Merge pull request #841 from to266/ENH_new_progressbar

replaced old progressbar.

.travis.yml

@@ -28,7 +28,7 @@ install:
   - conda create -n testenv --yes python=$TRAVIS_PYTHON_VERSION $DEPS
   - source activate testenv
   - conda install pip
-  - pip install coverage coveralls traits traitsui request
+  - pip install coverage coveralls traits traitsui request tqdm
   - python setup.py install
 
 script: python continuous_integration/nosetest.py --with-coverage hyperspy

appveyor.yml

@@ -57,7 +57,7 @@ install:
   - "%CMD_IN_ENV% move %PYTHON%\\sip %PYTHON%\\Lib\\site-packages\\PyQt4\\sip"
   - "%CMD_IN_ENV% conda install pip"
   # TODO: Remove once anaconda taitsui package is at v5:
-  - "IF \"%PYTHON_MAJOR%\" EQU \"3\" pip install --upgrade traitsui"
+  - "IF \"%PYTHON_MAJOR%\" EQU \"3\" pip install --upgrade traitsui tqdm"
   - ps: Add-AppveyorMessage "Installing hyperspy..."
   - "python setup.py install"
 
@@ -101,7 +101,7 @@ before_deploy:
   - "SET PATH=%ORIGPATH%"
   - "%CMD_IN_ENV% %WP_INSTDIR%/scripts/env.bat"
   - "%CMD_IN_ENV% python.exe setup.py install"
-  - "%CMD_IN_ENV% pip install --upgrade configobj traitsui natsort start_jupyter_cm"
+  - "%CMD_IN_ENV% pip install --upgrade configobj traitsui natsort start_jupyter_cm tqdm"
   # Custom installer step
   # TODO: Re-run tests in WinPython environment
   - ps: Add-AppveyorMessage "Creating installer..."

doc/sphinxext/docscrape.py

@@ -293,7 +293,7 @@ def _parse(self):
         for (section, content) in self._read_sections():
             if not section.startswith('..'):
                 section = ' '.join([s.capitalize()
-                                   for s in section.split(' ')])
+                                    for s in section.split(' ')])
             if section in ('Parameters', 'Returns', 'Raises', 'Warns',
                            'Other Parameters', 'Attributes', 'Methods'):
                 self[section] = self._parse_param_list(content)

doc/sphinxext/gen_rst.py

@@ -151,7 +151,7 @@ def generate_example_rst(app):
 
             # indent the contents
             contents = '\n'.join(['    %s' % row.rstrip()
-                                 for row in contents.split('\n')])
+                                  for row in contents.split('\n')])
             fh.write(contents)
 
             fh.write(

doc/user_guide/install.rst

@@ -208,7 +208,7 @@ Installing the required libraries
 
 When installing HyperSpy using Python installers or from source the Python
 programming language and the following libraries must be installed in the
-system: numpy, scipy, matplotlib (>= 1.2), ipython, natsort, traits and
+system: numpy, scipy, matplotlib (>= 1.2), ipython, natsort, tqdm, traits and
 traitsui. For full functionality it is recommended to also install h5py and
 scikit-learn. In addition, since version 0.7.2 the lowess filter requires
 statsmodels. In Windows HyperSpy uses the Ipython's QtConsole and therefore Qt
@@ -221,7 +221,7 @@ In Debian/Ubuntu you can install the libraries as follows:
 
     $ sudo apt-get install python-numpy python-matplotlib ipython
     ipython-notebook python-traits python-traitsui python-h5py
-    python-scikits-learn python-nose python-statsmodels
+    python-scikits-learn python-nose python-statsmodels python3-tqdm
 
