[Biomod-commits] Cannot find rasters for different rules of ensembleForecasting

Josep M Serra diaz pep.bioalerts at gmail.com
Fri Mar 1 16:06:46 CET 2013


Dear Damien,

sorry I did not explain myself, ...the main thing is that this object does
not exist after running biomod2, and if I try the example step by step,
this object is not created either....


> ls()

 [1] "myBiomodData"       "myBiomodEF"         "myBiomodEM"
"myBiomodModelEval"  "myBiomodModelOut"   "myBiomodOption"
"myBiomomodProj"
 [8] "myBiomomodProj2050" "myCurrentProj"      "myExpl"
"myExpl2050"         "myResp"             "myResp.ras"
"myRespName"
[15] "myRespXY"


> list.files(path='~/Myocastor/proj_t2050')

 [1] "proj_t2050_ClampingMask.grd"
"proj_t2050_ClampingMask.gri"
"proj_t2050_Myocastor_PA1_Full_AllAlgos_EMbyTSS.grd"
 [4] "proj_t2050_Myocastor_PA1_Full_AllAlgos_EMbyTSS.gri"
"proj_t2050_Myocastor_PA1_RUN1_AllAlgos_EMbyTSS.grd"
"proj_t2050_Myocastor_PA1_RUN1_AllAlgos_EMbyTSS.gri"
 [7] "proj_t2050_Myocastor_PA2_Full_AllAlgos_EMbyTSS.grd"
"proj_t2050_Myocastor_PA2_Full_AllAlgos_EMbyTSS.gri"
"proj_t2050_Myocastor_PA2_RUN1_AllAlgos_EMbyTSS.grd"
[10] "proj_t2050_Myocastor_PA2_RUN1_AllAlgos_EMbyTSS.gri"
"proj_t2050_Myocastor_ROCbin.grd"
"proj_t2050_Myocastor_ROCbin.gri"
[13] "proj_t2050_Myocastor.grd"
"proj_t2050_Myocastor.gri"



Therefore:

load("Myocastor/proj_t2050/Myocastor_PA1_AllRun_EM.TSS")
Error in readChar(con, 5L, useBytes = TRUE) : cannot open the connection
In addition: Warning message:
In readChar(con, 5L, useBytes = TRUE) :
  cannot open compressed file
'Myocastor/proj_t2050/Myocastor_PA1_AllRun_EM.TSS', probable reason 'No
such file or directory'






######### do not know if this helps

> sessionInfo()
R version 2.15.2 (2012-10-26)
Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit)

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] splines   stats     graphics  grDevices utils     datasets  methods
base

other attached packages:
 [1] mgcv_1.7-22        randomForest_4.6-7 mda_0.4-2
class_7.3-5        gbm_2.0-8          lattice_0.20-13    survival_2.37-2
MASS_7.3-23
 [9] rpart_4.1-0        nnet_7.3-5         rgdal_0.8-5
biomod2_2.0.0      raster_2.0-41      sp_1.0-5           abind_1.4-0

loaded via a namespace (and not attached):
[1] grid_2.15.2   Matrix_1.0-11 nlme_3.1-108


2013/3/1 Damien Georges <damien.georges2 at gmail.com>

> Dear Josep,
>
>
>
> On 01/03/2013 15:28, Josep M Serra diaz wrote:
>
>> Dear BIOMODers,
>>
>> I have been running bimod2 for my first time (great vignettes, by the way)
>> and I am struggling to find the rasters/rasterStack that shows different
>> ensembleForecasting according to different assembly rules  (e.g. em.cv,
>> em.mean, etc.). So I ended up running the script of the example to check
>> whether I was confused or I did something wrong.
>>
>> ...and I found that after running the whole example, I cannot load either
>> this rasterStack.
>>
>> I mean this part of the code:
>>
>>
>> ##############################**#####################
>> ### code chunk number 19: EnsembleForecasting_loading_**res
>> ##############################**#####################
>> load("Myocastor/proj_t2050/**Myocastor_PA1_AllRun_EM.TSS")
>> Myocastor_PA1_AllRun_EM.TSS
>>
>>
>> ##############################**#####################
>> ### code chunk number 20: EnsembleForecasting_plotting_**res
>> ##############################**#####################
>> plot(Myocastor_PA1_AllRun_EM.**TSS)
>>
>>
>>
>> QUESTIONS:
>> 1. Where can I find these different ensembles projections?
>>
> Ensemble-projections are within the object you just loaded. It's a
> multidimentional object, here a rasterStack where each layer is one
> ensemble model (e.g. mean, cv,...). You can know which is what with layer
> names :
>
> names(Myocastor_PA1_AllRun_EM.**TSS)
>
>
>  2. The assembly rule (the way the ensemble is done; mean/median/committee)
>> does not interfere with 'em.by' value in BIOMOD_EnsembleModeling()
>> function. Is that correct? I mean, we can always ask to ensamble using the
>> median of the predictions, or committee, but across different subsets (PA,
>> PA+algo, all, etc.)
>>
> Exactly !
>
>
> Cheers,
>
> Damien
>
>
>> Thanks,
>>
>> pep
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>>
>
>


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