diff --git a/wafo/dctpack.py b/wafo/dctpack.py
index 4640fbd..a8efe40 100644
--- a/wafo/dctpack.py
+++ b/wafo/dctpack.py
@@ -392,7 +392,7 @@ def test_dctn():
     print('xn = idctn(yn)')
     print(xn)
     print(' ')
-    print xn-a
+    print(xn-a)
 
 
 def test_dct2():
diff --git a/wafo/gaussian.py b/wafo/gaussian.py
index 6716148..a339494 100644
--- a/wafo/gaussian.py
+++ b/wafo/gaussian.py
@@ -1,3 +1,4 @@
+from __future__ import absolute_import
 from numpy import (r_, minimum, maximum, atleast_1d, atleast_2d, mod, ones,
                    floor, random, eye, nonzero, where, repeat, sqrt, exp, inf,
                    diag, zeros, sin, arcsin, nan)
@@ -6,7 +7,7 @@ from scipy.special import ndtr as cdfnorm, ndtri as invnorm
 from scipy.special import erfc
 import warnings
 import numpy as np
-from wafo.misc import common_shape
+from .misc import common_shape
 
 try:
     import mvn  # @UnresolvedImport
diff --git a/wafo/graphutil.py b/wafo/graphutil.py
index 9a7eba5..3f0a223 100644
--- a/wafo/graphutil.py
+++ b/wafo/graphutil.py
@@ -5,10 +5,10 @@ Created on 20. jan. 2011
 
 license BSD
 '''
-from __future__ import division
+from __future__ import absolute_import, division
 import warnings
 import numpy as np
-from wafo.plotbackend import plotbackend
+from .plotbackend import plotbackend
 from matplotlib import mlab
 __all__ = ['cltext', 'tallibing', 'test_docstrings']
 
diff --git a/wafo/integrate.py b/wafo/integrate.py
index 08aeae2..ce21a72 100644
--- a/wafo/integrate.py
+++ b/wafo/integrate.py
@@ -1,14 +1,14 @@
-from __future__ import division
+from __future__ import absolute_import, division
 import warnings
 import numpy as np
 from numpy import pi, sqrt, ones, zeros  # @UnresolvedImport
 from scipy import integrate as intg
 import scipy.special.orthogonal as ort
 from scipy import special as sp
-from wafo.plotbackend import plotbackend as plt
+from .plotbackend import plotbackend as plt
 from scipy.integrate import simps, trapz
-from wafo.demos import humps
-#from pychebfun import Chebfun
+from .demos import humps
+# from pychebfun import Chebfun
 
 _EPS = np.finfo(float).eps
 _POINTS_AND_WEIGHTS = {}
diff --git a/wafo/interpolate.py b/wafo/interpolate.py
index 37947be..c37da7a 100644
--- a/wafo/interpolate.py
+++ b/wafo/interpolate.py
@@ -1,5 +1,5 @@
 #!/usr/bin/env python
-from __future__ import division
+from __future__ import absolute_import, division
 import numpy as np
 import scipy.signal
 # import scipy.sparse.linalg  # @UnusedImport
@@ -7,7 +7,7 @@ import scipy.sparse as sparse
 from numpy import ones, zeros, prod, sin, diff, pi, inf, vstack, linspace
 from scipy.interpolate import PiecewisePolynomial, interp1d
 
-import polynomial as pl
+from . import polynomial as pl
 
 
 __all__ = [
diff --git a/wafo/kdetools.py b/wafo/kdetools.py
index 0d9cc06..19bbe6b 100644
--- a/wafo/kdetools.py
+++ b/wafo/kdetools.py
@@ -9,7 +9,7 @@
 # Licence:     LGPL
 # -------------------------------------------------------------------------
 #!/usr/bin/env python  # @IgnorePep8
-from __future__ import division
+from __future__ import absolute_import, division
 import copy
 import numpy as np
 import scipy
@@ -19,12 +19,12 @@ from scipy import interpolate, linalg, optimize, sparse, special, stats
 from scipy.special import gamma
 from numpy import pi, sqrt, atleast_2d, exp, newaxis  # @UnresolvedImport
 
