Merge remote-tracking branch 'upstream/0.8.x'

hyperspy/_signals/image.py

@@ -50,10 +50,11 @@ def plot(self,
              scalebar_color="white",
              axes_ticks=None,
              auto_contrast=True,
-             saturated_pixels=0.2,
+             saturated_pixels=0,
              vmin=None,
              vmax=None,
              no_nans=False,
+             centre_colormap="auto",
              **kwargs
              ):
         """Plot image.
@@ -117,14 +118,19 @@ def plot(self,
             If True, the contrast is stretched for each image using the
             `saturated_pixels` value. Default True.
         saturated_pixels: scalar
-            The percentage of pixels that are left out of the bounds.  For example,
-            the low and high bounds of a value of 1 are the 0.5% and 99.5%
-            percentiles. It must be in the [0, 100] range.
+            The percentage of pixels that are left out of the bounds.
+            For example, the low and high bounds of a value of 1 are the 0.5%
+            and 99.5% percentiles. It must be in the [0, 100] range.
         vmin, vmax : scalar, optional
-            `vmin` and `vmax` are used to normalize luminance data. If at least one of them is given
-            `auto_contrast` is set to False and any missing values are calculated automatically.
+            `vmin` and `vmax` are used to normalize luminance data. If at
+            least one of them is given `auto_contrast` is set to False and any
+            missing values are calculated automatically.
         no_nans : bool, optional
             If True, set nans to zero for plotting.
+        centre_colormap : {"auto", True, False}
+            If True the centre of the color scheme is set to zero. This is
+            specially useful when using diverging color schemes. If "auto"
+            (default), diverging color schemes are automatically centred.
         **kwargs, optional
             Additional key word arguments passed to matplotlib.imshow()
 
@@ -139,5 +145,6 @@ def plot(self,
             vmin=vmin,
             vmax=vmax,
             no_nans=no_nans,
+            centre_colormap=centre_colormap,
             **kwargs
         )

hyperspy/drawing/__init__.py

@@ -15,3 +15,8 @@
 #
 # You should have received a copy of the GNU General Public License
 # along with  HyperSpy.  If not, see <http://www.gnu.org/licenses/>.
+
+
+import matplotlib
+
+matplotlib.rcParams["image.cmap"] = "gray"

hyperspy/drawing/image.py

@@ -30,7 +30,9 @@
 from hyperspy.gui.tools import ImageContrastEditor
 from hyperspy.misc import math_tools
 from hyperspy.misc import rgb_tools
-from hyperspy.misc.image_tools import contrast_stretching
+from hyperspy.misc.image_tools import (contrast_stretching,
+                                       MPL_DIVERGING_COLORMAPS,
+                                       centre_colormap_values)
 from hyperspy.drawing.figure import BlittedFigure
 
 
@@ -61,6 +63,10 @@ class ImagePlot(BlittedFigure):
         The percentage of pixels that are left out of the bounds.  For example,
         the low and high bounds of a value of 1 are the 0.5% and 99.5%
         percentiles. It must be in the [0, 100] range.
+    centre_colormap : {"auto", True, False}
+        If True the centre of the color scheme is set to zero. This is
+        specially useful when using diverging color schemes. If "auto"
+        (default), diverging color schemes are automatically centred.
 
     """
 
@@ -95,6 +101,7 @@ def __init__(self):
         self._user_axes_ticks = None
         self._auto_axes_ticks = True
         self.no_nans = False
+        self.centre_colormap = "auto"
 
     @property
     def axes_ticks(self):
@@ -265,6 +272,16 @@ def add_marker(self, marker):
         self.ax_markers.append(marker)
 
     def update(self, auto_contrast=None, **kwargs):
+        # Turn on centre_colormap if a diverging colormap is used.
+        if self.centre_colormap == "auto":
+            if "cmap" in kwargs:
+                cmap = kwargs["cmap"]
+            else:
+                cmap = plt.cm.get_cmap().name
+            if cmap in MPL_DIVERGING_COLORMAPS:
+                self.centre_colormap = True
+            else:
+                self.centre_colormap = False
         ims = self.ax.images
         redraw_colorbar = False
         data = rgb_tools.rgbx2regular_array(
@@ -303,9 +320,13 @@ def format_coord(x, y):
             self._text.set_text(self.axes_manager.indices)
         if self.no_nans:
             data = np.nan_to_num(data)
+        if self.centre_colormap:
+            vmin, vmax = centre_colormap_values(self.vmin, self.vmax)
+        else:
+            vmin, vmax = self.vmin, self.vmax
         if ims:
             ims[0].set_data(data)
-            ims[0].norm.vmax, ims[0].norm.vmin = self.vmax, self.vmin
+            ims[0].norm.vmax, ims[0].norm.vmin = vmax, vmin
             if redraw_colorbar is True:
                 ims[0].autoscale()
                 self._colorbar.draw_all()
@@ -320,8 +341,8 @@ def format_coord(x, y):
                 self.figure.canvas.draw()
         else:
             new_args = {'interpolation': 'nearest',
-                        'vmin': self.vmin,
-                        'vmax': self.vmax,
+                        'vmin': vmin,
+                        'vmax': vmax,
                         'extent': self._extent,
                         'aspect': self._aspect,
                         'animated': True}

