This function runs a given algorithm on a small random toy dataset, to check that the algorithm works correctly
gedCheck(method, ..., maxIter = 5L, verbose = 3L)
ged
.FALSE/TRUE
or a number).returns invisibly the result of running the algorithm,
which usually is an NMFfit
object.
gedCheck('deconf')
## Using ged algorithm: "deconf"
## NMF algorithm: 'deconf'
## NMF seeding method: rprop
## Algorithm version 'fast'
## Scaling Strategy - coef: yes | signatures: yes
## Iterations: 0/5Iterations: 1/5Iterations: 2/5Iterations: 3/5Iterations: 4/5Iterations: 5/5
## DONE (stopped at 5/5 iterations)
## # NMF computation exit status ... OK
## Timing:
## user system elapsed
## 0.376 0.000 0.376
## GED final wrap up ... OK
gedCheck('DSA', log=FALSE)
## Using ged algorithm: "DSA"
## NMF algorithm: 'qprog'
## NMF seeding method: none
## Estimating basis and mixture coefficients matrices from marker features [DSA]
## Using 15/15 markers to estimate cell proportions:
## CL_1 CL_2 CL_3
## 5 5 5
## Checking data scale ... NOTE [log]
## Converting data to linear scale ... SKIP
## Computing proportions using DSA method ... OK
## Estimating basis matrix from mixture coefficients [qprog]
## Building data range constraint matrices: 0.18 <= x <= 20.12
## Not using any marker constraints
## # NMF computation exit status ... OK
## Timing:
## user system elapsed
## 0.628 0.016 0.642
## GED final wrap up ... OK