CONFIG kommentare eingefügt

cami/AlgorithmWrapper.py

@@ -10,7 +10,7 @@ class AlgorithmWrapper(object):
     def __init__(self):
         self.uid = '0000'
         self.name = ''
-        self.weight = 1
+        self.weight = default_weight #CONFIG default_weight = 1
         self.output_dir = ''
         self.ppi_network = Graph()
         self.seeds = list()

cami/DiamondWrapper.py

@@ -26,7 +26,7 @@ class DiamondWrapper(AlgorithmWrapper):
 
         out_filename = self.name_file('out') # name the outputfile
         algo_output = f'{self.output_dir}/{out_filename}' # specify the output location
-        command = f'{diamond} {ppi} {seeds} {nof_predictions} 1 {algo_output}'
+        command = f'{diamond} {ppi} {seeds} {nof_predictions} {alpha} {algo_output}' #CONFIG alpha = 1
         subprocess.call(command, shell=True, stdout=subprocess.PIPE)
         print(f"DIAMOnD results saved in {algo_output}")
         return self.extract_output(algo_output)
@@ -63,7 +63,7 @@ class DiamondWrapper(AlgorithmWrapper):
 
         # do not predict too much when there are not enough seeds
         nof_seeds = len(self.seeds)
-        nof_preds = min([nof_seeds * 10, 200])
+        nof_preds = min([nof_seeds * pred_factor, max_preds]) #CONFIG pred_factor = 10, max_preds = 100
         print(f'With {nof_seeds} seeds, {self.name} will try to predict {nof_preds} active modules.')
         inputparams.append(nof_preds)
         return inputparams

cami/DominoWrapper.py

@@ -28,10 +28,10 @@ class DominoWrapper(AlgorithmWrapper):
 
         slices_file = inputparams[2]
         
-        command = f'domino -a {seeds} -n {ppi} -s {slices_file} -o {self.output_dir} -v false'
+        command = f'domino -a {seeds} -n {ppi} -s {slices_file} -o {self.output_dir} -v visualization_flag' #CONFIG: visualization_flag = False
         subprocess.call(command, shell=True, stdout=subprocess.PIPE)
         outputname = (os.path.basename(seeds)).rsplit(".")[0]
-        algo_output = f'{self.output_dir}/{outputname}/modules.out'
+        algo_output = f'{self.output_dir}/{outputname}/{output_name}' #CONFIG output_name = 'modules.out'
 
         outputfilename = self.name_file('out', 'out')
         command = f'mv {algo_output} {self.output_dir}/{outputfilename}'

cami/RobustWrapper.py

@@ -41,7 +41,7 @@ class RobustWrapper(AlgorithmWrapper):
         out_filename = self.name_file('out')
         algo_output = f'{self.output_dir}/{out_filename}'
         # algo_output = f'./ms.graphml'
-        command = f'{robust} {ppi} {seeds} {algo_output} 0.25 0.9 30 0.1'
+        command = f'{robust} {ppi} {seeds} {algo_output} 0.25 0.9 30 0.1' #CONFIG according to robust documentation https://github.com/bionetslab/robust
         subprocess.call(command, shell=True, stdout=subprocess.PIPE)
         print(f"Robust results saved in {algo_output}")
         return self.extract_output(algo_output)

cami/cami.py

@@ -46,7 +46,7 @@ def main(ppi_network, seeds, tools, tool_weights, consensus, evaluate,
 
     # set weights for seed genes in ppi_graph
     for seed in seed_lst:
-        ppi_graph.vertex_properties["cami_score"][seed] = 10.0
+        ppi_graph.vertex_properties["cami_score"][seed] = seed_score #CONFIG seed_score = 10.0
 
     # change directory to ~/cami/cami (home of cami.py)
     cami_home = sys.argv[0].rsplit('/', 1)

cami/example_run.py

@@ -9,5 +9,5 @@ chdir((sys.argv[0].rsplit('/', 1))[0])
 networkfile = "../data/input/networks/example_network.tsv"
 seedfile = "../data/input/seeds/example_seeds.txt"
 identifier = "example_run"
-command = f'./cami.py -n {networkfile} -s {seedfile}  -id {identifier} -img -d --f;'
+command = f'./cami.py -n {networkfile} -s {seedfile}  -id {identifier} -ncbi -img -d --f;'
 subprocess.call(command, shell=True)
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