hyperspy/drawing/mpl_hie.py

@@ -32,6 +32,7 @@ def plot_signal(self,
                     vmin=None,
                     vmax=None,
                     no_nans=False,
+                    centre_colormap="auto",
                     **kwargs
                     ):
         """Plot image.
@@ -81,6 +82,7 @@ def plot_signal(self,
         imf.no_nans = no_nans
         imf.scalebar_color = scalebar_color
         imf.auto_contrast = auto_contrast
+        imf.centre_colormap = centre_colormap
         imf.plot(**kwargs)
         self.signal_plot = imf
 

hyperspy/drawing/utils.py

@@ -27,7 +27,9 @@
 import matplotlib.pyplot as plt
 import matplotlib as mpl
 
-from hyperspy.misc.image_tools import contrast_stretching
+from hyperspy.misc.image_tools import (contrast_stretching,
+                                       MPL_DIVERGING_COLORMAPS,
+                                       centre_colormap_values)
 from hyperspy.defaults_parser import preferences
 
 
@@ -356,7 +358,8 @@ def plot_images(images,
                 suptitle=None,
                 suptitle_fontsize=18,
                 colorbar='multi',
-                saturated_pixels=0.2,
+                centre_colormap="auto",
+                saturated_pixels=0,
                 scalebar=None,
                 scalebar_color='white',
                 axes_decor='all',
@@ -414,6 +417,10 @@ def plot_images(images,
             (non-RGB) image
             If 'single', all (non-RGB) images are plotted on the same scale,
             and one colorbar is shown for all
+        centre_colormap : {"auto", True, False}
+            If True the centre of the color scheme is set to zero. This is
+            specially useful when using diverging color schemes. If "auto"
+            (default), diverging color schemes are automatically centred.
         saturated_pixels: scalar
             The percentage of pixels that are left out of the bounds.  For example,
             the low and high bounds of a value of 1 are the 0.5% and 99.5%
@@ -500,7 +507,14 @@ def plot_images(images,
 
     # Get default colormap from pyplot:
     if cmap is None:
-        cmap = plt.get_cmap()
+        cmap = plt.get_cmap().name
+    elif isinstance(cmap, mpl.colors.Colormap):
+        cmap = cmap.name
+    if centre_colormap == "auto":
+        if cmap in MPL_DIVERGING_COLORMAPS:
+            centre_colormap = True
+        else:
+            centre_colormap = False
 
     # If input is >= 1D signal (e.g. for multi-dimensional plotting),
     # copy it and put it in a list so labeling works out as (x,y) when plotting
@@ -652,6 +666,8 @@ def plot_images(images,
         global_max = max([i.data.max() for i in non_rgb])
         global_min = min([i.data.min() for i in non_rgb])
         g_vmin, g_vmax = contrast_stretching(i.data, saturated_pixels)
+        if centre_colormap:
+            g_vmin, g_vmax = centre_colormap_values(g_vmin, g_vmax)
 
     # Check if we need to add a scalebar for some of the images
     if isinstance(scalebar, list) and all(isinstance(x, int)
@@ -682,6 +698,8 @@ def plot_images(images,
                 data = im.data
                 # Find min and max for contrast
                 l_vmin, l_vmax = contrast_stretching(data, saturated_pixels)
+                if centre_colormap:
+                    l_vmin, l_vmax = centre_colormap_values(l_vmin, l_vmax)
 
             # Remove NaNs (if requested)
             if no_nans:

hyperspy/gui/tools.py

@@ -39,6 +39,9 @@
 OurResetButton = tu.Action(name="Reset",
                            action="reset")
 
+OurCloseButton = tu.Action(name="Close",
+                           action="close_directly")
+
 OurFindButton = tu.Action(name="Find next",
                           action="find",)
 
@@ -67,6 +70,10 @@ def close(self, info, is_ok):
 
         return True
 
+    def close_directly(self, info):
+        if (info.ui.owner is not None) and self.close(info, False):
+            info.ui.owner.close()
+
     def apply(self, info, *args, **kwargs):
         """Handles the **Apply** button being clicked.
 
