--- a/pmat.py	Wed May 07 12:19:36 2008 -0400
+++ b/pmat.py	Wed May 07 13:07:33 2008 -0400
@@ -76,6 +76,31 @@
         X.byteswap(True)
     return X
 
+def load_pmat_as_array_dataset(fname):
+    import dataset,lookup_list
+    
+    #load the pmat as array
+    a=load_pmat_as_array(fname)
+    
+    #load the fieldnames
+    fieldnames = []
+    fieldnamefile = os.path.join(fname+'.metadata','fieldnames')
+    if os.path.isfile(fieldnamefile):
+        f = open(fieldnamefile)
+        for row in f:
+            row = row.split()
+            if len(row)>0:
+                fieldnames.append(row[0])
+        f.close()
+    else:
+        self.fieldnames = [ "field_"+str(i) for i in range(a.shape[1]) ]
+
+    return dataset.ArrayDataSet(a,lookup_list.LookupList(fieldnames,[x for x in range(a.shape[1])]))
+
+def save_array_dataset_as_pmat(fname,ds):
+    ar=ds.data
+    save_array_as_pmat(fname,ar,ds.fieldNames())
+
 def save_array_as_pmat( fname, ar, fieldnames=[] ):
     s = file(fname,'wb')
     
@@ -423,12 +448,23 @@
     pmat.close()
 
     pmat = PMat( 'tmp.pmat', 'r' )
-    print pmat
-    print pmat[:]
+    ar=load_pmat_as_array('tmp.pmat')
+    ds=load_pmat_as_array_dataset('tmp.pmat')
+    
+    print "PMat",pmat
+    print "PMat",pmat[:]
+    print "array",ar
+    print "ArrayDataSet",ds
+    for i in ds:
+        print i
+    save_array_dataset_as_pmat("tmp2.pmat",ds)
+    ds2=load_pmat_as_array_dataset('tmp2.pmat')
+    for i in ds2:
+        print i
     # print "+++ tmp.pmat contains: "
     # os.system( 'plearn vmat cat tmp.pmat' )
-
-    os.remove( 'tmp.pmat' )
-    if os.path.exists( 'tmp.pmat.metadata' ):
-        import shutil
-        shutil.rmtree( 'tmp.pmat.metadata' )
+    import shutil
+    for fname in ["tmp.pmat", "tmp2.pmat"]:
+        os.remove( fname )
+        if os.path.exists( fname+'.metadata' ):
+            shutil.rmtree( fname+'.metadata' )