-from wafo.misc import meshgrid, nextpow2, tranproc  # , trangood
-from wafo.containers import PlotData
-from wafo.dctpack import dct, dctn, idctn
-from wafo.plotbackend import plotbackend as plt
+from .misc import meshgrid, nextpow2, tranproc  # , trangood
+from .containers import PlotData
+from .dctpack import dct, dctn, idctn
+from .plotbackend import plotbackend as plt
 try:
-    from wafo import fig
+    from . import fig
 except ImportError:
     warnings.warn('fig import only supported on Windows')
 
diff --git a/wafo/misc.py b/wafo/misc.py
index 3c18c4d..238ead5 100644
--- a/wafo/misc.py
+++ b/wafo/misc.py
@@ -1,7 +1,7 @@
 '''
 Misc
 '''
-from __future__ import division
+from __future__ import absolute_import, division
 import collections
 import sys
 import fractions
@@ -20,7 +20,7 @@ from time import strftime, gmtime
 from .plotbackend import plotbackend
 from collections import OrderedDict
 try:
-    import c_library as clib  # @UnresolvedImport
+    from . import c_library as clib  # @UnresolvedImport
 except ImportError:
     warnings.warn('c_library not found. Check its compilation.')
     clib = None
diff --git a/wafo/objects.py b/wafo/objects.py
index fc6cb7f..232cd20 100644
--- a/wafo/objects.py
+++ b/wafo/objects.py
@@ -12,14 +12,15 @@
 # !/usr/bin/env python
 
 
-from __future__ import division
-from wafo.transform.core import TrData
-from wafo.transform.estimation import TransformEstimator
-from wafo.stats import distributions
-from wafo.misc import (nextpow2, findtp, findrfc, findtc, findcross,
+from __future__ import absolute_import, division
+from .transform.core import TrData
+from .transform.estimation import TransformEstimator
+from .stats import distributions
+from .misc import (nextpow2, findtp, findrfc, findtc, findcross,
                        ecross, JITImport, DotDict, gravity, findrfc_astm)
-from wafo.interpolate import stineman_interp
-from wafo.containers import PlotData
+from .interpolate import stineman_interp
+from .containers import PlotData
+from .plotbackend import plotbackend
 from scipy.integrate import trapz
 from scipy.signal import welch, lfilter
 from scipy.signal.windows import get_window  # @UnusedImport
@@ -35,12 +36,11 @@ from numpy import (inf, pi, zeros, ones, sqrt, where, log, exp, cos, sin,
                    cumsum, ravel, isnan, ceil, diff, array)
 from numpy.fft import fft  # @UnusedImport
 from numpy.random import randn
-import matplotlib
 from matplotlib.mlab import psd, detrend_mean
-from plotbackend import plotbackend
+
 
 floatinfo = finfo(float)
-matplotlib.interactive(True)
+
 _wafocov = JITImport('wafo.covariance')
 _wafocov_estimation = JITImport('wafo.covariance.estimation')
 _wafospec = JITImport('wafo.spectrum')
diff --git a/wafo/padua.py b/wafo/padua.py
index c5639db..69153c4 100644
--- a/wafo/padua.py
+++ b/wafo/padua.py
@@ -82,10 +82,10 @@ Contents.m              : Contents file for Matlab
 
 
 '''
-from __future__ import division
+from __future__ import absolute_import, division
 import numpy as np
 from numpy.fft import fft
-from wafo.dctpack import dct
+from .dctpack import dct
 # from scipy.fftpack.realtransforms import dct
 
 
diff --git a/wafo/polynomial.py b/wafo/polynomial.py
index bb35f82..9630d7d 100644
--- a/wafo/polynomial.py
+++ b/wafo/polynomial.py
@@ -17,9 +17,10 @@
 # Licence:     LGPL
 # -------------------------------------------------------------------------
 # !/usr/bin/env python
+from __future__ import absolute_import
 import warnings  # @UnusedImport
 from numpy.polynomial import polyutils as pu
-from plotbackend import plotbackend as plt
+from .plotbackend import plotbackend as plt
 import numpy as np
 from numpy import (zeros, asarray, newaxis, arange,
                    logical_or, any, pi, cos, round, diff, all, exp,
diff --git a/wafo/powerpoint.py b/wafo/powerpoint.py
index e012fce..cc742c1 100644
--- a/wafo/powerpoint.py
+++ b/wafo/powerpoint.py
@@ -30,11 +30,12 @@ Created on 15. des. 2009
 # MSO = win32com.client.gencache.EnsureModule(typelib_mso.clsid,
 #                        typelib_mso.lcid,
 #                              int(typelib_mso.major), int(typelib_mso.minor))
+from __future__ import absolute_import
 import os
 import warnings
 import win32com.client
-import MSO
-import MSPPT
+from . import MSO
+from . import MSPPT
 from PIL import Image  # @UnresolvedImport
 