@@ -771,23 +778,28 @@ def close(self):
 
 class ComponentFit(SpanSelectorInSpectrum):
     fit = t.Button()
+    only_current = t.List(t.Bool(True))
 
     view = tu.View(
         tu.Item('fit', show_label=False),
-        buttons=[OKButton, CancelButton],
+        tu.Item('only_current', show_label=False, style='custom',
+                editor=tu.CheckListEditor(values=[(True, 'Only current')])),
+        buttons=[OurCloseButton],
         title='Fit single component',
         handler=SpanSelectorInSpectrumHandler,
     )
 
     def __init__(self, model, component, signal_range=None,
-                 estimate_parameters=True, fit_independent=False, **kwargs):
+                 estimate_parameters=True, fit_independent=False,
+                 only_current=True, **kwargs):
         if model.spectrum.axes_manager.signal_dimension != 1:
             raise SignalDimensionError(
                 model.spectrum.axes_manager.signal_dimension, 1)
 
         self.signal = model.spectrum
         self.axis = self.signal.axes_manager.signal_axes[0]
         self.span_selector = None
+        self.only_current = [True] if only_current else []  # CheckListEditor
         self.model = model
         self.component = component
         self.signal_range = signal_range
@@ -831,6 +843,7 @@ def _fit_fired(self):
 
         # Setting reasonable initial value for parameters through
         # the components estimate_parameters function (if it has one)
+        only_current = len(self.only_current) > 0   # CheckListEditor
         if self.estimate_parameters:
             if hasattr(self.component, 'estimate_parameters'):
                 if (self.signal_range != "interactive" and
@@ -839,15 +852,18 @@ def _fit_fired(self):
                         self.signal,
                         self.signal_range[0],
                         self.signal_range[1],
-                        only_current=True)
+                        only_current=only_current)
                 elif self.signal_range == "interactive":
                     self.component.estimate_parameters(
                         self.signal,
                         self.ss_left_value,
                         self.ss_right_value,
-                        only_current=True)
+                        only_current=only_current)
 
-        self.model.fit(**self.fit_kwargs)
+        if only_current:
+            self.model.fit(**self.fit_kwargs)
+        else:
+            self.model.multifit(**self.fit_kwargs)
 
         # Restore the signal range
         if self.signal_range is not None:

hyperspy/misc/image_tools.py

@@ -218,3 +218,38 @@ def contrast_stretching(data, saturated_pixels):
     vmin = np.percentile(data, saturated_pixels / 2.)
     vmax = np.percentile(data, 100 - saturated_pixels / 2.)
     return vmin, vmax
+
+MPL_DIVERGING_COLORMAPS = [
+    "BrBG",
+    "bwr",
+    "coolwarm",
+    "PiYG",
+    "PRGn",
+    "PuOr",
+    "RdBu",
+    "RdGy",
+    "RdYIBu",
+    "RdYIGn",
+    "seismic",
+    "Spectral", ]
+# Add reversed colormaps
+MPL_DIVERGING_COLORMAPS += [cmap + "_r" for cmap in MPL_DIVERGING_COLORMAPS]
+
+
+def centre_colormap_values(vmin, vmax):
+    """Calculate vmin and vmax to set the colormap midpoint to zero.
+
+    Parameters
+    ----------
+    vmin, vmax : scalar
+        The range of data to display.
+
+    Returns
+    -------
+    cvmin, cvmax : scalar
+        The values to obtain a centre colormap.
+
+    """
+
+    absmax = max(abs(vmin), abs(vmax))
+    return -absmax, absmax

hyperspy/model.py

@@ -1850,6 +1850,7 @@ def fit_component(
             signal_range="interactive",
             estimate_parameters=True,
             fit_independent=False,
+            only_current=True,
             **kwargs):
         """Fit just the given component in the given signal range.
 
@@ -1888,7 +1889,8 @@ def fit_component(
         """
         component = self._get_component(component)
         cf = ComponentFit(self, component, signal_range,
-                          estimate_parameters, fit_independent, **kwargs)
+                          estimate_parameters, fit_independent,
+                          only_current, **kwargs)
         if signal_range == "interactive":
             cf.edit_traits()
         else:

hyperspy/signal.py

@@ -4791,6 +4791,13 @@ def add_marker(self, marker, plot_on_signal=True, plot_marker=True):
             marker.plot()
 
     def create_model(self):
+        """Create a model for the current signal
+
+        Returns
+        -------
+        A Model class
+
+        """
         from hyperspy.model import Model
         return Model(self)
 

hyperspy/tests/io/test_hdf5.py

@@ -162,7 +162,7 @@ class TestSavingMetadataContainers:
     def setUp(self):
         self.s = Signal([0.1])
 
-    @nt.timed(0.01)
+    @nt.timed(0.1)
     def test_save_long_list(self):
         s = self.s
         s.metadata.set_item('long_list', range(10000))

hyperspy/misc/tests/test_math_tools.py → hyperspy/tests/misc/test_math_tools.py

@@ -1,7 +1,7 @@
 import nose.tools
 import numpy as np
 
-from .. import math_tools
+from hyperspy.misc import math_tools
 
 
 def test_isfloat_float():

hyperspy/tests/model/test_model.py

@@ -254,7 +254,7 @@ def test_fit_bounded(self):
         self.m[0].centre.bmin = 0.5
         self.m[0].bounded = True
         self.m.fit(fitter="mpfit", bounded=True)
-        nose.tools.assert_almost_equal(self.m[0].A.value, 9991.65422046, 5)
+        nose.tools.assert_almost_equal(self.m[0].A.value, 9991.65422046, 4)
         nose.tools.assert_almost_equal(self.m[0].centre.value, 0.5)
         nose.tools.assert_almost_equal(self.m[0].sigma.value, 2.08398236966)