf)
n <- sum(h$counts)
# We don't want to use h$mids here, because we want at least
# to get the correct answers at the breakpoints.
x.vals <- h$breaks
y.vals <- c(0, cumsum(h$counts) / n)
if (inverse) {
vals.tmp <- x.vals
x.vals <- y.vals
y.vals <- vals.tmp
}
rval <- approxfun(x.vals, y.vals,
method = method, yleft = 0, yright = 1, f = f,
ties = "ordered")
class(rval) <- c("ecdf", "stepfun", class(rval))
assign("nobs", n, envir = environment(rval))
attr(rval, "call") <- sys.call()
rval
}
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