 In Arch Linux, the following command should install the required packages to
 get a fully functional installation:

hyperspy/Release.py

@@ -80,4 +80,3 @@
     http://www.hyperspy.org
 
     """ % version.replace('_', ' ')
-

hyperspy/_components/eels_vignetting.py

@@ -62,7 +62,8 @@ def function(self, x):
         if self.side_vignetting is True:
 
             x = x.tolist()
-            x = list(range(-ex, 0)) + x + list(range(int(x[-1]) + 1, int(x[-1]) + ex + 1))
+            x = list(range(-ex, 0)) + x + \
+                list(range(int(x[-1]) + 1, int(x[-1]) + ex + 1))
             x = np.array(x)
             v1 = A * np.cos((x - x0) / (2 * np.pi * period)) ** 4
             v2 = np.where(x < l,

hyperspy/_signals/eds_tem.py

@@ -151,8 +151,8 @@ def set_microscope_parameters(self,
                 probe_area)
         if real_time is not None:
             md.set_item(
-                 "Acquisition_instrument.TEM.Detector.EDS.real_time",
-                 real_time)
+                "Acquisition_instrument.TEM.Detector.EDS.real_time",
+                real_time)
 
         if set([beam_energy, live_time, tilt_stage, azimuth_angle,
                 elevation_angle, energy_resolution_MnKa]) == {None}:
@@ -382,9 +382,9 @@ def quantification(self,
             mass_thickness.metadata.General.title = 'Mass thickness'
         elif method == 'cross_section':
             results = utils_eds.quantification_cross_section(
-                                composition.data,
-                                cross_sections=factors,
-                                dose=self._get_dose(method))
+                composition.data,
+                cross_sections=factors,
+                dose=self._get_dose(method))
             composition.data = results[0] * 100
             number_of_atoms = utils.stack(intensities)
             number_of_atoms.data = results[1]

hyperspy/_signals/eels.py

@@ -336,18 +336,16 @@ def estimate_elastic_scattering_intensity(
         else:
             I0 = self._get_navigation_signal()
             I0.axes_manager.set_signal_dimension(0)
-            pbar = hyperspy.external.progressbar.progressbar(
-                maxval=self.axes_manager.navigation_size,
-            )
-            for i, s in enumerate(I0):
+            for i, s in progressbar(enumerate(self),
+                                    total=self.axes_manager.navigation_size,
+                                    disable=not show_progressbar,
+                                    leave=True):
                 threshold_ = threshold.isig[I0.axes_manager.indices].data[0]
                 if np.isnan(threshold_):
                     s.data[:] = np.nan
                 else:
                     s.data[:] = (self.inav[I0.axes_manager.indices].isig[
                                  :threshold_].integrate1D(-1).data)
-                pbar.update(i)
-            pbar.finish()
         I0.axes_manager.set_signal_dimension(
             self.axes_manager.navigation_dimension)
         I0.metadata.General.title = (
@@ -749,10 +747,10 @@ def richardson_lucy_deconvolution(self, psf, iterations=15, mask=None,
         imax = kernel.argmax()
         j = 0
         maxval = self.axes_manager.navigation_size
-        if maxval > 0:
-            pbar = progressbar(maxval=maxval,
-                               disabled=not show_progressbar)
-        for D in self:
+        show_progressbar = show_progressbar and (maxval > 0)
+        for D in progressbar(self, total=maxval,
+                             disable=not show_progressbar,
+                             leave=True):
             D = D.data.copy()
             if psf.axes_manager.navigation_dimension != 0:
                 kernel = psf(axes_manager=self.axes_manager)
@@ -767,10 +765,6 @@ def richardson_lucy_deconvolution(self, psf, iterations=15, mask=None,
                                      D / first)[mimax: mimax + psf_size])
             s[:] = O
             j += 1
-            if maxval > 0:
-                pbar.update(j)
-        if maxval > 0:
-            pbar.finish()
 
         return ds
 

hyperspy/external/mpfit/mpfit.py

@@ -1448,7 +1448,8 @@ def defiter(self, fcn, x, iter, fnorm=None, functkw=None,
 
         # Determine which parameters to print
         nprint = len(x)
-        print("Iter ", ('%6i' % iter), "   CHI-SQUARE = ", ('%.10g' % fnorm), " DOF = ", ('%i' % dof))
+        print("Iter ", ('%6i' % iter), "   CHI-SQUARE = ", ('%.10g' % fnorm),
+            " DOF = ", ('%i' % dof))
         for i in range(nprint):
             if (parinfo is not None) and ('parname' in parinfo[i]):
                 p = '   ' + parinfo[i]['parname'] + ' = '