 g = globals()
diff --git a/wafo/sg_filter.py b/wafo/sg_filter.py
index 5b1059e..28b9f60 100644
--- a/wafo/sg_filter.py
+++ b/wafo/sg_filter.py
@@ -1,4 +1,4 @@
-from __future__ import division
+from __future__ import absolute_import, division
 import numpy as np
 # from math import pow
 # from numpy import zeros,dot
@@ -6,13 +6,14 @@ from numpy import (pi, abs, size, convolve, linalg, concatenate, sqrt)
 from scipy.sparse import spdiags
 from scipy.sparse.linalg import spsolve, expm
 from scipy.signal import medfilt
-from wafo.dctpack import dctn, idctn
+from .dctpack import dctn, idctn
+from .plotbackend import plotbackend as plt
 import scipy.optimize as optimize
 from scipy.signal import _savitzky_golay
 from scipy.ndimage import convolve1d
 from scipy.ndimage.morphology import distance_transform_edt
 import warnings
-from wafo.plotbackend import plotbackend as plt
+
 
 __all__ = ['SavitzkyGolay', 'Kalman', 'HodrickPrescott', 'smoothn']
 
diff --git a/wafo/wafodata.py b/wafo/wafodata.py
deleted file mode 100644
index defde98..0000000
--- a/wafo/wafodata.py
+++ /dev/null
@@ -1,551 +0,0 @@
-import warnings
-from graphutil import cltext
-from plotbackend import plotbackend
-from time import gmtime, strftime
-import numpy as np
-from scipy.integrate.quadrature import cumtrapz  # @UnresolvedImport
-from scipy.interpolate import griddata
-from scipy import integrate
-
-__all__ = ['PlotData', 'AxisLabels']
-
-
-def empty_copy(obj):
-    class Empty(obj.__class__):
-
-        def __init__(self):
-            pass
-    newcopy = Empty()
-    newcopy.__class__ = obj.__class__
-    return newcopy
-
-
-def _set_seed(iseed):
-    if iseed is not None:
-        try:
-            np.random.set_state(iseed)
-        except:
-            np.random.seed(iseed)
-
-
-def now():
-    """Return current date and time as a string."""
-    return strftime("%a, %d %b %Y %H:%M:%S", gmtime())
-
-
-class PlotData(object):
-
-    """Container class for data objects in WAFO.
-
-    Member variables
-    ----------------
-    data : array_like
-    args : vector for 1D, list of vectors for 2D, 3D, ...
-    labels : AxisLabels
-    children : list of PlotData objects
-
-    Member methods
-    --------------
-    plot :
-    copy :
-
-
-    Example
-    -------
-    >>> import numpy as np
-    >>> x = np.arange(-2, 2, 0.2)
-
-    # Plot 2 objects in one call
-    >>> d2 = PlotData(np.sin(x), x, xlab='x', ylab='sin', title='sinus')
-    >>> h = d2.plot()
-
-    Plot with confidence interval
-    >>> d3 = PlotData(np.sin(x),x)
-    >>> d3.children = [PlotData(np.vstack([np.sin(x)*0.9, np.sin(x)*1.2]).T,x)]
-    >>> d3.plot_args_children=[':r']
-    >>> h = d3.plot()
-
-    See also
-    --------
-    specdata,
-    covdata
-
-    """
-
-    def __init__(self, data=None, args=None, *args2, **kwds):
-        self.data = data
-        self.args = args
-        self.date = now()
-        self.plotter = kwds.pop('plotter', None)
-        self.children = None
-        self.plot_args_children = kwds.pop('plot_args_children', [])
-        self.plot_kwds_children = kwds.pop('plot_kwds_children', {})
-        self.plot_args = kwds.pop('plot_args', [])
-        self.plot_kwds = kwds.pop('plot_kwds', {})
-
-        self.labels = AxisLabels(**kwds)
-        if not self.plotter:
-            self.setplotter(kwds.get('plotmethod', None))
-
-    def plot(self, *args, **kwds):
-        axis = kwds.pop('axis', None)
-        if axis is None:
-            axis = plotbackend.gca()
-        tmp = None
-        plotflag = kwds.get('plotflag', None)
-        if not plotflag and self.children is not None:
-            plotbackend.hold('on')
-            tmp = []
