Made code python 3 compatible:

Replaced round with numpy.round
replaced map with list-comprehension

wafo/misc.py

@@ -1802,7 +1802,7 @@ def common_shape(*args, ** kwds):
     --------
     broadcast, broadcast_arrays
     '''
-    args = map(asarray, args)
+    args = [asarray(x) for x in args]
     shapes = [x.shape for x in args]
     shape = kwds.get('shape')
     if shape is not None:
@@ -1947,7 +1947,7 @@ def stirlerr(n):
 
 
 def getshipchar(value=None, property="max_deadweight",  # @ReservedAssignment
-                ** kwds):  # @IgnorePep8
+                **kwds):  # @IgnorePep8
     '''
     Return ship characteristics from value of one ship-property
 
@@ -2026,23 +2026,23 @@ def getshipchar(value=None, property="max_deadweight",  # @ReservedAssignment
     max_deadweight = prop2max_dw.get(prop, lambda x: x)(value)
     propertySTD = prop + 'STD'
 
-    length = round(3.45 * max_deadweight ** 0.40)
+    length = np.round(3.45 * max_deadweight ** 0.40)
     length_err = length ** 0.13
 
-    beam = round(1.78 * max_deadweight ** 0.27 * 10) / 10
+    beam = np.round(1.78 * max_deadweight ** 0.27 * 10) / 10
     beam_err = beam * 0.10
 
-    draught = round(0.80 * max_deadweight ** 0.24 * 10) / 10
+    draught = np.round(0.80 * max_deadweight ** 0.24 * 10) / 10
     draught_err = draught * 0.22
 
     # S    = round(2/3*(L)**0.525)
-    speed = round(1.14 * max_deadweight ** 0.21 * 10) / 10
+    speed = np.round(1.14 * max_deadweight ** 0.21 * 10) / 10
     speed_err = speed * 0.10
 
     p_diam = 0.12 * length ** (3.0 / 4.0)
     p_diam_err = 0.12 * length_err ** (3.0 / 4.0)
 
-    max_deadweight = round(max_deadweight)
+    max_deadweight = np.round(max_deadweight)
     max_deadweightSTD = 0.1 * max_deadweight
 
     shipchar = OrderedDict(beam=beam, beamSTD=beam_err,

wafo/spectrum/core.py

@@ -1055,7 +1055,7 @@ class SpecData1D(PlotData):
         maxS = max(S.data)
         # Fs = 2*freq(end)+eps  # sampling frequency
 
-        for ix in xrange(max_sim):
+        for ix in range(max_sim):
             x2, x1 = self.sim_nl(ns=np, cases=cases, dt=None, iseed=iseed,
                                  method=method, fnlimit=fn_limit,
                                  output='timeseries')
@@ -1371,7 +1371,7 @@ class SpecData1D(PlotData):
         rind = Rind(**opts)
         # h11 = fwaitbar(0,[],sprintf('Please wait ...(start at: %s)',
         #        datestr(now)))
-        for pt in xrange(Nstart, Ntime):
+        for pt in range(Nstart, Ntime):
             Nt = pt - Nd + 1
             Ntd = Nt + Nd
             Ntdc = Ntd + Nc
@@ -3545,8 +3545,7 @@ class SpecData1D(PlotData):
         m, unused_mtxt = self.moment(nr=4, even=False)
 
         fact_dict = dict(alpha=0, eps2=1, eps4=3, qp=3, Qp=3)
-        fact = atleast_1d(map(lambda fact: fact_dict.get(fact, fact),
-                              list(factors)))
+        fact = atleast_1d(fact_dict.get(fact, fact) for fact in list(factors))
 
         # fact = atleast_1d(fact)
         alpha = m[2] / sqrt(m[0] * m[4])

wafo/stats/estimation.py

@@ -147,10 +147,10 @@ class Profile(object):
         self.xlabel = ''
         self.ylabel = 'Profile log'
         (self.i_fixed, self.N, self.alpha, self.pmin, self.pmax, self.x,
-         self.logSF, self.link) = map(
-            kwds.get,
+         self.logSF, self.link) = [kwds.get(name, val)
+                                   for name, val in zip(
             ['i', 'N', 'alpha', 'pmin', 'pmax', 'x', 'logSF', 'link'],
-            [i0, 100, 0.05, None, None, None, None, None])
+            [i0, 100, 0.05, None, None, None, None, None])]
 
         self.title = '%g%s CI' % (100 * (1.0 - self.alpha), '%')
         if fit_dist.method.startswith('ml'):