[1 Image patch extraction](#1-image-patch-extraction)  
[2 Prediction](#2-prediction)  
[3 Heatmap stitching](#3-heatmap-stitching)  
[4 Retreiving run-time statistics for prediction](#4-Retreiving-run-time-statistics-for-prediction)  
[5 Retreiving wall-clock time statistics for extraction and grouping](#5-Retreiving-wall-clock-time-statistics-for-extraction-and-grouping)  


# 1 Image patch extraction
- Adjust configuration parameters in files *config_testing.txt*, *config_normal.txt* and *config_tumor.txt* located at the <a href="https://github.com/DIDSR/HPC_DPAI"> root </a> directory of the codes.
- Run the commands listed in the following subsections to launch Son of Grid Engine (SGE) jobs to extract, group patches in HDF5 files and create a lookup table for every HDF5 file. 
## 1.1 Extract and group
- qsub ./image_patch_extract/split_main.sh ./config_testing.txt  
-- *split_main.sh* in turn submits *split_grp.sh* which in turns runs *split_grp.py* in array job fashion. Every task in the array job processes one slide.
- qsub ./image_patch_extract/split_main.sh ./config_normal.txt  
- qsub ./image_patch_extract/split_main.sh ./config_tumor.txt  

The \*.sh files mentioned in this section are located under <a href="https://github.com/DIDSR/HPC_DPAI/tree/master/image_patch_extract">image_patch_extract</a> directory while the config_*.txt files are at the <a href="https://github.com/DIDSR/HPC_DPAI"> root </a> directory of the codes.
## 1.2 Create lookup tables
- bash ./image_patch_extract/create_lookup_grp.sh ./config_testing.txt  
- bash ./image_patch_extract/create_lookup_grp.sh ./config_normal.txt  
- bash ./image_patch_extract/create_lookup_grp.sh ./config_tumor.txt  

The lookup tables are created only once and used at [Prediction](#2-prediction) stage for launching array job tasks. These tasks are run in parallel and scalable manner - if there are not enough resourcs for running all tasks then they are queued up automatically and started as resources become available. Each task processes only one group. 

The \*.sh file mentioned in this section is located under <a href="https://github.com/DIDSR/HPC_DPAI/tree/master/image_patch_extract">image_patch_extract</a> directory while the config_*.txt files are located at the <a href="https://github.com/DIDSR/HPC_DPAI"> root </a> directory of the codes.

# 2 Prediction
- Additionally adjust configuration parameters in files, *config_testing_cn_true.txt*, *config_normal_cn_true.txt*, *config_tumor_cn_true.txt* located at at the <a href="https://github.com/DIDSR/HPC_DPAI"> root </a> directory of the codes.
- Run commands listed in the below subsections to launch SGE jobs to generate prediction matrices.

The \*.sh files mentioned in sections 2.1 and 2.2  below are located under <a href="https://github.com/DIDSR/HPC_DPAI/tree/master/prediction">prediction</a> directory while the config_*.txt files are at the <a href="https://github.com/DIDSR/HPC_DPAI"> root </a> directory of the codes.

## 2.1 With color normalization
- qsub ./prediction/process_main.sh ./config_testing_cn_true.txt  
-- *process_main.sh* in turn submits a number of SGE jobs using *process_array.sh* which in turn runs *process_images_grp_normalization_wli.py* in the array jobs generated for every slide. Number of tasks in an array job determined automatically based on the number of groups in the corresponding HDF5 file.
- qsub ./prediction/process_main.sh ./config_normal_cn_true.txt  
- qsub ./prediction/process_main.sh ./config_tumor_cn_true.txt  

## 2.2 Without color normalization 
- qsub ./prediction/process_main.sh ./config_testing.txt  
- qsub ./prediction/process_main.sh ./config_normal.txt  
- qsub ./prediction/process_main.sh ./config_tumor.txt  

# 3 Heatmap stitching
After the predictions matrices have been generated an SGE job using *heatmap_main.sh* SGE scrip could be launched to genertae heatmaps. Two arguments for this launch are: a) type of the slides (test, normal or tumor); b) the root directory of the results, like in below example run:  
- qsub ./heatmap_stitch/heatmap_main.sh test results_directory  
-- *heatmap_main.sh* in turn calls *heatmap_arr.sh* which runs *heatmap_assembly.py* for the heatmap stitching of all slides in parallel/scalable manner.

The files mentioned in this section are located under <a href="https://github.com/DIDSR/HPC_DPAI/tree/master/heatmap_stitch">heatmap_stitch</a> directory.

# 4 Retreiving run-time statistics for prediction
## 4.1 CPU time
In *time_all_stats_pred.sh* file adjust job results root directory, DIR and slides type, PREFIX (normal, test or tumor), like below:  
- DIR=results_directory  
- PREFIX=normal  
Then run:  
- time bash ./time_all_stats_pred.sh
## 4.2 Wall-Clock time
In *wall_clock_time_stats_pred.sh* file adjust job results root directory, DIR and slides type, PREFIX (normal, test or tumor), like below:  
- DIR=results_directory  
- PREFIX=test  
Then run:  
- time bash ./wall_clock_time_stats_pred.sh  

# 5 Retreiving wall-clock time statistics for extraction and grouping
Run *time_stats_sg_V2.sh* Linux scrip with two arguments: a) type of slides (test, normal or tumor) and b) the root directory of the results:
- time bash time_stats_sg_V2.sh [test | normal | tumor] DIR  

An example run:  
- time bash wall_clock_time_split_group_V2.sh test results_directory