pep8 + build extensions for windows

pywafo/src/wafo/dctpack.py

@@ -1,5 +1,5 @@
 import numpy as np
-from scipy.fftpack import _fftpack
+# from scipy.fftpack import _fftpack
 from scipy.fftpack import dct as _dct
 from scipy.fftpack import idct as _idct
 import os
@@ -127,7 +127,7 @@ def dct(x, type=2, n=None, axis=-1, norm='ortho'):  # @ReservedAssignment
         # Hack until scipy.fftpack.dct implement this functionality
         x = _truncate_or_zero_pad(x, n, axis)
         n = None
-    return _dct(x, type, n, axis, norm)
+    # return _dct(x, type, n, axis, norm)
     dtype = np.result_type(np.float32, np.asarray(x))
     x0 = np.asarray(x, dtype=dtype)
     if dtype == complex:
@@ -137,21 +137,21 @@ def dct(x, type=2, n=None, axis=-1, norm='ortho'):  # @ReservedAssignment
         return _dct(x0, type, n, axis, norm)
 
 
-def test(type=2, dtype=None, normalize='ortho'):  # @ReservedAssignment
-    dtype = np.result_type(np.float64)
-    try:
-        nm = {None: 0, 'ortho': 1}[normalize]
-    except KeyError:
-        raise ValueError("Unknown normalize mode %s" % normalize)
-    try:
-        name = {'float64': 'ddct%d', 'float32': 'dct%d'}[dtype.name]
-    except KeyError:
-        raise ValueError("dtype %s not supported" % dtype)
-    try:
-        f = getattr(_fftpack, name % type)
-    except AttributeError as e:
-        raise ValueError(str(e) + ". Type %d not understood" % type)
-    return f, nm
+# def test(type=2, dtype=None, normalize='ortho'):  # @ReservedAssignment
+#     dtype = np.result_type(np.float64)
+#     try:
+#         nm = {None: 0, 'ortho': 1}[normalize]
+#     except KeyError:
+#         raise ValueError("Unknown normalize mode %s" % normalize)
+#     try:
+#         name = {'float64': 'ddct%d', 'float32': 'dct%d'}[dtype.name]
+#     except KeyError:
+#         raise ValueError("dtype %s not supported" % dtype)
+#     try:
+#         f = getattr(_fftpack, name % type)
+#     except AttributeError as e:
+#         raise ValueError(str(e) + ". Type %d not understood" % type)
+#     return f, nm
 
 
 def idct(x, type=2, n=None, axis=-1, norm='ortho'):  # @ReservedAssignment
@@ -446,6 +446,7 @@ def test_dctn():
     print(' ')
     print xn-a
 
+
 def test_dct2():
     import scipy.ndimage as sn
     import matplotlib.pyplot as plt
@@ -481,8 +482,14 @@ def test_docstrings():
     doctest.testmod(optionflags=doctest.NORMALIZE_WHITESPACE)
 
 
+def test_commands():
+    import commands
+    commands.getstatusoutput('preprocess -DFORMAT=html -DDEVICE=screen tutorial.do.txt > tmp_preprocess__tutorial.do.txt')
+
+
 if __name__ == '__main__':
-    test_dct2()
+    print(test_commands())
+    # test_dct2()
     # test_docstrings()
     # test_dctn()
     # test_shiftdim()

pywafo/src/wafo/demo_sg.py

@@ -1,6 +1,7 @@
-# @UnresolvedImport
-from pylab import subplot, plot, title, savefig, figure, arange, sin, random
-from sg_filter import calc_coeff, smooth
+import matplotlib.pyplot as plt
+from pylab import subplot, plot, title, figure
+from numpy import random, arange, sin
+from sg_filter import SavitzkyGolay, smoothn  # calc_coeff, smooth
 
 
 figure(figsize=(7, 12))
@@ -8,11 +9,11 @@ figure(figsize=(7, 12))
 
 # generate chirp signal
 tvec = arange(0, 6.28, .02)
-signal = sin(tvec * (2.0 + tvec))
+true_signal = sin(tvec * (2.0 + tvec))
 
 # add noise to signal
-noise = random.normal(size=signal.shape)
-signal += (2000. + .15 * noise)
+noise = random.normal(size=true_signal.shape)
+signal = true_signal + .15 * noise
 
