Rename ncpu parameter to cpu for consistency across SigProfiler tools

Author: mdbarnesUCSD

SigProfilerAssignment/Analyzer.py

@@ -24,7 +24,7 @@ def decompose_fit(
     export_probabilities=True,
     export_probabilities_per_mutation=False,
     volume=None,
-    ncpu=-1,
+    cpu=-1,
 ):
     decomp.spa_analyze(
         samples=samples,
@@ -52,7 +52,7 @@ def decompose_fit(
         export_probabilities=export_probabilities,
         export_probabilities_per_mutation=export_probabilities_per_mutation,
         volume=volume,
-        ncpu=ncpu,
+        cpu=cpu,
     )
 
 
@@ -78,7 +78,7 @@ def denovo_fit(
     export_probabilities=True,
     export_probabilities_per_mutation=False,
     volume=None,
-    ncpu=-1,
+    cpu=-1,
 ):
     decomp.spa_analyze(
         samples=samples,
@@ -105,7 +105,7 @@ def denovo_fit(
         export_probabilities=export_probabilities,
         export_probabilities_per_mutation=export_probabilities_per_mutation,
         volume=volume,
-        ncpu=ncpu,
+        cpu=cpu,
     )
 
 
@@ -132,7 +132,7 @@ def cosmic_fit(
     export_probabilities_per_mutation=False,
     sample_reconstruction_plots=False,
     volume=None,
-    ncpu=-1,
+    cpu=-1,
 ):
     decomp.spa_analyze(
         samples=samples,
@@ -160,5 +160,5 @@ def cosmic_fit(
         export_probabilities_per_mutation=export_probabilities_per_mutation,
         sample_reconstruction_plots=sample_reconstruction_plots,
         volume=volume,
-        ncpu=ncpu
+        cpu=cpu
     )

SigProfilerAssignment/decompose_subroutines.py

@@ -1836,7 +1836,7 @@ def make_final_solution(
     denovo_refit_option=True,
     exome=False,
     volume=None,
-    ncpu = -1
+    cpu = -1
 ):
     if processAvg.shape[0] == allgenomes.shape[0] and processAvg.shape[0] != 96:
         collapse_to_SBS96 = False
@@ -1925,10 +1925,10 @@ def make_final_solution(
     # Passing inputs as a single argument and unpacking in the process_sample function
         # with tqdm(total=len(inputs)) as progress_bar:
     n_samples = allgenomes.shape[1]
-    if ncpu == -1:
+    if cpu == -1:
         njobs=min(cpu_count(), allgenomes.shape[1])
     else:
-        njobs=min(ncpu, allgenomes.shape[1])
+        njobs=min(cpu, allgenomes.shape[1])
     # njobs=64
     # batchs= n_samples // njobs
     results = Parallel(n_jobs=njobs,mmap_mode='r',verbose=5,batch_size="auto")(delayed(process_sample)(input) for input in inputs)

SigProfilerAssignment/decomposition.py

@@ -261,7 +261,7 @@ def spa_analyze(
     sample_reconstruction_plots=None,
     make_metadata=True,
     volume=None,
-    ncpu=-1,
+    cpu=-1,
 ):
     """
     Decomposes the De Novo Signatures into COSMIC Signatures and assigns COSMIC signatures into samples.
@@ -686,7 +686,7 @@ def spa_analyze(
                 denovo_refit_option=denovo_refit_option,
                 exome=exome,
                 volume=volume,
-                ncpu =  -1,
+                cpu =  -1,
             )
 
         else:
@@ -695,7 +695,7 @@ def spa_analyze(
             signature_stats = devopts["signature_stats"]
             sequence = devopts["sequence"]
             processSTE = devopts["processSTE"]
-            ncpu_extractor = devopts["ncpu"]
+            cpu_extractor = devopts["cpu"]
 
             exposureAvg = sub.make_final_solution(
                 processAvg,
@@ -727,7 +727,7 @@ def spa_analyze(
                 denovo_refit_option=denovo_refit_option,
                 exome=exome,
                 volume=volume,
-                ncpu =  ncpu_extractor,
+                cpu =  cpu_extractor,
             )
 
         if make_metadata:
@@ -904,7 +904,7 @@ def spa_analyze(
             denovo_refit_option=denovo_refit_option,
             exome=exome,
             volume=volume,
-            ncpu=ncpu
+            cpu=cpu
         )
 
         if make_metadata:
@@ -1069,7 +1069,7 @@ def spa_analyze(
             denovo_refit_option=denovo_refit_option,
             exome=exome,
             volume=volume,
-            ncpu=ncpu,
+            cpu=cpu,
         )
         if make_metadata:
             with open(os.path.join(output, "JOB_METADATA_SPA.txt"), "a") as sysdata: