ran python 2to3 tool on Python test scripts, OK

Updated example slurm jobs scripts to work on USI ICS cluster
git ignore example script output files

TestChangeStatsDirected/.gitignore

@@ -19,3 +19,4 @@ polblogs_test_results_arrays.out
 testChangeStatsDirected_array.exe
 testChangeStatsDirected_array
 polblogs_test_results_baseline_no2pathtables.txt
+*.bak

pythonDemo/.gitignore

@@ -2,3 +2,8 @@
 *~
 dzA_values_*.txt
 theta_values_*.txt
+theta_values_*.eps
+dzA_values_*.txt
+dzA_values_*.eps
+*.bak
+slurm-*.out

pythonDemo/Digraph.py

@@ -67,15 +67,15 @@ def __init__(self, pajek_edgelist_filename, binattr_filename=None,
         self.binattr = None # binary attributes: list by node (int not boolean)
         self.catattr = None # categorical attributes: list by node
 
-        print 'Reading graph and building matrices...',
+        print('Reading graph and building matrices...', end=' ')
         start = time.time()
         f =  open(pajek_edgelist_filename)
         l = f.readline() # first line must be e.g. "*vertices 500"
         n = int(l.split()[1])
 
         # empty graph n nodes        
-        self.G = dict(zip(range(n), [dict() for i in range(n)]))
-        self.Grev = dict(zip(range(n), [dict() for i in range(n)]))
+        self.G = dict(list(zip(list(range(n)), [dict() for i in range(n)])))
+        self.Grev = dict(list(zip(list(range(n)), [dict() for i in range(n)])))
         self.InTwoPathMatrix =  np.zeros((n, n))
         self.OutTwoPathMatrix = np.zeros((n, n))
         self.MixTwoPathMatrix = np.zeros((n, n))
@@ -84,20 +84,20 @@ def __init__(self, pajek_edgelist_filename, binattr_filename=None,
             l = f.readline()
         lsplit = f.readline().split()
         while len(lsplit) == 2:
-            (i, j) = map(int, lsplit)
+            (i, j) = list(map(int, lsplit))
             assert(i >= 1 and i <= n and j >= 1 and j <= n)
             self.insertArc(i-1, j-1)    # input is 1-based but we are 0-based
             lsplit = f.readline().split()
 
         if binattr_filename is not None:
-            self.binattr = map(int, open(binattr_filename).read().split()[1:]) 
+            self.binattr = list(map(int, open(binattr_filename).read().split()[1:])) 
             assert(len(self.binattr) == n)
 
         if catattr_filename is not None:
-            self.catattr = map(int, open(catattr_filename).read().split()[1:]) 
+            self.catattr = list(map(int, open(catattr_filename).read().split()[1:])) 
             assert(len(self.catattr) == n)
 
-        print time.time() - start, 's'
+        print(time.time() - start, 's')
 
 
     def numNodes(self):
@@ -110,7 +110,7 @@ def numArcs(self):
         """
         Return number of arcs in digraph
         """
-        return sum([len(v.keys()) for v in self.G.itervalues()])
+        return sum([len(list(v.keys())) for v in self.G.values()])
 
     def density(self):
         """
@@ -143,13 +143,13 @@ def outIterator(self, i):
         """
         Return iterator over out-neighbours of i
         """
-        return self.G[i].iterkeys()
+        return iter(self.G[i].keys())
 
     def inIterator(self, i):
         """
         Return iterator over in-neighbours of i
         """
-        return self.Grev[i].iterkeys()
+        return iter(self.Grev[i].keys())
 
     def insertArc(self, i, j):
         """
@@ -175,7 +175,7 @@ def updateTwoPathMatrices(self, i, j, isAdd):
         """
         incval = 1 if isAdd else -1
         n = self.numNodes()
-        for v in xrange(n):
+        for v in range(n):
             if v == i or v == j:
                 continue
             if self.isArc(i, v):

pythonDemo/EstimNetDirectedSimpleDemo.py

@@ -62,10 +62,10 @@ def BasicSampler(G, changestats_func_list, theta, performMove):
     accepted = 0
     addChangeStats = np.zeros(n)
     delChangeStats = np.zeros(n)
-    for k in xrange(sampler_m):
+    for k in range(sampler_m):
         # basic sampler: select two nodes i and j uniformly at random
         # and toggle edge between them
-        (i, j) = random.sample(range(G.numNodes()), 2) # without replacement
+        (i, j) = random.sample(list(range(G.numNodes())), 2) # without replacement
         assert(i != j)
         isDelete = (G.isArc(i, j))
         if isDelete:
@@ -74,7 +74,7 @@ def BasicSampler(G, changestats_func_list, theta, performMove):
         # compute change statistics for each of the n statistics using the
         # list of change statistic functions
         changestats = np.zeros(n)
-        for l in xrange(n):
+        for l in range(n):
             changestats[l] = changestats_func_list[l](G, i, j)
             assert(changestats[l] >= 0)
         changeSignMul = -1 if isDelete else +1
@@ -124,7 +124,7 @@ def algorithm_S(G, changestats_func_list, M1, theta_outfile):
     n = len(changestats_func_list)
     theta = np.zeros(n)
     D0 = np.zeros(n)
-    for t in xrange(M1):
+    for t in range(M1):
         accepted = 0
         (acceptance_rate,
          addChangeStats,
@@ -136,7 +136,7 @@ def algorithm_S(G, changestats_func_list, M1, theta_outfile):
         assert(np.all(sumChangeStats >= 0)) # zero is handled below
         D0 += dzA**2 # 1/D0 is squared derivative
         da = np.zeros(n)
-        for l in xrange(n):
+        for l in range(n):
             if (sumChangeStats[l] != 0):
                 da[l] = ACA  / sumChangeStats[l]**2
         theta_step = np.sign(dzAmean) * da * dzA**2
@@ -173,9 +173,9 @@ def algorithm_EE(G, changestats_func_list, theta, D0,
     n = len(changestats_func_list)
     dzA = np.zeros(n)  # zero outside loop, dzA accumulates in loop
     t = 0
-    for touter in xrange(Mouter):
+    for touter in range(Mouter):
         thetamatrix = np.empty((M, n)) # rows theta vectors, 1 per inner iter
-        for tinner in xrange(M):
+        for tinner in range(M):
             accepted = 0
             (acceptance_rate,
              addChangeStats,
@@ -240,27 +240,27 @@ def run_on_network_attr(edgelist_filename, param_func_list, labels,
     # inner steps of EE    
     M = int(Msteps * G.density()*(1 - G.density())*G.numNodes()**2 / sampler_m)
 