 # plot signal
 subplot(311)
@@ -21,19 +22,21 @@ title('signal')
 
 # smooth and plot signal
 subplot(312)
-coeff = calc_coeff(8, 4)
-s_signal = smooth(signal, coeff)
-
+savgol = SavitzkyGolay(n=8, degree=4)
+s_signal = savgol.smooth(signal)
+s2 = smoothn(signal, robust=True)
 plot(s_signal)
+plot(s2)
+plot(true_signal, 'r--')
 title('smoothed signal')
 
 # smooth derivative of signal and plot it
 subplot(313)
-coeff = calc_coeff(8, 1, 1)
-d_signal = smooth(signal, coeff)
+savgol1 = SavitzkyGolay(n=8, degree=1, diff_order=1)
+
+d_signal = savgol1.smooth(signal)
 
 plot(d_signal)
 title('smoothed derivative of signal')
 
-# show plot
-savefig("savitzky.png")
+plt.show('hold')  # show plot

pywafo/src/wafo/f2py_tools.py

@@ -0,0 +1,63 @@
+"""
+f2py c_library.pyf c_functions.c -c
+
+See also http://www.scipy.org/Cookbook/CompilingExtensionsOnWindowsWithMinGW
+"""
+import os
+import sys
+
+
+def which(program):
+    """
+    Return filepath to program if it exists
+
+    In order to test if a certain executable exists, it will search for the
+    program name in the environment variables.
+    If program is a full path to an executable, it will check it exists
+
+    Copied from:
+    http://stackoverflow.com/questions/377017/test-if-executable-exists-in-python/
+    It is supposed to mimic the UNIX command "which"
+    """
+
+    def is_exe(fpath):
+        return os.path.exists(fpath) and os.access(fpath, os.X_OK)
+
+    fpath, unused_fname = os.path.split(program)
+    if fpath:
+        if is_exe(program):
+            return program
+    else:
+        for path in os.environ["PATH"].split(os.pathsep):
+            exe_file = os.path.join(path, program)
+            if is_exe(exe_file):
+                return exe_file
+
+    return None
+
+
+def f2py_call_str():
+    '''Return which f2py callable is in the path regardless of platform'''
+    
+    # define possible options:
+    # on Arch Linux, python and f2py are the calls corresponding to python 3
+    # and python2/f2py2 for python 2
+    # other Linux versions might still use python/f2py for python 2
+    
+    if os.path.basename(sys.executable).endswith('2'):
+        options = ('f2py2', 'f2py2.6', 'f2py2.7',)
+    else:  # on Windows and other Linux using python/f2py
+        options = ('f2py.bat', 'f2py', 'f2py2.6', 'f2py2.7', 'f2py.py',)
+    for k in options:
+        if which(k):
+            # Found the f2py path, no need to look further
+            f2py_call = k
+            f2py_path = which(k)
+            break
+
+    try:
+        print 'found f2py in:', f2py_path
+        return f2py_call
+    except NameError:
+        raise UserWarning('Couldn\'t locate f2py. '
+                          'Should be part of NumPy installation.')

pywafo/src/wafo/misc.py

@@ -2,7 +2,6 @@
 Misc
 '''
 from __future__ import division
-
 import sys
 import fractions
 import numpy as np

pywafo/src/wafo/plotbackend.py

@@ -5,7 +5,7 @@ import warnings
 verbose = False
 if False:
     try:
-        from scitools import easyviz as plotbackend
+        from scitools import easyviz as plotbackend  # @UnresolvedImport
         if verbose:
             print('wafo: plotbackend is set to scitools.easyviz')
     except:

pywafo/src/wafo/sg_filter.py

@@ -14,7 +14,7 @@ from scipy.ndimage.morphology import distance_transform_edt
 import warnings
 from wafo.plotbackend import plotbackend as plt
 
-__all__ = ['SavitzkyGolay', 'Kalman', 'HodrickPrescott']
+__all__ = ['SavitzkyGolay', 'Kalman', 'HodrickPrescott', 'smoothn']
 
 
 class SavitzkyGolay(object):

pywafo/src/wafo/transform/models.py

@@ -7,7 +7,7 @@ TrLinear
 '''
 # !/usr/bin/env python
 from __future__ import division
-from scipy.optimize import brentq
+from scipy.optimize import brentq  # @UnresolvedImport
 from numpy import (sqrt, atleast_1d, abs, imag, sign, where, cos, arccos, ceil,
                    expm1, log1p, pi)
 import numpy as np
@@ -106,10 +106,10 @@ class TrHermite(TrCommon2):
     Example:
     --------
     """ + _example.replace('<generic>', 'TrHermite') + """
-    >>> g.dist2gauss()
-    0.88230868748851499
-    >>> g2.dist2gauss()
-    1.1411663205144991
+    >>> np.allclose(g.dist2gauss(), 0.88230868748851499)
+    True
+    >>> np.allclose(g2.dist2gauss(), 1.1411663205144991)
+    True
 
