(remove some small docstring references to slurm)

flatironinstitute · Nov 21, 2023 · 2202528 · 2202528
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commit 2202528
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diff --git a/caiman/source_extraction/cnmf/map_reduce.py b/caiman/source_extraction/cnmf/map_reduce.py
@@ -41,7 +41,7 @@ def cnmf_patches(args_in):
                 number of global background components
 
             backend: string
-                'ipyparallel' or 'single_thread' or SLURM
+                'ipyparallel' or 'single_thread'
 
             n_processes: int
                 number of cores to be used (should be less than the number of cores started with ipyparallel)

diff --git a/caiman/source_extraction/cnmf/temporal.py b/caiman/source_extraction/cnmf/temporal.py
@@ -113,7 +113,6 @@ def update_temporal_components(Y, A, b, Cin, fin, bl=None, c1=None, g=None, sn=N
             ipyparallel, parallelization using the ipyparallel cluster.
             You should start the cluster (install ipyparallel and then type
             ipcluster -n 6, where 6 is the number of processes).
-            SLURM: using SLURM scheduler
 
         memory_efficient: Bool
             whether or not to optimize for memory usage (longer running times). necessary with very large datasets
@@ -287,7 +286,6 @@ def update_iteration(parrllcomp, len_parrllcomp, nb, C, S, bl, nr,
             ipyparallel, parallelization using the ipyparallel cluster.
             You should start the cluster (install ipyparallel and then type
             ipcluster -n 6, where 6 is the number of processes).
-            SLURM: using SLURM scheduler
 
         memory_efficient: Bool
             whether or not to optimize for memory usage (longer running times). necessary with very large datasets