HiClimR 2.2.1
- Updated package website
- Updated package
DESCRIPTION
and README
- Updated package dependencies and
WORDLIST
- Style and format Fortran code
HiClimR 2.2.0
- Fixed NOTE: Found (possibly) invalid URLs
HiClimR 2.1.9
- Updated citation in package DESCRIPTION
- Updated NAMESPACE and documentation
- Fixed spelling errors
- Updated lifecycle URL in the README
HiClimR 2.1.8
- Code cleanup and formatting
- Removed HISTORY comments from source code
- Replaced
1:n
expressions with seq_len(n)
- Updated citation, manual, and user information
- Updated documents after code formatting
- Updated package DESCRIPTION and added reference DOI
- Updated package URL: https://hsbadr.github.io/HiClimR/
- README: Updated README.md and added NEWS.md
HiClimR 2.1.7
- Updated package DESCRIPTION and author information
- Updated copyright year to 2021
- README: Added Markdown badges
- README: Added Digital Object Identifier (DOI) badge
- README: Linked version and download badges to CRAN
- README: Updated URLs
HiClimR 2.1.6
- README: Added CRAN downloads badge
- R: Fix non-informative failure for unsupported input of a vector
HiClimR 2.1.5
- R: Use
inherits()
to check class inheritance
HiClimR 2.1.4
- Added vignette for HiClimR Bug Reporting
HiClimR2nc
: Updated documentation and examples
- man: Use
\code{}
instead of \bold{}
for classes
HiClimR 2.1.3
- Fixed spelling errors and allowed custom words
HiClimR2nc
: Fixed timeseries variable definition
README
: Link HiClimR
to CRAN
package page
HiClimR 2.1.2
- Fixed example ERROR in CRAN checks
- Added example to export NetCDF-4 file
- Updated dependencies and suggested packages
HiClimR 2.1.1
fastCor
: Fixed row/col names of the correlation matrix
fastCor
: Cleaned up zero-variance data check
- Examples: Minor comment update
HiClimR 2.1.0
- Supported contiguity constraint based on geographic distance
- Exporting region map and mean timeseries into NetCDF-4 file
- Replaced
multi-variate
with multivariate
- Renamed
weightedVar
to weightMVC
- Updated citation information
- Updated and cleaned up package
DESCRIPTION
- Updated and cleaned up
README
HiClimR 2.0.0
- Fixed NOTE: Registering native routines
fastCor
: Removed zero-variance data
fastCor
: Introduced optBLAS
fastCor
: Code cleanup
- Reformatted R source code
- Updated and fixed the examples
- Updated CRU TS dataset citation
- Updated
README
and all URLs
HiClimR 1.2.3
- Fixed
geogMask
confusing country codes/names
- Fixed
geogMask
filtering InDispute
areas
- Corrected data construction in the user manual
x
should be created using as.vector(t(x0))
x0
is the n by m
original data matrix
n = length(unique(lon))
and m = length(unique(lat))
coarseR
now returns the original row numbers
- Minor
README
corrections and updates
HiClimR 1.2.2
- Changes for
Undefined global functions
- Checking geographic masking output
- Minor
README
corrections and updates
HiClimR 1.2.1
- Updating variance for multivariate clustering
- More plotting options (
pch
and cex
)
geogMask
supports ungridded data
- Updated user manual with the following notes:
- longitudes takes values from
-180
to 180
(not 0
to 360
)
- for gridded data, the rows of input data matrix for each variable is ordered by longitudes
- check
rownames(TestCase$x)
for example!
- each row represents a station (grid point)
- row name is in the form of
longitude,latitude
- Minor
verbose
fixes and updates
- Minor
README
corrections and updates
- Citation updated: technical paper has been published
HiClimR 1.2.0
- Multivariate clustering (MVC)
- the input matrix
x
can now be a list of matrices (one matrix for each variable)
length(x) = nvars
where nvars
is the number of variables
- number of rows
N
= number of objects (e.g., stations) to be clustered
- number of columns
M
may vary for each variables
- e.g., different temporal periods or record lengths
- Each variable is separately preprocessed to allow for all possible options
- preprocessing is specified by lists with length of
nvars
(number of variables)
length(meanThresh) = length(x) = nvars
length(varThresh) = length(x) = nvars
length(detrend) = length(x) = nvars
length(standardize) = length(x) = nvars
length(weightMVC) = length(x) = nvars
- filtering with
meanThresh
and varThresh
thresholds
- detrending with
detrend
option, if requested
- standardization with
standardize
option, if requested
- strongly recommended since variables may have different magnitudes
- weighting by the new
weightMVC
option (default is 1
)
- combining variables by column (for each object: spatial points or stations)
- applying PCA (if requested) and computing the correlation/dissimilarity matrix
- Preliminary big data support
- function
fastCor
can now split the data matrix into nSplit
splits
- adds a logical parameter
upperTri
to fastCor
function
- computes only the upper-triangular half of the correlation/dissimilarity matrix
- it includes all required information since the correlation/dissimilarity matrix is symmetric
- this almost halves memory use, which can be very important for big data.