     See also
     --------
@@ -336,10 +336,10 @@ class TrLinear(TrCommon2):
     Example:
     --------
     """ + _example.replace('<generic>', 'TrLinear') + """
-    >>> g.dist2gauss()
-    0.0
-    >>> g2.dist2gauss()
-    3.8594770921678001e-31
+    >>> np.allclose(g.dist2gauss(), 0)
+    True
+    >>> np.allclose(g2.dist2gauss(), 0)
+    True
 
     See also
     --------
@@ -404,10 +404,10 @@ class TrOchi(TrCommon2):
     Example
     -------
     """ + _example.replace('<generic>', 'TrOchi') + """
-    >>> g.dist2gauss()
-    1.410698801056657
-    >>> g2.dist2gauss()
-    1.988807188766706
+    >>> np.allclose(g.dist2gauss(), 1.410698801056657)
+    True
+    >>> np.allclose(g2.dist2gauss(), 1.988807188766706)
+    True
 
     See also
     --------

pywafo/src/wafo/wafodata.py

@@ -21,7 +21,7 @@ def empty_copy(obj):
 
 
 def _set_seed(iseed):
-    if iseed != None:
+    if iseed is not None:
         try:
             np.random.set_state(iseed)
         except:
@@ -29,16 +29,13 @@ def _set_seed(iseed):
 
 
 def now():
-    '''
-    Return current date and time as a string
-    '''
+    """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
+    """Container class for data objects in WAFO.
 
     Member variables
     ----------------
@@ -72,7 +69,8 @@ class PlotData(object):
     --------
     specdata,
     covdata
-    '''
+
+    """
 
     def __init__(self, data=None, args=None, *args2, **kwds):
         self.data = data
@@ -95,7 +93,7 @@ class PlotData(object):
             axis = plotbackend.gca()
         tmp = None
         plotflag = kwds.get('plotflag', None)
-        if not plotflag and self.children != None:
+        if not plotflag and self.children is not None:
             plotbackend.hold('on')
             tmp = []
             child_args = kwds.pop(
@@ -105,7 +103,7 @@ class PlotData(object):
             child_kwds['axis'] = axis
             for child in self.children:
                 tmp1 = child.plot(*child_args, **child_kwds)
-                if tmp1 != None:
+                if tmp1 is not None:
                     tmp.append(tmp1)
             if len(tmp) == 0:
                 tmp = None
@@ -179,9 +177,8 @@ class PlotData(object):
         return newcopy
 
     def setplotter(self, plotmethod=None):
-        '''
-            Set plotter based on the data type data_1d, data_2d, data_3d or data_nd
-        '''
+        """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:
@@ -212,7 +209,8 @@ class AxisLabels:
         return self.__str__()
 
     def __str__(self):
-        return '%s\n%s\n%s\n%s\n' % (self.title, self.xlab, self.ylab, self.zlab)
+        return '%s\n%s\n%s\n%s\n' % (self.title, self.xlab, self.ylab,
+                                     self.zlab)
 
     def copy(self):
         newcopy = empty_copy(self)
@@ -306,8 +304,9 @@ def plot1d(axis, args, data, dataCI, plotflag, *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)
+        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:
@@ -354,8 +353,7 @@ def plot1d(axis, args, data, dataCI, plotflag, *varargin, **kwds):
 
 
 def plotscale(plotflag):
-    '''
-    Return plotscale from plotflag
+    """Return plotscale from plotflag.
 
      CALL scale = plotscale(plotflag)
 
@@ -400,7 +398,8 @@ def plotscale(plotflag):
     See also
     --------
     transformdata
-    '''
+
+    """
     scaleId = plotflag // 100
     if scaleId > 7:
         logXscaleId = np.mod(scaleId, 10) > 0
@@ -429,8 +428,8 @@ def transformdata(x, f, plotflag):
             data = -np.log1p(-cumtrapz(f, x))
         else:
             if any(f < 0):
-                raise ValueError(
-                    'Invalid plotflag: Data or dataCI is negative, but must be positive')
+                raise ValueError('Invalid plotflag: Data or dataCI is '
+                                 'negative, but must be positive')
             data = 10 * np.log10(f)
     return data