Former-commit-id: 319744a2b8b6412fe4e911262130fbe4e0364fb1

* Changed default parameters for distinct_colors.

* Fixed bug dealing with subtracting 1 to make the factor indices to be zero based

* Changed EM function to use fastor colSumByGroupChange function to shift counts around after z labels have been altered

* updated documentation

* Added 'src/*.so' statement

* Changed 'split.each.z' to 'cC.splitZ' which utilizes the rowSumByGroupChange function to greatly increase speed in celda_C. However a separate function will be needed for the cells in celda_CG

* changed decomposed matrix to have TS as rows rather than columns (e.g. n.C.by.TS => n.TS.by.C)..

* Adding function for splitting clusters for celda_CG

* Reverted code to making any matrix with genes (G) or transcriptional state (TS) as being the rows. This eliminates the need for the counts.t matrix

* Reverted code to making any matrix with genes (G) or transcriptional state (TS) as being the rows and cells (C) or cell populations (CP) as columns. This eliminates the need for transposing matrices back and forth

* Debugged the new function 'cCG.splitZ' which will perform the cell splits for celda_CG in a much faster and more effecient way

* Refactor rowSumByGroupChange

* Modified the split for celda_G to use the faster rowSumByGroupChange function compared to rowSumByGroup

* Updated celda_CG y splitting function

* Fixed bug in using colSumByGroupChange

* updated NAMESPACE

* Updated testthat to reflect new defaults for distinct_color function

* Needed to added statement to load in previously simulated results

* Added missing lines in testthat for celda_C

* Removed dependency on Rmpfr by using functions from matrixStats package

* Changed default gamma in simulateCells functions to 5. Removed 'precision' argument in perplexity

* added 'seed' parameter to celdaTsne

* Updated NAMESPACE

* Added additional heuristic to cCG.splitY that reduces the size of the original counts matrix in the celda_G cluster splitting with L=2. It does this reduciton by splitting each current cell cluster into 'K.subclusters'. So if K=10 and K.subclusters=10, then the counts matrix will be reduced by clusterig each of the 10-K clusters into 10 additional subclusters (10 x 10 = 100 cells clusters). Therefore instead of performing celda_G on original counts matrix with large number of columns, the matrix will have at most K x K.subcluster columns.


Former-commit-id: b27139bbc2de25edb4c4e5689fa37c8cdb3c3df9

* Fix parameter checking code in celda wrapper.
* Removing deprecated parameter. Refactoring test.
* Updating documentation.
* Add SummarizedExperiment to Depends.
* Added _ prefix to C function names. Add data.table to namespace


Former-commit-id: f2efa67d604e95f3250f7ec6c4023f944cdcd859

* Changed default parameters for distinct_colors.

* Fixed bug dealing with subtracting 1 to make the factor indices to be zero based

* Changed EM function to use fastor colSumByGroupChange function to shift counts around after z labels have been altered

* updated documentation

* Added 'src/*.so' statement

* Changed 'split.each.z' to 'cC.splitZ' which utilizes the rowSumByGroupChange function to greatly increase speed in celda_C. However a separate function will be needed for the cells in celda_CG

* changed decomposed matrix to have TS as rows rather than columns (e.g. n.C.by.TS => n.TS.by.C)..

* Adding function for splitting clusters for celda_CG

* Reverted code to making any matrix with genes (G) or transcriptional state (TS) as being the rows. This eliminates the need for the counts.t matrix

* Reverted code to making any matrix with genes (G) or transcriptional state (TS) as being the rows and cells (C) or cell populations (CP) as columns. This eliminates the need for transposing matrices back and forth

* Debugged the new function 'cCG.splitZ' which will perform the cell splits for celda_CG in a much faster and more effecient way

* Refactor rowSumByGroupChange

* Modified the split for celda_G to use the faster rowSumByGroupChange function compared to rowSumByGroup

* Updated celda_CG y splitting function

* Fixed bug in using colSumByGroupChange

* updated NAMESPACE

* Updated testthat to reflect new defaults for distinct_color function

* Needed to added statement to load in previously simulated results

* Added missing lines in testthat for celda_C

* Removed dependency on Rmpfr by using functions from matrixStats package

* Changed default gamma in simulateCells functions to 5. Removed 'precision' argument in perplexity

* added 'seed' parameter to celdaTsne

* Updated NAMESPACE


Former-commit-id: 3e7a458f955513bef374fc98ed23c567155b13eb

Fixes #254

Former-commit-id: 8f60b4313d7041ba465dfe003179ca56e0d2194c

* Require class check on count matrix.

Require that all provided count matrices are checked to see if they're integer type, and if not, casting them to be that type.
Explicitly cast simulateCells() simulated count matrices to integer. Added unit tests to ensure this happens for this function.

* Updating documentation

* Fixing broken unit tests

* Moving dangling references to process.counts param

* Set integer storage.mode in processCounts()

* RcppEigen for fast matrix multiplication in celda_C EM

Use RcppEigen to do fast matrix multiplication in the newly implemented EM optimizations in celda_C.

* Fixed call to eigenMatMultInt. Added documentation.

* Rename rowsum functions. Documentation for eigenMatMultInt.

* Fixing loading of C++ function

* Adding fast implementation of rowSumsByGroup/colSumsByGroup.

* Removing .o and .dll files

* Ignore .o and .dll files

* Convert tests' simulated count matrices to integer.

* Regenerated test results.

* Fixing test data.


Former-commit-id: c6986abd6602f8b8f2bc7e762be655c942722103

Former-commit-id: d08ff9b141fa076374ba9fead13127f714f18be4