- fixes “integer overflow” for very large number of objects to be clustered
- Adds a logical parameter
verbose
for printing processing information
- Adds a logical parameter
dendrogram
for plotting dendrogram
- Uses
\dontrun{}
to skip time-consuming examples
- for more examples: https://github.com/hsbadr/HiClimR#examples
- Backward compatibility with previous versions
- The user manual is updated and revised
HiClimR 1.1.6
- Setting minimum
k = 2
, for objective tree cutting
- this addresses an issue caused by undefined
k = NULL
in validClimR
function
- when all inter-cluster correlations are significant at the user-specified significance level
- Code reformatting using
formatR
- Package description and URLs have been revised
- Source code is now maintained on GitHub by authors
HiClimR 1.1.5
- Updating description, URL, and citation info
HiClimR 1.1.4
- Addresses an issue for zero-length mask vector:
Error in -mask : invalid argument to unary operator
- this error was introduced in v1.1.2+ after fixing the data-mean bug
HiClimR 1.1.3
- The user manual is revised
lonSkip
and latSkip
renamed to lonStep
and latStep
, respectively
- Minor bug fixes
HiClimR 1.1.2
- A bug has been fixed where data mean is added to centered data if
standardize = FALSE
- objective tree cut and
data
component are now corrected
- to match input parameters especially when clustering of raw data
- centered data was used in previous versions
HiClimR 1.1.1
- Minor bug fixes and memory optimizations especially for the geographic masking function
geogMask
- The limit for data size has been removed (use with caution)
- A logical parameter
InDispute
is added to geogMask
function to optionally consider areas in dispute for geographic masking by country
HiClimR 1.1.0
- Code cleanup and bug fixes
- An issue with
fastCor
function that degrades its performance on 32-bit machines has been fixed
- A significant performance improvement can only be achieved when building R on 64-bit machines with an optimized
BLAS
library, such as ATLAS
, OpenBLAS
, or the commercial Intel MKL
- The citation info has been updated to reflect the current status of the technical paper
HiClimR 1.0.9
- Minor changes and fixes for CRAN
- For memory considerations,
- smaller test case with 1 degree resolution instead of 0.5 degree
- the resolution option (
res
parameter) in geographic masking is removed
- Mask data is only available in 0.1 degree (~10 km) resolution
LazyLoad
and LazyData
are enabled in the description file
- The
worldMask
and TestCase
data are converted to lists to avoid conflicts of variable names (lon
, lat
, info
, and mask
) with lazy loading
HiClimR 1.0.8
- Code cleanup and bug fixes
- Region maps are unified for both gridded and ungridded data
HiClimR 1.0.7
- Hybrid hierarchical clustering feature that utilizes the pros of the available methods
- especially the better overall homogeneity in Ward’s method and the separation and objective tree cut of the regional linkage method.
- The logical parameter
hybrid
is added to enable a second clustering step
- using
regional
linkage for reconstructing the upper part of the tree at a cut
- defined by
kH
(number of clusters to restart with using the regional
linkage method)
- If
kH = NULL
, the tree will be reconstructed for the upper part with the first merging cost larger than the mean merging cost for the entire tree
- merging cost is the loss of overall homogeneity at each merging step
- If hybrid clustering is requested, the updated upper-part of the tree will be used for cluster validation.
HiClimR 1.0.6
- Code cleanup and bug fixes
HiClimR 1.0.5
- Code cleanup and bug fixes
- Adds support to generate region maps for ungridded data
HiClimR 1.0.4
- Code cleanup and bug fixes
- The
coarseR
function is called inside the core HiClimR
function
- Adds
coords
component to the output tree for the longitude and latitude coordinates
- they may be changed by coarsening
validClimR
function does not require lon
and lat
arguments
- they are now available in the output tree (
coords
component)
HiClimR 1.0.3
- Code cleanup and bug fixes
- One main/wrapper function
HiClimR
internally calls all other functions
- Unified component names for all functions
- Objective tree cut is supported only for the
regional
linkage method
- Otherwise, the number of clusters
k
should be specified
- The new clustering method has been renamed from
HiClimR
to regional
linkage method
HiClimR 1.0.2
- Code cleanup and bug fixes.
- adds a new feature that to return the preprocessed data used for clustering, by a logical argument
retData
.
- the data will be returned in a component
data
of the output tree
- this can be used to utilize
HiCLimR
preprocessing options for further analysis
- Ordered regions vector for the selected number of clusters are now returned in the
region
component
- length equals the number of spatial elements
N
HiClimR 1.0.1
- Code cleanup and bug fixes
- Adds a new feature in
validCLimR
that enables users to exclude very small clusters from validation indices interCor
, intraCor
, diffCor
, and statSum
, by setting a value for the minimum cluster size (minSize > 1
)
- the excluded clusters can be identified from the output of
validClimR
in clustFlag
component, which takes a value of 1
for valid clusters or 0
for excluded clusters
- in
HiClimR
(currently, regional
linkage) method, noisy spatial elements (or stations) are isolated in very small-size clusters or individuals since they do not correlate well with any other elements
- this should be followed by a quality control step
- Adds
coarseR
function for coarsening spatial resolution of the input matrix x
HiClimR 1.0.0
- Initial version of
HiClimR
package that modifies hclust
function in stats
library
- Adds a new clustering method to the set of available methods
- The new method is explained in the context of a spatiotemporal problem, in which
N
spatial elements (e.g., stations) are divided into k
regions, given that each element has observations (or timeseries) of length M
- minimizes the inter-regional correlation between region means
- modifies
average
update formulae by incorporating the standard deviation of the mean of the merged region
- a function of the correlation between the individual regions, and their standard deviations before merging
- equals the average of their standard deviations if and only if the correlation between the two merged regions is
100%
.
- in this special case, the new method is reduced to the classic
average
linkage clustering method
- Several features are included to facilitate spatiotemporal analysis applications:
- options for preprocessing and postprocessing
- efficient code execution for large datasets.
- cluster validation function
validClimR
- implements an objective tree cut to find an optimal number of clusters
- Applicable to any correlation-based clustering