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Revision 4aef71fa

Added by Benoit Parmentier over 9 years ago

adding barplot of predicted days for Africa 1992 assessment

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climate/research/oregon/interpolation/presentation_global_run_scalingup_assessment.Rmd
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knit        : slidify::knit2slides
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---
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```{r,echo=F}


  		




  
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```{r,echo=FALSE}


  		




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#First let's set up the input parameters for the script in R:


  		




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in_dir <- "/data/project/layers/commons/NEX_data/output_run10_1500x4500_global_analyses_pred_1992_09012015"


  		




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#region_name <- "world" #PARAM 13 #reg4 South America, Africa reg5,Europe reg2, North America reg1, Asia reg3


  		




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#mosaicing_method <- c("unweighted","use_edge_weights")


  		




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out_suffix <- paste(region_name,"_","pred_1992_09032015",sep="") 


  		




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#_mosaic_run10_1500x4500_global_analyses_06212015


  		




  
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#region_name <- "reg4" #PARAM 13 #reg4 South America, Africa reg5,Europe reg2, North America reg1, Asia reg3


  		




  
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#out_suffix <- paste(region_name,"_","pred_1992_09032015",sep="") 


  		




  
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out_suffix <- "pred_1992_09032015"


  		




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#day_to_mosaic <- c("20100831",


  		




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#                   "20100901") #PARAM7


  		




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## Tiles of 1500x4500 km


  		




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There were 43 tiles for region 4 (Africa)


  		




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1. Tiles were run for 365 days.


  		




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2. Year tested was 1992.


  		




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3. Assessment of number of days predicted and accuracy was carried out.


  		




  
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3. Assessments for the number of days predicted and accuracy were carried out.


  		




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--- .class #id 


  		




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</style>


  		




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# Tiles of 1500x4500km global run 


  		




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```{r, echo=FALSE}


  		




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```


  		




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```{r image_file1, echo = F, results = 'asis'}


  		




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#| I am text to the left  | ![Flowers](/flowers.jpeg) |


  		




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#md_str <- paste('\n|        |![](',image_file1,')\n',sep="") 


  		




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#md_str <- paste('\n->![alt text](',image_file1,'),<-\n',sep="")


  		




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#<center>![Alt test](http://upload.wikimedia.org/wikipedia/en/b/bc/Wiki.png)</center>


  		




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md_str <- paste('\n<center>![](',image_file1,')<center>\n',sep="")


  		




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#md_str <- paste('\n![](',image_file1,'#center)\n',sep="")


  		




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#fig.align = "center"


  		




  
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cat(md_str)


  		




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```


  		




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# ACCUARY PER TILES FOR MODEL 1


  		




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```{r, echo=FALSE}


  		




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#image_file2 <- file.path(in_dir,"Figure9_clim_mosaics_day_test_edge_weighted_20100831_world_mosaic_07092015.png")


  		




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fname <- paste("Figure2a_boxplot_with_oultiers_by_tiles_mod1_run10_1500x4500_global_analyses_pred_1992_09012015.png")


  		




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image_file2 <- file.path(in_dir,fname)


  		




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```


  		




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```{r image_file2, echo = F, results = 'asis', fig.show = 'hold', out.width = '50%',out.extra='style=""'}


  		




  
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```{r image_file2, image_file3 , echo = F, results = 'asis', fig.show = 'hold', out.width = '50%',out.extra='style=""'}


  		




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md_str <- paste('\n![](',image_file2,') ','![](',image_file3,')\n',sep="") 


  		




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cat(md_str)


  		




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#md_str <- paste('\n![](',image_file2,')\n',sep="") 


  		




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#cat(md_str)


  		




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#![alt-text-1](image1.png "title-1") ![alt-text-2](image2.png "title-2")


  		




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---


  		




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# Predicted less than 367


  		




  
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# Predicted tiles for 1992


  		




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```{r, echo=FALSE}


  		




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#image_file1 <- file.path(in_dir,"Figure9_clim_mosaics_day_test_unweighted_20100831_world_mosaic_07092015")


  		




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---


  		




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# Predicted less than 365


  		




  
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# Predicted less than 365, at least one missing day


  		




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```{r, echo=FALSE}


  		




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#image_file1 <- file.path(in_dir,"Figure9_clim_mosaics_day_test_unweighted_20100831_world_mosaic_07092015")


  		




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#md_str <- paste('\n![](',image_file1,'#center)\n',sep="")


  		




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#fig.align = "center"


  		




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cat(md_str)


  		




  
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```


  		




  
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---


  		




  
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---


  		




  
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# Missing days


  		




  
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```{r echo = F}


  		




  
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#tb <- read.table(file=file.path(out_dir,paste("tb_diagnostic_v_NA","_",out_suffix,".txt",sep="")),sep=",")


  		




  
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tb <- read.table(file.path("/data/project/layers/commons/NEX_data/output_run10_1500x4500_global_analyses_pred_1992_09012015","tb_diagnostic_v_NA_run10_1500x4500_global_analyses_pred_1992_09012015.txt"),sep=",")


  		




  
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#table(tb$pred_mod)


  		




  
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#table(tb$index_d)


  		




  
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#table(subset(tb,pred_mod!="mod_kr"))


  		




  
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#table(subset(tb,pred_mod=="mod1")$index_d)


  		




  
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#aggregate()


  		




  
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tb$predicted <- 1


  		




  
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test <- aggregate(predicted~pred_mod+tile_id,data=tb,sum)


  		




  
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#as.character(unique(test$tile_id)) #141 tiles


  		




  
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#dim(subset(test,test$predicted==365 & test$pred_mod=="mod1"))


  		




  
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#histogram(subset(test, test$pred_mod=="mod1")$predicted)


  		




  
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#unique(subset(test, test$pred_mod=="mod1")$predicted)


  		




  
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summary_predicted <-table((subset(test, test$pred_mod=="mod1")$predicted))


  		




  
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```


  		




  
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```{r summary_predicted, echo = F}


  		




  
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barplot(summary_predicted,main="Frequency of number of days predicted")


  		




  
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print(summary_predicted)


  		




  
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```


  		




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---


  		












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