--- a/lib/python/cc/spearman.py	Fri Nov 24 19:52:14 2023 +0000
+++ b/lib/python/cc/spearman.py	Fri Nov 24 19:52:52 2023 +0000
@@ -151,11 +151,11 @@
                     x_mean_ranked[i],
                     fd_ranked[i]] for i in range(N)])
 
-def main():
-  global counts, id, corr, ALL, all_s, all_m, x, xd, xs, xm, xsd, x_ranks, rr
+def main(file,id):
+  # this should be a class with all these globals as instance vars
+  global counts, corr, ALL, all_s, all_m, x, xd, xs, xm, xsd, x_ranks, rr
   global aa, aa_by_all, N
-  counts=loadtxt(sys.argv[1]+".csv",delimiter=',')
-  id=sys.argv[2]
+  counts=loadtxt(file+".csv",delimiter=',')
   N=counts.shape[1]-1
   # "If axis=0 (default), then each column represents a variable, with
   #        observations in the rows"
@@ -181,6 +181,10 @@
   aa=ranks()
   aa_by_all=aa[aa[:,1].argsort()]
 
+if __name__ == '__main__':
+  sys.exit(main(*sys.argv[1:]))
+
+
 ### I need to review rows, e.g. counts[0] is an array of N+1 counts
 ###   for the most common label in the complete crawl,
 ###   from the complete crawl and ALL the segments