-            child_args = kwds.pop(
-                'plot_args_children', tuple(self.plot_args_children))
-            child_kwds = dict(self.plot_kwds_children).copy()
-            child_kwds.update(kwds.pop('plot_kwds_children', {}))
-            child_kwds['axis'] = axis
-            for child in self.children:
-                tmp1 = child.plot(*child_args, **child_kwds)
-                if tmp1 is not None:
-                    tmp.append(tmp1)
-            if len(tmp) == 0:
-                tmp = None
-        main_args = args if len(args) else tuple(self.plot_args)
-        main_kwds = dict(self.plot_kwds).copy()
-        main_kwds.update(kwds)
-        main_kwds['axis'] = axis
-        tmp2 = self.plotter.plot(self, *main_args, **main_kwds)
-        return tmp2, tmp
-
-    def eval_points(self, *args, **kwds):
-        '''
-        >>> x = np.linspace(0,5,20)
-        >>> d = PlotData(np.sin(x),x)
-        >>> xi = np.linspace(0,5,60)
-        >>> di = PlotData(d.eval_points(xi, method='cubic'),xi)
-        >>> h = d.plot('.')
-        >>> hi = di.plot()
-
-        '''
-        if isinstance(self.args, (list, tuple)):  # Multidimensional data
-            ndim = len(self.args)
-            if ndim < 2:
-                msg = '''Unable to determine plotter-type, because len(self.args)<2.
-                If the data is 1D, then self.args should be a vector!
-                If the data is 2D, then length(self.args) should be 2.
-                If the data is 3D, then length(self.args) should be 3.
-                Unless you fix this, the plot methods will not work!'''
-                warnings.warn(msg)
-            else:
-                return griddata(self.args, self.data.ravel(), *args, **kwds)
-        else:  # One dimensional data
-            return griddata((self.args,), self.data, *args, **kwds)
-
-    def integrate(self, a, b, **kwds):
-        '''
-        >>> x = np.linspace(0,5,60)
-        >>> d = PlotData(np.sin(x), x)
-        >>> d.integrate(0,np.pi/2)
-        0.99940054759302188
-
-        '''
-        method = kwds.pop('method', 'trapz')
-        fun = getattr(integrate, method)
-        if isinstance(self.args, (list, tuple)):  # Multidimensional data
-            ndim = len(self.args)
-            if ndim < 2:
-                msg = '''Unable to determine plotter-type, because len(self.args)<2.
-                If the data is 1D, then self.args should be a vector!
-                If the data is 2D, then length(self.args) should be 2.
-                If the data is 3D, then length(self.args) should be 3.
-                Unless you fix this, the plot methods will not work!'''
-                warnings.warn(msg)
-            else:
-                return griddata(self.args, self.data.ravel(), **kwds)
-        else:  # One dimensional data
-
-            x = self.args
-            ix = np.flatnonzero((a < x) & (x < b))
-            xi = np.hstack((a, x.take(ix), b))
-            fi = np.hstack(
-                (self.eval_points(a), self.data.take(ix), self.eval_points(b)))
-            return fun(fi, xi, **kwds)
-
-    def show(self):
-        self.plotter.show()
-
-    def copy(self):
-        newcopy = empty_copy(self)
-        newcopy.__dict__.update(self.__dict__)
-        return newcopy
-
-    def setplotter(self, plotmethod=None):
-        """Set plotter based on the data type data_1d, data_2d, data_3d or
-        data_nd."""
-        if isinstance(self.args, (list, tuple)):  # Multidimensional data
-            ndim = len(self.args)
-            if ndim < 2:
-                msg = '''Unable to determine plotter-type, because len(self.args)<2.
-                If the data is 1D, then self.args should be a vector!