-    print 'M1 = ', M1, ' Mouter = ', Mouter, ' M = ', M
+    print('M1 = ', M1, ' Mouter = ', Mouter, ' M = ', M)
 
     theta_outfile = open(THETA_OUTFILENAME, 'w',1) # 1 means line buffering
     theta_outfile.write('t ' + ' '.join(labels) + ' ' + 'AcceptanceRate' + '\n')
-    print 'Running Algorithm S...',
+    print('Running Algorithm S...', end=' ')
     start = time.time()
     (theta, Dmean) = algorithm_S(G, param_func_list, M1, theta_outfile)
-    print time.time() - start, 's'
-    print 'after Algorithm S:'
-    print 'theta = ', theta
-    print 'Dmean = ', Dmean
+    print(time.time() - start, 's')
+    print('after Algorithm S:')
+    print('theta = ', theta)
+    print('Dmean = ', Dmean)
     dzA_outfile = open(DZA_OUTFILENAME, 'w',1)
     dzA_outfile.write('t ' + ' '.join(labels) + '\n')
-    print 'Running Algorithm EE...',
+    print('Running Algorithm EE...', end=' ')
     start = time.time()
     theta = algorithm_EE(G, param_func_list, theta, Dmean,
                          Mouter, M, theta_outfile, dzA_outfile)
-    print time.time() - start, 's'
+    print(time.time() - start, 's')
     theta_outfile.close()
     dzA_outfile.close()
-    print 'at end theta = ', theta
+    print('at end theta = ', theta)
 
 
 

pythonDemo/README

@@ -7,9 +7,6 @@ The only module (other than default pythone
 ones) it needs is numpy https://www.scipy.org/scipylib/download.html
 just for simple and efficient vector and matrix data types.
 
-Note python scripts all require Python 2 (and NOT Python 3,
-which is not backward compatibile with Python 2).
-
 sample_statistics_n500_directed_binattr_sim420000000.txt and
 binaryAttributes_50_50_n500.txt is a simulated 500 node network 
 with binary attribute, simulated from the following ERGM parameters using PNet:

pythonDemo/example_n1000_slurm_script.sh

@@ -6,10 +6,13 @@
 
 echo -n "started at: "; date
 
-module load numpy/1.8.2-vlsci_intel-2015.08.25-Python-2.7.9
-module load R/3.2.1-vlsci_intel-2015.08.25
 
-time python ./runExample_n1000.py
+module load python/3.8.5
+
+time python3 ./runExample_n1000.py
+
+module unload python # on cluster module load r will not work if this is not done
+module load r
 
 time Rscript plotEstimNetSimpleDemoResults.R theta_values_sample_statistics_n1000_directed_binattr_sim620000000.txt dzA_values_sample_statistics_n1000_directed_binattr_sim620000000.txt
 

pythonDemo/example_polblogs_slurm_script.sh

@@ -2,14 +2,16 @@
 
 #SBATCH --job-name="Py_EstimNetSimple"
 #SBATCH --ntasks=1
-#SBATCH --time=0-24:00:00
+#SBATCH --time=0-48:00:00
 
 echo -n "started at: "; date
 
-module load numpy/1.8.2-vlsci_intel-2015.08.25-Python-2.7.9
-module load R/3.2.1-vlsci_intel-2015.08.25
+module load python/3.8.5
 
-time python ./runExample_polblogs.py
+time python3 ./runExample_polblogs.py
+
+module unload python # on cluster module load r will not work if this is not done
+module load r
 
 time Rscript plotEstimNetSimpleDemoResults.R theta_values_polblogs_arclist.txt dzA_values_polblogs_arclist.txt
 

pythonDemo/example_slurm_script.sh

@@ -6,10 +6,12 @@
 
 echo -n "started at: "; date
 
-module load numpy/1.8.2-vlsci_intel-2015.08.25-Python-2.7.9
-module load R/3.2.1-vlsci_intel-2015.08.25
+module load python/3.8.5
 
-time python ./runExample.py
+time python3 ./runExample.py
+
+module unload python # on cluster module load r will not work if this is not done
+module load r
 
 time Rscript plotEstimNetSimpleDemoResults.R theta_values_sample_statistics_n500_directed_binattr_sim420000000.txt dzA_values_sample_statistics_n500_directed_binattr_sim420000000.txt