-                If the data is 2D, then length(self.args) should be 2.
-                If the data is 3D, then length(self.args) should be 3.
-                Unless you fix this, the plot methods will not work!'''
-                warnings.warn(msg)
-            elif ndim == 2:
-                self.plotter = Plotter_2d(plotmethod)
-            else:
-                warnings.warn('Plotter method not implemented for ndim>2')
-
-        else:  # One dimensional data
-            self.plotter = Plotter_1d(plotmethod)
-
-
-class AxisLabels:
-
-    def __init__(self, title='', xlab='', ylab='', zlab='', **kwds):
-        self.title = title
-        self.xlab = xlab
-        self.ylab = ylab
-        self.zlab = zlab
-
-    def __repr__(self):
-        return self.__str__()
-
-    def __str__(self):
-        return '%s\n%s\n%s\n%s\n' % (self.title, self.xlab, self.ylab,
-                                     self.zlab)
-
-    def copy(self):
-        newcopy = empty_copy(self)
-        newcopy.__dict__.update(self.__dict__)
-        return newcopy
-
-    def labelfig(self, axis=None):
-        if axis is None:
-            axis = plotbackend.gca()
-        try:
-            h1 = axis.set_title(self.title)
-            h2 = axis.set_xlabel(self.xlab)
-            h3 = axis.set_ylabel(self.ylab)
-            # h4 = plotbackend.zlabel(self.zlab)
-            return h1, h2, h3
-        except:
-            pass
-
-
-class Plotter_1d(object):
-
-    """
-
-    Parameters
-    ----------
-    plotmethod : string
-        defining type of plot. Options are:
-        bar : bar plot with rectangles
-        barh : horizontal bar plot with rectangles
-        loglog : plot with log scaling on the *x* and *y* axis
-        semilogx :  plot with log scaling on the *x* axis
-        semilogy :  plot with log scaling on the *y* axis
-        plot : Plot lines and/or markers (default)
-        stem : Stem plot
-        step : stair-step plot
-        scatter : scatter plot
-    """
-
-    def __init__(self, plotmethod='plot'):
-        self.plotfun = None
-        if plotmethod is None:
-            plotmethod = 'plot'
-        self.plotmethod = plotmethod
-        self.plotbackend = plotbackend
-#        try:
-#            self.plotfun = getattr(plotbackend, plotmethod)
-#        except:
-#            pass
-
-    def show(self):
-        plotbackend.show()
-
-    def plot(self, wdata, *args, **kwds):
-        axis = kwds.pop('axis', None)
-        if axis is None:
-            axis = plotbackend.gca()
-        plotflag = kwds.pop('plotflag', False)
-        if plotflag:
-            h1 = self._plot(axis, plotflag, wdata, *args, **kwds)
-        else:
-            if isinstance(wdata.data, (list, tuple)):
-                vals = tuple(wdata.data)
-            else:
-                vals = (wdata.data,)
-            if isinstance(wdata.args, (list, tuple)):
-                args1 = tuple((wdata.args)) + vals + args
-            else:
-                args1 = tuple((wdata.args,)) + vals + args
-            plotfun = getattr(axis, self.plotmethod)
-            h1 = plotfun(*args1, **kwds)
-        h2 = wdata.labels.labelfig(axis)
-        return h1, h2
-
-    def _plot(self, axis, plotflag, wdata, *args, **kwds):
-        x = wdata.args
-        data = transformdata(x, wdata.data, plotflag)
-        dataCI = getattr(wdata, 'dataCI', ())
-        h1 = plot1d(axis, x, data, dataCI, plotflag, *args, **kwds)
-        return h1
-
-
-def plot1d(axis, args, data, dataCI, plotflag, *varargin, **kwds):
-
-    plottype = np.mod(plotflag, 10)
-    if plottype == 0:  # %  No plotting
-        return []
-    elif plottype == 1:
-        H = axis.plot(args, data, *varargin, **kwds)
-    elif plottype == 2:
-        H = axis.step(args, data, *varargin, **kwds)
-    elif plottype == 3:
-        H = axis.stem(args, data, *varargin, **kwds)
-    elif plottype == 4:
-        H = axis.errorbar(args, data,
-                          yerr=[dataCI[:, 0] - data, dataCI[:, 1] - data],
-                          *varargin, **kwds)
-    elif plottype == 5:
-        H = axis.bar(args, data, *varargin, **kwds)
-    elif plottype == 6:
-        level = 0
-        if np.isfinite(level):
-            H = axis.fill_between(args, data, level, *varargin, **kwds)
-        else:
-            H = axis.fill_between(args, data, *varargin, **kwds)
-    elif plottype == 7:
-        H = axis.plot(args, data, *varargin, **kwds)
-        H = axis.fill_between(
-            args, dataCI[:, 0], dataCI[:, 1], alpha=0.2, color='r')
-
-    scale = plotscale(plotflag)
-    logXscale = 'x' in scale
-    logYscale = 'y' in scale
-    logZscale = 'z' in scale
-
-    if logXscale:
-        axis.set(xscale='log')
-    if logYscale:
-        axis.set(yscale='log')
-    if logZscale:
-        axis.set(zscale='log')
-
-    transFlag = np.mod(plotflag // 10, 10)
-    logScale = logXscale or logYscale or logZscale
-    if logScale or (transFlag == 5 and not logScale):
-        ax = list(axis.axis())
-        fmax1 = data.max()
-        if transFlag == 5 and not logScale:
-            ax[3] = 11 * np.log10(fmax1)
-            ax[2] = ax[3] - 40
-        else:
-            ax[3] = 1.15 * fmax1
-            ax[2] = ax[3] * 1e-4
-
-        axis.axis(ax)
-
-    if np.any(dataCI) and plottype < 3:
-        axis.hold(True)
-        plot1d(axis, args, dataCI, (), plotflag, 'r--')
-    return H
-
-
-def plotscale(plotflag):
-    """Return plotscale from plotflag.
-
-     CALL scale = plotscale(plotflag)
-
-     plotflag = integer defining plotscale.
-       Let scaleId = floor(plotflag/100).
-       If scaleId < 8 then:
-          0 'linear' : Linear scale on all axes.
-          1 'xlog'   : Log scale on x-axis.
-          2 'ylog'   : Log scale on y-axis.
-          3 'xylog'  : Log scale on xy-axis.
-          4 'zlog'   : Log scale on z-axis.
-          5 'xzlog'  : Log scale on xz-axis.
-          6 'yzlog'  : Log scale on yz-axis.
-          7 'xyzlog' : Log scale on xyz-axis.
-      otherwise
-       if (mod(scaleId,10)>0)            : Log scale on x-axis.
-       if (mod(floor(scaleId/10),10)>0)  : Log scale on y-axis.
-       if (mod(floor(scaleId/100),10)>0) : Log scale on z-axis.
-
-     scale    = string defining plotscale valid options are:
-           'linear', 'xlog', 'ylog', 'xylog', 'zlog', 'xzlog',
-           'yzlog',  'xyzlog'
-
-    Example
-    >>> for id in range(100,701,100):
-    ...    plotscale(id)
-    'xlog'
-    'ylog'
-    'xylog'
-    'zlog'
-    'xzlog'
-    'yzlog'
-    'xyzlog'
-
-    >>> plotscale(200)
-    'ylog'
-    >>> plotscale(300)
-    'xylog'
-    >>> plotscale(300)
-    'xylog'
-
-    See also
-    --------
-    transformdata
-
-    """
-    scaleId = plotflag // 100
-    if scaleId > 7:
-        logXscaleId = np.mod(scaleId, 10) > 0
-        logYscaleId = (np.mod(scaleId // 10, 10) > 0) * 2
-        logZscaleId = (np.mod(scaleId // 100, 10) > 0) * 4
-        scaleId = logYscaleId + logXscaleId + logZscaleId
-
-    scales = ['linear', 'xlog', 'ylog', 'xylog',
-              'zlog', 'xzlog', 'yzlog', 'xyzlog']
-
-    return scales[scaleId]
-
-
-def transformdata(x, f, plotflag):
-    transFlag = np.mod(plotflag // 10, 10)
-    if transFlag == 0:
-        data = f
-    elif transFlag == 1:
-        data = 1 - f
-    elif transFlag == 2:
-        data = cumtrapz(f, x)
-    elif transFlag == 3:
-        data = 1 - cumtrapz(f, x)
-    if transFlag in (4, 5):
-        if transFlag == 4:
-            data = -np.log1p(-cumtrapz(f, x))
-        else:
-            if any(f < 0):
-                raise ValueError('Invalid plotflag: Data or dataCI is '
-                                 'negative, but must be positive')
-            data = 10 * np.log10(f)
-    return data
-
-
-class Plotter_2d(Plotter_1d):
-
-    """
-    Parameters
-    ----------
-    plotmethod : string
-        defining type of plot. Options are:
-        contour (default)
-        contourf
-        mesh
-        surf
-    """
-
-    def __init__(self, plotmethod='contour'):
-        if plotmethod is None:
-            plotmethod = 'contour'
-        super(Plotter_2d, self).__init__(plotmethod)
-
-    def _plot(self, axis, plotflag, wdata, *args, **kwds):
-        h1 = plot2d(axis, wdata, plotflag, *args, **kwds)
-        return h1
-
-
-def plot2d(axis, wdata, plotflag, *args, **kwds):
-    f = wdata
-    if isinstance(wdata.args, (list, tuple)):
-        args1 = tuple((wdata.args)) + (wdata.data,) + args
-    else:
-        args1 = tuple((wdata.args,)) + (wdata.data,) + args
-    if plotflag in (1, 6, 7, 8, 9):
-        isPL = False
-        # check if contour levels is submitted
-        if hasattr(f, 'clevels') and len(f.clevels) > 0:
-            CL = f.clevels
-            isPL = hasattr(f, 'plevels') and f.plevels is not None
-            if isPL:
-                PL = f.plevels  # levels defines quantile levels? 0=no 1=yes
-        else:
-            dmax = np.max(f.data)
-            dmin = np.min(f.data)
-            CL = dmax - (dmax - dmin) * \
-                (1 - np.r_[0.01, 0.025, 0.05, 0.1, 0.2, 0.4, 0.5, 0.75])
-        clvec = np.sort(CL)
-
-        if plotflag in [1, 8, 9]:
-            h = axis.contour(*args1, levels=CL, **kwds)
-        # else:
-        #  [cs hcs] = contour3(f.x{:},f.f,CL,sym);
-
-        if plotflag in (1, 6):
-            ncl = len(clvec)
-            if ncl > 12:
-                ncl = 12
-                warnings.warn(
-                    'Only the first 12 levels will be listed in table.')
-
-            clvals = PL[:ncl] if isPL else clvec[:ncl]
-            # print(contour level text)
-            unused_axcl = cltext(clvals, percent=isPL)
-        elif any(plotflag == [7, 9]):
-            axis.clabel(h)
-        else:
-            axis.clabel(h)
-    elif plotflag == 2:
-        h = axis.mesh(*args1, **kwds)
-    elif plotflag == 3:
-        # shading interp % flat, faceted       % surfc
-        h = axis.surf(*args1, **kwds)
-    elif plotflag == 4:
-        h = axis.waterfall(*args1, **kwds)
-    elif plotflag == 5:
-        h = axis.pcolor(*args1, **kwds)  # %shading interp % flat, faceted
-    elif plotflag == 10:
-        h = axis.contourf(*args1, **kwds)
-        axis.clabel(h)
-        plotbackend.colorbar(h)
-    else:
-        raise ValueError('unknown option for plotflag')
-    # if any(plotflag==(2:5))
-    #   shading(shad);
-    # end
-    #    pass
-
-
-def test_eval_points():
-    plotbackend.ioff()
-    x = np.linspace(0, 5, 21)
-    d = PlotData(np.sin(x), x)
-    xi = np.linspace(0, 5, 61)
-    di = PlotData(d.eval_points(xi, method='cubic'), xi)
-    d.plot('.')
-    di.plot()
-    di.show()
-
-
-def test_integrate():
-    x = np.linspace(0, 5, 60)
-    d = PlotData(np.sin(x), x)
-    print(d.integrate(0, np.pi / 2, method='simps'))
-
-
-def test_docstrings():
-    import doctest
-    doctest.testmod()
-
-
-def main():
-    pass
-
-if __name__ == '__main__':
-
-    # test_integrate()
-    # test_eval_points()
-    test_docstrings()
-    # main()